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Generating reference maps of the interactome networks underlying most cellular functions can greatly illuminate genetic studies by providing a protein-centric approach to finding new components of existing pathways, complexes, and processes. Here, we applied state-of-the-art experimental and bioinformatics methods to identify high-confidence binary protein-protein interactions (PPIs) for Drosophila melanogaster. We performed four all-by-all yeast two-hybrid (Y2H) screens of >10,000 Drosophila proteins, resulting in the ‘FlyBi’ dataset of 8,723 PPIs among 2,939 proteins. As part of this effort, we tested subsets of our data and data from previous PPI datasets using an orthogonal assay, which allowed us to normalize data quality across datasets. Next, we integrated our FlyBi data with previous PPI data, resulting in an expanded, high-confidence binary Drosophila reference interaction network, DroRI, comprising 17,232 interactions among 6,511 proteins. These data are accessible through the Molecular Interaction Search Tool (MIST) and other databases. To assess the utility of the PPI resource, we used novel interactions from the FlyBi dataset to generate an autophagy interaction network that we validated in vivo using two different autophagy-related assays. We found that deformed wings (dwg) encodes a protein that is both a regulator and a target of autophagy. Altogether, the resources generated in this project provide a strong foundation for building high-confidence new hypotheses regarding protein networks and function.

The accumulation of biological and biomedical literature outpaces the ability of most researchers and clinicians to stay abreast of their own immediate fields, let alone a broader range of topics. Although available search tools support identification of relevant literature, finding relevant and key publications is not always straightforward. For example, important publications might be missed in searches with an official gene name due to gene synonyms. Moreover, ambiguity of gene names can result in retrieval of a large number of irrelevant publications. To address these issues and help researchers and physicians quickly identify relevant publications, we developed BioLitMine, an advanced literature mining tool that takes advantage of the medical subject heading (MeSH) index and gene-to-publication annotations already available for PubMed literature. Using BioLitMine, a user can identify what MeSH terms are represented in the set of publications associated with a given gene of the interest, or start with a term and identify relevant publications. Users can also use the tool to find co-cited genes and a build a literature co-citation network. In addition, BioLitMine can help users build a gene list relevant to a MeSH term, such as a list of genes relevant to “stem cells” or “breast neoplasms.” Users can also start with a gene or pathway of interest and identify authors associated with that gene or pathway, a feature that makes it easier to identify experts who might serve as collaborators or reviewers. Altogether, BioLitMine extends the value of PubMed-indexed literature and its existing expert curation by providing a robust and gene-centric approach to retrieval of relevant information.

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.

CRISPR-Cas9 is a powerful genome editing technology in which a single guide RNA (sgRNA) confers target site specificity to achieve Cas9-mediated genome editing. Numerous sgRNA design tools have been developed based on reference genomes for humans and model organisms. However, existing resources are not optimal as genetic mutations or single nucleotide polymorphisms (SNPs) within the targeting region affect the efficiency of CRISPR-based approaches by interfering with guide-target complementarity. To facilitate identification of sgRNAs (1) in non-reference genomes, (2) across varying genetic backgrounds, or (3) for specific targeting of SNP-containing alleles, for example, disease relevant mutations, we developed a web tool, SNP-CRISPR (https://www.flyrnai.org/tools/snp_crispr/). SNP-CRISPR can be used to design sgRNAs based on public variant data sets or user-identified variants. In addition, the tool computes efficiency and specificity scores for sgRNA designs targeting both the variant and the reference. Moreover, SNP-CRISPR provides the option to upload multiple SNPs and target single or multiple nearby base changes simultaneously with a single sgRNA design. Given these capabilities, SNP-CRISPR has a wide range of potential research applications in model systems and for design of sgRNAs for disease-associated variant correction.

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.

Metabolic flexibility of muscle tissue describes the capacity to use glucose or lipids as energy substrates and its disruption is associated with metabolic dysfunction. Cancer-induced cachexia is a metabolic syndrome linked with muscle wasting, changes in muscle energy metabolism and lower life expectancy in cancer patients. The molecular mechanisms driving metabolic changes in muscle, however, are poorly characterized. Here, using a Drosophila model of systemic metabolic dysfunction triggered by yorkie-induced gut tumors, we identify the transcription factor REPTOR as a key regulator of energy metabolism in muscle. We show that REPTOR is upregulated in muscles of adult flies with gut yorkie-tumors, where it is necessary to modulate glucose metabolism. REPTOR expression in muscles is induced by ImpL2, a tumor-derived insulin binding protein that reduces systemic insulin signaling, or by nutritional restriction. Further, in vitro and in vivo studies indicate that high activity of REPTOR is sufficient to increase glucose content, transcriptionally repress phosphofructokinase and increase mitochondrial respiration. Consistent with the fly studies, higher levels of CREBRF, the mammalian ortholog of REPTOR, reduce glycolysis in mouse myotubes while promoting an oxidative phenotype. Altogether, our results implicate REPTOR/CREBRF as key regulators of muscle metabolism and metabolic flexibility that share a conserved function as repressors of glycolysis and promoters of oxidative phosphorylation.

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 (L-R) expression. Recently, data generated from single cell RNA sequencing (scRNA-seq) have enabled L-R 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 L-R pairs for the major fly signaling pathways and developed FlyPhoneDB, a quantification algorithm that calculates interaction scores to predict L-R interactions between cells. At the FlyPhoneDB user interface, results are presented in a variety of tabular and graphical formats to facilitate biological interpretation. To demonstrate that FlyPhoneDB can effectively identify active ligands and receptors to uncover cell-cell communication events, we applied FlyPhoneDB to Drosophila scRNA-seq 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 scRNA-seq data in Drosophila.

Mosquito-borne diseases present a worldwide public health burden. Current efforts to understand and counteract them have been aided by the use of cultured mosquito cells. Moreover, application in mammalian cells of forward genetic approaches such as CRISPR screens have identified essential genes and genes required for host-pathogen interactions, and in general, aided in functional annotation of genes. An equivalent approach for genetic screening of mosquito cell lines has been lacking. To develop such an approach, we design a new bioinformatic portal for sgRNA library design in several mosquito genomes, engineer mosquito cell lines to express Cas9 and accept sgRNA at scale, and identify optimal promoters for sgRNA expression in several mosquito species. We then optimize a recombination-mediated cassette exchange system to deliver CRISPR sgRNA and perform pooled CRISPR screens in an Anopheles cell line. Altogether, we provide a platform for high-throughput genome-scale screening in cell lines from disease vector species., Forward genetic approaches such as CRISPR screens are powerful ways to identify essential genes and those that influence host-pathogen interactions. Here the authors design a bioinformatics portal for sgRNA design and a recombination-mediated cassette system for delivery into mosquito cell lines.

Graphical abstract, 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.

The CRISPR-Cas9 system makes it possible to cause double-strand breaks in specific regions, inducing repair. In the presence of a donor construct, repair can involve insertion or 'knock-in' of an exogenous cassette. One common application of knock-in technology is to generate cell lines expressing fluorescently tagged endogenous proteins. The standard approach relies on production of a donor plasmid with ∼500 to 1000 bp of homology on either side of an insertion cassette that contains the fluorescent protein open reading frame (ORF). We present two alternative methods for knock-in of fluorescent protein ORFs into Cas9-expressing Drosophila S2R+ cultured cells, the single-stranded DNA (ssDNA) Drop-In method and the CRISPaint universal donor method. Both methods eliminate the need to clone a large plasmid donor for each target. We discuss the advantages and limitations of the standard, ssDNA Drop-In, and CRISPaint methods for fluorescent protein tagging in Drosophila cultured cells. © 2019 by John Wiley & Sons, Inc. Basic Protocol 1: Knock-in into Cas9-positive S2R+ cells using the ssDNA Drop-In approach Basic Protocol 2: Knock-in into Cas9-positive S2R+ cells by homology-independent insertion of universal donor plasmids that provide mNeonGreen (CRISPaint method) Support Protocol 1: sgRNA design and cloning Support Protocol 2: ssDNA donor synthesis Support Protocol 3: Transfection using Effectene Support Protocol 4: Electroporation of S2R+-MT::Cas9 Drosophila cells Support Protocol 5: Single-cell isolation of fluorescent cells using FACS.

High-throughput screens in Drosophila melanogaster cell lines have led to discovery of conserved gene functions related to signal transduction, host-pathogen interactions, ion transport, and more. CRISPR/Cas9 technology has opened the door to new types of large-scale cell-based screens. Whereas array-format screens require liquid handling automation and assay miniaturization, pooled-format screens, in which reagents are introduced at random and in bulk, can be done in a standard lab setting. We provide a detailed protocol for conducting and evaluating genome-wide CRISPR single guide RNA (sgRNA) pooled screens in Drosophila S2R+ cultured cells. Specifically, we provide step-by-step instructions for library design and production, optimization of cytotoxin-based selection assays, genome-scale screening, and data analysis. This type of project takes ∼3 months to complete. Results can be used in follow-up studies performed in vivo in Drosophila, mammalian cells, and/or other systems. © 2019 by John Wiley & Sons, Inc. Basic Protocol: Pooled-format screening with Cas9-expressing Drosophila S2R+ cells in the presence of cytotoxin Support Protocol 1: Optimization of cytotoxin concentration for Drosophila cell screening Support Protocol 2: CRISPR sgRNA library design and production for Drosophila cell screening Support Protocol 3: Barcode deconvolution and analysis of screening data.