Cholinergic neurons trigger epithelial Ca2+ currents to heal the gut.

A fundamental and unresolved question in regenerative biology is how tissues return to homeostasis after injury. Answering this question is essential for understanding the aetiology of chronic disorders such as inflammatory bowel diseases and cancer1. We used the Drosophila midgut2 to investigate this and discovered that during regeneration a subpopulation of cholinergic3 neurons triggers Ca2+ currents among intestinal epithelial cells, the enterocytes, to promote return to homeostasis. We found that downregulation of the conserved cholinergic enzyme acetylcholinesterase4 in the gut epithelium enables acetylcholine from specific Egr5 (TNF in mammals)-sensing cholinergic neurons to activate nicotinic receptors in innervated enterocytes. This activation triggers high Ca2+, which spreads in the epithelium through Innexin2-Innexin7 gap junctions6, promoting enterocyte maturation followed by reduction of proliferation and inflammation. Disrupting this process causes chronic injury consisting of ion imbalance, Yki (YAP in humans) activation7, cell death and increase of inflammatory cytokines reminiscent of inflammatory bowel diseases8. Altogether, the conserved cholinergic pathway facilitates epithelial Ca2+ currents that heal the intestinal epithelium. Our findings demonstrate nerve- and bioelectric9-dependent intestinal regeneration and advance our current understanding of how a tissue returns to homeostasis after injury.

Transcriptional programs mediating neuronal toxicity and altered glial-neuronal signaling in a Drosophila knock-in tauopathy model.

Missense mutations in the gene encoding the microtubule-associated protein TAU (current and approved symbol is MAPT) cause autosomal dominant forms of frontotemporal dementia. Multiple models of frontotemporal dementia based on transgenic expression of human TAU in experimental model organisms, including Drosophila, have been described. These models replicate key features of the human disease but do not faithfully recreate the genetic context of the human disorder. Here we use CRISPR-Cas-mediated gene editing to model frontotemporal dementia caused by the TAU P301L mutation by creating the orthologous mutation, P251L, in the endogenous Drosophila tau gene. Flies heterozygous or homozygous for Tau P251L display age-dependent neurodegeneration, display metabolic defects, and accumulate DNA damage in affected neurons. To understand the molecular events promoting neuronal dysfunction and death in knock-in flies, we performed single-cell RNA sequencing on approximately 130,000 cells from brains of Tau P251L mutant and control flies. We found that expression of disease-associated mutant tau altered gene expression cell autonomously in all neuronal cell types identified. Gene expression was also altered in glial cells, suggestive of non-cell-autonomous regulation. Cell signaling pathways, including glial-neuronal signaling, were broadly dysregulated as were brain region and cell type-specific protein interaction networks and gene regulatory programs. In summary, we present here a genetic model of tauopathy that faithfully recapitulates the genetic context and phenotypic features of the human disease, and use the results of comprehensive single-cell sequencing analysis to outline pathways of neurotoxicity and highlight the potential role of non-cell-autonomous changes in glia.

PANGEA: a new gene set enrichment tool for Drosophila and common research organisms.

Gene set enrichment analysis (GSEA) plays an important role in large-scale data analysis, helping scientists discover the underlying biological patterns over-represented in a gene list resulting from, for example, an 'omics' study. Gene Ontology (GO) annotation is the most frequently used classification mechanism for gene set definition. Here we present a new GSEA tool, PANGEA (PAthway, Network and Gene-set Enrichment Analysis; https://www.flyrnai.org/tools/pangea/), developed to allow a more flexible and configurable approach to data analysis using a variety of classification sets. PANGEA allows GO analysis to be performed on different sets of GO annotations, for example excluding high-throughput studies. Beyond GO, gene sets for pathway annotation and protein complex data from various resources as well as expression and disease annotation from the Alliance of Genome Resources (Alliance). In addition, visualizations of results are enhanced by providing an option to view network of gene set to gene relationships. The tool also allows comparison of multiple input gene lists and accompanying visualisation tools for quick and easy comparison. This new tool will facilitate GSEA for Drosophila and other major model organisms based on high-quality annotated information available for these species.

Transcriptional and functional motifs defining renal function revealed by single-nucleus RNA sequencing.

Recent advances in single-cell sequencing provide a unique opportunity to gain novel insights into the diversity, lineage, and functions of cell types constituting a tissue/organ. Here, we performed a single-nucleus study of the adult Drosophila renal system, consisting of Malpighian tubules and nephrocytes, which shares similarities with the mammalian kidney. We identified 11 distinct clusters representing renal stem cells, stellate cells, regionally specific principal cells, garland nephrocyte cells, and pericardial nephrocytes. Characterization of the transcription factors specific to each cluster identified fruitless (fru) as playing a role in stem cell regeneration and Hepatocyte nuclear factor 4 (Hnf4) in regulating glycogen and triglyceride metabolism. In addition, we identified a number of genes, including Rho guanine nucleotide exchange factor at 64C (RhoGEF64c), Frequenin 2 (Frq2), Prip, and CG1093 that are involved in regulating the unusual star shape of stellate cells. Importantly, the single-nucleus dataset allows visualization of the expression at the organ level of genes involved in ion transport and junctional permeability, providing a systems-level view of the organization and physiological roles of the tubules. Finally, a cross-species analysis allowed us to match the fly kidney cell types to mouse kidney cell types and planarian protonephridia, knowledge that will help the generation of kidney disease models. Altogether, our study provides a comprehensive resource for studying the fly kidney.

FlyRNAi.org-the database of the Drosophila RNAi screening center and transgenic RNAi project: 2021 update.

The FlyRNAi database at the Drosophila RNAi Screening Center and Transgenic RNAi Project (DRSC/TRiP) provides a suite of online resources that facilitate functional genomics studies with a special emphasis on Drosophila melanogaster. Currently, the database provides: gene-centric resources that facilitate ortholog mapping and mining of information about orthologs in common genetic model species; reagent-centric resources that help researchers identify RNAi and CRISPR sgRNA reagents or designs; and data-centric resources that facilitate visualization and mining of transcriptomics data, protein modification data, protein interactions, and more. Here, we discuss updated and new features that help biological and biomedical researchers efficiently identify, visualize, analyze, and integrate information and data for Drosophila and other species. Together, these resources facilitate multiple steps in functional genomics workflows, from building gene and reagent lists to management, analysis, and integration of data.

A cell atlas of the adult Drosophila midgut.

Studies of the adult Drosophila midgut have led to many insights in our understanding of cell-type diversity, stem cell regeneration, tissue homeostasis, and cell fate decision. Advances in single-cell RNA sequencing provide opportunities to identify new cell types and molecular features. We used single-cell RNA sequencing to characterize the transcriptome of midgut epithelial cells and identified 22 distinct clusters representing intestinal stem cells, enteroblasts, enteroendocrine cells (EEs), and enterocytes. This unbiased approach recovered most of the known intestinal stem cells/enteroblast and EE markers, highlighting the high quality of the dataset, and led to insights on intestinal stem cell biology, cell type-specific organelle features, the roles of new transcription factors in progenitors and regional variation along the gut, 5 additional EE gut hormones, EE hormonal expression diversity, and paracrine function of EEs. To facilitate mining of this rich dataset, we provide a web-based resource for visualization of gene expression in single cells. Altogether, our study provides a comprehensive resource for addressing functions of genes in the midgut epithelium.

Modeling exercise using optogenetically contractible Drosophila larvae.

The pathophysiological effects of a number of metabolic and age-related disorders can be prevented to some extent by exercise and increased physical activity. However, the molecular mechanisms that contribute to the beneficial effects of muscle activity remain poorly explored. Availability of a fast, inexpensive, and genetically tractable model system for muscle activity and exercise will allow the rapid identification and characterization of molecular mechanisms that mediate the beneficial effects of exercise. Here, we report the development and characterization of an optogenetically-inducible muscle contraction (OMC) model in Drosophila larvae that we used to study acute exercise-like physiological responses. To characterize muscle-specific transcriptional responses to acute exercise, we performed bulk mRNA-sequencing, revealing striking similarities between acute exercise-induced genes in flies and those previously identified in humans. Our larval muscle contraction model opens a path for rapid identification and characterization of exercise-induced factors.

MARRVEL: Integration of Human and Model Organism Genetic Resources to Facilitate Functional Annotation of the Human Genome.

One major challenge encountered with interpreting human genetic variants is the limited understanding of the functional impact of genetic alterations on biological processes. Furthermore, there remains an unmet demand for an efficient survey of the wealth of information on human homologs in model organisms across numerous databases. To efficiently assess the large volume of publically available information, it is important to provide a concise summary of the most relevant information in a rapid user-friendly format. To this end, we created MARRVEL (model organism aggregated resources for rare variant exploration). MARRVEL is a publicly available website that integrates information from six human genetic databases and seven model organism databases. For any given variant or gene, MARRVEL displays information from OMIM, ExAC, ClinVar, Geno2MP, DGV, and DECIPHER. Importantly, it curates model organism-specific databases to concurrently display a concise summary regarding the human gene homologs in budding and fission yeast, worm, fly, fish, mouse, and rat on a single webpage. Experiment-based information on tissue expression, protein subcellular localization, biological process, and molecular function for the human gene and homologs in the seven model organisms are arranged into a concise output. Hence, rather than visiting multiple separate databases for variant and gene analysis, users can obtain important information by searching once through MARRVEL. Altogether, MARRVEL dramatically improves efficiency and accessibility to data collection and facilitates analysis of human genes and variants by cross-disciplinary integration of 18 million records available in public databases to facilitate clinical diagnosis and basic research.

Molecular Interaction Search Tool (MIST): an integrated resource for mining gene and protein interaction data.

Model organism and human databases are rich with information about genetic and physical interactions. These data can be used to interpret and guide the analysis of results from new studies and develop new hypotheses. Here, we report the development of the Molecular Interaction Search Tool (MIST; http://fgrtools.hms.harvard.edu/MIST/). The MIST database integrates biological interaction data from yeast, nematode, fly, zebrafish, frog, rat and mouse model systems, as well as human. For individual or short gene lists, the MIST user interface can be used to identify interacting partners based on protein-protein and genetic interaction (GI) data from the species of interest as well as inferred interactions, known as interologs, and to view a corresponding network. The data, interologs and search tools at MIST are also useful for analyzing 'omics datasets. In addition to describing the integrated database, we also demonstrate how MIST can be used to identify an appropriate cut-off value that balances false positive and negative discovery, and present use-cases for additional types of analysis. Altogether, the MIST database and search tools support visualization and navigation of existing protein and GI data, as well as comparison of new and existing data.

FlyRNAi.org-the database of the Drosophila RNAi screening center and transgenic RNAi project: 2017 update.

The FlyRNAi database of the Drosophila RNAi Screening Center (DRSC) and Transgenic RNAi Project (TRiP) at Harvard Medical School and associated DRSC/TRiP Functional Genomics Resources website (http://fgr.hms.harvard.edu) serve as a reagent production tracking system, screen data repository, and portal to the community. Through this portal, we make available protocols, online tools, and other resources useful to researchers at all stages of high-throughput functional genomics screening, from assay design and reagent identification to data analysis and interpretation. In this update, we describe recent changes and additions to our website, database and suite of online tools. Recent changes reflect a shift in our focus from a single technology (RNAi) and model species (Drosophila) to the application of additional technologies (e.g. CRISPR) and support of integrated, cross-species approaches to uncovering gene function using functional genomics and other approaches.

The Drosophila Gene Expression Tool (DGET) for expression analyses.

BACKGROUND: Next-generation sequencing technologies have greatly increased our ability to identify gene expression levels, including at specific developmental stages and in specific tissues. Gene expression data can help researchers understand the diverse functions of genes and gene networks, as well as help in the design of specific and efficient functional studies, such as by helping researchers choose the most appropriate tissue for a study of a group of genes, or conversely, by limiting a long list of gene candidates to the subset that are normally expressed at a given stage or in a given tissue. RESULTS: We report DGET, a Drosophila Gene Expression Tool ( www.flyrnai.org/tools/dget/web/ ), which stores and facilitates search of RNA-Seq based expression profiles available from the modENCODE consortium and other public data sets. Using DGET, researchers are able to look up gene expression profiles, filter results based on threshold expression values, and compare expression data across different developmental stages, tissues and treatments. In addition, at DGET a researcher can analyze tissue or stage-specific enrichment for an inputted list of genes (e.g., 'hits' from a screen) and search for additional genes with similar expression patterns. We performed a number of analyses to demonstrate the quality and robustness of the resource. In particular, we show that evolutionary conserved genes expressed at high or moderate levels in both fly and human tend to be expressed in similar tissues. Using DGET, we compared whole tissue profile and sub-region/cell-type specific datasets and estimated a potential source of false positives in one dataset. We also demonstrated the usefulness of DGET for synexpression studies by querying genes with expression profile similar to the mesodermal master regulator Twist. CONCLUSION: Altogether, DGET provides a flexible tool for expression data retrieval and analysis with short or long lists of Drosophila genes, which can help scientists to design stage- or tissue-specific in vivo studies and do other subsequent analyses.

Mechanistic characterization of a Drosophila model of paraneoplastic nephrotic syndrome.

Paraneoplastic syndromes occur in cancer patients and originate from dysfunction of organs at a distance from the tumor or its metastasis. A wide range of organs can be affected in paraneoplastic syndromes; however, the pathological mechanisms by which tumors influence host organs are poorly understood. Recent studies in the fly uncovered that tumor secreted factors target host organs, leading to pathological effects. In this study, using a Drosophila gut tumor model, we characterize a mechanism of tumor-induced kidney dysfunction. Specifically, we find that Pvf1, a PDGF/VEGF signaling ligand, secreted by gut tumors activates the PvR/JNK/Jra signaling pathway in the principal cells of the kidney, leading to mis-expression of renal genes and paraneoplastic renal syndrome-like phenotypes. Our study describes an important mechanism by which gut tumors perturb the function of the kidney, which might be of clinical relevance for the treatment of paraneoplastic syndromes.

Transcriptional programs mediating neuronal toxicity and altered glial-neuronal signaling in a Drosophila knock-in tauopathy model.

Missense mutations in the gene encoding the microtubule-associated protein tau cause autosomal dominant forms of frontotemporal dementia. Multiple models of frontotemporal dementia based on transgenic expression of human tau in experimental model organisms, including Drosophila, have been described. These models replicate key features of the human disease, but do not faithfully recreate the genetic context of the human disorder. Here we use CRISPR-Cas mediated gene editing to model frontotemporal dementia caused by the tau P301L mutation by creating the orthologous mutation, P251L, in the endogenous Drosophila tau gene. Flies heterozygous or homozygous for tau P251L display age-dependent neurodegeneration, metabolic defects and accumulate DNA damage in affected neurons. To understand the molecular events promoting neuronal dysfunction and death in knock-in flies we performed single-cell RNA sequencing on approximately 130,000 cells from brains of tau P251L mutant and control flies. We found that expression of disease-associated mutant tau altered gene expression cell autonomously in all neuronal cell types identified and non-cell autonomously in glial cells. Cell signaling pathways, including glial-neuronal signaling, were broadly dysregulated as were brain region and cell-type specific protein interaction networks and gene regulatory programs. In summary, we present here a genetic model of tauopathy, which faithfully recapitulates the genetic context and phenotypic features of the human disease and use the results of comprehensive single cell sequencing analysis to outline pathways of neurotoxicity and highlight the role of non-cell autonomous changes in glia.

Epithelial Ca2+ waves triggered by enteric neurons heal the gut.

A fundamental and unresolved question in regenerative biology is how tissues return to homeostasis after injury. Answering this question is essential for understanding the etiology of chronic disorders such as inflammatory bowel diseases and cancer. We used the Drosophila midgut to investigate this question and discovered that during regeneration a subpopulation of cholinergic enteric neurons triggers Ca2+ currents among enterocytes to promote return of the epithelium to homeostasis. Specifically, we found that down-regulation of the cholinergic enzyme Acetylcholinesterase in the epithelium enables acetylcholine from defined enteric neurons, referred as ARCENs, to activate nicotinic receptors in enterocytes found near ARCEN-innervations. This activation triggers high Ca2+ influx that spreads in the epithelium through Inx2/Inx7 gap junctions promoting enterocyte maturation followed by reduction of proliferation and inflammation. Disrupting this process causes chronic injury consisting of ion imbalance, Yki activation and increase of inflammatory cytokines together with hyperplasia, reminiscent of inflammatory bowel diseases. Altogether, we found that during gut regeneration the conserved cholinergic pathway facilitates epithelial Ca2+ waves that heal the intestinal epithelium. Our findings demonstrate nerve- and bioelectric-dependent intestinal regeneration which advance the current understanding of how a tissue returns to its homeostatic state after injury and could ultimately help existing therapeutics.

PANGEA: A New Gene Set Enrichment Tool for Drosophila and Common Research Organisms.

Gene set enrichment analysis (GSEA) plays an important role in large-scale data analysis, helping scientists discover the underlying biological patterns over-represented in a gene list resulting from, for example, an 'omics' study. Gene Ontology (GO) annotation is the most frequently used classification mechanism for gene set definition. Here we present a new GSEA tool, PANGEA (PAthway, Network and Gene-set Enrichment Analysis; https://www.flyrnai.org/tools/pangea/ ), developed to allow a more flexible and configurable approach to data analysis using a variety of classification sets. PANGEA allows GO analysis to be performed on different sets of GO annotations, for example excluding high-throughput studies. Beyond GO, gene sets for pathway annotation and protein complex data from various resources as well as expression and disease annotation from the Alliance of Genome Resources (Alliance). In addition, visualisations of results are enhanced by providing an option to view network of gene set to gene relationships. The tool also allows comparison of multiple input gene lists and accompanying visualisation tools for quick and easy comparison. This new tool will facilitate GSEA for Drosophila and other major model organisms based on high-quality annotated information available for these species.

Tumor Cytokine-Induced Hepatic Gluconeogenesis Contributes to Cancer Cachexia: Insights from Full Body Single Nuclei Sequencing.

A primary cause of death in cancer patients is cachexia, a wasting syndrome attributed to tumor-induced metabolic dysregulation. Despite the major impact of cachexia on the treatment, quality of life, and survival of cancer patients, relatively little is known about the underlying pathogenic mechanisms. Hyperglycemia detected in glucose tolerance test is one of the earliest metabolic abnormalities observed in cancer patients; however, the pathogenesis by which tumors influence blood sugar levels remains poorly understood. Here, utilizing a Drosophila model, we demonstrate that the tumor secreted interleukin-like cytokine Upd3 induces fat body expression of Pepck1 and Pdk, two key regulatory enzymes of gluconeogenesis, contributing to hyperglycemia. Our data further indicate a conserved regulation of these genes by IL-6/JAK-STAT signaling in mouse models. Importantly, in both fly and mouse cancer cachexia models, elevated gluconeogenesis gene levels are associated with poor prognosis. Altogether, our study uncovers a conserved role of Upd3/IL-6/JAK-STAT signaling in inducing tumor-associated hyperglycemia, which provides insights into the pathogenesis of IL-6 signaling in cancer cachexia.

Paralog Explorer: A resource for mining information about paralogs in common research organisms.

Paralogs are genes which arose via gene duplication, and when such paralogs retain overlapping or redundant function, this poses a challenge to functional genetics research. Recent technological advancements have made it possible to systematically probe gene function for redundant genes using dual or multiplex gene perturbation, and there is a need for a simple bioinformatic tool to identify putative paralogs of a gene(s) of interest. We have developed Paralog Explorer (https://www.flyrnai.org/tools/paralogs/), an online resource that allows researchers to quickly and accurately identify candidate paralogous genes in the genomes of the model organisms D. melanogaster, C. elegans, D. rerio, M. musculus, and H. sapiens. Paralog Explorer deploys an effective between-species ortholog prediction software, DIOPT, to analyze within-species paralogs. Paralog Explorer allows users to identify candidate paralogs, and to navigate relevant databases regarding gene co-expression, protein-protein and genetic interaction, as well as gene ontology and phenotype annotations. Altogether, this tool extends the value of current ortholog prediction resources by providing sophisticated features useful for identification and study of paralogous genes.

FlyPhoneDB: an integrated web-based resource for cell-cell communication prediction in Drosophila.

Multicellular organisms rely on cell-cell communication to exchange information necessary for developmental processes and metabolic homeostasis. Cell-cell communication pathways can be inferred from transcriptomic datasets based on ligand-receptor expression. Recently, data generated from single-cell RNA sequencing have enabled ligand-receptor interaction predictions at an unprecedented resolution. While computational methods are available to infer cell-cell communication in vertebrates such a tool does not yet exist for Drosophila. Here, we generated a high-confidence list of ligand-receptor pairs for the major fly signaling pathways and developed FlyPhoneDB, a quantification algorithm that calculates interaction scores to predict ligand-receptor interactions between cells. At the FlyPhoneDB user interface, results are presented in a variety of tabular and graphical formats to facilitate biological interpretation. To illustrate that FlyPhoneDB can effectively identify active ligands and receptors to uncover cell-cell communication events, we applied FlyPhoneDB to Drosophila single-cell RNA sequencing data sets from adult midgut, abdomen, and blood, and demonstrate that FlyPhoneDB can readily identify previously characterized cell-cell communication pathways. Altogether, FlyPhoneDB is an easy-to-use framework that can be used to predict cell-cell communication between cell types from single-cell RNA sequencing data in Drosophila.

Coordination of tumor growth and host wasting by tumor-derived Upd3.

yki-induced gut tumors in Drosophila are associated with host wasting, including muscle dysfunction, lipid loss, and hyperglycemia, a condition reminiscent of human cancer cachexia. We previously used this model to identify tumor-derived ligands that contribute to host wasting. To identify additional molecular networks involved in host-tumor interactions, we develop PathON, a web-based tool analyzing the major signaling pathways in Drosophila, and uncover the Upd3/Jak/Stat axis as an important modulator. We find that yki-gut tumors secrete Upd3 to promote self-overproliferation and enhance Jak/Stat signaling in host organs to cause wasting, including muscle dysfunction, lipid loss, and hyperglycemia. We further reveal that Upd3/Jak/Stat signaling in the host organs directly triggers the expression of ImpL2, an antagonistic binding protein for insulin-like peptides, to impair insulin signaling and energy balance. Altogether, our results demonstrate that yki-gut tumors produce a Jak/Stat pathway ligand, Upd3, that regulates both self-growth and host wasting.

DRscDB: A single-cell RNA-seq resource for data mining and data comparison across species.

With the advent of single-cell RNA sequencing (scRNA-seq) technologies, there has been a spike in studies involving scRNA-seq of several tissues across diverse species including Drosophila. Although a few databases exist for users to query genes of interest within the scRNA-seq studies, search tools that enable users to find orthologous genes and their cell type-specific expression patterns across species are limited. Here, we built a new search database, DRscDB (https://www.flyrnai.org/tools/single_cell/web/), to address this need. DRscDB serves as a comprehensive repository for published scRNA-seq datasets for Drosophila and relevant datasets from human and other model organisms. DRscDB is based on manual curation of Drosophila scRNA-seq studies of various tissue types and their corresponding analogous tissues in vertebrates including zebrafish, mouse, and human. Of note, our search database provides most of the literature-derived marker genes, thus preserving the original analysis of the published scRNA-seq datasets. Finally, DRscDB serves as a web-based user interface that allows users to mine gene expression data from scRNA-seq studies and perform cell cluster enrichment analyses pertaining to various scRNA-seq studies, both within and across species.