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679 results for “Gut microbiome”
A Comprehensive Assessment of Demographic, Environmental and Host Genetic Associations with Gut Microbiome Diversity in Healthy Individuals (Metadata)
<p>Associated demographic, lifestyle, environmental and biochemical metadata accompanying manuscript "A Comprehensive Assessment of Demographic, Environmental and Host Genetic Associations with Gut Microbiome Diversity in Healthy Individuals". Data is available for 827 individuals that gave consent for their data to be shared outside of the Milieu intérieur consortium. </p>
Metaproteomics reveals age-specific alterations of gut microbiome in hamsters with SARS-CoV-2 infection
<p><span>The gut microbiome's pivotal role in health and disease is well-established. SARS-CoV-2 infection often causes gastrointestinal symptoms and is associated with changes of the microbiome in both human and animal studies. While hamsters serve as important animal models for coronavirus research, there exists a notable void in functional characterization of their microbiomes with metaproteomics. In this study, we present a workflow for analyzing the hamster gut microbiome, including a metagenomics-derived hamster gut microbial protein database and a data-independent acquisition metaproteomics method. Using this workflow, we identified 32419 protein groups from the fecal microbiomes of young and old hamsters infected with SARS-CoV-2 . We showed age-specific changes in the expressions of microbiome functions and host proteins associated with microbiomes, providing further functional insight into the dysbiosis and aberrant cross-talks between the microbiome and host in SARS-CoV-2 infection. Altogether this study established and demonstrated the capability of metaproteomics for the study of hamster microbiomes.<span> </span></span></p>
The influence of the gut microbiome on BCG-induced trained immunity
<p>This repository contains the code to reproduce the analysis in the study investigating the effects of gut microbiota on Bacillus Calmette-Guerin (BCG) vaccination of 321 healthy Dutch individuals. The results are presented in the paper</p> <p><em>The influence of the gut microbiome on BCG-induced trained immunity</em></p> <p>by</p> <p>Martin Stražar, Vera P. Mourits, Valerie A.C.M. Koeken, L. Charlotte J. de Bree, Simone J.C.F.M. Moorlag, Leo A.B. Joosten, Reinout van Crevel, Hera Vlamakis, Mihai G. Netea, Ramnik J. Xavier</p> <p>(2021)</p> <p> </p> <p>The bacillus Calmette-Guérin (BCG) vaccine protects against tuberculosis and heterologous infections but elicits high interindividual variation in specific and nonspecific (trained) immune responses. While the gut microbiome is increasingly recognized as an important modulator of vaccine responses and immunity in general, its potential role in BCG-induced protection is largely unknown. </p> <p>Stool and blood were collected from 321 healthy adults before BCG vaccination, followed by blood sampling two weeks and three months afterwards. Metagenomics based on de novo genome assembly revealed 43 immunomodulatory taxa. The nonspecific, trained immune response was detected by altered production of cytokines IL-6, IL-1β, and TNF-α upon ex vivo blood restimulation with Staphylococcus aureus and negatively correlated with abundance of Roseburia. The specific response, measured by IFN-γ production upon Mycobacterium tuberculosis stimulation, was associated positively with Ruminococcus and Eggerthella lenta. The immunomodulatory taxa identified also had the strongest effects on circulating metabolites, with Roseburia predominantly affecting phenylalanine metabolism. This was corroborated by abundances of relevant enzymes, suggesting alternate phenylalanine metabolism modules are activated in a Roseburia species-dependent manner. </p> <p><br> Variability in cytokine production after BCG vaccination was associated with the abundance of microbial genomes, which in turn affect or produce metabolites in circulation. Roseburia was found to alter both trained immune responses and phenylalanine metabolism, revealing microbes and microbial products that may alter BCG-induced immunity. Together, our findings contribute to the understanding of specific and trained immune responses after BCG vaccination.</p> <p>The analysis and dataset details are further described in README.md and <a href="https://gitlab.com/xavier-lab-computation/public/bcg300">https://gitlab.com/xavier-lab-computation/public/bcg300</a> .</p>
Data for: Context-dependent effects of glucocorticoids on the lizard gut microbiome
<p><strong>Data from: Context-dependent effects of glucocorticoids on the lizard gut microbiome </strong>(provisionally accepted, Molecular Ecology 2021) </p> <p>Metadata is in Sheet 2. Address queries to kirstyjmacleod@gmail.com.</p> <p><strong>Publication abstract:</strong> The vertebrate gut microbiota (bacterial, archaeal, and fungal communities of the gastrointestinal tract) can have profound effects on physiological processes of their hosts. Although relatively stable, changes in microbiome structure and composition occur due to changes in the environment, including exposure to stressors and associated increases in glucocorticoid hormones. Although a growing number of studies have linked stressor exposure to microbiome changes, few studies have experimentally explored the specific influence of glucocorticoids on the microbiome in wild animals, or across ecologically-important processes (e.g., reproductive stages). Here we tested the response of the gut microbiota of adult female Sceloporus undulatus across gestation to ecologically relevant elevations of a stress-relevant glucocorticoid hormone (CORT) in order to determine a) how experimentally elevated CORT influenced microbiome characteristics, and b) whether this relationship was dependent on reproductive context (i.e. whether females were gravid or not, and in those that were gravid, gestational stage). We show that the effects of CORT on gut microbiota are complex and depend on both gestational state and stage. CORT treatment altered microbial community membership and resulted in an increase in microbiome diversity in late-gestation females, and microbial community membership varied according to treatment. In non-gravid females, CORT treatment resulted in inter-individual variation in microbial communities, but this effect was not observed in late-gestation females. Our results highlight the need for a more holistic understanding of the downstream physiological effects of glucocorticoids, as well as the importance of context (here, gestational state and stage) in interpreting stress effects in ecology.</p>
NGS Data Accompanying "Deep Learning Enables Design of Multifunctional Synthetic Human Gut Microbiome Dynamics"
<p>NGS Data Accompanying "Deep Learning Enables Design of Multifunctional Synthetic Human Gut Microbiome Dynamics", currently in review.</p>
A field experiment reveals seasonal variation in the Daphnia gut microbiome
<p>The gut microbiome is increasingly recognized for its impact on host fitness, but it remains poorly understood how naturally variable environments influence gut microbiome diversity and composition. We studied changes in the gut microbiome of ten genotypes of water fleas (<em>Daphnia magna</em>) in submerged mesocosm enclosures in a eutrophic lake over a period of 16 weeks, from early summer to autumn. The microbial diversity increased when <em>Daphnia</em> were reintroduced from the laboratory to the lake, and the composition of gut microbes drastically changed. Both gut microbiome diversity and composition continued to change over the 16-week period, with alpha diversity peaking in late summer. The gut microbiome community was clearly distinct from that of the surrounding water, and temporal changes in the two communities were independent of each other. There were no consistent differences in the gut microbiomes among <em>Daphnia</em> genotypes in the lake environment. The change in gut microbiome over the season was accompanied by a decline in reproductive output and survival. There were weak, but statistically supported, effects of microbiota composition on<em> Daphnia </em>fitness, but there was no evidence that natural variation in microbiome diversity or composition was associated with tolerance to the cyanotoxin microcystin. We conclude that the gut microbiome of <em>Daphnia</em> is highly dynamic in a natural lake environment, but that host genetic effects on microbiome diversity and composition between genotypes within a population can be vanishingly small. These results emphasize that establishing the ecological effects of gut microbiota will require largescale experiments under natural conditions.</p>
Resources from: Gut microbiome composition better reflects host phylogeny than diet diversity in breeding wood-warblers
<p>Understanding the factors that shape microbiomes can provide insight on the importance of host-symbiont interactions and on co-evolutionary dynamics. Unlike for mammals, previous studies have found little or no support for an influence of host evolutionary history on avian gut microbiome diversity and instead have suggested a greater influence of the environment or diet due to fast gut turnover. Because effects of different factors may be conflated by captivity and sampling design, examining natural variation using large sample sizes is important. Our goal was to overcome these limitations by sampling wild birds to compare environmental, dietary, and evolutionary influences on gut microbiome structure. We performed fecal metabarcoding to characterize both the gut microbiome and diet of fifteen wood-warbler species across a four-year period and from two geographic localities. We find host taxonomy generally explained ~10% of the variation between individuals, which is ~6-fold more variation of any other factor considered, including diet diversity. Further, gut microbiome similarity was more congruent with the host phylogeny than with host diet similarity and we found little association between diet diversity and microbiome diversity. Together, our results suggest evolutionary history is the strongest predictor of gut microbiome differentiation among wood-warblers. Although the phylogenetic signal of the warbler gut microbiome is not very strong, our data suggest that a stronger influence of diet (as measured by diet diversity) does not account for this pattern. The mechanism underlying this phylogenetic signal is not clear, but we argue host traits may filter colonization and maintenance of microbes.</p>
Degenerative Cervical Myelopathy (DCM) induces sex-specific dysbiosis in the mouse gut bacterial microbiome, altering abundance and function
<p><strong>Background:</strong> Degenerative cervical myelopathy (DCM) represents the commonest cause of spinal cord impairment induced by non-traumatic events in the elderly population. It describes a spectrum of disorders that cause progressive spinal cord compression, neurological impairment, loss of bladder and bowel functions, as well as gastrointestinal dysfunction. The gut microbiota has been increasingly recognized as an environmental factor that can modulate both the central nervous system and immune response through the microbiota-gut-brain axis. Changes in gut microbiota composition or in the microbiota producing factors have been linked in the progression and development of several different pathologies such as traumatic spinal cord injury (SCI). Little is known about the molecular mechanisms that trigger DCM manifestation, and the potential role of the gut microbiota.</p> <p><strong>Results: </strong>Herein DCM was induced in female and male C57BL/6 mice by implanting an aromatic polyether material underneath the C5-6 laminae. The extent of DCM-induced changes in microbiota composition, also known as dysbiosis, was assessed by 16S rRNA sequencing from fecal samples at 3 different time points (6, 9 and 12 weeks after DCM induction). Several bacterial members were identified based on BLAST against the largest collection of metagenome-derived genomes from the mouse gut up to date. In both, female and males DCM caused gut dysbiosis compared with the sham group. However, dysbiosis was more pronounced in males than females, where several bacterial members of the families <em>Lachnospiraceae</em> and <em>Muribaculaceae</em> were significantly altered in the DCM group. These changes were also associated with altered immune cell composition in gut-associated lymphoid tissue, blood, and microbe-derived metabolic changes in propionate, butyrate, and lactate-producing bacterial members.</p> <p><strong>Conclusions: </strong>Our results demonstrate for the first time that DCM causes dynamic changes over time in the gut microbiota. Furthermore, we identify specie-specific abundance changes during DCM progression. DCM strongly reduces the abundance of butyrate-producing bacteria, and lactate-producing bacteria in much less extent. Sequence-based pangenomics cores were not resolved between the latter bacteria, but the gap-filling reactions and metabolic modelling successfully identified pyruvate-to-butanoate and pyruvate-to-propionate genes such as Buk and ACH1, respectively. These results aid to better understand markers and the molecular mechanisms that over time trigger DCM manifestation in females and males.</p>
Gut microbiome composition associated with Plasmodium infection in the Eurasian tree sparrow
<p>Recent expansion of microbiome research has uncovered connections between resident microbial communities and blood parasite risk, establishing the potential for microbial disease treatments such as probiotics in the future. However, this field has largely focused on humans and model organisms, leaving much unknown about how microbial communities might directly or indirectly impact parasite infection in wild populations and non-mammals. To contribute to this knowledge base in wild birds, we collected fecal and blood samples from wild Eurasian tree sparrows (<em>Passer montanus</em>) in the United States to test for associations between blood parasite infection and the gut microbiome. We used a widespread molecular approach to test 81 samples from peripheral blood for <em>Plasmodium</em> and <em>Haemoproteus</em>, and we characterized the gut microbiome using fecal samples as a proxy. Neither alpha nor beta diversity significantly varied with detected <em>Plasmodium</em> infection. However, differential abundance analysis highlighted a number of significantly varying bacteria, with the greatest representation within the phyla <em>Proteobacteria</em> and <em>Firmicutes</em> in <em>Plasmodium</em>-infected birds. These differentially abundant taxa offer a starting point for experimental work establishing the relationship between microbial abundance and <em>Plasmodium</em> infection.</p>
MAGs and gapseq models for auxotrophy predictions in the human gut microbiome
<p>This dataset contains MAGs, their DNA sequence, genome statistics, quantification per sample, and their metabolic model reconstructions from two human population cohorts from northern Germany.</p>
Design, construction, and in vivo augmentation of a complex gut microbiome
<p>Please cite: <a href="https://doi.org/10.1016/j.cell.2022.08.003">10.1016/j.cell.2022.08.003</a></p> <blockquote> <p>Cheng AG, Ho PY, Aranda-Díaz A, Jain S, Yu FB, Meng X, Wang M, Iakiviak M, Nagashima K, Zhao A, Murugkar P, Patil A, Atabakhsh K, Weakley A, Yan J, Brumbaugh AR, Higginbottom S, Dimas A, Shiver AL, Deutschbauer A, Neff N, Sonnenburg JL, Huang KC, Fischbach MA. Design, construction, and in vivo augmentation of a complex gut microbiome. Cell. 2022 Sep 15;185(19):3617-3636.e19. doi: 10.1016/j.cell.2022.08.003. Epub 2022 Sep 6. PMID: 36070752; PMCID: PMC9691261.</p> </blockquote> <p>Original raw sequencing data is available in the BioProject: <a href="https://www.ncbi.nlm.nih.gov/bioproject/PRJNA746600">PRJNA746600</a></p> <p><strong>Article summary:</strong></p> <blockquote> <p>Efforts to model the human gut <a href="https://www.sciencedirect.com/topics/biochemistry-genetics-and-molecular-biology/microbiome">microbiome</a> in mice have led to important insights into the mechanisms of host-microbe interactions. However, the model communities studied to date have been defined or complex, but not both, limiting their utility. Here, we construct and characterize <em>in vitro</em> a defined community of 104 bacterial species composed of the most common taxa from the human <a href="https://www.sciencedirect.com/topics/biochemistry-genetics-and-molecular-biology/intestine-flora">gut microbiota</a> (hCom1). We then used an iterative experimental process to fill open niches: germ-free mice were colonized with hCom1 and then challenged with a human fecal sample. We identified new species that engrafted following fecal challenge and added them to hCom1, yielding hCom2. In <a href="https://www.sciencedirect.com/topics/biochemistry-genetics-and-molecular-biology/gnotobiotics">gnotobiotic mice</a>, hCom2 exhibited increased stability to fecal challenge and robust <a href="https://www.sciencedirect.com/topics/immunology-and-microbiology/colonisation-resistance">colonization resistance</a> against pathogenic <em>Escherichia coli</em>. Mice colonized by either hCom2 or a human fecal community are phenotypically similar, suggesting that this consortium will enable a mechanistic interrogation of species and genes on microbiome-associated phenotypes.</p> </blockquote> <p><strong>File Descriptions:</strong></p> <ul> <li><strong>hCom2.tar.gz:</strong> This dataset contains genomic sequences and <a href="https://github.com/oschwengers/bakta">bakta</a> annotations of members of the hCom2 community. Please note that these may not be identical to the ones used in the publication. For the exact versions used in the publication, please reach out to the authors. </li> <li> <p><strong>hCom2_20221117.ninjaIndex.tar.gz:</strong> This tarball contains the ninjamap index and the source files used to create this index. Please use this tarball if you wish to run <a href="https://github.com/FischbachLab/ninjaMap">NinjaMap</a> against the hCom2 community.</p> </li> </ul>
Enterosignatures define common bacterial guilds in the human gut microbiome (data)
<p>Additional data related to the manuscript <em>Enterosignatures define common bacterial guilds in the human gut microbiome.</em></p> <p>The deposit contains the following files:</p> <ul> <li>GMR_dataset.zip - data and results related to enterosignature computation in the GMR dataset: raw data, enterosignature composition, metabolic potentials of the associated metagenomic species</li> </ul> <p><strong>GMR_dataset</strong><br> ├── NMF_results <em># results of NMF decomposition, from k = 2 signatures to 10, 5 being the optimal number</em><br> │ ├── 10_H.tsv<br> │ ├── ....<br> │ ├── 9_W.tsv<br> │ └── README.txt<br> ├── age_metadata.tsv <em># age of individuals in the GMR dataset</em><br> ├── drama_MGS_gtdbtk_taxonomy.tsv <em># taxonomy of the MGS </em><br> ├── drama_genus_level_abundance.tsv <em># genus-level abundance table used for NMF</em><br> └── metabo_data <em># Metabolic potential of the MGS associated to the enterosignatures</em><br> ├── cazymes_by_genome.tsv <em># cazymes</em><br> ├── gene_numbers.tsv <em># number of genes</em><br> ├── kegg_metabolic_processes_by_genome.tsv <em># Kegg annotations</em><br> ├── level1_onto_metabolites.tsv <em># Metacyc classes of metabolites, highest level</em><br> ├── level2_onto_metabolites.tsv <em># Metacyc classes of metabolites, second level</em><br> ├── metabolic_producers_full_community.tsv <em># predicted producers of metabolites, all genomes considered</em><br> ├── metabolic_producers_withinES.tsv <em># predicted producers of metabolites, within an ES</em><br> └── westerndiet.sbml <em># nutrients considered for metabolic modelling</em></p> <ul> <li>BMIS_dataset.zip - data and results related to enterosignature computation in the BMIS dataset</li> </ul> <p><strong>BMIS_dataset</strong><br> ├── bmis_es_composition.tsv <em># ES assignments of BMIS samples (ES computed on the GMR dataset)</em><br> ├── bmis_es_et_assignments.tsv<em> # ES and enterotype assignments of BMIS samples</em><br> └── bmis_genus-level_abundance.tsv <em># genus-level abundance matrix used for ES abundance computation</em></p> <ul> <li>NonWestern_dataset.zip - data and results related to enterosignature computation in the non-western dataset</li> </ul> <p><strong>NonWestern_dataset</strong><br> ├── nonwestern_es_composition.tsv <em># ES assignments of Non-western samples (ES computed on the GMR dataset)</em><br> └── nonwestern_genus_abundance_normalised.tsv <em># genus-level abundance matrix used for ES abundance computation</em></p> <p>The data is also available in the following repository:<em> </em><a href="https://gitlab.inria.fr/cfrioux/enterosignature-paper/">https://gitlab.inria.fr/cfrioux/enterosignature-paper/</a>.</p> <p>See also <a href="https://enterosignatures.quadram.ac.uk/">https://enterosignatures.quadram.ac.uk/</a>.</p>
Supplementary Material for publication "Bifidobacteria Define Gut Microbiome Profiles of Golden Lion Tamarin (Leontopithecus rosalia} and Marmoset Callithrix sp. Metagenomic Shotgun Pools
<p>Supplementary Tables and Figure for the publication "Bifidobacteria Define Gut Microbiome Profiles of Golden Lion Tamarin <em>Leontopithecus rosalia</em> and Marmoset <em>Callithrix</em> sp. Metagenomic Shotgun Pools"</p>
TableS1 of ML-based predictive gut microbiome analysis for health assessment
<p>Complete list of species associated with the COVID and Control cohort (ANOVA F score > 1). Comparison with respect to the original set of species used by Gupta <em>et al.</em>, and ANOVA-F values are reported.</p>
Gut feeling: Host and habitat as drivers of the microbiome in blackbuck (Antilope cervicapra)
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Data from: Longitudinal gut microbiome dynamics in relation to age and senescence in a wild animal population
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Gut microbiome of house sparrows during experimental Plasmodium relictum infection
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Resources from: Gut microbiome composition better reflects host phylogeny than diet diversity in breeding wood-warblers
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Gene-specific selective sweeps are pervasive across human gut microbiomes
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A field experiment reveals seasonal variation in the Daphnia gut microbiome
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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.