109 research outputs found

    Fine Pathogen Discrimination within the APL1 Gene Family Protects Anopheles gambiae against Human and Rodent Malaria Species

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    Genetically controlled resistance of Anopheles gambiae mosquitoes to Plasmodium falciparum is a common trait in the natural population, and a cluster of natural resistance loci were mapped to the Plasmodium-Resistance Island (PRI) of the A. gambiae genome. The APL1 family of leucine-rich repeat (LRR) proteins was highlighted by candidate gene studies in the PRI, and is comprised of paralogs APL1A, APL1B and APL1C that share ≥50% amino acid identity. Here, we present a functional analysis of the joint response of APL1 family members during mosquito infection with human and rodent Plasmodium species. Only paralog APL1A protected A. gambiae against infection with the human malaria parasite P. falciparum from both the field population and in vitro culture. In contrast, only paralog APL1C protected against the rodent malaria parasites P. berghei and P. yoelii. We show that anti-P. falciparum protection is mediated by the Imd/Rel2 pathway, while protection against P. berghei infection was shown to require Toll/Rel1 signaling. Further, only the short Rel2-S isoform and not the long Rel2-F isoform of Rel2 confers protection against P. falciparum. Protection correlates with the transcriptional regulation of APL1A by Rel2-S but not Rel2-F, suggesting that the Rel2-S anti-parasite phenotype results at least in part from its transcriptional control over APL1A. These results indicate that distinct members of the APL1 gene family display a mutually exclusive protective effect against different classes of Plasmodium parasites. It appears that a gene-for-pathogen-class system orients the appropriate host defenses against distinct categories of similar pathogens. It is known that insect innate immune pathways can distinguish between grossly different microbes such as Gram-positive bacteria, Gram-negative bacteria, or fungi, but the function of the APL1 paralogs reveals that mosquito innate immunity possesses a more fine-grained capacity to distinguish between classes of closely related eukaryotic pathogens than has been previously recognized

    Anopheles Gambiae PRS1 Modulates Plasmodium Development at Both Midgut and Salivary Gland Steps

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    Background: Invasion of the mosquito salivary glands by Plasmodium is a critical step for malaria transmission. From a SAGE analysis, we previously identified several genes whose expression in salivary glands was regulated coincident with sporozoite invasion of salivary glands. To get insights into the consequences of these salivary gland responses, here we have studied one of the genes, PRS1 (Plasmodium responsive salivary 1), whose expression was upregulated in infected glands, using immunolocalization and functional inactivation approaches. Methodology/Principal Findings: PRS1 belongs to a novel insect superfamily of genes encoding proteins with DM9 repeat motifs of uncharacterized function. We show that PRS1 is induced in response to Plasmodium, not only in the salivary glands but also in the midgut, the other epithelial barrier that Plasmodium has to cross to develop in the mosquito. Furthermore, this induction is observed using either the rodent parasite Plasmodium berghei or the human pathogen Plasmodium falciparum. In the midgut, PRS1 overexpression is associated with a relocalization of the protein at the periphery of invaded cells. We also find that sporozoite invasion of salivary gland cells occurs sequentially and induces intra-cellular modifications that include an increase in PRS1 expression and a relocalization of the corresponding protein into vesicle-like structures. Importantly, PRS1 knockdown during the onset of midgut and salivary gland invasion demonstrates that PRS1 acts as an agonist for the development of both parasite species in the two epithelia, highlighting shared vector/parasite interactions in both tissues. Conclusions/Significance: While providing insights into potential functions of DM9 proteins, our results reveal that PRS1 likely contributes to fundamental interactions between Plasmodium and mosquito epithelia, which do not depend on the specific Anopheles/P. falciparum coevolutionary history

    Contrasting responses of mean and extreme snowfall to climate change

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    Snowfall is an important element of the climate system, and one that is expected to change in a warming climate. Both mean snowfall and the intensity distribution of snowfall are important, with heavy snowfall events having particularly large economic and human impacts. Simulations with climate models indicate that annual mean snowfall declines with warming in most regions but increases in regions with very low surface temperatures. The response of heavy snowfall events to a changing climate, however, is unclear. Here I show that in simulations with climate models under a scenario of high emissions of greenhouse gases, by the late twenty-first century there are smaller fractional changes in the intensities of daily snowfall extremes than in mean snowfall over many Northern Hemisphere land regions. For example, for monthly climatological temperatures just below freezing and surface elevations below 1,000 metres, the 99.99th percentile of daily snowfall decreases by 8% in the multimodel median, compared to a 65% reduction in mean snowfall. Both mean and extreme snowfall must decrease for a sufficiently large warming, but the climatological temperature above which snowfall extremes decrease with warming in the simulations is as high as −9 °C, compared to −14 °C for mean snowfall. These results are supported by a physically based theory that is consistent with the observed rain–snow transition. According to the theory, snowfall extremes occur near an optimal temperature that is insensitive to climate warming, and this results in smaller fractional changes for higher percentiles of daily snowfall. The simulated changes in snowfall that I find would influence surface snow and its hazards; these changes also suggest that it may be difficult to detect a regional climate-change signal in snowfall extremes.National Science Foundation (U.S.) (Grant AGS-1148594)United States. National Aeronautics and Space Administration (ROSES Grant 09-IDS09-0049

    Segment-Specific Neuronal Subtype Specification by the Integration of Anteroposterior and Temporal Cues

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    To address the question of how neuronal diversity is achieved throughout the CNS, this study provides evidence of modulation of neural progenitor cell “output” along the body axis by integration of local anteroposterior and temporal cues

    Contribution of Distinct Homeodomain DNA Binding Specificities to Drosophila Embryonic Mesodermal Cell-Specific Gene Expression Programs

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    Homeodomain (HD) proteins are a large family of evolutionarily conserved transcription factors (TFs) having diverse developmental functions, often acting within the same cell types, yet many members of this family paradoxically recognize similar DNA sequences. Thus, with multiple family members having the potential to recognize the same DNA sequences in cis-regulatory elements, it is difficult to ascertain the role of an individual HD or a subclass of HDs in mediating a particular developmental function. To investigate this problem, we focused our studies on the Drosophila embryonic mesoderm where HD TFs are required to establish not only segmental identities (such as the Hox TFs), but also tissue and cell fate specification and differentiation (such as the NK-2 HDs, Six HDs and identity HDs (I-HDs)). Here we utilized the complete spectrum of DNA binding specificities determined by protein binding microarrays (PBMs) for a diverse collection of HDs to modify the nucleotide sequences of numerous mesodermal enhancers to be recognized by either no or a single subclass of HDs, and subsequently assayed the consequences of these changes on enhancer function in transgenic reporter assays. These studies show that individual mesodermal enhancers receive separate transcriptional input from both I–HD and Hox subclasses of HDs. In addition, we demonstrate that enhancers regulating upstream components of the mesodermal regulatory network are targeted by the Six class of HDs. Finally, we establish the necessity of NK-2 HD binding sequences to activate gene expression in multiple mesodermal tissues, supporting a potential role for the NK-2 HD TF Tinman (Tin) as a pioneer factor that cooperates with other factors to regulate cell-specific gene expression programs. Collectively, these results underscore the critical role played by HDs of multiple subclasses in inducing the unique genetic programs of individual mesodermal cells, and in coordinating the gene regulatory networks directing mesoderm development.National Institutes of Health (U.S.) (Grant R01 HG005287

    Drosophila Araucan and Caupolican Integrate Intrinsic and Signalling Inputs for the Acquisition by Muscle Progenitors of the Lateral Transverse Fate

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    A central issue of myogenesis is the acquisition of identity by individual muscles. In Drosophila, at the time muscle progenitors are singled out, they already express unique combinations of muscle identity genes. This muscle code results from the integration of positional and temporal signalling inputs. Here we identify, by means of loss-of-function and ectopic expression approaches, the Iroquois Complex homeobox genes araucan and caupolican as novel muscle identity genes that confer lateral transverse muscle identity. The acquisition of this fate requires that Araucan/Caupolican repress other muscle identity genes such as slouch and vestigial. In addition, we show that Caupolican-dependent slouch expression depends on the activation state of the Ras/Mitogen Activated Protein Kinase cascade. This provides a comprehensive insight into the way Iroquois genes integrate in muscle progenitors, signalling inputs that modulate gene expression and protein activity

    A Machine Learning Approach for Identifying Novel Cell Type–Specific Transcriptional Regulators of Myogenesis

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    Transcriptional enhancers integrate the contributions of multiple classes of transcription factors (TFs) to orchestrate the myriad spatio-temporal gene expression programs that occur during development. A molecular understanding of enhancers with similar activities requires the identification of both their unique and their shared sequence features. To address this problem, we combined phylogenetic profiling with a DNA–based enhancer sequence classifier that analyzes the TF binding sites (TFBSs) governing the transcription of a co-expressed gene set. We first assembled a small number of enhancers that are active in Drosophila melanogaster muscle founder cells (FCs) and other mesodermal cell types. Using phylogenetic profiling, we increased the number of enhancers by incorporating orthologous but divergent sequences from other Drosophila species. Functional assays revealed that the diverged enhancer orthologs were active in largely similar patterns as their D. melanogaster counterparts, although there was extensive evolutionary shuffling of known TFBSs. We then built and trained a classifier using this enhancer set and identified additional related enhancers based on the presence or absence of known and putative TFBSs. Predicted FC enhancers were over-represented in proximity to known FC genes; and many of the TFBSs learned by the classifier were found to be critical for enhancer activity, including POU homeodomain, Myb, Ets, Forkhead, and T-box motifs. Empirical testing also revealed that the T-box TF encoded by org-1 is a previously uncharacterized regulator of muscle cell identity. Finally, we found extensive diversity in the composition of TFBSs within known FC enhancers, suggesting that motif combinatorics plays an essential role in the cellular specificity exhibited by such enhancers. In summary, machine learning combined with evolutionary sequence analysis is useful for recognizing novel TFBSs and for facilitating the identification of cognate TFs that coordinate cell type–specific developmental gene expression patterns
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