The Interactive Fly
Zygotically transcribed genes
| Olfactory receptors | Olfactory neurons of the antenna and maxillary palp | Olfactory glomeruli in the antennal lobe | Mushroom body and olfactory learning |
Although the size of the receptor gene family is similar in nematodes and mice, the logic of olfactory perception differs in the two organisms. The discrimination of olfactory information requires neural mechanisms capable of distinguishing which of the numerous receptors have been activated by a given odorant. In C. elegans, a family of 1000 receptor genes is expressed in only 16 pairs of sensory cells, and each neuron expresses multiple odorant receptors. Activation of any one of the multiple receptors expressed in one cell will lead to chemoattraction, whereas activation of a receptor in a different cell results in chemorepulsion. Thus, the behavioral response to a specific sensory input is a property of the neuron that is activated and not a function of the chemosensory receptor itself. This organization allows for the recognition of a diverse array of odorous ligands but diminishes the organism's discriminatory power (Vosshall, 2000 and references therein).
A different logic is employed to discriminate odors by the mammalian olfactory system. In mice, each of the two million olfactory receptor neurons expresses only one of a thousand odorant receptor genes. Neurons expressing a given receptor project axons with precision to two of 1800 discrete synaptic structures, the glomeruli, within the olfactory bulb. The pattern of projections is spatially invariant, providing a two-dimensional representation of receptor activation in the brain. The existence of a physical map that segregates the projections of neurons expressing a given receptor (and therefore responsive to given odors) is in accord with both electrophysiological and imaging studies that demonstrate that different odors elicit defined patterns of spatial activity within the olfactory bulb (Vosshall, 2000 and references therein).
How is olfactory information represented in the insect brain? Does the logic of olfactory discrimination in the fruit fly, Drosophila, more closely resemble that of the invertebrate C. elegans or the more complex olfactory system of vertebrates? The anatomy of the insect olfactory system is reminiscent of vertebrates. Olfactory recognition in Drosophila is accomplished by sensory hairs distributed over the surface of the third antennal segment and the maxillary palp. Olfactory neurons within sensory hairs send projections to one of 43 glomeruli within the antennal lobe of the brain (see Anatomical organization of the olfactory nervous system in Drosophila). The glomeruli are innervated by dendrites of the projection neurons, the insect equivalent of the mitral cells in the vertebrate olfactory bulb. In turn, these antennal lobe neurons project to the mushroom body and lateral horn of the protocerebrum. 2-deoxyglucose mapping in the fruit fly demonstrates that different odorants elicit defined patterns of glomerular activity, suggesting that in insects, as in vertebrates, a topographic map of odor quality is represented in the antennal lobe. However, in the absence of the genes encoding the receptor molecules, it has not been possible to define a physical basis for this spatial map (Vosshall, 2000 and references therein).
The 'complete' family of Drosophila odorant receptors (DORs) has now been identified and these genes have been employed to visualize the projections of individual neurons to the fly brain. Fifty-seven DOR genes within the Drosophila genome have been described. Individual receptors are expressed in from 2 to 50 olfactory neurons in a conserved pattern that defines a topographic map on the surface of the antenna. Individual neurons are likely to express only one receptor gene. Neurons expressing a given receptor gene project with precision to spatially invariant glomeruli within the antennal lobe. In the fly, as in mammals, a topographic map of receptor activation in the peripheral sense organs is represented in the brain. These spatial patterns may then be decoded in higher sensory centers in the brain to translate stimulus features into meaningful neural information. These data suggest a logic of odor discrimination that has been maintained over the 500 million years of evolution separating insects from mammals, perhaps reflecting an efficient solution to the complex problem of olfactory sensory perception (Vosshall, 2000).
Analysis of the recently completed euchromatic genome sequence of Drosophila using BLAST searches with existing members of the DOR gene family indicates that a total of 57 DOR genes are present in the genome. This family of 57 genes is tentatively defined as the 'complete' complement of DOR genes, recognizing that 60 Mb of heterochromatic DNA remain to be analyzed. Each of the 57 genes encodes a putative seven transmembrane domain protein of ~380 amino acids. The family as a whole is extremely divergent and exhibits from 17% to 26% amino acid identity. However, each of the genes shares short common motifs in fixed positions that define these sequences as highly divergent members of a gene family. Analysis of the sequence of all 57 receptors reveals the existence of discrete subfamilies whose members exhibit significantly higher sequence identity, ranging from 40% to 60% (Vosshall, 2000).
The DOR genes are widely dispersed in the genome and most exist as single genes that distribute on each of the Drosophila chromosomes. There are two clusters of three-linked genes and eight examples of two-linked receptors. The approximate chromosomal position of each of the DOR genes was determined relative to sequence-tagged sites generated by the Berkeley Drosophila Genome Project. Thus, the 57 DOR genes identified within the euchromatic Drosophila genome may constitute the complete family of odorant receptor genes (Vosshall, 2000).
A profile of receptor expression has been obtained by performing in situ hybridization with digoxigenin-labeled RNA antisense probes to each of the 57 DOR genes. The expression of 32 of the DOR genes is restricted to the antenna; seven are expressed solely in the maxillary palp, and one is expressed in both olfactory organs. No expression of 17 DOR genes has been detected in embryonic, larval, or adult olfactory organs nor in other regions of the adult head. Each receptor is expressed in a spatially restricted subpopulation of neurons. The number of cells that express a given receptor gene, as well as the spatial pattern of expression, is conserved between individuals and is bilaterally symmetric in the two antennae. Or49b, for example, is expressed in two cells at the lateral edge of the antenna at the midpoint of the proximodistal axis. At the other extreme, Or47b is expressed in ~50 antennal neurons that reside in the lateral distal edge of the antenna. These patterns were conserved in over 30 individual flies examined for each gene (Vosshall, 2000).
In situ hybridization, coupled with immunocytochemistry with pan neuronal markers, demonstrates that this family of receptor genes is expressed in sensory neurons rather than support cells or glia within the antenna and the maxillary palp. Expression of this gene family is only observed in cells within the antenna and maxillary palp. No hybridization is observed in neurons of the brain, nor is hybridization observed elsewhere in the adult fly (including the taste cells of the proboscis) or in any tissue at any stage during embryonic or larval development. Thus, it seems likely that this receptor family is dedicated to the perception of volatile olfactory stimuli by adult sensory neurons in the antenna and maxillary palp (Vosshall, 2000).
The diversity of receptor expression in individual sensory neurons will have important implications for the logic of odor discrimination. In C. elegans, individual neurons may express up to 20 different receptor genes, whereas in mammals, olfactory sensory neurons transcribe only a single member of the gene family. Individual sensory neurons in Drosophila express different complements of receptors. At the extreme, these experiments are consistent with a model in which individual neurons express only a single receptor gene. The availability of the 'complete' repertoire of receptor genes has allowed this question of diversity of receptor expression to be examined in greater detail (Vosshall, 2000).
This problem is best addressed in the maxillary palp, which contains about 120 sensory neurons and expresses only seven members of the DOR gene family. Each of the seven DOR genes expressed in the palp identifies about 20 neurons, consistent with a model in which individual sensory neurons are functionally distinct. Two-color in situ hybridization experiments were performed in which the neurons expressing Or85e were identified with antisense RNA probes labeled with fluorescein. Neurons expressing Or46a in the maxillary palp were detected with RNA probes labeled with digoxigenin, and expression was visualized with fluorescent antibodies that distinguish the two probes. These two-color in situ hybridization experiments and additional experiments with mixed probes reveal that Or85e, Or46a, and Or59c are expressed in nonoverlapping subsets of cells (Vosshall, 2000).
Demonstrating the expression of a single receptor gene in individual sensory neurons within the antenna is more difficult since this olfactory organ expresses 32 members of the DOR gene family in ~1000 sensory cells. The lateral distal domain of the antenna contains about 300 neurons, 50 of which express Or47b. This same domain expresses 15 other receptors, including Or47a, Or23a, Or67a, Or43a, Or88a, Or49b, Or98a, and Or83c. In pairwise experiments, antennal sections were annealed with an Or47b antisense RNA probe and either individual or mixed probes for these eight additional receptors. RNA probes were labeled with either fluorescein or digoxigenin and visualized with antibodies that distinguish the two types of probes. Or47b is expressed in a subpopulation distinct from that expressing any of these eight receptors. A similar experiment was performed to examine DOR gene expression in the medial proximal region of the antenna. Or22a probes were labeled with fluorescein and a mix of probes complementary to five additional genes expressed in this domain (Or7a, Or56a, Or85b, Or42b, and Or59b) was labeled with digoxigenin. Despite the interspersion of Or22a cells with cells expressing other DOR genes in the domain, there is no overlap in the expression of Or22a with any of these five DOR genes. Taken together, these data provide strong support for a model reminiscent of the mammalian olfactory system, in which individual sensory neurons express only a single receptor. This conclusion must be tempered by the previous description of an odorant receptor gene, Or83b, that is expressed in all olfactory sensory neurons in both the antenna and maxillary palp. If Or83b does indeed recognize odorous ligands, then this data would indicate that all sensory neurons express two receptors rather than one: Or83b and one additional gene from the family of DOR genes (Vosshall, 2000).
These experiments suggest that there are 39 distinct neuronal cell types within the Drosophila olfactory organs. In the mammalian olfactory system, neurons expressing the same receptor project their axons to two spatially invariant glomeruli. It was therefore determined whether cells expressing a given receptor in Drosophila converge upon spatially defined loci in the antennal lobe, the first relay station for olfactory information in the fly brain. Axons from the antenna and maxillary palp have been found to synapse with the dendrites of projection neurons in the antennal lobe. There are 43 morphologically distinct synaptic structures or glomeruli in the antennal lobe that are invariant in position and size in individual flies. The number of antennal lobe glomeruli dedicated to olfactory input (41) approximates the number of different sensory neurons identified in the two olfactory organs (39), suggesting that olfactory neurons expressing a given receptor may converge on a single glomerulus (Vosshall, 2000).
Genetic experiments were performed that permit the visualization of the axonal projections from neurons expressing a given receptor. Transgenic flies were generated in which DOR gene promoters direct the expression of the yeast transcriptional activator, Gal4. These flies were then crossed with stocks bearing a transgene in which the Gal4-responsive promoter, UAS, drives the expression of either beta-galactosidase (LacZ) or a C-terminal fusion of green fluorescent protein (GFP) to neuronal synaptobrevin (nsyb-GFP). The expression of LacZ in specific subpopulations of sensory neurons allows the visualization of cell bodies, whereas the expression of nsyb-GFP, which selectively labels synaptic vesicles in nerve terminals, allows the visualization of terminal axonal projections (Vosshall, 2000).
Two to eight kilobases of DNA immediately upstream of the putative translation start from five DOR genes were fused to the coding sequence of Gal4. To demonstrate that these transgenes recapitulate the expression of the endogenous gene, the DOR-Gal4 strains were crossed with UAS-lacZ responders. The progeny of these crosses express LacZ in spatially defined subsets of cells in the antenna or maxillary palp that mirror the pattern of expression of the endogenous receptor. To confirm that these cells are sensory neurons, it was demonstrated that cells expressing LacZ are also labeled with an antibody that recognizes the neuron-specific RNA binding protein Elav. As a further test for the fidelity of expression of the promoter fusions, it was demonstrated that all cells expressing LacZ from the transgenes also express the corresponding endogenous odorant receptor RNA. In these experiments, RNA in situ hybridization was used to detect endogenous receptor RNA; immunofluorescence localized the expression of LacZ protein. Each of five DOR promoter fusions recapitulates the pattern of expression of the endogenous receptor gene (Vosshall, 2000).
The DOR-Gal4 transgenes were used to drive the expression of UAS-nsyb-GFP to visualize the projections of different populations of sensory neurons. Flies carrying five different DOR-Gal4 transgenes were crossed with animals bearing a UAS-nsyb-GFP transgene, and the brains of the adult progeny were then examined for localization of GFP. Immunofluorescence was performed on whole-mount brain preparations with antibody directed against GFP and with the monoclonal antibody, nc82, which labels neuropil in the fly brain and identifies the individual glomeruli in the antennal lobe. Four DOR-Gal4 promoter fusions (Or47a, Or47b, Or22a, and Or23a) are expressed in subpopulations of antennal neurons. When these flies are crossed with flies carrying the UAS-nsyb-GFP transgene, GFP labeling is seen in spatially invariant subsets of glomeruli within the antennal lobe. Or47a, for example, is expressed in 20 lateral distal neurons and their axonal projections converge on a single bilaterally symmetric glomerulus located at the dorsal medial limit of the antennal lobe. Or47b is expressed in 50 lateral distal neurons and these cells project axons that converge on a single large glomerulus that lies at the ventral lateral edge of the antennal lobe. Neurons expressing Or22a converge upon one dorsal glomerulus. The projections of one of the seven different subpopulations of sensory neurons from the maxillary palp have also been visualized. Sensory neurons expressing the palp receptor, Or46a, project to a single glomerulus that resides ventrally in the antennal lobe (Vosshall, 2000).
These four subpopulations of olfactory sensory neurons therefore project axons to single spatially invariant, bilaterally symmetric glomerulus within the antennal lobe. Cells expressing Or23a, however, send processes to two glomeruli. Or23a fibers enter the brain and initially converge upon a small dorsal glomerulus. Axons are seen extending more ventrally into the anterior of the antennal lobe where they converge upon a larger glomerulus. These two Or23a glomeruli are bilaterally symmetric and positionally invariant in multiple independent transgenic lines. It is not possible at present to determine whether individual fibers branch to form synapses within the two glomeruli nor if Or23a-expressing neurons sort such that individual subpopulations project to either one of the two glomeruli (Vosshall, 2000).
The topographic map of all five populations of olfactory sensory projections in the antennal lobe is unrelated to spatial domains of receptor expression in the antenna. For instance, while the 20 neurons that express Or22a in a proximal medial domain of the antenna converge upon a dorsal medial glomerulus, the Or47a glomerulus is situated directly adjacent to the Or22a glomerulus but receives input from cells in the lateral distal domain of the antenna. These precise patterns of glomerular convergence were observed in at least 20 individuals derived from multiple independent transgenic lines obtained for each of the four constructs. At a low frequency (1/100 flies), Or47a-expressing olfactory neurons project to two bilaterally symmetric medial glomeruli in addition to the OR47a glomerulus. The basis for this variation in axon targeting is unknown (Vosshall, 2000).
Anatomical tracing experiments in Drosophila have defined two subtypes of olfactory neurons in the antenna: those that project solely to the ipsilateral antennal lobe and others that branch and project to bilaterally symmetric glomeruli. The axonal projections from neurons expressing a given receptor in a single antenna or maxillary palp were traced to both the left and right antennal lobe. Removal of both the antenna and maxillary palp from one side of the fly results in effective deafferentation (Vosshall, 2000).
When either the left or right sensory organs were removed singly, it was found that the projections from the remaining antenna or maxillary palp converge upon the correct glomerulus in both the left and right antennal lobes. The position and size of the glomerulus is unaffected by unilateral deafferentation, but the density of nsyb-GFP-labeled fibers is decreased by about half. These data indicate that each of the four distinct subsets of olfactory neurons extend axons that innervate both the ipsilateral and contralateral antennal lobes equally. It is not possible from these studies to discern if individual axons branch or if distinct populations of axons independently sort to the left and right antennal lobes. However, it is known that afferent axons split into ipsilateral and contralateral branches. Thus, neurons expressing a given receptor project axons both ipsi- and contra-laterally to one or two spatially invariant glomeruli, creating a topographic map of receptor activation in the antennal lobe (Vosshall, 2000).
The diversity of odors recognized by a species is likely to be a function of the number of different odorant receptors it expresses. Thus, the repertoire of odors detected by the fruit fly may be small and may reflect the diminished importance of olfaction in insect species with a highly developed visual system. Drosophila, with rotting fruit as its sole source of food, may have evolved a narrow DOR gene repertoire that adequately accommodates its ecological niche. However, the true range of odors detectable by fruit flies in their natural environment has not been examined, nor has there been an analysis of subtle aspects of odor discrimination. It should be noted that even a relatively small repertoire of receptors and an equivalent number of glomeruli could allow the discrimination of a vast array of odorants that numerically far exceed the size of the receptor repertoire. Imaging studies in both invertebrates and vertebrates reveal that a given odor, even if composed of a single molecular species, activates multiple glomeruli. This spatial pattern of glomerular activation may constitute a combinatorial code that would be read in higher sensory centers. If a given odor activates ten receptors and therefore ten glomeruli, then a repertoire of 40 receptors could generate over 108 different spatial patterns. Moreover, the relatively small number of odorant receptor genes in Drosophila may not be representative of other insects. The honeybee, Apis mellifera, has about 160 glomeruli and by inference 160 different odorant receptors, suggesting that in this insect, olfaction may be a more central means of acquiring sensory information from the environment. Whatever the fruit fly's sensory capabilities, its olfactory sensory system is endowed with a relatively small number of receptor genes (Vosshall, 2000 and references therein).
Of the 57 DOR genes in the Drosophila genome, 39 are expressed in subpopulations of sensory neurons, and one gene (Or83b) is expressed in all olfactory sensory neurons. Expression of 17 genes was not detected in either embryonic, larval, or adult olfactory organs or in any other regions of the adult head. Despite the inability to detect expression of these 17 genes by in situ hybridization, analysis of their sequence does not reveal nonsense or frame shift mutations that characterize pseudogenes within families of odorant receptors in other species. If these sequences indeed represent pseudogenes, then the annotation generating an intact coding sequence may be incorrect. Alternatively, these 17 genes may be expressed either in olfactory organs or elsewhere at levels below that which can be detected by in situ hybridization techniques (5-10 mRNAs per cell). This level of expression is far below estimates of receptor mRNA content in olfactory neurons in any species examined. However, other studies have employed RT-PCR to demonstrate the expression within olfactory sensory organs of several of the 17 DOR genes is not detected by in situ hybridization. Experiments in which the putative promoter regions from these genes are used to drive the expression of Gal4 transgenes will provide more definitive information concerning these 17 genes (Vosshall, 2000 and references therein).
The diversity of receptor expression in individual sensory neurons has important implications for odor discrimination. In C. elegans it is estimated that chemosensory cells express up to 20 receptor genes, whereas in mammals neurons express only a single receptor. Discrimination requires that the brain determine which receptors have been activated by an odorant. If a sensory neuron expresses only one receptor, then this problem reduces to the simpler requirement that the brain discern which neurons have been activated by a given odorant. In the fly, individual neurons express the Or83b along with only one of the remaining DOR genes. This is perhaps easiest to demonstrate in the maxillary palp, which expresses seven DOR genes and Or83b. The seven DOR genes expressed in the maxillary palp together hybridize with about 120 cells. This value is close to the total number of neurons in the palp, suggesting that every neuron in the palp can be identified with seven genes from the DOR gene family. Moreover, two-color in situ hybridization with either pairwise combinations or mixes of these genes as probes consistently reveals that a sensory neuron expresses a single receptor gene. The data suggesting that neurons express only a single receptor are difficult to reconcile with electrophysiological recordings that have been interpreted to indicate that individual palp neurons express multiple receptors (Vosshall, 2000 and references therein).
What is the role of Or83b, the only DOR gene family member expressed in all olfactory sensory neurons? Or83b might encode a receptor capable of binding odorous ligands, thus affording each cell a common and a unique specificity. One model would argues that Or83b does not serve as an odorant receptor but performs a function in sensory neurons independent of ligand binding. For example, recent studies reveal that the metabotropic GABAB receptor is composed of a heterodimeric pair of seven transmembrane domain proteins. Surface expression and functional ligand binding of the GABABR1 subunit is obtained only upon coexpression of a second GABAB receptor, GABABR2. Thus, Or83b might perform a function essential for chemosensory signaling, independent of odor binding, thereby retaining the one neuron-one receptor rule (Vosshall, 2000 and references therein).
In situ hybridization with 39 of the 57 DOR genes reveals that each receptor is expressed in a spatially restricted subpopulation of cells in the antenna and palp. Both the pattern of receptor expression and the number of neurons expressing a given receptor are conserved in different individuals. Some genes are expressed in as few as two spatially defined cells in the antenna, whereas other genes are expressed in as many as 50 neurons. These experiments with the 'complete' set of receptor genes define a neural epithelium in which each of 1000 cells in the antenna is marked by the expression of one of 32 unique genes. It is presumed that this spatial patterning is a consequence of axes of positional information that ultimately dictate the expression of specific genes. At present, it is not possible to determine the precision of the pattern of specific receptor expression. Nonetheless, the fine control of neural identity reflected by receptor expression is likely to be distinct from the more coarse patterning that generates the three morphologically distinct sensilla (trichoid, basiconic, and coeloconic) that populate the olfactory sensory organs (Vosshall, 2000 and references therein)
If graded positional information governs a spatial map of receptor expression in the periphery, why is there interdigitating pattern in which two cells expressing a given receptor are interspersed by a cell expressing a different receptor? It is possible that precise patterning to the level of individual cells indeed occurs early in development and neural migration results in local disruptions in the peripheral map. Alternatively, positional information may dictate a set of defined spatial domains within which the expression of not one but a subset of receptors is permitted. This latter suggestion is reminiscent of a model of receptor expression in mammals in which a given receptor gene is expressed within one of four broad but circumscribed zones within the olfactory epithelium of the nose. Within a zone, however, neurons expressing a given receptor appear randomly dispersed. Such a mechanism would also be consistent with the patterns of expression of receptor genes in the fly antenna. More precise reconstructions of the spatial patterns of expression of multiple different receptors will be required to distinguish between these alternatives (Vosshall, 2000 and references therein).
One distinction between receptor expression in mice and flies is that in mice neurons express a single receptor gene from either the maternal or paternal allele, but never from both alleles (monoallelic expression). Moreover, in mice, neurons that express an odorant receptor transgene do not express the same gene from its endogenous locus. In contrast, in Drosophila, sensory neurons that express a transgene driven by a DOR promoter always express the appropriate endogenous DOR gene. In the fly, therefore, two DOR promoters can be activated in the same cell, arguing that monoallelic expression is not occurring in Drosophila olfactory neurons (Vosshall, 2000).
The organization of the peripheral olfactory sensory system in the fruit fly is remarkably similar to that of vertebrates. In mammals, olfactory neurons express only one of a thousand odorant receptor genes, the organization and functional logic of the complex process of olfactory sensory perception has been maintained over five hundred million years of evolution despite dramatic differences in other aspects of neural function. It is suggested that this evolutionary conservation reflects the maintenance of an efficient solution to the complex problem of recognition and discrimination of a vast repertoire of odors in the environment (Vosshall, 2000).
Olfactory systems confer the recognition and discrimination of a large number of structurally distinct odor molecules. Recent molecular analysis of odorant receptor (OR) genes and circuits has led to a model of odor coding in which a population of olfactory sensory neurons (OSNs) expressing a single OR converges upon a unique olfactory glomerulus. Activation of the OR can thus be read out by the activation of its cognate glomerulus. Drosophila is a powerful system in which to test this model because the entire repertoire of 62 ORs can be manipulated genetically. However, a complete understanding of how fly olfactory circuits are organized is lacking. A nearly complete map is presented of OR projections from OSNs to the antennal lobe (AL) in the fly brain. Four populations of OSNs coexpress two ORs along with Or83b, and a fifth expresses one OR and one gustatory receptor (GR) along with Or83b. One glomerulus receives coconvergent input from two separate populations of OSNs. Three ORs label sexually dimorphic glomeruli implicated in sexual courtship and are thus candidate Drosophila pheromone receptors. This olfactory sensory map provides an experimental framework for relating ORs to glomeruli and ultimately behavior (Fishilevich, 2005).
This study presents the results of a large-scale genetic effort to label OSNs expressing each of the 62 known OR genes and map their projections to approximately 50 morphologically defined glomeruli in the adult antennal lobe. Putative regulatory regions upstream of 49 ORs were cloned in front of the Gal4 transcription factor, and transgenic flies carrying these OR-Gal4 transgenes were crossed to cytoplasmic (UAS-lacZ) and synaptic (UAS-nsyb-GFP) reporters. Of these 49 OR-Gal4 transgenes, 30 (comprising 25 antennal and five maxillary palp ORs) produce appropriate gene expression in subpopulations of adult OSNs and are presented in this study. Of the remaining 19 OR-Gal4 constructs, 11 are selectively expressed in the larval olfactory system, one (Or83b) is broadly expressed in most OSNs, where it plays an essential role in olfaction, and seven either show no expression or are ectopically expressed. The remaining 13 OR-Gal4 lines were not generated as a result of design constraints imposed by the tight linkage of these ORs to unrelated genes or technical difficulties. Patterns of OR-Gal4:UAS-lacZ gene expression of 30 transgenes in the antenna and maxillary palp are similar to those obtained by an in situ hybridization screen and follow the same strict segregation of ORs expressed in the antenna and maxillary palp, with no OR-Gal4 lines expressed in both organs. These same lines were later used to determine the map of connectivity to the antennal lobe. Double-RNA in situ hybridization was performed to verify that OR-Gal4 lines reflect the expression of the endogenous OR mRNA. Although levels of staining varied, all cells appeared to have both endogenous OR and Gal4 transcripts. At least two OR-Gal4 lines were examined for each OR (Fishilevich, 2005).
To determine how OSNs expressing different ORs connect to the brain, genetically labeled axons were traced to their termini in the adult-fly antennal lobe. Analysis of glomerular projections of the 25 antennal OR-Gal4:UAS-nsyb-GFP strains reveals that 23 populations of OSNs expressing different ORs target a single glomerulus, whereas two (Or33b and Or67d) project to two glomeruli. Both Or33b-Gal4 and Or67d-Gal4 are coexpressed with their respective endogenous ORs, suggesting that these OSN populations indeed innervate two glomeruli. There is some apparent redundancy in the map, which was investigated further: six glomeruli are independently labeled by two different OR-Gal4 lines (Fishilevich, 2005).
In some cases, weak and variable labeling was observed, in secondary glomeruli, that reflects either variability in the expression levels of ORs in different subpopulations of neurons or transgene variability. Distinguishing between these possibilities is constrained by detection thresholds of in situ hybridization, which may not detect OR transcripts in cells weakly positive for the OR-Gal4 transgene. Some Or23a-Gal4 lines mark a second, ventrally located glomerulus (possibly DP1m). Other cases of weak and variable secondary innervation include the following: Or65a-Gal4, in the vicinity of D; Or85a-Gal4, in the vicinity of DM3; Or56a-Gal4, in the vicinity of DL4; Or10a-Gal4, in the vicinity of VA7m, and Or33b-Gal4, variable ectopic expression in multiple glomeruli. The general conclusions below are based on those glomeruli that show strong and reproducible labeling, although it is recognized that the weakly labeled glomeruli may also contribute to the odor code (Fishilevich, 2005).
Axonal projections of the five maxillary palp OR-Gal4 lines were examined in brain whole mounts. All palp neurons target the same ventral-medial region in the antennal lobe that does not receive projections from antennal OSNs. Or33c and Or85e are coexpressed, and these OSNs target the VC1 glomerulus. Or46a-expressing OSNs target an AL region with diffuse glomerular boundaries, and thus no glomerular identity could be assigned. To clarify the position of Or46a relative to the assigned palp glomeruli, the projections of Or46a-expressing neurons compared to other palp OSNs were examined simultaneously. The Or71a glomerulus is located in the same anterior-posterior plane but medial to Or46a, whereas the Or33c/Or85e glomerulus is located posterior and slightly medial to Or46a. The segregation of antennal and maxillary palp projections in Drosophila has been seen in anatomical tracing studies that preceded the advent of OR markers. The functional significance of antennal and maxillary palp segregation remains obscure because no exclusive function has been ascribed to either olfactory organ (Fishilevich, 2005).
A complete list of ORs and the glomeruli they target is presented in this study. Five cases were found in which two OR-Gal4 lines label the same glomerulus and one case in which a single glomerulus is marked by an OR-Gal4 and a GR-Gal4 line. Two-color RNA in situ hybridization was carried out to distinguish between two possibilities that would lead to two different OR-Gal4 lines apparently labeling the same glomerulus -- either the same population of OSNs is labeled by different OR-Gal4 lines, or two separate OSN populations marked by two different OR-Gal4 lines coconverge to the same glomerulus. Endogenous mRNAs for Or33a/Or56a, Or10a/Gr10a, Or33b/Or47a, Or33b/Or85a, and Or33c/Or85e are coexpressed. Whereas Or33b is coexpressed with both Or47a and Or85a, Or47a and Or85a are expressed in different OSNs. Or67d and Or82a are not coexpressed. Therefore, glomerulus VA6 receives input from two separate populations of OSNs expressing different ORs (Fishilevich, 2005).
The availability of a more complete map of AL projections allowed an examination of the organizational logic of this first olfactory synapse. There is a general trend for OSNs located in lateral/distal positions in the antenna to project to lateral AL glomeruli and for medial/proximal OSNs to target medial AL glomeruli. This segregation is most likely related to the topographic segregation of trichoid and basiconic classes of sensilla on the surface of the antenna. Or47b, Or88a, and Or67d are examples of the former, and Or42b, Or33b, and Or22a are examples of the latter. There are exceptions, notably Or19a, which targets a dorsal/medial glomerulus, although Or19a OSNs are located in the lateral/distal domain in the antenna. Of the 47 distinct glomerular compartments described, this study assigns a genetic OR identity to 26. No name could be assigned to Or46a, which may be a previously unnamed glomerulus. Other studies mapped Gr21a OSNs to V and Or59c OSNs to 1, bringing the total known number of OR assignments to AL glomeruli in the present literature to 29. Eighteen glomeruli remain to be associated with chemosensory receptors, and 20 ORs were not included in the mapping in this study. Thus, it is likely that projections of distinct OSNs can account for the remaining uncharacterized glomeruli (Fishilevich, 2005).
Available knowledge of OSN odor-response profiles were synthesized with their glomerular identity to determine whether there is any obvious chemotopic organization in the fly AL. This analysis was constrained by the limited and nonoverlapping collections of odorants used by different groups as well as differences in experimental techniques that make it difficult to compare across studies. Each OR/glomerulus was screened with a small subset of the 76 odors used across these six studies, and thus no comprehensive survey of the ligand specificity of a given OR/glomerulus exists. Nevertheless, a greater tendency was found for OSNs expressing broadly responsive ORs to project to dorsal/medial glomeruli, whereas the more selective glomeruli are located at ventral/lateral positions. However, there are many exceptions to this rule, and the ordered chemotopy described in the mouse olfactory bulb (Fishilevich, 2005).
Five subpopulations of OSNs are described that express multiple receptors along with the universal coreceptor Or83b. What might be the function of such OR coexpression? On the basis of previously published odor-response profiles for Or33b, Or47a, and Or85a, it is suggested that OR coexpression could modulate ligand-response profiles. Both Or47a and Or85a respond to more odors when ectopically expressed in the ab3A 'empty' neuron than the native neurons, which coexpress Or33b/Or47a or Or33b/Or85a. Or33b expressed alone in the 'empty' neuron responds weakly and with inhibition to most odors, giving a weak excitatory response only to ethyl propionate. Thus, Or33b coexpression in the native OSN could function to temper the relatively broad tuning of Or47a and Or85a. Confirmation of such a role awaits further genetic analysis of these ORs in vivo (Fishilevich, 2005).
An intriguing OSN population was identified that coexpresses members of the OR and GR families, along with Or83b. The role of GRs in the antenna is poorly understood, although Gr21a is expressed in neurons that respond to carbon dioxide. It will be interesting to determine whether Gr10a contributes to the detection of odors along with Or10a and subserves an olfactory instead of gustatory function (Fishilevich, 2005).
Recent work examining the expression of the male-specific isoform of the fruitless (fru) transcription factor implicates two large, sexually dimorphic glomeruli (VA1lm and DA1) in male courtship behavior. This study has revealed the molecular identity of the OSNs projecting to these glomeruli as Or47b and Or67d, respectively. Other glomeruli that receive input from fru-expressing OSNs are VL2a and, occasionally, VA6, which is identified in this study as receiving coconvergent input from Or82a- and Or67d-expressing OSNs. The identity of the VL2a-projecting OSNs remains obscure. Interestingly, these OSNs and the glomeruli to which they project show little or no activation in response to general odors. The exception is Or82a, which responds very selectively to geranyl acetate, a green-leaf volatile that is also a major component of medfly male sex pheromone. On the basis of anatomical tracing studies, it is suggested that Or82a- and Or67d-expressing OSNs target the same glomerulus. Whether they synapse uniformly upon the same population of postsynaptic projection neurons or whether the glomerulus has functional subcompartments is not known. In either scenario, the glomerulus might act as a coincidence detector that would require both the Or82a ligand, geranyl acetate, and the unknown Or67d ligand for activation (Fishilevich, 2005).
Courtship behavior in Drosophila involves multimodal input from visual, gustatory, auditory, and olfactory cues. The involvement of volatile pheromones in Drosophila sexual behavior has long been inferred, but neither the putative pheromones nor the receptors that detect them are known. It is suggested that these ORs are pheromone receptors that respond to volatile pheromones. In support of this, silencing or reprogramming these OSNs leads to selective disruption in male sexual behavior (Fishilevich, 2005)
This paper presents a nearly complete map of olfactory projections to the fly AL. From this map, five populations of OSNs were identified that express multiple receptors and two populations of OSNs expressing different ORs that coconverge upon a common glomerulus. An analysis of published odor-response profiles for these ORs and their glomeruli suggests that more broadly tuned neurons map to the dorsal/medial domain, whereas more restricted OSNs map to ventral/lateral glomeruli. Candidate Drosophila pheromone receptors were identified by virtue of their innervation of sexually dimorphic fru-positive glomeruli. A number of intriguing questions follow from this study. (1) What is the genetic identity of the projections that target the posterior face of the antennal lobe? These glomeruli may receive input from OSNs expressing OR or GR genes not examine in this study. (2) It will be of interest to understand in greater detail what effects receptor coexpression and OSN coconvergence have on the capacity of the fly to detect and discriminate odors. (3) The availability of candidate pheromone receptors in Drosophila will make it possible to study sex pheromones in a genetically tractable organism from the circuits they activate to the stereotyped behaviors they elicit (Fishilevich, 2005).
In Drosophila and mice, olfactory receptor neurons (ORNs) expressing the same receptors have convergent axonal projections to specific glomerular targets in the antennal lobe/olfactory bulb, creating an odor map in this first olfactory structure of the central nervous system. Projection neurons of the Drosophila antennal lobe send dendrites into glomeruli and axons to higher brain centers, thereby transferring this odor map further into the brain. The MARCM method has been used to perform a systematic clonal analysis of projection neurons, allowing the correlation of lineage and birth time of projection neurons with their glomerular choice. Projection neurons are prespecified by lineage and birth order to form synapses with specific incoming ORN axons, and therefore to carry specific olfactory information. This prespecification could be used to hardwire the fly's olfactory system, enabling stereotyped behavioral responses to odorants. Developmental studies have led to the hypothesis that recognition molecules ensure reciprocally specific connections of ORNs and projection neurons. These studies also imply a previously unanticipated role for precise dendritic targeting by postsynaptic neurons in determining connection specificity (Jefferis, 2001).
A common process in neural network formation is the establishment of one-to-one corresponding connections between two groups of neurons in two different locations, thereby generating a neural map. Three basic mechanisms for the formation of such neural maps can be proposed. In the first two mechanisms, either input or target neurons are genetically prespecified, whereas neurons of the remaining field are naive until specified by the identity of their partners during the connection process. In the third mechanism, input and target neurons are independently specified. This problem has been explored in the wiring of the Drosophila olfactory system. The organization of the Drosophila peripheral olfactory pathway is very similar to that of mammals. About 1,300 ORNs expressing 40-60 different receptors project their axons to 40-50 individually identifiable glomeruli of the antennal lobe (equivalent to the mammalian olfactory bulb). Information leaves the antennal lobe through an estimated 150 projection neurons (equivalent to mammalian mitral/tufted cells), whose cell bodies are located at the periphery of the antennal lobe. Projection neurons project their dendrites to glomeruli and their axons to higher brain centers, including the mushroom bodies and the lateral horn. As in mice, each ORN probably expresses one specific receptor, and the axons of ORNs expressing the same receptors converge at the same morphologically and spatially distinct glomeruli. In mice, ORNs seem to be genetically programmed to project to specific glomeruli, instructed by the receptors that they express; indeed, this convergence seems to be independent of the presence of the target neurons of the olfactory bulb. Although analogous experiments have not been reported in flies, ORNs expressing a particular receptor reside in stereotypic and discrete zones of the antennae and maxillary palps -- the fly's olfactory appendages. Assuming that ORN cell bodies do not relocate after their axons reach the antennal lobe, it seems probable that their glomerular targets are prespecified. Thus, of the three models for formation of the neural map, the second model seems unlikely in both mice and Drosophila. It was of interest to distinguish whether Drosophila projection neurons are specified by virtue of their connection with ORNs or are independently specified (Jefferis, 2001).
The MARCM (mosaic analysis with a repressible cell marker) system can be used to determine neuronal lineage and the projection patterns of individual neurons. A typical neuroblast in the Drosophila brain undergoes asymmetric division to regenerate a new neuroblast and a ganglion mother cell, which divides once more to generate two postmitotic neurons. Using MARCM, one can generate positively-labelled single-cell clones as well as neuroblast clones. By controlling the timing of mitotic recombination using heat-shock-induced FLP recombinase, one can produce labelled clones of cells born at different developmental times. To study projection neurons of the antennal lobe, use was made of a GAL4 line, GAL4-GH146, which drives marker expression in a large subset of projection neurons (approximately 90). By crossing GH146 with a membrane marker, UAS-mouse CD8-green fluorescent protein (GFP), the cell body and dendrites of projection neurons in the antennal lobe can be visualized in the anterior part of the brain, as well as their axonal projections in the posterior part of the brain. When the MARCM technique is applied using GAL4-GH146, subsets of these projection neurons can be selectively visualized as either neuroblast clones or single-cell clones (Jefferis, 2001).
Systematic clonal analysis revealed that GH146-positive projection neurons (referred to as projection neurons) are derived from three neuroblasts: an anterodorsal, a lateral and a ventral neuroblast. When neuroblast clones are induced in the early embryo and then examined in adults, the anterodorsal, lateral and ventral neuroblasts give rise to approximately 50, 35 and 6 projection neurons, respectively. These three numbers correspond well to the number of projection neurons present in the three GH146- positive cell groups. Since no clones can be induced by applying heat shock after puparium formation (APF), and neuroblast clones generated in late larvae contain 3-5 cells, it is inferred that all projection neurons are born well before the arrival of pioneering adult ORN axons in the antennal lobe around 20-24 h APF. Subsequent analyses focused on anterodorsal projection neurons and lateral projection neurons since most of these neurons have uniglomerular dendritic projections, whereas some ventral projection neurons have diffuse dendritic arborizations, and all project by means of a different path to the higher brain centers, bypassing the mushroom bodies (Jefferis, 2001).
When glomerular projections of neuroblast clones generated in early larvae were examined, it was found that anterodorsal and lateral neuroblast clones appear to innervate stereotypical, intercalated but non-overlapping glomeruli. By contrast, an anterodorsal neuroblast clone and a lateral neuroblast clone examined at the same depth, projected to complementary glomeruli. In the 54 anterodorsal neuroblast and 25 lateral neuroblast clones examined, no exception to this rule was found, despite the fact that there is no obvious relationship between the positions of projection neuron cell bodies and their glomeruli. These observations indicate that the neuroblast from which a projection neuron is derived restricts its glomerular choice and consequently the subset of olfactory information that it can carry further into the brain. It was next asked whether projection neurons are further specified within a neuroblast lineage. Because labelled, single-cell MARCM clones are born shortly after heat-shock induction of mitotic recombination, it was possible to test whether projection neurons born during specific developmental periods would project to specific glomeruli by using the time of heat shock as a variable. It was found that anterodorsal single-cell projection neuron clones with particular glomerular projections were generated within restricted and characteristic developmental windows. Notably, single-cell clones induced by early larval heat shock (0-36 h) exclusively produced projection neurons projecting to glomerulus DL1 (Jefferis, 2001).
Because individual larvae develop at different rates, and FLP recombinase can persist for some time after heat-shock induction, single-cell clone analysis cannot distinguish unequivocally the birth order of projection neuons that are born immediately after each other. Therefore a complementary approach was taken in which multicellular neuroblast clones generated at different developmental periods were examined, and it was determined whether they included certain landmark glomeruli. If projection neurons innervating different glomeruli are produced in a defined sequence, then multicellular neuroblast clones induced at progressively later times during development should innervate a subset of the glomeruli in neuroblast clones generated at earlier times. Eventually the last-born, smallest clones should contain projection neurons innervating only one glomerulus. Such a nested set is exactly what was observed when anterodorsal neuroblast clones were scored for the presence or absence of projection neurons innervating ten landmark glomeruli. An ordered birth sequence of projection neurons (VA2, DL1, DC2, D, VA3, VA1d, VM7, VM2, DM6, VA1lm) could be inferred from the 54 clones analysed. No neuroblast clone was found in which projection neurons projecting to a particular glomerulus were altered from this order; for example, neuroblast clones containing projection neurons projecting to VM7 always additionally contained all three of the later-born types of projection neuron, VM2, DM6 and VA1lm. Since, on average, about three projection neurons innervate each glomerulus, the fact that an order can be inferred implies that projection neurons innervating a common glomerulus are likely to be born at a similar time. Together with the single-cell clone analysis, it can be concluded that, at least for these ten glomeruli, there is a strict order of generation of projection neurons that can predict future glomerular targets (Jefferis, 2001).
How can the birth time of a projection neuron predict which glomerulus it will eventually innervate? One possibility is that the ordered generation of projection neurons could result in the ordered differentiation of their dendrites, and that temporally ordered availability of proto-glomeruli for innervation restricts projection neurons born at a certain time to a particular glomerulus. However, it was found that at around 22 h APF, when pioneering ORN axons just start to invade the antennal lobe, projection neurons born at different times had similar dendritic differentiation statuses, having already initiated their dendritic branches in the vicinity of the antennal lobe region. The axons of the projection neurons had already reached the mushroom body and the lateral horn. These observations argue against the hypothesis of differentiation timing. Instead the hypothesis is favored that individual projection neurons and ORNs are independently specified to carry molecular signals that allow them to recognize either each other or a common set of cues located at the developing antennal lobe. Although it is assumed that stereotyped ORN axon projections depend on a guidance map in the developing antennal lobe, these results imply that such cues may also be used for precise dendritic targeting of projection neurons, or that projection neuron dendrites actively participate in creating the guidance map (Jefferis, 2001).
Independent pre-patterning of input and target fields has been demonstrated in the formation of vertebrate retinotectal projections along the anterior-posterior axis, and even implicated in the development of ocular dominance columns. In both systems, activity-dependent processes have important roles in refining the coarse map at the level of the single cell. This study shows the independent specification of projection neurons at the single-cell level, matching the precision of the ORN identities. These experiments support the importance of independent specification in formation of the neural map. Moreover, since no obvious logic correlates cell body position of the projection neuron, birth time and the location of the glomerular projection, simple molecular gradient/counter-gradient models as used for axon guidance in the retinotectal system are unlikely to suffice. Instead, it is proposed that dendrites of projection neurons use a combination of recognition molecules specific to each eventual glomerulus; mechanisms that generate a complex repertoire of cell-surface molecules have recently been described. Furthermore, this study uncovers an elegant mechanism for specifying different projection neurons: the precisely ordered generation by a single neuroblast of a large number of distinct neurons. Currently it is being determined whether timer mechanism intrinsic to the neuroblast, cues from neighboring cells at the time of birth, or a combination of such mechanisms are used, perhaps to specify the expression of recognition molecules (Jefferis, 2001).
Given the similarities in organization of the Drosophila and
mammalian peripheral olfactory systems, it will be of great
interest to test whether and to what extent the mitral/tufted
cells in the mammalian olfactory system are independently
specified. It is conceivable that the information used to pattern
the olfactory bulb for ORN axon targeting could be used to
prespecify mitral/tufted cells, thereby coordinating their
dendritic targets in the olfactory bulb and axonal projections in
higher brain centers. Such prespecification mechanisms may also be
used in neural map formation in other parts of the developing
brain (Jefferis, 2001).
In both insects and mammals, olfactory receptor neurons (ORNs) expressing specific olfactory receptors converge their axons onto specific glomeruli, creating a spatial map in the brain. Second order projection neurons (PNs) in Drosophila are prespecified by lineage and birth order to send their dendrites to one of ~50 glomeruli in the antennal lobe. How can a given class of ORN axons match up with a given class of PN dendrites? The cellular and developmental events that lead to this wiring specificity have been examined. Before ORN axon arrival, PN dendrites have already created a prototypic map that resembles the adult glomerular map, by virtue of their selective dendritic localization. Positional cues that create this prototypic dendritic map do not appear to be either from the residual larval olfactory system or from glial processes within the antennal lobe. It is proposed instead that this prototypic map might originate from both patterning information external to the developing antennal lobe and interactions among PN dendrites (Jefferis, 2004).
A key finding in this study is that PN dendritic development is surprisingly independent of presynaptic ORN axons. It is generally thought that dendritic growth and maturation are coupled with presynaptic axon invasion and synapse formation, which might be significantly shaped by electrical activity. Before ORN axons reach the developing AL, PN dendrites, however, have undergone significant growth and branching. More strikingly, dendrites of different PN classes have created a pattern in the AL at 18 hours APF that resembles the adult glomerular map, in the complete absence of their presynaptic partners. This observation is in contrast to the prevailing view of olfactory development and underlines a very significant dendritic contribution to the origins of wiring specificity (Jefferis, 2004).
It is important to realize that this finding is not a natural prediction of previous findings that PNs are prespecified to synapse with a specific class of ORNs by lineage and birth order. The current study clearly favours the idea that PN dendrites are patterned first. It is probable that gradual invasion of ORN axons from 24 hours APF refines and consolidates this prototypic dendritic map, allowing rapid development of the AL to essentially adult form by 50 hours APF (Jefferis, 2004).
Site selection of one synaptic partner before the other has also been described recently in Caenorhabditis elegans. Interestingly, in that case, the presynaptic partner selects the synaptic site in the absence of its postsynaptic partner by interacting with a third party guidepost cell (Jefferis, 2004 and references therein).
What positional cues allow dendritic patterning before ORN axon arrival? The first leading candidate to provide positional cues is the larval lobe because it is presumably patterned for larval olfaction, albeit in a form simpler than that of the adult AL. However, at early pupal stages, the developing adult AL is clearly distinct from the larval lobe and is minimally invaded by remnants of the degenerating larval lobe. Glia are a second candidate and, indeed, glia have been suggested to play important roles in sorting ORN axons into individual classes in the moth and are the leading candidates in the mouse olfactory bulb to provide positional cues for ORN axon targeting. However, no significant glial processes are found within the developing AL between 0 hours and 18 hours APF, the critical period for PN dendritic patterning. Although it is likely that glial cells and processes surrounding the AL contribute to PN dendritic patterning, it is difficult to imagine that the surrounding tissues could contribute all the positional cues that allow dendrites of a specific class to occupy specific regions of the AL, which is a three-dimensional sphere (Jefferis, 2004).
These analyses have led to the speculation that PN dendrite-dendrite interaction might contribute significantly to the eventual patterning of PN dendrites for the following reasons. (1) PN dendrites appear to be a major constituent of the developing adult-specific AL, which is composed predominantly, if not exclusively, of neuronal processes. Indeed, preliminary electron microscopic analysis using genetically encoded electron microscopy markers suggests that the developing AL is composed entirely of neuronal profiles and that GH146-positive PN dendritic profiles (enhancer trap GAL4-GH146 labels ~90 of the estimated 150 PN) are clustered together without intermingling with other neuronal profiles. (2) Different classes of PNs are probably endowed with molecular differences because of their lineage and birth order -- these differences could be used to create heterogeneities in the developing lobe. LN processes do remain a possible source of information for which neither positive evidence could be found nor could it be ruled out. However, it is more difficult to imagine how heterogeneity is created by LNs, because processes from each LN occupy a large proportion of the AL, rather than individual glomeruli (Jefferis, 2004).
Based on these considerations, how is it envisaged that PN patterning could occur in early pupa before ORN arrival? A hierarchy of positional cues is proposed. Global cues, which could be diffusible or contact-mediated guidance molecules from outside the lobe, could allow dendrites to target to an approximate region of the developing lobe with respect to the body axes, causing, for example, glomerulus V to form ventrally and glomerulus D to form dorsally. Local dendrite-dendrite interactions would then allow PN dendrites of the same class to adhere tightly; dendrites destined to occupy neighboring glomeruli would associate more weakly and/or be repelled. This hierarchy of cues seems to be essential for generating a structure that has global order and highly reproducible local spatial relationships among neighboring PN classes. The observations at 18 hours APF suggest that although the global targeting of dendrites to specific regions of the AL is largely complete, the sorting process is not, because dendrites from neighboring classes can still exhibit significant overlap. Continuing dendrite-dendrite interaction after 18 hours APF and interaction with ORN axons would further refine this prototypic dendritic map (Jefferis, 2004).
The observation that in Drosophila PN patterning precedes that of ORNs seems at odds with existing observations in insects and vertebrates, emphasizing the primary role of ORN axons in organizing glomerular development. In all these studies, glomerular formation was first evident in the accumulation of ORN axons in protoglomeruli. This organizational function of ORNs is further supported by several perturbation experiments. For instance, in the moth Manduca sexta, developmental deantennation prevents normal glomerular formation, whereas surgical removal of a subset of PNs still permits ORNs to form relatively normal glomerular terminations outlined by glial cells. Similarly, genetic ablation of most mitral or granule cells in mutant mice still permits axonal convergence of specific ORN classes, although the structure of the olfactory bulb is disorganized. In Drosophila, it was reported that in atonal mutants, formation of a proposed pioneer class of ORNs is disrupted, axonal targeting of other ORNs is delayed and glial processes are disturbed. It was further suggested that PN development must depend on ORNs because, in atonal mutants, PN patterning [as visualized by GH146 staining (labelling ~90 PNs)] is disrupted (Jefferis, 2004 and references therein).
Many of these apparent contradictions can be resolved by treating spatial patterning and glomerular formation as two distinct processes. An important technical improvement of this study is that it was possible to visualize the dendritic fields of identifiable PNs down to the single cell level with MARCM or small groups of cells with GAL4-Mz19. It was therefore possible to describe much earlier developmental events with higher anatomical resolution, demonstrating the existence of spatial patterning well before glomeruli are morphologically distinct and, indeed, before one major component of the glomeruli -- the ORN axons -- is even present. For example, dendrites of DL1 PNs occupy a discrete and specific location in the developing lobe. However, because their dendrites still overlap with other PN classes, this patterning is not that obvious when looking at larger numbers of neurons and is scarcely apparent at all when more cells are visualized. Indeed, some existing single cell labelling studies have shown that PNs in Manduca have restricted dendritic arborizations before any glomerular patterning is evident. However, without being able to label specific classes of PNs, such studies cannot determine whether PN dendrites are in a spatially appropriate location (Jefferis, 2004).
How do ORN axons come into register with the prototypic PN map when they reach the lobe? At one extreme, ORN patterning might be completely dependent on PN patterning. ORN axons could simply recognize specific classes of pre-patterned PN dendrites through receptor-ligand or homophilic interactions. Alternatively, PN patterning could generate a third-party map, which is recognized by ORNs. Although certainly consistent with the developmental studies described here, these models are not supported by experiments in other organisms. In addition, transplantation experiments in moth or the formation of a novel glomerulus upon expression of a rat olfactory receptor in mice, indicate that ORNs might have substantial autonomous patterning ability. At the other extreme, patterning of ORN axons could be completely independent of the prototypic map created by PN dendrites. In theory, ORN axons could recognize third-party cues previously used to pattern PN dendrites. However, such third-party cues could not be found within the developing AL. Of course, ORNs could still be patterned by PN independent cues external to the lobe and axon-axon interactions, in a manner directly analogous to the hypothesis for PN patterning. In the case of such strict independence, ORNs expressing a particular receptor would form specific connections with partner PNs, rather than inappropriate adjacent PNs, only because both sets of neurons target with great precision to exactly the same spatial location. This degree of independence seems both implausible and inefficient (Jefferis, 2004).
Instead, it is proposed that both ORN axons and PN dendrites have substantial autonomous patterning ability -- for instance through PN-PN or ORN-ORN mutual interactions and interactions with cellular cues surrounding the developing AL -- but that the two resultant proto-maps interact during development to generate the final mature glomerular organization. This proposal is the most parsimonious explanation for the existing data supporting the organizational functions of ORNs. This model also has the advantage of robustness -- each map could reinforce and refine the other, resulting in a precise match between pre- and postsynaptic partners without the necessity for extreme targeting precision. Furthermore, although two maps might seem to be more complicated than one, they need not be molecularly more complex. Many of the molecules used for PN patterning could also be used for ORN patterning or for interactions between ORNs and PNs. Having described with great precision the cellular and developmental events that led to the patterning of the AL, the molecular basis of wiring specificity in the Drosophila olfactory system can now be attacked (Jefferis, 2004).
Neurons are interconnected with extraordinary precision to assemble a functional nervous system. Compared to axon guidance, far less is understood about how individual pre- and postsynaptic partners are matched. To ensure the proper relay of olfactory information in the fruitfly Drosophila, axons of approximately 50 classes of olfactory receptor neurons (ORNs) form one-to-one connections with dendrites of approximately 50 classes of projection neurons (PNs). In this study, using genetic screens, two evolutionarily conserved, epidermal growth factor (EGF)-repeat containing transmembrane Teneurin proteins, Ten-m and Ten-a, were identified as synaptic-partner-matching molecules between PN dendrites and ORN axons. Ten-m and Ten-a are highly expressed in select PN-ORN matching pairs. Teneurin loss- and gain-of-function cause specific mismatching of select ORNs and PNs. Finally, Teneurins promote homophilic interactions in vitro, and Ten-m co-expression in non-partner PNs and ORNs promotes their ectopic connections in vivo. It is proposed that Teneurins instruct matching specificity between synaptic partners through homophilic attraction (Hong, 2012).
To identify potential PN-ORN matching molecules, select PN dendrites and ORN axons were simultaneously labeled in two colors, and two complementary genetic screens were performed. 410 candidate cell-surface molecules, comprising ~40% of the potential cell-recognition molecules in Drosophila were overexpressed. In the first screen, Mz19-GAL4 was used to label DA1, VA1d and DC3 PNs (referred to as Mz19 PNs), and Or47b-rCD2 was ised to label Or47b ORNs. Or47b ORN axons normally project to the VA1lm glomerulus and are adjacent to Mz19 PN dendrites without overlap. Candidate cell-surface molecules were overexpressed only in Mz19 PNs to identify those that promoted ectopic connections between Or47b axons and Mz19 dendrites. It was found that overexpression of ten-m produced ectopic connections (Hong, 2012).
In the second screen, Mz19 PNs were labelled as above and Or88a ORNs were labelled using Or88a-rCD2. Or88a ORN axons normally project to the VA1d glomerulus, intermingling extensively with VA1d PN dendrites. Candidate cell-surface molecules were overexpressed in Mz19 PNsm, and it was found that overexpression of ten-a partially disrupted the intermingling of Or88a axons and Mz19 dendrites (Hong, 2012).
In addition to impairing PN-ORN matching, ten-m and ten-a overexpression shifted Mz19 PN dendrite position. However, mismatching was not a secondary consequence of axon or dendrite mispositioning; mispositioning alone, caused by perturbation of other genes, does not alter PN-ORN matching. Furthermore, among 410 candidate molecules, only ten-m and ten-a overexpression exhibited mismatching defects, suggesting their specificity in PN-ORN matching (Hong, 2012).
Both ten-m and ten-a appear to encode type II transmembrane proteins. They possess highly similar domain compositions and amino acid sequences; each contains eight EGF-like and multiple YD (tyrosine-aspartate) repeats within its large C-terminal extracellular domain. Ten-m and Ten-a were discovered as Tenascin-like molecules, but vertebrate Teneurins were later identified as their true homologs based on sequence and domain similarity. Ten-m and Ten-a are referred to as Drosophila Teneurins. Teneurins are present in nematodes, flies and vertebrates. In human, Teneurin-1 and Teneurin-2 are located in chromosomal regions associated with mental retardation, and Teneurin-4 is linked to susceptibility to bipolar disorder (Hong, 2012).
Drosophila ten-m was originally identified as a pair-rule gene required for embryonic patterning, but was recently determined otherwise. Teneurins were implicated in synapse development at the neuromuscular junction, and Ten-m also regulates motor axon guidance. Neither the underlying mechanisms nor their potential roles in the central nervous system are known. Vertebrate Teneurins are widely expressed in the nervous system and interact homophilically in vitro, suggesting their potential role as homophilic cell adhesion molecules in patterning neuronal connectivity (Hong, 2012).
Both Drosophila Teneurins were endogenously expressed in the developing antennal lobe. At 48 hrs after puparium formation (APF), when individual glomeruli just become identifiable, elevated Teneurin expression was evident in select glomeruli. The subset of glomeruli expressing elevated Ten-m was distinct but partially overlapping with that expressing elevated Ten-a. Teneurins were also detected at a low level in all glomeruli. Both basal and elevated Teneurin expressions were eliminated by pan-neuronal RNAi targeting the corresponding gene, suggesting that Teneurins are produced predominantly by neurons. In a ten-a null mutant this study found, all Ten-a expression was eliminated, confirming antibody specificity (Hong, 2012).
The antennal lobe consists of ORN axons as well as PN and local interneuron dendrites. This study used intersectional analysis to determine the cellular source for elevated Teneurin expression. For ten-m, GAL4 enhancer traps near the ten-m gene were used, and NP6658 (hereafter as ten-m-GAL4) that recapitulated the glomerulus-specific Ten-m staining pattern, was identifed. A FLPout reporter UAS>stop>mCD8GFP or a PN-specific GH146-Flp were used to determine the intersection of ten-m-GAL4 and an ORN-specific ey-Flp. It was found that ten-m-GAL4 was selectively expressed in a subset of ORNs and PNs. Due to reagent availability, focused was placed on five glomeruli (DA1, VA1d, VA1lm, DC3, DA3), adjacently located on the lateral and anterior side of the antennal lobe. In these five glomeruli, Ten-m expression in PN and ORN classes matched: high levels in PNs corresponded to high levels in ORNs and vice versa (Hong, 2012).
To determine the cellular origin of elevated Ten-a expression, tissue-specific RNAi of endogenous Ten-a was performed, as no GAL4 enhancer trap is available near ten-a. To isolate Ten-a expression in ORNs, pan-neuronal ten-a RNAi was performed while specifically suppressing RNAi in ORNs using tubP>stop>GAL80 and ey-Flp. To restrict Ten-a expression to central neurons, ten-a RNAi was expressed in all ORNs. It was found that Ten-a was highly expressed in a subset of ORNs and central neurons, and also showed a matching expression in five glomeruli focused in this study. The glomerular-specific differential Ten-a expression in central neurons likely arises mainly from PNs as they target dendrites to specific glomeruli, and punctate Ten-a staining was observed in PN cell bodies. In summary, Ten-m and Ten-a are each highly expressed in a distinct, but partially overlapping, subset of matching ORNs and PNs (Hong, 2012).
To examine whether Teneurins are required for proper PN-ORN matching, tissue-specific RNAi was performed in all neurons using C155-GAL4, in PNs using GH146-GAL4, or in ORNs using peb-GAL4. To label specific subsets of PN dendrites independent of GAL4-UAS, the Q binary expression system was used, and Mz19-GAL4 was converted to Mz19-QF by BAC recombineering. It was thus possible to perform GAL4-based RNAi knockdown while labeling PN dendrites and ORN axons in two colors independent of GAL4. The analysis focused on Mz19 dendrites and Or47b axons, which innervate neighboring glomeruli but never intermingle in wild type ( (Hong, 2012).
Pan-neuronal RNAi of both teneurins shifted Or47b axons to a position between two adjacent Mz19 glomeruli, DA1 and VA1d. Moreover, Mz19 dendrites and Or47b axons intermingled without a clear border, reflecting a PN-ORN matching defect. This was confirmed using independent RNAi lines targeting different regions of the ten-m and ten-a transcripts. Further, knocking down teneurins only in PNs or ORNs also led to Mz19-Or47b intermingling, indicating that Teneurins are required in both PNs and ORNs to ensure proper matching (Hong, 2012).
Next, the contribution of each Teneurin was examined by individual RNAi knockdown in ORNs. Knocking down ten-m, and to a lesser extent, ten-a, caused mild mismatching. This was greatly enhanced by simultaneous teneurin knockdown, likely because Mz19-Or47b mismatching requires weakening connections with their respective endogenous partners. This synergy implies that multiple matching molecules can enhance partner matching robustness (Hong, 2012).
The functions of individual Teneurins in PNs was examined. It was found that the Mz19-Or47b mismatching was caused by PN-specific knockdown of ten-a, but not ten-m. As VA1d/DC3 and DA1 PNs arise from separate neuroblast lineages, MARCM neuroblast clones were generated to label and knock down ten-a in DA1 or VA1d/DC3 PNs. ten-a knockdown only in DA1 PNs (normally Ten-a high) caused dendrite mismatching with Or47b axons. By contrast, ten-a knockdown in VA1d/DC3 PNs (normally Ten-a low) did not cause mismatching. Similarly, MARCM loss-of-function of ten-a mutant in DA1 but not in VA1d/DC3 PNs resulted in mismatching with Or47b ORNs. Thus, removal of ten-a from Ten-a-high DA1 PNs caused dendrite mismatching with Ten-a-low Or47b ORNs. The differential requirements of Ten-m and Ten-a in ORNs or PNs in preventing Mz19-Or47b mismatching likely reflect differential expression of Ten-m and Ten-a in the mismatching partners (Hong, 2012).
The finding that loss of ten-a caused Ten-a-high PNs to mismatch with Ten-a-low ORNs, together with the matching expression of Teneurins in PNs and ORNs, raised the possibility that Teneurins instruct class-specific PN-ORN connections through homophilic attraction: PNs expressing high-level Ten-m or Ten-a connect to ORNs with high-level Ten-m or Ten-a, respectively (Hong, 2012).
This homophilic attraction hypothesis predicts that overexpression of a given Teneurin in PNs (1) should preferentially affect PNs normally expressing low levels of that Teneurin, causing their dendrites to lose endogenous connections with their cognate ORNs, and (2) should cause these PNs to make ectopic connections with ORNs expressing high levels of that Teneurin (Hong, 2012).
To test the first prediction, whether Teneurin overexpression in Mz19 PNs impaired their endogenous connections with cognate ORNs was examined. Consistently, Ten-m overexpression specifically disrupted the connections of DA1 PNs and Or67d ORNs, a PN-ORN pair expressing low-level Ten-m. Connections of the other two pairs were unaffected. Likewise, Ten-a overexpression specifically disrupted connections between VA1d PNs and Or88a ORNs, a PN-ORN pair expressing low-level Ten-a, but not between the other two PN-ORN pairs (Hong, 2012).
To test the second prediction, the specificity of ectopic connections made by Mz19 PNs overexpressing Teneurins were examined, and sampled with non-partner ORN classes that project axons nearby Mz19 dendrites. It was found that Ten-m overexpression in Mz19 PNs caused dendrite mismatching only with Or47b ORNs. To examine additional mismatching phenotypes that may occur within Mz19 glomeruli and to determine whether DA1 or VA1d/DC3 PNs contribute to the ectopic connections, MARCM was used to overexpress Ten-m in individual PN classes. It was found that Ten-m overexpression in DA1 PNs (Ten-m low) caused dendrite mismatching with Or47b and (to a lesser extent) Or88a ORNs, both endogenously expressing high-level Ten-m. By contrast, Ten-m overexpression in VA1d/DC3 PNs did not produce ectopic connections with any non-matching ORNs tested (Hong, 2012).
Likewise, Ten-a overexpression in Mz19 PNs caused dendrite mismatching only with Or23a ORNs among all non-matching ORN classes sampled outside the Mz19 region. Further, MARCM overexpression of Ten-a in VA1d/DC3 PNs (Ten-a low) caused dendrite mismatching specifically with Or23a and (to a lesser extent) Or67d ORNs, both endogenously expressing high-level Ten-a. By contrast, Ten-a overexpression in DA1 PNs (Ten-a high) did not produce ectopic connections with any non-matching ORNs tested. Thus, both Ten-m and Ten-a overexpression analyses support the homophilic attraction hypothesis (Hong, 2012).
The data also suggest that additional molecule(s) are required to completely determine the wiring specificity of the five PN-ORN pairs examined. For example, VA1d-Or88a and VAl1m-Or47b have indistinguishable Ten-m/Ten-a expression patterns, and may require additional molecules to distinguish target choice. Indeed, Ten-a knockdown or Ten-m overexpression caused DA1 PNs to mismatch preferentially with Or47b as opposed to Or88a axons. This suggests that the non-adjacent DA1 and VA1lm share a more similar Teneurin-independent cell-surface code than the adjacent VA1d and VA1lm. Likewise, Ten-a overexpression caused VA1d PNs to mismatch with the non-adjacent Or23a more so than the adjacent Or67d ORNs, even though both ORNs express high-level Ten-a. Finally, Ten-m overexpression in DC3 PNs, which express low-level Ten-m, did not change its matching specificity, suggesting that Teneurin-independent mechanisms are involved in matching DC3 PNs and Or83c ORNs (Hong, 2012).
In summary, this study has shown that Teneurin overexpression in Teneurin-low PNs caused their dendrites to lose endogenous connections with Teneurin-low ORNs and mismatch with Teneurin-high ORNs. However, Teneurin overexpression in Teneurin-high PNs did not disrupt their proper connections. These data strongly support that Teneurins instruct connection specificity likely through homophilic attraction, by matching Ten-m or Ten-a levels in PN and ORN partners (Hong, 2012).
To test whether Teneurins interact in vitro, two populations of Drosophila S2 cells were separately transfected with FLAG- and HA-tagged Teneurins, and co-immunoprecipitations were performed from lysates of these cells after mixing. Strong homophilic interactions were detected between FLAG- and HA-tagged Ten-m proteins, and to a lesser extent between FLAG- and HA-tagged Ten-a proteins . Ten-m and Ten-a also exhibited heterophilic interactions, which may account for their role in synapse organization (Hong, 2012).
Next, whether Teneurins can homophilically promote in vivo trans-cellular interactions between PN dendrites and ORN axons was tested. Ten-m was simultaneously overexpressed in Mz19 PNs using Mz19-QF, and Or67a and Or49a ORNs using AM29-GAL4. This enabled independently labeling and manipulation of Mz19 dendrites and AM29 axons with distinct markers and transgenes. AM29-GAL4 was chosed because of its early onset of expression, whereas other class-specific ORN drivers start to express only after PN-ORN connection is established. AM29 axons do not normally connect with Mz19 dendrites (Hong, 2012).
Simultaneous overexpression of Ten-m in both Mz19 PNs and AM29 ORNs produced ectopic connections between them, suggesting that Ten-m homophilically promotes PN-ORN attraction. By contrast, Ten-m overexpression only in PNs or ORNs did not produce any ectopic connections, despite causing dendrite or axon mistargeting, respectively. These data ruled out the involvement of heterophilic partners in Ten-m-mediated attraction. Simultaneous overexpression of Ten-a in Mz19 PNs and AM29 ORNs did not produce ectopic connections, possibly due to lower expression or weaker Ten-a homophilic interactions (Hong, 2012).
Finally, whether these ectopic connections lead to the formation of synaptic structures was examined. Indeed, the ectopic connections between Mz19 dendrites and AM29 axons were enriched in synaptotagmin-HA expressed from AM29 ORNs, suggesting that these connections can aggregate synaptic vesicles and could be functional. It is proposed that Teneurins promote attraction between PN-ORN synaptic partners through homophilic interactions, eventually leading to synaptic connections (Hong, 2012).
Compared to axon guidance, relatively little is known about synaptic target selection mechanisms. Among the notable examples, the graded expressions of vertebrate EphA and Ephrin-A instruct the topographic targeting of retinal ganglion cell axons. Chick DSCAMs and Sidekicks promote lamina-specific arborization of retinal neurons. Drosophila Capricious promotes target specificity of photoreceptor and motor axons. C. elegans SYG-1 and SYG-2 specify synapse location through interaction between pre-synaptic axons and intermediate guidepost cells>. However, it is unclear whether any of these molecules mediate direct, selective interactions between individual pre- and post-synaptic partners. Indeed, in complex neural circuits, it is not clear a priori whether molecular determinants mediate such interactions. For example, the final retinotopic map is thought to result from both Ephrin signaling and spontaneous activity. Mammalian ORN axon targeting involves extensive axon-axon interactions through activity-dependent and independent modes, with minimal participation of postsynaptic neurons identified thus far (Hong, 2012).
This study has shown that Teneurins instruct PN-ORN matching through homophilic attraction. Although each glomerulus contains many synapses between cognate ORNs and PNs, these synapses transmit the same information and can be considered identical with regard to specificity. Thus, Teneurins represent a strong case in determining connection specificity directly between pre- and post-synaptic neurons. It was further demonstrated that molecular determinants can instruct connection specificity of a moderately complex circuit at the level of individual synapses (Hong, 2012).
This study reveals a requirement for PN-ORN attraction in the stepwise assembly of the olfactory circuit. PN dendrites and ORN axons first independently target to appropriate regions using global cues, dendrite-dendrite and axon-axon interactions. These initial, independent dendrite and axon targeting are eventually coordinated in their final one-to-one matching. Teneurins were identified as the first molecules to medicate this matching process, through direct PN-ORN attraction. These analyses have focused on a subset of ORN-PN pairs involving trichoid ORNs, including Or67d/Or88a/Or47b that are implicated in pheromone sensation. The partially overlapping expressions of Teneurins in other PN and ORN classes suggest a broader involvement of Teneurins. At the same time, additional cell-surface molecules are also needed to completely determine connection specificity of all 50 PN-ORN pairs (Hong, 2012).
Understanding information flow through neuronal circuits requires knowledge of their synaptic organization. This study utilized fluorescent pre- and postsynaptic markers to map synaptic organization in the Drosophila antennal lobe, the first olfactory processing center. Olfactory receptor neurons (ORNs) produce a constant synaptic density across different glomeruli. Each ORN within a class contributes nearly identical active zone number. Active zones from ORNs, projection neurons (PNs), and local interneurons have distinct subglomerular and subcellular distributions. The correct number of ORN active zones and PN acetylcholine receptor clusters requires the Teneurins, conserved transmembrane proteins involved in neuromuscular synapse organization and synaptic partner matching. Ten-a acts in ORNs to organize presynaptic active zones via the spectrin cytoskeleton. Ten-m acts in PNs autonomously to regulate acetylcholine receptor cluster number and transsynaptically to regulate ORN active zone number. These studies advanced the ability to assess synaptic architecture in complex CNS circuits and their underlying molecular mechanisms (Mosca, 2014: PubMed).
Understanding information flow through neuronal circuits requires knowledge of their synaptic organization. This study utilized fluorescent pre- and postsynaptic markers to map synaptic organization in the Drosophila antennal lobe, the first olfactory processing center. Olfactory receptor neurons (ORNs) produce a constant synaptic density across different glomeruli. Each ORN within a class contributes nearly identical active zone number. Active zones from ORNs, projection neurons (PNs), and local interneurons have distinct subglomerular and subcellular distributions. The correct number of ORN active zones and PN acetylcholine receptor clusters requires the Teneurins, conserved transmembrane proteins involved in neuromuscular synapse organization and synaptic partner matching. Ten-a acts in ORNs to organize presynaptic active zones via the spectrin cytoskeleton. Ten-m acts in PNs autonomously to regulate acetylcholine receptor cluster number and transsynaptically to regulate ORN active zone number. These studies advanced the ability to assess synaptic architecture in complex CNS circuits and their underlying molecular mechanisms (Mosca, 2014).
A functional synapse consists of a presynaptic neurotransmitter release site and a postsynaptic neurotransmitter receptor cluster. Therefore, critical parameters of synaptic organization within a circuit not only include the location and number of presynaptic active zones, but also postsynaptic receptor clusters. Therefore, this study examined the organization of postsynapses. Given that ORNs are cholinergic, an ideal labeling strategy would image postsynaptic acetylcholine receptors (Mosca, 2014).
The Dα7 acetylcholine receptor subunit was chosen because it is endogenously expressed in the antennal lobe (Fayyazuddin, 2006) and it has been used to examine organization in the mushroom body, a higher olfactory center (Leiss, 2009a, 2009b; Kremer, 2010; Christiansen, 2011). A GFP-tagged Dα7 transgene under the control of the GAL4/UAS system was used to visualize postsynapses in vivo. Expression of Dα7-GFP in PNs revealed distinct puncta, possibly corresponding to acetylcholine receptor (AChR) clusters. These puncta were apposed to endogenous Brp puncta, as revealed by nc82 staining, consistent with these puncta representing bona fide synapses. To examine AChR clusters in PNs, Dα7-GFP was co-expressed with mtdT as a general neurite label. As such, the approach is analogous to a Brp-Short assay and yielded similar results, enabling a quantitative assessment of the number and density of AChR clusters (Mosca, 2014).
As the study was limited to genetically accessible PN subsets, focus was placed on identifying organizational parameters in the PNs that innervate the DA1 and VA1d glomeruli via the Mz19-GAL4 driver. As with ORN presynapses, the assay revealed that the number of AChR puncta scales with glomerular size. Further, known sex-specific differences in DA1, as seen in glomerular volume and in ORN synapses, were also observed. The differences between the Brp-Short and AChR assays for the DA1 and VA1d glomeruli may reflect the fact that the Brp-Short assay does not distinguish ORN synapses onto PNs and LNs, and the Dα7-GFP assay does not distinguish synapses from ORNs and LNs onto PNs. As these values are less than twofold different, this is consistent with the majority of synapses labeled being ORN to PN synapses. The similarity between the numbers of endogenous Brp and Brp-Short puncta suggests that Brp-Short is a more accurate estimator of absolute synapse number. The larger number of AChRs detected in each glomerulus may reflect an overestimation associated with full-length Dα7 overexpression or that these are postsynaptic not just to cholinergic ORNs, but also other excitatory neurons such as local interneurons or PN-PN chemical synapses (Mosca, 2014).
Calculation of AChR puncta density in PNs revealed subtle but significant differences across different glomeruli. In the VA1d glomerulus, the densities were identical between males and females. However, these were different from AChR puncta densities in the DA1 glomerulus. There was a modest but significant difference between both male and female AChR densities in DA1 and between both DA1 AChR densities and the shared VA1d AChR density. Unlike ORNs, where the Brp-Short density was identical across different classes of neurons, PNs can have different densities between distinct glomeruli and even between sexes for the same glomerulus. Thus, the parameters that govern presynaptic density may differ from those that govern postsynaptic density in the same glomerulus (Mosca, 2014).
To further examine if the Teneurins regulate postsynaptic acetylcholine receptor number and density, the Dα7-GFP assay was used to determine the effect of Teneurin perturbation on AChR puncta number. PNs were examined in DA1 and VA1d and the AChR puncta of both glomeruli were counted together as one measurement, as partner matching defects following Teneurin perturbation make it difficult to differentiate between the two glomeruli. In ten-a mutants, the number of AChR clusters in these glomeruli was decreased by 23%, compared to wild type. This is consistent with results from the Brp-Short assay. Moreover, PN neurite volume was unaffected, so AChR puncta density was similarly reduced. Thus, two independent assays, both pre- and postsynaptic, show the same phenotypes, demonstrating a clear effect of ten-a loss on synapse organization in olfactory neurons (Mosca, 2014).
At the NMJ, presynaptic Ten-a functions largely in a transsynaptic, heterophilic complex with postsynaptic Ten-m to regulate synapse organization. Ten-a functions presynaptically in ORNs to ensure proper synapse number. Thus, it was hypothesized that the loss of Ten-m in postsynaptic PNs should result in a similar phenotype. As the ten-m mutant is larval lethal, a previously validated transgenic RNAi line against ten-m was expressed in Mz19 PNs, and AChR puncta number was quantitated using the Dα7 assay. ten-m knockdown phenocopied the ten-a phenotype. As above, PN neurite volume was unaffected, leading to a concomitant decrease in AChR puncta density that also phenocopied the ten-a phenotype. Further, this reduction was not enhanced by knocking down ten-m in PNs of a ten-a null mutant, suggesting that the two function in the same genetic pathway (Mosca, 2014).
This study has identified parameters that govern synapse number, density, and subcellular organization using two fluorescently-tagged synaptic proteins expressed from single transgenes in combination with high-resolution confocal microscopy and image processing to visualize synapses in the Drosophila olfactory system in vivo. It was demonstrated that these methods are amenable to analysis in both individual neuronal classes and individual neurons. The study provides a synapse-level analysis of innervation of olfactory receptor neurons, projection neurons, and local interneurons in the antennal lobe, which has emerged as a model circuit for analyzing principles of information processing. Finally, using these synaptic tagging assays, it was shown that the Teneurins are required for the proper synapse number in ORNs and PNs as well as the structure of the active zones themselves. This reveals a critical role for these transmembrane proteins in organizing central synapses, likely by regulating the cytoskeleton. These approaches can be broadly used to study synaptic organization of neurons for which genetic access is available, and to investigate the functions of any other proteins in the organization and development of CNS synapses (Mosca, 2014).
In Drosophila, previous approaches to studying central synapses used tagged synaptic vesicle proteins to reveal putative synaptic sites. While consistent with synapses, they could also stain non-synaptic, trafficking vesicles. This study utilized a structural active zone component, Brp. By expressing a truncated Brp transgene, Brp-Short, using the GAL4/UAS system, this approach can label synapses in any neurons with genetic access. Brp-Short expression requires endogenous Brp for proper localization. Thus, it accurately reports endogenous active zones. Recently, an elegant technique, STaR, was developed that tags an additional BAC-sourced copy of Brp with an epitope tag whose expression is conditional upon FLP-recombinase-mediated excision of an intervening stop codon. An important advantage of STaR is that Brp expression is controlled by its endogenous promoter, thus guarding against mislocalization of Brp or perturbation of synaptic function due to overexpression. A caveat of Brp-Short is that it is controlled by GAL4 and thus the levels may be different from the endogenous level. While Brp-Short overexpression does not interfere with synaptic function, care must be taken not to overexpress it to a level that saturates the active zone localization machinery when utilized in new cell types. The advantages of Brp-Short over STaR are (a) that it does not require a cell type-specific FLP transgene, which is not as widely available as GAL4 lines, or a BAC-bearing copy of Brp, and (b) that it can be co-expressed with UAS-transgenes for rescue or RNAi for perturbation experiments, although STaR can also achieve this aspect by using a cell-type-specific GAL4 and an extra UAS-FLP transgene (Mosca, 2014).
To examine putative postsynaptic acetylcholine receptor clusters, a GFP-tagged subunit, Dα7, was used to study cholinergic synapses in the antennal lobe. This transgene has been used to examine synaptic organization. Though false positives can be associated with full-length protein overexpression, the current observation of endogenous Brp puncta apposed to these Dα7-GFP puncta suggests that these receptors are properly localized to endogenous synapses. This assay complements the Brp-Short presynaptic assay and can be adapted for other tagged postsynaptic receptor transgenes (Mosca, 2014).
Though considerable advances have been made in understanding of the wiring specificity and physiological properties of the Drosophila olfactory circuit in the antennal lobe, little is known about its synaptic organization. Since this system has emerged as a model neural network, a detailed mapping of synaptic organizational principles is integral towards advancing the study of circuit dynamics. Indeed, the juxtaposition of distinct types of synapses between multiple neuronal classes in the antennal lobe provides a model to study complex synaptic interactions compared to a neuromuscular synapse that features only two synaptic partners: the motoneuron and the muscle. This study utilized the Brp-Short and Dα7 assays to probe how synapses in ORNs, PNs, and LNs are organized in the antennal lobe with respect to their number, density, and location. This work offers the first comprehensive information on (1) the number of active zones made by each ORN within a glomerulus, (2) the stereotypy of synapse numbers between those individual ORNs, (3) the prominence of PN presynaptic inputs within a glomerulus, suggesting a robust feedback mechanism, and (4) the relatively small contribution of LN active zones to the antennal lobe circuit. These analyses suggest distinct rules that govern the synaptic organization of antennal lobe neurons. ORNs, the primary input neurons of the olfactory system, are diverse in their olfactory receptor expression, ligand specificity, and glomerular targeting specificity; this study now shows that they also differ in the absolute synapse number. However, despite such differences, all five classes examined (DA1, VA1d, VA1lm, DL4, and DM6 ORNs) have identical synaptic densities, suggesting that this represents a general rule for other ORN classes. This may further suggest that the primary job of the ORN is to convey information from the environment into the system as faithfully as possible, that all information is treated equally at this level, and that weighting computations occur downstream in the brain. Indeed, analyses indicate that each ORN makes an equivalent, discrete number of synapses within a given glomerulus with little variation, further supporting this hypothesis (Mosca, 2014).
Interestingly, the density of postsynaptic receptors differs between glomeruli and even within the same glomerulus between sexes. This variation can be due to technical caveats, such as Mz19-GAL4 does not label all PNs that innervate DA1 and VA1d, or that Dα7-GFP clusters do not reflect the absolute number of AChRs. As the relative numbers still show these differences, an interesting possibility suggested by these results is that postsynaptic PN AChRs already reflect a transformed olfactory representation compared to output synapses of ORNs. The difference in PN AChR density as compared to the constant density of ORN active zones suggests that different classes of PNs may modulate how information is received by regulating the number of acetylcholine receptors. This can thus contribute to the transformation of olfactory representation by antennal lobe neurons (Mosca, 2014).
Fine-scale analysis of synapse localization within projections of ORNs, LNs, and PNs suggested that these three types of neurons differ in their subglomerular organization. While occupying the vast majority of territory throughout the entire glomerulus, ORN processes and synapses leave distinct voids. A significant proportion of LNs form synapses in these voids, likely to other LNs or PNs. However, there is also overlap between LN and ORN processes and synapses, consistent with physiologically characterized ORN -> LN and LN -> ORN synapses. Within their respective neurites, ORNs and PNs display uneven distributions and synaptic clusters to varying degrees while active zones in LNs are more evenly distributed throughout their processes. These characterizations contribute to the growing repertoire of studies seeking to understand synaptic organization in Drosophila olfactory circuits, adding synapse-level imaging to physiological techniques. Finally, the existence of synaptic organization parameters detailing number and location suggests molecular mechanisms designed to enforce those rules, both at cellular and circuit levels. Indeed, such analysis represents an integral part of neuronal circuit analysis, as recent work on retinal neurons has shown that accounting for synapse position is a critical aspect of modeling connectivity (Mosca, 2014).
The data demonstrate that the Teneurins, a family of transsynaptic adhesion molecules, regulate one of these synaptic organizational paradigms: synapse number. Beyond molecules like RPTPs and Wnts , there is little known conservation between the organization mechanisms of central synapses and the NMJ. In vertebrates, previous studies have identified a number of synaptogenic signaling and cell adhesion molecules in the CNS, but in many cases, their roles at the NMJ are either minimal or unknown. Likewise, the roles of pathways including Rapsyn, Dok7, MuSK, and Tid1, which are well established at the NMJ, have no well-established roles at CNS synapses. Among the identified central synaptogenic molecules, no master controller of synapses, like Agrin, has been discovered. In the mammalian CNS, synaptic adhesion molecules like Neurexin and Neuroligin have demonstrated organizational roles but their role (if any) at the NMJ is largely unknown. In Drosophila, considerable work has been done at the NMJ to understand synapse formation and organization. For example, neuromuscular Neurexin and Neuroligin regulate synaptic development and assembly, but remain (as with many other identified molecules) largely untested in the CNS due to the absence of techniques for doing so (Mosca, 2014).
The approaches described in this study have now enabled such an examination, uncovering a strongly conserved synaptic organization function of the Teneurins from PNS to CNS. Recent work has shown that these evolutionarily conserved proteins are involved in synaptic partner matching between neurons in the Drosophila olfactory system and between muscles and motoneurons at the NMJ. As there are marked differences between central and peripheral synapses (like the NMJ), it is further unclear whether the mechanisms would be conserved or if they would be wholly different. This study found, as assayed by Brp-Short, ultrastructural, and Dα7 analyses, that Teneurins in olfactory neurons are required for normal synapse number. Teneurin perturbation also reduces synaptic density, a parameter that is highly invariable for ORNs under normal conditions. It was determined that presynaptic Ten-a in ORNs likely functions with postsynaptic Ten-m in PNs to regulate levels of the spectrin cytoskeleton. The evidence is consistent with spectrin and the Teneurins functioning in the same genetic pathway to regulate synapse organization and density. The perturbation of active zone number in ORNs by knocking down ten-m in PNs further suggests that Teneurins regulate synapse number and organization in the CNS via a transsynaptic mechanism. This highlights further conservation between central and peripheral synapse organization in the use of Teneurins. There are, however, some differences between the CNS and the PNS regarding the Teneurins. While presynaptic ten-m has a minor role in synaptic organization at the NMJ, the data suggests the lack of such a role in the CNS. Thus, these different systems may also use the Teneurins differently. Mammalian Teneurins organize the visual system and Ten-2 can serve as a ligand for Latrophilin and localize to synapses in cultured neurons. However, as proper synaptic function is impaired in many neuropsychiatric disorders and human Teneurin-4 is associated with increased susceptibility to bipolar disorder, understanding how the Teneurins regulate central synapses is a question with clinical relevance. Studies in vivo will be important to determine how mammalian Teneurins regulate synaptic organization and whether the different Teneurins can have specific roles at synapses (Mosca, 2014).
In summary, the results demonstrate a role for the Teneurins in regulating the number of central synapses and highlight mechanistic conservation between peripheral and central synapse formation. Moreover, the fact that ORNs can be mistargeted but still have the correct number of synapses suggests that target choice and synapse organization can be biologically separable, even when they employ the same molecules (Mosca, 2014).
Proper function of the neural network results from the precise connections between axons and dendrites of presynaptic and postsynaptic neurons, respectively. In the Drosophila olfactory system, the dendrites of projection neurons (PNs) stereotypically target one of approximately 50 glomeruli in the antennal lobe (AL), the primary olfactory center in the brain, and form synapses with the axons of olfactory receptor neurons (ORNs). This study shows that Eph and Ephrin, the well-known axon guidance molecules, instruct the dendrodendritic segregation during the discrete olfactory map formation. The Eph receptor tyrosine kinase is highly expressed and localized in the glomeruli related to reproductive behavior in the developing AL. In one of the pheromone-sensing glomeruli (DA1), the Eph cell-autonomously regulates its dendrites to reside in a single glomerulus by interacting with Ephrins expressed in adjacent PN dendrites. These data demonstrate that the trans interaction between dendritic Eph and Ephrin is essential for the PN dendritic boundary formation in the DA1 olfactory circuit, potentially enabling strict segregation of odor detection between pheromones and the other odors (Anzo, 2017).
The proper assembly of neural circuits during development is necessary for the formation of functional neural networks. One of the key steps for establishing a functional neural circuit is to construct a precise connection between the axons and dendrites of presynaptic and postsynaptic neurons, respectively. In the visual and auditory systems, neighboring neurons in the input field target the neighboring regions in the output field. In the olfactory systems of mammals and insects, the axons of the primary olfactory receptor neurons (ORNs) that express the same olfactory or ionotropic receptors converge to one specific glomerulus in the primary olfactory center. The ORN axons form synaptic connections with dendrites of second-order neurons that also typically target one particular glomerulus among those discretely distributed. Unlike in other sensory systems, there is less spatial correlation between axon and dendrite targeting in the olfactory system. Thus, the neuronal wiring in the olfactory system can be the most striking example of specific targeting achieved by both axons and dendrites among the neural targeting events during development. The previous studies have shown that the topographic mapping in the visual system and the neuronal wiring in the olfactory system are mostly governed by axon guidance. In comparison, dendrite targeting is far less understood not only due to the complex morphology and diversity of dendrites but also because its historical background has received little attention (Anzo, 2017).
The Drosophila olfactory system is a suitable model to study the mechanisms underlying dendrite targeting. The primary olfactory center, the antennal lobe (AL), consists of ~50 discrete structures called glomeruli that are identifiable from their shape, relative size, and position. Most of the projection neuron (PN) dendrites invade one particular glomerular space and form synapses with axons of a single ORN class. In addition, genetic tools such as mosaic analysis with a repressible cell marker (MARCM) allow labelling of specific subsets of PNs at a single-cell resolution in vivo and simultaneously manipulate genes in the labeled neurons (Anzo, 2017).
By taking advantage of the Drosophila olfactory system, the cell surface molecules that regulate dendrite targeting have been gradually revealed. Cell surface molecules such as Semaphorin-1a (Sema-1a) and Toll-6 cell-autonomously regulate dendrite targeting along the dorsolateral-ventromedial axis and mediolateral axis, respectively. The PN dendrites determine their coarse position in the AL along the axes depending on the expression level of Sema-1a or Toll-6 therein. The leucine-rich repeat transmembrane protein Capricious (Caps) is differentially expressed in a subset of PNs and represents a mosaic pattern in the developing AL. The differential Caps expression cell-autonomously instructs glomerular-specific PN targeting, especially the segregation of Caps-positive and Caps-negative PN classes. These findings indicate that besides axial information, discrete determinants also provide positional information to the PN dendrites. Moreover, the cell adhesion molecule N-cadherin (Ncad) and immunoglobulin superfamily protein Dscam act as attractive or repulsive signals in most of the PN classes that restrict the dendritic field to the appropriate glomerular space. In addition to these findings, it was found in this study that the dendritic boundary formation between specific subtypes of PNs are instructed by cell surface molecules, Eph, and Ephrin (Anzo, 2017).
The Eph receptor and its ligand, Ephrin, are the largest family of receptor tyrosine kinases (RTKs) and are widely conserved from invertebrates to mammals. Eph and Ephrin have been well studied as axon guidance molecules in retinotectal topographic mapping. In the vertebrate tectum/superior colliculus (SC), the EphA/EphrinA and EphB/EphrinB countergradients are formed along the anterior-posterior and nasal-temporal axes, respectively. The axons of retinal ganglion cells (RGCs) determine their target field by recognizing the relative position based on the expression levels of their ligands at the tectum/SC. For example, the temporal RGC axon expressing EphA receives a repulsive signal from EphrinA expressed in the tectum/SC, which causes the temporal axon to avoid the posterior tectum/SC. In vertebrates, Ephrins are divided into two groups based on the type of membrane linkage: GPI-anchored EphrinAs (EphrinA1-6) and transmembrane EphrinBs (EphrinB1-3). Ephs are also divided into two subtypes depending on the affinity to Ephrins: EphAs (EphA1-8 and Eph10) bind to multiple EphrinAs, and, similarly, EphBs (EphB1-4 and Eph6) bind to multiple EphrinBs, with the exception of EphA4 binding to both EphrinAs and EphrinBs. Since both Ephs and Ephrins are membrane-bound proteins, the signal is essentially activated via contact-dependent cell-cell interaction. The bidirectional Eph/Ephrin signal works repulsively in a majority of the cases, although an adhesive response has also been described. Since Drosophila has only a single pair of Eph-Ephrin, the overlapping function of their family members as is considered in vertebrate studies can be excluded. Drosophila Eph shows ~71% identity with both vertebrate EphA3 and EphB2, and Drosophila Ephrin has a vertebrate EphrinB-like cytoplasmic domain. A previous study of topographic mapping in the Drosophila visual system strongly suggested that Drosophila Eph/Ephrin signal functions in an evolutionarily conserved fashion (Anzo, 2017).
This study found that Eph/Ephrin signal instructs dendrodendritic segregation during discrete olfactory map formation. Unlike Ncad or Dscam, which affects most of the PN classes, Eph/Ephrin signal selectively functions in only specific PN classes. High Eph RTK expression was observed specifically in the glomeruli associated with reproductive behavior in the developing AL. In addition, genetic data indicate that Eph/Ephrin trans interaction between neighboring glomeruli plays a central role in local dendrodendritic segregation through bidirectional repulsive responses (Anzo, 2017).
This study demonstrates that the trans interaction between the DA1 dendritic Eph and Ephrin on the adjacent dendrites is required for proper dendritic boundary formation. How can this be possible considering the patterned expression of Eph and the ubiquitous expression of Ephrin in the developing AL? It is proposed that the restricted expression of Eph in the DA1 dendrites could effect the activation of differential signal transduction between the dendrites in the DA1 and the adjacent glomeruli even though Ephrin is expressed ubiquitously throughout the developing AL. As the result of the trans interaction between the DA1 dendritic Eph and the adjacent dendritic Ephrin, the Eph forward signal seems to be transmitted to the Eph-expressing DA1 l-PNs, and the Ephrin reverse signal seems to be transmitted to the adjacent PNs. This transinteraction model involving Eph forward and Ephrin reverse signals also fits well with the result that the Eph-null mutant (EphX652), but not Eph-shRNA expression in the VA1d ad-PNs, exhibited dendritic spillover from the VA1d to the DA1 glomerulus. The loss of Eph in the EphX652 mutant could weaken the Ephrin reverse signal in addition to the Eph forward signal, resulting in dendritic spillover from both the DA1 and VA1d dendrites. In contrast, the cell-autonomous reduction of Eph in the VA1d dendrites with Eph-shRNA has no way to reduce the Ephrin reverse signal. In vertebrates, the trans Eph-Ephrin interaction leads to the formation of higher signaling clusters. Oligomers of Ephs and Ephrins are terminated by bidirectional transendocytosis or its cleavage by ADAM-type proteases, leading to the activation of Rho family GTPases. This activation of Rho family GTPases by Eph/Ephrin oligomerization modulates actin cytoskeletal dynamics, which induce cell-cell repulsion in the most cases. Hence, the segregation model is proposed as follows. The transinteraction between the DA1 dendritic Eph and the adjacent dendritic Ephrin results in a bidirectional repulsive Eph forward and Ephrin reverse signal running in both DA1 and VA1d PNs, respectively; thus, they segregate from each other, thereby forming a proper dendritic glomerular boundary. Additional studies may be required to describe the molecular features of the Drosophila Ephrin reverse signal in the future (Anzo, 2017).
When Eph was knocked down, the dendritic spillover phenotype was observed specifically near the DA1 and DL3 glomeruli. Why is the Eph/Ephrin system used to form the dendritic boundary of such specific glomeruli? Among 50 glomeruli, the DA1, DL3, VA1lm, and VL2a glomeruli exhibited high Eph expression during development, holding the line against the other glomeruli by their unique function. Unlike other glomeruli, the DA1, DL3, VA1lm, and VL2a glomeruli receive inputs from the axons of ORNs (Or67d, Or65a, Or47b, and Ir84a, respectively) dedicated to sensing odors related to reproductive behavior, such as pheromones and food-derived odors promoting male courtship behaviors. Among them, Or67d, the primary neuron of the DA1 olfactory circuit, detects Drosophila male-specific pheromone 11 cis-vaccenyl acetate (cVA) and triggers sex-specific courtship behavior in both male and female flies. In addition, the DA1 PNs show sexually dimorphic neural circuitry. The primary neuron of DL3 (Or65a) also responds to cVA when flies are exposed to it for a long period. DL3 olfactory neurons suppress pheromonal activation of DA1 olfactory neurons. Furthermore, as in Drosophila, the pheromone-sensing organs of Manduca sexta (macroglomerular complex [MGC]) and mice (vomeronasal organ [VNO]) express Ephrin, and their adjacent regions express Eph (Anzo, 2017).
Although Drosophila shows an opposite pattern of Eph/Ephrin (Eph in the pheromone-sensing circuit and Ephrin in the adjacent region), the same signaling machinery seems to have a conserved role in glomerular boundary formation across species. Interestingly, the mouse accessory olfactory bulb receiving input from the VNO, the moth MGC, and the Drosophila pheromone sensory glomeruli are all clustered and located dorsally to the other ordinary glomeruli in the mouse main olfactory bulb and the moth/Drosophila ALs, respectively. This conserved anatomical feature also suggests a notion that a unique signaling pathway is playing a role to secure the strict segregation between the pheromone-sensing circuits and the other olfactory circuits. Taken together, it is hypothesized that the reproductive behavior circuit is highly specific and segregated from the others using the Eph/Ephrin signal. Since Eph and Ephrin are both membrane-bound proteins, the signal is activated in a contact-dependent manner. In addition, the bidirectional signal transduction characteristic of the Eph/Ephrin signal system is reasonable for the local dendrodendritic segregation. It is possible that proper segregation in a dendrite level is necessary for building a well-organized neural network, thus allowing the optimal transfer of pheromone-related information to a higher brain center while controlling the courtship behavior (Anzo, 2017).
Formation of functional neural networks requires the coordination of cell surface receptors and downstream signaling cascades, which eventually leads to dynamic remodeling of the cytoskeleton. Although a number of guidance receptors affecting actin cytoskeleton remodeling have been identified, it is relatively unknown how microtubule dynamics are regulated by guidance receptors. This study used Drosophila olfactory projection neurons to study the molecular mechanisms of neuronal morphogenesis. Dendrites of each projection neuron target a single glomerulus of approximately 50 glomeruli in the antennal lobe, and the axons show stereotypical pattern of terminal arborization. In the course of genetic analysis of the dachsous mutant allele (dsUAO71), this study identified a mutation in the tubulin folding cofactor D gene (TBCD) as a background mutation. TBCD is one of five tubulin-folding cofactors required for the formation of alpha- and beta-tubulin heterodimers. Single-cell clones of projection neurons homozygous for the TBCD mutation displayed disruption of microtubules, resulting in ectopic arborization of dendrites, and axon degeneration. Interestingly, overexpression of TBCD also resulted in microtubule disruption and ectopic dendrite arborization, suggesting that an optimum level of TBCD is crucial for in vivo neuronal morphogenesis. It was further found that TBCD physically interacts with the intracellular domain of Down syndrome cell adhesion molecule (Dscam), which is important for neural development and has been implicated in Down syndrome. Genetic analyses revealed that TBCD cooperates with Dscam in vivo. This study may offer new insights into the molecular mechanism underlying the altered neural networks in cognitive disabilities of Down syndrome (Okumura, 2015).
Neural circuits are often remodeled after initial connections are established. The mechanisms by which remodeling occurs, in particular whether and how synaptically connected neurons coordinate their reorganization, are poorly understood. In Drosophila, olfactory projection neurons (PNs) receive input; their dendrites synapse with olfactory receptor neurons in the antennal lobe and relay information to the mushroom body (MB) calyx and lateral horn. Embryonic-born PNs participate in both the larval and adult olfactory circuits. In the larva, these neurons generally innervate a single glomerulus in the antennal lobe and one or two glomerulus-like substructures in the MB calyx. They persist in the adult olfactory circuit and are prespecified by birth order to receive input from a subset of glomeruli distinct from larval-born PNs. Developmental studies indicate that these neurons undergo stereotyped pruning of their dendrites and axon terminal branches locally during early metamorphosis. Electron microscopy analysis reveals that these PNs synapse with MB gamma neurons in the larval calyx and that these synaptic profiles are engulfed by glia during early metamorphosis. As with MB gamma neurons, PN pruning requires cell-autonomous reception of the nuclear hormone ecdysone. Thus, these synaptic partners are independently programmed to prune their dendrites and axons (Marin, 2005).
One of the best-studied examples of neuronal reorganization in an insect brain is the gamma neuron of Drosophila mushroom bodies (MBs). MB gamma neurons are born during embryonic and early larval stages. They send dendrites into the MB calyx and axons into larval medial and dorsal MB axon lobes. During early metamorphosis, gamma neurons prune their larva-specific dendrites and axon branches before re-extending adult-specific processes. What happens to their synaptic partners while MB gamma neurons reorganize their dendrites and axons? In this study, it was shown that a subset of olfactory projection neurons -- the major presynaptic partners of MB gamma neurons -- are also morphologically differentiated to function in both larva and adult. The reorganization of these neurons during metamorphosis is independently controlled by some of the same molecular mechanisms as that of the MB gamma neurons (Marin, 2005).
In the adult fly, odors are detected by olfactory receptors (ORs) on the dendrites of about 1300 olfactory receptor neurons (ORNs) in the antennae and maxillary palps. In general, each ORN appears to express one of ~45 possible OR types, and the axons of all ORNs expressing a given OR converge to one of ~45 stereotypical glomeruli in the antennal lobe (AL), the equivalent of the mammalian olfactory bulb. From there, 150-200 projection neurons (PNs) relay olfactory activity to higher brain centers, the MB calyx and the lateral horn (LH) of the protocerebrum. Systematic clonal analysis using the MARCM method to label single and clonally related clusters of PNs that express the GAL4 driver GH146 revealed that these PNs are prespecified by lineage and birth order to receive input via their dentrites from particular glomeruli in the adult AL. Moreover, each glomerular class of PNs exhibits a characteristic axon branching pattern in the LH, suggesting stereotyped targets in at least one higher olfactory center (Marin, 2005).
The Drosophila larval olfactory system is much smaller and simpler by comparison, shown to consist of only 21 ORNs in the dorsal organ and believed to include ~50 PNs relaying information to the larval MB and LH. Developmental analysis has shown that the PNs born during larval stages exhibit only a single unbranched process from the cell body to the MB calyx until early metamorphosis, when dendrites and axon terminal branches start to elaborate. Thus, larval-born PNs do not participate in the larval olfactory circuit (Marin, 2005).
What, then, is the origin of the relay interneurons that connect the larval AL to higher olfactory centers? Do they contribute to the adult olfactory system as well? This study shows that, in contrast to the larval-born PNs, PNs generated during embryogenesis exhibit morphologically differentiated dendrites and axons in both larva and adult. These neurons prune their processes locally during the first few hours of metamorphosis and later re-extend them to innervate developing adult structures. This pruning process is regulated by ecdysone and TGFß signaling, as has been demonstrated previously for MB gamma neurons. Thus, developmentally programmed remodeling allows these embryonic-born PNs to participate in two distinct olfactory circuits at two different stages in the Drosophila life cycle (Marin, 2005).
The MARCM method allows the labeling of a single neuron, or all neurons born from the same neuroblast, that express a particular GAL4 driver. These studies focus on the ~90 (out of an estimated total 150-200) PNs that express GAL4-GH146. A heatshock-promoter-driven FLP recombinase was used to control the timing of the mitotic recombination that results in labeled MARCM clones. In a previous study (Jefferis, 2004), at least one GAL4-GH146-positive PN was identified that could only be labeled by heatshock-induced mitotic recombination during embryogenesis. This embryonic-born PN specifically targeted its dendrites to glomerulus VA2, one of many glomeruli innervated when labeling the entire population of GH146 PNs, yet never by PN single-cell or neuroblast clones labeled by heatshock during larval stages. This discrepancy in the number of innervated glomeruli suggested that a fraction of adult AL glomeruli were being targeted by a subset of PNs born during embryogenesis (Marin, 2005).
To study the embryonic-born neurons labeled by the GH146 driver, MARCM clones were systematically generated by heatshock induction at embryonic stages. Large anterodorsal neuroblast clones labeled by heatshock early in embryogenesis innervated at least 15 glomeruli not targeted by either the anterodorsal or lateral neuroblast clones labeled by heatshocking newly hatched larvae. MARCM single-cell clones were used to characterize embryonic-born PNs that innervate eight different landmark glomeruli in the adult AL. The gross morphology of these PNs in the adult brain is quite similar to that of the larval-born PNs previously described: each PN generally innervates a single glomerulus in the antennal lobe (distinct from those innervated by larval-born PNs), then sends its axon via the inner antennocerebral tract to display a characteristic terminal branching pattern in the LH according to its glomerular class, along with a number of collaterals in the MB calyx that end in prominent boutons (Marin, 2005).
By comparing the specific glomeruli innervated in each partial anterodorsal neuroblast clone generated by heatshock at different times during embryogenesis, it was ascertained that: (1) these embryonic-born PNs were generated in the order DP1m, VL2p, VA6, VA2, DL5, DM3, VM3 and finally DL6, and (2) every clone labeled by embryonic heatshock included all of the larval-born anterodorsal PNs analyzed in the previous study, indicating that both PN subsets originate from the same neuroblast. Upon generation of the DL6 PN(s), the anterodorsal neuroblast apparently arrests, producing additional projection neurons later only in larval life (as indicated by heatshock-induced labeling of just a single anterodorsal glomerular class, DL1, until about 36 hours after larval hatching) (Marin, 2005).
In summary, embryonic-born PNs look just like larval-born PNs with regard to both their dendritic and axonal projections in the adult brain. Moreover, since their dendrites target a distinct subset of AL glomeruli and their axons exhibit characteristic terminal branching patterns in the LH according to their glomerular classes, these embryonic-born PNs serve to expand the repertoire of odor representation in adults beyond the larval-born PNs previously characterized (Marin, 2005).
Given their early origin, these GH146-positive embryonic-born PNs may participate in the larval olfactory circuit as well. Indeed, examining third instar larval brains reveals that GH146 is strongly expressed in presumptive projection neurons that appear to innervate the larval AL and to send axons up to the MB calyx and larval equivalent of the adult LH. These projections appear to be contributed by about 16 to 18 clustered neurons that are presumably derived from the anterodorsal neuroblast (Marin, 2005).
To examine the morphology and connectivity of these PNs in the larval olfactory system with greater resolution, the MARCM method was used to specifically label PNs generated prior to larval hatching and brains were dissected from wandering third instar larvae. In contrast to the larval-born PNs analyzed in earlier studies (Jefferis, 2004), all anterodorsal embryonic-born PNs exhibited densely branched dendrites in the larval AL and axons with large synaptic structures targeting glomerulus-like subregions in the MB calyx as well as branches in the presumptive LH. The large majority of the anterodorsal embryonic-born PNs each targeted a single glomerulus in the LAL and/or in the MB. In some cases, individual PNs targeted two glomeruli in one or both structures (Marin, 2005).
Several lines of evidence suggest that the embryonic-born PNs observed in the larval olfactory system are the same cells as the PNs that contribute to the much larger and more complex adult circuit. (1) The frequencies of labeled single-cell clones are comparable between the two stages, arguing against the possibilities that embryonic-born PNs are either dying off during metamorphosis or remaining quiescent and undetected through larval life. (2) The numbers of GH146-positive PNs observed at the time of puparium formation and in the adult are similar. (3) Most importantly, each embryonic-born PN undergoes characteristic morphological changes during metamorphosis. Therefore, the PNs labeled by embryonic heatshock are referred to as persistent projection neurons (PPNs). However, at this point, the methods do not allow correlation of specific glomerular classes in larva with those observed later in adulthood (Marin, 2005).
Prior studies have used MB gamma neurons as a model system to study the molecular mechanisms of axon pruning. γ neuron pruning depends on cell-autonomous reception of the steroid hormone ecdysone; single neurons that are homozygous mutant for the ecdysone co-receptor ultraspiracle (usp) in an otherwise heterozygous brain fail to reorganize their processes and retain both dorsal and medial axon lobes in the adult brain. In addition, gamma neurons must upregulate the expression of ecdysone receptor isoform B1 (EcRB1) prior to axon pruning. This upregulation requires TGFß signaling; MB gamma neurons that are mutant for the TGFß/Activin Type I receptor baboon (babo) or its downstream effector mad do not upregulate EcRB1 expression and consequently fail to prune (Marin, 2005 and references therein).
It was asked whether a similar molecular pathway is utilized during PPN reorganization. To ascertain whether the pruning of PPNs is also regulated by ecdysone, EcRB1 expression patterns were analzyed. At puparium formation, only 20 of the ~90 GH146+ projection neurons present were strongly positive for EcRB1. These strongly stained PNs, ~18 of which belonged to the anterodorsal cluster, also had noticeably larger and brighter cell bodies than surrounding PNs, which were probably immature larval-born PNs. Single-cell MARCM clones generated by embryonic heatshock were also strongly positive for EcRB1 at puparium formation. Thus, it is concluded that EcRB1 expression is highly expressed in PPNs at the onset of metamorphosis (Marin, 2005).
Is TGFβ signaling generally required to regulate expression of EcRB1 for neuronal pruning during metamorphosis? MARCM was used to label cells that were homozygous for the strongest baboon allele, baboFd4, in a heterozygous background to test whether PPNs also require TGFß reception for normal pruning. At the wandering third instar stage, PPNs homozygous for baboFd4 appeared to have normal dendritic and axonal projections. However, baboFd4 PPNs failed to show high-level expression of EcRB1 by the onset of puparium formation. This result indicates that, as for the MB gamma neurons, high-level expression of EcRB1 in remodeling PPNs depends on TGFß signaling (Marin, 2005).
Consistent with the loss of EcRB1 expression, baboFd4 PPNs fail to reorganize their processes normally during the first few hours of metamorphosis. For wild-type PPNs at 8 hours APF, approximately 95% of dendrites, 80% of MB calyx processes, and 85% of LH processes are in the final two stages of pruning. However, most of the embryonic-born baboFd4 PPNs still retain dendrites and axons with larval morphology at this time. Dense dendritic processes were visible in the larval AL for 100% of PN clones examined, and only 14% of axon branches in the LH appeared to resemble the final two stages of pruning. The degree of pruning in the calyx was more difficult to estimate, due to the concurrent degeneration of gamma MB neuron dendrites and loss of glomerular organization, but disappearance of synaptic boutons still seemed inhibited (Marin, 2005).
To confirm that this failure to prune resulted from loss of ecdysone signal reception, MARCM was used to label PPNs that were homozygous for a well-characterized mutant allele of the ecdysone co-receptor, usp3. At the wandering third instar stage, usp3 PPNs exhibit normal morphology, and, as expected, EcRB1 was expressed at wild-type levels at the time of puparium formation (Marin, 2005).
However, when these brains were examined at 8 hours APF, a significant defect in dendrite and axon pruning was observed. In the majority of cases, both dendritic densities in the location of the larval antennal lobe and axon branches in the MB calyx and LH had been retained. Taken together, these mosaic experiments suggest that PPN dendritic and axonal pruning require cell-autonomous function of EcRB1/USP, as has been shown previously for MB gamma neurons (Marin, 2005).
What are the consequences for the adult olfactory circuit when larval circuits fail to prune? PPNs homozygous for usp3 or baboFd4 that failed to prune their dendrites and axons during metamorphosis allowed investigation of this question. When examined in adults, wild-type PPN dendrites were confined to a single glomerulus in the adult AL with the exception of the VL2p+ class. Dendrites of single-cell PPN clones homozygous for usp3 generally appeared to target glomeruli in the adult AL appropriate for PPNs; however, ectopic processes in additional areas of the AL, which could be interpreted as persisting larval dendrites, were often present. In a few cases, usp3 PPN dendrites were sparser and less specifically targeted to particular glomeruli, but still remained somewhat confined to certain regions of the AL. Likewise, whereas wild-type PPNs always exhibit terminal swellings on short side branches, about 40% of usp3 PPNs retained larval-like boutons directly on their main trunks in the MB calyx; however, they always had side branches with terminal swellings as well, implying that re-extension and adult-specific outgrowth were not completely impaired. In addition, the main axon trunk often diverted conspicuously from the inner antennocerebral tract in the MB calyx, presumably to maintain contact with the larval boutons. Nearly all usp3 PPN axons exhibited grossly wild-type morphologies in adult LH; only one usp3 PPN axon in the sample failed to enter the LH. In summary, usp3 PPNs display ectopic processes in AL and MB that appear to be due to defects in pruning during early metamorphosis; these pruning defects do not seem to interfere with the growth or even targeting (in the case of AL) of adult-specific processes (Marin, 2005).
In comparison, baboFd4 PPNs exhibited more severe dendritic and axonal phenotypes in the adult brain. In a few cases, these PPNs had targeted an appropriate glomerulus but also featured ectopic processes. More commonly, sparse diffuse processes were observed in the AL that were somewhat localized but did not appear to target any specific glomerulus. Processes also occasionally strayed to arborize outside the ventral AL. In the most severe cases, sparse dendrites were distributed broadly throughout the AL. In the MB calyx, all baboFd4 PPN axons appeared to have retained large larval-like boutons directly on their main trunks, rather than exclusively terminal swellings on short side branches as in wild type; in 64% of cases, there were no MB collaterals with wild-type adult appearance at all. The main axon trunk often diverged dramatically from the inner antennocerebral tract in the MB calyx. Finally, in the LH, the majority of baboFd4 PPNs featured significant aberrations including unusually profuse swellings along the branches, failure to enter the LH and/or failure to elaborate higher order branches in the LH. These phenotypes imply an axon re-extension, pathfinding and/or targeting defect in addition to the impaired pruning observed at 8 hours APF (Marin, 2005).
In summary, both usp3 and baboFd4 PPNs exhibit phenotypes in the adult brain consistent with blockage of pruning during early metamorphosis, including extraglomerular processes in the AL as well as large larval-like boutons on the main trunk and diversion from the inner antennocerebral tract as the axon passes through the MB calyx. However, baboFd4 PPNs also feature more severe phenotypes, particularly a complete lack of glomerular innervation and of adult-like axon collaterals with terminal swellings in the MB calyx, as well as failure to enter the LH and/or to elaborate higher order terminal branches. These latter phenotypes appear to be qualitatively different from those attributable to a simple loss of pruning, suggesting that TGFß signaling via baboon may have an additional role in re-extension and/or adult-specific targeting during metamorphosis (Marin, 2005).
In this study, the PPNs of the Drosophila olfactory system have been shown to play analogous functions in two neural circuits at different life stages. They do so by developmentally programmed disassembly and reassembly of synaptic connections during metamorphosis. The implications of these findings for the larval and adult olfactory systems and to neural circuit reorganization are discussed below (Marin, 2005).
Therefore, PPNs serve as relay interneurons connecting the antennal lobe to the MB calyx and the presumptive LH in larvae, just as previously characterized larval-born projection neurons do in adults. Each PPN generally targets its dendrites to one glomerular substructure in the larval AL, probably receiving input from one of the 21 olfactory receptor neurons of the dorsal organ. From there, the PPN's axon extends to higher brain centers, forming one or two large synaptic structures en passant on its way through the MB calyx to the LH. Electron microscopy studies with genetically encoded markers expressed separately in PPNs or in MB gamma neurons established that PPNs form functional synapses in the larval circuit and that MB gamma neurons are among their postsynaptic partners (Marin, 2005).
This analysis of these PPNs in the adult olfactory circuit confirmed and extended the developmental and wiring logic derived from previous analysis of larval-born PNs. Just like larval-born PNs, embryonic-born PPNs are prespecified to target their dendrites to particular glomeruli according to their birth order. Specifically, most PPNs are derived from the same anterodorsal neuroblast that later gives rise to about half the GH146-positive PNs. Like the larval-born PNs, PPNs exhibit stereotyped terminal arborization patterns in the LH. Interestingly, in the adult AL, PPNs innervate a distinct subset of glomeruli from either their larval-born anterodorsal cousins or the projection neurons generated by the lateral neuroblast. This indicates that, in addition to relaying activity from larva-specific olfactory receptor neurons earlier in development, PPNs expand the olfactory repertoire of the adult circuit (Marin, 2005).
In addition to serving larval-specific functions, one proposed function for larval circuits is to provide a foundation upon which adult circuits can be built. In the case of the olfactory circuit, however, previous analysis indicates that the adult-specific antennal lobes form adjacent to, but spatially distinct from, the larval antennal lobe (Jefferis, 2004). Analysis of PPN remodeling supports the notion that the adult circuit is constructed de novo rather than upon the larval circuit. A developmental timecourse analysis revealed that PPNs prune their dendrites and axon branches during early metamorphosis, so that only the main unbranched process from the cell body to the distal edge of the calyx remains by 12 hours APF. By contrast, the larval-born PNs begin to elaborate dendrites at the onset of puparium formation and restrict their processes to specific regions of the developing AL between 6 and 12 hours APF (Jefferis, 2004). Persistent projection neurons start exhibiting this type of localized dendritic outgrowth in the adjacent but distinct adult AL site only at 18 hours APF, around the time that adult-specific ORN axons arrive but prior to their invasion of the AL. This strongly implies that, far from providing contact-mediated cues for differentiating larval-born PNs, PPNs target glomeruli in the developing AL only after the larval-born PNs have established their dendritic target domains. The finding that PPN-specific glomeruli are intercalated with those targeted by dendrites of larval-born PNs, rather than occupying a spatially segregated domain in the adult antennal lobe, implies complex targeting rules in the establishment of wiring specificity of the adult circuit (Marin, 2005).
The fact that PPNs have clearly identifiable addresses for their dendritic targeting in the adult circuit suggested an interesting question: does assembly of the adult circuit depend on the disassembly of the larval circuit? The data suggest that neuronal reorganization appears to be separable into two at least partially independent events, pruning and re-extension. Even usp3 PPNs whose larva-specific dendrites and axons appear unpruned still exhibit the random fine filopodial extensions characteristic of wild-type neurons at 8-12 hours APF, and moreover target their new dendrites to appropriate adult antennal lobe glomeruli, as well as exhibiting adult-specific axon collaterals in the MB calyx and grossly wild-type terminal branches in the LH (Marin, 2005).
The fact that most usp3 persistent PNs still innervate appropriate glomeruli in the adult antennal lobe and have axons with adult characteristics would suggest that ultraspiracle-mediated execution of ecdysone signaling is required for pruning but not for responding to re-extension and/or targeting cues in the developing brain. However, most baboFd4 PPNs failed to target appropriately in the adult olfactory system. This difference in phenotypes may be due to differential perdurance of wild-type Usp versus Babo protein in single-cell MARCM clones and/or to differences in the severity of the alleles examined, consistent with the observation that baboFd4 PPNs show slightly more homogeneous pruning phenotypes at 8 hours APF. However, usp3 carries a missense mutation that alters an invariant arginine in the DNA-binding domain and blocks MB gamma neuron pruning completely. Thus, the possibility is favored that baboon is required for additional ultraspiracle-independent functions during metamorphosis, in the initiation of pruning, re-extension and/or targeting of adult olfactory structures (Marin, 2005).
An often-overlooked aspect of neural plasticity is the plasticity of neuronal composition, in which the numbers of neurons of particular classes are altered in response to environment and experience. The Drosophila brain features several well-characterized lineages in which a single neuroblast gives rise to multiple neuronal classes in a stereotyped sequence during development. This study has found that in the intrinsic mushroom body neuron lineage, the numbers for each class are highly plastic, depending on the timing of temporal fate transitions and the rate of neuroblast proliferation. For example, mushroom body neuroblast cycling can continue under starvation conditions, uncoupled from temporal fate transitions that depend on extrinsic cues reflecting organismal growth and development. In contrast, the proliferation rates of antennal lobe lineages are closely associated with organismal development, and their temporal fate changes appear to be cell cycle-dependent, such that the same numbers and types of uniglomerular projection neurons innervate the antennal lobe following various perturbations. It is proposed that this surprising difference in plasticity for these brain lineages is adaptive, given their respective roles as parallel processors versus discrete carriers of olfactory information (Lin, 2013).
Taken together, these results suggest that both cell cycle and temporal identity transitions in the AL lineages are dynamically regulated in accordance with organismal development. They are comparably slowed down and delayed upon prolongation of larval development by nutrient deprivation or other manipulations, including PTTH neuron ablation, ultimately generating lineages of unaltered neuronal composition. This further implies that the temporal identity changes in the AL NB lineages are likely to be cell cycle-dependent (Lin, 2013)
This study has found that environmental factors, including
nutrition, sculpt different lineages of the Drosophila olfactory
system to widely varying degrees. The intrinsic MB lineage is
highly plastic, with numbers of each class changing in response to
growth conditions and neuroblast proliferation rates. In contrast,
the adPN and lAL lineages consist of an invariant number of
uniglomerular neurons following similar manipulations, suggesting
that both neuroblast proliferation rates and temporal transitions
are altered in accordance with organismal development. It is
proposed that these differences in plasticity of composition are
be adaptive, ensuring a functional olfactory system under a wide
variety of conditions, yet enhancing olfactory learning and memory
in a resource-scarce environment (Lin, 2013).
Odors are detected by sensory neurons that carry information to the olfactory lobe where they connect to projection neurons and local interneurons in glomeruli: anatomically well-characterized structures that collect, integrate and relay information to higher centers. Recent studies have revealed that the sensitivity of such networks can be modulated by wide-field feedback neurons. The connectivity and function of such feedback neurons are themselves subject to alteration by external cues, such as hormones, stress, or experience. Very little is known about how this class of central neurons changes its anatomical properties to perform functions in altered developmental contexts. A mechanistic understanding of how central neurons change their anatomy to meet new functional requirements will benefit greatly from the establishment of a model preparation where cellular and molecular changes can be examined in an identified central neuron. This study examined a wide-field serotonergic neuron in the Drosophila olfactory pathway and mapped the dramatic changes that it undergoes from larva to adult. Expression of a dominant-negative form of the ecdysterone receptor prevents remodeling. Different transgenic constructs were used to silence neuronal activity, and defects are reported in the morphology of the adult-specific dendritic trees. The branching of the presynaptic axonal arbors is regulated by mechanisms that affect axon growth and retrograde transport. The neuron develops its normal morphology in the absence of sensory input to the antennal lobe, or of the mushroom bodies. However, ablation of its presumptive postsynaptic partners, the projection neurons and/or local interneurons, affects the growth and branching of terminal arbors. These studies establish a cellular system for studying remodeling of a central neuromodulatory feedback neuron and also identify key elements in this process. Understanding the morphogenesis of such neurons, which have been shown in other systems to modulate the sensitivity and directionality of response to odors, links anatomy to the development of olfactory behavior (Singh, 2007).
Changes in the pattern of arborization of a mature neuron can come about as a consequence of removal of its afferent inputs or targets, chronic stress or other environmental inputs, such as delivered during learning or exercise. Many of these changes are effected through the action of growth factors and developmental signals acting in concert with steroid hormones and neuronal activity to modify the cytoskeleton or synaptic properties relevant to an altered functional setting. Metamorphosis in Drosophila (a period during which mature larval neurons are often altered to take on new adult functions) provides a context where the mechanistic underpinnings of such neuronal change can be genetically dissected (Singh, 2007).
This study used a genetic method to mark the serotonin-immunoreactive deutocerebral interneurons (CSDn), recently identified on the basis of serotonin immunoreactivity. While this preparation identifies a central neuron, it also has an important feature that allows the analysis of mechanisms underlying the changes it undergoes during remodeling. This system, because of the random nature of the RN2-FLP action, results in bilateral, unilateral or no excision of the FRT element in the Tub-FRT-CD2-FRT-Gal4 construct in the CSDn. Thus, it was possible to choose and analyze preparations where the CSDn from only one hemisphere was labeled: this facility is vital as it allows the analysis of contralateral and ipsilateral projections of the CSDn, without this being obscured by projections of the neuron from the other hemisphere to the same target sites. The GFP reporter in the RN2-Flp, Tub-FRT-CD2-FRT-Gal4, UAS mCD8-GFP strain is first detected very late in embryogenesis (stage 20), after the neuron has acquired its mature larval pattern. These features thus provide a preparation where an identified central neuron, whose function is known, can be followed and genetically manipulated as it changes its form in response to external and internal cues during metamorphosis (Singh, 2007).
The neuron, present during the larval stages, undergoes well-defined changes during pupation to give rise to a more complex adult architecture. What are the factors that regulate the stereotyped pruning and re-growth of arbors in the CSDn during metamorphosis? The results suggest that the interaction of external factors and autonomous properties (some of which could be identified) establish the homeostasis required during branching and establishment of the adult form (Singh, 2007).
Arbors from the larval neuron are removed by pruning over the first 20 hours of pupation before the adult pattern is elaborated. The EcR-B1 isoform, whose expression is typically seen in neurons that alter their larval form and contribute to the circuitry in the adult, is detected in CSDn. Down-regulating EcR in the CSDn during metamorphosis results in a failure of remodeling and the 'adult' neuron retains a larval morphology. The detailed mechanisms by which EcR signaling acts to bring about sculpting of cell shape are not totally understood and reports on Manduca sexta indicate that steroid-induced modifications in dendritic shape can be regulated by activity-dependent mechanisms (Singh, 2007).
Studies on the cellular and molecular mechanisms of pruning events during metamorphosis could provide valuable insights into understanding of degeneration in higher systems. These events require ubiquitin-mediated proteolysis, and it is known that local activity of caspases is involved in dendritic pruning in an identified sensory neuron. Degeneration of specific branches is followed by migration of glial cells into the site of activity. The role of these glia in bringing about pruning and in clearing debris from the vicinity requires further study (Singh, 2007).
The assembly of complex circuits is dependent on a carefully orchestrated interplay of intrinsic and extrinsic cues. Does activity play a role in determining neuronal shape? Spontaneous and evoked activity in the CSDn were silenced using different methods and changes were observed in the dendritic arbors as well as in presynaptic terminals. The effects on the terminals and dendrites are possibly due to distinct mechanisms and will be discussed separately (Singh, 2007).
The strongest effects on presynaptic terminal branching were produced by expression of TeTxLC, which blocks synaptic release, and a dominant-negative Shi protein, which affects receptor-mediated endocytosis. Apart from blocking neuronal activity by abrogating synaptic vesicle release, both treatments could potentially affect axon growth. Consistent with this is the observation that TeTxLC expression affects re-growth of CSDn terminals during metamorphosis, while pruning occurred normally. Weak anatomical defects have also been described in other, non-modulatory neurons, some of which could be explained by a role in the regulation of levels of cell adhesion molecules (Singh, 2007).
Increases in size and branching pattern of the dendritic trees is a robust effect occurring notably when neuronal activity was silenced by Kir2.1expression. In the third instar larva, expression of TNT-G leads to an increase in dendritic arbors with no significant effect on the presynaptic terminals. Expression using the RN2-Flp, Tub-FRT-CD2-FRT-Gal4, stock initiates in the fully developed larval neuron; hence, the changes in dendritic branches are likely to be a consequence of lack of neuronal activity, rather than a developmental effect. What are the mechanisms by which neuronal activity can alter morphologies of neurons? It has been demonstrated that tetanus toxin expression in motorneurons not only affects its presynaptic release because of cleavage of synaptobrevin, but also alters synaptic input by an as yet unknown mechanism. The finding of altered dendritic morphology supports the possibility that homeostatic alterations occur to compensate for a lack of activity (Singh, 2007).
A large body of data provides evidence for retrograde signaling in the development and consolidation of synapses. The observation of expanded dendritic trees upon expression of a dominant negative form of Glued, while intriguing, is difficult to explain in this light. The changes that were seen are in the dendritic (post-synaptic) field when retrograde transport is blocked cell-autonomously. While this needs further investigation, a possible explanation is that these effects are an indirect consequence of physiological alterations at the presynaptic terminals. Local morphological changes in neurons can be effected by sequestration of proteosomes and other molecules at different regions of the cell in response to activity, which could result in sculpting of cellular architecture due to altered protein composition at different cellular regions (Singh, 2007).
Defects in branching observed by abrogation of vesicle release at the synapse in a serotonergic neuron could implicate this modulator in paracrine or autocrine signaling in regulation of neuronal outgrowth, target selection and synapse formation. Such effects have been demonstrated in the gastropod Helisoma , as well as in Drosophila, where serotonin levels regulate neuronal branching and modulate the development of neuronal varicosities in the central nervous system. In these experiments, no significant changes were detected in the branching pattern of CSDn upon strong reduction of serotonin (and dopamine) using a temperature sensitive allele of dopa decarboxylase. Furthermore, unlike in M. sexta, where afferents are necessary for the formation of glomerular tufts of the serotonergic neuron within the antennal lobe, development of the CSDn occurs normally in the absence of sensory input from the antenna (Singh, 2007).
The olfactory pathway consists of afferent sensory neurons, local integrating neurons and projection neurons. Circuitry for an additional level of integration exists in the atypical projection neurons (aPNs), the antennal posterior superior protocerebral neuron (APSP), the giant symmetric relay interneurons (GSI) and the bilateral ACT relay interneurons (bACT). The architecture as well as the serotonergic nature of the CSDn closely resembles the S1 neuron in M. sexta, which receives input from bilateral projections in the protocerebrum and terminates in the lobe contralateral to the soma to modulate the activity of interneurons. It is proposed that the ipsilateral dendrites receive input from as-yet unidentified neural elements in the antennal lobe, while some axonal arbors are postsynaptic to interneurons in the calyx of the mushroom bodies and the lateral horn. It is speculated that the targets of the terminal arbors are either the PNs or the LNs since their ablation results in a reduction in branching. This architecture, which needs to be confirmed by electron microscopic analysis, provides circuitry for 'top-down' regulation of the primary olfactory center. It seems very likely that the CSDn, like its counterpart in the moth, responds to mechanosensory stimulation, providing an important role in responses to odor stimulation coupled with airflow, as would be expected in insects during flight. The modulatory effects of this large field neuron on its partners in the antennal lobe needs to be investigated by high-resolution functional imaging (Singh, 2007).
This study describes a serotonergic neuron whose anatomy suggests
feedback integration within the antennal lobe of insects. The neuron
undergoes remodeling during pupal life from a simple larval to a
more complex adult pattern. These studies suggest that the
morphology of the dendritic arbors that terminate in the lobe
ipsilateral to the soma is regulated by neuronal activity. The
arborization of terminal arbors depends on vesicle recycling,
endocytosis and Dynein-dependant retrograde transport. These
findings demonstrate a useful identified-neuronal preparation where
developmental mechanisms and remodeling can be studied in the
context of olfactory behavior (Singh, 2007).
The antennal lobe of Drosophila is perhaps one of the best understood neural circuits, because of its well-described anatomical and functional organization and ease of genetic manipulation. Olfactory lobe interneurons - key elements of information processing in this network - are thought to be generated by three identified central brain neuroblasts, all of which generate projection neurons. One of these neuroblasts, located lateral to the antennal lobe, also gives rise to a population of local interneurons, which can either be inhibitory (GABAergic) or excitatory (cholinergic). Recent studies of local interneuron number and diversity suggest that additional populations of this class of neurons exist in the antennal lobe. This implies that other, as yet unidentified, neuroblast lineages may contribute a substantial number of local interneurons to the olfactory circuitry of the antennal lobe. This study identified and characterized a novel glutamatergic local interneuron lineage in the Drosophila antennal lobe. MARCM (mosaic analysis with a repressible cell marker) and dual-MARCM clonal analysis techniques to identify this novel lineage unambiguously, and to characterize interneurons contained in the lineage in terms of structure, neurotransmitter identity, and development. The glutamatergic nature of these interneurons was demonstrated by immunohistochemistry and an enhancer-trap strain was used that reports the expression of the Drosophila vesicular glutamate transporter (DVGLUT). The neuroanatomical features of these local interneurons at single-cell resolution, and the marked diversity in their antennal lobe glomerular innervation patterns was documented. Finally, the development of these dLim-1 and Cut positive interneurons was tracked during larval and pupal stages. This study has identified a novel neuroblast lineage that generates neurons in the antennal lobe of Drosophila. This lineage is remarkably homogeneous in three respects. All of the progeny are local interneurons, which are uniform in their glutamatergic neurotransmitter identity, and form oligoglomerular or multiglomerular innervations within the antennal lobe. The identification of this novel lineage and the elucidation of the innervation patterns of its local interneurons (at single cell resolution) provides a comprehensive cellular framework for emerging studies on the formation and function of potentially excitatory local interactions in the circuitry of the Drosophila antennal lobe (Das, 2011).
Naive Drosophila larvae show vigorous chemotaxis toward many odorants including ethyl acetate (EA). Chemotaxis toward EA is substantially reduced after a 5-min pre-exposure to the odorant and recovers with a half-time of ~20 min. An analogous behavioral decrement can be induced without odorant-receptor activation through channelrhodopsin-based, direct photoexcitation of odorant sensory neurons (OSNs). The neural mechanism of short-term habituation (STH) requires the (1) Rutabaga adenylate cyclase; (2) transmitter release from predominantly GABAergic local interneurons (LNs); (3) GABA-A receptor function in projection neurons (PNs) that receive excitatory inputs from OSNs; and (4) NMDA-receptor function in PNs. These features of STH cannot be explained by simple sensory adaptation and, instead, point to plasticity of olfactory synapses in the antennal lobe as the underlying mechanism. These observations suggest a model in which NMDAR-dependent depression of the OSN-PN synapse and/or NMDAR-dependent facilitation of inhibitory transmission from LNs to PNs contributes substantially to short-term habituation (Larkin, 2010).
Experience-induced plasticity of synapses is believed to be a fundamental mechanism of learning and memory. However, central synaptic changes that underlie memory have not been clearly defined, even for relatively simple nonassociative learning processes such as habituation (Larkin, 2010).
During habituation, unreinforced exposure to a repeated or prolonged stimulus results in a reversible decrease in response to that stimulus. Habituation probably serves as an important building block for more complex cognitive function. By allowing unchanging or irrelevant stimuli to be ignored, it allows cognitive resources to be focused on more salient stimuli (Larkin, 2010 and references therein).
The neural basis of short-term habituation (STH) is best studied in the marine snail, Aplysia californica. Here STH (lasting ~30 min) of the defensive gill-withdrawal reflex in response to tactile stimulation of the siphon is thought to arise from presynaptic depression of transmitter release at sensorimotor synapses. However, even here, presynaptic plasticity may not be cell-autonomous, potentially requiring, for instance, activity of yet-to-be-identified interneurons (Larkin, 2010).
Several forms of habituation have been described in Drosophila and are often shown to require the function of genes that regulate cAMP-dependent forms of associative memory. For instance, habituation of proboscis extension reflex as well as odor-evoked startle reflex in adult Drosophila requires rutabaga (rut)-encoded Ca2+/calmodulin-sensitive adenylyl cyclase. In addition, habituation of the ethanol-induced startle response requires the shaggy/GSK-3 signaling pathway. Despite such pioneering observations, the mechanisms of these various forms of habituation, even whether the primary neuronal changes are purely sensory or involve plasticity of central synapses (involving centrally located interneurons that may integrate various different kinds of modulatory, inhibitory, and excitatory inputs), remain poorly understood (Larkin, 2010).
Recent advances in understanding the circuitry that underlies Drosophila olfactory behavior, as well as the development of new tools to perturb identified neurons in vivo, has opened the opportunity for understanding mechanisms of olfactory habituation at the level of the underlying neural circuitry (Larkin, 2010).
In the larval olfactory system, 21 olfactory sensory neurons (OSNs), each expressing a single odorant receptor (together with the broadly expressed Or83b co-receptor), synapse, respectively, onto 21 cognate projection neurons (PNs) within 21 glomeruli in the larval antennal lobe (AL). Local, predominantly GABAergic interneurons (LNs) synapse widely within the antennal lobe, interlinking different glomeruli. Various neuromodulatory synapses also form on the larval antennal lobe and mushroom body. Thus, odorant-stimulated signals in sensory neurons are processed in the antennal lobe, modulated by motivational or emotional states, and relayed through projection neurons to higher brain centers (Larkin, 2010).
Previous work has shown that in Drosophila larvae, olfactory chemotaxis decreases after odorant pre-exposure. This study shows that this behavioral habituation, alternatively referred to as 'adaptation' by some previous investigators, arises from mechanisms of synaptic plasticity. This study demonstrates that odorant receptor activation is not necessary for olfactory habituation; however, local interneuron activity and projection neuron signaling is necessary. These observations suggest a model in which habituation occurs by a pathway in which NMDA receptors in projection neurons signal depression of OSN-PN synapses and/or facilitation of LN-PN synapses (Larkin, 2010).
Previous studies have not clearly discriminated between peripheral and central mechanisms. Indeed, the term 'adaptation,' better applied to sensory neuron changes such as receptor desensitization, has often been used interchangeably with the term 'habituation', which is usually restricted to behavioral changes arising from central synaptic mechanisms (Larkin, 2010). .
The form of larval olfactory STH characterized in this study displays at least some of the defining behavioral characteristics of habituation. First, there is a behavioral decrement in response to repeated or sustained application of a particular stimulus. Second, STH shows spontaneous recovery with time in the absence of the habituating stimulus. And third, STH is susceptible to dishabituation when habituated larvae are presented with of a strong or noxious stimulus. The property of dishabituation is particularly significant, as an important way of distinguishing between habituation and either fatigue or sensory adaptation. Dishabituation shows that the habituated animal retains the capability to respond and suggests that the attenuated behavioral response arises from some form of active suppression. Thus, the behavioral data suggest (1) that the term 'habituation' may be better used in place of 'adaptation,' while referring to the behavioral phenomenon that was studied; and (2) that STH probably arises from central synaptic mechanisms, rather than sensory neuron adaptation (Larkin, 2010).
Three main lines of data support the conclusion that STH arises from a central synaptic mechanism that resides in the antennal lobe, rather than from adaptation of olfactory receptor signaling in the OSN. First, behavioral decrements similar to STH can be induced by direct depolarization of OSNs, indicating that STH may potentially be induced by processes stimulated by activation action-potential firing in OSNs, independently of olfactory receptor activation. Second, and more striking, STH requires synaptic-vesicle exocytosis from local interneurons during the process of odorant exposure, when STH is being established. This requirement is incompatible with an exclusively sensory mechanism. Third, STH requires the function of NMDA receptors on postsynaptic projection neurons. This last observation also provides a particularly strong argument for a synaptic mechanism, indicating a need for plasticity of OSN and/or LN synapses made onto dendrites of projection neurons in the antennal lobe. Given that OSNs are excitatory and LNs are primarily inhibitory, it appears most likely that NMDAR functions in PNs to depress excitatory OSN-PN synapses and/or to potentiate inhibition by strengthening the LN-PN synapse. It is suggestd that the LN-PN mechanism may be involved because (1) LN transmission seems necessary for both induction and expression of habituation; and (2) the process of dishabituation could be attractively explained as arising from the inhibition of local inhibitory synapses through descending neuromodulation. A requirement for facilitation of the LN-PN synapse would be consistent with previous studies (Sachse, 2007) showing that adult-long-term olfactory habituation is associated with an increase in odor-evoked calcium fluxes in GABAergic processes within the Drosophila antennal lobe (Larkin, 2010).
Based both on experimental and theoretical arguments, a simple model is suggested for short-term olfactory habituation. Since this is a model, no claim is being made to to having ruled out additional major contributing mechanisms, It is suggested that during initial odorant pre-exposure, dendritic NMDA receptors on projection neurons detect and respond to membrane depolarization occurs coincident with transmitter release from LNs. Calcium entry through dendritic NMDA receptors may trigger a local retrograde signal required for facilitation of transmitter release from the LNs. Although existing data do not rule out functions for rutabaga in higher larval brain centers, it is suggested that either the generation of a retrograde signal in PN dendrites or the presynaptic response of LNs to this signal could be dependent on the rut adenylate cyclase. In habituated animals, facilitation of GABA release would reduce odor-evoked projection neuron outputs to higher brain centers, thereby reducing olfactory behavior. As NMDAR signaling would only occur at active glomeruli, this mechanism can account not only for the observed odor selectivity of habituation, but also the instances of cross-habituation (Larkin, 2010).
Such a model also naturally suggests a hypothesis for the mechanism of dishabituation: namely, that dishabituating stimuli cause release of neuromodulators that act to reduce GABA release from local inhibitory synapses (Larkin, 2010).
Given the remarkable similarities in the anatomical organization of insect and mammalian olfactory systems, a significant conservation of olfactory mechanisms would be expected. In rodents, at least two forms of habituation have been described, lasting 2-3 and 30-60 min, respectively: the latter equivalent in timescale to larval STH described in this study. Consistent with a similar underlying mechanism, the more persistent form of olfactory habituation can be blocked by an N-methyl-D-aspartate (NMDA) receptor antagonist in the olfactory bulb, a structure homologous to the insect antennal lobe. Thus, larval STH described in this study has some similarities to a previously characterized form of mammalian olfactory habituation. Analysis of the underlying mechanisms is therefore likely to provide directly transferable insights in mammalian olfaction. The data make the prediction that the activity of mammalian olfactory interneurons, either periglomerular or granule cells, is critical for the establishment and display of at least one timescale of olfactory habituation (Larkin, 2010).
In addition to providing some insight into mechanisms of olfactory habituation in mammals, it possible that circuit mechanisms of larval olfactory habituation are relevant to other forms of behavioral habituation. In at least three previous instances, increased inhibition has been associated with attenuated behavior. For example, habituation of an escape reflex mediated by the lateral giant fibers in the crayfish has been associated with enhanced GABAergic transmission onto giant fibers. Similarly, LTP of inhibitory synapses controlling excitability of the Mauthner cell has been associated with reduced escape behavior in goldfish. Furthermore, ethanol, a potentiator of GABA synapses, has been shown to enhance habituation of a motor pathway in the frog spinal cord. Could these different instances of habituation all involve circuit mechanisms similar to those used in Drosophila larval olfactory behavior (Larkin, 2010)?
In all brain regions, principal/projection neurons are subject to inhibitory feedback modulation and a pathway that has been appreciated as potentially essential for neuronal homeostasis. Potentiation of inhibitory feedback triggered by the pattern of principle cell activation would be predicted to preferentially dampen this particular output pattern. Thus, the circuit mechanism suggest in this study is theoretically generalizable to other and more complex forms of habituation. Further experiments will be required to determine the validity of this very testable hypothesis (Larkin, 2010).
The importance of habituation has been underlined by the fact that deficits in sensory gating and pre-pulse inhibition (PPI), processes with similarities to habituation, have been linked with various neurological problems, including autism and schizophrenia. Indeed, a circuit model for understanding schizophrenia has specifically proposed that altered negative feedback in the hippocampus may underlie both positive and negative symptoms of schizophrenia (Larkin, 2010).
In addition, defects in habituation or habituation-like processes
have been described in Fragile X syndrome and migraines. It has also
been shown to have important effects relating to learning
disabilities, age-related changes in learning, and substance abuse.
If mechanisms of olfactory habituation prove to be general, then
studies of olfactory plasticity may prove relevant for other forms
of cognition as well as for human neurological disease (Larkin,
2010).
Olfactory perception is very individualized in humans and also in Drosophila. The process that individualize olfaction is adaptation that across multiple time scales and mechanisms shape perception and olfactory-guided behaviors. Olfactory adaptation occurs both in the central nervous system and in the periphery. Central adaptation occurs at the level of the circuits that process olfactory inputs from the periphery where it can integrate inputs from other senses, metabolic states, and stress. This study focused on the periphery and how the fast, slow, and persistent (lifelong) adaptation mechanisms in the olfactory sensory neurons individualize the Drosophila olfactory system (Jafari, 2021).
The Drosophila antennal lobe is organized into glomerular compartments, where olfactory receptor neurons synapse onto projection neurons. Projection neuron dendrites also receive input from local neurons, which interconnect glomeruli. This study investigated how activity in this circuit changes over time when sensory afferents are chronically removed in vivo. In the normal circuit, excitatory connections between glomeruli are weak. However, after receptor neuron axons projecting to a subset of glomeruli were chronically severed by removal of antennae, it was found that odor-evoked lateral excitatory input to deafferented projection neurons was potentiated severalfold. This was caused, at least in part, by strengthened electrical coupling from excitatory local neurons onto projection neurons, as well as increased activity in excitatory local neurons. Merely silencing receptor neurons was not sufficient to elicit these changes, implying that severing receptor neuron axons is the relevant signal. When the neuroprotective gene Wallerian degeneration slow (WldS; Hoopfer, 2006) was expressed in receptor neurons before severing their axons, this blocked the induction of plasticity. Because expressing WldS prevents severed axons from recruiting glia, this result suggests a role for glia. Consistent with this, it was found that blocking endocytosis in ensheathing glia blocked the induction of plasticity. In sum, these results reveal a novel injury response whereby severed sensory axons recruit glia, which in turn signal to central neurons to upregulate their activity. By strengthening excitatory interactions between neurons in a deafferented brain region, this mechanism might help boost activity to compensate for lost sensory input (Kazama, 2011).
The results demonstrate that when all the ORN afferents to a subset of glomeruli are removed, excitatory interactions between glomeruli become stronger. As a result, deafferented PNs acquire robust responses to odors. Whereas normal PNs respond selectively to different odor stimuli, deafferented PNs respond nonselectively. This presumably reflects the fact that each excitatory LN (eLN; excitatory input to projection neurons) arborizes in most or all glomeruli. Thus, these PNs likely pool indirect excitatory input from all surviving ORNs (Kazama, 2011).
The key finding of this study is that that removing ORN input causes an upregulation of excitatory connections between glomeruli. Previously, it was shown that overstimulating one ORN type causes an upregulation of inhibitory input to a glomerulus (Sachse, 2007). Both of these phenomena may be seen as forms of compensatory plasticity. Compensatory plasticity also occurs in the mammalian olfactory bulb at several synaptic sites (Kazama, 2011).
Silencing electrical activity in ORNs was not sufficient to induce the same functional changes produced by severing ORN axons. This implies that the trigger is not the loss of electrical activity, but rather a molecular signal that is produced by severed axons. Mis-expressing WldS in ORNs blocks induction, and this implies that WldS suppresses the signal that severed axons produce. Suppressing endocytosis in ensheathing glia also blocks induction. This suggests that the signal produced by severed axons acts on glial receptors that require endocytosis for signal transduction. It is interesting that blocking endocytosis in astrocytes had no effect, because astrocytes interact with neurons in other systems. It is possible that astrocytes are involved in this process, but astrocytic endocytosis is not required (Kazama, 2011).
It is notable that both the manipulations that blocked the induction of plasticity (mis-expressing WldS in ORNs, or blocking endocytosis in ensheathing glia) also block the recruitment of ensheathing glia into deafferented glomeruli after ORNs are removed. This would appear to suggest that the same signal triggers both neural plasticity and morphological changes in glia. However, these signaling cascades clearly diverge: the recruitment of glial membranes to degenerating neurons is blocked by mutating the glial transmembrane receptor draper, whereas draper is not required for the plasticity described in this study. Interestingly, removing only one antenna was not sufficient to induce plasticity in glomerulus VM2 PNs. This manipulation kills half the ORNs that target these PNs. It should be noted that removing both palps kills fourfold fewer ORNs than removing one antenna, and this manipulation also affects fewer glomeruli, yet this was sufficient to induce plasticity in palp PNs. Removing both palps is also sufficient for glial mobilization and phagocytosis in the palp glomeruli (Doherty, 2009). The current results argue that the relevant factor is not the total number of afferents that are killed, but the proportion of live and dead axons in a given glomerulus. However, it also seems that killing all the ORNs that target a single glomerulus is not sufficient. This conclusion arises from the finding that removing the ipsilateral antenna did not produce potentiation in glomerulus V PNs, which receive strictly ipsilateral antennal input. This result implies that some minimum number of glomeruli must be completely deafferented to trigger the described phenomenon (Kazama, 2011).
The results indicate that after some ORNs are chronically removed, several changes occur in the antennal lobe circuit over time. First, depolarization propagates more effectively from eLNs to PNs. This could reflect increased gap junctional conductance from eLNs onto PNs. However, the possibility cannot be excluded that it is the result of a change in the intrinsic properties of eLNs that produces better propagation of voltages from the eLN soma to the site of the eLN-PN gap junctions. In this latter scenario, there would not necessarily be a change in gap junction conductance. Because good voltage clamp in eLNs cannot be achieved, these alternatives could not be evaluated directly, but two pieces of evidence argue for a change in the gap junction itself. First, the gap junction subunit composition of these electrical connections is evidently changed, because it was observed that electrical coupling from eLNs onto PNs is no longer completely dependent on the ShakB.neural subunit. Whereas in normal flies odor-evoked lateral excitation is abolished by the shakB2 mutation, which eliminates ShakB.neural, odor-evoked lateral excitation is not abolished in mutant antennal PNs after chronic antennal removal. Second, no significant change was found in any intrinsic properties of eLNs, including input resistance, resting potential, or excitability (Kazama, 2011).
A second change that occurs in chronically deafferented PNs is that spontaneous membrane potential fluctuations are larger in these PNs compared with acutely deafferented PNs. This may result from the increased input from eLNs onto PNs (Kazama, 2011).
A third change is that odors elicit stronger depolarization in eLNs. The intrinsic excitability of eLNs does not significantly increase, and therefore this change is likely caused by increased synaptic drive to eLNs. This potentiated synaptic drive may originate from PNs: because odor responses in deafferented PNs become larger after the induction of plasticity, and because PNs make chemical as well as electrical synapses onto eLNs, a net increase in the synaptic drive that PNs provide onto eLNs would be expected. In addition, it is possible that ORN-to-eLN synapses are potentiated (Kazama, 2011).
In sum, the net effect of these changes is to produce more robust activity in chronically deafferented PNs, compared with acutely deafferented PNs. These findings also help explain why plasticity is expressed globally rather than locally: if eLNs are responding more robustly to odors, and each eLN innervates all glomeruli, then this increased excitation should propagate across the antennal lobe (Kazama, 2011).
Whereas normal PNs are selective for odor stimuli, the potentiated odor responses of deafferented PNs are comparatively nonspecific. This presumably reflects the fact that each eLN arborizes in most or all glomeruli and so likely pools input from all surviving ORN types. Nevertheless, the odor responses of deafferented PNs may still be useful from the perspective of higher olfactory brain regions. Because acutely deafferented PNs regain normal levels of activity over time, this type of plasticity should tend to restore normal levels of activity in higher olfactory regions. This might help maintain the sensitivity of these regions to sensory signals, or maintain tropic support to these regions (Kazama, 2011).
More broadly, it is speculated that the phenomenon describe in thes study might reflect a general injury response in the Drosophila nervous system, and perhaps also a phenomenon that occurs during normal nervous system development. By triggering the upregulation of specific interactions between surviving neurons following the death of other neurons, this mechanism might help increase the number of neurons that are driven by active afferents. This could be a generally useful adaptation to neuronal death because it should tend to maintain total neural activity within a normal dynamic range (Kazama, 2011).
The reorganization of central sensory representations following changes in sensory input is generally thought to reflect changes in the strength of chemical synapses. The results suggest that central electrical synapses can also be persistently altered following sensory deafferentation. It is well known that neuromodulators can produce short-term changes in the strength of electrical synapses, as illustrated by studies in the vertebrate retina and crustacean stomatogastric ganglion. There are fewer examples of long-term changes in electrical synapse strength, but a growing literature suggests that this may be a fundamental mechanism of neural plasticity (Kazama, 2011).
The reorganization of central sensory representations following sensory deafferentation is sometimes assumed to be triggered by reduced electrical activity, not cell death. However, there is growing evidence that changes in electrical activity may produce synaptic plasticity via signaling pathways that are also linked to injury and inflammation. Thus, changes in electrical activity can produce synaptic plasticity by 'co-opting' signaling systems that are involved in injury responses. The results show that, in the Drosophila antennal lobe, some functional rearrangements following deafferentation can be specific responses to cell death signals, and are not necessarily induced by electrical silencing. In this study, reduced electrical activity was disambiguated from cell death because genetic tools were used to create 'undead' severed axons. The results are reminiscent of studies in vertebrates showing that sensory afferent death can produce changes in target brain regions that are not mimicked by electrical silencing using pharmacological manipulations (Kazama, 2011).
Finally, these findings provide a new window on neural-glial interactions. In mammals, there is good evidence that glia can modulate synaptic transmission and neural excitability. In both mammals and in Drosophila, glia also play important roles following injury. In particular, there are many instances of sensory afferent injury causing morphological changes in glia and glial proliferation in target brain regions . However, it is not entirely clear how such glial responses might affect neuronal physiology and sensory codes in these brain regions. The results illustrate specific cellular and synaptic changes in a sensory circuit that result from glial responses to sensory afferent injury. More broadly, the results illustrate the power of Drosophila as a genetically tractable model for studying neural-glial interactions in vivo (Kazama, 2011).
Trace conditioning is valued as a simple experimental model to assess how the brain associates events that are discrete in time. This study adapted an olfactory trace conditioning procedure in Drosophila by training fruit flies to avoid an odor that is followed by foot shock many seconds later. The molecular underpinnings of the learning are distinct from the well-characterized simultaneous conditioning, where odor and punishment temporally overlap. First, Rutabaga adenylyl cyclase (Rut-AC), a putative molecular coincidence detector vital for simultaneous conditioning, is dispensable in trace conditioning. Second, dominant-negative Rac expression, thought to sustain early labile memory, significantly enhances learning of trace conditioning, but leaves simultaneous conditioning unaffected. It was further shown that targeting Rac inhibition to the mushroom body (MB) but not the antennal lobe (AL) suffices to achieve the enhancement effect. Moreover, the absence of trace conditioning learning in D1 dopamine receptor mutants is rescued by restoration of expression specifically in the adult MB. These results suggest the MB as a crucial neuroanatomical locus for trace conditioning, which may harbor a Rac activity-sensitive olfactory 'sensory buffer' that later converges with the punishment signal carried by dopamine signaling. The distinct molecular signature of trace conditioning revealed in this study should contribute to the understanding of how the brain overcomes a temporal gap in potentially related events (Shuai, 2011).
In trace conditioning, the conditional stimulus (CS) and the unconditional stimulus (US) are separated in time by a stimulus- free interval. This so-called 'trace interval' can last for a fraction of a second in eyeblink conditioning but many seconds in fear conditioning, which poses a challenging question: how does the brain overcome this temporal gap to form the association between the CS and US? Intriguingly, trace conditioning in mammals engages neural substrates fundamentally different from delay conditioning, where the CS precedes but also temporally overlaps with the US. Early evidence comes from lesion studies with experimental animals showing that acquisition of trace conditioning requires intact hippocampal formation and medial prefrontal cortex, whereas delay conditioning can occur even with the entire forebrain removed. Later studies involving human subjects further validate the involvement of different brain circuits in these two conditioning variants and even suggest, more surprisingly, that conscious awareness might be a prerequisite for trace but not delay conditioning. It is then hypothesized that the participation of hippocampus and neocortex, as well as the associated higher cognitive function, is necessary in trace conditioning to maintain a representation of the CS or CS/US contingency so as to bridge the temporal gap. However, little is known about what form this representation takes and how it eventually converges with the US (Shuai, 2011 and references therein).
This study characterized trace conditioning in the fruit fly and used mutant analyses to show that it is distinct from the well-characterized simultaneous conditioning at the molecular level. These data complement the mammalian circuit-level studies and, more importantly, open up a molecular understanding of the internal trace that the brain uses to bridge the temporal gap (Shuai, 2011).
Odor footshock pairing elicits robust learning in fruit flies. The current study adapted this assay to study trace conditioning simply by modifying the timing relationship between the CS+ odor and the US punishment. To mimic the widely used simultaneous conditioning paradigm, CS- presentation is kept at 45 s after the punishment. Single-trial training is sufficient to elicit considerable learning performance; the learning index for OCT and 4-methycyclohexanol (MCH) is ~35 for trace conditioning at a trace interval of 30 s. Although a portion of the score (~10) might be attributed to attraction to the CS- via backward conditioning, the behavioral results clearly indicate a marked ability of fruit flies to associate events that are temporally discrete (Shuai, 2011).
One remarkable finding of the current study is that flies devoid of Rut-AC perform normally in trace conditioning. This result is interesting in view of the belief that dually regulated adenylyl cyclase plays a central role in invertebrate associative learning. The function of Rut-AC is best described as a molecular coincidence detector that is synergistically activated by the CS-evoked calcium entry and the US-evoked G protein-coupled receptor activation. It has been hypothesized that the stimulus-free gap in trace conditioning can be bridged by the temporal integration property of Rut-AC. However, the current results disagree with this hypothesis. The normal or even higher performance of rut-deficient mutants suggests that CS-US association in trace conditioning may recruit separate molecular machineries or occur in a distinct group of neurons. Also pertinent to this study is that cAMP levels in the prefrontal cortex negatively influence working memory performance. Therefore, whereas cAMP signaling is essential for some learning tasks, it is dispensable or even detrimental for others (Shuai, 2011).
Another intriguing finding is that induced expression of dominant-negative Rac enhances the learning of trace but not simultaneous conditioning. Notably, no learning enhancement was observed in a number of simultaneous conditioning variants with altered training parameters, including lowered odor concentration and conditioned intensity discrimination in the current work, as well as reduced shock pulses and lowered shock voltage in a previous report. Thus, the differential effects are not explained by a ceiling effect or other ancillary factors. Trace conditioning testing was performed almost immediately (within 3 min) after the training, rendering a better retention of the acquired associative memory also unlikely. Trace conditioning becomes less efficient as trace interval increases, indicating that an inner trace of the odor gradually degrades with time. It is therefore speculated that inhibition of Rac activity might preserve this transient 'sensory buffer' so as to facilitate trace conditioning. In the learning of simultaneous conditioning, the co-occurrence of odor and shock makes it possible to process the CS and US information automatically, e.g., via simple convergence on coincidence detection molecules like Rut-AC; hence the requirement of an olfactory sensory buffer is superfluous, which explains the lack of enhancement from Rac inhibition. The above speculation is particularly attractive considering a recently established role of Rac in the forgetting of a cold-shock sensitive early associative memory. It appears that the perdurance of two short-lived memory forms, one registered after a passive olfactory experience and lasting tens of seconds and the other registered after an associative reinforcement and lasting several hours, are both sensitive to Rac signaling manipulation (Shuai, 2011).
Drac1(N17) takes effect in the MB, the center for olfactory learning and sensory integration in insects. The localization of the Drac1 (N17) effect, combined with the full rescue of the dDA1 mutant phenotype in the MB, implies a possible trace conditioning model in which the MB bridges the temporal gap by holding a short-term sensory buffer of the odor, which later converges with the reinforcement signal carried by dopamine signaling. In accordance with this model, two recent studies in fruit fly and honey bee found no correlation between trace conditioning behavior and the postodor calcium response patterns in olfactory sensory neurons and projection neurons of the AL. Both studies pointed out the likelihood that the sensory buffer relevant to trace conditioning is in neurons downstream of the AL, most likely in the MB. Nonetheless, the AL may still retain odor information in biochemical signals other than calcium or in shortterm synaptic plasticityThe rapidly evolving molecular imaging techniques in fruit flies may help to delineate the nature of the putative sensory buffer and how it interacts later with a biologically significant stimulus (Shuai, 2011).
Synaptic vesicle secretion requires the assembly of fusogenic SNARE complexes. Consequently proteins that regulate SNARE complex formation can significantly impact synaptic strength. The SNARE binding protein tomosyn has been shown to potently inhibit exocytosis by sequestering SNARE proteins in nonfusogenic complexes. The tomosyn-SNARE interaction is regulated by protein kinase A (PKA), an enzyme implicated in learning and memory, suggesting tomosyn could be an important effector in PKA-dependent synaptic plasticity. This hypothesis was tested in Drosophila, in which the role of the PKA pathway in associative learning has been well established. It was first determined that panneuronal tomosyn knockdown by RNAi enhanced synaptic strength at the Drosophila larval neuromuscular junction, by increasing the evoked response duration. Next memory performance was assayed 3 min (early memory) and 3 h (late memory) after aversive olfactory learning. Whereas early memory was unaffected by tomosyn knockdown, late memory was reduced by 50%. Late memory is a composite of stable and labile components. Further analysis determined that tomosyn was specifically required for the anesthesia-sensitive, labile component, previously shown to require cAMP signaling via PKA in mushroom bodies. Together these data indicate that Tomosyn has a conserved role in the regulation of synaptic transmission and provide behavioral evidence that Tomosyn is involved in a specific component of late associative memory (Chen, 2011).
Synaptic transmission is dependent on the formation of SNARE complexes between the vesicle SNARE synaptobrevin and the plasma membrane SNAREs syntaxin and SNAP-25. SNARE complex assembly produces fusion-competent (primed) vesicles, docked at the plasma membrane. Originally identified as a syntaxin-binding protein, tomosyn has emerged as a negative regulator of secretion by directly competing with synaptobrevin to form nonfusogenic tomosyn SNARE complexes (Fujita, 1998; Hatsuzawa, 2003; Pobbati, 2004). The N terminus of tomosyn also promotes SNARE complex oligomerization, sequestering SNARE monomers required for priming, and impedes the function of the calcium-sensor synaptotagmin. By these means tomosyn is involved in regulating SNARE complex assembly and controlling the size of the readily releasable pool of synaptic vesicles. Evidence suggests that the interaction between tomosyn and the SNARE machinery can be modulated by cAMP-dependent protein kinase A (PKA) phosphorylation of tomosyn, a second messenger cascade previously implicated in several forms of behavioral and synaptic plasticity. This study characterized the synaptic function of Drosophila tomosyn and probed the functional relevance of tomosyn in the regulation of behavioral plasticity (Chen, 2011).
The results demonstrate that tomosyn suppresses synaptic function and is necessary in mushroom body intrinsic neurons specifically for a long-term cAMP-dependent component of associative olfactory learning in Drosophila. The prominent biophysical change observed at the fly NMJ after tomosyn RNAi is a prolonged EJC resulting in an increased total charge transfer, similar to that observed at C. elegans tomosyn mutant synapses. Although the underlying cause of the altered EJC duration in either C. elegans or Drosophila has yet to be determined, one potential explanation is the occurrence of late fusion events possibly resulting from ectopically primed vesicles distal to release sites. This hypothesis is supported by ultrastructural data from C. elegans tomosyn mutants, in which a twofold increase in the number of morphologically docked vesicles was observed, the additional vesicles positioned further from the presynaptic density (Gracheva, 2006). Analyses of priming defective unc-13 and syntaxin C. elegans mutants, in which docked vesicles were found to be greatly reduced, suggest that vesicle docking is a morphological correlate of priming. On the basis of these data, it has been proposed that distally primed vesicles in C. elegans tomosyn mutants exhibit delayed release relative to those close to the presynaptic density, the presumed site of calcium entry, leading to a broadened evoked response (Chen, 2011).
The observed increase in synaptic release at the fly NMJ after tomosyn RNAi adds to a growing body of evidence that tomosyn suppresses synaptic strength. For example, the twofold increase in docked vesicles observed at C. elegans tomosyn mutant synapses correlates with a doubling of the readily releasable pool assessed by applying hyperosmotic saline and corresponds to the enhanced evoked EJC charge integral. The increase in quantal content and reduction in PPD at the fly NMJ after tomosyn RNAi is also consistent with an enhanced primed vesicle pool. Similar conclusions were reached for changes in paired-pulse facilitation at central synapses of mouse tomosyn mutants (Chen, 2011).
The observation that tomosyn knockdown at the fly NMJ results in the addition of mEJCs with slower decay kinetics could also be a manifestation of ectopic vesicle priming. Alternatively, this change in fly mEJCs could reflect a change in fusion pore dynamics in the absence of tomosyn, a possibility given previously observed genetic and/or physical interactions between tomosyn and several key components of the exocytic machinery, including the SNARE proteins synaptotagmin, Munc-13, and Munc-18. Because the presynaptic density is responsible for localizing elements of the vesicle fusion machinery such as UNC-13 and calcium channels, spatial misregulation of vesicle docking in the absence of tomosyn may be related to these changes in fusion properties. However, definitive evidence for ectopically primed vesicles at the fly NMJ after tomosyn RNAi is not yet available, and therefore the cause of the altered evoked response kinetics remains speculative (Chen, 2011).
Evidence indicates that vertebrate tomosyn is a PKA target. Although it cannot yet be definitively establish that tomosyn function is down-regulated by PKA phosphorylation at fly synapses pending the availability of a tomosyn null mutant, the fact that tomosyn RNAi phenocopies the NMJ response to cAMP activation and that these two treatments show nonadditivity supports this notion (Chen, 2011).
On the basis of this analysis of NMJ function, it is predicted that, as in mouse tomosyn mutants, synapses within the fly CNS will experience similar increases in synaptic strength after tomosyn RNAi or cAMP activation. This prediction is supported by the specific ASM aversive odor learning deficit observed in the fly olfactory CNS after tomosyn knockdown in mushroom body Kenyon cells, the site of cAMP-mediated associative memory formation (Chen, 2011).
Drosophila aversive odor learning has long been used to investigate the molecular and cellular mechanisms underlying associative memory formation. In the Drosophila mushroom bodies, neuronal signals representing odor cues and electric shock converge onto type I adenylyl cyclase encoded by rutabaga (rut-AC I) to initiate cAMP signals necessary and sufficient to form engrams underlying associative odor memory. These instructive cAMP signals localize to the Kenyon cells in which presynaptic changes are thought to represent a particular odor memory. Stabilization of aversive odor memory over time requires signals from dorsal-paired medial (DPM) neurons, the putative release sites of amnesiac peptide — the fly homolog to mammalian pituitary adenylate cyclase-activating polypeptide (PACAP) — onto mushroom body Kenyon cells. Amnesiac neuropeptides are known to stimulate cAMP production, whereas the major fly PKA is required from 30 min to 3 h after acquisition to sustain late odor memory. The two distinct components of late odor memory, ASM and ARM, differ in both temporal dynamics and molecular mechanisms. Whereas ARM requires the active zone protein Bruchpilot, ASM is not only tomosyn-dependent, according to the current observations, but also requires synapsin, a conserved PKA phosphorylation target associated with synaptic vesicles. Adult synapsin mutant flies exhibit impaired ASM in aversive odor learning. Furthermore, PKA-dependent phosphorylation of synapsin within Kenyon cells is necessary to support larval appetitive odor learning. Thus, both tomosyn and synapsin are required for the cAMP-dependent ASM phase of associate learning (Chen, 2011).
How might synapsin and tomosyn function together in ASM? Mechanistically, PKA phosphorylation of synapsin is implicated in the mobilization and supply of synaptic vesicles from the reserve pool to the active zone, whereas PKA phosphorylation of tomosyn promotes SNARE complex assembly (Baba, 2005). This suggests that enhanced vesicle delivery and increased priming capacity through PKA regulation of synapsin and tomosyn, respectively, may act in concert to maintain synaptic strength in support of ASM. Because knockdown of either protein disrupts ASM, it seems that both vesicle mobilization and enhanced priming capacity are required for this phase of synaptic plasticity (Chen, 2011).
Several lines of evidence suggest that PKA-dependent modulation of tomosyn function provides a possible molecular mechanism for the transduction of cAMP signaling into synaptic plasticity within the olfactory system underlying ASM. First, at the level of the NMJ, it was shown that tomosyn regulates synaptic strength and that this regulation occludes cAMP-dependent synaptic enhancement. Second, within the olfactory neuronal network, it was demonstrated that tomosyn function is likely required within Kenyon cells to support ASM: the cells that receive instructive signals to initiate cAMP-dependent synaptic changes underlying appropriate behavioral plasticity. Third, synaptic output from Kenyon cells is necessary to support both early and late odor memories. Fourth, DPM signaling onto Kenyon cells is required for late aversive odor memory, and DPM neurons stain positive for the amnesiac peptide, which is known to stimulate cAMP production. Fifth, enhanced synaptic transmission in cultured neurons induced by the vertebrate amnesiac homolog PACAP requires PKA-dependent tomosyn phosphorylation (Baba, 2005). Sixth, postacquisitional PKA activity is necessary for late aversive odor memory and is likely mediated by an A kinase-anchoring protein (AKAP)-bound pool of PKA holoenzymes within Kenyon cells. Finally, biochemical evidence demonstrating that PKA-dependent phosphorylation of tomosyn reduces its affinity for the SNARE machinery suggests a potential mechanistic link between cAMP signaling within Kenyon cells and the up-regulation of synaptic strength (Chen, 2011).
On the basis of this evidence, it is postulated that loss of tomosyn inhibitory function leads to a generalized up-regulation of synaptic strength at Drosophila synapses. In Kenyon cells enhanced synaptic transmission resulting from loss of tomosyn likely occludes cAMP-dependent plasticity. This speculation is supported by the observed occlusion of forskolin-dependent synaptic enhancement at the NMJ after tomosyn RNAi. Similarly, PACAP-induced synaptic plasticity in cultured neurons is occluded when tomosyn is no longer phosphorylatable by PKA (Baba, 2005). It is further speculated that within Kenyon cells the phosphorylation of Drosophila tomosyn is due to postacquisitional, Amnesiac-induced PKA activity. This hypothesis would fit with the observed requirement of AKAP-bound PKA for late but not early ASM. It is thus tempting to speculate that tomosyn phosphorylation is dependent on localized signaling via AKAPs at specific subdomains of Kenyon cells that occur after early ASM is established (Chen, 2011).
The global logic used by the brain for differentially encoding positive and negative experiences remains unknown along with how such experiences are represented by collections of memory traces at the cellular level. This study contrasts the cellular memory traces that form in the dorsal paired medial (DPM) neurons of Drosophila after conditioning flies with odors associated with aversive or appetitive unconditioned stimuli (US). The results show that the appetitive DPM neuron trace is distinguished from the aversive in three fundamental ways: (1) The DPM neurons do not respond to an appetitive US of sucrose by itself, in contrast to their robust response to an aversive US. (2) The appetitive trace persists for twice as long as the aversive trace. (3) The appetitive trace is expressed in both neurite branches of the neuron, rather than being confined to a single branch like the aversive trace. In addition, it was demonstrated that training flies with nonnutritive sugars that elicit a behavioral memory that decays within 24 hr generates, like aversive conditioning, a short-lived and branch-restricted memory trace. These results indicate that the persistence and breadth of the DPM neuron memory trace influences the duration of behavioral memory (Cervantes-Sandoval, 2012).
These results address the perplexing question of how the brain encodes memories of positive or negative value. They show that there is an overlap in the neurons that encode memories of opposite value. An alternative possibility was that appetitive and aversive memory traces might form in nonoverlapping sets of neurons. A second important conclusion is that the cellular changes that occur with learning in these neurons are qualitatively and quantitatively different depending on the valence of the conditioning. The appetitive memory trace forming in the DPM neurons is more persistent than the aversive trace, existing across a time window of ∼150 min after conditioning, and is cell-wide, forming in the two major branches of the DPM neuron that innervate the vertical and horizontal lobes of the MBs. The appetitive memory trace is also dependent on the amnesiac gene product and influenced by the nutritive value of the sugar used for reinforcement. The observations together lead to the major conceptual conclusion that appetitive cellular memory traces form in at least some of the same neurons that encode aversive memories, but they differ in essential features like persistence and cellular expanse (Cervantes-Sandoval, 2012).
Although the molecular mechanisms underlying these differences remain unknown, this study provides compelling evidence that the persistent and cell-wide DPM appetitive memory trace underlies time-stable, appetitive behavioral memory. The simplest model to explain this is that conditioning instills an increase in DPM neuron excitability, for an hour after aversive conditioning and for 2.5 hours after appetitive conditioning. This increase in excitability must translate to increased spontaneous synaptic activity onto follower neurons, presumably the MB neurons, to help stabilize memory. Evidence is provided for this model by synaptic blocking experiments across different time intervals after conditioning and by relating the persistence and spatial extension of the memory trace to the stability of behavioral memory. Training flies with nonnutritive sugars that produce a decaying memory generate a short-lived and branch-restricted trace. When supplemented with a nutritive carbohydrate source, a nonnutritive sugar is capable of engendering a longer-lasting trace along with robust stable behavioral memory. Thus, there exists an intimate relationship between the long-lasting and cell-wide DPM neuron memory trace and stable behavioral memory (Cervantes-Sandoval, 2012).
Attached to the relationship between the persistent and cell-wide DPM neuron memory trace and the marked stability of appetitive behavioral memory is the fly's perception of nutrient value. Sugars like sucrose may provide two types of information that are integrated with the odor CS: sweetness and nutrient value. Sweetness, per se, appears sufficient to induce the short-lived trace and decaying behavioral memory, whereas nutrient value is required for the formation of the extended memory trace and stable behavioral memory. This suggests that the fly assesses the nutrient value of the appetitive US using unknown mechanisms and then passes this assessment onto the DPM neurons to influence the duration of the memory trace (Cervantes-Sandoval, 2012).
Associative brain centers, such as the insect mushroom body, need to represent sensory information in an efficient manner. In Drosophila melanogaster, the Kenyon cells of the mushroom body integrate inputs from a random set of olfactory projection neurons, but some projection neurons-namely those activated by a few ethologically meaningful odors-connect to Kenyon cells more frequently than others. This biased and random connectivity pattern is conceivably advantageous, as it enables the mushroom body to represent a large number of odors as unique activity patterns while prioritizing the representation of a few specific odors. How this connectivity pattern is established remains largely unknown. This study tested whether the mechanisms patterning the connections between Kenyon cells and projection neurons depend on sensory activity or whether they are hardwired. A large number of mushroom body input connections were mapped in partially anosmic flies-flies lacking the obligate odorant co-receptor Orco-and in wild-type flies. Statistical analyses of these datasets reveal that the random and biased connectivity pattern observed between Kenyon cells and projection neurons forms normally in the absence of most olfactory sensory activity. This finding supports the idea that even comparatively subtle, population-level patterns of neuronal connectivity can be encoded by fixed genetic programs and are likely to be the result of evolved prioritization of ecologically and ethologically salient stimuli (Hayashi, 2022).
Animals form and update learned associations between otherwise neutral sensory cues and aversive outcomes (i.e., punishment) to predict and avoid danger in changing environments. When a cue later occurs without punishment, this unexpected omission of aversive outcome is encoded as reward via activation of reward-encoding dopaminergic neurons. How such activation occurs remains unknown. Using real-time in vivo functional imaging, optogenetics, behavioral analysis and synaptic reconstruction from electron microscopy data, this study identified the neural circuit mechanism through which Drosophila reward-encoding dopaminergic neurons are activated when an olfactory cue is unexpectedly no longer paired with electric shock punishment. Reduced activation of punishment-encoding dopaminergic neurons relieves depression of olfactory synaptic inputs to cholinergic neurons. Synaptic excitation by these cholinergic neurons of reward-encoding dopaminergic neurons increases their odor response, thus decreasing aversiveness of the odor. These studies reveal how an excitatory cholinergic relay from punishment- to reward-encoding dopaminergic neurons encodes the absence of punishment as reward, revealing a general circuit motif for updating aversive memories that could be present in mammals (McCurdy, 2021).
This study defines a role of the cAMP intermediate EPAC in
Drosophila aversive odor learning
by means of null epac mutants. Complementation analysis revealed
that EPAC acts downstream from the rutabaga adenylyl cyclase and in
parallel to protein kinase A. By
means of targeted knockdown and genetic rescue, mushroom body Kenyon cells (KCs) were
identified as a necessary and sufficient site of EPAC action.
Mechanistic insights were provided by analyzing acquisition dynamics and
using the 'performance increment' as a means to access the trial-based
sequential organization of odor learning. Thereby it was shown that
versatile cAMP-dependent mechanisms are engaged within a sequential
order that correlate to individual trials of the training session (Richlitzki, 2017).
The cAMP signaling pathway is central to the regulation of plasticity
and can mediate cellular responses via different intermediaries, i.e.,
PKA (protein kinase A), EPACs (exchange proteins directly activated by
cAMP), and CNGs (cyclic nucleotide gated channels). While
the numerous contributions of PKA to the regulation of plasticity have
been described in great detail, the role of EPAC was not
recognized until 1998.
Since then, its operation as a noncanonical cAMP sensor has been proven
in numerous studies, aided by the development of selective cAMP analogs
and/or genetic models that allow discrimination between PKA and EPAC
functions. Epac has been shown to
enhance neurotransmitter release, activate neuronal excitability via Ca2+-dependent
K+-channels, and enhance hippocampal long-term
potentiation and memory consolidation. This study investigated a potential role of Epac
in the Drosophila aversive odor-learning paradigm (Richlitzki, 2017).
This study has distinguish epac-dependent from epac-independent learning by
means of a Drosophila null-epac mutant and used the performance increment
as a means to address the functional disparity of individual training
trials. Disparity impacts on the learning rate suggesting an
evolutionary benefit of alternative cAMP mediators as this provides a
mechanism for transforming rut-derived cAMP signals into behavioral
output following different strategies (Richlitzki, 2017).
Rutabaga adenylyl cyclase (rut-AC1) is supposed to act as
coincidence detector between US- and CS-derived impulses that converge
at the level of KC synapses and consequently induce cAMP-dependent
plasticity within an odor specific matrix of KCs. This KC synapse matrix
is widely accepted as a neuronal representation of learning and thought
of as an engram of an odor memory. Dopaminergic
neurons (DANs) provide the major share of KCs' dopamine-induced cAMP
signals, however KC synapses are not uniform but exhibit different
sensitivities for cAMP. Likewise,
learning is not an instantaneous process but develops over the multiple
trials of a training session. As a consequence, cAMP gain over the time
course of training would not be uniform but effectively determined by
the sensitivity of a particular KC synapse within the odor specific
matrix. This disparity would proceed to the next levels, i.e.,
activation gain of alternative downstream cAMP intermediaries that, in
turn, are unequally sensitive as reflected by characteristic
half-maximal cAMP concentrations (IC50), i.e., IC50 values for PKA ~80
nm; for HCN channels ~ 100 nm; and for EPAC ~ 800 nm. By this design, KCs diversify into high and low
cAMP gain fractions that activate mediators responsive to either high
and/or low cAMP amplitudes at quite different rates. Thereby, a
particular odor-specific KC matrix can interconnect to multiple outputs
via different mechanisms of cAMP-dependent plasticity as its synaptic
elements exhibit disparate hysteresis, i.e., different time-dependent
changes in the cellular cAMP levels (Richlitzki, 2017).
The surprising result that insensitive EPAC recruits early, i.e., during the
second trial of the training session, suggests existence of a fast,
high-amplitude cAMP signal that meets EPAC's thresholds early during
training. Similarly, one has to assume that the efficacy of later
training trials is mediated by a perpetuating low-amplitude signal that
develops with low gain over multiple trials. Given the fact that PKA
acts isogenic to EPAC and null epac mutants show regular learning during
late training trials-that is from the third trial onward-neither of
these intermediates is likely to account for late trial learning. One
plausible mechanism would be HCN channels, i.e., subthreshold,
voltage-gated ion channels that reduce membrane resistance and promote
neuronal firing probability. Within sparsely firing KCs
such channels might stabilize an odor-specific synaptic matrix, i.e.,
the CS-representation, over the 1-min time course of the training cycle
and promote its transfer to mushroom body output neurons (MBONs), the
recognized convergence site for KCs. In contrast, epac has been shown to
enhance neurotransmitter release and/or activated neuronal excitability via different mechanisms (Richlitzki, 2017).
While epac-dependent and independent learning mechanisms clearly
dissociate at the molecular level, their learning rates appear
counter-intuitive as a high-amplitude signal precedes a low-amplitude
one, but both originate from rut-AC1. If one considers the animal's need
to trade off certainty of a prediction against its computation time,
this seemingly counterintuitive design appears deliberate and beneficial
as it holds the possibility of combining both contrarian needs (DasGupta, 2014): First, epac-dependent learning requires a short
computation time, i.e., after two trials, compared with the slow and
cumbersome integration over multiple trials needed for epac-independent
learning. Second, epac-dependent learning is restricted to salient
conditions, i.e., high voltages that represent a serious threat to the
animal's health, while this part of the animal's memory is spared with
the 15 V DC US. In fact, wild-type strains trained with 15
V exhibited similar learning to epac-null mutants trained with 120 V
suggesting that epac amplifies conditioned avoidance under trusted
environmental circumstances (Richlitzki, 2017).
Do training trials clock recurrent computation within the learning
network? How individual training trials are represented within the fly
brain is unclear. However, functional studies have identified DANs as
critical substrates of the US that tightly innervate KCs at the level of
the MBs. In general, DANs and KCs work together with MBONs, the
recognized readout routes of aversive odor memory. Moreover, their anatomy suggests that MBONs serve as critical inter-loops that reiterate the MBs' computational output to DANs, i.e., its major modulatory input: This recurrent connectivity exhibits a
remarkable zonal architecture as dendrites of MBONs tile the length of
KC axons in a nonoverlapping manner, where they meet with dopaminergic
neurons (DANs), the other main innervation of the MB lobes. The DANs
tile the MB lobes in a corresponding manner so that the dendrites of a
particular MBON meet axonal projections of cognate DANs. Moreover,
dendrites of DANs overlap with MBON axons within the MBON projection
zones outside the MBs suggesting that MBONs modulate the activity of
DANs and thereby generate recurrent loops. By this
design MBON activity is dually modulated by DANs, first via a direct
connection, and second via a KC detour that undergoes cAMP-dependent
plasticity. However, further research will be required to understand the
rules by which repetitive trials clock the computation within the
DAN/KC/MBON network (Richlitzki, 2017).
Habituation is the process that enables salience filtering, precipitating perceptual changes that alter the value of environmental stimuli. To discern the neuronal circuits underlying habituation to brief inconsequential stimuli, a novel olfactory habituation paradigm was developed, identifying two distinct phases of the response that engage distinct neuronal circuits. Responsiveness to the continuous odor stimulus is maintained initially, a phase termed habituation latency; it requires Rutabaga Adenylyl-Cyclase-depended neurotransmission from GABAergic Antennal Lobe Interneurons and activation of excitatory Projection Neurons (PNs) and the Mushroom Bodies. In contrast, habituation depends on the inhibitory PNs of the middle Antenno-Cerebral Track, requires inner Antenno-Cerebral Track PN activation and defines a temporally distinct phase. Collectively, these data support the involvement of Lateral Horn excitatory and inhibitory stimulation in habituation. These results provide essential cellular substrates for future analyses of the molecular mechanisms that govern the duration and transition between these distinct temporal habituation phases (Semelidou, 2018).
Drosophila is a premier system for molecular approaches to understand habituation because of its advanced molecular and classical genetics. In fact, it is a well-established model for habituation of various sensory modalities such as taste, vision, mechanosensory and escape responses, reflecting that habituation is apparent in most, if not all, circuits and modalities of the nervous system. However, in most of these paradigms, the circuits engaged to process the stimulus and establish the experimentally measured attenuated behavioral response are unclear. Importantly, the advanced understanding of the Drosophila olfactory circuitry and stimulus processing facilitates exploration of the mechanisms mediating decreased stimulus responsiveness and habituation to inconsequential odors. Such a recently described paradigm of olfactory habituation in Drosophila required 30 min of odor exposure and was mediated entirely by antennal lobe neurons. In contrast, habituation to repetitive 30 s odor pulses required functional Mushroom Bodies, neurons on the central brain also implicated in associative learning and memory in flies (Semelidou, 2018).
To resolve this paradox, this study focused on the early behavioral dynamics of habituation upon continuous odor stimulation. To that end, a novel habituation paradigm was developed and characterized to rather brief continuous odors. The behavioral responses define two distinct phases, an initial phase termed habituation latency, when stimulus responsiveness is maintained, which is followed by a significant response decrement reflecting habituation. Analogous response dynamics have been reported for footshock habituation. In addition, whether these phases engage and are mediated by distinct neuronal circuits was. The results highlight the stimulus duration-dependent activation of specific neuronal subsets and their distinct roles in securing timely habituation latency and habituation induction (Semelidou, 2018).
This study describes a novel olfactory habituation paradigm to brief odor stimuli and operationally defines two distinct phases in the response dynamics. The initial period of ~120 s is termed habituation latency and is characterized by maintenance of responsiveness to the odor. This is followed by manifestation of the habituated response, characterized behaviorally by attenuated osmotaxis. Focusing on the behavioral dynamics early in the process complements previous work olfactory habituation to continuous odor stimulation in Drosophila. A number of criteria differentiate these two paradigms from other types of habituation to olfactory stimuli as discussed below (Semelidou, 2018).
Drosophila habituate equally well to continuous or pulsed olfactory stimuli. This likely reflects the nature of olfactory stimuli, which typically are continuous rather than pulsed. On the other hand, habituation of the startle response to ethanol vapor may specifically require short (30 s) pulses due to its sedative properties and this may also be reflected by the rather long 6 min ITIs compared to the 15 s to 2.5-min intervals used herein for OCT. Short odor pulses are also required for the odor-mediated jump and flight response habituation, suggesting that pulsing may be necessary to evoke the startle response per se (Semelidou, 2018).
An important property shared with all habituation paradigms in Drosophila and other systems is spontaneous recovery of the response. This is another differentiating parameter among habituation paradigms in Drosophila. For the olfactory habituation paradigms, whereas 6 min suffice for spontaneous recovery after 4 and 30 min continuous odor exposure, 15-30 to surprisingly 60 min
are required for recovery in the olfactory startle paradigms. Habituation to mechanosensory stimuli typically also requires shorter spontaneous recovery times, with habituation of the giant fiber-mediated jump-and-flight response requiring a mere 2 min and electric footshock habituation 6 min. Interestingly, other non-mechanosensory habituation paradigms require long spontaneous recovery periods with 30 min for habituation of the proboscis extension reflex (PER), and surprisingly, 2 hr for habituation of odor-induced leg response. It is posited that these differences reflect the engagement of distinct neuronal circuits mediating habituation to these diverse stimuli and the properties and connections of the neuronal types that comprise them (Semelidou, 2018).
Overall, these data suggest that latency and habituation to brief odor exposure involve modulation of lateral horn (LH) output, a neuropil innately encoding response valence to odor stimuli. It is propose dthat habituation latency involves processes that are not permissive to, or actively prevent stimulus devaluation. Latency duration depends on stimulus strength and is consistent with the notion that it is adaptive not to devalue strong, hence potentially important stimuli, expediently. In fact, it is posited that habituation latency serves to facilitate associations with concurrent stimuli, a requirement for associative learning. Shortened latency leading to premature habituation is predicted to compromise associative learning (Semelidou, 2018).
Importantly, maintaining responsiveness early upon odorant exposure requires activity of GABAergic inhibitory neurons, which are essential for lateral inhibition of antennal lobe glomeruli. LN activation appears to prevent saturation by strong continuous odors and hence reduce PN activity. Therefore, shortening habituation latency by blocking GABAergic neurotransmission in the antennal lobe may effectively reduce stimulus intensity, expediting habituation as suggested by the dilute odor experiments. This interpretation is further supported by the decreased habituation latency upon silencing the iACT PNs conveying olfactory signals to the MBs and the LH, but not by the mACT neurons innervating only the LH. Since iACT PNs are mainly excitatory, it appears that response maintenance requires excitatory signaling to the LH and the MBs (Semelidou, 2018).
All MB neuronal types except the γ, are essential for habituation latency. This suggests that at least part of the excitatory signal conveyed by the iACT PNs impinges upon the αβ and α' β' MB neurons, which is consistent with their role in associative learning and the proposal that habituation latency facilitates it. Neurotransmission from the MBs to LH neurons mediating aversive responses likely engages MB output neurons (MBONs), to maintain the valence and intensity of the odor and sustain aversion. Distinct MBONs are known to drive both attraction and aversion to odors and their potentially differential involvement in habituation is currently under investigation (Semelidou, 2018).
Dishabituation results in stimulus value recovery and apparently resets habituation latency. Clearly it requires neurotransmission via the GH146-marked neurons and MBs because silencing these neurons disables dishabituation, consistent with their role in response maintenance. These results lead to the hypothesis that dishabituating stimuli might converge on the MBs and/or iACT, possibly stimulating excitatory neurotransmission to the LH, to reinstate stimulus aversion. This hypothesis is currently under investigation as well (Semelidou, 2018).
In contrast, habituation requires prolonged or repeated exposure to the odorant and functional iACT and mACT PNs converging on the LH. Interestingly, the mainly GABAergic mACT PNs receive input both from the olfactory sensory neurons and the excitatory iACT PNs. Their depolarization also activates the excitatory iACT neurons via direct chemical synapses. This apparent feedback loop may be required for mACT activation after prolonged exposure to aversive odors, since these neurons were reported to respond mainly to attractive stimuli. It is proposed that prolonged aversive odor exposure enhances iACT activation, which in turn leads to habituation, while shorter exposure does not activate the iACT neurons, reflected by their dispensability for habituation latency. Importantly, the mACT innervates the LH downstream of the iACT PNs, providing feedforward inhibition. These characteristics likely underlie the necessary and sufficient role of mACT PNs in habituation upon 4-min odor stimulation. Collectively, these results are consistent with the proposal that mACT activation inhibits the innate LH-mediated avoidance response to the aversive odorant, establishing habituation (see A model of the neuronal subsets underlying (A) Habituation Latency and (B) Habituation, after exposure to aversive stimuli.). However, full mACT activation appears to also require iACT neurotransmission, which if abrogated eliminates habituation but is insufficient to establish it on its own (Semelidou, 2018).
Because the MZ699 Gal4 driver also marks ventrolateral protocerebrum (vlpr) neurons it is possible that they also play a role in habituation. In fact, vlpr neurons function in aversive odor responses, are activated by excitatory iACT PNs, inhibited by the inhibitory PNs, and are afferent to the LH. Thus, they could act in parallel or synergistically to mACT PNs to establish the habituated response. As no specific vlpr driver is available, it is impossible at the moment to address this possibility directly. Briefly then, the current collective results strongly suggest a novel role for the inhibitory PNs innervating the LH, and possibly vlpr neurons, in inhibition of the innate response and habituation. The kinetics of inhibitory projection neuron activation and their output on downstream neurons could serve as a measure of the duration of odor exposure. Upon prolonged exposure, these neurons mediate inhibition of odor avoidance, thus devaluing the stimulus (Semelidou, 2018).
Analysis of the neuronal subsets underlying habituation has focused on aversive odors. However, considering the neuronal clusters involved in the process, it would be relatively safe to assume that the results extend to attractive odor habituation as well. It is possible that the neuronal circuitry comprised of PNs, the LH and MBs may be mediating habituation independently of odor valence. However, specific neuronal clusters may differ in odor valance-dependent activation or inhibition of other circuit components with opposing effects on the behavioral readout. For example, inhibitory PNs (iPNs) mediate attraction by releasing GABA in the LH to inhibit avoidance. If inhibited themselves, the resultant attenuated attraction will likely drive a behavioral output of habituation to an attractive odor (Semelidou, 2018).
In accord with this notion, attractive and aversive odors are represented in different AL glomerular clustersand this valence-dependent organization is preserved into higher brain centers. In fact, the posterior-dorsal LH responds to attractive and its ventral complement to aversive odors, while third order neurons convey information from ventral LH to the vlpr and from the dorsal LH to the superior medial protocerebrum. This organization potentially reflects differential recruitment of these neuronal clusters in habituation to aversive and attractive odors. The circuits involved in habituation to attractive odors and their specific contribution to the process will be the focus of future work (Semelidou, 2018).
Although behaviorally there is significant osmotactic attenuation after both 4 and 30 min aversive odor exposure, the experiments suggest that these represent distinct types of olfactory habituation. Habituation after 4 min of odor exposure does not require the MBs, but rather the projection neurons innervating the LH. Habituation after 30 min of exposure is also independent of MB function, but appears to be entirely mediated by iLNs and reside within the AL. This clear difference suggests that the specific potentiation of inhibitory synapses shown to underlie habituation after 30 min of exposure is not necessary for habituation to the brief 4-min exposure. Additionally, while Rut is required within the iLNs during the latency period upon brief odor exposure, it is surprisingly required within the same neurons for habituation to long odor exposure. Therefore, Rut-driven activity within the iLNs yields opposing time-dependent behavioral outputs in accord with the abovementioned notion that the same circuit components may drive opposing outputs (Semelidou, 2018).
Furthermore, the fact that mechanosensory stimuli are not effective dishabituators after 30 min of odor exposure as they are after 4 min, augments the conclusion these are different types of olfactory habituation and suggests that distinct dishabituators likely recruit different neuronal subsets to modulate the habituated response. Such neuronal circuits and the effect of different dishabituators in response recovery are currently under investigatio (Semelidou, 2018).
Altogether, the results indicate different mechanisms for 4 min and 30 min habituation to aversive odors with the former mediated by the interaction between iPNs, ePNs and their targets in the LH, while the latter is based on the inhibition of ePNs by iLNs at the AL level. However, it is possible that the potentiated PN inhibition would decrease their output to the LH to drive reduced avoidance. This argues that the LH could be involved in the behavioral output indicating habituation after 30 min of OCT exposure as well. An AL-mediated reduction in the perceived intensity or valence of a chronically present odor probably serves an adaptive evolutionary role distinct from short exposure to the same stimulus. In fact, filtering away the chronic odor at the antenna, the first olfactory synaptic station, might facilitate evaluation of additional odors at higher order neurons such as the MBs or the LH (Semelidou, 2018).
Significantly, this interpretation is congruent with timescale habituation in mice, where short-timescale odor habituation is mGluR-dependent and mediated by the anterior piriform cortex while long-timescale habituation requires NMDAR and is mediated by the olfactory bulb. In addition, studies in mice, rats and primates have shown that habituation of the higher order neurons is faster and more prominent than in olfactory bulb neurons. Therefore, temporal and spatial principles for olfactory habituation appear broadly conserved between insects and mammals, despite their evolutionary distance (Semelidou, 2018).
Adjusting behavior to changed environmental contingencies is critical for survival, and reversal learning provides an experimental handle on such cognitive flexibility. This study investigated reversal learning in larval Drosophila. Using odor-taste associations, olfactory reversal learning was established in the appetitive and the aversive domain, using either fructose as a reward or high-concentration sodium chloride as a punishment, respectively. Reversal learning is demonstrated both in differential and in absolute conditioning, in either valence domain. In differential conditioning, the animals are first trained such that an odor A is paired, for example, with the reward whereas odor B is not (A+/B); this is followed by a second training phase with reversed contingencies (A/B+). In absolute conditioning, odor B is omitted, such that the animals are first trained with paired presentations of A and reward, followed by unpaired training in the second training phase. The results reveal "true" reversal learning in that the opposite associative effects of both the first and the second training phase are detectable after reversed-contingency training. In what is a surprisingly quick, one-trial contingency adjustment in the Drosophila larva, the present study establishes a simple and genetically easy accessible study case of cognitive flexibility (Mancini, 2019).
Learning-induced changes in synaptic transmission are often distributed across many neurons and levels of processing in the brain. Therefore, methods to visualize learning-dependent synaptic plasticity across neurons are needed. The fruit fly Drosophila melanogaster represents a particularly favorable model organism to study neuronal circuits underlying learning. The protocol presented in this study demonstrates a way in which the processes underlying the formation of associative olfactory memories, i.e., synaptic activity and their changes, can be monitored in vivo. Using the broad array of genetic tools available in Drosophila, it is possible to specifically express genetically encoded calcium indicators in determined cell populations and even single cells. By fixing a fly in place, and opening the head capsule, it is possible to visualize calcium dynamics in these cells while delivering olfactory stimuli. Additionally, a set-up is demonstrated in which the fly can be subjected, simultaneously, to electric shocks to the body. This provides a system in which flies can undergo classical olfactory conditioning - whereby a previously naive odor is learned to be associated with electric shock punishment - at the same time as the representation of this odor (and other untrained odors) is observed in the brain via two-photon microscopy. The generation of synaptically localized calcium sensors, which enables one to confine the fluorescent calcium signals to pre- or postsynaptic compartments, has been previously reported. Two-photon microscopy provides a way to spatially resolve fine structures. This is exemplified by focusing on neurons integrating information from the mushroom body, a higher-order center of the insect brain. Overall, this protocol provides a method to examine the synaptic connections between neurons whose activity is modulated as a result of olfactory learning (Hancock, 2019).
Learning and memory are basic aspects in neurogenetics as most of the neurological disorders start with dementia or memory loss. Several genes associated with memory formation have been discovered. MicroRNA genes miR-1000 and miR-375 were reported to be associated with neural integration and glucose homeostasis in some insects and vertebrates. However, neuronal function of these genes is yet to be established in D. melanogaster. Possible role of miR-1000 and miR-375 in learning and memory formation in this fly has been explored in the present study. Both appetitive and aversive olfactory conditional learning were tested in the miR-1000 and miR-375 knockout (KO) strains and compared with wild one. Five days old third instar larvae were trained by allowing them to be associated with an odor with reward (fructose) or punishment (salt). Then, the larvae were tested to calculate their preferences to the odor trained with. Learning index (LI) values and larval locomotion speed were calculated for all strains. No significant difference was observed for larval locomotion speed in mutant strains. Knockout strain of miR-1000 showed significant deficiency in both appetitive and aversive memory formation whereas miR-375 KO strain showed a significantly lower response only in appetitive one. The results of the present study indicate important role played by these two genes in forming short-term memory in D. melanogaster (Rahman, 2020).
During associative conditioning, animals learn which sensory cues are predictive for positive or negative conditions. Because sensory cues are encoded by distributed neurons, one has to monitor plasticity across many synapses to capture how learned information is encoded. This study analyzed synaptic boutons of Kenyon cells of the Drosophila mushroom body gamma lobe, a brain structure that mediates olfactory learning. A fluorescent Ca(2+) sensor was expressed in single Kenyon cells so that axonal boutons could be assigned to distinct cells and Ca(2+) could be measured across many animals. Learning induced directed synaptic plasticity in specific compartments along the axons. Moreover, it was shown that odor-evoked Ca(2+) dynamics across boutons decorrelate as a result of associative learning. Information theory indicates that learning renders the stimulus representation more distinct compared with naive stimuli. These data reveal that synaptic boutons rather than cells act as individually modifiable units, and coherence among them is a memory-encoding parameter (Bilz, 2020).
Deciphering how brain circuits, the neurons they consist of, and their synaptic connections acquire and encode learned information is a key task in modern neuroscience. Decades of research have led to current understanding of changes in synaptic transmission as a key neuronal substrate underlying learning and memory formation. Sensory stimuli that can be learned and memorized are encoded in the brain as neuronal activity that is sparsely distributed across ensembles of neurons and levels of processing. Physical changes in synaptic transmission underlying the encoding of a specific memory are, therefore, also distributed across many neurons and synapses. It is assumed that, during learning, synaptic connections between neuronal ensembles that are active during the perception of a stimulus become modified such that their combined activity pattern can be retrieved during memory recall, thereby instructing future behavioral action. The sparsely distributed nature of these memory traces (or engrams) makes it challenging to experimentally determine the rules by which many individual synaptic connections change. It is difficult to monitor plasticity in individual synapses at sufficient resolution and to observe many synapses comprehensively at the same time (Bilz, 2020).
This problem was addressed using the fruit fly Drosophila melanogaster, a key model organism for the analysis of neuronal substrates underlying learning and memory. The system is advantageous because it combines few but often genetically tractable neurons with a behavioral repertoire and neuronal complexity rich enough to allow for conceptual comparison with mammals. In Drosophila, classical olfactory conditioning is a widely used learning paradigm. In this training procedure, animals learn to avoid or approach a specific odor as a conditioned stimulus (CS) when it is temporally paired with a punishing or rewarding unconditional stimulus (US), such as an electric shock or sugar. Odors are detected by ~1,320 olfactory sensory neurons per hemisphere, located on the third antennal segments and maxillary palps, that project to the glomeruli of the antennal lobes, which are the structural and functional analogs of the vertebrate olfactory bulbs. Second-order olfactory projection neurons relay the processed odor information to the lateral horn and the mushroom body (MB) calyx; this structure forms the main sensory input region of the MB, which consists of approximately 2,000-2,500 intrinsic neurons (Kenyon cells [KCs]). At the projection neuron-to-KC synapses, odor information is transformed from highly combinatorial neuronal activity (dense code)-analogous to the situation in the mammalian olfactory bulb-to a nonstereotypic and sparsely distributed pattern of KC activity (sparse code)-similar to the situation in the anterior piriform cortex of mammals. The parallel bundles of KC axons collectively form the MB lobes. The site of coincidence between the CS and US and the synaptic circuitry that underlies associative olfactory learning and short-term memory is confined to the γ lobes, which contain approximately 650 KCs per hemisphere. The γ lobes are divided into five zonal compartments (γ1-γ5), each of which is defined by the dendritic innervations of only one or two MB output neurons (MBONs), whose dendritic trees integrate information across multiple KCs (Bilz, 2020).
MBONs show behavior-instructive properties: optogenetic activation of MBONs that innervate the γ1, γ2, or γ3 compartments induces behavioral attraction toward the light source, whereas optogenetic activation of MBONs that innervate the γ4 and γ5 compartments induces behavioral repulsion from light. In addition, the γ lobes also receive compartmentalized input from dopaminergic neurons (DANs), which exert punishing or rewarding US-signaling properties, similar to the function of DANs in mammals. Dopaminergic neurons that innervate the γ1 and γ2 compartments mediate punishment. In contrast, DANs that innervate the γ4 and γ5 compartments signal reward. Importantly, synaptic plasticity induced by optogenetic stimulation of DANs is presynaptically localized to KCs, but not postsynaptically localized to MBONs. Postsynaptic changes in odor-evoked MBON activity as a result of associative learning or optogenetic activation of DANs have been determined electrophysiologically and by using optical Ca2+ imaging. However, learning-induced presynaptic plasticity in axonal KC synapses has never been directly observed. The sparsely distributed and stochastic nature of odor representations and the density of axonal KC fibers make an analysis of plasticity at the presynaptic level extremely challenging. Thus, the rules by which KC presynapses change in order to convert a high-dimensional sensory code into a low-dimensional, behavior-instructing output remain unclear. To elucidate the changes that KC synapses undergo following associative learning, this study used Ca2+ imaging to visualize synaptic activity in Drosophila at the exact integration point between the CS and US signals (i.e., at the axonal KC boutons) (Bilz, 2020).
This paper quantitatively determined stimulus-evoked Ca2+ dynamics at axonal synaptic boutons within individual KCs and distributed across KCs of the MB. These data unexpectedly revealed that boutons along KC axons are not uniformly activated by odors. Rather, individual boutons, even of the same neurons, show individualized responsiveness. However, boutons located within the same compartments γ2-γ4 showed a more coherent odor tuning, implicating that these compartments act as functional units, the borders of which are likely determined by input neurons, such as DANs. In fact, compartmentalized modulation of subcellular cyclic AMP (cAMP) levels in KCs, driven by input DANs, has been shown. The γ5 compartment represented an exception in that the KC boutons showed less correlated odor-evoked activity, which might underlie the reported finding that γ5 MBONs do not reliably respond to odors. The variability in odor responsiveness between individual boutons of even the same KCs is reminiscent of the plasticity- and rutabaga-dependent individualization of MBONs, which can be interpreted as a reflection of an animal's individual olfactory prior experience. Because MBONs are the direct downstream targets of axonal KC synapses, and dopamine-dependent plasticity has been shown to be presynaptically localized to KC boutons, it is suggested that the variability between boutons might represent the source of individualization of MBON responses. The concept that learning-dependent plasticity is localized to axonal KC presynapses and not to MBON postsynapses is also corroborated by reports that reversibly blocking transmitter release from KCs during training only does not prevent the acquisition of an associative memory (Bilz, 2020).
Mechanistically, the phenomenon of functional individualization of synaptic boutons has been analyzed in motor neurons of the neuromuscular junctions in larval Drosophila. Here, octopamine acts as a neuromodulator that alters cAMP levels in synaptic boutons, similar to the action of dopamine in KCs. The distribution of the phosphodiesterase Dunce located at the peripheral rims of boutons restricts the diffusion of cAMP to individual boutons. Because Dunce is enriched in KCs and is required for proper olfactory learning, future research would be well placed to test whether Dunce mediates functional individualization of synaptic boutons in KCs also. Individualized modulation of synaptic boutons, rather than entire neurons, is also reminiscent of the situation in mammals. Here, dendritic spines have been shown to be selectively modified in the course of learning, implying that synapses and spines represent basal elements of learning and memory formation rather than entire neurons (Poo, 2016; Bilz, 2020).
To analyze how learning modifies the synaptically distributed odor representation, the animals were subjected to an aversive associative training procedure. Previous studies on MBONs have shown that pairing an odor with electric shock or artificial activation of punishment-mediating DANs leads to a depression of the activity of MBONs innervating the γ1 and γ2 compartments. The optogenetic activation of these MBONs confers behavioral attraction of animals toward the light source. The function of the γ3 compartment in associative learning is less clear. However, punitive electric shocks evoke activity in DANs innervating γ1, γ2, and γ3, in contrast to a rewarding sugar stimulus that activates DANs targeting γ4 and γ5. Therefore, the predominant hypothesis in light of the above findings is that the relative activity of compartment-specific MBONs encodes the learned valence of odor stimuli. In agreement with this hypothesis, this study shows that the median Ca2+ response amplitudes across the γ2 and γ3 compartments are reduced after aversive conditioning, homogeneous depression was not observed but bidirectional modulation was observed across these bouton populations. As a novel finding, a complementary effect for the CS− condition was observed; i.e., more boutons showed an increase in activity in the γ4 compartment. It is well established that, in the course of differential olfactory conditioning, the CS− is learned as indicative for the absence of punishment. The finding of opposite effects for CS+ and CS−, both in the direction of changes in Ca2+ activity and different γ lobe compartments (γ2 versus γ4), modifies the prevailing model of associative learning. However, it must also be noted that the current experiments differed from many previously reported approaches in two aspects. First, electric shock punishment was used as an US, in contrast to artificial activation of single DANs. Second, the animals were subjected to a training procedure while they were restrained under a microscope, allowing for a within-animal comparison of before and after training. This approach differs from the comparison of untrained animals with animals 1 h after associative training (Bilz, 2020).
The current findings relate to one aspect of classical conditioning: the learned stimulus representation embodies behavior-instructive properties. Specifically, in the case of aversive olfactory conditioning, it induces repulsion from the odor source. However, a second aspect of associative learning is the 'memory content.' The specific stimulus representation (i.e., odor identity) must be demarcated as outcome predictive from other representations that do not carry any learned valence. The sparse nature of KC odor tuning and the relatively large array of KCs ensures a high degree of odor specificity, although γ-type KCs are less selective compared with α/β and α'/β' KCs. However, odor discriminability of individual KCs cannot be complete; KCs respond in some instances to more than one odorant, such as both the trained CS+ and CS− conditions. This was also the case in some synaptic KC responses to the odorants measured in this study. The degree of overlap between neuronal stimulus representations determines the degree to which a learned response toward one stimulus is generalized to a second stimulus. However, through differential training, flies can learn to disentangle similar odorants and increase their ability to differentiate between them. This phenomenon cannot be explained by gross facilitation or depression of KC presynapses. This study found that association of an odor with punishment caused a strong decorrelation of odor-evoked Ca2+ activity across boutons of most γ lobe compartments, both between and within individual KCs, and independent from valence (aversive punishment and appetitive relief learning). Therefore, overlapping KC boutons can be part of both the CS+ and CS− representations, dependent on correlations with the remaining synapses that encode the respective stimuli. It is suggested that this could represent a mechanism by which synaptic interference between overlapping neuronal assemblies encoding for learned, aversive odors (CS+) and similar odors not predictive for punishment (CS−) may be circumvented. The finding that synaptic boutons show decorrelated activity in response to a trained stimulus suggests that the particular odor representation is also uniquely demarcated from other odor representations. Coding theory suggests that stimulus-specific information is transmitted most efficiently if the units encoding the stimulus are decorrelated, reducing redundancy. Exactly this is quantitatively shown in this study in the gain in entropy through associative training that was found for the synaptic odor representation. This principle is not confined to the MB or insect brains. It has, for example, recently been shown that, in the rat hippocampus, an increased variability in synaptic activity within populations of CA1 neurons as a result of learning increases the information coding ability of this brain region (Bilz, 2020).
Currently clear understanding is lacking of the physiological mechanisms that enable synaptic boutons to correlate or decorrelate Ca2+ activity both temporally and in amplitude, depending on whether the driving stimulus has been trained. Coherent neuronal activity, be it correlations between spike trains or between synaptic Ca2+ transients, is regarded as an emergent property of a neuronal circuit that typically depends on the balance between excitatory and inhibitory input. Recent connectomic studies based on electron microscopic 3D reconstructions of MBs of larval and adult Drosophila have uncovered remarkable microcircuitry complexity at the axonal KC bouton level. For example, groups of KCs are synaptically interconnected with each other, and KC-MBON connections are often confined to Rosetta-like structures indicative of cooperative action of KC outputs. The KC-KC and KC-MBON connections also show electrical coupling through gap junctions. Synchronous, correlated neuronal activity often depends on gap junctions, such as in the olfactory bulb of mammals, in the antennal lobe of insects, or in the mammalian cortex. Thus, it is tempting to speculate that modulation of gap junctions might potentially affect correlative activity of KC boutons as a result of associative training. Regardless of the exact physiological mechanism, the data suggest that correlations at the synaptic circuit level contribute to encoding learned information, thereby combining the concept of a synaptic (rather than cellular) distribution of a memory code with that of correlated neuronal activity as a coding parameter (Bilz, 2020).
In order to represent complex stimuli, principle neurons of associative learning regions receive combinatorial sensory inputs. Density of combinatorial innervation is theorized to determine the number of distinct stimuli that can be represented and distinguished from one another, with sparse innervation thought to optimize the complexity of representations in networks of limited size. How the convergence of combinatorial inputs to principle neurons of associative brain regions is established during development is unknown. This study explored the developmental patterning of sparse olfactory inputs to Kenyon cells of the Drosophila melanogaster mushroom body. By manipulating the ratio between pre- and post-synaptic cells, it was found that postsynaptic Kenyon cells set convergence ratio: Kenyon cells produce fixed distributions of dendritic claws while presynaptic processes are plastic. Moreover, this study showed that sparse odor responses are preserved in mushroom bodies with reduced cellular repertoires, suggesting that developmental specification of convergence ratio allows functional robustness (Elkahlah, 2020).
The environmental stimuli animals encounter on a day-to-day basis are extraordinarily numerous. Olfactory systems have evolved to cope with this diversity by maximizing the chemicals that can be detected, through the amplification of chemosensory receptor gene families, and through combinatorial coding, which expands representation capacity from the number of receptors in the genome to the number of combinations among them. The arthropod mushroom body is a cerebellum-like associative learning structure with a well-understood role in representing sensory stimuli and associating sensory and contextual cues. While mushroom bodies of different insect species process information from a variety of sensory modalities, 90% of Kenyon cell inputs in Drosophila melanogaster are olfactory. The mushroom body of each hemisphere has ~2000 Kenyon cells (KCs), which are two synapses from the sensory periphery. Each olfactory receptor neuron in the antennae of adult flies expresses one or two of 75 olfactory receptor genes encoded in the genome. The axons of neurons expressing the same receptor converge on one of 54 glomeruli in the antennal lobe. Approximately 150 uniglomerular projection neurons (PNs) have dendrites in one of the 54 glomeruli and carry signals about distinct receptor channels to two regions of the protocerebrum, the lateral horn and the mushroom body calyx. PN inputs to the lateral horn are thought to underlie innate behaviors, while inputs to the mushroom body allow flexible learned association of odor stimuli with behavioral context (Elkahlah, 2020).
In the mushroom body calyx, the presynaptic sites of individual olfactory PNs cluster into multi-synaptic boutons, with PNs of different types (innervating different glomeruli) producing consistent, characteristic bouton numbers. Each PN makes 1-20 boutons, and each bouton is wrapped by claws of ~10 KCs, such that each PN sends output to between 10 and 200 of the 2000 KCs. KCs in turn have 3-10 (average of five) claws, which innervate boutons of various PNs. Each KC therefore receives innervation from only a minority of the 54 incoming sensory channels, and different individual KCs receive different and relatively unstructured combinations of inputs. The sets of inputs to individual cells vary across hemispheres and likely across individuals. Associative learning mechanisms operate at KC output synapses, in the mushroom body axonal lobes, to re-weight KC outputs depending on experience and shift animal behavior (Elkahlah, 2020).
The mushroom body is a simplified and experimentally tractable example of an expansion layer, in which a set of sensory inputs is mapped combinatorially onto a much larger set of postsynaptic cells, increasing the dimensionality of sensory representations. Like the diversification of antibodies by V(D)J recombination, the diversification of sensory input combinations across KCs is thought to allow them to represent arbitrary odors, regardless of evolutionary experience. Neurons of many other expansion layers receive similarly few, or sparse, sensory inputs. These include the cerebellum proper, the electric organ of mormyrid fish, the dorsal cochlear nucleus, and the hippocampus. Cerebellar granule cells have an average of four large, claw-shaped dendrites that are innervated by clustered mossy fiber presynaptic sites in mossy fiber rosettes. The similar convergence ratios in the cerebellum and mushroom body (4 or 5 sensory inputs, respectively, per expansion layer cell) are thought to maximize dimensionality of sensory representations by optimizing the tradeoff between stimulus representation, which is maximized when expansion layer neurons receive large combinations of inputs, and stimulus separation, which is maximized when expansion layer neurons receive few inputs. The number of sensory inputs received by expansion layer neurons is thus a crucial parameter in sensory coding. How the density of inputs to expansion layer neurons is developmentally programmed is not understood in any system (Elkahlah, 2020).
Innervation complexity more generally has been studied in the peripheral nervous system and in the developing mammalian cortex. In peripheral sensory neurons, most prominently those of the Drosophila larval body wall, cell-autonomous mechanisms profoundly influence dendritic complexity. However, sensory neurons do not need to coordinate their innervation with presynaptic partners. In the vertebrate peripheral nervous system, including the rabbit ciliary ganglion and vertebrate neuromuscular junction, postsynaptic neurons or muscles are thought to dictate wiring complexity. In contrast, in the developing cortex, extracellular signals including BDNF play a strong role in influencing dendritic complexity, suggesting that presynaptic cells and glia also influence connectivity density. Therefore, while mechanisms acting in both pre- and post-synaptic cells can influence innervation complexity, there is a need to directly compare how pre- and post-synaptic cells influence one another (Elkahlah, 2020).
This study sought to ask how convergence ratio is set in the mushroom body calyx. By bidirectionally varying the populations of pre- and post-synaptic cells, it was possible to make many different mushroom body aberrations. Across these conditions, a consistent pattern of compensations was found: the number of claws per KC remained largely constant, while the number of presynaptic boutons per olfactory PN varied bidirectionally and in response to changes of both the PN and KC populations. It is therefore concluded that in this circuit, connectivity density is set by aspects of KC specification and is accomplished by flexible innervation of the calyx by PNs (Elkahlah, 2020).
Cerebellum-like architectures are found repeatedly in phylogenetically distinct organisms, suggesting that they have broad evolutionary utility. Yet the developmental production of sparseness, a key wiring feature allowing high-dimensional sensory representations, is not understood. This study begins to investigate the development of sparse connectivity in the cerebellum-like associative learning center of insects, the mushroom body. By varying the ratio between presynaptic olfactory PNs and postsynaptic KCs, it was found that connectivity density is set by KCs: KC claw number changes little across a wide range of PN::KC ratios, KC number predicts PN bouton number, and PNs exhibit wide variety in bouton number to satisfy KC demands. This strategy for generating connectivity density would preserve sparseness in KC inputs across developmental time and upon evolutionary changes in cell repertoires and thus maintain the olfactory coding function of the mushroom body over a range of conditions (Elkahlah, 2020).
Implications for development: Different projection neuron to Kenyon cell ratios across developmental stages
For many animals, brain development continues while juveniles are already living freely--searching for food, navigating, and learning about the environment. Developmental transitions in brain structure are particularly stark in holometabolous insects, who build the brain twice. In D. mel, neurons generated during embryonic and early larval stages wire the larval nervous system. These circuits support larval behaviors, while neural stem cells continue to generate additional neurons that will be used to build the adult circuit. In keeping with this, the ratio between PNs and KCs in the larval olfactory circuit is starkly different from the adult: 21 embryonically-born PNs wire to early-born KCs to construct the larval mushroom body . Connections among these populations dissolve in early pupae, and are then re-wired during pupal development, joined by ~100 more larvally-born PNs, and >1000 more KCs per hemisphere that continue to be born until immediately before adult eclosion (Elkahlah, 2020).
The 21 PNs in the early larva connect to ~75 KCs, a 1:3 ratio, while in the adult, ~150 PNs connect to ~2000 KCs, a 1:10 ratio. (Eichler, 2017; Zheng, 2018). This study found that unlike cells in many other systems, including the vertebrate cerebellum, PNs and KCs did not rely on each other for survival signals. This may be due to the constantly changing ratio between these cell types across developmental time. Instead, setting connectivity density cell-autonomously in KCs could allow KCs to obtain the appropriate number of inputs at the different life stages of the animal, when cellular constituents are very different from one another. Similarly, while PN neurogenesis ceases well before PNs and KCs begin to contact one another in the pupa, it is estimated that ~10% of KCs are born after PN:KC synapsis has already initiated. Strict, cell-autonomous dendrite structuring and flexible PN bouton production could together ensure that late-born KCs obtain the inputs appropriate to support coding (Elkahlah, 2020).
Implications for coding: Balancing projection neuron representations across the calyx
Olfactory PNs of different types are specified in a predictable temporal order, have characteristic numbers of boutons, and overlap in their innervation of the calyx. Differences in bouton number across different PNs allow different odor channels to be differentially represented in the calyx and in KC odor responses. Several classes of PNs also differ in number between the sexes. While PNs changed their individual bouton repertoires in response to changes in cell repertoires, this study found that to some extent, the representation level of different PNs in the calyx was preserved. For example, this study shows the effect of reducing KC number on bouton production by the VM6 PN and 42D01 PNs. While each population of PNs reduced individual bouton number in this condition, they retained their typical relative representation. The VM6 PN reduced its boutons from 10 to 5, while the 42D01 PNs decreased their boutons from 4 to 2. Similarly, this study expanded the PN population by inducing ectopic PN neuroblast duplication. In these experiments, amplification of the ventrolateral clone was mainly observed. It was found that individual anterodorsal VM6 cells did not scale down their boutons when the ventrolateral PN clone expanded, but only when VM6 itself was duplicated. Again, this could maintain the relative wild type representations of different odor channels in the calyx. A recent analysis suggests that the spontaneous activity of different ORs correlates with number of boutons representing that odor channel in the calyx. One possible model for how PNs scale to KC numbers while maintaining their relative representations in the calyx is thus that KC number limits total bouton number across all PNs, while allocation of these boutons to individual PNs is determined by activity-based competition among PN types (Elkahlah, 2020).
Implications for coding: Maximizing dimensionality of odor representations
Qualitative aspects of sparse coding in the mushroom body appear robust to severe perturbations to the circuit. Alternative developmental compensatory mechanisms would be much less likely to preserve sparse coding. For example, this study increased the ratio of PNs to KCs in two ways, by increasing the number of PNs and by decreasing the number of KCs. In both cases, PNs dialed down their bouton number, making 25-50% of the boutons they make in wild type. This allowed the KCs to receive their typical number of inputs. If in contrast bouton number was rigid and claw number flexible, in these cases KCs would have expanded their claw production 2-4 fold to innervate all the incoming PN boutons. Individual KCs with for example 20 instead of 5 claws would receive input from ~40% of glomeruli, increasing the overlap in tuning across different KCs and degrading the ability of the network to distinguish different stimuli from one another (Elkahlah, 2020).
In two other cases, this study increased the ratio of KCs to PNs, by increasing the number of KCs and by decreasing the number of PNs. Again, KCs retained their typical claw number. If instead PNs had maintained a static production of boutons while KCs had adjusted their claw production, KCs would receive very few inputs. While increasing the number of inputs per KC is theorized to reduce dimensionality of odor responses by making different KCs more similar to one another, decreasing the number of inputs per KC is theorized to reduce dimensionality by reducing the number of different possible KC input combinations (Litwin-Kumar, 2017). That this sweet spot maximizing dimensionality, ~5 inputs per cell, is programmed into KC identity testifies to the evolutionary importance of maintaining connectivity density in associative brain centers that rely on combinatorial coding (Elkahlah, 2020).
Implications for evolution: The potential for mushroom body function despite perturbations
The olfactory receptors are the largest insect gene family and have been subject to frequent and extreme gains and losses in many clades. Similarly, brain centers devoted to learning are radically different across species, as exemplified by the diversity in KC repertoire across arthropods. In order to acquire a novel olfactory circuit, many different evolutionary changes are required: A new receptor must evolve, an OSN type that uniquely expresses the receptor needs to arise, that OSN needs to synapse onto PNs, and a new PN type and new glomerulus must arise. For these events to accrue over time, each individual change must be compatible with continued circuit function and olfactory behavior. While development of a dedicated circuit that assigns an innate meaning to a newly-detectable odor would require many further changes, the signal could add to fitness immediately through representation in the mushroom body (Elkahlah, 2020).
This study has described two mechanisms of developmental robustness that maintain coherent mushroom body wiring in the face of a broad range of phenotypic alterations. First, it was observed that olfactory PNs can adjust to gain and loss of PNs while maintaining the balance of odor channel representations in the calyx. Plastic development of PN presynaptic sites that makes room for additional players in the repertoire would allow immediate access of evolutionarily expanded PNs to the calyx and the use of their signals for olfactory learning, thus making time for the evolution of hardwired circuits for innate interpretations. Second, this study showed that developmental programs wiring the calyx can accommodate variation in KC number from at least 1/4 to 2-fold the endogenous complement. Again, this flexibility could support continued MB function on the path to the evolution of mushroom body innovations. Future experiments will ask how KC claw number is developmentally programmed, and what mechanisms operate in olfactory PNs to allow them to tailor bouton production to the KC repertoire (Elkahlah, 2020).
Forming long-term memory (LTM) often requires repetitive experience spread over time. Studies in Drosophila suggest aversive olfactory LTM is optimal after spaced training, multiple trials of differential odor conditioning with rest intervals. Memory after spaced training is frequently compared to that after the same number of trials without intervals. This study shows that, after spaced training, flies acquire additional information and form an aversive memory for the shock-paired odor and a slowly emerging and more persistent 'safety-memory' for the explicitly unpaired odor. Safety-memory acquisition requires repetition, order, and spacing of the training trials and relies on triggering specific rewarding dopaminergic neurons. Co-existence of aversive and safety memories is evident as depression of odor-specific responses at different combinations of junctions in the mushroom body output network; combining two outputs appears to signal relative safety. Having complementary aversive and safety memories augments LTM performance after spaced training by making the odor preference more certain (Jacob, 2020).
The gain in memory performance obtained from spacing learning sessions has intrigued scientists for over a century. Early work using Drosophila demonstrated that spaced training produced protein-synthesis-dependent 'aversive LTM', whereas massed training did not. Many subsequent studies have compared memory after spaced training to that following massed training. This study found that flies learn additional safety information for the CS odor when subjected to spaced training. Parallel complementary CS+ aversive and CS approach memories therefore account for the discriminative odor preference observed 24 h after differential spaced training. In contrast, flies only form an avoidance memory for the shock-paired odor when they are mass trained. Surprisingly, radish mutant flies did not form CS+ aversive memory after spaced training, yet their CS memory appeared unaffected. In contrast, CXM feeding abolished CS memory, but CS+ memory was not significantly reduced. If previous operational definitions are used, these data suggest that CS memory is protein-synthesis-dependent LTM, whereas the CS+ component is ARM. It is therefore important to rethink the many prior studies that have assumed they were measuring only avoidance of CS+ after spaced training (Jacob, 2020).
Recording a timeline of performance after spaced training revealed that CS+ avoidance and CS approach memories have a very different dynamic. The CS+ avoidance memory was evident immediately after training, rapidly decayed over 24 h, and was absent at 4 days. In stark contrast, CS approach memory emerged slowly after training and lasted for at least 4 days-a trajectory reminiscent of that of long-term appetitive memory reinforced by nutritious sugar. The discovery that the processes underlying CS+ (ARM) and CS (LTM) memories have different timing, and different anatomical locations, gives the previously reported mechanistic differences an entirely new perspective. The current data suggest that, rather than occurring in the same neurons, ARM and LTM represent each of the odors employed in differential spaced training. They are therefore likely to be represented in unique populations of odor-activated KCs. In addition, different DANs reinforce CS+ ARM and CS LTM at different KC-MBON junctions (see Circuit diagrams of the mushroom body). It follows that, after spaced training, processing of CS+ ARM, which includes the mushroom body-enriched radish encoded Rap GAP, will occur in different KCs and at different KC locations and output synapses than do the molecular mechanisms that underlie protein-synthesis-dependent CS LTM (Jacob, 2020).
The valence of olfactory memories can be reversed from aversive to appetitive if the relative timing of odor and reinforcement is altered during training. If shock, or artificial DAN activation, is presented ~45 s before the odor, flies form an appetitive relief memory for that odor. Experiments with artificial DAN activation suggest that relief learning is represented by dopamine potentiating an MBON's response to the conditioned odor. If spaced training utilized the same relief-from-punishment mechanism as that in Handler (2019), CS approach memory would be coded as potentiation of the same connections as those coding CS+ avoidance as a depression. However, this study observed co-existence of aversive and approach memories at different places in the MBON network. The data instead indicate that CS approach is coded by specific appetitively reinforcing DANs that direct depression of KC outputs onto corresponding MBONs. This study also explicitly tested whether spaced relief training could form an equivalent long-term CS approach memory. These experiments demonstrated that the memory formed differs greatly from that formed after differential spaced training. Most importantly, memory after spaced relief training can be measured immediately but does not persist for 24 h. CS memory after spaced training emerges slowly and persists for at least 4 days. It is therefore proposed that CS approach after spaced training reflects a safety memory for the CS, rather than that the CS has been associated with the cessation of punishment. Relief and safety learning are also different in rodents. It is proposed that the reason massed training does not form CS approach memory is that it lacks a period of safety after each CS presentation (Jacob, 2020).
Aversive LTM performance, after spaced training, is largely considered to rely on αβ KCs and to be retrieved via α2sc (MB-V2) MBONs. However, others have indicated that the network properties are more distributed and that output from γ3, &gamma3β'1- and α3MBONs is required to retrieve aversive LTM. The current work suggests that there are different reasons why blocking these MBONs during testing impairs 24 h memory after spaced training. Consistent with prior work, this study recorded depressed responses to CS+ in α2sc-MBONs 24 h after spaced training. Depression of α2sc-MBON responses is therefore critical if flies are to express CS+ avoidance. This study also observed strong depression of MBON-α3 CS+ responses after spaced training. The role for α3 MBONs has been disputed. At this point it is not possible to reconcile differences between the studies, other than perhaps the number of training trials, strength of reinforcement, and relative hunger state of the flies. It is also noted that many recent studies use robots where flies remain in the same tube for the entire training session. In contrast, earlier studies and the current experiments utilized manual training where flies are transferred from the training chamber between trials. Nevertheless, the current data suggest that α2sc- and α3- MBONs house plasticity relevant for expression of CS+ aversive memory (Jacob, 2020).
Bouzaiane (2015) reported that MBON-β2mp and MBON-γ5β'2α (M4/6) are not required for LTM retrieval after spaced training. However, this study found that appropriately ordered CS+/CS spaced trials depressed responses to CS in β' 2mp-MBONs. In addition, this study found that PAM-b' 2mp DANs are required for the formation of CS approach memory. The current results therefore indicate a specific role for the β' 2mp subcompartment of the β' 2 MB zone and that MBON-β' 2mp plasticity is required to express CS approach memory (Jacob, 2020).
The negative sign of odor response plasticity of α2sc-, α3-, and β2mp-MBONs makes intuitive sense with the known valence of these pathways. Responses to CS+ in approach-directing α2sc- and α3- MBONs were depressed, which would favor odor avoidance. In contrast, depressing responses to CS to avoidance-directing β'2mp-MBONs should promote odor approach (Jacob, 2020).
This study also discovered roles for PAM-γ3 and PAM-β'1 DANs and recorded traces of both CS+ and CS memory in the corresponding γ3,γ3b'1-MBONs. MBON dendrites in the γ3 compartment showed a decreased response to the CS+, irrespective of the order of CS+ and CS in the training trials, consistent with the rules of forming aversive CS+ memory. In contrast, CS responses were decreased in the β'1 tuft of γ3β'1 MBON dendrites, but only if flies were trained with CS+ and then CS, in that order. Plasticity in β'1 of the γ3β'1 MBON therefore followed the order rule observed for conditioning CS approach behavior. Interestingly, recording in the axons of g3 and g3b01 MBONs suggested that CS+ and CS plasticity cancel each other out. Unfortunately, the split-GAL4 used for driving GCaMP expression in g3b01 MBONs also labels g3 MBONs. Therefore, although only the γ3β'1 MBONs have a dendrite in both γ3 and β'1 compartments, it is not possible at this stage to be certain that γ3β'1 MBONs alone integrate CS+ and CS memory traces (Jacob, 2020).
To decipher the relative role of γ3 and β'1 plasticity, this study individually blocked output from PAM-γ3 and PAM-β'1 DANs during training and tested the resulting memories. Behavioral observations after the PAM-γ3 block were particularly revealing. PAM-γ3 DANs respond to shock, and their forced activation reinforces aversive memories. However, blocking PAM-γ3 DANs during spaced training did not impair CS+ avoidance and instead impaired CS approach when flies were tested with CS versus a novel odor. A CS memory defect was also observed when the appetitively reinforcing PAM β'1 DANs were blocked during training, although this manipulation also impaired CS+ versus CS performance. Lastly, blocking the γ3, γ3β'1-MBONs during testing selectively impaired expression of CS but not CS+ memory. It is therefore proposed that γ3β'1 MBONs integrate the γ3 CS+ danger and β'1 CS safety plasticity to compute a relative safety signal. The importance of this is only obvious if the γ3,γ3β'1-MBONs are blocked during testing or remove aversive CS+ plasticity in γ3 and thereby reveal the behavioral consequence of unopposed CS plasticity in the β'1 region of γ3β'1 MBONs. Since MBON-γ3 and MBON-γ3β'1 are GABAergic, spaced training sequentially alters the level of CS+ and CS driven inhibition that is imposed on their downstream target neurons (Jacob, 2020).
The results of this study demonstrate that DANs reinforce the delayed recognition of safety. Formation of CS approach memory requires appetitively reinforcing PAM-β'2mp and PAM-β'1 DANs and, surprisingly, aversively reinforcing PAM-γ3 DANs. As noted above, PAM-γ3 DANs most likely provide an aversive teaching signal that directs CS+ plasticity in the γ3 region of MBON-γ3β'1 dendrites. Blocking output from PAM-β'2mp, PAM-β'1, or PAM-γ3 DANs, which are presumably responsible for each part of the LTM-correlated plasticity, reveals they are required for the formation of CS approach memories during training. Blocking most PAM DANs further localized an essential role during CS presentation in each spaced training trial, suggesting that safety-memory formation is driven by CS odor. However, safety-memory formation also requires that each CS+ exposure precedes each CS exposure in each training trial. Therefore, PAM DANs also have to somehow register a temporally locked negatively reinforced CS+ reference to be able to classify the following CS as safe. Lastly, repetition is a necessary element of triggering DANs to code safety. Imaging of the activity of appetitively reinforcing PAM-β2mp and PAM-β'1 DANs during and after training suggests they gradually acquire the capacity to reinforce CS approach memory across differential spaced-training trial repetitions. Both PAM-β'2mp and PAM-β'1 DANs exhibited an increased activation by CS odor, relative to the CS+, over consecutive training trials, and this difference was particularly clear when activity after the sixth training trial was compared to activity before training. In addition, the shock responsiveness of PAM-β2mp appeared to diminish over time. It is proposed that over repetitive trials the CS odor becomes the trigger that activates PAM-β2mp and PAM-β'1 DANs (Jacob, 2020).
It is conceivable that formation of long-term CS+ and CS memories is orchestrated by aversive reinforcement signals provided by the PPL1-γ1pedc (MP1) and PPL1-γ2α'1 (MV1) DANs in each shock-paired CS+ trial. PPL1-γ1pedc DANs code aversive learning by depressing odor-specific input to feedforward GABAergic g1pedc>a;αβ (MVP2) MBONs. Although MVP2 output is only required for the expression of short-term aversive memory, the plasticity remains for several hours. Each shock-reinforced odor trial therefore changes the state of the rest of the MBON and DAN network for subsequent exposures and reinforced trials. This has been proposed to release PPL1- α'2α2 DANs so they can reinforce LTM at the KC-MBON- α2sc junction. A similar release from inhibition of PPL1-α3, PAM-β'2mp, and PAM-β'1 DANs could account for spaced-training-driven plasticity at MBON-α3 and prime the PAM-β'2mp and PAM-β'1 to reinforce the CS memory (Jacob, 2020).
However, the data instead suggest that plasticity of the GABAergic γ3β'1 MBONs is essential for the formation of safety memory. Whereas blocking all PPL1 DANs abolished CS+ memory, CS memory was unaffected by this manipulation. In contrast, blocking shock-activated PAM-γ3 DANs during training selectively impaired the formation of CS memory. It is therefore proposed that spaced-training-evoked PAM-γ3 DAN activity cumulatively depresses CS+ driven activity of γ3β'1 MBONs, and this releases the PAM-β'1 and PAM- β2mp DANs from inhibition to reinforce CS memory. Such a model potentially explains the required relationship between CS+ and CS memories, the need for trial repetition, and the relative increase in the responses of these DANs to CS with each training trial. Although the results do not provide an explanation for the optimal 15 min ITI (or proposed period of safety), prior studies have suggested that protein-synthesis-dependent LTM formation requires the timing of consecutive spaced training trials to coincide with the peak of training-induced MAPK activity in KCs (Jacob, 2020).
Reinforcing PAM DANs have also been implicated in memory formation with sugar, water, and alcohol reward, with relative shock, with the absence of expected shock, and after courtship. In addition, they provide control of state-dependent memory expression and unlearned behavioral responses to volatile cues. In some cases, these processes clearly involve different DANs, whereas in others they appear to involve DANs that innervate the same MB compartments. More refined tools, connectomics, and experiments should help reveal the full extent of functional heterogeneity (Jacob, 2020).
Fly behavior has previously been shown to depend on the addition of supporting or conflicting experience. When differentially conditioned by the pairing of one odor with shock and the other with sugar, flies show additive initial performance compared to that observed if only one of the two odors is reinforced. This situation resembles that described in this study after spaced training except that the second odor is explicitly unpaired, and additive performance emerges from complementary LTM. With the benefit of retrospect, it makes intuitive sense that over repetitive spaced trials flies learn 'where the punishment is and where it is not.' These parallel memories make it easier for flies to distinguish between the two odors when tested together (Jacob, 2020).
In contrast, flies simultaneously form parallel competing memories when trained with bitter-tainted sugar, and their performance switches from aversion to approach over time, as dictated by the superior persistence of the nutrient-dependent sugar memory. A similar time-dependent behavioral transition is evident when flies are trained with alcohol reinforcement. A competition between memories of opposing valence also underlies the extinction of both appetitive and aversive memories. However, opposing extinction memories are sequentially formed and are reinforced by the absence of an expected outcome, rather than explicit pairing. In these cases, forming parallel memories reduces the certainty of odor choice (Jacob, 2020).
Together, these studies suggest that forming parallel memories in different places is a general MBON network feature that allows flies to summate experience over time to optimize the expression of learned behavior (Jacob, 2020).
Associative learning allows animals to establish links between stimuli based on their concomitance. In the case of Pavlovian conditioning, a single stimulus A (the conditional stimulus, CS) is reinforced unambiguously with an unconditional stimulus (US) eliciting an innate response. This conditioning constitutes an 'elemental' association to elicit a learnt response from A(+) without US presentation after learning. However, associative learning may involve a 'complex' CS composed of several components. In that case, the compound may predict a different outcome than the components taken separately, leading to ambiguity and requiring the animal to perform so-called non-elemental discrimination. This study focussed on such a non-elemental task, the negative patterning (NP) problem, and provides the first evidence of NP solving in Drosophila. Drosophila were shown to learn to discriminate a simple component (A or B) associated with electric shocks (+) from an odour mixture composed either partly (called 'feature-negative discrimination' A(+) versus AB(-)) or entirely (called 'NP' A(+)B(+) versus AB(-)) of the shock-associated components. Furthermore, this study shows that conditioning repetition results in a transition from an elemental to a configural representation of the mixture required to solve the NP task, highlighting the cognitive flexibility of Drosophila (Durrieu, 2020).
It has been shown that during odor plume navigation, walking Drosophila melanogaster bias their motion upwind in response to both the frequency of their encounters with the odor, and the intermittency of the odor signal, which this study defines to be the fraction of time the signal is above a detection threshold. This study combined and simplified previous mathematical models that recapitulated these data to investigate the benefits of sensing both of these temporal features, and how these benefits depend on the spatiotemporal statistics of the odor plume. Through agent-based simulations, this study found that navigators that only use frequency or intermittency perform well in some environments - achieving maximal performance when gains are near those inferred from experiment - but fail in others. Robust performance across diverse environments requires both temporal modalities. However, a steep tradeoff was found when using both sensors simultaneously, suggesting a strong benefit to modulating how much each sensor is weighted, rather than using both in a fixed combination across plumes. Finally, it was shown that the circuitry of the Drosophila olfactory periphery naturally enables simultaneous intermittency and frequency sensing, enhancing robust navigation through a diversity of odor environments. Together, these results suggest that the first stage of olfactory processing selects and encodes temporal features of odor signals critical to real-world navigation tasks (Jayaram, 2022).
To navigate towards a food source, animals frequently combine odor cues about source identity with wind direction cues about source location. Where and how these two cues are integrated to support navigation is unclear. This study describes a pathway to the Drosophila fan-shaped body that encodes attractive odor and promotes upwind navigation. This study showed that neurons throughout this pathway encode odor, but not wind direction. Using connectomics, fan-shaped body local neurons called hΔC that receive input from this odor pathway and a previously described wind pathway. hΔC neurons exhibit odor-gated, wind direction-tuned activity, that sparse activation of h∆C neurons promotes navigation in a reproducible direction, and that hΔC activity is required for persistent upwind orientation during odor. Based on connectome data, a computational model was developed showing how hΔC activity can promote navigation towards a goal such as an upwind odor source. The results suggest that odor and wind cues are processed by separate pathways and integrated within the fan-shaped body to support goal-directed navigation (Matheson, 2022).
Animals form sensory associations and store them as memories to guide behavioral decisions. Although unimodal learning has been studied extensively in insects, it is important to explore sensory cues in combination because most behaviors require multimodal inputs. This study optimized the T-maze to employ both visual and olfactory cues in a classical aversive learning paradigm in Drosophila melanogaster. In contrast to unimodal training, bimodal training evoked a significant short-term visual memory after a single training trial. Interestingly, the same protocol did not enhance short-term olfactory memory and even had a negative impact. However, compromised long-lasting olfactory memory significantly improved after bimodal training. This study demonstrates that the effect of bimodal integration on learning is not always beneficial and is conditional upon the formed memory strengths.It is postulated that flies utilize information on a need-to basis: bimodal training augments weakly formed memories while stronger associations are impacted differently (Thiagarajan, 2022).
Learning and memory storage is a complex process that has proven challenging to tackle. It is likely that, in nature, the instructive value of reinforcing experiences is acquired rather than innate. The association between seemingly neutral stimuli increases the gamut of possibilities to create meaningful associations and the predictive power of moment-by-moment experiences. This study reports physiological and behavioral evidence of olfactory unimodal sensory preconditioning in fruit flies. The presentation of a pair of odors (S1 and S2) before one of them (S1) is associated with electric shocks elicits a conditional response not only to the trained odor (S1) but to the odor previously paired with it (S2). This occurs even if the S2 odor was never presented in contiguity with the aversive stimulus. In addition, this study shows that inhibition of the small G protein Rac1, a known forgetting regulator, facilitates the association between S1/S2 odors. These results indicate that flies can infer value to olfactory stimuli based on the previous associative structure between odors, and that inhibition of Rac1 lengthens the time window of the olfactory 'sensory buffer', allowing the establishment of associations between odors presented in sequence (Martinez-Cervantes, 2022).
The neural basis of behavior is identified by systematically manipulating the activity of specific neurons and screening for loss or gain of phenotype. Therefore, robust, high-scoring behavioral assays are necessary for determining the neural circuits of novel behaviors. This study reports a simple Y-maze design for Drosophila olfactory learning and memory assay. Memory scores in the Y-mazes are considerably better and longer-lasting than scores obtained with commonly used T-mazes. The results suggest that trapping flies to an odor choice in a Y-maze could improve scores. It is postulated that the improved scores could reveal previously undetectable memory traces, enabling the study of underlying neural mechanisms. Indeed, unreported protein synthesis-dependent long-term memories (LTMs) were identified, reinforced by ingestion of (1) an aversive compound and (2) a sweet but nonnutritious sugar, both 24 h after training. Y-mazes were used to probe how using a greater reward may change memory dynamics. These findings predict that a greater sugar reward may extend existing memory traces or reinforce additional novel ones (Mohandasan, 2023).
Individuals of many animal populations exhibit idiosyncratic behaviors. One measure of idiosyncratic behavior is a behavior syndrome, defined as the stability of one or more behavior traits in an individual across different situations. While behavior syndromes have been described in various animal systems, their properties and the circuit mechanisms that generate them are poorly understood. Thus there is an incomplete understanding of how circuit properties influence animal behavior. This study characterize olfactory behavior syndromes in the Drosophila larva. Larvae were shown to exhibit idiosyncrasies in their olfactory behavior over short time scales. They are influenced by the larva's satiety state and odor environment. Additionally, a group of antennal lobe local neurons was identified that influence the larva's idiosyncratic behavior. These findings reveal previously unsuspected influences on idiosyncratic behavior. They further affirm the idea that idiosyncrasies are not simply statistical phenomena but manifestations of neural mechanisms. In light of these findings, the importance of idiosyncrasies to animal survival and how they might be studied was discussed more broadly (Odell, 2023).
Recent connectome analyses of the entire synaptic circuit in the nervous system have provided tremendous insights into how neural processing occurs through the synaptic relay of neural information. Conversely, the extent to which ephaptic transmission which does not depend on the synapses contributes to the relay of neural information, especially beyond a distance between adjacent neurons and to neural processing remains unclear. This study shows that ephaptic transmission mediated by extracellular potential changes in female Drosophila melanogaster can reach >200 μm, equivalent to the depth of its brain. Furthermore, ephaptic transmission driven by retinal photoreceptor cells mediates light-evoked firing rate increases in olfactory sensory neurons. These results indicate that ephaptic transmission contributes to sensory responses that can change momentarily in a context-dependent manner (Ikeda, 2022).
Ephaptic transmission of light information from photoreceptor cells in the retina mediates the increase in firing rate in the OSNs during odor stimulations. This study has not revealed whether the ephaptic transmission directly changes the firing rate of the OSNs. Amputation of the antennal nerve abolished the firing rate increases during sustained light, suggesting that once the light information might be received by neurons in the brain, the information would be relayed by the neurons through the antennal nerve to the antenna, resulting in the firing rate increases in the OSNs (Ikeda, 2022).
While ephaptic coupling has been reported earlier, such as between neighboring neurons within the same sensillum, or between Purkinje cells, which is at a distance of <100 μm , this study shows that ephaptic transmission reaches >200 μm in vivo, equivalent to the depth of the entire fly brain, beyond the distance between neighboring neurons. Light stimulations cause ~10 mV field potential deflections in a retina. If endogenous fields are neglected in the brain, light stimulations may induce ~33.3 mV/mm electric field between the retina and center of the brain (0 mV), since the distance between them is ~300 μm. This electric field is strong enough to modulate neural activities, as even weaker electric fields (<0.5 mV/mm) changed the firing patterns of neurons in vitro (Ikeda, 2022).
In rodents, the firing rate of cerebellar Purkinje cells either decreased or increased when a current was injected into the extracellular field around their axons, causing field potential changes of 0.2 mV. In insects, odor-evoked field potential oscillations whose amplitude is comparable with that caused by the current injection in the rodents, are induced by synchronous firing of olfactory neurons in the antennal lobe which are mediated by GABAergic neurons forming reciprocal synapses with excitatory projection neurons. Changes in the extracellular field potential are commonly observed in many nervous systems. While such extracellular field potential activities have been considered as a side effect of synchronized spiking of neurons, this study suggests that such field potential changes evoked by a sensory stimulus can control the excitability of distant neurons, in addition to adjacent neurons. As ephaptic transmission is more effective at a short distance, the ephaptic transmission from the retinae may contribute significantly to firing rate changes in downstream neurons of the photoreceptor cells in the optic lobe (Ikeda, 2022).
This study also revealed that odor responses of OSNs were clearly modulated when light conditions changed transiently. This mechanism may help flies switch attention to newly presented sensory cues or maintain attention toward those remaining after the change. Turning the light on, for example, reduces the firing rates of the OSNs, which may enable the flies to pay more attention to visual information, whereas turning the light off increases the firing rates of the OSNs, which may help them attend to olfactory sensory cues (Ikeda, 2022).
Recent connectome analyses have revealed the entire synaptic network in the CNS in Drosophila and provides insight into how neural information is subject to synaptic relays to determine the behavioral output. This study has show that ephaptic relays also contribute to modulating the firing rate of distant neurons and modify the sensory responses that can change momentarily in a context-dependent manner. To build an integrated model of the fly brain, we should also consider ephaptic relay of neural information (Scheffer and Meinertzhagen, 2021). The compound eye-antenna model would be a suitable model to determine the role of ephaptic transmission in neural processing (Ikeda, 2022).
Dopaminergic neurons in Drosophila play
critical roles in diverse brain functions such as motor control,
arousal, learning, and memory. Using genetic and behavioral
approaches, it has been firmly established that proper dopamine
signaling is required for olfactory classical conditioning (e.g.,
aversive and appetitive learning). Dopamine mediates its functions
through interaction with its receptors. There are two different
types of dopamine receptors in Drosophila: 1) Dopamine 1-like,
including Dopamine (DA) is an important neurotransmitter mediating a variety of
brain functions including locomotion, reward, awareness, learning and
memory, and cognition. Genetic and pharmacological studies revealed
that the dopaminergic system in the fruit fly Drosophila melanogaster
plays multiple roles in motor function and associative learning. Using
the sophisticated genetic tools available for the fruit fly, it has
been firmly established that release of dopamine is required for
associative learning in Drosophila adults and larvae. Dopaminergic
neural circuits mediating olfactory learning have been also
characterized in the fruit fly brain (Qi, 2014). DA mediates its physiological functions through interaction with its
receptors. Analysis of the primary structure of the DA receptors
revealed that those receptors belong to the G-protein coupled receptor
(GPCR) family. Generally, DA receptors can be divided into two
families in vertebrates. The D1-like receptor family stimulates cAMP
production by activation of the receptor-coupled Gs subunit of G
proteins. The D2-like receptor family belongs to the pertussis toxin
(PTX)-sensitive G protein (i.e., Gi and Go)-coupled receptor (GPCR)
superfamily. Therefore, actions of D2-like receptor members have been
characterized as inhibitory. In relation to regulation of DA
signaling, DA neurons were found to possess receptors for their own
transmitter, dopamine, at their synaptic nerve terminals. These DA
autoreceptors (autoR) function as self-inhibitory regulators (Qi,
2014). In Drosophila, there are four DA receptors (dDA1,
DAMB,
DopEcR,
and DD2R) that have been cloned and characterized. Two DA receptors
(dDA1, DAMB) were cloned first and appear to be members of the D1-like
receptor family on the basis of their ability to stimulate adenylyl
cyclase (AC) in a heterologous expression system. In contrast, only
one Drosophila DA receptor DD2R gene has been identified. Functional
expression of the DD2R gene in HEK293 cells indicated that DA caused a
marked decrease in forskolin-induced cAMP level, indicating that DD2R
belongs to the inhibitory D2-like receptor family. Interestingly, two
recent studies confirmed the existence of DA autoreceptors in
Drosophila (Qi, 2014). Olfactory associative learning in adult flies requires expression of
Drosophila D1 receptor dDA1 in the mushroom body, the anatomical
center for learning and memory. The dDA1 mutant dumb showed
impaired appetitive learning as well as aversive learning. These
impaired learning behaviors were fully rescued by expression of the
wild-type dDA1 transgene in MB neurons in mutant flies, further
confirming the role of Drosophila D1-like receptors in learning.
However, no previous study has attempted to characterize the role of
D2-like DD2R in Drosophila learning and memory. Interestingly, there
was one study showing that a D2 agonist eticlopride did not disrupt
visual learning (e.g., T maze assay) in adult flies (Qi, 2014). Drosophila larvae carrying DD2R-RNAi transgene were used to examine
the role of D2-like receptors in associative learning. Two different
types of tissue-specific drivers were used to examine both presynaptic
D2 autoreceptors and postsynaptic D2 receptors. Dopaminergic-specific
driver TH-Gal4 was used to induce DD2R-RNAi expression in DA neurons.
Since the target of dopaminergic innervation is the mushroom body
(MB), the center for learning and memory in Drosophila, MB-specific
drivers (201Y-Gal4, 30Y-Gal4) were used to down-regulate postsynaptic
DD2R combined with DD2R-RNAi transgene. The results showed that both
presynaptic DD2R autoreceptors and postsynaptic receptors are required
for aversive and appetitive olfactory learning in Drosophila larvae
(Qi, 2014). The Drosophila D2 receptor DD2R has been shown to play an important
role in locomotion, aggression, and neuroprotection. Interestingly, no
study has shown whether Drosophila DD2R is involved in learning and
memory, although dopaminergic (DA) neural circuits and D1 receptors
are known to mediate Drosophila aversive learning. The present study,
for the first time, demonstrated that DD2R is involved in olfactory
associative learning in Drosophila larvae. Further, we showed that
both presynaptic and postsynaptic DD2Rs mediate aversive and
appetitive learning in the fly larvae as down-regulation of DD2R in DA
and mushroom body (MB) neurons resulted in impaired olfactory learning
(Qi, 2014). Multiple studies have proved that dopamine signaling is necessary in
Drosophila aversive learning. However, it is uncertain whether
dopamine signaling is involved in appetitive learning. Several
laboratories reported that DA signaling is not necessary for
appetitive learning, which is mediated by another biogenic amine,
octopamine In contrast, DA signaling has been shown to be necessary
for appetitive learning; inhibition of DA release resulted in reduced
appetitive learning. Furthermore, D1 receptor mutants (e.g., dDA1)
showed impaired appetitive learning (Qi, 2014). This study has demonstrated that dopamine mediates not only aversive
learning, but also appetitive learning. Both learning behaviors are
impaired when DD2R-RNAi is expressed in DA neurons or in MB neurons.
Interestingly, aversive learning was completely impaired, while
appetitive learning was only partially impaired when DD2R-RNAi was
expressed in DA neurons. A possible explanation is that the effect of
DD2R-RNAi is partial as RNAi down-regulates the target gene
expression. Another possibility is that DA is not the only modulatory
neurotransmitter mediating appetitive learning; another biogenic
amine, octopamine, is involved in appetitive learning. Therefore,
octopamine can mediate appetitive learning to a certain extent even if
DA signaling is impaired. In contrast, no modulatory neurotransmitter
other than DA is known to be involved in aversive learning (Qi, 2014).
Reduced locomotion due to expression of DD2R-RNAi has been reported.
The current findings do not support that result since the larvae
carrying DD2R-RNAi showed no changes in sensory and motor function,
compared to WT and control fly strains. This discrepancy can be
explained through the following reasons. first, it may be related to
developmental-specific effects. This study used third-instar larvae
while adult flies were used by Draper. Second, there are differences
in locomotion assays. Draper quantified total activity counts, amount
of time active, and number of activity-rest bouts. In the current
study, crawling speed was measured. Third, DD2R-RNAi expression
patterns are different. Draper used Act5C-Gal or elav-Gal4 to express
DD2R-RNAi ubiquitously or pan-neuronally, respectively. In contrast,
DD2R-RNAi was only expressed in DA or MB neurons in the current study.
Therefore, neural circuits affected by DD2R-RNAi can be different,
resulting in different behaviors. It is also possible that expression
level of DD2R-RNAi is different due to different drivers (Qi, 2014). Since the identification of Drosophila D2 receptor DD2R, two studies
have revealed the autoreceptor function of DD2R. D2R agonists have
been reported to reduce DA release in the Drosophila larval central
nervous system. It was also shown that DD2R autoreceptors suppress
excitability of DA neurons in Drosophila primary neuronal cultures.
This study showed that DD2R is involved in mediating both appetitive
and aversive olfactory learning. DD2R-RNAi in DA neurons
down-regulates DD2R autoreceptor function. Thus excitability of DA
neurons is increased, leading to an increase of DA release. Our
results indicate that excessive DA release impairs olfactory learning.
Indeed, it has been shown that olfactory learning is impaired in
Drosophila DA transporter mutant fumin, likely due to
increased synaptic DA levels. In contrast, a lack of DA release is
known to cause impaired learning in Drosophila larvae. Therefore, it
appears that homeostatic regulation of DA release by DD2R is important
for both appetitive and aversive olfactory learning as either too much
or too little synaptic DA causes impaired learning. Taking these facts
into consideration, a model is proposed to explain the role of
presynaptic DD2R autoreceptors. Presynaptic DD2R autoreceptors
suppress release of DA at the presynaptic terminals in the MB. If
presynaptic DD2R function is suppressed, then more DA is released into
MB neurons. Increased DA tone in the MB impairs both aversive and
appetitive learning behaviors (Qi, 2014). This study also showed that olfactory learning in Drosophila larvae
is impaired by down-regulation of postsynaptic DD2R in MB neurons. As
the role of DD2R is inhibitory, the effects of DD2R-RNAi in MB neurons
are expected to increase neuronal excitability, and thus olfactory
learning is impaired by hyperexcitability in MB neurons. This
observation might not be consistent with the physiological findings
that learning and memory are mediated by enhanced neuronal
excitability and synaptic transmission. Such well-known examples are
long-term facilitation (LTF) and long-term potentiation (LTP). In this
study, DD2R-RNAi is expressed throughout the larval stage. Therefore,
hyperexcitability is chronic and thus this increased baseline activity
interferes with coding new information in the MB. Indeed, olfactory
learning is impaired in Drosophila by the chronic increase of
excitatory cholinergic synaptic transmission due to the
phosphodiesterase gene dunce mutation, resulting in increased
cAMP levels. Taken together, temporal increases in excitability are
key physiological changes underlying associative learning and thus
DD2R-RNAi interferes with this change by inducing chronic
hyperexcitability in MB neurons (Qi, 2014). In addition to DD2R, there are Drosophila D1-like receptors (dDA1 and
DAMB) that are known to be highly expressed in MB neurons. In fact,
dDA1 null mutants showed defects in olfactory learning. Since D1-like
receptors increase neuronal excitability via the cAMP-PKA signaling
pathway, dDA1 mutant MB neurons are less depolarized when DA is
released at the synaptic terminal in the MB, and thus cannot mediate
olfactory learning. Proper excitability of MB neurons should be
maintained by balancing actions of D1- and D2-like receptors in MB
neurons (Qi, 2014). It has been proposed that the adenylyl cyclase gene rutabaga
in MB is a coincidence detector for CS and US in Drosophila olfactory
learning and memory. Therefore, on the basis of the current results, a
model is proposed to explain postsynaptic mechanisms underlying
aversive and appetitive learning. Postsynaptic DD2Rs in MBNs inhibit
neuronal excitability while dDA1 stimulates neural circuits
associating CS with US in MB. DA receptors dDA1 and DD2R regulate AC
in MB neurons in the opposite direction to maintain homeostatic
balance of MB neuronal excitability, which is an important
physiological element for Drosophila larval olfactory learning (Qi,
2014). In conclusion, this study examined the role of D2-like receptor DD2R
in Drosophila olfactory associative learning. The results showed that
suppression of presynaptic DD2R autoreceptors impairs both appetitive
and aversive learning. Similarly, postsynaptic DD2R in MB neurons
appears to be involved in both appetitive and aversive learning (Qi,
2014). The data strongly support the hypothesis that presynaptic DD2R
autoreceptors suppress release of DA at the presynaptic terminals in
the MB. If presynaptic DD2R function is suppressed, then more DA is
released. Increasing DA tone to MB neurons impairs both aversive and
appetitive learning behaviors. Postsynaptically, DD2R-RNAi impaired
olfactory associative learning most likely by inducing chronic
hyperexcitability in MB neurons. Therefore, the role of postsynaptic
DD2R is to maintain the proper excitability in MB neurons during
learning. Taken together, this study, for the first time, demonstrated
that DD2R plays an important role in Drosophila olfactory associative
learning (Qi, 2014).
In Drosophila, dopamine signaling to the mushroom body intrinsic neurons, Kenyon cells (KCs), is critical to stabilize olfactory memory. Little is known about the downstream intracellular molecular signaling underlying memory stabilization. This study addresses this question in the context of sugar-rewarded olfactory long-term memory (LTM). Associative conditioning increases the phosphorylation of MAPK in KCs, via Dop1R2 signaling. Consistently, the attenuation of Dop1R2, Raf or MAPK expression in KCs selectively impairs LTM but not short-term memory. Moreover, this study shows that the LTM deficit caused by the knockdown of Dop1R2 can be rescued by expressing active Raf in KCs. Thus, the Dop1R2/Raf/MAPK pathway is a pivotal downstream effector of dopamine signaling for stabilizing appetitive olfactory memory (Sun, 2020).
This study supports the idea that Dop1R2 signaling through the Raf/MAPK pathway in KCs is critical in stabilizing appetitive memory. This could be achieved through acquisition or consolidation of appetitive LTM. How is post-training Dop1R2 signaling triggered in this context? Accumulating evidence implies that Dop1R2 detects the basal dopamine release after learning. In aversive olfactory learning, the post-training enhancement of the oscillatory activity of MB-projecting DANs (MB-MP1 and MB-MV1) underlies LTM consolidation, and Dop1R2 in KCs is responsible for detecting the enhanced dopamine signals. This signaling is also reported to mediate forgetting early labile memory, suggesting distinct neural mechanisms to regulate memories with different temporal dynamics. In appetitive learning, Dop1R2 is suggested to be the mediator of the oscillating DANs, which represent the energy value of the reward and consolidate LTM. Collectively, after conditioning Dop1R2 signaling upon specific reinforcement input is a conserved mechanism to stabilize LTM. As MB-projecting DANs are also engaged in conveying reward information during memory acquisition, the Dop1R2/Raf/MAPK pathway might additionally be involved during the acquisition of LTM (Sun, 2020).
In contrast to the well characterized receptor tyrosine kinase signaling, it is rather unexpected to find the Raf/MAPK pathway as a downstream target of Dop1R2, a G-protein-coupled receptor. Dop1R2 was recently shown to have a preferential affinity to the Gαq subunit to elicit a robust intracellular Ca2+ increase upon ligand stimulation in KCs. There are multiple lines of biochemical evidence suggesting that Gαq-dependent Ca2+ signals could trigger several pathways, such as small GTPase Rap1, protein kinase C, or Ras, to activate Raf. Furthermore, some reports suggested that calcium influx through N-methyl-d-aspartate receptor induces transient MAPK phosphorylation. Hence, intracellular Ca2+ might be the key second-messenger system to link Dop1R2 and Raf/MAPK in appetitive LTM (Sun, 2020).
This study found that MAPK has a pivotal role to stabilize appetitive memory in KCs. MAPK signaling is known to regulate different cellular processes ranging from cytoskeletal dynamics to transcriptional modulation. In Drosophila, a recent work unveiled that MAPK stabilizes presynaptic structural changes in KCs upon associative training with electric shocks, reportedly by changing the activity of an actin cytoskeleton regulator (Zhang, 2018). Such MAPK-induced cytoskeletal change might also occur in appetitive learning. Alternatively, a recent study showed that LTM consolidation involves MAPK translocation to the nuclei in KCs (Li, 2016). Consistently, it is reported that MAPK activates transcription factors like c-Fos and cAMP response element-binding protein (CREB) in KCs to form aversive LTM. Appetitive LTM is also dependent on CREB in KCs. Collectively, it is proposed that MAPK stabilizes appetitive memory by regulating these transcription factors. Future investigation on the downstream of the MAPK pathway should reveal the newly transcribed genes for memory stabilization (Sun, 2020).
Another remaining puzzle is that both
simultaneous and trace conditioning, although recruiting different
molecular mechanisms, rely on the MB as a mutual crucial site.
This seems at variance with the view from mammalian studies, where
trace conditioning recruits neural circuits distinct from delay
conditioning. Species or paradigm differences might explain the
discrepancy, but it awaits to be fully addressed by future studies
exploring whether brain regions outside the MB are additionally
engaged in trace conditioning in fruit flies and, more
importantly, whether various MB subdivisions contribute
differentially to these two conditioning variants (Shuai, 2011).
Drosophila learn to avoid odors that are paired with aversive stimuli. Electric shock is a potent aversive stimulus that acts via dopamine neurons to elicit avoidance of the associated odor. While dopamine signaling has been demonstrated to mediate olfactory electric shock conditioning, it remains unclear how this pathway is involved in other types of behavioral reinforcement, such as in learned avoidance of odors paired with increased temperature. To better understand the neural mechanisms of distinct aversive reinforcement signals, an olfactory temperature conditioning assay were established comparable to olfactory electric shock conditioning. The AC neurons, which are internal thermal receptors expressing dTrpA1, are selectively required for odor-temperature but not for odor-shock memory. Furthermore, these separate sensory pathways for increased temperature and shock converge onto overlapping populations of dopamine neurons that signal aversive reinforcement. Temperature conditioning appears to require a subset of the dopamine neurons required for electric shock conditioning. It is concluded that dopamine neurons integrate different noxious signals into a general aversive reinforcement pathway (Galili, 2014).
Whether specific learning experiences by parents influence the behavior of subsequent generations remains unclear. This study examines whether and what aspects of parental sensorimotor training prior to conception affect the behavior of subsequent generations and identifies the neural circuitries in Drosophila responsible for mediating these effects. Using genetic and anatomic techniques, this study found that both first- and second-generation offspring of parents who underwent prolonged olfactory training over many days displayed a weak but selective approach bias to the same trained odors. However, it was also found that the offspring did not differentiate between orders based on whether parental training was aversive or appetitive. Disruption of both olfactory-receptor and dorsal-paired-medial neuron input into the mushroom bodies abolished this change in offspring response, but disrupting synaptic output from α/β neurons of the mushroom body themselves had little effect on behavior even though they remained necessary for enacting newly trained conditioned responses. This study provides a circuit-based understanding of how specific sensory experiences in Drosophila may bias the behavior of subsequent generations, and identifies a transgenerational dissociation between the effects of conditioned and unconditioned sensory stimuli (Williams, 2016).
In Drosophila, negatively reinforcing dopaminergic neurons also provide the inhibitory control of satiety over appetitive memory expression. This study shows that aversive learning causes a persistent depression of the conditioned odor drive to two downstream feed-forward inhibitory GABAergic interneurons of the mushroom body, called MVP2, or mushroom body output neuron (MBON)-γ1pedc>α/β. However, MVP2 neuron output is only essential for expression of short-term aversive memory. Stimulating MVP2 neurons preferentially inhibits the odor-evoked activity of avoidance-directing MBONs and odor-driven avoidance behavior, whereas their inhibition enhances odor avoidance. In contrast, odor-evoked activity of MVP2 neurons is elevated in hungry flies, and their feed-forward inhibition is required for expression of appetitive memory at all times. Moreover, imposing MVP2 activity promotes inappropriate appetitive memory expression in food-satiated flies. Aversive learning and appetitive motivation therefore toggle alternate modes of a common feed-forward inhibitory MVP2 pathway to promote conditioned odor avoidance or approach (Perisse, 2016).
Prior work in Drosophila indicated that negative reinforcement and hunger-state-dependent motivational control of appetitive memory performance might be controlled by the same dopaminergic neurons (DANs). The presynaptic field of the MP1/PPL1-γ1pedc DANs occupies a defined region of the MB that also contains the MVP2/MBON-γ1pedc >αβ dendrites, suggesting that these DANs modulate the efficacy of this specific KC-MBON connection. The results of the current study demonstrate that the MVP2 MBONs also play a critical role in the expression of short-term aversive memory and the state-dependence of appetitive memory expression. Since these findings directly mirror the described roles for the MP1 DANs (Krashes, 2009), it is concluded that DAN modulation of the KC-MVP2 junction is critical for both negative reinforcement during olfactory learning and the motivational salience of appetitive odor cues (Perisse, 2016).
The GABA-ergic MVP2 neurons have postsynaptic and presynaptic processes in the MB, suggesting that they are interneurons of the MB and feed-forward inhibit other MBON compartments. Dendrites of MVP2 neurons (and the presynaptic terminals of the MP1 DANs) innervate the γ1 region and more densely innervate the αβs than the αβ core (αβc) region of the αβ ensemble (Krashes, 2009). MVP2 are therefore likely to be primarily driven by αβs KCs. Since αβs neurons contribute to conditioned approach and avoidance, whereas αβc are particularly important for conditioned approach (Perisse, 2013), there is an imbalance in the drive to approach and avoidance behaviors at this level of the MBON network (Perisse, 2016).
Artificial activation of MVP2 neurons in naive flies drives approach behavior, consistent with them preferentially inhibiting MBON compartments that direct avoidance -- as opposed to those that drive approach. Anatomical and functional connectivity and odor-directed behavioral data are consistent with such a model. MVP2 stimulation inhibits odor-evoked activity in M4/6 but not in V2αV2α' MBONs. MVP2 stimulation also promotes expression of approach memory in food-satiated flies, yet it inhibits naive odor avoidance behavior. It is concluded that MVP2 directly inhibit the M4/6 class of horizontal lobe MBONs through synapses made on the primary axonal segment as it exits the MB lobes. Inhibition exerted in this area might be expected to control the gain of the MBON responses following integration of KC inputs in the MBON dendrite in a manner similar to perisomatic inhibition in mammals. Consistent with this anatomy and idea, no obvious changes were found in the odor drive to the dendritic region of M4/6 neurons between hungry and satiated flies, but a hunger-dependent decrease was apparent when odor-evoked responses were measured in the efferent neurites. In contrast, MVP2 neurons do not functionally inhibit or densely innervate the neurites of V2αV2α' MBONs, nor does hunger reduce odor-evoked responses in V2αV2α' MBONs. It therefore seems likely that MVP2 neurons contact DANs or other neurons that occupy the α2 compartment of the MB lobe (Perisse, 2016).
The data also demonstrate that aversive learning reduces the relative conditioned odor drive to MVP2 neurons, which would presumably decrease feed-forward inhibition onto the relevant MBON compartments and thereby render them more responsive to odors. Output from the glutamatergic M4/6 neurons, which are postsynaptic to the KCs in the horizontal tip regions, is required for expression of aversive and appetitive memory. Furthermore, the relative odor-drive to M4/6 neurons was shown to be depressed by reward learning (Owald, 2015) and potentiated by aversive learning (Owald, 2015; Bouzaiane, 2015). Since aversive learning reduces the conditioned odor drive of the MVP2 neuron, it is proposed that the observed increase in odor-drive to M4/6 after aversive learning results from reduced feed-forward inhibition from MVP2. This would mean that bi-directional output plasticity could emerge via a direct junctional plasticity following reward conditioning, but a network property of reduced MVP2 feed-forward inhibition after aversive conditioning. Such a layered feed-forward network architecture linking one site of DAN-driven KC-MBON plasticity to another KC-MBON connection would provide a means to achieve odor-specific bi-directional plasticity at a particular synaptic junction using dopamine-driven synaptic depression in two different places. It is proposed that this circuit design principle in which plasticity at one site of a neuron can, via feed-forward inhibition, indirectly alter the efficacy of output elsewhere in the same neuron, could be a general feature in the brain of the fly and other animals. It is possible that the KC-MVP2 junction also exhibits bi-directional plasticity, notably with inverted polarity relative to M4/6 plasticity traces (Perisse, 2016).
The layered network architecture places the aversive memory relevant MVP2 plasticity on top of the M4/6 plasticity that is relevant for appetitive memory (Owald, 2015). This organization could accommodate the co-existence of aversive and appetitive olfactory memories following conditioning reinforced by sugar laced with bitter taste. Immediately after such training flies avoid the conditioned odor because the aversive taste memory relieves feed-forward inhibition onto the sites that are depressed by appetitive sugar plasticity and therefore over-rides the expression of approach memory. However, as the aversive memory decays, feed-forward inhibition returns and appetitive memory is then expressed. A similar mechanism might account for the time-dependent switch from conditioned aversion to approach following odor conditioning reinforced by alcohol (Kau, 2011). It is notable that learning-induced plasticity of relative odor-drive to MVP2 persists for at least 3 hr after training whereas output from MVP2 is dispensable for the expression of aversive memory at that time. Since expression of different phases of aversive memory requires distinct combinations of MBON pathways (Bouzaiane, 2015), it is proposed that more persistent MVP2 plasticity might provide a permissive gate for both the formation of aversive memory in, and the expression from, other parts of the MBON network. This would be reminiscent of fear conditioning in the neural circuitry of the mouse amygdala, where dopamine suppresses feed-forward GABA-ergic inhibition from local interneurons to facilitate the induction of long-term potentiation (Perisse, 2016).
MVP2 neuron output is required for the expression of sugar-reinforced approach memory at all times. Moreover, odors evoked larger MVP2 responses in hungry than in food-satiated flies, and elevating MVP2 activity in satiated flies promoted inappropriate expression of appetitive memory. These results are consistent with the model that hunger generally increases feed-forward inhibition through MVP2 to support appetitive memory expression). This result is also the mirror-image of that with MP1 DANs whose activity increases when the flies are satiated and whose inhibition leads to the expression of appetitive memory in satiated flies. Taken with prior work, it is therefore proposed that hunger increases dNPF, which releases MP1 inhibition over the KC-MVP2 connection. This results in an increase of odor-evoked MVP2 feed-forward inhibition onto the MBON compartments such as M4/6 that contain the KC-MBON synapses that are directly modified by appetitive conditioning. The increase of MVP2 inhibition into these, and other, compartments allows more efficient expression of the appetitive memory-directed approach behavior by effectively raising the motivational salience of learned food-related odors. Appetitive conditioning may also increase odor-specific recruitment of MVP2 feed-forward inhibition (Perisse, 2016).
The current findings therefore suggest that the MVP2 neuron pathway functions in at least three modes that are presumably selected by the aversively reinforcing MP1 DANs. If the flies are aversively conditioned, phasic MP1 specifically depresses conditioned-odor drive to MVP2 neurons. In a food-satiated fly, tonic MP1 limits general odor-driven MVP2 activity. Lastly, in the hungry fly, lower MP1 activity generally enhances odor-drive to MVP2. In the OFF modes, low-level MVP2 feed-forward inhibition skews the MBON network toward behavioral avoidance, whereas in the ON mode the increased feed-forward inhibition from MVP2 skews the MBON network toward favoring conditioned approach. The MP1 DANs signal the aversive reinforcing properties of electric shock, heat, and bitter taste, suggesting they provide general aversive influence. The satiated state presumably uses a tonic version of this aversive signal to limit the fly approaching an appetitive odor cue (Perisse, 2016).
The parallels between the fly and mammalian dopaminergic systems appear striking. DANs in the basal ganglia of the mammalian brain also support reinforcement learning and the prediction of stimuli that potentially lead to rewarding outcomes. Furthermore, like the fly DANs, mammalian DANs can be anatomically divided into those that generate aversion and different types of reward. GABA-ergic neurons in the mouse ventral tegmental area, whose cell bodies are interspersed with the DANs, have been proposed to signal the value of expected reward and provide a source of subtraction to DANs that calculate a reward prediction error. Negatively reinforcing MP1 DANs in the fly modulate odor-drive to the MVP2 neurons to provide the motivational control over actions to gain reward. Therefore, MVP2 neurons may provide an inhibitory bridge between MBON domains that are controlled by aversive and rewarding DANs (Perisse, 2016).
Avoiding associatively learned predictors of danger is crucial for survival. Aversive memories can, however, become counter-adaptive when they are overly generalized to harmless cues and contexts. In a fruit fly odor-electric shock associative memory paradigm, this study found that learned avoidance lost its specificity for the trained odor and became general to novel odors within a day of training. The possible neural circuit mechanisms of this effect are discussed, and the parallelism is highlighted to over-generalization of learned fear behavior after an incubation period in rodents and humans, with due relevance for post-traumatic stress disorder (Konig, 2017).
Developmental neuronal remodeling is crucial for proper wiring of the adult nervous system. While remodeling of individual neuronal populations has been studied, how neuronal circuits remodel-and whether remodeling of synaptic partners is coordinated-is unknown. This study found that the Drosophila anterior paired lateral (APL) neuron undergoes stereotypic remodeling during metamorphosis in a similar time frame as the mushroom body (MB) γ-neurons, with whom it forms a functional circuit. By simultaneously manipulating both neuronal populations, this study found that cell-autonomous inhibition of γ-neuron pruning resulted in the inhibition of APL pruning in a process that is mediated, at least in part, by Ca(2+)-Calmodulin and neuronal activity dependent interaction. Finally, ectopic unpruned MB γ axons display ectopic connections with the APL, as well as with other neurons, at the adult, suggesting that inhibiting remodeling of one neuronal type can affect the functional wiring of the entire micro-circuit (Mayseless, 2018).
Value coding of external stimuli in general, and odor valence in particular, is crucial for survival. In flies, odor valence is thought to be coded by two types of neurons: mushroom body output neurons (MBONs) and lateral horn (LH) neurons. MBONs are classified as neurons that promote either attraction or aversion, but not both, and they are dynamically activated by upstream neurons. This dynamic activation updates the valence values. In contrast, LH neurons receive scaled, but non-dynamic, input from their upstream neurons. It remains unclear how such a non-dynamic system generates differential valence values. Recently, PD2a1/b1 LH neurons were demonstrated to promote approach behavior at low odor concentration in starved flies. This study demonstrates that at high odor concentrations, these same neurons contribute to avoidance in satiated flies. The contribution of PD2a1/b1 LH neurons to aversion is context dependent. It is diminished in starved flies, although PD2a1/b1 neural activity remains unchanged, and at lower odor concentration. In addition, PD2a1/b1 aversive effect develops over time. Thus, these results indicate that, even though PD2a1/b1 LH neurons transmit hard-wired output, their effect on valence can change. Taken together, it is suggested that the valence model described for MBONs does not hold for LH neurons (Lerner, 2020).
In order to survive, animals must attach value to external stimuli, be it due to innate or learned behavior. In particular, the ability to accurately evaluate potential food resources is a critical trait for survival. To make such an assessment, animals use many senses, with olfaction often serving as a primary cue (Lerner, 2020).
The Drosophila olfactory system resembles that of mammals, and uses similar principles to decode olfactory information. Odors bind to olfactory receptor neurons (ORNs), which are located in the antennae and maxillary palps, where each ORN expresses a single type of odorant receptor (OR). All ORNs expressing the same OR converge onto the same region in the antennal lobe termed the glomerulus. Second-order excitatory cholinergic projection neurons (ePNs) have dendrites that are restricted to a single glomerulus, whereas inhibitory GABAergic projection neurons (iPNs) are mostly multiglomerular. Both PN types project to the lateral horn (LH), whereas only ePNs project to the calyx of the mushroom body (MB). Until recently, associative learning and memory processes were generally believed to occur in the MB, with innate behavior driven by the LH. However, although the LH is still believed to contribute greatly to innate behavior, it has become apparent that the rigid functional distinction between the two neuropils cannot be upheld. There is now evidence that the MB also plays a role in some innate olfactory behaviors, mostly attractive, while the LH is involved in some forms of associative memory (Lerner, 2020).
The LH compartment contains over 1300 cells that are categorized into over 150 types, each with individual morphology. Cells that share morphological features are also more likely to share PN connectivity, although there is some variability. Nine LH cell types could be distinguished by optogenetic activation to drive either attraction (3 cell types) or aversion (6 cell types). In the case of odor stimuli, effects on odor valence were demonstrated for only three types of LH neurons and under very specific conditions: I. AV1a1 LH neurons, which trigger aversion and are required for geosmin avoidance; II. LH neurons, labeled by the R21G11- and R23C09-GAL4 driver lines, and which process CO2 avoidance; III. PD2a1/b1 neurons (previously known as type I LH neurons or ML9 and ML8, respectively) (Lerner, 2020).
IPD2a1/b1 neurons belong to the lateral horn output neurons (LHON)15. They have their somata in the lateral posteriodorsal protocerebrum, extend a short primary neurite towards the brain center and then bifurcate to connect their input regions in the LH (PD2a1/b1) and in the MB (PD2b1 only) with their presynaptic target areas in the superior intermediate protocerebrum (SIP) and superior medial protocerebrum (SMP) around the vertical MB stalk. About one third of input synapses in both LH and calyx derive from uniglomerular PNs, with another third provided by local LH neurons. In addition, reciprocal LHON input accounts for about 20%, and a varying amount of ipsi- and contralateral axoaxonic input in the SIP comes from the mushroom body output neuron (MBON)-α2sc15. PD2a1/b1 neurons were found to contribute to food odor approach at odor concentrations in the range of 10-7 to 10-5 dilution in starved flies. In addition, PD2a1/b1 neurons were also shown to be required for aversive conditioning and it was suggested that reduced activation of PD2a1/b1 neurons following aversive conditioning was responsible for the reduced odor approach. These observations are in agreement with current knowledge about learning and memory processes occurring at the MB and MBONs. Accordingly, MBONs are divided into neurons that drive either attraction or aversion, and plasticity between MB and MBONs shifts the balance between attraction and aversion for each odor. However, in contrast to the known plasticity of the synapse between MB neurons and MBONs, there is no information about any such similar plasticity between PNs and LH neurons. Furthermore, optogenetic activation of PD2a1/b1 neurons generated a mild aversion rather than attraction. In this context, odor valence can range from attractive to aversive, depending on the interplay of external factors (such as odor concentration) and internal states (such as satiation level), where a high odor concentration (even in the case of food odors) is usually associated with aversion. PN input to PD2a1/b1 neurons is positively correlated with odor concentration and as a result the activity of PD2a1/b1 neurons increases linearly with odor concentration. Thus, it is unclear how increased input to neurons which underlie attraction supports an overall aversive response to odors. This seemingly contradicts the notion that PD2a1/b1 neurons only drive attraction. Therefore this stusy examined whether PD2a1/b1 neurons always contribute to approach behavior or whether their role is context dependent. Thus, the contribution of PD2a1/b1 neurons to behavior responses under broader conditions and in particular, higher odor concentrations and satiated flies was examined (Lerner, 2020).
This study shows that PD2a1/b1 neurons, which were found to mediate an approach to odors in starved flies and at low odor concentrations, can also contribute to odor avoidance at higher odor concentrations in satiated flies. In accordance with these observations, the effects seene on avoidance behavior are influenced not only by odor identity (there are differences even between odors with similar activation patterns) and odor concentration, but also by exposure time, and satiation. In particular, starvation abolished the contribution of PD2a1/b1 neurons to an aversive response to odors even though there was no effect on the PD2a1/b1 neuron odor responses (Lerner, 2020).
The results described in this study indicate that PD2a1/b1 neurons can mediate aversive behavioral responses of satiated flies to odor at the relatively high concentration of 10-2. This effect is context dependent and is influenced by odor identity (even between odors with a similar activation pattern), odor concentration, exposure time, and fly satiation. Interestingly, starvation blocks the PD2a1/b1 aversive effect but not by directly affecting the activity of PD2a1/b1 neurons (Lerner, 2020).
The temporal dynamics of the PD2a1/b1 neuron response vary dramatically, with some odors eliciting a prolonged and robust response but only at high odor concentrations. The most likely explanation for this prolonged odor response is that this is not an intrinsic property of PD2a1/b1 neurons but can rather be attributed to properties of the ORNs. The most likely candidate is OR59b, which, according to the DoOR database, is the OR shared by all odors that generate a prolonged odor response. This notion is also supported by results indicating prolonged odor responses to ethyl acetate in DM4, the glomerulus cognate to OR59b, which was shown to be connected to PD2a1/b1 cells (Lerner, 2020).
The results presented in this study concerning the role of PD2a1/b1 neurons in driving aversive behavioral responses to odors, seem to contradict a previous report that claimed that PD2a1/b1 neurons exclusively drive attraction. It is important to note that this previous study used 3 day old flies for the behavioral experiments, rather than the 7-14 day old flies used in this study. However, this difference is unlikely to explain the difference in the effects on naive odor valence observed in the two studies following silencing of PD2a1/b1 neurons. This apparent discrepancy may be explained if PD2a1/b1 neurons reinforce a valence value that is generated by other neurons in the fly's brain. Thus, for an odor with a positive valence value, indicating attraction, PD2a1/b1 neurons further strengthen the attractive response. Conversely, for an odor with a negative value, indicating aversion, PD2a1/b1 neurons further strengthen the aversive response. If this is indeed the case, silencing PD2a1/b1 neuronal output should push the flies towards a random choice (i.e., 0 preference index) rather than driving either attraction or aversion. However, the results obtained with Apple cider vinegar (ACV) and geranyl acetate negate this option. Satiated flies exposed to high concentrations of ACV or geranyl acetate showed no preference to the odor and had a preference index around zero. However, silencing PD2a1/b1 neurons resulted in a marked increase in attraction towards these odors, pushing the preference index to positive values (Lerner, 2020).
Another possible explanation for the apparent discrepancy in results may be the different behavioral approaches (with some marked differences) used in the two studies. Specifically, flies in behavioral chambers (as used in this study) are in constant motion, so that they repeatedly enter and exit the odor plume, and make multiple decisions each time. In contrast, flies in the T-maze make fewer decisions and reach steady state more rapidly. Another difference is that flies in a T-maze make their decision within 3-4 seconds, whereas the standard analysis of the behavioral chambers takes into account a two minute window with repeated decisions. Given the strong context dependent effect of PD2a1/b1 neurons it is very plausible that PD2a1/b1 neurons contribute to both attraction and aversion. Consistent with this notion, while this study did not identify a role for PD2a1/b1 neurons in attraction, starvation and low odor concentration abolished the aversive effect of activating these neurons. In addition both studies demonstrated that PD2a1/b1 neurons contribute differentially to odor valence even if the neural activity elicited by the odors is similar. In this context, it is important to note that optogenetic activation of PD2a1/b1 neurons resulted in a mild yet significant aversive response. Thus, the combined results of this study and previous studies suggest that PD2a1/b1 neurons may affect odor valence in a number of apparently contradictory ways. This conclusion is further supported by recent results demonstrating that PD2a1 neurons are essential for context-dependent long term memory, but not for 'classical' mushroom body-mediated, context-independent long term memory (Lerner, 2020).
PN input to PD2a1/b1 neurons consists of neurons innervating predominantly six glomeruli: DM1, DM4, VA2, VM3, DP1m, and DP1l. These glomeruli are considered to drive attraction as they are activated by appetitive and food odors. This raises the question of how an input, which presumably generates an attraction behavior, can generate an aversive response to odor. However, these glomeruli were also reported to drive aversion (VM366), to respond to aversive odors (DM4, VA265) or to have no effect on attraction (DM467). Furthermore, it was suggested that in the case of Drosophila larvae, hyperactivation of Or42b neurons, which are the cognate neurons to glomerulus DM1 can trigger repulsion from odors. Thus, it is possible that glomeruli that innervate PD2a1/b1 neurons also participate in aversive behavioral responses to odors (Lerner, 2020).
How can a single neuron class generate opposing behavioral responses? Without knowledge and genetic access to the downstream neurons, this is difficult to answer. However, one plausible explanation is that recruitment of downstream neuron types depends heavily on PD2a1/b1 neuronal activity. Thus, a low odor concentration that activates PD2a1/b1 neurons only weakly, may efficiently recruit one neuronal pathway leading to attraction. In contrast, a high odor concentration that produces a robust activation of PD2a1/b1 neurons may recruit a different neuronal pathway leading to aversion. This notion was demonstrated with salt, where low and high concentrations of salt, (leading to attraction and aversion, respectively), are encoded by different neuronal pathways. Similarly, while a low concentration of ACV triggers innate attraction by activating two glomeruli, DM1 and VA2, a higher concentration of ACV recruits an additional glomerulus, DM5, which leads to reduced attraction. For mechanosensory processing, the bandpass filtering mechanism of Drosophila antennal vibration sensation requires downstream neurons to have different levels of voltage-gated channels and different membrane resting potentials (Lerner, 2020).
What may be the neurons downstream of PD2a1/b1 neurons? Unfortunately, the trans-Tango experiments did not provide a clear identification of the neurons downstream of PD2a1/b1. In accordance with a previous EM analysis, this study saw strong labeling of LH neurons, but in contrast, the current experiment also detected a signal in the MB, although the labeled subsets were not consistent.Neither dopaminergic neurons or MBONs were detected, which have been suggested to be innervated by PD2a1/b1 neurons. In some preparations trans-Tango labeling was detected in layer 6 of the fan-shaped body (FSB). Together with the recently described trans-Tango label in the same layer by MBONs, this would imply a downstream integrator of both MB and LH information in a premotor center. The FSB would represent an ideal candidate for a downstream integration site for olfactory information processed independently by both the MB and the LH. As part of the central complex, the FSB belongs to the main premotor center of the central brain, analogous to the basal ganglia in vertebrates. The central complex itself serves as the main hub, integrating innate and conditioned multisensory information to relay behavioral decisions to the respective downstream effectors (Lerner, 2020).
A number of models have been proposed to explain odor identity and the associated valence in order to explain how a fly associates valence to a specific odor. One approach, termed 'labeled lines', demonstrated that odors of particular relevance are often detected by ORNs expressing highly selective receptors that respond to only a single compound. In the case of Drosophila, this type of preferential relationship was demonstrated for sex pheromones, harmful substances, oviposition cues, and even food. According to this model, activation of the labeled line generates a hardwired behavioral response. However, since most ORNs are broadly tuned to odors, the labeled line approach is probably insufficient to explain behavioral responses in these cases. Indeed, behavioral responses to general odors are dependent on population neural activity. Nevertheless, even under the population neural activity approach, a semi-labeled line assumption exists, according to which, a neuron always drives either attractive or aversive behavior (but not both), and it is the sum of the attractive and aversive signals from all the responding neurons that eventually determines the odor valence. More recently, this notion was also demonstrated using optogenetic mapping of MBONs. Accordingly, an attractive or aversive behavior is observed following optogenetic activation of MBONs, and appetitive or aversive associative conditioning will cause an odor to activate MBONs that drive attractive or aversive behavior, respectively. This model is extremely suitable for the MB, where odor tuning of MBONs is modified by plasticity based on experience. Recently, similar optogenetic mapping of LH neurons classified them as driving either attractive or aversive behavior. However, it is well established that context affects innate behavioral output, which is mediated by the LH. Thus, while the dynamic nature of KC-to-MBON connectivity allows for context-dependent changes, it is less clear how the LH, which as far as is known receives mostly hardwired inputs from PNs, makes context-dependent changes in neuronal activity. The current results suggest that at least for the LH, the notion that a neuron can be categorized as driving either attraction or aversion may need to be reconsidered (Lerner, 2020).
Animal behavior is shaped both by evolution and by individual experience. Parallel brain pathways encode innate and learned valences of cues, but the way in which they are integrated during action-selection is not well understood. This study used electron microscopy to comprehensively map with synaptic resolution all neurons downstream of all Mushroom Body output neurons (encoding learned valences) and characterized their patterns of interaction with Lateral Horn neurons (encoding innate valences) in Drosophila larva. The connectome revealed multiple convergence neuron types that receive convergent Mushroom Body and Lateral Horn inputs. A subset of these receives excitatory input from positive-valence MB and LH pathways and inhibitory input from negative-valence MB pathways. Functional connectivity from LH and MB pathways and behavioral roles of two of these neurons was confirmed. These neurons encode integrated odor value and bidirectionally regulate turning. Based on this it is speculated that learning could potentially skew the balance of excitation and inhibition onto these neurons and thereby modulate turning. Together, this study provides insights into the circuits that integrate learned and innate valences to modify behavior (Eschbach, 2021).
Selecting whether to approach or avoid specific cues in the environment is essential for survival across the animal kingdom. Many cues have both innate valences acquired through evolution and learned valences acquired through experience that can guide action selection. Innate and learned valences are thought to be computed in distinct brain areas, but the circuit mechanisms by which they are integrated and by which learned valences can override innate ones are poorly understood. Using the tractable Drosophila larva as a model system, this study describes with synaptic resolution the patterns of convergence between the output neurons of a learning center (the MB) and an innately attractive pathway in the lateral horn (the LH). 62 neurons per brain hemisphere were identified that represent direct points of convergence between the MB and the LH, that fall into a number of different subtypes based on their patterns of MB and LH inputs and potentially encode a number of distinct features. One subtype of 10 convergence neurons (CNs) receives excitatory input from positive-valence MB and LH pathways and inhibitory input from negative-valence MB pathways. Functional connectivity from LH and MB pathways and behavioral roles of two of these neurons were confirmed. These neurons encode integrated odor value (coding for positive value with an increase in their activity) and regulate turning. They are activated by an attractive odor, and when activated they repress turning. Conversely, when inactivated, they increase turning. Based on this, it is speculated that learning could potentially skew the balance of excitation and inhibition onto these neurons and thereby modulate turning. For one of these neurons, this study indeed verified that aversive learning skews inputs towards inhibition. Together, this study provides insights into the circuit mechanisms by which learned valences could interact with innate ones to modify behavior (Eschbach, 2021).
The brain areas that compute innate and learned valences of stimuli interact with each other, but despite recent progress, their patterns of interaction are not fully understood. In principle, MBONs could synapse directly onto LHNs thereby directly modifying innate valences. Alternatively, LHNs could directly synapse onto MBONs. Finally, learned and innate valences could initially be kept separate, and MBONs and LHNs could converge on downstream neurons. This study found that in Drosophila larva (1) some MBONs synapse directly onto some LHNs; (2) some MBONs received direct synaptic input from LHNs and (3) many MBONs and LHNs converge onto downstream CNs, similar to findings in the adult. One MBON (m1) was also a CN, receiving significant direct input from other MBONs and from LHNs. Overall, the architecture suggests some early mixing of representations of innate and learned valences, but to some extent these representations are also kept separate in the LH and MB, and then integrated by the downstream CNs. Maintaining some initial separation of representations of innate and learned valences prior to integration could offer more flexibility and independent regulation, for example by context or internal state. Convergence neurons could compute learned valence by comparing odor-drive to positive- and negative-valence MBONs (Eschbach, 2021).
The prevailing model of MB function in adult Drosophila proposes that in naive animals the odor drive to positive- and negative-valence MBONs is equal such that their outputs cancel each other out and the LH circuits guide olfactory behavior. Learning alters the overall output towards positive- or negative-valence MBONs by modifying specific KC-to-MBON connections. This model raises several important questions. First, how is the output from MBONs of opposite valence integrated to compute a learned valence? Second, how does it interact with the output of the LH. The current findings provide further support for this model and shed insight into these questions (Eschbach, 2021).
EM reconstruction combined with neurotransmitter information has revealed a class of 10 CNs that receive excitatory input from positive-valence MBONs and inhibitory input from negative-valence MBONs. These CNs are well poised to compute the learned odor valence by comparing the odor drive to positive- and negative-valence MBONs (Eschbach, 2021).
For two members of this class (MBON-m1 and CN-33), their MB drive was tested in untrained larvae, in vivo or in explants. On average, across the population of untrained individuals, KC activation did not induce a significant change in ∂F/F0 in either CN. However, it was found that in some individuals the MB drive onto the CNs was excitatory, and in others inhibitory, indicating that the MB can provide both excitatory and inhibitory drive to the CNs. Consistently, when inhibitory neurotransmission was blocked using PTX, MBON-m1 and CN-33 showed strong excitatory responses to KC activation (Eschbach, 2021).
High variability was observed in the responses of both CN-33 and MBON-m1 both to activation of the whole MB pathway, as well as to odor presentation. This variability may in part be due to technical reasons. Indeed, the variable responses to pan-KC optogenetic activation could be due to differences in CsChrimson expression in KCs across individuals (the expression of CsChrimson was verified for each individual recording but it was not quantified). However, such a difference is unlikely to be a reason for a range of responses that spans inhibition to excitation following the stimulation of the same neuronal population. Likewise, the exposure of the sensory organ to an odor may vary from one animal to the other depending on the location of the larva's head in the chip's channel. Together with other technical aspects, this may account for some of the variance observed in in vivo. Indeed, a decomposition of the variance within the datasets by ANOVA revealed a significant effect of the identity of the individual on the variance. Interestingly though, the inter-individual variability contributed to a higher fraction of the overall variance in odor response in larvae with functional MBs than in larvae with silenced MBs. This analysis suggests that the MB pathway is a significant source of variability in odor-evoked responses in MBON-m1 and CN-33 and is consistent with the highly variable responses of these CNs to direct KC activation. The variability in response of CNs to MB inputs across untrained individuals could be due to different experiences prior to these experiments, as suggested also by the fact that MBON-m1 responses to trained odors are modified with training. High variability in MBON responses to odor across individuals has previously also been observed in the adult flies and has been related to different individual experiences. The MBs can also compute other kinds of information, such as internal state which may modulate an individual's disposition toward sensory stimuli. Therefore, the average response across untrained individuals might be similar to the response of a single individual in a naive neutral state (with any interindividual differences averaged out across a population), and the variability may represent the degree of freedom for the MB to tune this response to a stimulus depending on previous experience or state (Eschbach, 2021).
How do the learned valences modify the innate ones? How is conflict between opposite innate and learned valences resolved during action selection? One possibility could involve the integration of conflicting signals into a unified representation of value, a notion similar to common currency valuation of options, which could then be used to promote or suppress specific actions. The findings suggest that the 10 CNs that can read out the learned valence by comparing MBON inputs of opposite valence also integrate the learned valence with the innate one. Thus, the 10 CNs that receive inhibitory input from negative-valence MBONs and excitatory input from positive-valence MBONs, also receive inputs from a positive-valence LHN pathway. These neurons are therefore well poised to compute an integrated odor value and code for a positive value with an increase in their activity. For two members of this class (MBON-m1 and CN-33) it was possible to confirm these predictions. This study has shown they are activated by an innately attractive odor via the LH pathway in untrained animals. Furthermore, when the innate attractiveness of an odor was reduced through aversive training, the activity of MBON-m1 was also reduced. Finally, it was shown that activating MBON-m1 and CN-33 represses turning, further supporting the idea that their activation encodes positive value. Interestingly, it was also found that a decrease in their activity promotes turning, raising the possibility that they could bi-directionally encode value, coding for negative value with a decrease in their activity (Eschbach, 2021).
In principle, a single CN of this type could potentially be sufficient to compute integrated odor value and regulate turning, but a population of 10 CNs with similar patterns of input from positive- and negative-valence pathways was found that likely operate partially redundantly with each other. Each CN also had unique aspects of connectivity, raising the possibility that they may also encode partially complementary features and that the integrated value could be distributed across the CN population (Eschbach, 2021).
Based on these findings the following model is proposed that could explain the way in which learning could modulate innate responses to odors through a population of integrative CNs: (1) In naive animals, the CNs are activated by innately attractive odors, mainly via the LH pathway (3) when activated these neurons repress turning, which enables crawling towards an attractive odor source; (3) in naive animals the net MB drive onto these CNs is close to 0; (4) aversive learning can skew the net MB output onto CNs towards inhibition, so that aversively-conditioned odor fails to activate these neurons; (5) if CNs are not activated, turning rate remains high when crawling towards the odor; (6) without sufficient suppression of turning by an odor, the animals' ability to approach the odor source is impaired. This proposed model could explain how aversive learning suppresses approach of innately attractive odors. To fully suppress approach, multiple CNs of this class would likely need to be silenced (Eschbach, 2021).
The model presented above could readily be extended to explain how appetitive learning could enhance odor approach and how strong aversive learning could switch innate odor approach to learned avoidance. Thus, appetitive learning could skew the net MB drive towards excitation thereby repressing turning even more. In contrast, strong aversive learning could skew the conditioned odor drive towards inhibitory negative-valence MBONs so much that the inhibition would become stronger than the excitatory LH drive. The CN would then be inhibited by the aversively conditioned odor. Since inhibition of CNs promotes turning, the aversively conditioned odor could promote odor avoidance by inducing turning. Consistent with this idea, inhibitory responses to the innately attractive odor were observed in MBON-m1 and in CN-33, in some untrained individuals, and strong excitatory responses in others, proving that odor drive onto CNs can range all the way from strong excitation to inhibition. Inhibition of MBON-m1 following aversive learning in the microfluidic device was not observed, but this could be because the animals did not form a very strong aversive memory under these conditions. Testing these proposed extensions of the model will require the future development of automated single-animal training assays and calcium imaging tracking microscopes to correlate the strength of the learned behavior with the conditioned-odor response of the CNs (Eschbach, 2021).
Finally, EM reconstruction did reveal a potentially opposite population of CNs that are inhibited by MBONs of positive value. It will be interesting to test in the future whether these neurons potentially encode negative value with an increase in their activity and positive value with a decrease in their activity and regulate turning in the opposite way: promoting turning when they are activated and repressing it when they are inhibited. Having two different populations of neurons that encode value in opposite ways could further increase the dynamic range of a distributed value code (Eschbach, 2021).
This study found that many of the CNs that receive input from both MBONs and LHNs also provide direct (including CN-33) or indirect (including MBON-m1) feedback to MB modulatory neurons that provide teaching signals for learning (n = 18). In a former study, it was shown that at least some of these feedback connections are functional and can influence memory formation. For example, CN-33/FAN-7 is capable of generating an olfactory memory when it is paired with an odor. This type of connectivity is consistent with learning theories that propose that future learning is influenced by predicted value computed based on prior learning. A major role of the CNs discovered in this study may therefore be not only to organize current actions, but also to regulate learning (Eschbach, 2021).
In summary, the comprehensive synaptic-resolution architecture of the circuits downstream of the learning center output neurons presented in this study is a valuable resource for constraining future modelling and function studies of value computation, action selection, and learning (Eschbach, 2021).
Understanding neuronal representations of odor-evoked activities and their progressive transformation from the sensory level to higher brain centers features one of the major aims in olfactory neuroscience. This study investigated how odor information is transformed and represented in higher-order neurons of the lateral horn, one of the higher olfactory centers implicated in determining innate behavior, using Drosophila melanogaster. This study focused on a subset of third-order glutamatergic lateral horn neurons (LHNs) and characterized their odor coding properties in relation to their presynaptic partner neurons, the projection neurons (PNs), by two-photon functional imaging. Odors evoke reproducible, stereotypic, and odor-specific response patterns in LHNs. Notably, odor-evoked responses in these neurons are valence-specific in a way that their response amplitude is positively correlated with innate odor preferences. It is postulated that this valence-specific activity is the result of integrating inputs from multiple olfactory channels through second-order neurons. GRASP and micro-lesioning experiments provide evidence that glutamatergic LHNs obtain their major excitatory input from uniglomerular PNs, while they receive an odor-specific inhibition through inhibitory multiglomerular PNs. In summary, this study indicates that odor representations in glutamatergic LHNs encode hedonic valence and odor identity and primarily retain the odor coding properties of second-order neurons (Das Chakraborty, 2022).
Insects are the most successful taxon among the whole animal kingdom in terms of their distribution and ability to survive in a multitude of environmental conditions. Largely they rely on their olfactory sense to carry out their fundamental goal-directed behaviors, such as food navigation, mating, ovipositing, or escape from predators. The powerful ability to detect odor cues, to evaluate the information efficiently with a relatively small number of neurons and to transform the neuronal signal into an appropriate behavioral output, makes the insect olfactory system a premier model system for olfactory research. Numerous studies have investigated the neuronal representation of odors at successive neuronal layers from the periphery to higher brain levels using Drosophila melanogaster as a model organism. Although much progress has been made in understanding odor coding at the antennal lobe (AL) level, the coding strategies and processing mechanisms of higher brain centers still remain largely elusive. In this regard, the lateral horn (LH) has recently gained attention as a crucial signal processing center integrating both innate and learned behavioral information. Several studies during recent years have advanced understanding of the anatomical and functional properties of higher-order lateral horn neurons (LHNs) regarding odor processing. The generation of several LH cell-type-specific lines, characterization of polarity and neurotransmitter identity of LHNs, as well as the establishment of detailed EM connectomic datasets have led to a significant progress in the field to study the function of specific LHN classes. The LH is comprised of three categories of neurons, which include LH input neurons (LHINs, which are mainly olfactory projection neurons [PNs] along with mechanosensory, thermosensory, and gustatory neurons), LH local neurons (LHLNs), and LH output neurons (LHONs). In terms of PN-LHN connectivity, the olfactory PNs deriving from individual glomeruli of the AL form stereotyped and conserved connections with certain LHNs. Although all kinds of connections are possible, PNs having similar odor-tuning patterns are prone to target similar LHN types. Certain pairs of narrowly tuned glomeruli encoding ecologically relevant odors and eliciting specific kinds of behavior, such as courtship, aggregation, or food seeking, converge onto the same LHN types and have been shown to be overrepresented in the LH in terms of synaptic densities. Furthermore, a high amount of divergence has also been described to occur at the level of PN to LHN connectivity. Altogether, these complex connectivity patterns, in addition to direct pooling of feedforward inputs from PNs innervating different glomeruli, result in broader tuning patterns of LHNs compared to their presynaptic PNs. In addition to the observed broadly tuned LHNs, narrowly tuned LHNs also exist, which receive input from a single type of PN and which are assumed to be further modulated by odorant-selective inhibition through inhibitory neurons. Although several studies agree that odors are compartmentalized in the LH based on either their chemical identity, behavioral significance, or hedonic valence, it still remains controversial how the odor information is transformed from the PN to the LHN level and which odor features are coded by subtypes of LHNs (Das Chakraborty, 2022).
This study aimed to elucidate the odor coding and processing strategies of LHNs by investigating how a neuronal subset of particular neurotransmitter identity encodes different odor features in the LH and how this representation is correlated to their presynaptic partner neurons in the AL, the uniglomerular PNs (uPNs) and multiglomerular PNs (mPNs). Using photoactivatable GFP, diverse clusters of LHNs were first identified based on their different neurotransmitter identities, and the detailed analysis further focused exclusively on glutamatergic LHNs. Using in vivo two-photon functional imaging, several aspects of odor-evoked activity were characterized in these neurons, such as odor-specific response patterns, reproducibility of repeated stimulations, as well as stereotypy across different individuals. It was possible to successfully demonstrate that attractive and aversive odors are clearly segregated and that the response amplitudes of glutamatergic LHNs are positively correlated with the innate behavioral preference to an odor. How the excitatory input from uPNs and odor-specific inhibition from mPNs contribute to the fine-tuning of odor-specific response patterns of LHNs was further dissected. Altogether, this study demonstrates a significant role of glutamatergic LHNs regarding olfactory processing and extends knowledge about the transformation processes of neuronal information taking place from the periphery to higher brain levels, such as the LH (Das Chakraborty, 2022).
This study functionally characterizes a subset of glutamatergic higher-order neurons in the LH regarding odor coding and processing. It was demonstrated that glutamatergic LHNs respond in a reproducible, stereotypic, and odor-specific manner and these response properties emerge at the level of presynaptic uPNs. Notably, the differential activity levels of glutamatergic LHNs to attractive and aversive odors are positively correlated to the olfactory behavioral preference, indicating that these neurons are mainly tuned to attractive odors. The response features do not arise from the OSN level, but rather derive from local processing within the LH by integrating inputs from multiple olfactory channels through uPNs, which also show a valence-specific odor representation. Furthermore, laser transection experiments demonstrate that these higher-order neurons receive their major excitatory input from uPNs and an odor-specific inhibitory input from mPNs. Lastly, the data show that the observed mPN-mediated inhibition seems to be required for generating an odor-specific response map in the LH (Das Chakraborty, 2022).
A growing body of evidence suggests the existence of an anatomical and functional stereotypy in early processing centers of the insect olfactory pathway. This stereotypy becomes obvious first at the sensory neuron (OSN) level, where OSNs expressing a certain OR target and converge on a stereotypic glomerulus, resulting in a conserved spatial map in the AL between different individuals. This anatomical stereotypy was shown to be retained at the postsynaptic PN level (Das Chakraborty, 2022).
Several studies support the notion that an anatomical stereotypy might also be present at the level of the LH, particularly shown for the PN to LHN connectivity. Along this line, functional studies have demonstrated that LHNs respond in a reproducible and stereotyped manner to odors and this stereotypy is a general feature of the LH. However, how an ensemble of LHNs integrates inputs from several olfactory channels, that is, the presynaptic excitatory and inhibitory PNs, and whether each odor induces a specific and stereotyped response pattern in the LH was not clearly addressed before. In this study, it was demonstrated that each odor is represented by an odor-specific activity pattern in the LH, while the examined glutamatergic LHNs display broader tuning patterns than their presynaptic partner neurons. Although it has been assumed previously that odor specificity may not be encoded in higher-order brain centers, the findings are in accordance with a recent study by Frechter (2019), who demonstrate the existence of 33 different LH cell types exhibiting stereotypic odor response properties with increased tuning breadth than PNs. The observed odor-evoked response features of LHNs that are odor-specific but with a broader tuning breadth could be due to several reasons. First, they receive input from similarly as well as differently tuned uPNs; therefore, the topographic map of uPN axonal terminals is not clearly retained at the level of LHNs. Second, LHNs integrate inputs from multiple odor channels, for example, one LHN receives on average excitatory input from ~5.2-6.2 glomeruli. Third, both uPNs and mPNs provide input to glutamatergic LHNs and those LHNs in turn feedback onto those second-order neurons and provide feedforward information to other LHNs. This study observed that uPNs are more efficient in encoding odor identity than the glutamatergic LHNs in the LH, whereas LHNs reveal an improved categorization of odors either based on behavioral significance, 'odor scene' or chemical group. However, the distinct odor-specific response map by glutamatergic LHNs observed in this study suggests that the dimensionality of odor features might not get reduced but still retains information about the odor specificity at the third-order processing stage (Das Chakraborty, 2022).
The functional imaging recordings revealed that odor valence is encoded by glutamatergic LHNs, leading to different activation strengths and patterns for attractive and aversive odors in the LH. Although the valence code is already present at the AL level in uPNs, it could be assumed that the same valence code might be translated to the next level of higher-order neurons. However, evidence of high convergence and divergence of neurons from different sensory modalities in the LH argues against a simple translation of the valence code or odor identity to the LHN level. This observation is well in line with previous studies that have revealed that odor-evoked responses in higher brain centers are generally categorized according to certain odor features as already mentioned above. For example, using functional imaging or patch-clamp recordings of second-order olfactory neurons revealed the existence of distinct attractive and aversive odor response domains in the LH formed by uniglomerular and multiglomular projection neurons (uPNs and mPNs). Such a categorization according to hedonic valence is also visible in this study when the odor-evoked responses of glutamatergic LHNs were plotted in a PCA, taking into account the spatial response patterns as well as the intensity of activity. Although no prominent spatial domain of attractive or aversive odors was evident in the recordings, attractive odors evoked a generally stronger activity when compared to aversive odors in this subset of LHNs. A similar trend is noted in second-order uPNs. However, their response strength was neither correlated with the olfactory preference determined in behavior nor the odor response properties of LHNs. The observed significant correlation between the amount of odor-evoked activity in glutamatergic LHNs to the behavioral valence of an odor leads to a postulate that the activity strengths of higher-order olfactory neurons to odor stimulation might determine the behavioral response - an assumption that needs to be tested in future studies (Das Chakraborty, 2022).
Although this study has documented how the glutamatergic LHNs determine the innate behavioral valence, odor valence in the LH can also be achieved through learning and LHNs have also been shown to play a critical role for learned behavior. A specific class of LHNs (so-called PD2a1/b1) has been reported to mediate innate approach response in addition to learned avoidance response in an odor concentration-dependent manner. Therefore, depending upon the context, the same LHNs can mediate innate as well as learned behavior with opposing valence. Extensive interconnections between the two higher brain centers, the MB and the LH through MBONs and LHONs, signify how the MB modulates the innate olfactory pathways and the valence code in the LH (Das Chakraborty, 2022).
This study suggests that glutamatergic LHNs use different strategies to extract different features of odor information, (1) conserving the identity of an olfactory stimulus by forming an odor-specific activity map and (2) encoding the valence of an odor by integrating information from multiple olfactory channels. It is an ongoing debate regarding how neurons in the LH evaluate an odor stimulus. Gradual detection, encoding, and categorization of an odor at different olfactory processing levels can result in a simple binary choice or complex behavioral responses of an animal. The behavioral preferences are simply reflected in either to approach (positive) or to leave (negative), to copulate (positive) or to reject (negative), and to oviposit (positive) or to find another suitable oviposition site (negative) depending upon the behavioral assays. Hence, based on the context or ecological relevance, an odor can be evaluated either as 'pleasant' or 'unpleasant,' which is well reflected by the response properties of glutamatergic LHNs regarding their valence specificity and their correlation between response strength and behavioral odor preference (Das Chakraborty, 2022).
Notably, such a correlation between response intensity and behavioral preference has also been observed in previous studies, where the amplitude of food odor-evoked activity in neuropeptide F (dNPF) neurons was found to strongly correlate with food odor attractiveness. Another study that combined functional imaging with tracking of innate behavioral responses revealed that the behavioral output could be accurately predicted by a model summing up the normalized glomerular responses, in which each glomerulus contributes a small but specific part to the resulting odor preference\. At the level of the LH, LHNs then integrate the olfactory information from the glomerular responses conveyed via uPNs and mPNs. In a previous study, it was demonstrated that mPNs respond differently to attractive and aversive odors, and mediate behavioral attraction. In this context, this study complements the previous finding by showing that also uPNs display distinct valence-specific responses in the LH to attractive and aversive odors. Information from these two PN pathways becomes integrated and processed in the LH, resulting in valence-specific activities in glutamatergic LHNs, which may in turn determine the relative behavioral preference (Das Chakraborty, 2022).
mPNs inhibit the glutamatergic LHNs in an odor-selective manner, leading to an odor-specific response pattern. According to observations of this study, glutamatergic LHNs receive a stronger inhibition from mPNs in response to the odors vinegar and acetophenone than to benzaldehyde, whereas other odors, such as 2,3 butanedione, linalool, and ethyl acetate, seem not to induce an inhibition. In the absence of this inhibition, it is noted that in addition to an increased response amplitude and altered odor representation, the activity patterns of different odors became more strongly correlated and hence more similar. It is therefore conclude that the mPN-mediated selective inhibition on this glutamatergic subset of LHNs is necessary to maintain odor specificity. Along this line, a previous study has reported that mPNs provide an odor-selective input to vlpr neurons, another class of third-order LHNs. This odor-specific modulation depends on the nature of the odor and results from the stereotyped connectivity of mPNs in the AL as well as in the LH. Although this study provides evidence that uPNs are not presynaptically inhibited by mPNs, another study established that mPNs indeed inhibit uPNs in the LH, facilitating odor discrimination. In addition to uPNs and vlpr neurons, this study identifies another class of recipient neurons (glutamatergic LHNs) that receives mPN-mediated odorant-selective inhibition (Das Chakraborty, 2022).
The glutamatergic LHN population in this study comprises glutamatergic LHONs as well as LHLNs since a broad line was used that labels an ensemble of all glutamatergic LHNs. A previous study employed specific split-Gal4 lines to selectively label LHINs, LHLNs, and LHONs with different neurotransmitter identities and analyzed their connectivity using EM connectomics. By employing artificial activation of specific subsets of LHNs via CsChrimson, it was demonstrated that one class of glutamatergic LHLNs (so-called PV4a1:5) forms excitatory synapses with AV1a1 LHONs that mediate aversive behavioral responses. In the current study, since a generic Gal4-line was used to label all glutamatergic LHNs, this study could neither activate nor silence specific neuronal subsets to observe their relevance with regard to odor-guided behavior. However, when the odor response strength of LHNs was correlated to the olfactory preference, these neurons were observed to be mainly tuned to attractive odors, suggesting that they are involved in mediating approach behavior. Although it was not possible to clearly differentiate the functional properties between different populations of LHONs and LHLNs, this study provides the first understanding of how odors are integrated, transformed, and finally represented in the LH by an ensemble of glutamatergic LHNs (Das Chakraborty, 2022).
Intriguingly, the neurotransmitter identity of this class of LHNs opens up another interesting aspect: Knowing that glutamate can act as an excitatory or inhibitory neurotransmitter, as well as a coincident detector, depending upon the receptors present in the postsynaptic neurons, further experiments are needed to reveal the consequences of glutamatergic LHN input onto their postsynaptic partner neurons. Certainly, the presence of an impressive amount of vesicular glutamate in the LH points towards a significant role of glutamatergic LHNs with regard to odor coding and processing at this higher brain center (Das Chakraborty, 2022).
The Drosophila brain contains about 50 distinct morphological types of dopamine neurons. Physiological studies of Drosophila dopamine neurons have been largely limited to one brain region, the mushroom body, where they are implicated in learning. By comparison, little is known about the physiology of other Drosophila dopamine neurons. Interestingly, a recent whole-brain imaging study found that dopamine neuron activity in several fly brain regions is correlated with locomotion. This is notable because many dopamine neurons in the rodent brain are also correlated with locomotion or other movements; however, most rodent studies have focused on learned and rewarded behaviors, and few have investigated dopamine neuron activity during spontaneous (self-timed) movements. This study monitored dopamine neurons in the Drosophila brain during self-timed locomotor movements, focusing on several previously uncharacterized cell types that arborize in the superior-lateral brain, specifically the lateral horn and superior-lateral protocerebrum. It was found that activity of all of these dopamine neurons correlated with spontaneous fluctuations in walking speed, with different cell types showing different speed correlations. Some dopamine neurons also responded to odors, but these responses were suppressed by repeated odor encounters. Finally, the same identifiable dopamine neuron encode different combinations of locomotion and odor in different individuals. If these dopamine neurons promote synaptic plasticity-like the dopamine neurons of the mushroom body-then, their tuning profiles would imply that plasticity depends on a flexible integration of sensory signals, motor signals, and recent experience (Marquis, 2022).
The GABAergic system serves as a vital negative modulator in cognitive functions, such as learning and memory, while the mechanisms governing this inhibitory system remain to be elucidated. In Drosophila, the GABAergic anterior paired lateral (APL) neurons mediate a negative feedback essential for odor discrimination; however, their activity is suppressed by learning via unknown mechanisms. In aversive olfactory learning, a group of dopaminergic (DA) neurons is activated on electric shock (ES) and modulates the Kenyon cells (KCs) in the mushroom body, the center of olfactory learning. This study found that the same group of DA neurons also form functional synaptic connections with the APL neurons, thereby emitting a suppressive signal to the latter through Drosophila dopamine 2-like receptor (DD2R). Knockdown of either DD2R or its downstream molecules in the APL neurons results in impaired olfactory learning at the behavioral level. Results obtained from in vivo functional imaging experiments indicate that this DD2R-dependent DA-to-APL suppression occurs during odor-ES conditioning and discharges the GABAergic inhibition on the KCs specific to the conditioned odor. Moreover, the decrease in odor response of the APL neurons persists to the postconditioning phase, and this change is also absent in DD2R knockdown flies. Taken together, these findings show that DA-to-GABA suppression is essential for restraining the GABAergic inhibition during conditioning, as well as for inducing synaptic modification in this learning circuit. Such circuit mechanisms may play conserved roles in associative learning across species (Zhou, 2019).
Amino acids are important nutrients for animals because they are necessary for protein synthesis in particular during growth, as well as for neurotransmission. However, little is known about how animals use past experience to guide their search for amino-acid-rich food. It was reasoned that the larvae of Drosophila melanogaster are suitable for investigating this topic because they are the feeding and growth stages in the life cycle of these holometabolous insects. Specifically, whether experiencing an odour with a 20-amino-acid mixture as a semi-natural tastant during training establishes odour-tastant associative memories was investigated. Across a broad concentration range (0.01-20 mM), such an amino-acid mixture was found to have a rewarding effect, establishing appetitive memory for the odour. Surprisingly, however, manipulation of the test conditions revealed that relatively high concentrations of the amino-acid mixture (3.3 mM and higher) in addition establish aversive memory for the odour. Both these oppositely-valenced memories were then characterized in terms of their dependency on the number of training trials, their temporal stability, their modulation through starvation, and the specific changes in locomotion underlying them. Collectively, and in the light of what is known about the neuronal organization of odour-food memory in larval Drosophila, the data suggest that these memories are established in parallel. The similarity of these results to what has been reported for sodium chloride is discussed along with the possible neurogenetic bases for concentration-dependent changes in valence when these tastants are used as reinforcers (Toshima, 2019).
Olfactory learning and conditioning in the fruit fly is typically modelled by correlation-based associative synaptic plasticity. It was shown that the conditioning of an odor-evoked response by a shock depends on the connections from Kenyon cells (KC) to mushroom body output neurons (MBONs). Although on the behavioral level conditioning is recognized to be predictive, it remains unclear how MBONs form predictions of aversive or appetitive values (valences) of odors on the circuit level. This study presents behavioral experiments that are not well explained by associative plasticity between conditioned and unconditioned stimuli, and two alternative models are suggested for how predictions can be formed. In error-driven predictive plasticity, dopaminergic neurons (DANs) represent the error between the predictive odor value and the shock strength. In target-driven predictive plasticity, the DANs represent the target for the predictive MBON activity. Predictive plasticity in KC-to-MBON synapses can also explain trace-conditioning, the valence-dependent sign switch in plasticity, and the observed novelty-familiarity representation. The model offers a framework to dissect MBON circuits and interpret DAN activity during olfactory learning (Zhao, 2021).
Predicting the future from sensory input is fundamental for survival. Co-appearing stimuli can be used for improving a prediction, or for predicting important events themselves, as observed in classical conditioning. In fruit fly odor conditioning, an odor that will become the conditioned stimulus (CS), is paired with the unconditioned stimulus (US), in this study an electroshock, that triggers an avoidance behavior and in internal representation of a negative value (valence). After conditioning, and the negative value representation (although not the full unconditioned response) previously elicited by the electroshock will be reproduced by the odor itself. Classical conditioning theories posit that throughout learning the odor becomes predictive for the electroshock. During learning, the prediction error decreases, and learning stops when the predictive odor value matches the strength of the electroshock (Zhao, 2021).
Predictive olfactory learning in fruit flies is a widely recognised concept in the experimental literature, and dopaminergic neurons (DANs) in the mushroom body (MB) have been suggested to predict punishment or reward. Yet, despite the acknowledgment of its predictive nature, computational models on fruit fly conditioning are mostly guided by the formation of associations, a notion that relates more to memories rather than predictions. Similarly, the concept of predictive learning is well recognized for olfactory conditioning in insects in general, but synaptic plasticity models are not formulated in terms of explicit predictions, but rather in terms associations and correlations, with plasticity being driven by two or three factors, each representing a temporal nonlinear function of the pre- or postsynaptic activities or of a modulatory signal, sometimes combined with homeostatic plasticity. This type of associative models exist for fruit flies, locusts or honey bees. They differ from target learning, where the unconditioned stimulus sets a target that is learned to be reproduced by the conditioned stimulus. Target learning becomes predictive learning when including a temporal component. It involves a difference operation, and learning stops when the target is reached. The stop-learning feature is difficult to be reproduced by purely correlation-based associative learning, while a purely predictive model also intrinsically captures associative properties (Zhao, 2021).
Associative learning was suggested to be implemented through spike- or stimulus-timing dependent plasticity (STDP) that would underlie conditioning. STDP strengthens or weakens a synapse based on the temporal correlation between the US (electroshock) and the CS (odor), both on the neuronal time scale of 10s of milliseconds and on the behavioral time scale of 10s of seconds. Whether an association is strengthened by just repeating the pairing until the behavioral saturation is reached, or the association saturates due to a faithful prediction, however, has not been investigated in the fruit fly so far. This study shows that olfactory conditioning in Drosophila is better captured as predictive plasticity that stops when a US-imposed target is reached, rather than by correlation-based plasticity, such as STDP, that does not operate with an explicit error or a target. According to this scheme, it is only the aversive/appetitive value of the US that is predicted by the CS after faithful learning, not the US itself. Based on the common value representation in the mushroom body output neurons (MBONs), the corresponding avoidance/approach reaction as one aspect of the unconditioned response is elicited by the CS alone (Zhao, 2021).
The Drosophila olfactory system represents a unique case for studying associative /predictive learning, and the MB is known to be essential in olfactory learning. The Kenyon cells (KCs) receive olfactory input from olfactory projection neurons and form a sparse representation of an odor. The parallel axons of the Kenyon cells (KCs) project to the MB lobes, along which the compartmentalized dendritic arbors of the MB output neurons (MBONs) collect the input from a large number of KCs. Reward or punishment activates specific clusters of DANs PAM and PPL1, respectively which project to corresponding compartments of the MB lobes, modulating the activity of the MBONs and the behavioral response. Recently, a detailed mapping of the MB connectome has been accomplished for larvae and of the vertical lobe for the adult Drosophila. Several studies show that not only the feedforward modulation from DANs to MBONs, but also the feedback from MBONs to DANs play an important role in olfactory learning (Zhao, 2021).
Previous studies have given insights into the possible cellular and subcellular mechanisms of olfactory conditioning. Yet, the suggested learning rules remain correlation-based and miss the explicit predictive element postulated by the classical conditioning theories. This study presents distinctive conditioning experiments showing that olfactory learning is best explained by predictive plasticity. These experiments, in contrast, could not be reproduced by various types of correlation-based associative learning rules. A mathematical model captures the new and previous data on olfactory conditioning, including trace conditioning. The model encompasses the odor/shock encoding and the learning of the aversive odor value with the stochastic response. It is further suggested how the predictive plasticity could be implemented in the MB circuit, with MBONs encoding the value ('valence') of the odor stimulus, and DANs calculating either the error or the target that drives the KC-to-MBON plasticity. The predictive plasticity rule for the KC-to-MBON synapses is shown to be consistent with the experimental results showing the involvement of these synapses in the novelty-familiarity representation (Zhao, 2021).
This study has reconsidered classical odor conditioning in the fruit fly and presents experimental and modeling evidence showing that olfactory learning, also on the synaptic level, is better described as predictive rather than associative. The key observation is that repetitive and time-continuous odor-shock pairing stops strengthening the conditioned response after roughly 1 minute of pairing, even if the shock intensity is below the behavioral saturation level. During conditioning, the odor is learned to predict the co-applied shock stimulus. As a consequence, the odor-evoked avoidance reaction stops strengthening at a level that depends on the shock strength, irrespective of the pairing time beyond 1 min. Associative synaptic plasticity, defined by a possibly nonlinear function of the CS-US correlation strength, as suggested by STDP models, fails to reproduce the early saturation of learning (Zhao, 2021).
A simple phenomenological model for predictive plasticity is suggested according to which synapses change their strength proportionally to the prediction error. This error is expressed as a difference between the internal shock representation and the value representation of the odor. The model encompasses a description of the shock and value representation, the stochastic response behavior of individual flies, and the synaptic dynamics (using a total of 5 parameters). It faithfully reproduces the conditioning experiments (with a total of 28 data points from 3 different types of experiments) as well as previously studied trace conditioning experiments (without need for further fitting). As compared to the associative rules (Hebbian, linear and nonlinear STDP, covariance rule), the predictive plasticity rule obtained the best fits with the least number of parameters. The model was further compared by the Akaike information criterion that considers the number of parameters beside the fitting quality. This criterion yields a likelihood for the predictive plasticity rule to be the best one that is at least 7 orders of magnitude larger as compared to the other four associative rules considered (Zhao, 2021).
The same phenomenological model of predictive learning may be implemented in two versions by the recurrent MB circuitry. In both versions the MBONs code for the odor value ('valence') that drives the conditioned response. For the error-driven predictive plasticity, the DANs directly represent the shock-prediction error by comparing the shock strength with its MBON estimate, and this prediction error modulates the KC-to-MBON plasticity (see Suggested implementation of error- and target-driven predictive plasticity). For the target-driven predictive plasticity, the DANs represent the shock stimulus itself that is then provided as a target for the KC-to-MBON plasticity. In this target-driven predictive learning, the DANs may also learn to predict the shock stimulus based on the MBON feedback, preventing a fast extinction of the KC-to-MBON memory (Zhao, 2021).
Predictive plasticity for both types of implementation has its experimental support. In general, MBON activity is well recognized to encode the aversive or appetitive value of odors and to evoke the corresponding avoidance or approach behavior, while KC-to-MBON synapses were mostly shown to undergo long-term depression, but also potentiation. DAN responses are shown to be involved in both the representation of punishment and reward that drive the aversive or appetitive olfactory conditioning. This conditioning further involves the recurrent feedback from MBONs to DANs that may be negative or positive. Moreover, the connectome from the larvae and adult fruit fly MBON circuit reveals feedback projections from DANs to the presynaptic side on the KC and the postsynaptic side on the MBONs at the KC-to-MBON synaptic connection giving different handles to modulate synaptic plasticity (Zhao, 2021).
With regard to the specific implementations, the error-driven predictive plasticity is consistent with the observation that DAN activity decreases during the conditioning. The two models have opposite predictions for learning while blocking MBON activity. The error-driven predictive plasticity would yield a higher learning index (LI) while the target-driven predictive plasticity would yield a lower LI. It was also shown that some DANs increased their activity with learning while other DANs, in the same PPL1 cluster that is supposed to represent aversive valences, decreased their activity. In fact, error- and target-driven predictive plasticity may both act in concert to enrich and stabilize the representations. DAN activity would decrease in those DANs involved in error-driven predictive plasticityand increase in those involved in target-driven predictive plasticity (Zhao, 2021).
While error-driven predictive plasticity offers access to an explicit error representation in DANs, target-driven predictive plasticity has its own merits. If DANs and MBONs code for similar information, they can support a positive feedback-loop to represent a short-term memory beyond the presence of an odor or a shock, as it was observed for aversive valences in PPL1 DANs and for appetitive PAM DANs. A positive feedback-loop between MBONs and DANs is further supported by the persistent firing between these cells after a rejected courtship that may consolidate memory of the rejection, linked to a specific pheromone (Zhao, 2021).
Target-driven plasticity has further functional advantages in terms of memory retention time. Any odor-related input to the DANs, arising either through a forward hierarchy from KC48 or a recurrence via MBONs to the DANs, will extend the memory life-time in a 2-stage prediction process: the unconditioned stimulus (s) that drives the DAN activity (d) to serve as a target for the value learning in the MBONs via KC-to-MBON synapses, will itself be predicted in the DANs. Extending the memory life-time through circuit plasticity might be attractive under the light of energy efficiency, showing that long-term memory in a synapse involving de novo protein synthesis can be costly, while cheaper forms of individual synaptic memories likely have limited retention times. Moreover, distributed memory that includes the learning of an external target representation offers more flexibility, including the regulation of the speed of forgetting (Zhao, 2021).
Target-driven predictive plasticity may also explain the novelty-familiarity representation observed in the recurrent triple of KCs, DANs and MBONs. The distributed representation of valences allows for expressing temporal components of the memories. Spontaneous activity in the KCs and their downstream cells injures a minimal strength of the KC-to-MBON synapses through predictive plasticity. A novel odor that drives KCs will then also drive MBONs and, to a smaller extent (as is assumed in this study), also DANs. If the DANs that represent the target for the KC-to-MBON plasticity are only weakly activated by the odor, the KC-to-MBON synapses learn to predict this weaker activity and depress. The depression results in a repetition suppression of MBONs and the corresponding familiarization of the fly to the ongoing odor. However, when the odor is cleared away, the MBON activity induced by spontaneously active KCs via depressed synapses now becomes lower than the spontaneous DAN activity, and predictive plasticity recovers the original synaptic strength. Eventually the spontaneous MBON and DAN activites match again and the response to the originally novel odor is also recovered, as seen in the experiment (Zhao, 2021).
Olfactory learning is likely distributed across several classes of synapses in the MB. The acquisition of olfactory memories was shown to be independent of transmitter release in KC-to-MBON synapses, although the behavioral recall of these memories required the intact transmission. In fact, learning may also be supported by plasticity upstream of the MBONs such that the effect of blocking KC-to-MBON transmission during learning is behaviorally compensated. Predictive plasticity at the KC-to-MBON synapses requires the summed synaptic transmissions across all synapses to be compared with the target d, also during the memory acquisition. This type of plasticity would therefore be impaired by blocking the release (Zhao, 2021).
Distributed learning also offers flexibility in acquiring predictions from new cues. While the original Rescorla-Wagner rule would predict blocking, this has not been observed in the fruit fly. Blocking refers to the phenomenon that, if the first odor of a compound-CS is pre-conditioned, the second odor of the compound will not be learned to become predictive for the shock. Because the predictive plasticity rules are expressed at the neuronal but not at the phenomenological level, predictions about blocking will depend on the neuronal odor representation. If the two odors activate the same MBONs, blocking would be observed since the MBONs are already driven to the correct value representation by the first odor. If they activate different MBONs, however, blocking would not be observed since the MBONs of the second odor did not yet have the chance to learn the correct value during the first conditioning. Hence, since blocking has not been observed in the fruit fly, it is postulated that the odors of the compound-CS in these experiments were represented by different groups of MBONs (Zhao, 2021).
How does this model relate to the concentration-specificity and the timing-specifity of odor conditioning? First, olfactory learning was found to be specific to the odor concentration, with different concentrations changing the subjective odor identity. The response behavior was described to be non-monotonic in the odor intensity, with the strongest response for the specific concentration the flies were conditioned with. It was suggested that this may arise from a non-monotonic odor representation in the KC population as a function of odor intensity. Given such a presynaptic encoding of odor concentrations, the predictive olfactory learning in the KC-to-MBON connectivity would also inherit the concentration specificity from the odor representation in the KCs. This predictive plasticity, and also the Rescorla-Wagner model, further predicts that learning with a higher odor concentration (but the same electroshock strength) only speeds up learning, but would not change the asymptotic performance (Zhao, 2021).
Second, olfactory conditioning was also shown to depend on the timing of the shock application before or after the conditioning odor. While a shock application 30s after an odor assigns this odor an aversive valence, an appetitive valence is assigned if the shock application arises 30s before the odor presentation. Modeling the approaching behavior in the context of predictive plasticity would require duplicating this model to also represent appetitive valences, and the action selection would depend on the difference between aversive and appetitive valences. Inverting the timing of CS and US may explain 'relief learning' if a stopping electroshock would cause a decrease of the target for aversive MBONs and an increase of the target for appetitive MBONs. An odor presented after the shock would then predict the increased appetitive target and explain the relief from pain behavior, similar to the model of relief learning in humans (Zhao, 2021).
Overall, these behavioral experiments and the plasticity model for the KC-to-MBON synapses support the notion of predictive learning in olfactory conditioning, with the DANs representing either the CS-US prediction error or the prediction itself. While predictive coding is recognized as a hierarchical organization principle in the mammalian cortex that explains animal and human behavior it may also offer a framework to investigate the logic of the MB and the multi-layer MBON readout network as studied by various experimental work (Zhao, 2021).
Regulation of reward signaling in the brain is critical for appropriate judgement of the environment and self. In Drosophila, the protocerebral anterior medial (PAM) cluster dopamine neurons mediate reward signals. This study shows that localized inhibitory input to the presynaptic terminals of the PAM neurons titrates olfactory reward memory and controls memory specificity. The inhibitory regulation was mediated by metabotropic gamma-aminobutyric acid (GABA) receptors clustered in presynaptic microdomain of the PAM boutons. Cell type-specific silencing the GABA receptors enhanced memory by augmenting internal reward signals. Strikingly, the disruption of GABA signaling reduced memory specificity to the rewarded odor by changing local odor representations in the presynaptic terminals of the PAM neurons. The inhibitory microcircuit of the dopamine neurons is thus crucial for both reward values and memory specificity. Maladaptive presynaptic regulation causes optimistic cognitive bias (Yamagata, 2021).
Regulation of reward signaling in the brain is critical for maximizing positive outcomes and for avoiding futile costs of the behaviors at the same time. Across animal phyla, dopamine neurons are primarily involved in reward processing. In the fruit fly Drosophila melanogaster, a subset of dopamine neurons in the protocerebral anterior medial (PAM) cluster mediates the reinforcement property of sugar reward. In olfactory learning, dopamine input to the mushroom body (MB) causes changes in preference of a simultaneously presented odor by modulating the output of odor-representing MB intrinsic neurons, Kenyon cells (KCs). Such associative presentations of odor and electric shocks were reported to change the activity of MB-projecting dopamine neurons. Recent studies suggest that axon terminals of the dopamine neurons locally integrate olfactory inputs to function as multiple independent units, though such subcellular reward processing has yet to be examined (Yamagata, 2021).
The results of this study indicate that presynaptic modulation of the PAM neurons is a critical component for determining the magnitude of dopaminergic reward signals. Notably, abolition of the local GABAergic input to the PAM terminals not only enhanced the internal reward intensity but compromised memory specificity. These behavioral alterations can be explained by a dual physiological role of GABA-B-R3, that is, the gain control and the spatial segmentation of dopaminergic reward signals in the PAM terminals. As the behavioral traits caused by the downregulation of GABA-B-R3 are characteristic in optimism, presynaptic control of reward signals may underlie such a cognitive bias. It would be fruitful to examine if a similar subcellular modulation of punishment-mediating neurons conversely leads to the pessimistic bias (Yamagata, 2021).
The most studied form of associative learning in Drosophila consists in pairing an odorant, the conditioned stimulus (CS), with an unconditioned stimulus (US). The timely arrival of the CS and US information to a specific Drosophila brain association region, the mushroom bodies (MB), can induce new olfactory memories. Thus, the MB is considered a coincidence detector. It has been shown that olfactory information is conveyed to the MB through cholinergic inputs that activate acetylcholine (ACh) receptors, while the US is encoded by biogenic amine (BA) systems. In recent years, understanding has advanced with regard to the specific neural BA pathways and receptors involved in olfactory learning and memory. However, little information exists on the contribution of cholinergic receptors to this process. This study evaluates the proposition that, as in mammals, muscarinic ACh receptors (mAChRs; see mAChR-A ) contribute to memory formation in Drosophila. The results show that pharmacological and genetic blockade of mAChRs in MB disrupts olfactory aversive memory in larvae. This effect is not explained by an alteration in the ability of animals to respond to odorants or to execute motor programs. These results show that mAChRs in MB contribute to generating olfactory memories in Drosophila (Silva, 2015).
Different training protocols used in Drosophila have helped advance understanding of the cellular and genetic basis for learning and memory. One of the most studied and best understood is the associative learning of odors, where an odorant that has or does not has an intrinsic value for the animal (the CS) is paired with the US. Thus, the odorant acquires a new value for this animal. The type of memory generated depends on the quality of the US: while in some training protocols electric shock or aversive chemicals such as quinine or salt have been used as US to generate aversive memories, odors can also be paired with sugar to generate appetitive memories. Behavioral and genetic studies have demonstrated that this associative learning depends on the integrity of the major neuropil in the fly brain, the MB, and their principal neurons, the Kenyon Cells (KCs). Therefore, it has been accepted that the timely, coincident arrival of the information of the CS and the US to MB KCs is essential to generate new olfactory memories. This is valid not only for adult flies but also in animals at the larval stage (Silva, 2015).
The literature supports the idea that neurons containing and releasing BAs transmit the US information to the MB, both in adult flies and also in larvae. Remarkably, recent reports have advanced knowledge on the neural aminergic pathways innervating the MB, the specific receptors activated, and some of the cellular events gated by amines in KCs that could underlie the generation of new memories both in larva and the adult fly (Silva, 2015).
On the other hand, the CS is relayed to KCs through cholinergic inputs arising from the antennal lobe (AL) via the inner antennal cerebral tract. This is consistent with the idea that ACh is the main excitatory neurotransmitter in the insect brain. In mammals it is well known that ACh exerts its diverse actions by activation of the fast-acting ionotropic nicotinic receptors (nAChRs) and also metabotropic muscarinic ACh receptors (mAChRs). Ten different genes encode the different subunits for Drosophila nAChRs and although the exact subunit composition of native fly neuronal nAChRs is not known, cell physiology experiments have led to some insights on the functional properties of these channels. For instance, electrophysiological studies have shown that ACh activates ?-bungarotoxin-sensitive nAChRs underlying fast excitatory synaptic currents in Drosophila brain neurons. Moreover, it has been recently shown in an in vitro preparation that the enhancement of the AL Projection Neuron-MB synapse depends on the activity of nAChRs. Consistent with all these data, imaging studies have shown that activation of nAChRs induces an increase in intracellular calcium that mediates cellular plasticity (Silva, 2015).
On the other hand, one mAChR has been identified and cloned in Drosophila. The Drosophila mAChR shows high sequence homology to the vertebrate M1-type mAChR and accordingly it was shown to increase the metabolism of membrane phospholipids when expressed in heterologous systems. Interestingly, no information is available on the possibility that mAChRs are involved in olfactory processing in Drosophila, even though it has been shown that this receptor is highly expressed in MB. This lab has generated a new protocol to induce olfactory aversive memories in Drosophila larvae. By using this protocol, this study shows that mAChRs expressed in Drosophila MB contribute to larval olfactory aversive learning and memory (Silva, 2015).
The reciprocal training protocol regularly used in these experiments is aimed at getting a robust, reproducible memory of odors that is thought to be independent of the odorant dilutions used for training and/or memory testing, as in different sets of experiments the US-paired odorant is switched. This is different from training protocols where only one odorant is associated with an US. However, the current data show that even when using the reciprocal training protocol it is necessary to establish the adequate experimental conditions leading to an equilibrated distribution of animals exposed to the odorants in the test chamber before any training. In fact, two different experiments carried out with EA/AA dilution ratios of 10 lead to a different naïve preference: when this ratio is obtained starting from a 1:10 AA dilution, preference observed is above 60%; when a 1:100 AA dilution is used to prepare this dilution ratio, the preference observed is about 50%. This data suggests that it is important to control for naïve preference of animals for the odorants to be used in olfactory learning and memory experiments, as this complex behavior depends on the ability of animals to adequately sense and respond to odorant stimuli. Other factors that could also affect the performance of animals in this associative behavior include the presence of drugs (in the current case atropine) or the US (i.e., salt in these experiments). All these factors have been controlled in the experiments to make sure the results are indeed explained by the ability of animals to generate new memories (Silva, 2015).
The existence of one G-protein coupled metabotropic muscarinic ACh receptor (mAChR, aka mAChR-A) has been shown in Drosophila. This mAChR shows high sequence homology to vertebrate M1-type mAChRs and as expected induces the activation of PLC to modulate membrane phospholipids in heterologous systems. Recently a second mAChR was identified (a.k.a. mAChR-B). This second putative mAChR shows several differences in its amino acid sequence and pharmacological and physiological properties with all previously described vertebrate and invertebrate mAChRs, including the fact that it is not activated by muscarine or blocked by atropine or scopolamine, two well-known mAChR antagonists. Thus, it is not clear whether this is actually a mAChR. For all these reasons this study focused only on the mAChR-A (Silva, 2015).
Expression studies have shown that the mAChR is highly expressed in the adult MB and AL. Information obtained from high-throughput expression studies indicates that this receptor is also expressed in the larval CNS, although up to now there was no information on the expression of this receptor in specific larval brain regions. The current data show that the mAChR is expressed in somas and processes in the ventral nerve cord and the larval MB region, specifically in the calyx and larval MB lobes, positioning this receptor in the right place to modulate olfactory learning (Silva, 2015).
Two different but complementary approaches were used to assess the contribution of mAChRs to olfactory aversive learning in larvae. In one hand, animals were trained and tested in presence of atropine, a well-known antagonist for mAChRs. Data obtained show that these animals are unable to form an aversive olfactory memory, which suggests that mAChRs are required for memory formation. This approach does not speak of the site where mAChRs are acting to modulate memory formation, and therefore several situations could explain this result. Since cholinergic neurons convey the information of the CS to the MB, it is possible that mAChRs are presynaptically located in the AL Projection Neuron-MB synapse to modulate ACh release in the MB region, similar to what has already been suggested for nAChRs in an in vitro AL-MB synapse preparation. mAChRs could also be located in the aminergic terminals responsible for sending the information of the US to the MB, modulating this synapse. The modulation of the release of amines by cholinergic ligands is a possibility that has recently been shown in an in vitro fly brain preparation. It is also possible that mAChRs expressed in the MB neurons directly modulate the activity of these cells to induce memory formation. Since the current expression studies support this proposition, this study used a genetic approach to assess this last possibility. Remarkably, the specific expression of an RNAimAChR in MB fully inhibited the formation of new aversive olfactory memory in larvae. Altogether, these data demonstrate for the first time that mAChRs expressed in MB are required for the generation of aversive memory in Drosophila larvae (Silva, 2015).
The contribution of mAChRs in olfactory memory is something already established in other systems. For instance, it has been previously shown that mAChRs contribute to olfactory memories in honeybees. Interestingly, these data support the idea that the muscarinic receptors are only required for olfactory memory retrieval, not acquisition. Moreover, the effect of mAChRs on olfactory memory in honeybees depends specifically on the MB ?-lobe. In it not known whether mAChRs are required for specific memory phases or processes in Drosophila or if as in bees mAChRs are required in specific larval MB regions, but these are issues are currently being evaluated (Silva, 2015).
On the other hand, it has been shown that the administration of scopolamine, a nonselective antagonist for M1-M5 vertebrate mAChRs, decreases different types of memory in mammals. Moreover, data obtained in mice expressing a mutation for the M1-type mAChR show defects on memory acquisition and consolidation. Remarkably, rats treated with scopolamine in the prelimbic cortex show deficient olfactory memory. These data show that mAChRs are important contributors in the generation of memories, particularly olfactory memory, in mammals as it is in insects. The data contribute to the understanding of the molecular underpinnings of memory formation in Drosophila but further support the proposition that regardless of obvious anatomical differences, the key contributors to complex phenomenon including olfactory learning and memory are conserved from arthropods to mammals (Silva, 2015).
Fragile X mental retardation protein (FMRP) and Ataxin-2 (Atx2) are triplet expansion disease- and stress granule-associated proteins implicated in neuronal translational control and microRNA function. This study shows that Drosophila FMRP (dFMR1) is required for long-term olfactory habituation (LTH), a phenomenon dependent on Atx2-dependent potentiation of inhibitory transmission from local interneurons (LNs) to projection neurons (PNs) in the antennal lobe. dFMR1 is also required for LTH-associated depression of odor-evoked calcium transients in PNs. Strong transdominant genetic interactions among dFMR1, atx2, the deadbox helicase me31B, and argonaute1 (ago1) mutants, as well as coimmunoprecitation of dFMR1 with Atx2, indicate that dFMR1 and Atx2 function together in a microRNA-dependent process necessary for LTH. Consistently, PN or LN knockdown of dFMR1, Atx2, Me31B, or the miRNA-pathway protein GW182 increases expression of a Ca2+/calmodulin-dependent protein kinase II (CaMKII) translational reporter. Moreover, brain immunoprecipitates of dFMR1 and Atx2 proteins include CaMKII mRNA, indicating respective physical interactions with this mRNA. Because CaMKII is necessary for LTH, these data indicate that fragile X mental retardation protein and Atx2 act via at least one common target RNA for memory-associated long-term synaptic plasticity. The observed requirement in LNs and PNs supports an emerging view that both presynaptic and postsynaptic translation are necessary for long-term synaptic plasticity. However, whereas Atx2 is necessary for the integrity of dendritic and somatic Me31B-containing particles, dFmr1 is not. Together, these data indicate that dFmr1 and Atx2 function in long-term but not short-term memory, regulating translation of at least some common presynaptic and postsynaptic target mRNAs in the same cells (Sudhakaran, 2013).
Observations presented in this study lead to three significant insights into the endogenous functions of dFmr1 and Atx2 in the nervous system and their contribution to long-term synaptic plasticity. First, the data strongly indicate that both proteins function in the same pathway, namely translational control, to mediate the form of long-term memory analyzed in this study. Second, the remarkably similar effects of knocking down these proteins in LNs and PNs provide in vivo support for an emerging idea that translational control of mRNAs in both presynaptic and postsynaptic compartments of participating synapses is necessary for long-term synaptic plasticity. Finally, although both dFmr1 and Atx2 have isoforms containing prion-like, Q/N domains, the different effects of loss of Atx2 and dFmr1 on neuronal Me31B aggregates indicate important differences in the mechanisms by which the two proteins function in translational control (Sudhakaran, 2013).
The different molecular and clinical consequence of pathogenic mutations in FMRP and Atx2 encoding genes has led to largely different perspectives on their functions. Fragile X causative mutations cause reduced levels of the encoding mRNA and lower levels of FMRP, leading to increased protein synthesis and a range of pathologies evident in children and young adults. These pathologies importantly do not include the formation of inclusion bodies. In contrast, SCA-2 and amyotrophic laterosclerosis causative mutations in Atx2 result in the dominant formation of inclusion body pathologies and age-dependent degeneration of the affected neuronal types. Observations made in this article indicate that the distinctive pathologies of the two diseases have obscured common molecular functions for the two proteins in vivo (Sudhakaran, 2013).
The genetic, behavioral, and biochemical observations show (1) shared roles of the two proteins in olfactory neurons for long-term but not short-term habituation, and (2) striking transdominant genetic interactions of dfrm1 and atx2 mutations with each other as well as with miRNA pathway proteins, which is not only consistent with prior genetic and behavioral studies of the two respective proteins but also strongly indicative of a common role for the two proteins in translational repression of neuronal mRNAs. This conclusion is supported at a mechanistic level by (3) the finding that both proteins are required for efficient repression mediated by the 3' UTR of CaMKII, a 3' UTR that this study shows to be repressed by the miRNA pathway, and (4) strong evidence for in vivo biochemical interaction among dFmr1 and Atx2 and for binding of these regulatory proteins with the UTR of the CaMKII transcript that they jointly regulate. Thus, dFMR1 and Atx2 function with miRNA pathway proteins for the regulation of a dendritically localized mRNA in identified olfactory neurons (Sudhakaran, 2013).
An unexpected observation was that dFMR1 and Atx2 seemed to be necessary for LTH as well as for CaMKII reporter regulation in both inhibitory LNs and excitatory PNs of the antennal lobe (Sudhakaran, 2013).
Until recently mammalian FMRP was regarded as a postsynaptic protein, consistent with the view that translational control of mRNAs essential for long-term plasticity occurs exclusively in postsynaptic dendrites. In contrast, work in Aplysia indicated that translational control of mRNAs is required in presynaptic terminals for long-term synaptic plasticity. This conflict between vertebrate and invertebrate perspectives is beginning to be resolved by findings that (1) mammalian FMRP is present in axons and presynaptic terminals; and that (2) translational control of both presynaptic and postsynaptic mRNAs is essential for long-term plasticity of cultured Aplysia sensorimotor synapses (Sudhakaran, 2013 and references therein).
Prior studies at the Drosophila neuromuscular junction have strongly indicated presynaptic functions for dFmr1 and translational control but have also pointed to their significant postsynaptic involvement in neuromuscular junction maturation, growth, and plasticity. More direct studies of experience-induced long-term plasticity have been performed in the context of Drosophila olfactory associative memory, wherein a specific dFmr1 isoform in particular and translational control in general are necessary for long-term forms of memory. However, the incomplete understanding of the underlying circuit mechanism has made it difficult to conclude presynaptic, postsynaptic, or dual locations for dFmr1 function in long-term memory. In contrast, recent work showing an essential role for Atx2 and Me31B in PNs for LTH more strongly indicate a postsynaptic requirement for translational control mediated by these proteins; however, this did not address a potential additional presynaptic function (Sudhakaran, 2013).
The finding that dFmr1 and Atx2 are necessary in both LNs and PNs for LTH, a process driven by changes in the strength of LNâPN synapses, provides powerful in vivo support for a consensus model in which translational control on both sides of the synapse is necessary for long-term plasticity. A formal caveat is that the anatomy of LNâPN synapses in Drosophila antennal lobes remains to be clarified at the EM level. If it emerges that these are reciprocal, dendrodendritic synapses, similar to those between granule and mitral cells in the mammalian olfactory bulb, then a clear assignment of the terms 'presynaptic' and 'postsynaptic' to the deduced activities of dFmr1 and Atx2 in this context may require further experiments (Sudhakaran, 2013).
Previous studies in Drosophila have indicated a broader role for Atx2 than dFmr1 in miRNA function in nonneuronal cells. Although Atx2 is necessary for optimal repression of four miRNA sensors examined in wing imaginal disk cells, dFmr1 is not necessary for repression of any of these sensors. The resulting conclusion that dFmr1 is required only for a subset of miRNAs to function in context of specific UTRs is consistent with the observation that only a subset of neuronal miRNAs associate with mammalian FMRP and that the protein shows poor colocalization with miRNA pathway and P-body components in mammalian cells. Parallel studies have shown that Atx2 in cells from yeast to man is required for the formation of mRNP aggregates termed stress granules, which in mammalian cells also contain Me31B/RCK and FMRP. In addition, biochemical interactions between these proteins and their mammalian homologs with each other as well as with other components of the miRNA pathway have been reported. However, neither the mechanisms of Atx2-driven mRNP assembly, nor the potential role for FMRP in such assembly, have been tested in molecular detail (Sudhakaran, 2013).
The demonstration that loss of Atx2 in neurons results in a substantial depletion of Me31B-positive foci in PN cell bodies and in dendrites is consistent with Atx2 being required for the assembly of these two different (somatic and synaptic) in vivo mRNP assemblies. Thus, the mechanisms that govern their assembly, particularly of synaptic mRNPs in vivo, overlap with mechanisms used in P-body and stress granule assembly in nonneuronal cells (Sudhakaran, 2013).
The finding that loss of dFmr1 has no visible effect on these Me31B-positive foci can be explained using either of two models. A simple model is that dFmr1 is not required for mRNP assembly, a function mediated exclusively by Atx2. This would suggest that Atx2 contains one or more functional domains missing in dFmr1 that allow the multivalent interactions necessary for mRNP assembly. This is most consistent with the observation that that although dFMR1 is a component of stress granules in Drosophila nonneuronal cells, it is not required for their assembly. An alternative model would allow both dFmr1 and Atx2 to mediate mRNP assembly but posit that dFmr1 is only present on a small subset of mRNPs, in contrast to Atx2, which is present on the majority. In such a scenario, loss of dFmr1 would only affect a very small number of mRNPs, too low to detect using the microscopic methods used in this study. In the context of these models, it is interesting that both dFmr1 and Atx2 contain prion-like Q/N domains, potentially capable of mediating mRNP assembly. It is to be noted here that the dFmr1 Q/N domain, although lacking prion-forming properties, is capable of serving as a protein interaction domain enabling the assembly of dFmr1 into RNP complexes. This observation would support the view that dFmr1 may be involved in the formation of only a subset of cellular mRNP complexes. Future studies that probe the potential distinctive properties of these assembly domains may help discriminate between these models. In addition, potential interaction of Atx2 with other proteins that are involved in mRNP formation across species, like Staufen, could help to understand the mechanisms behind Atx2-dependent function in mRNP assembly (Sudhakaran, 2013).
However, the observations presented in this study clearly show that despite the remarkable similarities in the roles of dFmr1 and Atx2 for repression of CaMKII expression at synapses and the control of synaptic plasticity that underlies long-term olfactory habituation, both proteins also have distinctive molecular functions in vivo (Sudhakaran, 2013).
Mutations that affect neuronal translational control are frequently associated with neurological disease, particularly with autism and neurodegeneration. Although these clinical conditions differ substantially in their presentation, a broadly common element is the reduced ability to adapt dynamically to changing environments, a process that may require activity-regulated translational control at synapses. Taken together with others, the observations of this study suggest that there may be two routes to defective activity-regulated translation. First, as in dFmr1 mutants, the key mRNAs are no longer sequestered and repressed, leading to a reduced ability to induce a necessary activity-induced increase in their translation. Second, it is suggested that increased aggregation of neuronal mRNPs (indicated by the frequent occurrence of TDP-43 and Atx2-positive mRNP aggregates in neurodegenerative disease) may result in a pathologically hyperrepressed state from which key mRNAs cannot be recruited for activity-induced translation. Thus, altered activity-regulated translation may provide a partial explanation not only for defects in memory consolidation associated with early-stage neurodegenerative disease but also for defects in adaptive ability seen in autism spectrum disorders (Sudhakaran, 2013).
microRNAs (miRNAs) are small noncoding RNAs
that regulate gene expression post-transcriptionally. Prior studies
have shown that they regulate numerous physiological processes
critical for normal development, cellular growth control, and
organismal behavior. This study systematically surveyed 134
different miRNAs for roles in olfactory
learning and memory formation using "sponge" technology to
titrate their activity broadly in the Drosophila melanogaster
central
nervous system. At least five different miRNAs involved in memory
formation or retention were identified from this large screen,
including miR-9c,
miR-31a,
miR-305,
miR-974,
and miR-980.
Surprisingly, the titration of some miRNAs increases memory, while the
titration of others decreases memory. More detailed experiments were
performed on two miRNAs, miR-974 and miR-31a, by
mapping their roles to subpopulations of brain neurons and testing the
functional involvement in memory of potential mRNA targets through
bioinformatics and a RNA interference knockdown approach. This screen
offers an important first step toward the comprehensive identification
of all miRNAs and their potential targets that serve in gene
regulatory networks important for normal learning and memory (Busto, 2015).
Adult Drosophila melanogaster locate food resources by using distinct olfactory cues that often are associated with the fermentation of fruit. However, in addition to being an odorous food source and providing a possible site for oviposition, fermenting fruit also provides a physical substrate upon which flies can attract and court a potential mate. This study demonstrates that Drosophila adults are able to recruit additional flies to a food source by covering the exposed surface area with fecal spots, and that this recruitment is mediated via olfactory receptors (Ors). Analyses of the deposited frass material demonstrates that frass contains several previously studied pheromone components, such as methyl laurate (ML), methyl myristate (MM), methyl palmitate (MP), and 11-cis-vaccenyl acetate (cVA), in addition to several cuticular hydrocarbons (CHCs) that are known to be behaviorally active. Moreover, this study also demonstrates that adult feeding is increased in the presence of frass, although it appears that Ors are less likely to mediate this phenomenon. In summary, the frass deposited by the fly onto the fruit provides both pheromone and CHC cues that lead to increased feeding and aggregation in Drosophila. This research is the first step in examining Drosophila frass as an important chemical signature that provides information about both the sex and the species of the fly that generated the fecal spots (Keesey, 2016).
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date revised: 26 December 2021
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