The discovery, distribution and diversity of DNA viruses associated with Drosophila melanogaster in Europe

International audienceDrosophila melanogaster is an important model for antiviral immunity in arthropods, but very few DNA viruses have been described from the family Drosophilidae. This deficiency limits our opportunity to use natural host-pathogen combinations in experimental studies, and may bias our understanding of the Drosophila virome. Here we report fourteen DNA viruses detected in a metagenomic analysis of approximately 6500 pool-sequenced Drosophila, sampled from 47 European locations between 2014 and 2016. These include three new nudiviruses, a new and divergent entomopoxvirus, a virus related to Leptopilina boulardi filamentous virus, and a virus related to Musca domestica salivary gland hypertrophy virus. We also find an endogenous genomic copy of galbut virus, a dsRNA partitivirus, segregating at very low frequency. Remarkably, we find that Drosophila Vesanto virus, a small DNA virus previously described as a bidnavirus, may be composed of up to 12 segments and thus represent a new lineage of segmented DNA viruses. Two of the DNA viruses, Drosophila Kallithea nudivirus and Drosophila Vesanto virus are relatively common, found in 2% or more of wild flies. The others are rare, with many likely to be represented by a single infected fly. We find that virus prevalence in Europe reflects the prevalence seen in publicly-available datasets, with Drosophila Kallithea nudivirus and Drosophila Vesanto virus the only ones commonly detectable in public data from wild-caught flies and large population cages, and the other viruses being rare or absent. These analyses suggest that DNA viruses are at lower prevalence than RNA viruses in D. melanogaster, and may be less likely to persist in laboratory cultures. Our findings go some way to redressing an earlier bias toward RNA virus studies in Drosophila, and lay the foundation needed to harness the power of Drosophila as a model system for the study of DNA viruses

Drosophila evolution over space and time (DEST):A new population genomics resource

Drosophila melanogaster is a leading model in population genetics and genomics, and a growing number of whole-genome datasets from natural populations of this species have been published over the last years. A major challenge is the integration of disparate datasets, often generated using different sequencing technologies and bioinformatic pipelines, which hampers our ability to address questions about the evolution of this species. Here we address these issues by developing a bioinformatics pipeline that maps pooled sequencing (Pool-Seq) reads from D. melanogaster to a hologenome consisting of fly and symbiont genomes and estimates allele frequencies using either a heuristic (PoolSNP) or a probabilistic variant caller (SNAPE-pooled). We use this pipeline to generate the largest data repository of genomic data available for D. melanogaster to date, encompassing 271 previously published and unpublished population samples from over 100 locations in > 20 countries on four continents. Several of these locations have been sampled at different seasons across multiple years. This dataset, which we call Drosophila Evolution over Space and Time (DEST), is coupled with sampling and environmental meta-data. A web-based genome browser and web portal provide easy access to the SNP dataset. We further provide guidelines on how to use Pool-Seq data for model-based demographic inference. Our aim is to provide this scalable platform as a community resource which can be easily extended via future efforts for an even more extensive cosmopolitan dataset. Our resource will enable population geneticists to analyze spatio-temporal genetic patterns and evolutionary dynamics of D. melanogaster populations in unprecedented detail.DrosEU is funded by a Special Topic Networks (STN) grant from the European Society for Evolutionary Biology (ESEB). MK (M. Kapun) was supported by the Austrian Science Foundation (grant no. FWF P32275); JG by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (H2020-ERC-2014-CoG-647900) and by the Spanish Ministry of Science and Innovation (BFU-2011-24397); TF by the Swiss National Science Foundation (SNSF grants PP00P3_133641, PP00P3_165836, and 31003A_182262) and a Mercator Fellowship from the German Research Foundation (DFG), held as a EvoPAD Visiting Professor at the Institute for Evolution and Biodiversity, University of Münster; AOB by the National Institutes of Health (R35 GM119686); MK (M. Kankare) by Academy of Finland grant 322980; VL by Danish Natural Science Research Council (FNU) grant 4002-00113B; FS Deutsche Forschungsgemeinschaft (DFG) grant STA1154/4-1, Project 408908608; JP by the Deutsche Forschungsgemeinschaft Projects 274388701 and 347368302; AU by FPI fellowship (BES-2012-052999); ET Israel Science Foundation (ISF) grant 1737/17; MSV, MSR and MJ by a grant from the Ministry of Education, Science and Technological Development of the Republic of Serbia (451-03-68/2020-14/200178); AP, KE and MT by a grant from the Ministry of Education, Science and Technological Development of the Republic of Serbia (451-03-68/2020-14/200007); and TM NSERC grant RGPIN-2018-05551.Peer reviewe

Corrigendum to: Drosophila Evolution over Space and Time (DEST): a New Population Genomics Resource

Drosophila melanogaster is a leading model in population genetics and genomics, and a growing number of whole-genome datasets from natural populations of this species have been published over the last years. A major challenge is the integration of disparate datasets, often generated using different sequencing technologies and bioinformatic pipelines, which hampers our ability to address questions about the evolution of this species. Here we address these issues by developing a bioinformatics pipeline that maps pooled sequencing (Pool-Seq) reads from D. melanogaster to a hologenome consisting of fly and symbiont genomes and estimates allele frequencies using either a heuristic (PoolSNP) or a probabilistic variant caller (SNAPE-pooled). We use this pipeline to generate the largest data repository of genomic data available for D. melanogaster to date, encompassing 271 previously published and unpublished population samples from over 100 locations in > 20 countries on four continents. Several of these locations have been sampled at different seasons across multiple years. This dataset, which we call Drosophila Evolution over Space and Time (DEST), is coupled with sampling and environmental meta-data. A web-based genome browser and web portal provide easy access to the SNP dataset. We further provide guidelines on how to use Pool-Seq data for model-based demographic inference. Our aim is to provide this scalable platform as a community resource which can be easily extended via future efforts for an even more extensive cosmopolitan dataset. Our resource will enable population geneticists to analyze spatio-temporal genetic patterns and evolutionary dynamics of D. melanogaster populations in unprecedented detail.DrosEU is funded by a Special Topic Networks (STN) grant from the European Society for Evolutionary Biology (ESEB). MK (M. Kapun) was supported by the Austrian Science Foundation (grant no. FWF P32275); JG by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (H2020-ERC-2014-CoG-647900) and by the Spanish Ministry of Science and Innovation (BFU-2011-24397); TF by the Swiss National Science Foundation (SNSF grants PP00P3_133641, PP00P3_165836, and 31003A_182262) and a Mercator Fellowship from the German Research Foundation (DFG), held as a EvoPAD Visiting Professor at the Institute for Evolution and Biodiversity, University of Münster; AOB by the National Institutes of Health (R35 GM119686); MK (M. Kankare) by Academy of Finland grant 322980; VL by Danish Natural Science Research Council (FNU) grant 4002-00113B; FS Deutsche Forschungsgemeinschaft (DFG) grant STA1154/4-1, Project 408908608; JP by the Deutsche Forschungsgemeinschaft Projects 274388701 and 347368302; AU by FPI fellowship (BES-2012-052999); ET Israel Science Foundation (ISF) grant 1737/17; MSV, MSR and MJ by a grant from the Ministry of Education, Science and Technological Development of the Republic of Serbia (451-03-68/2020-14/200178); AP, KE and MT by a grant from the Ministry of Education, Science and Technological Development of the Republic of Serbia (451-03-68/2020-14/200007); and TM NSERC grant RGPIN-2018-05551.Peer reviewe

Glucose-induced incretin hormone release and inactivation are differently modulated by oral fat and protein in mice.

Monounsaturated fatty acids, such as oleic acid (OA), and certain milk proteins, especially whey protein (WP), have insulinotropic effects and can reduce postprandial glycemia. This effect may involve the incretin hormones glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1). To explore this, we examined the release and inactivation of GIP and GLP-1 after administration of glucose with or without OA or WP through gastric gavage in anesthetized C57BL/6J mice. Insulin responses to glucose (75 mg) were 3-fold augmented by addition of WP (75 mg; P < 0.01), which was associated with enhanced oral glucose tolerance (P < 0.01). The insulin response to glucose was also augmented by addition of OA (34 mg; P < 0.05) although only 1.5-fold and with no associated increase in glucose elimination. The slope of the glucose-insulin curve was increased by OA (1.7-fold; P < 0.05) and by WP(4-fold; P < 0.01) compared with glucose alone, suggesting potentiation of glucose-stimulated insulin release. WP increased GLP-1 secretion (P < 0.01), whereas GIP secretion was unaffected. OA did not affect GIP or GLP-1 secretion. Nevertheless, WP increased the levels of both intact GIP and intact GLP-1 (both P < 0.01), and OA increased the levels of intact GLP-1 (P < 0.05). WP inhibited dipeptidyl peptidase IV activity in the proximal small intestine by 50% (P < 0.05), suggesting that luminal degradation of WP generates small fragments, which are substrates for dipeptidyl peptidase IV and act as competitive inhibitors. We therefore conclude that fat and protein may serve as exogenous regulators of secretion and inactivation of the incretin hormones with beneficial influences on glucose metabolism

Incretin and islet hormonal responses to fat and protein ingestion in healthy men.

Glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) regulate islet function after carbohydrate ingestion. Whether incretin hormones are of importance for islet function after ingestion of noncarbohydrate macronutrients is not known. This study therefore examined integrated incretin and islet hormone responses to ingestion of pure fat (oleic acid; 0.88 g/kg) or protein (milk and egg protein; 2 g/kg) over 5 h in healthy men, aged 20-25 yr (n = 12); plain water ingestion served as control. Both intact (active) and total GLP-1 and GIP levels were determined as was plasma activity of dipeptidyl peptidase-4 (DPP-4). Following water ingestion, glucose, insulin, glucagon, GLP-1, and GIP levels and DPP-4 activity were stable during the 5-h study period. Both fat and protein ingestion increased insulin, glucagon, GIP, and GLP-1 levels without affecting glucose levels or DPP-4 activity. The GLP-1 responses were similar after protein and fat, whereas the early (30 min) GIP response was higher after protein than after fat ingestion (P < 0.001). This was associated with sevenfold higher insulin and glucagon responses compared with fat ingestion (both P < 0.001). After protein, the early GIP, but not GLP-1, responses correlated to insulin (r(2) = 0.86; P = 0.0001) but not glucagon responses. In contrast, after fat ingestion, GLP-1 and GIP did not correlate to islet hormones. We conclude that, whereas protein and fat release both incretin and islet hormones, the early GIP secretion after protein ingestion may be of primary importance to islet hormone secretion

Secretion and Dipeptidyl Peptidase-4-Mediated Metabolism of Incretin Hormones after a Mixed Meal or Glucose Ingestion in Obese Compared to Lean, Nondiabetic Men.

Context: Glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1) are cleaved by dipeptidyl peptidase-4 (DPP-4); plasma activity of DPP-4 may be increased in obesity. The impact of this increase on incretin hormone secretion and metabolism is not known. Objective: The aim of the study was to assess incretin hormone secretion and degradation in lean and obese nondiabetic subjects. Design, Settings, and Participants: We studied the ingestion of a mixed meal (560 kcal) or oral glucose (2 g/kg) in healthy lean (n = 12; body mass index, 20-25 kg/m(2)) or obese (n = 13; body mass index, 30-35 kg/m(2)) males at a University Clinical Research Unit. Main Outcome Measures: We measured the area under the curve of plasma intact (i) and total (t) GIP and GLP-1 after meal ingestion and oral glucose. Results: Plasma DPP-4 activity was higher in the obese subjects (38.5 +/- 3.0 vs. 26.7 +/- 1.6 mmol/min . mul; P = 0.002). Although GIP secretion (AUCtGIP) was not reduced in obese subjects after meal ingestion or oral glucose, AUCiGIP was lower in obese subjects (8.5 +/- 0.6 vs. 12.7 +/- 0.9 nmol/liter x 300 min; P < 0.001) after meal ingestion. GLP-1 secretion (AUCtGLP-1) was reduced in obese subjects after both meal ingestion (7.3 +/- 0.9 vs. 10.0 +/- 0.6 nmol/liter x 300 min; P = 0.022) and oral glucose (6.6 +/- 0.8 vs. 9.6 +/- 1.1 nmol/liter x 180 min; P = 0.035). iGLP-1 was reduced in parallel to tGLP-1. Conclusions: 1) Release and degradation of the two incretin hormones show dissociated changes in obesity: GLP-1 but not GIP secretion is lower after meal ingestion and oral glucose, whereas GIP but not GLP-1 metabolism is increased after meal ingestion. 2) Increased plasma DPP-4 activity in obesity is not associated with a generalized augmented incretin hormone metabolism