Drosophila PDGF/VEGF signaling from muscles to hepatocyte-like cells protects against obesity

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.

Insect Insights at the Single-Cell Level: Technologies and Applications

Single-cell techniques are a promising way to unravel the complexity and heterogeneity of transcripts at the cellular level and to reveal the composition of different cell types and functions in a tissue or organ. In recent years, advances in single-cell RNA sequencing (scRNA-seq) have further changed our view of biological systems. The application of scRNA-seq in insects enables the comprehensive characterization of both common and rare cell types and cell states, the discovery of new cell types, and revealing how cell types relate to each other. The recent application of scRNA-seq techniques to insect tissues has led to a number of exciting discoveries. Here we provide an overview of scRNA-seq and its application in insect research, focusing on biological applications, current challenges, and future opportunities to make new discoveries with scRNA-seq in insects.

Heuristic-enabled active machine learning: A case study of predicting essential developmental stage and immune response genes in Drosophila melanogaster

Computational prediction of absolute essential genes using machine learning has gained wide attention in recent years. However, essential genes are mostly conditional and not absolute. Experimental techniques provide a reliable approach of identifying conditionally essential genes; however, experimental methods are laborious, time and resource consuming, hence computational techniques have been used to complement the experimental methods. Computational techniques such as supervised machine learning, or flux balance analysis are grossly limited due to the unavailability of required data for training the model or simulating the conditions for gene essentiality. This study developed a heuristic-enabled active machine learning method based on a light gradient boosting model to predict essential immune response and embryonic developmental genes in Drosophila melanogaster. We proposed a new sampling selection technique and introduced a heuristic function which replaces the human component in traditional active learning models. The heuristic function dynamically selects the unlabelled samples to improve the performance of the classifier in the next iteration. Testing the proposed model with four benchmark datasets, the proposed model showed superior performance when compared to traditional active learning models (random sampling and uncertainty sampling). Applying the model to identify conditionally essential genes, four novel essential immune response genes and a list of 48 novel genes that are essential in embryonic developmental condition were identified. We performed functional enrichment analysis of the predicted genes to elucidate their biological processes and the result evidence our predictions. Immune response and embryonic development related processes were significantly enriched in the essential immune response and embryonic developmental genes, respectively. Finally, we propose the predicted essential genes for future experimental studies and use of the developed tool accessible at http://heal.covenantuniversity.edu.ng for conditional essentiality predictions.

Aging Fly Cell Atlas identifies exhaustive aging features at cellular resolution

Aging is characterized by a decline in tissue function, but the underlying changes at cellular resolution across the organism remain unclear. Here, we present the Aging Fly Cell Atlas, a single-nucleus transcriptomic map of the whole aging Drosophila. We characterized 163 distinct cell types and performed an in-depth analysis of changes in tissue cell composition, gene expression, and cell identities. We further developed aging clock models to predict fly age and show that ribosomal gene expression is a conserved predictive factor for age. Combining all aging features, we find distinctive cell type-specific aging patterns. This atlas provides a valuable resource for studying fundamental principles of aging in complex organisms.

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.

Enteric bacterial infection in Drosophila induces whole-body alterations in metabolic gene expression independently of the immune deficiency signaling pathway

When infected by intestinal pathogenic bacteria, animals initiate both local and systemic defence responses. These responses are required to reduce pathogen burden and also to alter host physiology and behavior to promote infection tolerance, and they are often mediated through alterations in host gene expression. Here, we have used transcriptome profiling to examine gene expression changes induced by enteric infection with the Gram-negative bacteria Pseudomonas entomophila in adult female Drosophila. We find that infection induces a strong upregulation of metabolic gene expression, including gut and fat body-enriched genes involved in lipid transport, lipolysis, and beta-oxidation, as well as glucose and amino acid metabolism genes. Furthermore, we find that the classic innate immune deficiency (Imd)/Relish/NF-KappaB pathway is not required for, and in some cases limits, these infection-mediated increases in metabolic gene expression. We also see that enteric infection with Pseudomonas entomophila downregulates the expression of many transcription factors and cell–cell signaling molecules, particularly those previously shown to be involved in gut-to-brain and neuronal signaling. Moreover, as with the metabolic genes, these changes occurred largely independent of the Imd pathway. Together, our study identifies many metabolic, signaling, and transcription factor gene expression changes that may contribute to organismal physiological and behavioral responses to enteric pathogen infection.

Intravital lipid droplet labeling and imaging reveals the phenotypes and functions of individual macrophages in vivo

Macrophages play pivotal roles in the maintenance of tissue homeostasis. However, the reactivation of macrophages toward proinflammatory states correlates with a plethora of inflammatory diseases, including atherosclerosis, obesity, neurodegeneration, and bone marrow (BM) failure syndromes. The lack of methods to reveal macrophage phenotype and function in vivo impedes the translational research of these diseases. Here, we found that proinflammatory macrophages accumulate intracellular lipid droplets (LDs) relative to resting or noninflammatory macrophages both in vitro and in vivo, indicating that LD accumulation serves as a structural biomarker for macrophage phenotyping. To realize the staining and imaging of macrophage LDs in vivo, we developed a fluorescent fatty acid analog-loaded poly(lactic-co-glycolic acid) nanoparticle to label macrophages in mice with high efficiency and specificity. Using these novel nanoparticles, we achieved in situ functional identification of single macrophages in BM, liver, lung, and adipose tissues under conditions of acute or chronic inflammation. Moreover, with this intravital imaging platform, we further realized in vivo phenotyping of individual macrophages in the calvarial BM of mice under systemic inflammation. In conclusion, we established an efficient in vivo LD labeling and imaging system for single macrophage phenotyping, which will aid in the development of diagnostics and therapeutic monitoring. Moreover, this method also provides new avenues for the study of lipid trafficking and dynamics in vivo.

Roles of Insect Oenocytes in Physiology and Their Relevance to Human Metabolic Diseases

Oenocytes are large secretory cells present in the abdomen of insects known to synthesize very-long-chain fatty acids to produce hydrocarbons and pheromones that mediate courtship behavior in adult flies. In recent years, oenocytes have been implicated in the regulation of energy metabolism. These hepatocyte-like cells accumulate lipid droplets under starvation and can non-autonomously regulate tracheal waterproofing and adipocyte lipid composition. Here, we summarize evidence, mostly from Drosophila, establishing that oenocytes perform liver-like functions. We also compare the functional differences in oenocytes and the fat body, another lipid storage tissue which also performs liver-like functions. Lastly, we examine signaling pathways that regulate oenocyte metabolism derived from other metabolic tissues, as well as oenocyte-derived signals that regulate energy homeostasis.

Cancer cachexia: lessons from Drosophila

Cachexia, a wasting syndrome that is often associated with cancer, is one of the primary causes of death in cancer patients. Cancer cachexia occurs largely due to systemic metabolic alterations stimulated by tumors. Despite the prevalence of cachexia, our understanding of how tumors interact with host tissues and how they affect metabolism is limited. Among the challenges of studying tumor-host tissue crosstalk are the complexity of cancer itself and our insufficient knowledge of the factors that tumors release into the blood. Drosophila is emerging as a powerful model in which to identify tumor-derived factors that influence systemic metabolism and tissue wasting. Strikingly, studies that are characterizing factors derived from different fly tumor cachexia models are identifying both common and distinct cachectic molecules, suggesting that cachexia is more than one disease and that fly models can help identify these differences. Here, we review what has been learned from studies of tumor-induced organ wasting in Drosophila and discuss the open questions.

Origin and Development of the Adipose Tissue, a Key Organ in Physiology and Disease

Adipose tissue is a dynamic organ, well known for its function in energy storage and mobilization according to nutrient availability and body needs, in charge of keeping the energetic balance of the organism. During the last decades, adipose tissue has emerged as the largest endocrine organ in the human body, being able to secrete hormones as well as inflammatory molecules and having an important impact in multiple processes such as adipogenesis, metabolism and chronic inflammation. However, the cellular progenitors, development, homeostasis and metabolism of the different types of adipose tissue are not fully known. During the last decade, Drosophila melanogaster has demonstrated to be an excellent model to tackle some of the open questions in the field of metabolism and development of endocrine/metabolic organs. Discoveries ranged from new hormones regulating obesity to subcellular mechanisms that regulate lipogenesis and lipolysis. Here, we review the available evidences on the development, types and functions of adipose tissue in Drosophila and identify some gaps for future research. This may help to understand the cellular and molecular mechanism underlying the pathophysiology of this fascinating key tissue, contributing to establish this organ as a therapeutic target.

Analysis of Single-Cell Transcriptome Data in Drosophila

The fly Drosophila is a versatile model organism that has led to fascinating biological discoveries. In the past few years, Drosophila researchers have used single-cell RNA-sequencing (scRNA-seq) to gain insights into the cellular composition, and developmental processes of various tissues and organs. Given the success of single-cell technologies a variety of computational tools and software packages were developed to enable and facilitate the analysis of scRNA-seq data. In this book chapter we want to give guidance on analyzing droplet-based scRNA-seq data from Drosophila. We will initially describe the preprocessing commonly done for Drosophila, point out possible downstream analyses, and finally highlight computational methods developed using Drosophila scRNA-seq data.

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.

Drosophila melanogaster: A Powerful Tiny Animal Model for the Study of Metabolic Hepatic Diseases

Animal experimentation is limited by unethical procedures, time-consuming protocols, and high cost. Thus, the development of innovative approaches for disease treatment based on alternative models in a fast, safe, and economic manner is an important, yet challenging goal. In this paradigm, the fruit-fly Drosophila melanogaster has become a powerful model for biomedical research, considering its short life cycle and low-cost maintenance. In addition, biological processes are conserved and homologs of ∼75% of human disease-related genes are found in the fruit-fly. Therefore, this model has been used in innovative approaches to evaluate and validate the functional activities of candidate molecules identified via in vitro large-scale analyses, as putative agents to treat or reverse pathological conditions. In this context, Drosophila offers a powerful alternative to investigate the molecular aspects of liver diseases, since no effective therapies are available for those pathologies. Non-alcoholic fatty liver disease is the most common form of chronic hepatic dysfunctions, which may progress to the development of chronic hepatitis and ultimately to cirrhosis, thereby increasing the risk for hepatocellular carcinoma (HCC). This deleterious situation reinforces the use of the Drosophila model to accelerate functional research aimed at deciphering the mechanisms that sustain the disease. In this short review, we illustrate the relevance of using the fruit-fly to address aspects of liver pathologies to contribute to the biomedical area.

Single-cell RNA sequencing in Drosophila: Technologies and applications

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for investigating cell states and functions at the single-cell level. It has greatly revolutionized transcriptomic studies in many life science research fields, such as neurobiology, immunology, and developmental biology. With the fast development of both experimental platforms and bioinformatics approaches over the past decade, scRNA-seq is becoming economically feasible and experimentally practical for many biomedical laboratories. Drosophila has served as an excellent model organism for dissecting cellular and molecular mechanisms that underlie tissue development, adult cell function, disease, and aging. The recent application of scRNA-seq methods to Drosophila tissues has led to a number of exciting discoveries. In this review, I will provide a summary of recent scRNA-seq studies in Drosophila, focusing on technical approaches and biological applications. I will also discuss current challenges and future opportunities of making new discoveries using scRNA-seq in Drosophila. This article is categorized under:   Technologies > Analysis of the Transcriptome.

Metabolic decisions in development and disease-a Keystone Symposia report

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.

Methods and tools for spatial mapping of single-cell RNAseq clusters in Drosophila

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.

The Drosophila model to interrogate triacylglycerol biology

The deposition of storage fat in the form of triacylglycerol (TAG) is an evolutionarily conserved strategy to cope with fluctuations in energy availability and metabolic stress. Organismal TAG storage in specialized adipose tissues provides animals a metabolic reserve that sustains survival during development and starvation. On the other hand, excessive accumulation of adipose TAG, defined as obesity, is associated with an increasing prevalence of human metabolic diseases. During the past decade, the fruit fly Drosophila melanogaster, traditionally used in genetics and developmental biology, has been established as a versatile model system to study TAG metabolism and the etiology of lipid-associated metabolic diseases. Similar to humans, Drosophila TAG homeostasis relies on the interplay of organ systems specialized in lipid uptake, synthesis, and processing, which are integrated by an endocrine network of hormones and messenger molecules. Enzymatic formation of TAG from sugar or dietary lipid, its storage in lipid droplets, and its mobilization by lipolysis occur via mechanisms largely conserved between Drosophila and humans. Notably, dysfunctional Drosophila TAG homeostasis occurs in the context of aging, overnutrition, or defective gene function, and entails tissue-specific and organismal pathologies that resemble human disease. In this review, we summarize the physiology and biochemistry of TAG in Drosophila and outline the potential of this organism as a model system to understand the genetic and dietary basis of TAG storage and TAG-related metabolic disorders.

Muscle signals to the rescue

The skeletal muscle of fruit flies communicates with other organs to prevent the accumulation of too much fat and to protect adults against obesity.

Drosophila PDGF/VEGF signaling from muscles to hepatocyte-like cells protects against obesity

PDGF/VEGF ligands regulate a plethora of biological processes in multicellular organisms via autocrine, paracrine, and endocrine mechanisms. We investigated organ-specific metabolic roles of Drosophila PDGF/VEGF-like factors (Pvfs). We combine genetic approaches and single-nuclei sequencing to demonstrate that muscle-derived Pvf1 signals to the Drosophila hepatocyte-like cells/oenocytes to suppress lipid synthesis by activating the Pi3K/Akt1/TOR signaling cascade in the oenocytes. Functionally, this signaling axis regulates expansion of adipose tissue lipid stores in newly eclosed flies. Flies emerge after pupation with limited adipose tissue lipid stores and lipid level is progressively accumulated via lipid synthesis. We find that adult muscle-specific expression of pvf1 increases rapidly during this stage and that muscle-to-oenocyte Pvf1 signaling inhibits expansion of adipose tissue lipid stores as the process reaches completion. Our findings provide the first evidence in a metazoan of a PDGF/VEGF ligand acting as a myokine that regulates systemic lipid homeostasis by activating TOR in hepatocyte-like cells.

The Role of Muscle in Insect Energy Homeostasis

Maintaining energy homeostasis is critical for ensuring proper growth and maximizing survival potential of all organisms. Here we review the role of somatic muscle in regulating energy homeostasis in insects. The muscle is not only a large consumer of energy, it also plays a crucial role in regulating metabolic signaling pathways and energy stores of the organism. We examine the metabolic pathways required to supply the muscle with energy, as well as muscle-derived signals that regulate metabolic energy homeostasis.