BIOLOGICAL OVERVIEW

Pointed is required for the differentiation of glial cells in the ventral nerve cord known as the CNS, and is also required downstream of Ras in the development of the eye. This discussion will deal with the role of pointed in glial differentiation. Glia are companion cells for neurons, providing a substrate for axon growth as well as nourishment, protection and insulation for mature neurons. The central nervous system has two embryonic origins: the mesectoderm, which gives rise to the ventral midline and the neuroectoderm, which gives rise to the CNS proper. Pointed is involved in glial differentiation in both these systems.

Mutations of single-minded, a gene required for the proper formation of the ventral midline, delete the glial cells that express pointed. These cells known as midline glia are absent in pointed mutants. One of two Pointed transcripts, P2, is involved in this functional determination of midline glia. pointed also affects longitudinal glia, another group of glial cells only a few cells away from midline glia. They are not 4 the VUM-neurons, suggesting that kette is expressed in neuronal midline cells. Here kette could either control neuronal development or could be involved in the actual neuron-glia interaction at the midline. But why do commissures fail to develop in pointed;kette double mutant embryos? If attraction of first commissural growth cones is mediated by signals emanating from the midline neurons, this would imply that neuronal differentiation at the midline is more defective in the double mutant, when compared to either of the single mutants. As a consequence, neuronal differentiation as well as glial differentiation in the midline must depends on pointed function. In the CNS, pointed is expressed only in glial cells and in pointed mutant embryos the VUM neurons are present and appear to project in their normal pattern. However, they fail to properly differentiate and do not express orthodenticle at high levels. It is presently unknown whether this disruption of VUM glia differentiation is due to a lack of pointed in the midline glia or depends on pointed function in the VUM support glial cells. Based on this evidence it can also be deduced that klötzchen and kästchen do not influence the development of the midline neurons but encode new components regulating glial development (Hummel, 1999b).

The following model is proposed for commissure formation. The initial growth of commissural growth cones towards the midline in stage 12 embryos is guided by an attractive signal expressed by the midline neurons. Presumably, this attraction is mediated by early Netrin expression in the midline neurons or alternatively by the action of a Schizo/Weniger attractive system. At this early developmental stage the midline glial cells are elongated in shape, contacting the epidermis with their basal side and are assumed to send out cellular processes contacting the VUM-midline neurons at the dorsal side of the nervous system. The midline glial cells express a repulsive signal that is conveyed to lateral axons via the Robo receptor and/or the karussell gene product. This repulsive function restricts the first axons to cross the midline just anterior of the VUM neurons. The midline glial cells also express a contact dependent permissive guidance cue helping the axons to cross the midline. Subsequently, neuron-glia interaction at the midline results in the migration of the midline glial cells along processes of the VUM neurons (Hummel, 1999b).

Ets transcription factor Pointed promotes the generation of intermediate neural progenitors in Drosophila larval brains

Intermediate neural progenitor (INP) cells are transient amplifying neurogenic precursor cells generated from neural stem cells. Amplification of INPs significantly increases the number of neurons and glia produced from neural stem cells. In Drosophila larval brains, INPs are produced from type II neuroblasts (NBs, Drosophila neural stem cells), which lack the proneural protein Asense (Ase) but not from Ase-expressing type I NBs. To date, little is known about how Ase is suppressed in type II NBs and how the generation of INPs is controlled. This study shows that one isoform of the Ets transcription factor Pointed (Pnt), PntP1, is specifically expressed in type II NBs, immature INPs, and newly mature INPs in type II NB lineages. Partial loss of PntP1 in genetic mosaic clones or ectopic expression of the Pnt antagonist Yan, an Ets family transcriptional repressor, results in a reduction or elimination of INPs and ectopic expression of Ase in type II NBs. Conversely, ectopic expression of PntP1 in type I NBs suppresses Ase expression the NB and induces ectopic INP-like cells in a process that depends on the activity of the tumor suppressor Brain tumor. These findings suggest that PntP1 is both necessary and sufficient for the suppression of Ase in type II NBs and the generation of INPs in Drosophila larval brains (Zhu, 2011).

This study has demonstrated that Drosophila PntP1 is a key molecule that suppresses Ase expression in type II NBs and promotes the generation of INPs. PntP1 is specifically expressed in type II NB lineages. Ectopic PntP1 expression suppresses Ase expression in type I NBs and induces ectopic INP-like cells. The generation of ectopic INP-like cells requires prior suppression of Ase in the NBs and Brat activity. Conversely, partial loss of PntP1 or inhibiting PntP1 activity results in the reduction or elimination of INPs and activation of Ase expression in type II NBs (Zhu, 2011).

How does PntP1 suppress Ase expression? Given that Pnt was known to function mainly as a transcriptional activator, it is likely PntP1 suppresses Ase expression indirectly by activating the expression of yet to be identified target genes. However, Ets family proteins with transcriptional activation activity, such as Pnt homolog Ets1, could also function as transcriptional repressors in a cell type- and promoter-dependent manner. It cannot be entirely ruled out that PntP1 acts as a transcriptional repressor to suppress Ase expression in type II NBs (Zhu, 2011).

Although results from this study as well as others suggest that suppressing Ase expression in NBs is necessary for the generation of INPs, loss of Ase expression alone in type I NB lineages does not lead to the generation of ectopic INPs. Therefore, in addition to suppressing Ase expression, PntP1 must activate other target genes to promote the generation of INPs. One of the major features that distinguish INPs from GMCs is that INPs undergo several rounds of self-renewing divisions, whereas GMCs divide terminally. Thus, among PntP1 target genes could be cell-cycle regulators that promote INPs to undergo self-renewing divisions. This finding is consistent with the well-established function of Ets transcription factors in cell-cycle control and tumorigenesis. Ets proteins stimulate cell proliferation by inducing the expression of cell-cycle regulators, such as Cyclin D1, Cdc2 kinase, and Myc. In the developing Drosophila eye disk, Pnt up-regulates the expression of String, the Drosophila homolog of Cdc25, to promote the G2-M transition. Therefore, PntP1 likely activates the expression of cell-cycle regulators to promote the self-renewing division of INPs. A partial loss of PntP1 in pntδ33 mutant clones or inhibition of PntP1 activity by Yan may lead to reduced expression of cell-cycle regulators and subsequent precocious termination of self-renewing divisions of INPs, resulting in a reduction or elimination of INPs in type II NB lineages (Zhu, 2011).

Like in type II NB lineages, the results show that the induction of INP-like cells by ectopic expression of PntP1 involves a Brat-mediated maturation process. Brat functions as a translational repressor, but exact targets of Brat in immature INPs remain unknown. The results show that when Brat is knocked down via RNAi, ectopic PntP1 expression leads to overproliferation of type II NB-like cells in type I NB lineages, similar to the phenotype observed in type II NB lineages when Brat is lost (Zhu, 2011).

However, neither ectopic PntP1 expression nor Brat knockdown alone causes similar overproliferation phenotypes in type I NB lineages. Therefore, it is possible that Brat promotes the maturation of INPs in part by translationally suppressing the expression of PntP1 target genes, particularly cell cycle-related genes, in immature INPs, thus preventing PntP1 from activating cell cycle progression in immature INPs before they fully mature (Zhu, 2011).

Although this study shows that PntP1 is able to induce the generation of ectopic INP-like cells, not every type I NB lineage ectopically expressing PntP1 produces INP-like cells. One explanation could be that additional factors may be required for the generation of INPs. These factors could be specifically expressed in type II NB lineages and function either independently, or together with PntP1 as cofactors, to promote the generation of INPs. In the absence of these factors, PntP1 promotes the generation of INPs at a much reduced efficiency. Ets transcription factors often regulate target-gene expression by recruiting other proteins. For example, Pnt interacts with Jun to induce R7 cell-fate specification in the Drosophila retina. It is possible that PntP1 needs cofactors to efficiently activate the expression of target genes that are involved in the generation of INPs. However, it is also possible that Ase and Pros in GMCs in type I NB lineages might counteract the role of PntP1 in cell-cycle progression by activating the expression of the cell-cycle inhibitor Dacapo, thus preventing the generation of self-renewing INP-like cells (Zhu, 2011).

In conclusion, this study demonstrates that PntP1 is responsible for the suppression of Ase in type II NBs and the generation of INPs. Suppression of Ase is likely a prerequisite for PntP1 to induce the generation of INPs. Furthermore, PntP1 possibly activates yet-to-be identified target genes, including cellcycle regulators, to induce the generation of INPs and to promote their self-renewing divisions. In addition, the data suggest that, at least in part, Brat promotes the maturation of INPs likely by suppressing the expression PntP1-regulated cell cycle-related genes in immature INPs, thus preventing immature INPs from entering self-renewing divisions before they fully mature (Zhu, 2011).

Cooperative recruitment of Yan via a high-affinity ETS supersite organizes repression to confer specificity and robustness to cardiac cell fate specification

Cis-regulatory modules (CRMs) are defined by unique combinations of transcription factor-binding sites. Emerging evidence suggests that the number, affinity, and organization of sites play important roles in regulating enhancer output and, ultimately, gene expression. This study investigated how the cis-regulatory logic of a tissue-specific CRM responsible for even-skipped (eve) induction during cardiogenesis organizes the competing inputs of two E-twenty-six (ETS) members: the activator Pointed (Pnt) and the repressor Yan. Using a combination of reporter gene assays and CRISPR-Cas9 gene editing, it is suggested that Yan and Pnt have distinct syntax preferences. Not only does Yan prefer high-affinity sites, but an overlapping pair of such sites is necessary and sufficient for Yan to tune Eve expression levels in newly specified cardioblasts and block ectopic Eve induction and cell fate specification in surrounding progenitors. Mechanistically, the efficient Yan recruitment promoted by this high-affinity ETS supersite not only biases Yan-Pnt competition at the specific CRM but also organizes Yan-repressive complexes in three dimensions across the eve locus. Taken together, these results uncover a novel mechanism by which differential interpretation of CRM syntax by a competing repressor-activator pair can confer both specificity and robustness to developmental transitions (Boisclair Lachance, 2018).

Development of a multicellular organism relies on tissue-specific gene expression programs to establish distinct cell fates and morphologies. The requisite patterns of gene expression must be both spatiotemporally precise and robust in the face of genetic and environmental variation; this is achieved through the action of transcription factors (TFs), whose activating and repressive inputs are integrated at the cis-regulatory modules (CRMs) or enhancers of their target genes. Consequently, the sequence of each CRM provides a physical blueprint for a combinatorial regulatory code that translates upstream signaling information into downstream gene expression. While significant advances have been made in the ability to distinguish regulatory elements from background noncoding genomic DNA and identify consensus TF-binding motifs within them, understanding of how the intrinsic logic of the cis-regulatory syntax (namely, the number, affinity, position, spacing, and orientation of binding sites) organizes the necessary set of protein-protein and protein-DNA interactions remains poor. Because single-nucleotide polymorphisms in TF-binding sites are being increasingly correlated with altered gene expression and disease susceptibility, the ability to deduce the regulatory logic of an enhancer based on its sequence is important (Boisclair Lachance, 2018).

The tendencies for TFs to cluster into superfamilies and for cells to coexpress multiple nonredundant members of the same superfamily imply that enhancer syntax must enable TFs with very similar DNA-binding preferences to compete, cooperate, and discriminate between binding sites to achieve appropriate gene expression output. Recent insight into these behaviors has come from studies of Hox family TFs. The emerging model suggests a specificity-affinity trade-off such that low-affinity sites are best discriminated, while high-affinity sites can be bound by many different Hox factors. Clustering multiple low-affinity Hox sites permits the cooperative and additive interactions needed for robust gene activation responses without compromising specificity. Whether analogous syntax rules apply to other TF superfamilies is not known, and how transcriptional repressors solve the specificity-affinity problem remains to be tested (Boisclair Lachance, 2018).

The ETS superfamily includes both activators and repressors, all of which recognize the same core DNA sequence, 5'-GGAA/T-3'. ETS TFs are found across metazoan phyla and play key roles in regulating the gene expression programs that direct many aspects of normal development and patterning. Exemplifying this, the Drosophila transcriptional activator Pointed (Pnt) and the repressor Yan operate downstream from receptor tyrosine kinase (RTK) signaling pathways to orchestrate numerous cell fate transitions. Much of the current understanding of Yan and Pnt stems from studying their regulation of even-skipped (eve) expression during cardiac muscle precursor specification at stage 11 of embryogenesis and prospero (pros) expression during R7 photoreceptor specification in the developing eye. Abrogating Pnt-mediated activation or Yan-mediated repression of eve or pros leads to respective loss or ectopic induction of the associated cell fate. Gel shift assays using probes from eve or pros CRMs revealed that most Yan-bound ETS sites are also bound by Pnt, and subsequent high-throughput assays confirm their preferences for very similar sequences. Because none of the in vitro biochemistry has been done with full-length proteins, how accurately the results will predict the outcome of Yan-Pnt competition for ETS sites in CRMs in vivo is uncertain (Boisclair Lachance, 2018).

Hints that binding site syntax might influence Yan recruitment come from in vitro binding studies with TEL1, the human counterpart of Drosophila Yan, and from mathematical modeling of Yan's ETS site occupancy. TEL1 and Yan, unlike Pnt or its mammalian counterpart, ETS1, self-associate via their sterile α motifs (SAMs), and this homotypic interaction is essential for transcriptional repression in both flies and humans. Using gel shift assays, SAM-SAM interactions were shown to mediate cooperative binding of TEL1 at paired ETS sites. A recent theoretical analysis of TEL1/Yan occupancy at equilibrium explains how such cooperative SAM-SAM interactions might promote preferential recruitment to tandem ETS-binding sites. Because neither study examined repressive output, the question of whether preferential or cooperative binding of Yan to closely apposed ETS sites might bias Yan-Pnt competition to permit more complex discrimination of CRM syntax than current models assume remains pressing (Boisclair Lachance, 2018).

To evaluate how CRM syntax organizes the opposing repressive and activating inputs from Yan and Pnt to dictate precise transcriptional output, this study assessed the impact of mutating the eight putative ETS-binding sites identified in the eve muscle heart enhancer (MHE) that drives eve expression in 10 segmentally arrayed clusters of pericardial and muscle cells. This study found that sites with strong affinity best discriminate between Yan and Pnt, with paired sites showing the strongest bias. Thus, mutating a pair of overlapping, conserved, high-affinity ETS sites significantly elevated or expanded MHE reporter expression, consistent with compromised repression. Using CRISPR/Cas9 gene editing of the endogenous MHE, it was shown that mutation of this high-affinity ETS supersite reduced Yan recruitment to not only the MHE but also two other CRMs across the eve locus. Mesodermal Eve expression was elevated, consistent with compromised Yan recruitment, resulting in inadequate repression. In this compromised background, environmental and genetic stresses that would normally be buffered against were now sufficient to induce specification of ectopic Eve-positive (Eve+) cells and reduce survival. It is concluded that the conserved high-affinity ETS pair within the MHE plays a unique and pivotal role in not just recruiting Yan-repressive complexes to the isolated enhancer but also longer-range coordination of transcriptional complex organization and function across the locus (Boisclair Lachance, 2018).

Focusing on ETS-binding motifs within a conserved regulatory module, the eve MHE, this study identified a simple syntax that allows for robust qualitative and quantitative control of enhancer output. Based on extensive mutagenesis of this enhancer, it is proposed that Yan's and Pnt's respective preferences for high- and low-affinity ETS sites provide a mechanism for integrating their competing repressive and activating inputs at individual CRMs. In particular, it was found that the use of paired strong-affinity sites appears critical to the assembly of repressive complexes that dampen eve expression in newly specified cardiac precursors where Yan levels are low and prevent ectopic eve induction in the surrounding mesoderm where levels of activating TFs such as Twi are high. CRISPR/Cas9-mediated mutation of the endogenous MHE confirmed the importance of such optimized syntax for precise Eve expression levels and uncovered an unexpected role of the ETS2,3 dual Yan-binding supersite in longer-range organization of Yan complexes across the locus. It is speculated that efficient Yan recruitment to high-affinity supersites not only influences short-range interactions at the specific enhancer but also fosters longer-range communication across multiple CRMs (Boisclair Lachance, 2018).

The unique repressive contribution of the ETS2,3 pair may reflect an unconventional form of cooperative recruitment that provides novel regulatory capabilities to Yan-repressive complexes. Specifically, even though the two sites in the ETS2,3 pair are probably too close to permit simultaneous occupancy, their immediate juxtaposition may significantly increase the probability of stable Yan binding. For example, although nothing is known about the kinetics and dynamics of Yan-DNA interactions, the presence of two overlapping high-affinity binding sites could promote stable occupancy by increasing the chance that a newly dissociated Yan molecule would immediately rebind. The syntax could also support a more organized dynamic in which the two molecules of a Yan dimer toggle back and forth rapidly between bound and unbound states at the two sites. Even more speculatively, because SAM-mediated dimerization is required for Yan-mediated repression, if the configuration of the ETS2,3 pair ensured that one molecule of the dimer was always bound, this could leave the second free to interact with either an adjacent nonspecific sequence, as was modeled previously (Hope, 2017); another high-affinity ETS site elsewhere in the MHE (for example, site 8); or, even more speculatively, an ETS motif in the D1 or D2 CRM. It is also possible that the in vivo mechanism by which full-length Yan contacts DNA is different from that suggested by the in vitro assays. For example, interactions with other TFs and cofactors might somehow mitigate the steric clash to allow simultaneous occupancy by a Yan dimer. In this case, higher-order Yan complexes (for example, trimers or tetramers) could mediate the requisite longer-range contacts. Regardless of specific mechanism, the idea that high-affinity 'supersites' might be used to anchor longer-range TF-TF and TF-DNA interactions will be an interesting direction for future investigations (Boisclair Lachance, 2018).

Previous work exploring the in vivo functionality of a Yan protein in which the SAM-SAM interface has been mutated to prevent self-association further supports the importance of SAM-mediated repressor cooperativity. Specifically, it was found that although Yan monomers are recruited to enhancers genome-wide in a pattern close to that of wild-type Yan, adequate repression does not occur, and phenotypes consistent with yan loss of function ensue (Webber, 2013a). This work also noted the prevalence of clustered high-affinity ETS sites across a number of Yan ChIP targets, suggesting that the mechanisms uncovered in the dissection of MHE ETS site syntax might be broadly applicable. Focusing on eve, it is suspected that at the resolution of individual ETS sites, in the absence of SAM-mediated cooperativity, Yan occupancy of the ETS2,3 tandem would be insufficiently stable to either compete appropriately with Pnt at the MHE or organize the necessary 3D communication across the locus (Boisclair Lachance, 2018).

A parallel is noted between the consequences of mutating the high-affinity ETS2,3 supersite in the endogenous eve locus and the findings of an earlier analysis in which three different Yan-bound CRMs were deleted within a genomic Eve-YFP BAC transgene (Webber, 2013b). In this earlier study, while deleting the pattern-driving MHE almost completely ablated mesodermal Eve-YFP induction, deleting a 'repressive' Yan-bound element (referred to as the D1) increased Eve-YFP expression ∼1.5-fold and led to the specification of extra Eve+cells. Additionally, deletion of either the MHE or the D1 in the BAC transgene reduced Yan occupancy at not only the deleted element but also the remaining intact CRMs. This study reports a comparable loss of Yan occupancy across the eve locus upon mutation of the MHE ETS2,3 supersite but only a modest increase in Eve levels and no cell fate specification defects. The discrepancy between reduced Yan occupancy and increased Eve levels in the eveMHEmut2,3 mutant relative to the D1 deletion mutant suggests that deleting an entire CRM not only compromises Yan occupancy across the locus but also disrupts additional repressive inputs. Consistent with this interpretation, the eveMHEmut2,3 background appeared highly sensitized, with the increase in Eve levels and Eve+ cell fate specification associated with a twofold increase in pnt dose almost exactly matching the effects of deleting an entire 'repressive' CRM. Further exploration of how high-affinity ETS pairs organize Yan repression at and between CRMs and how this coordinates the competing and collaborating inputs from other TFs will be needed to test these ideas at eve and, more broadly, other target genes (Boisclair Lachance, 2018).

To conclude, a working model is proposed in which Yan's and Pnt's differential interpretation of ETS syntax adds a 'dimmer' capability to the classic on/off switch, thereby refining its sensitivity and tunability. Focusing on eve as an example, prior to the onset of RTK-induced cardiac cell fate specification or in cells subject to submaximal signaling, it is suggested that Yan's bias for high-affinity sites ensures an effectively 100% probability of occupancy at the ETS2,3 supersite and hence stable repression. In this regime, Yan could also outcompete Pnt at the lower-affinity sites to occupy fully the CRM, or, if Yan levels are limiting, as the data suggest, its preference for high-affinity sites and relative 'distaste' for lower-affinity sites could offer Pnt an opportunity to occupy the latter and perhaps influence Yan repression. In contrast, if Yan and Pnt had identical ETS-binding preferences, a less tuned response to RTK signaling would be expected; indeed, when the high-affinity 2,3 pair was removed and hence the strong bias toward Yan occupancy and repression at the MHE, stochastic ectopic expression was induced in the surrounding mesoderm where RTK levels are submaximal. Thus, their distinct preferences ensure that only maximal RTK activation will trigger the necessary shift in Yan-Pnt occupancy and activity to activate eve expression. Furthermore, while previous models assumed a complete switch from total Yan occupancy to total Pnt occupancy as Eve+ cell fates are specified, this work suggests that the ETS2,3 supersite still recruits Yan-repressive input even in Eve+ cells with very low Yan concentration. It is speculated that the ability to apply continued Yan-repressive input after cell fate induction may contribute to the robustness of certain developmental transitions by stabilizing the newly acquired cell fate. In agreement with this, in the context of the endogenous eve locus, disruption of the ETS2,3 pair sensitized eve to both fluctuations in upstream signaling and environmental conditions (Boisclair Lachance, 2018).

More broadly, it is speculated that the interplay between the cis-regulatory logic of a CRM and the unique biophysical parameters of different TFs permits evolution to fine-tune gene expression output to a specific threshold depending on each cell's developmental requirement. In the case of Yan-Pnt-regulated genes, the interplay between the degree of Yan SAM-mediated self-association and ETS syntax enables this repressor-activator pair to discriminate between ETS sites with unexpected precision. Furthermore, instead of RTK activation inducing a complete switch from Yan occupancy to Pnt occupancy as cell fates are induced, the cooperative recruitment of Yan to supersites may enable newly differentiating cells with lower Yan:Pnt ratios to sustain the Yan-repressive influence needed to ensure precision and robustness of the gene expression patterns. It is suggested that these ideas provide an interesting new vantage point for considering how single-nucleotide polymorphisms in TF-binding sites may heighten susceptibility to disease by compromising the robustness of gene regulatory networks (Boisclair Lachance, 2018).

Sensory neuron lineage mapping and manipulation in the Drosophila olfactory system

Nervous systems exhibit myriad cell types, but understanding how this diversity arises is hampered by the difficulty to visualize and genetically-probe specific lineages, especially at early developmental stages prior to expression of unique molecular markers. This study used a genetic immortalization method to analyze the development of sensory neuron lineages in the Drosophila olfactory system, from their origin to terminal differentiation. This approach was applied to define a fate map of nearly all olfactory lineages and refine the model of temporal patterns of lineage divisions. Taking advantage of a selective marker for the lineage that gives rise to Or67d pheromone-sensing neurons and a genome-wide transcription factor RNAi screen, the spatial and temporal requirements for Pointed, an ETS family member, was identified in this developmental pathway. Transcriptomic analysis of wild-type and Pointed-depleted olfactory tissue reveals a universal requirement for this factor as a switch-like determinant of fates in these sensory lineages (Chai, 2019).

By combining genetic drivers labeling small subsets of precursor cells with methods for immortalization of expression patterns within defined temporal windows, this study generated a fate map of the complete peripheral Drosophila olfactory system. This resource adds a novel developmental perspective on the Drosophila olfactory circuitry, complementing the maps of glomerular innervations and PN projections to higher brain centers. While the concentric spatial organization of SOPs is partially maintained in the distribution of olfactory sensilla, there is only a limited relationship with the organization of the axon projections of OSNs in the antennal lobe. Future immortalization of additional enhancer-GAL4 drivers with restricted antennal disc expression should help improve the resolution of the fate map, and identify unique sensilla lineage markers in addition to the at1 driver. This information will be important to investigate the developmental mechanisms that act within a particular arc to specify up to 5-6 different SOP types (Chai, 2019).

Previous screening for transcriptional determinants of OSN fates identified a small set of factors that act in a combinatorial manner to activate or repress olfactory receptor expression in specific OSN classes. Such factors are likely to act only at the end of more elaborate gene regulatory networks that ensure the specification of SOP type, and determination and coordination of OSN receptor expression and axon targeting. Genome-wide, constitutive RNAi screen of transcriptional regulators has identified a large number of new molecules that are likely to function in several of these processes. This study focused on the role of the ETS homolog, Pnt, because of its unique mutant phenotype, which reveals a role in limiting, rather than determining, Or67d neuron specification. With ab at1 lineage marker (GMR82D08-GAL4, a driver that labels SOPs that exclusively produce at1 sensilla), protein expression and gain- and loss-of-function analyses, evidence is provided that this transcription factor has a switch-like function in distinguishing the terminal Svp-expressing Naa cell from its Svp-negative sibling Nab. Interestingly, this role of Pnt appears to be distinct from other functions of this transcription factor where it serves as a nuclear read-out of various MAPK signaling pathways. Antennal transcriptomic analysis indicates that this role of Pointed is likely to be universal in olfactory sensilla. Moreover, the switch-like function is not the only role of Pnt in the antenna, as it also contributes to the specification of the correct global number of SOPs, and may more directly regulate the expression of specific olfactory receptor genes (e.g., Ir84a). Pnt's broad expression in the non-neuronal sublineage suggests it could also participate in support cell development (Chai, 2019).

With the OSN lineage driver, it is now possible to exploit single-cell RNA-seq and chromatin profiling technologies to examine the gene expression and epigenetic states of the at1 lineage from birth to maturity, and how these may be influenced by internal state and environmental conditions. While cellular-resolution level transcriptomic/epigenomic data are undeniably important to understand neural development, the combination of these with methods for visualizing specific lineages in vivo is essential for a complete view of how structural and functional diversity develops in the nervous system (Chai, 2019).

Longevity is determined by ETS transcription factors in multiple tissues and diverse species

Ageing populations pose a major public health crises. Reprogramming gene expression by altering the activities of sequence-specific transcription factors (TFs) can ameliorate deleterious effects of age. This explore how a circuit of TFs coordinates pro-longevity transcriptional outcomes, which reveals a multi-tissue and multi-species role for an entire protein family: the E-twenty-six (ETS) TFs. In Drosophila, reduced insulin/IGF signalling (IIS) extends lifespan by coordinating activation of Aop, an ETS transcriptional repressor, and Foxo, a Forkhead transcriptional activator. Aop and Foxo bind the same genomic loci, and this study shows that, individually, they effect similar transcriptional programmes in vivo. In combination, Aop can both moderate or synergise with Foxo, dependent on promoter context. Moreover, Foxo and Aop oppose the gene-regulatory activity of Pnt, an ETS transcriptional activator. Directly knocking down Pnt recapitulates aspects of the Aop/Foxo transcriptional programme and is sufficient to extend lifespan. The lifespan-limiting role of Pnt appears to be balanced by a requirement for metabolic regulation in young flies, in which the Aop-Pnt-Foxo circuit determines expression of metabolic genes, and Pnt regulates lipolysis and responses to nutrient stress. Molecular functions are often conserved amongst ETS TFs, prompting examination of whether other Drosophila ETS-coding genes may also affect ageing. This study shows that five out of eight Drosophila ETS TFs play a role in fly ageing, acting from a range of organs and cells including the intestine, adipose and neurons. This study expands the repertoire of lifespan-limiting ETS TFs in C. elegans, confirming their conserved function in ageing and revealing that the roles of ETS TFs in physiology and lifespan are conserved throughout the family, both within and between species (Dodson, 2019).

Ageing is characterised by a steady systematic decline in biological function, and increased likelihood of disease. Understanding the basic biology of ageing therefore promises to help improve the overall health of older people, who constitute an ever-increasing proportion of populations. In experimental systems, healthy lifespan can be extended by altered transcriptional regulation, coordinated by sequence-specific TFs. Thus, understanding TFs' functions can reveal how to promote health in late life. Forkhead family TFs, especially Forkhead Box O (Foxo) orthologues, have been studied extensively in this context. This effort has been driven by the association of Foxo3a alleles with human longevity; and the findings that the activation of Foxos is necessary and sufficient to explain the extension of lifespan observed following reduced insulin/IGF signalling (IIS) in model organisms. Foxos interact with additional TFs in regulatory circuits, and it is in this context that their function must be understood. For example, in Caenorhabditis elegans, the pro-longevity activity of Daf-16 is orchestrated with further TFs including Hsf, Elt-2, Skn-1, Pqm-1 and Hlh-30/Tfeb. Examining regions bound by Foxos across animals has highlighted the conserved presence of sites to bind ETS family TFs. In Drosophila, two members of this family, namely Aop (a.k.a. Yan) and Pnt, have been linked to ageing via genetic interactions with Foxo and IIS, and similar interactions are evident in C. elegans. These findings raise questions of the overall roles of ETS factors in ageing, and their relationship to the activities of Foxos (Dodson, 2019).

The ETS TFs are conserved across animals, including 28 representatives in humans. Their shared, defining feature is a core helix-turn-helix DNA-binding domain, which binds DNA on 5'-GGA(A/T)-3' ETS-binding motifs (EBMs). They are differentiated by tissue-specific expression, and variation in peripheral amino acid residues which, along with variation in nucleotides flanking the core EBM, confers DNA-binding specificity. ETS TFs generally function as transcriptional activators, but a few repress transcription. Aop is one such repressor in Drosophila. Aop and its human orthologue Tel are thought to repress transcription by competing with activators for binding sites, recruiting co-repressors, and forming homo-oligomers that limit activator access to euchromatin. Consequently, Aop's role in physiology must be explored in the context of its interactions with additional TFs, especially activators. Foxo is one such activator. Both Foxo and Aop are required for longevity by IIS inhibition, each is individually sufficient to extend lifespan, and both are recruited to the same genomic loci in vivo. Whilst activating either in the gut and fat body extends lifespan, the effect of activating both is not additive. Furthermore, if Aop is knocked down, activating Foxo not only ceases to extend lifespan, but even becomes deleterious for lifespan. Overall, these findings suggest that gene expression downstream of IIS is orchestrated by the coordinated activity of Aop and Foxo, and that there is a redundancy in the function of the two TFs, even though Foxo is a transcriptional activator and Aop a transcriptional repressor. This study started by characterising Aop and its relationship with relevant transcriptional activators, including Foxo. This led revealing that roles in ageing are widespread throughout the ETS TF family, extending across multiple fly tissues and diverse animal taxa (Dodson, 2019).

Promoting healthy ageing by transcriptional control is an attractive prospect, because targeting one specific protein can restructure global gene expression to provide broad-scale benefits. This study suggests key roles for ETS TFs in such optimisation. The results show dual roles for Aop: balancing Foxo's outputs, and opposing Pnt's outputs. These functions coordinate transcriptional changes that correspond to lifespan. Repressing transcription from the ETS site appears to be the key longevity-promoting step, and indeed lifespan was extended by limiting multiple ETS TFs, in multiple fly tissues, and in multiple taxa. Altogether, these results show that inhibiting lifespan is a general feature of ETS transcriptional activators. Presumably the expression of these TFs is maintained, despite costs in late life, because of benefits in other contexts. For example, Pnt is important during development, and expression may simply run-on into adulthood. This study now shows that Pnt is also important for adults facing nutritional variation or stress, and genomic evidence suggests equivalent functions for Ets-4 in C. elegans. In addition, Ets21C is required to mount an effective immune response, and both Ets21C and Pnt control gut homeostasis. Tissue environment appears to be another important contextual factor that determines the lifespan effects of specific ETS TFs. Differences between tissues in chromatin architecture are likely to alter the capacity of a given TF to bind a given site, and the current results show that a given TF, and also upstream RTKs, do not necessarily lead to the same lifespan effect across all tissues. The tissue-specific functions that are shown for ETS TFs, Foxo and RTKs, suggests that transcription is locally coordinated by distinct receptors and TFs in distinct tissues, but that lifespan-regulatory signalling nevertheless converges on the ETS site. This differentiation makes it all the more remarkable that roles in lifespan appear to be conserved amongst ETS family TFs, even in diverse tissue contexts (Dodson, 2019).

The structure of molecular networks and their integration amongst tissues underpins phenotype, including into old age. Unravelling the basics of these networks is a critical step in identifying precise anti-ageing molecular targets. Identifying the least disruptive perturbation of these networks, by targeting the 'correct' effector, is a key goal in order to achieve desirable outcomes without undesirable trade-offs that may ensue from broader-scale perturbation. This targeting can be at the level of specific proteins, cell types, points in the life-course, or a combination of all three. The tissue-specific expression pattern of ETS TFs, and the apparent conservation of their roles in longevity, highlights them as important regulators of tissue-specific programs that may be useful in precise medical targeting of specific senescent pathologies (Dodson, 2019).

Paths and pathways that generate cell-type heterogeneity and developmental progression in hematopoiesis

Mechanistic studies of Drosophila lymph gland hematopoiesis are limited by the availability of cell-type specific markers. Using a combination of bulk RNA-Seq of FACS-sorted cells, single cell RNA-Seq, and genetic dissection, this study identified new blood cell subpopulations along a developmental trajectory with multiple paths to mature cell types. This provides functional insights into key developmental processes and signaling pathways. Metabolism is highlighted as a driver of development, graded Pointed expression is shown to allow distinct roles in successive developmental steps, and mature crystal cells are shown to specifically express an alternate isoform of Hypoxia-inducible factor (Hif/Sima). Mechanistically, the Musashi-regulated protein Numb facilitates Sima-dependent non-canonical, and inhibits canonical, Notch signaling. Broadly, it was found that prior to making a fate choice, a progenitor selects between alternative, biologically relevant, transitory states allowing smooth transitions reflective of combinatorial expressions rather than stepwise binary decisions. Increasingly, this view is gaining support in mammalian hematopoiesis (Girard, 2021).

The Drosophila lymph gland is the major hematopoietic organ that develops during the larval stages for the purpose of providing blood cells during later pupal/adult periods. Hematopoietic function for the larva itself is largely provided by a separate set of sessile or circulating blood cells outside of the lymph gland. The only time the lymph gland provides blood cells to the circulating larval hemolymph is if the larva faces a stress or immune challenge. This study entirely concentrates on the primary/anterior lobes of the lymph gland, which display the highest hematopoietic activity during normal larval development (Girard, 2021).

Past work has identified specific functional zones. The PSC (Posterior Signaling Center) is marked by expression of Antp and knot/collier (kn/col). The PSC signals progenitors that belong to the medullary zone (MZ) and are marked by domeMESO (mesodermal enhancer of domeless) and Tep4. Differentiating cells form the cortical zone (CZ), expressing Hemolectin (Hml), Peroxidasin (Pxn), lozenge (lz), and other differentiating cell markers. A narrow band of cells that are double positive for domeMESO and HmlΔ occupy the edge abutting these two zones in the early third instar, and is referred to as the intermediate zone (IZ), which contains intermediate progenitors (IPs) (Girard, 2021).

Invertebrates predate the evolution of the lymphoid system for adaptive immunity. Accordingly, Drosophila blood cells are all similar in function to cells of the vertebrate myeloid lineage. The most predominant class of blood cells, the plasmatocytes (PLs; 95% of all hemocytes), share a monophyletic relationship with vertebrate macrophages. PLs function in the engulfment of microbes and apoptotic cells, and they produce extracellular matrix proteins. A minor (2-5%), but important class is represented by crystal cells (CCs) named for their crystalline inclusions of the pro-phenoloxidase enzymes, PPO1 and PPO2. CCs are necessary for melanization, blood clot formation, immunity against bacterial infections, and to help mitigate hypoxic stress. The transcription factor Lozenge (Lz) cooperates with Notch signaling to express a number of target genes (such as hindsight/pebbled) to specify CCs, whereas the Sima (vertebrate HIF-1α) protein is required for their maintenance. The orthologue of Lz in mammals is RUNX1, with broad hematopoietic function at many developmental stages, and RUNX1 is often dysregulated in acute myeloid leukemias. The third class of blood cells, lamellocytes (<1%), is usually present only during parasitization by wasps (Girard, 2021).

In early genetic studies, the MZ appeared to consist of a fairly homogeneous group of cells, although a small number of cells clustered near the heart (dorsal vessel) are identified as pre-progenitors. More recent reports have noted considerable heterogeneity and complexity within the progenitor population. Particularly noteworthy, in this context, is the functional distinction into a Hh-sensitive and a Hh-resistant group of progenitors within the MZ (Girard, 2021).

Hematopoiesis requires complex collaborations between direct cell to cell signals (e.g., Serrate/Notch), interzonal communication (e.g., Hedgehog), signals from the neighboring cardiac tube, and systemic signals (e.g., olfactory and nutritional). An important type of interzonal signaling mechanism relevant to this paper involves multiple cell types across the zones. In brief, progenitors are maintained not only through PSC-derived signals but also through a signaling relay mediated by the differentiating cells. This backward signal from the differentiating cells to the precursors is named the Equilibrium Signal. In this process, Pvf1 (PDGF- and VEGF-related factor 1) produced by the PSC, trans-cytoses through the MZ to bind its receptor Pvr (PDGF/VEGF receptor), which is expressed at high levels in the CZ. This initiates a STAT-dependent but JAK-independent signaling cascade that ultimately leads to the secretion of the extracellular enzyme ADGF-A (adenosine deaminase-related growth factor A). This enzyme breaks down adenosine, preventing its mitogenic signal and proliferation of MZ progenitors. Acting together the niche and the backward signal maintain a balance between progenitor and differentiated cell types. The genetic studies broadly implicated the CZ cells as originators of this backward signal. Finer analysis, afforded by cell-separated bulk and single-cell RNA-Seq in this study, allows this role to be attributed to a smaller and more specific subset of cells (Girard, 2021).

RNA-Seq has been used recently as a technique to study Drosophila blood cells. Four of the cited studies analyze circulating blood cells that have a completely different developmental profile than the lymph gland. Cho (2020) utilized the lymph gland and validated its zonal structure at the level of gene expression. Additionally, new markers and sub-zones were identified. The broader picture revealed in the current work is largely consistent with Cho (2020), but several important details and interpretations vary. The results and conclusions of the two independent studies are compared and contrasted in this paper. Importantly, the primary motivation of this current study is to use the combined strategies of several RNA-Seq analyses as a tool to provide data that can be combined seamlessly with the powerful genetics available in Drosophila. This functional validation of the two approaches is an advancement over the use of transcriptomics to distinguish cell types by their expressed markers. This is a level of in vivo mechanistic analysis that is not yet available for many mammalian systems, but for which Drosophila could serve as a model. While this work also describes subzones and their characteristic markers, the primary emphasis that makes it distinct is the use of a complex strategy that allows this study to extend beyond cell type identification and to dissect mechanisms that define alternate paths and pathways that were not solvable by earlier genetic methods alone (Girard, 2021).

The novel conclusions from this analysis include a clear characterization of the IZ cells (IPs), and a demonstration of the IPs as a distinct cell type; identification of two separate transitional populations that define distinct paths between progenitors and differentiated cells fates; the role of metabolism in a zone-specific developmental program; previously uncharacterized functional aspects of transcriptional regulation by the JNK and RTK pathways; the unique mechanism of CC maturation by a novel and specific isoform of Sima identified in the RNA-Seq analysis and a previously uncharacterized interaction of this Sima isoform with Notch, Numb, and Musashi, which provides a full mechanism for CC formation and maintenance (Girard, 2021).

This combination of molecular genetics and whole genome approaches makes it clear that hematopoietic cells are far more heterogeneous and diverse than previously realized by genetics alone, and helps shift the view of hematopoiesis from being a series of discrete steps to a more continuous journey of cells with similar, but not identical transcriptomic profiles along multiple paths. The multiplicity in layers of decision points creates new routes, which can each lead to a distinct differentiated endpoint, or, alternatively, follow their parallel trajectories to a single final outcome (Girard, 2021).

The cells of the small, hematopoietic lymph gland tissue are far more complex at the genome-wide expression level than could have been anticipated by earlier marker and genetic analyses. This is now confirmed by this work, and by the earlier results of (Cho, 2020). The first step in this analysis was to separate cells by FACS based on the canonical markers that classically define each zone within the lymph gland. When probed for the presence of known 'hallmark genes,' the separated cells expressing them match up with their corresponding zones, providing early validation of the methods used. This process also allows identification of zone enriched gene expression for less well-characterized cell types, including the IZ cells (IPs), as well as immature and mature CC types (iCC and mCC). This bulk RNA-Seq approach was further extended using scRNA-Seq and genetics to identify possible combinations of markers that identify each cell type. However, the primary goal of this work is not to identify more tissue-specific hallmark genes (although several were found), but to utilize RNA-Seq as a tool with other genetic strategies to understand cell-fate specification, the multiple developmental paths available to a cell, and the mechanistic links between expression trends and developmental function. Many individual examples, and two complete case studies are presented that solve long-standing questions in Drosophila hematopoiesis (Girard, 2021).

The transcriptomic data are most useful in determining trends in the collective behavior of a set of related genes. At the core of this assertion is the fact that most developmentally relevant genes function in a context-dependent manner, and their individual expression is therefore not exclusively limited to a single cell type, but certain combinations of expressed genes could approximate their identities. Obvious exceptions are genes marking functions of terminal states such as lz or NimC1, but even in such cases, RNA expression begins in multipotent precursors and continues in the terminal cell types. The case studies presented in this work demonstrate this concept, showing that a graded expression pattern of a transcription factor allows the identification of specific phenotypes for each developmental step. Similarly, expression of an alternate isoform for the protein Sima and the RNA-binding protein Msi explains why Numb inhibits canonical Ser/Notch function but not non-canonical Sima/Notch function in the same cell type. Thus the motivation for this study is to provide multiple examples that take advantage of the ready access to genetic tools that make Drosophila a particularly attractive system in which to establish detailed mechanistic aspects of complex pathways. Based on the long history of conservation of basic principles, it is not unreasonable to expect that parallels to such mechanisms will be found in mammalian hematopoiesis (Girard, 2021).

Employing fairly conservative criteria for cluster separation in scRNA-Seq, this study identified eight primary clusters. The CCs were subclustered to yield iCC and mCC giving rise to the following nine groups of cells: a single cluster each for PSC, X (a mitosis and replication stress-related cluster), PL, and CC (subclustered into iCC and mCC). Two clusters each were identified for MZ (MZ1 and MZ2), and one for the two transitional populations (IZ and proPL). The compact arrangement of the majority of clusters implies smooth developmental transitions between them even as, from a gene-enrichment point of view, they represent different cell types. However, from a developmental biology point of view, it is the functional differences between clusters that must be used to define them as distinct cell types. It is virtually impossible to find any transcript that is 100% cell-specific, and therefore this analysis focused on trends and enrichments in transcriptional patterns. Sometimes, as in the case of pnt, the changes in expression along each developmental step can be very small, but the trend defines its multiple functions and only functional data from mutant analysis provides validation for the gene expression patterns (Girard, 2021).

RNA-Seq is by now a commonly used technique in many fields, although its first use in lymph gland hematopoiesis was relatively recent (Cho, 2020). That study identified new markers and validated the expression of a representative number of the expressed genes. A detailed comparison of the transcriptional map comparing the clusters and subclusters of Cho, with those generated in the current single-cell RNA-Seq is presented. By comparing the sizes of the clusters/subclusters, the overlapping gene lists, and the expression patterns and genetic profiles, this study found that MZ1 is similar to the PH1 and PH2 subclusters in Cho; MZ2 is similar to PH3 and PH4; IZ to PH5 and PH6; proPL to PM1; PL to PM2, PM 3, and PM4; PSC to PSC; iCC to CC1; mCC to CC2; and X is most similar to the 'GST-rich' cluster of Cho. The differences in where boundaries are drawn could arise from many sources, such as the experimental technique (drop Seq by Cho vs. 10x), genetic background (Oregon R vs. w1118), and perhaps most importantly, the computational strategy (manual curation and aggregation of the clusters based on known gene expression by Cho. vs. unsupervised graph-based clustering in this study). Both studies provide useful data. The strength of the current study is that FACS was used to sort populations defined as MZ, CZ, IZ, CC, and so on, and therefore, it is certain that the two clusters MZ1 and MZ2, for example, belong to the traditionally defined 'MZ' and the same is true for the others. The second strength is that the current strategy requires the use of multiple backgrounds and biological replicates, and the results are very consistent. Finally, given that most expression patterns represent trends rather than specific cells, and often different from the proteins they encode (such as for numb), the strongest validation of expression data, is thought to be when it is in agreement with genetic strategies based on loss of function in a subset of cells (such as with pnt or Mmp1) (Girard, 2021).

The results of this study are presented as a model of lymph gland development (see Summary of markers, case studies, and a model for the developmental progression of lymph gland cells). This analysis is based on a single time point in development but the occupancy states in pseudotime allow maturation states to be used as a form of developmental clock. The model is largely based on adjacencies, genetic compositions, and validation by mutant analysis. Transition from pre-progenitors to progenitors, then through transitional IZ or proPL populations, finally on to PLs or CCs is a continuous process traversing gradually through a permissive landscape. It does not appear to be a set of pre-programmed, quantal decisions that a cell makes based on the expression of a single fate-specifying gene. This idea is gaining increased traction in the newer reports on mammalian hematopoiesis (Girard, 2021).

The developmental trajectory for Drosophila hematopoiesis is branched, and the subdivision of 9 expression-based clusters into 22 subpopulations is based on both cell type and the trajectory state in which they reside. It is important to point out that in this context, the cluster name (e.g., MZ1 or MZ2) represents cell types distinguishable by their gene-enrichment profile, whereas the 'states' (such as MZ2-1, MZ2-2, and MZ2-3) represent the same cell type (MZ2), but appearing at different pseudo-times (1, 2, or 3). Although the analysis is a snapshot of a particular real-time point in development, many developmental steps of a single cell type are represented as progress in pseudotime. For example, the MZ2-3 state is composed of the most mature cells of the MZ2 cell type. The next transitions to either of the two separate transitional cell types, IZ or proPL, that define alternate developmental paths. The cell states MZ2-3, IZ-5, and PL-7a/b are nodes of bifurcation based on this model. Some details of the model require further functional confirmation in vivo that is beyond the scope of the current manuscript. It is anticipated that such details of cell identity will change with future refinements. However, the model provides a blueprint and a rich opportunity to study changes in signaling, cell cycle, or possible modes of cell divisions that promote alternate cell fates (Girard, 2021).

An important finding of this study is the demonstration of alternate paths that initiate with the same progenitor types and terminate in the same differentiated fate, but they traverse through distinct transitory cell types. The distinction between transitional states such as IZ and proPL would be less remarkable, if they did not also have additional unique characteristics and functions. For example, together the genetic and RNA-Seq data suggest that proPL is likely a major source of the equilibrium signal, whereas IZ largely contributes to the JNK signal. The two cell types are largely non-overlapping and virtually non-adjacent in a 3D t-SNE representation of the clusters. These alternate routes are reminiscent of the concept of progression through alternate epigenetic landscapes proposed by Waddington at the very dawn of Developmental Biology. Finally, in T cell development, there is evidence to suggest that intermediate cells bridge the major singly and doubly marked populations, but even less is known about their possible developmental roles (Girard, 2021).

Minor paths not involving either of the two major transitional states (IZ or proPL) are consistent with, but not fully established yet by the data. For instance, the earliest PL clusters (PL-3) are sandwiched between MZ2 and PL-7 with no intervening proPL or IZ cells, suggesting a direct MZ to PL path, or perhaps one that involves X as an intermediary. As another example of a minor path, a small number of iCC cells follow the path PL-7/iCC-7/iCC-6/mCC-6. The iCC-7 to iCC-6 transition is a reversal in pseudotime. Although unexpected, this supports the concepts of transdifferentiation and dedifferentiation proposed in Drosophila hematopoiesis. It will be interesting to determine in future studies if paths that are minor during homeostasis become more prominent under stress or immune challenge when a rapid and amplified response is prioritized over orderly development (Girard, 2021).

Contrary to a commonly held viewpoint, metabolic pathways are regulated in a cell-specific manner and their participation is not limited to 'housekeeping' roles during development. Indeed, data on both cancer and developmental metabolism show that selective use of such pathways can drive certain critical developmental decisions instead of the other way around (Girard, 2021).

The analysis presented in this paper demonstrates that in Drosophila hematopoiesis, cells within individual zones are not only defined by their position within the organ and the markers that they express, but also by their metabolic status that is foreshadowed by the content of their transcriptome. The PSC cells, as a group, for example, are well represented by most upper glycolysis genes that are then used, not for bioenergetic purposes, but to increase the PPP flux of glucose metabolism that aids in maintaining an NADPH/GSH-dependent low ROS status for these cells. This is important as high ROS in the PSC is a trigger for a specific immune response that must be repressed during homeostasis. Interestingly, the immediately adjacent MZ cells are lower in NADPH-forming enzymes, and their genes controlling oxidative phosphorylation are higher than in the PSC. This would lead to higher ROS even during homeostasis. Indeed, the MZ ROS levels are high and this physiological amount is essential for progenitor differentiation. A very interesting example of metabolic control is in the IZ cluster. Surprisingly, this narrow band of cells is enriched for genes required for both synthesis and clearance of free ceramide from a cell. This is important given the known role of ceramide in the activation of the JNK pathway, and genetic and immunohistochemical evidence is provided of transient activation of JNK and MMP1 in this group of cells (Girard, 2021).

Unlike cancer metabolism, developmental metabolism is at a surprisingly early phase of research, and Drosophila hematopoiesis could be a very attractive system to study this phenomenon during homeostasis. More broadly, the results point to the continued relevance of the use of Drosophila as the singular invertebrate hematopoietic model, which provides a logical framework within which to establish less-studied concepts such as the characterization of parallel transitory populations, the roles of developmental metabolism, mechanisms of unusual signaling paradigms, and genetic dissection of pleiotropy (Girard, 2021).

The Ets protein Pointed P1 represses Asense expression in type II neuroblasts by activating Tailless

Intermediate neural progenitors (INPs) boost the number and diversity of neurons generated from neural stem cells (NSCs) by undergoing transient proliferation. In the developing Drosophila brains, INPs are generated from type II neuroblasts (NBs). In order to maintain type II NB identity and their capability to produce INPs, the proneural protein Asense (Ase) needs to be silenced by the Ets transcription factor pointed P1 (PntP1), a master regulator of type II NB development. However, the molecular mechanisms underlying the PntP1-mediated suppression of Ase is still unclear. This study utilized genetic and molecular approaches to determine the transcriptional property of PntP1 and identify the direct downstream effector of PntP1 and the cis-DNA elements that mediate the suppression of ase. The results demonstrate that PntP1 directly activates the expression of the transcriptional repressor, Tailless (Tll), by binding to seven Ets-binding sites, and Tll in turn suppresses the expression of Ase in type II NBs by binding to two hexameric core half-site motifs. This study further showa that Tll provides positive feedback to maintain the expression of PntP1 and the identity of type II NBs. Thus, thus this study identifies a novel direct target of PntP1 and reveals mechanistic details of the specification and maintenance of the type II NB identity by PntP1 (Chen, 2022).

This study has dissected the molecular mechanism of how PntP1 suppresses Ase expression to specify the type II NB identity. PntP1 was demonstrated to acts as a transcriptional activator to indirectly suppress Ase expression by activating Tll, whereas Tll provides positive feedback to maintain the expression of PntP1 and the type II NB identity. The cis-elements that mediate the suppression of Ase by Tll and the activation of Tll by PntP1 were mapped. Thus, this work reveals mechanistic details of PntP1-mediated suppression of Ase expression and specification of type II NBs and identifies a novel direct target of PntP1 in type II NBs (Chen, 2022).

This study has demonstrated that PntP1 functions as a transcriptional activator by showing that the artificial chimeric repressor protein EnR-Ets antagonizes the function of endogenous PntP1 proteins when expressed in type II NB lineages and that the artificial chimeric activator proteins VP16AD-pntP1^1/2C-Ets could functionally mimic endogenous PntP1 protein when expressed in type I NBs. These results are in line with a previous in vitro study showing that PntP1 substantially activates bacterial chloramphenicol acetyltransferase (CAT) reporter expression under the control of Ets binding sites. Interestingly, the results show that the chimeric protein VP16AD-Ets is not sufficient to functionally mimic endogenous PntP1 proteins even though the Ets domain can bind to PntP1 target DNAs as demonstrated by the antagonization of PntP1's function by the EnR-Ets protein. Only when the C-terminal sub-fragment (aa. 256-511) of PntP1 is included can the chimeric activator protein functionally mimic endogenous PntP1 proteins. The Ets family proteins usually recruit additional cofactors to activate/repress target gene expression. This C-terminal fragment likely contains protein-protein interaction domains that are essential to recruit its cofactors. Since neither the pntP1^1/2C-Ets truncated protein nor the chimeric protein VP16AD-pntP1^1/2N-Ets is able to mimic wild type PntP1 protein's function, it is unlikely that this C-terminal sub-fragment contains the activation domain of PntP1 and the other N-terminal sub-fragment [pntP1^1/2N] contains the protein-protein interaction domains instead. Otherwise, with the VP16AD functioning as an activation domain and the N-terminal sub-fragment recruiting cofactors, the chimeric VP16AD-pntP1^1/2N-Ets protein would be able to functionally mimic wild type PntP1 protein. Given that a large number of Ets family transcription factors share highly conserved Ets domains but have diverse functions and activities in distinct cell types, the C-terminal sub-fragment of PntP1 may recruit cell-type-specific cofactors to regulate the expression of specific target genes in type II NB lineages, such as Erm and Tll, as it has been proposed as a general strategy for Ets family proteins to regulate the expression of tissue-specific target genes. However, the regions of PntP1 subfragments that was included in chimeric repressor/activator constructs were arbitrarily defined. The results do not tell the precise boundaries of the activation domains or potential protein-protein interaction domains. To precisely map these functional domains will require more detailed and systemic analyses in the future (Chen, 2022).

PntP1 performs diverse functions in different cell types in type II NB lineages. For example, in type II NBs, PntP1 is required to suppress Ase expression. In newly generated imINPs, PntP1 prevents premature differentiation of INPs, whereas late during imINP development, it promotes INP cell fate commitment and prevents dedifferentiation of imINPs. Therefore, as a transcriptional activator, PntP1 must activate the expression of many different target genes in type II NB lineages. However, Erm is the only direct target that has been identified previously. This study identified Tll as another direct target of PntP1 that functions primarily in type II NBs to suppress Ase expression. PntP1 is both necessary and sufficient for Tll expression. Seven putative binding sites were identified and EMSAs and ChIP-qPCR assays verified that all these sites can bind to PntP1 both in vitro and in vivo. Although ChIP-qPCR was done using type II NB-enriched DNAs isolated from Brat knockdown larval brains, it is unlikely the results are artifacts. A previous study has demonstrated that type II NB-enriched chromatin isolated from brat mutant larval brains maintains similar transcriptional status for multiple genes examined, including pntP1, as in wild type type II NBs. Furthermore, Brat mainly functions as an RNA-binding protein in the imINPs to promote degradation of mRNAs of self-renewing genes such as dpn and klu. Therefore, loss of Brat unlikely affects the binding of PntP1 to its target DNAs in type II NBs, but this possibility was not fully verified particularly because the supernumerary type II NBs in Brat knockdown brains are derived from dedifferentiation of imINPs and it has never been extensively evaluated whether the dedifferentiated type II NBs have the exact same gene expression profiles as wild type type II NBs. It might be helpful to further verify the results by single-cell ChIP using isolated wild type type II NBs. However, since the bioinformatic prediction of PntP1 binding sites was limited to the enhancer region R31F04, it is not certain whether any additional PntP1 binding sites exist outside this enhancer region and contribute the activation of tll by PntP1. In any event, the seven binding sites identified within this enhancer region are sufficient for tll to be activated by PntP1 in type II NBs as demonstrated by the specific expression of R31F04-GAL4 in type II NBs (Chen, 2022).

This work further demonstrates that Tll is the direct target of PntP1 that mediates the suppression of Ase in type II NBs by showing that simultaneous knockdown of Tll essentially blocks the suppression of Ase by misexpressed PntP1 in type I NBs. By fine mapping the cis-repressive elements in ase regulatory regions, two Tll binding sites were idnetified located at -1,292bp ~ - 1,262bp upstream of the ase TSS, consistent with a recent study showing that Tll binds to a 5-kb region upstream of the ase TSS [21]. Although the core hexameric sequences of these two binding sites are not exactly the same as the typical Tll binding hexamer 5'-AAGTCA, EMSA results demonstrate that Tll can indeed bind to these sites either as a monomer or a homodimer, the latter of which is common for orphan nuclear receptors (Chen, 2022).

In addition to PntP1 binding sites, other studies report that Suppressor of Hairless [Su(H)], a binding partner of the intracellular domain of Notch, and Zelda (Zld) also bind to the enhancer region of tll, implicating that Notch and Zld could be upstream activator of Tll. However, Su(H) and Zld are not just expressed in type II NBs but also in type I NBs. Thus, Su(H) and Zld are unlikely to be sufficient to activate Tll, but whether PntP1 acts together with Su(H) and Zld to activate Tll in type II NBs is worth further investigation (Chen, 2022).

A previous study shows that PntP1 is expressed not only in type II NBs but also strongly in imINPs. However, Tll is primarily expressed in type II NBs but only very weakly in imINPs, and ectopic expression of Tll in imINPs reverts imINPs to type II NBs. Therefore, there must be a mechanism to inhibit the activation of Tll by PntP1 in imINPs. A recent study proposed that Erm and Hamlet (Ham) function sequentially to suppresses Tll expression in imINPs based on 1) decreasing or increasing the copy number of the tll gene suppresses or enhances the supernumerary type II NB phenotype in ham erm double heterozygous mutants, respectively; and 2) overexpressing Erm or Ham in type II NBs inhibits the expression of Tll in type II NBs. However, these data could be also explained by changes in the expression of PntP1 as it is demonstrated in this study that there is a positive feedback loop between PntP1 and Tll. For example, the reduction in the Tll expression resulting from Erm overexpression in type II NBs could be due to inhibition of PntP1 by Erm in type II NB as was reported previously rather than direct inhibition of Tll by Erm. Furthermore, Erm and Ham are not expressed in the newly generated imINPs, in which Tll expression is already largely suppressed. Therefore, the suppression of Tll in the newly generated imINPs cannot be explained by the inhibition by Erm and Ham. Other mechanisms are likely involved in suppressing Tll in imINPs (Chen, 2022).

The current results not only demonstrate that PntP1 is a direct upstream activator of Tll but also show that Tll is required to maintain PntP1 expression in type II NBs. Therefore, there is a positive feedback loop between PntP1 and Tll that is essential for maintaining the type II NB identity. Considering that PntP1 misexpression induces Tll expression in all type I NBs and generation of mINPs in a subset of type I NB lineages, whereas Tll misexpression induces PntP1 expression only in a small subset of type I NB lineages and does not induce the generation of mINPs, it is thought that PntP1 functions as a master regulator of type II NB lineage development and acts upstream of Tll, which in turn suppresses Ase expression in type II NBs. Since Tll mainly functions as a transcriptional repressor as was also demonstrated in this study, it is unlikely that Tll directly activates PntP1 expression. A previous study suggests that there might be an unknown feedback signal from INPs that could be required for maintaining PntP1 expression. Thus, one potential explanation for the loss of PntP1 expression in Tll knockdown type II NBs could be the loss of INPs and their feedback signal resulting from the ectopic Ase expression in type II NBs. However, since Tll misexpression is able to induce PntP1 expression albeit only in a small subset of type I NBs, it is more likely that Tll suppresses the expression of another unknown transcriptional repressor that is normally suppressed by Tll in type II NBs. When Tll is knocked down, this unknown transcriptional repressor could be turned on in type II NBs to suppress PntP1 expression. Whereas in type I NBs, this unknown repressor may be normally expressed to suppress PntP1 expression and misexpression of Tll may relieve the suppression of PntP1 expression (Chen, 2022).

The GAL4 reporter assays also identified in the ase enhancer region a ~50-bp fragment that is sufficient for activating Ase expression in both type I and type II NBs. Earlier studies show that the Achaete-Scute (AS-C) complex proteins together with Daughterlesss (Da) activate Ase expression in NBs during the initial specification of NBs at embryonic stages by directly binding to four E-boxes in the 5'-UTR of ase. But how Ase is maintained in NBs once they are specified is not known. The current study identified a distinct enhancer region for activating/maintaining Ase expression in NBs, suggesting that factor(s) other than the AS-C proteins may be involved in activating/maintaining Ase expression in NBs after they are specified. Therefore, the lack of Ase expression in type II NBs is not because of the absence of an activation mechanism, but rather this activation mechanism is actively suppressed by Tll. Identifying the transcriptional activator(s) involved in activating/maintaining Ase expression after NBs are specified may shed a new light on the mechanisms regulating the development and maintenance of type I and type II NBs (Chen, 2022).

GENE STRUCTURE

TRANSCRIPT #1 (P1)

Amino Acids - 623

Bases in 5' UTR - 1046

Exons - four: the first is not shared with transcript #2 and encodes 229 amino acids.

Bases in 3' UTR - 233

TRANSCRIPT #2 (P2)

Bases in 5' UTR - 775

Exons - eight exons, spanning over 50 kb. The first five are not shared with transcript #1 and encode 324 amino acids.

Bases in 3' UTR - 233

PROTEIN STRUCTURE

Amino Acids 718

Structural Domains

Pointed has an ETS oncogene domain and a second evolutionally conserved domain, the pointed domain, present in the N-terminal region of P2 but not P1. The pointed domain is shared with murine ETS 1, GA binding protein alpha, and other ETS homologs (Klambt, 1993).

Homology of Pointed ETS domain to mouse or human ELK 1 is 95% in the central ETS domain (Klambt, 1993).

Genetic analysis of lin-1 loss-of-function mutations suggests that lin-1 controls multiple cell-fate decisions during Caenorhabditis elegans development and is negatively regulated by a conserved receptor tyrosine kinase-Ras-ERK mitogen-activated protein (MAP) kinase signal transduction pathway. LIN-1 protein contains an ETS domain and presumably regulates transcription. The vertebrate proteins Elk-1, SAP-1a, and Net/ERP/SAP-2 are classified as members of the Elk subfamily of ETS proteins because they share three regions of significant sequence conservation: an N-terminal ETS domain, a centrally positioned B box, and a C-terminal C box. Based on the positions and sequences of their ETS domains and the positions and sequences of regions similar to the C box, it is proposed that LIN-1 and Drosophila Aop are both members of the Elk subfamily. The ETS domain of LIN-1 shares more sequence identity with the ETS domain of human Elk-1 (67% identity) and human SAP-1a (61% identity) than with any other ETS domain. Likewise, the ETS domain of Aop is most similar to the ETS domain of Elk-1 (51% identity). The ETS domains of LIN-1 and Aop are somewhat less similar (41% identity). LIN-1 (441 residues), Elk-1 (428 residues), SAP-1a (453 residues) and Net (409 residues) are similarly sized and have ETS domains similarly positioned in the N-terminal region. By comparison, Aop (688 residues) is larger and has more residues N-terminal to the ETS domain, which is located near the center of the protein. However, the number of residues C-terminal to the ETS domain is similar among all five proteins analyzed. Sequence similarity outside the ETS domain provides further evidence that ETS proteins are members of a subfamily. By studying the C termini of these proteins, it was found that LIN-1, Elk-1, SAP-1a, and Net each have the sequence FQFP, while Aop has the sequence FQFHP. In Elk-1, SAP-1a, and Net, the FQFP sequence is at the end of the C box. The C boxes of ELK-1, SAP-1a, and Net are characterized by five or six S/TP sequences, which are potential MAP kinase phosphorylation sites. In the corresponding regions, LIN-1 has five S/TP sequences and Aop has three. Elk-1, SAP-1a, and Net have additional identities in the C box that are not conserved in LIN-1 and Aop. These observations suggest that LIN-1 and Aop contain divergent C boxes. Thus, lin-1, aop, elk-1, sap-1, and net appear to be derived from an ancestral gene that encoded a protein with an N-terminal ETS domain and a C-terminal C box (Jacobs, 1998 and references).

The Pointed (PNT) domain and an adjacent mitogen-activated protein (MAP) kinase phosphorylation site are defined by sequence conservation among a subset of ets transcription factors and are implicated in two regulatory strategies: protein interactions and posttranslational modifications, respectively. By using NMR, the structure of a 110-residue fragment of murine Ets-1 has been determined that includes the PNT domain and MAP kinase site. The Ets-1 PNT domain forms a monomeric five-helix bundle. The architecture is distinct from that of any known DNA- or protein-binding module, including the helix-loop-helix fold proposed for the PNT domain of the ets protein TEL. The MAP kinase site is in a highly flexible region of both the unphosphorylated and phosphorylated forms of the Ets-1 fragment. Phosphorylation alters neither the structure nor monomeric state of the PNT domain. These results suggest that the Ets-1 PNT domain functions in heterotypic protein interactions and support the possibility that target recognition is coupled to structuring of the MAP kinase site (Slupsky, 1998).

date revised:  5 August 2023

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