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679 results for “Gut microbiome”
Data from: How gut microbiome interactions affect nutritional traits of Drosophila melanogaster
<p>Most research on the impact of the gut microbiome on animal nutrition is designed to identify the effects of single microbial taxa and single metabolites of microbial origin, without considering the potentially complex network of interactions among co-occurring microorganisms. Here, we investigate how different microbial associations and their fermentation products affect host nutrition, using Drosophila melanogaster colonized with three gut microorganisms (the bacteria Acetobacter fabarum and Lactobacillus brevis and the yeast Hanseniaspora uvarum) in all seven possible combinations. Some microbial effects on host traits could be attributed to single taxa (e.g. yeast-mediated reduction of insect development time), while other effects were sex-specific and driven by among-microbe interactions (e.g. male lipid content determined by interactions between the yeast and both bacteria). Parallel analysis of nutritional indices of microbe-free flies administered different microbial fermentation products (acetic acid, acetoin, ethanol and lactic acid) revealed a single consistent effect: that the lipid content of both male and female flies is reduced by acetic acid. This effect was recapitulated in male flies colonized with both yeast and Acetobacter, but not for any microbial treatment in females nor in males with other microbial complements. These data suggest that the effect of microbial fermentation products on host nutritional status is strongly context-dependent, with respect to both the combination of associated microorganisms and host sex. Taken together, our findings demonstrate that among-microbe interactions can play a critically important role in determining the physiological outcome of host-microbiome interactions in Drosophila and, likely, in other animal hosts.</p>
PIBAC: Extensive cultivation of the pig gut microbiome identifies novel bacterial diversity and functions and enables tailored functional studies
<p>In-depth cultivation of the pig gut microbiome towards novel bacterial diversity and tailored functional studies:</p> <ul> <li>780 MAGs from all-in-one assembly of 295 pig gut metagenomic samples (Xiao, 2016)</li> <li>38 isolates representing novel species (single draft genomes)</li> <li>representing in total 617 species (hqMAGs-dereplicated_genomes, comp>90%, con<5%</li> </ul> <p>More information you can find here:</p> <p>https://github.com/tillrobin/PIBAC</p> <p>https://www.dsmz.de/pibac</p> <p> </p> <p>External study providing data:</p> <p>Xiao, Liang, et al. "A reference gene catalogue of the pig gut microbiome." Nature microbiology 1.12 (2016): 16161. <a href="https://doi.org/10.1038/nmicrobiol.2016.161">https://doi.org/10.1038/nmicrobiol.2016.161</a> </p>
Data from: Social networks predict gut microbiome composition in wild baboons
Social relationships have profound effects on health in humans and other primates, but the mechanisms that explain this relationship are not well understood. Using shotgun metagenomic data from wild baboons, we found that social group membership and social network relationships predicted both the taxonomic structure of the gut microbiome and the structure of genes encoded by gut microbial species. Rates of interaction directly explained variation in the gut microbiome, even after controlling for diet, kinship, and shared environments. They therefore strongly implicate direct physical contact among social partners in the transmission of gut microbial species. We identified 51 socially structured taxa, which were significantly enriched for anaerobic and non-spore-forming lifestyles. Our results argue that social interactions are an important determinant of gut microbiome composition in natural animal populations—a relationship with important ramifications for understanding how social relationships influence health, as well as the evolution of group living.
Data from: Gut microbiome composition and metabolomic profiles of wild western lowland gorillas (Gorilla gorilla gorilla) reflect host ecology
The metabolic activities of gut microbes significantly influence host physiology; thus, characterizing the forces that modulate this micro-ecosystem is key to understanding mammalian biology and fitness. To investigate the gut microbiome of wild primates and determine how these microbial communities respond to the host's external environment, we characterized faecal bacterial communities and, for the first time, gut metabolomes of four wild lowland gorilla groups in the Dzanga-Sangha Protected Areas, Central African Republic. Results show that geographical range may be an important modulator of the gut microbiomes and metabolomes of these gorilla groups. Distinctions seemed to relate to feeding behaviour, implying energy harvest through increased fruit consumption or fermentation of highly fibrous foods. These observations were supported by differential abundance of metabolites and bacterial taxa associated with the metabolism of cellulose, phenolics, organic acids, simple sugars, lipids and sterols between gorillas occupying different geographical ranges. Additionally, the gut microbiomes of a gorilla group under increased anthropogenic pressure could always be distinguished from that of all other groups. By characterizing the interplay between environment, behaviour, diet and symbiotic gut microbes, we present an alternative perspective on primate ecology and on the forces that shape the gut microbiomes of wild primates from an evolutionary context.
Data from: City life alters the gut microbiome and stable isotope profiling of the eastern water dragon (Intellagama lesueurii)
Urbanisation is one of the most significant threats to biodiversity, due to the rapid and large-scale environmental alterations it imposes on the natural landscape. It is, therefore, imperative that we understand the consequences of, and mechanisms by which, species can respond to it. In recent years, research has shown that plasticity of the gut microbiome may be an important mechanism by which animals can adapt to environmental change, yet empirical evidence of this in wild non-model species remains sparse. Using an empirical replicated study system, we show that city life alters the gut microbiome of a wild native non-model species – the eastern water dragon (Intellagama lesueurii). City dragons exhibit a more diverse gut microbiome than their native riparian counterparts and show gut microbial signatures of a high fat and plant rich diet. These results highlight the role that gut microbial plasticity plays in an animals' response to human-altered landscapes.
Data from: Reproductive and behavior dysfunction induced by maternal androgen exposure and obesity is likely not gut microbiome-mediated
Polycystic ovary syndrome (PCOS) is a common endocrine and metabolic disorder of unclear etiology in women and is characterized by androgen excess, insulin resistance, and mood disorders. The gut microbiome is known to influence conditions closely related with PCOS, and several recent studies have observed changes in the stool microbiome of women with PCOS. The mechanism by which the gut microbiome interacts with PCOS is still unknown. We used a mouse model to investigate if diet-induced maternal obesity and maternal dihydrotestosterone (DHT) exposure, mimicking the lean and obese PCOS women, cause lasting changes in the gut microbiome of offspring. Fecal microbiome profiles were assessed using Illumina paired-end sequencing of 16S rRNA gene V4 amplicons. We found sex-specific effects of maternal and offspring diet, and maternal DHT exposure on fecal bacterial richness and taxonomic composition. Female offspring exposed to maternal obesity and DHT displayed reproductive dysfunction and anxiety-like behavior. Fecal microbiota transplantation from DHT and diet-induced obesity exposed female offspring to wild-type mice did not transfer reproductive dysfunction and did not cause the expected increase in anxiety-like behavior in recipients. Maternal obesity and androgen exposure affect the gut microbiome of offspring, but the disrupted estrous cycles and anxiety-like behavior are likely not microbiome-mediated.
Phylogenetically under‐dispersed gut microbiomes are not correlated with host genomic heterozygosity in a genetically diverse reptile community
<p>We are providing semi-processed datasets relevant to the paper "Phylogenetically under-dispersed gut microbiomes across a range of host genetic diversity in a reptile community point to structuring by conserved host genes." Specifically, we include VCF files of RADseq data from host individuals, which are processed versions of the raw reads available at NCBI's Short Read Archive under PRJA744273. These data were processed for heterozygosity calculation using an adapted of the pipeline presented in Singhal et al. 2017, "Genetic diversity is largely unpredictable but scales with museum occurrences in a species-rich clade of Australian lizards."</p> <p>In addition, we include a database of 16S sequences from gut microbiome amplicon sequencing from the same host animals. The raw reads are available at NCBI's Short Read Archive under PRJNA746253. The sequences accessioned here are a curated, cleaned set of reference reads to which we realigned reads from each individual host.</p>
Dynamics of bacterial recombination in the human gut microbiome — figure data
<p>Data associated with Figures 1-6, S1-41 in the manuscript "Dynamics of bacterial recombination in the human gut microbiome" (DOI: <a href="https://doi.org/10.1101/2022.08.24.505183">10.1101/2022.08.24.505183)</a></p>
Cyprinodon pupfish gut microbiomes
<p>Adaptive radiations offer an excellent opportunity to understand the eco-evolutionary dynamics of gut microbiota and host niche specialization. In a laboratory common garden, we compared the gut microbiota of two novel derived trophic specialist pupfishes, a scale-eater and a molluscivore, to closely related and distant outgroup generalist populations, spanning both rapid trophic evolution within 10 kya and stable generalist diets persisting over 11 Mya. We predicted an adaptive and highly divergent microbiome composition in the trophic specialists reflecting their rapid rates of craniofacial and behavioral diversification. We sequenced 16S rRNA amplicons of gut microbiomes from lab-reared adult pupfishes raised under identical conditions and fed the same high-protein diet. In contrast to our predictions, gut microbiota largely reflected phylogenetic distance among species, rather than generalist or specialist life history, in support of phylosymbiosis. However, we did find significant enrichment of <em>Burkholderiaceae</em> bacteria in replicated lab-reared scale-eater populations. These bacteria sometimes digest collagen, the major component of fish scales, supporting an adaptive shift. We also found some enrichment of <em>Rhodobacteraceae</em> and <em>Planctomycetia</em> in lab-reared molluscivore populations, but these bacteria target cellulose. Overall phylogenetic conservation of microbiome composition contrasts with predictions of adaptive radiation theory and observations of rapid diversification in all other trophic traits in these hosts, including craniofacial morphology, foraging behavior, aggression, and gene expression, suggesting that the functional role of these minor shifts in microbiota will be important for understanding the role of the microbiome in trophic diversification.</p>
Linking the gut microbiome to host DNA methylation by a discovery and replication epigenome-wide association study
<p>BACKGROUND: The datafiles deposited here are products of the research project "<strong>Linking the gut microbiome to host DNA methylation by a discovery and replication epigenome-wide association study"</strong></p><p>Authors: Ayşe Demirkan1,2, Jenny van Dongen3,4, Casey T. Finnicum5, Harm-Jan Westra1, Soesma Jankipersadsing1, Gonneke Willemsen3,4, Richard G. Ijzerman6, Dorret I. Boomsma3,4, Erik A. Ehli5, Marc Jan Bonder1, Jingyuan Fu,1,7 Lude Franke1, Cisca Wijmenga1, Eco J.C. de Geus3,4, Alexander Kurilshikov1, Alexandra Zhernakova1</p><p>1 Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands</p><p>2 Section of Statistical Multi-omics, Department of Clinical and Experimental Medicine, School of Biosciences and Medicine & People-Centered AI institute University of Surrey, Guildford, United Kingdom</p><p>3 Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands</p><p>4 Amsterdam Public Health Research Institute, Amsterdam, the Netherlands</p><p>5 Avera Institute of Human Genetics, Avera McKennan Hospital & University Health Center, Sioux Falls, SD, USA</p><p>6 Department of Endocrinology, Amsterdam University Medical Center, location VUMC, Amsterdam, the Netherlands</p><p>7 Department of Pediatrics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands</p><p><strong>Corresponding Authors: </strong>Alexandra Zhernakova; Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands</p><p>Ayse Demirkan; Section of Statistical Multi-omics, Department of Clinical and Experimental Medicine, School of Biosciences and Medicine & People-Centered AI institute University of Surrey, Guildford, United Kingdom.</p><p>FILES: </p><p>1-merged_lld16s.Rata: Epigenome-wide association of 16s microbial abundances in LifeLines-Deep (LLD, n = 616, 450k methylation array) </p><p>2-lld_mgs.Rdata: Epigenome-wide association ofshotgun metagenomic sequencing derived taxa relative abundances (n = 683, 450k methylation array))</p><p>3-lld_<i>mgs_</i>pathways. Rdata: Epigenome-wide association ofshotgun metagenomic sequencing derived bacterial pathway relative abundances (n = 683, 450k methylation array)</p><p>FUNDING: The Lifelines initiative has been made possible by subsidy from the Dutch Ministry of Health, Welfare and Sport, the Dutch Ministry of Economic Affairs, the University Medical Center Groningen (UMCG), Groningen University and the Provinces in the North of the Netherlands (Drenthe, Friesland, Groningen). The Netherlands Twin Register acknowledges funding from the Netherlands Organization for Scientific Research (NWO): (NWO 911–09–032; NWO 480-04-004; 480-15-001/674, NWO 916-130-82), Biobanking and Biomolecular Research Infrastructure (184.033.111), and the BBRMI-NL-financed BIOS Consortium (NWO 184.021.007), NWO Large Scale infrastructures X-Omics (184.034.019), Genotype/phenotype database for behaviour genetic and genetic epidemiological studies (ZonMw Middelgroot 911-09-032); Netherlands Twin Registry Repository: researching the interplay between genome and environment (NWO-Groot 480-15-001/674); the Avera Institute, Sioux Falls (USA), the European Research Council (Genetics of Mental Illness 230374), the European Research Council (Genetics of Mental Illness 230374), and INRA-Pfizer. Pfizer provided support for data collection, but did not have any additional role in the study design, data analysis, decision to publish, or preparation of the manuscript.</p><p> </p>
Data for the publication Climate and nutrition drive gut microbiome variation in a fruit-specialist primate
Open the record for dataset details and reuse information.
Healthy Japanese gut microbiome data
<p>This dataset provides 36,553 MAGs with >70% completeness and <5% contamination, as evaluated using CheckM, reconstructed based on short-read sequencing of 1,268 fecal metagenomes of 1,100 predominantly healthy individuals from multiple geopgraphic locations accross Japan.</p>
Age-related differences in gut microbiome and fecal metabolome of captive African penguins (Spheniscus demersus)
<p><span>The code applied for the study: "Age-related differences in gut microbiome and fecal metabolome of captive African penguins (Spheniscus demersus)".</span></p>
Twenty-five metagenome assembled genomes recovered from the gut microbiome of the domestic ferret, Mustela putorius
<p>This is metadata provided in a single excel file for 25 unique metagenome assembled genomes (MAGs) recovered from the gut microbiome of three domestic ferrets (<em>Mustela putorius</em>). Details on both MAG and host ferret metadata, as well as information on sample collection, DNA sequencing, and bioinformatic processing can be found here, in association with the American Society for Microbiology Resource Announcement by Amundson et al. (in prep). </p>
Validation of StarinIQ software performance using metagenomic data from the ATCC gut microbiome genomic mix
<p>StrainIQ (Strain Identification and Quantification) is a novel tool that implements a new <em>n</em>-gram based algorithm for predicting and quantifying strain-level taxa from whole genome metagenomic sequencing data. We tested our method using simulated (GI tract reference genomes) and mock metagenomic datasets (from ATCC microbial genomic mix) and compared its performance with existing methods. The gut_even.zip file contains the metagenomic sequence data from the ATCC Gut Microbiome Genomic Mix (MSA-1006). From this original sequencing sequence (nearly 120X), we created additional datasets with 90X, 60X, 30X, 5X, 3X, and 1X coverage and tested StrainIQ performance on those sequencing datasets with varying coverage.</p> <p>Please find the new link for this data at https://zenodo.org/record/8132164</p>
Gut microbiome dataset for glaucoma analysis
<p>Glaucoma is an eye disease that is the commonest cause of irreversible blindness worldwide. It has been suggested that gut microbiota can produce reactive oxygen species and pro-inflammatory cytokines that may travel from the gastric mucosa to distal sites, such as the optic nerve head or trabecular meshwork. There is evidence for a gut-eye axis, as microbial dysbiosis has been associated with retinal diseases. Moreover, gut microbial dysbiosis is involved in the pathogenesis of Alzheimer’s disease. The eye and brain have a shared embryonic origin, and glaucoma and Alzheimer’s disease share multiple common biochemical and pathological changes. Here, we investigated the association between glaucoma prevalence and the gut microbiome. Moreover, we analyzed the association of the gut microbiome with intraocular pressure (IOP; risk factor of glaucoma) and vertical cup-to-disc ratio (VCDR; quantifying glaucoma severity).</p> <p>The discovery analyses include participants of the Rotterdam Study and the Erasmus Glaucoma Cohort. A total of 225 glaucoma patients and 1247 age- and sex-matched participants without glaucoma were included in our analyses. Stool samples were collected and used to generate 16S rRNA gene profiles.</p>
Effect of a Probiotic Mixture on the Gut Microbiome and Fatigue in Patients With Quiescent Inflammatory Bowel Disease
ClinicalTrials.gov study NCT03266484. IPD Sharing: NO. Countries: 1. Publications: 0.
Diet / Gut Microbiome Interaction and Influence on Inflammatory Disease in HIV Patients
ClinicalTrials.gov study NCT02610374. IPD Sharing: Not stated. Countries: 1. Publications: 1.
The Effects of Oral Probiotics and Herbal Supplementation on the Gut Microbiome and Sebum Excretion Rate in Non-Cystic Acne
ClinicalTrials.gov study NCT05919810. IPD Sharing: NO. Countries: 1. Publications: 1.
Targeting the Gut Microbiome for Prader-Willi Syndrome Treatment
ClinicalTrials.gov study NCT03548480. IPD Sharing: NO. Countries: 1. Publications: 1.
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.