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.
There is an increasing appreciation for the role of metabolism in cell signaling and cell decision making. Precise metabolic control is essential in development, as evident by the disorders caused by mutations in metabolic enzymes. The metabolic profile of cells is often cell-type specific, changing as cells differentiate or during tumorigenesis. Recent evidence has shown that changes in metabolism are not merely a consequence of changes in cell state but that metabolites can serve to promote and/or inhibit these changes. Metabolites can link metabolic pathways with cell signaling pathways via several mechanisms, for example, by serving as substrates for protein post-translational modifications, by affecting enzyme activity via allosteric mechanisms, or by altering epigenetic markers. Unraveling the complex interactions governing metabolism, gene expression, and protein activity that ultimately govern a cell's fate will require new tools and interactions across disciplines. On March 24 and 25, 2021, experts in cell metabolism, developmental biology, and human disease met virtually for the Keystone eSymposium, "Metabolic Decisions in Development and Disease." The discussions explored how metabolites impact cellular and developmental decisions in a diverse range of model systems used to investigate normal development, developmental disorders, dietary effects, and cancer-mediated changes in metabolism.
Uncovering how transcription factors regulate their targets at DNA, RNA and protein levels over time is critical to define gene regulatory networks (GRNs) and assign mechanisms in normal and diseased states. RNA-seq is a standard method measuring gene regulation using an established set of analysis stages. However, none of the currently available pipeline methods for interpreting ordered genomic data (in time or space) use time-series models to assign cause and effect relationships within GRNs, are adaptive to diverse experimental designs, or enable user interpretation through a web-based platform. Furthermore, methods integrating ordered RNA-seq data with protein-DNA binding data to distinguish direct from indirect interactions are urgently needed. We present TIMEOR (Trajectory Inference and Mechanism Exploration with Omics data in R), the first web-based and adaptive time-series multi-omics pipeline method which infers the relationship between gene regulatory events across time. TIMEOR addresses the critical need for methods to determine causal regulatory mechanism networks by leveraging time-series RNA-seq, motif analysis, protein-DNA binding data, and protein-protein interaction networks. TIMEOR's user-catered approach helps non-coders generate new hypotheses and validate known mechanisms. We used TIMEOR to identify a novel link between insulin stimulation and the circadian rhythm cycle. TIMEOR is available at https://github.com/ashleymaeconard/TIMEOR.git and http://timeor.brown.edu.
The organs and metabolic pathways involved in energy metabolism, and the process of ATP production from nutrients, are comparable between humans and Drosophila melanogaster This level of conservation, together with the power of Drosophila genetics, makes the fly a very useful model system to study energy homeostasis. Here, we discuss the major organs involved in energy metabolism in Drosophila and how they metabolize different dietary nutrients to generate adenosine triphosphate. Energy metabolism in these organs is controlled by cell-intrinsic, paracrine, and endocrine signals that are similar between Drosophila and mammals. We describe how these signaling pathways are regulated by several physiological and environmental cues to accommodate tissue-, age-, and environment-specific differences in energy demand. Last, we discuss several genetic and diet-induced fly models of obesity and diabetes that can be leveraged to better understand the molecular basis of these metabolic diseases and thereby promote the development of novel therapies.
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.
Culex mosquitoes are a global vector for multiple human and animal diseases, including West Nile virus, lymphatic filariasis, and avian malaria, posing a constant threat to public health, livestock, companion animals, and endangered birds. While rising insecticide resistance has threatened the control of Culex mosquitoes, advances in CRISPR genome-editing tools have fostered the development of alternative genetic strategies such as gene drive systems to fight disease vectors. However, though gene-drive technology has quickly progressed in other mosquitoes, advances have been lacking in Culex. Here, we develop a Culex-specific Cas9/gRNA expression toolkit and use site-directed homology-based transgenesis to generate and validate a Culex quinquefasciatus Cas9-expressing line. We show that gRNA scaffold variants improve transgenesis efficiency in both Culex quinquefasciatus and Drosophila melanogaster and boost gene-drive performance in the fruit fly. These findings support future technology development to control Culex mosquitoes and provide valuable insight for improving these tools in other species.
Conventional approaches to identify secreted factors that regulate homeostasis are limited in their abilities to identify the tissues/cells of origin and destination. We established a platform to identify secreted protein trafficking between organs using an engineered biotin ligase (BirA*G3) that biotinylates, promiscuously, proteins in a subcellular compartment of one tissue. Subsequently, biotinylated proteins are affinity-enriched and identified from distal organs using quantitative mass spectrometry. Applying this approach in Drosophila, we identify 51 muscle-secreted proteins from heads and 269 fat body-secreted proteins from legs/muscles, including CG2145 (human ortholog ENDOU) that binds directly to muscles and promotes activity. In addition, in mice, we identify 291 serum proteins secreted from conditional BirA*G3 embryo stem cell-derived teratomas, including low-abundance proteins with hormonal properties. Our findings indicate that the communication network of secreted proteins is vast. This approach has broad potential across different model systems to identify cell-specific secretomes and mediators of interorgan communication in health or disease.
Single-cell RNA sequencing (scRNAseq) experiments provide a powerful means to identify clusters of cells that share common gene expression signatures. A major challenge in scRNAseq studies is to map the clusters to specific anatomical regions along the body and within tissues. Existing data, such as information obtained from large-scale in situ RNA hybridization studies, cell type specific transcriptomics, gene expression reporters, antibody stainings, and fluorescent tagged proteins, can help to map clusters to anatomy. However, in many cases, additional validation is needed to precisely map the spatial location of cells in clusters. Several approaches are available for spatial resolution in Drosophila, including mining of existing datasets, and use of existing or new tools for direct or indirect detection of RNA, or direct detection of proteins. Here, we review available resources and emerging technologies that will facilitate spatial mapping of scRNAseq clusters at high resolution in Drosophila. Importantly, we discuss the need, available approaches, and reagents for multiplexing gene expression detection in situ, as in most cases scRNAseq clusters are defined by the unique coexpression of sets of genes.
Dysregulated mTORC1 signaling alters a wide range of cellular processes, contributing to metabolic disorders and cancer. Defining the molecular details of downstream effectors is thus critical for uncovering selective therapeutic targets. We report that mTORC1 and its downstream kinase S6K enhance eIF4A/4B-mediated translation of Wilms' tumor 1-associated protein (WTAP), an adaptor for the N-methyladenosine (mA) RNA methyltransferase complex. This regulation is mediated by 5' UTR of WTAP mRNA that is targeted by eIF4A/4B. Single-nucleotide-resolution mA mapping revealed that MAX dimerization protein 2 (MXD2) mRNA contains mA, and increased mA modification enhances its degradation. WTAP induces cMyc-MAX association by suppressing MXD2 expression, which promotes cMyc transcriptional activity and proliferation of mTORC1-activated cancer cells. These results elucidate a mechanism whereby mTORC1 stimulates oncogenic signaling via mA RNA modification and illuminates the WTAP-MXD2-cMyc axis as a potential therapeutic target for mTORC1-driven cancers.
The RB1 tumor suppressor is recurrently mutated in a variety of cancers including retinoblastomas, small cell lung cancers, triple-negative breast cancers, prostate cancers, and osteosarcomas. Finding new synthetic lethal (SL) interactions with RB1 could lead to new approaches to treating cancers with inactivated RB1. We identified 95 SL partners of RB1 based on a Drosophila screen for genetic modifiers of the eye phenotype caused by defects in the RB1 ortholog, Rbf1. We validated 38 mammalian orthologs of Rbf1 modifiers as RB1 SL partners in human cancer cell lines with defective RB1 alleles. We further show that for many of the RB1 SL genes validated in human cancer cell lines, low activity of the SL gene in human tumors, when concurrent with low levels of RB1 was associated with improved patient survival. We investigated higher order combinatorial gene interactions by creating a novel Drosophila cancer model with co-occurring Rbf1, Pten and Ras mutations, and found that targeting RB1 SL genes in this background suppressed the dramatic tumor growth and rescued fly survival whilst having minimal effects on wild-type cells. Finally, we found that drugs targeting the identified RB1 interacting genes/pathways, such as UNC3230, PYR-41, TAK-243, isoginkgetin, madrasin, and celastrol also elicit SL in human cancer cell lines. In summary, we identified several high confidence, evolutionarily conserved, novel targets for RB1-deficient cells that may be further adapted for the treatment of human cancer.
The Drosophila midgut has emerged in recent years as a model system to study stem cell renewal and differentiation and tissue homeostasis. Histological, genetic and gene expression studies have provided a wealth of information on gut cell types, regionalization, genes and pathways involved in cell proliferation and differentiation, stem cell renewal, and responses to changes in environmental factors such as the microbiota and nutrients. Here, we review the contribution of single cell transcriptomic methods to our understanding of gut cell type diversity, lineage and behavior.
Endonuclease G (ENDOG), a mitochondrial nuclease, is known to participate in many cellular processes, including apoptosis and paternal mitochondrial elimination, while its role in autophagy remains unclear. Here, we report that ENDOG released from mitochondria promotes autophagy during starvation, which we find to be evolutionally conserved across species by performing experiments in human cell lines, mice, Drosophila and C. elegans. Under starvation, Glycogen synthase kinase 3 beta-mediated phosphorylation of ENDOG at Thr-128 and Ser-288 enhances its interaction with 14-3-3γ, which leads to the release of Tuberin (TSC2) and Phosphatidylinositol 3-kinase catalytic subunit type 3 (Vps34) from 14-3-3γ, followed by mTOR pathway suppression and autophagy initiation. Alternatively, ENDOG activates DNA damage response and triggers autophagy through its endonuclease activity. Our results demonstrate that ENDOG is a crucial regulator of autophagy, manifested by phosphorylation-mediated interaction with 14-3-3γ, and its endonuclease activity-mediated DNA damage response.
Mechanistic Target of Rapamycin Complex 1 (mTORC1) is a central regulator of cell growth and metabolism that senses and integrates nutritional and environmental cues with cellular responses. Recent studies have revealed critical roles of mTORC1 in RNA biogenesis and processing. Here, we find that the mA methyltransferase complex (MTC) is a downstream effector of mTORC1 during autophagy in and human cells. Furthermore, we show that the Chaperonin Containing Tailless complex polypeptide 1 (CCT) complex, which facilitates protein folding, acts as a link between mTORC1 and MTC. The mTORC1 activates the chaperonin CCT complex to stabilize MTC, thereby increasing mA levels on the messenger RNAs encoding autophagy-related genes, leading to their degradation and suppression of autophagy. Altogether, our study reveals an evolutionarily conserved mechanism linking mTORC1 signaling with mA RNA methylation and demonstrates their roles in suppressing autophagy.
FlyBase (flybase.org) is an essential online database for researchers using Drosophila melanogaster as a model organism, facilitating access to a diverse array of information that includes genetic, molecular, genomic and reagent resources. Here, we describe the introduction of several new features at FlyBase, including Pathway Reports, paralog information, disease models based on orthology, customizable tables within reports and overview displays ('ribbons') of expression and disease data. We also describe a variety of recent important updates, including incorporation of a developmental proteome, upgrades to the GAL4 search tab, additional Experimental Tool Reports, migration to JBrowse for genome browsing and improvements to batch queries/downloads and the Fast-Track Your Paper tool.
Precise genome editing is a valuable tool to study gene function in model organisms. Prime editing, a precise editing system developed in mammalian cells, does not require double-strand breaks or donor DNA and has low off-target effects. Here, we applied prime editing for the model organism and developed conditions for optimal editing. By expressing prime editing components in cultured cells or somatic cells of transgenic flies, we precisely introduce premature stop codons in three classical visible marker genes, , , and Furthermore, by restricting editing to germ cells, we demonstrate efficient germ-line transmission of a precise edit in to 36% of progeny. Our results suggest that prime editing is a useful system in to study gene function, such as engineering precise point mutations, deletions, or epitope tags.
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.
Characterizing the proteome composition of organelles and subcellular regions of living cells can facilitate the understanding of cellular organization as well as protein interactome networks. Proximity labeling-based methods coupled with mass spectrometry (MS) offer a high-throughput approach for systematic analysis of spatially restricted proteomes. Proximity labeling utilizes enzymes that generate reactive radicals to covalently tag neighboring proteins. The tagged endogenous proteins can then be isolated for further analysis by MS. To analyze protein-protein interactions or identify components that localize to discrete subcellular compartments, spatial expression is achieved by fusing the enzyme to specific proteins or signal peptides that target to particular subcellular regions. Although these technologies have only been introduced recently, they have already provided deep insights into a wide range of biological processes. Here, we provide an updated description and comparison of proximity labeling methods, as well as their applications and improvements. As each method has its own unique features, the goal of this review is to describe how different proximity labeling methods can be used to answer different biological questions. This article is categorized under: Technologies > Analysis of Proteins.
Most organs and tissues are composed of many types of cells. To characterize cellular state, various transcription profiling approaches are currently available, including whole-tissue bulk RNA sequencing, single cell RNA sequencing (scRNA-Seq), and cell type-specific RNA sequencing. What is missing in this repertoire is a simple, versatile method for bulk transcriptional profiling of cell types for which cell type-specific genetic markers or antibodies are not readily available. We therefore developed Probe-Seq, which uses hybridization of gene-specific probes to RNA markers for isolation of specific types of cells, to enable downstream FACS isolation and bulk RNA sequencing. We show that this method can enable isolation and profiling of specific cell types from mouse retina, frozen human retina, midgut, and developing chick retina, suggesting that it is likely useful for most organisms.
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.