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108 results for “human microbiota”
Raw metabolomics data of the paper: New findings in the metabolism of the saffron apocarotenoids, crocins and crocetin, by the human gut microbiota
<p>Raw dataset of the metabolomicas data of the study : New findings in the metabolism of the saffron apocarotenoids, crocins and crocetin, by the human gut microbiota.</p> <p>The csv file contain the raw data matrix exported from MS-DIAL software after total ions aligment across all study samples.</p>
MMGC: gene catalogues of the mouse and human microbiota
<p>We produced protein cluster catalogues in order to establish the gene-level taxonomic overlap between the human and mouse microbiome. </p> <p>For gene-clustering, we concatenated 76,937,350 pre-clustered human predicted proteins for non-redundant, near-complete genomes of the UHGG with 45,598,646 mouse predicted protein-coding sequences from non-redundant, near-complete species of the MMGC, and performed protein clustering using the ‘linclust’ function from MMseqs285 v10-6d92c (-c 0.8 --cov-mode 1 --cluster-mode 2 --kmer-per-seq 80). Proteins were clustered at 100%, 90%, 80% and 50% sequence identity; clusters were considered shared if they contained genes from both human and mouse commensals.</p> <p>This archive includes two files for each sequence identity threshold: a representative protein sequence file (.fa) and a sequence membership file (.tsv). </p> <p> </p> <p> </p>
Illumina Sequencing Data for "Elucidating human gut microbiota interactions that robustly inhibit diverse Clostridioides difficile strains across different nutrient landscapes"
<p>Illumina Sequencing Data for Sulaiman et al., "Elucidating human gut microbiota interactions that robustly inhibit diverse Clostridioides difficile strains across different nutrient landscapes".</p>
The impact of cefuroxime prophylaxis on human intestinal microbiota in surgical oncological patients - Dataset (FASTQ FILES)
<p>Dataset containing FASTQ files of the sequenced samples, generated by the Illumina MiSeq platform. </p> <p><span>This data is freely available under a CC-BY license; if you use it in your work, please cite our paper, "The impact of cefuroxime prophylaxis on human intestinal microbiota in surgical oncological patients" (DOI 10.3389/frmbi.2022.1092771).</span></p>
Link to dataset related to article "Endogenous murine microbiota member Faecalibaculum rodentium and its human homologue protect from intestinal tumour growth "
<p>This record contains raw data related to article “ Endogenous murine microbiota member Faecalibaculum rodentium and its human homologue protect from intestinal tumour growth"</p> <p>The microbiota has been shown to promote intestinal tumourigenesis, but a possible anti-tumourigenic effect has also been postulated. Here, we demonstrate that changes in the microbiota and mucus composition are concomitant with tumourigenesis. We identified two anti-tumourigenic strains of the microbiota-Faecalibaculum rodentium and its human homologue, Holdemanella biformis-that are strongly under-represented during tumourigenesis. Reconstitution of Apc<sup>Min/+</sup> or azoxymethane- and dextran sulfate sodium-treated mice with an isolate of F. rodentium (F. PB1) or its metabolic products reduced tumour growth. Both F. PB1 and H. biformis produced short-chain fatty acids that contributed to control protein acetylation and tumour cell proliferation by inhibiting calcineurin and NFATc3 activation in mouse and human settings. We have thus identified endogenous anti-tumourigenic bacterial strains with strong diagnostic, therapeutic and translational potential.</p>
HiFi Metagenomic Sequencing Enables Assembly of Accurate and Complete Genomes from Human Gut Microbiota.
<p>We reported 102 complete metagenome assembled genomes (cMAGs) from five human fecal HiFi sequencing samples.</p> <p>102_cMAGs_fna.tar.gz: Fasta sequence files of 102 cMAGs.</p> <p>gc_skew_figures.tar.gz: GC-skew pattern figures of 102 cMAGs. (SVG format)</p> <p>coverage_plots.tar.gz: Genome coverage plot of 102 cMAGs.</p>
Phylogenies related to: Codiversification of gut microbiota with humans
<p><span>The gut microbiomes of human populations worldwide have many core microbial species in common. However, within a species, some strains can show remarkable population specificity. The question is whether such specificity arises from a shared evolutionary history (codiversification) between humans and their microbes. To test for codiversification of host and microbiota, we analyzed paired gut metagenomes and human genomes for 1225 individuals in Europe, Asia, and Africa, including mothers and their children. Between and within countries, signals of codiversification were evident for humans and their gut microbes. Moreover, species displaying the strongest codiversification independently evolved traits characteristic of host dependency, including reduced genomes, and oxygen and temperature sensitivity. These findings all point to the importance of understanding the potential role of population-specific microbial strains in microbiome-mediated disease phenotypes.</span></p>
Simulation data for "MicroPro: using metagenomic unmapped reads to provide insights into human microbiota and disease associations"
<p>This is the simulation data used in the analysis of microbiome-disease association using MicroPro pipeline. Samples 0-24 and 25-49 are cases and controls respectively.</p>
Dataset supporting the paper "Effect of prebiotic fermentation products from primary human gut microbiota on an in vitro intestinal model"
<p>Short chain fatty acids (SCFA) originate from the bacterial fermentation of dietary fibre in the gastrointestinal tract. They are hypothesised to play a key role in microbiota–gut–brain crosstalk and the effect of individual SCFAs or mixtures thereof has been broadly studied. However, studies using fermentation products to evaluate the effect of microbiota-targeted interventions, such as prebiotics, probiotics, or diet, are sparse, particularly in humans. In addition, the complexity of these physiological processes translates as a challenge for their simulation<em> in vitro</em>. In this work, fermentation products of prebiotic-enriched media by bacteria present in primary human faecal samples were tested using an epithelium model based on a Caco-2/HT29-MTX co-culture. The prebiotics raftilose and fructo-oligosaccharides (FOS) were tested and the experimental conditions (contact time and minimal dilution) optimised to avoid cytotoxicity. None of the conditions tested compromised the intestinal epithelium integrity as verified by the TEER and the expression of the tight junction-specific protein – occludin. In addition, none of the fermentation products caused an inflammatory response as determinedby the expression of inflammatory genes by qRT-PCR. The products of fermentation of media enriched with FOS showed a moderate protective effect against the formation of reactive oxygen species. This work provides an important basis for the development of <em>in vitro</em> models using a simple approach to evaluate host-gut microbiota interactions, using co-cultures of intestinal cell lines and products of <em>in vitro</em> fermentations by primary human gut microbiota. </p>
Investigation of the Gut Microbiota in Regulating Nutrient Absorption in Humans
ClinicalTrials.gov study NCT02037295. IPD Sharing: Not stated. Countries: 1. Publications: 5.
Measuring Free Radicals in Human Sperm Cells Related to Microbiota and Lifestyle Factors
ClinicalTrials.gov study NCT05514223. IPD Sharing: UNDECIDED. Countries: 1. Publications: 14.
Human-associated microbiota suppress invading bacteria even under disruption by antibiotics
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Phylogenies related to: Codiversification of gut microbiota with humans
Open the record for dataset details and reuse information.
Distribution and activity of nitrate and nitrite reductases in the microbiota of the human intestinal tract
Open the record for dataset details and reuse information.
Fecal microbiota transplants (FMT) of three distinct human communities to germ-free mice exacerbated inflammation and decreased lung function in their offspring
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Large-scale metabolic interaction network of the mouse and human gut microbiota
<p>The role of our gut microbiota in health and disease is largely attributed to the collective metabolic activities of the inhabitant microbes. A system-level framework of the microbial community structure, mediated through metabolite transport, would provide important insights into the complex microbe-microbe and host-microbe chemical interactions. This framework, if adaptable to both mouse and human systems, would be useful for mechanistic interpretations of the vast amounts of experimental data from gut microbiomes in murine animal models, whether humanized or not. Here, we constructed a literature-curated, interspecies network of the mammalian gut microbiota for mouse and human hosts, called NJC19. This network is an extensive data resource, encompassing 838 microbial species (766 bacteria, 53 archaea, and 19 eukaryotes) and 6 host cell types, interacting through 8,224 small-molecule transport and macromolecule degradation events. Moreover, we compiled 912 negative associations between organisms and metabolic compounds that are not transportable or degradable by those organisms. Our network may facilitate experimental and computational endeavors for the mechanistic investigations of host-associated microbial communities.</p>
A catalog of genes and species of the human oral microbiota
<p></p><h1>Data sources</h1><br>The oral gene catalog was built using three primary sources:<br><br>Bacterial Genomes from the Human Oral Microbiome Database (HOMD).<br>Fungal Genomes from the NCBI RefSeq database.<br>Metagenomic Sequencing Data from multiple oral microbiome studies.<br>The creation of the oral gene catalog was a multi-step process, combining and refining genes from each source.<br><br><h1>Bacterial Genes</h1><br>A total of 1,505 bacterial genomes were downloaded from HOMD (version 20170215, accessed in December 2017). Genes shorter than 60 nucleotides or containing ambiguous bases were filtered out. Redundancy was removed using CD-HIT-EST (v4.6; parameters: -aS 0.9 -c 0.95 -T 0 -M 0 -t 0 -d 0 -G 0). This process yielded 1,459,394 unique HOMD genes for the catalog.<br><br><h1>Fungal Genes</h1><br>1,017 fungal genomes were downloaded from NCBI RefSeq (May 2017). For the 492 genomes lacking existing annotations, gene calling was performed using Genemark-ES in fungi mode. After initial redundancy removal with CD-HIT-EST (v4.6; parameters: -aS 0.9 -c 0.95 -T 0 -M 0 -t 0 -d 0 -G 0), genes were selected for inclusion only if their corresponding genome was present in at least 20% of the samples in one of the metagenomic cohorts, determined by mapping reads with Bowtie2 (v2.2.3). This led to the selection of 2,440,644 fungal genes.<br><br><h1>Metagenomic Sequencing Data</h1><br>The gene catalog was supplemented with data from 689 oral metagenomes, including newly sequenced samples, from the following studies:<br><br>Human Microbiome Project (HMP): 382 samples (bioproject PRJNA255439).<br>Chinese Cohort: 212 samples (bioproject PRJEB6997).<br>TwinsUK Cohort: 48 newly sequenced samples (bioproject: PRJEB38483).<br>Raw reads were subjected to quality control and trimmed using AlienTrimmer 0.4.0 (parameters: -k 10 -l 45 -m 5 -p 40 -q 20). Human sequences were removed by mapping against the human reference genome (GRCh38.p11) using Bowtie2 2.2.3. Metagenomic assembly was performed using SPAdes 3.9.0 (parameters: "-k 21,33,55 --only-assembler –meta" for Illumina paired-end data, or "--iontorrent -t 24 -m 300 -k 21,33,55 --only-assembler" for Ion Torrent single-end data). Contigs shorter than 500 bp or with coverage less than 2x were discarded. Gene calling was conducted with Prodigal (parameters: -m -p meta). Genes shorter than 60 bp were filtered out, and redundancy was removed with CD-HIT-EST (v4.6; parameters: -aS 0.9 -c 0.95 -T 0 -M 0 -t 0 -d 0 -G 0).<br><br><h1>Final Gene Catalog</h1><br>The final gene catalog was assembled by sequentially adding non-redundant genes from each data source. Genes from HOMD and fungal genomes were combined first using cd-hit-est-2d. Then, non-redundant genes from the HMP, Chinese, and TwinsUK cohorts were sequentially added using cd-hit-est-2d (same parameters as cd-hit-est). A final redundancy removal step was performed. This process resulted in a catalogue of 8.4 million non-redundant genes<br><br><h1>MSPs Recovery</h1><br>The 689 metagenomic samples were aligned against the final gene catalog using the Meteor software suite to produce a gene abundance table. Then, co-abundant genes were binned into 853 Metagenomic Species Pan-genomes (MSPs) using MSPminer.<br><br><h1>MSPs Taxonomic Annotation</h1><br>Taxonomic annotation for the MSPs was performed by aligning all core and accessory genes against representative genomes from the GTDB database (release r214) using blastn (task: megablast, word_size: 16).<br><br>A species-level assignment was given if over 50% of the genes matched a representative genome with a mean nucleotide identity of at least 95% and a mean gene length coverage of at least 90%.<br>The remaining MSPs were assigned to a higher taxonomic level (genus to superkingdom) if more than 50% of their genes shared the same annotation.<h1>Mapping rate distribution across public cohorts</h1>We generated mapping rate distribution plots using Meteor2 (default parameters), comparing performance between: PRJEB6997, PRJNA255439, PRJNA48479 (cohort used in catalogue assembly) and PRJEB24090, PRJEB28422, PRJEB45799 (independent cohort not used in assembly).<p></p>
Updated Metagenomic Species Pan-genomes (MSPs) of the human gastrointestinal microbiota
<p></p><h1>Gene catalog construction</h1><br>The methodology for creating the IGC2 catalog is described in the original papers: Li et al., 2014 and Wen et al., 2017<br><h1>MSP creation</h1><br>Reads from publicly available human gut metagenomes were aligned against the IGC2 catalog with the Meteor to produce a raw gene abundance table (10.4M genes quantified in >2000 samples). Then, co-abundant genes were binned in 1,989 Metagenomic Species Pan-genomes (MSPs, i.e. clusters of co-abundant genes that likely belong to the same microbial species) using MSPminer.<br><h1>MSPs taxonomic annotation</h1><br>MSPs taxonomic annotation was performed by aligning MSP core and accessory genes against representative genomes of the Genome Taxonomy Database (GTDB r207) using blastn (task = megablast, word_size = 16). The 20 best hits for each gene were kept (--max-target-seq 20). Using an in-house pipeline, a species-level assignment was given if > 50% of the genes matched the representative genome of a given species, with a mean identity ≥ 95% and mean gene length coverage ≥ 90%. The remaining MSPs were assigned to a higher taxonomic level (genus to superkingdom), if more than 50% of their genes had the same annotation.<br><h1>Construction of the phylogenetic tree</h1><br>39 universal phylogenetic markers genes were extracted from the MSPs with fetchMGs. Then, the markers were separately aligned with MUSCLE. The alignments were merged and trimmed with trimAl (parameters: -automated1). Finally, the phylogenetic tree was computed with FastTreeMP (parameters: -gamma -pseudo -spr -mlacc 3 -slownni). <h1>Mapping rate distribution across public cohorts</h1>We generated mapping rate distribution plots using Meteor2 (default parameters), comparing performance between: PRJEB1786, PRJEB5224, PRJEB6337, PRJNA422434 (cohort used in catalogue assembly) and PRJEB11532, PRJEB33500, PRJEB37249, PRNJNA834801 (independent cohort not used in assembly).<p></p>
A catalog of genes and species of the human skin microbiota
<p></p><h1>Dataset overview</h1><br>This dataset provides:<br>a non-redundant high-quality catalog of 2.9 million genes<br>392 Metagenomic Species Pangenomes (MSPs)<br>This dataset can be used to analyze shotgun sequencing data of the human skin microbiota.<br><h1>How to use this dataset</h1><br>Create a gene abundance table by aligning reads from each sample against the catalog. For this purpose, you can use Meteor or NGLess. Then, normalize raw counts by gene length.<br>Taxonomic profiling: the abundance of each species can be estimated as the average abundance of its 100 first core genes. To reduce the false positive rate, only consider that a species is present if at least 10/100 marker genes are detected.<br><h1>Methods</h1><br><h2>Data sources</h2><br>This dataset was built using the following data sources:<br>118 isolate-derived genomes from the HMRGD<br>246 isolate-derived genomes from the Skin Microbial Genome Collection (SMGC)<br>1,407 skin metagenome assemblies from the Skin Microbial Genome Collection (SMGC)<br><h2>Non-redundant gene catalog</h2><br>After filtering out short contigs (<1500 bp), genes were predicted with Prodigal on genomes (mode: single) and metagenome assemblies (mode: meta). Complete genes (partial=00) were pooled and clustered with cd-hit-est (parameters -c 0.95 -aS 0.90 -G 0 -d 0 -M 0 -T 0) by choosing those from the longest contigs as representatives.<br><h2>Functional annotation</h2><br>KOs assignments were obtained with KofamScan using the KEGG 107 database.<br><h2>MSPs recovery</h2><br>Reads from the 1,120 skin metagenomes available in the bioproject PRJNA46333 were aligned against the non-redundant gene catalog with the Meteor software suite to produce a raw gene abundance table (2.9M genes quantified in 1,120samples). Then, co-abundant genes were binned in 392 Metagenomic Species Pan-genomes (MSPs, i.e. clusters of co-abundant genes that likely belong to the same microbial species) using MSPminer.<br><h2>MSPs taxonomic annotation</h2><br>Taxonomic annotation was performed by alignment of all core and accessory genes against representative genomes of the GTDB database (release r214) using blastn (version 2.7.1, task = megablast, word_size = 16). A species-level assignment was given if > 50% of the genes matched the representative genome of a given species, with a mean nucleotide identity ≥ 95% and mean gene length coverage ≥ 90%. The remaining MSPs were assigned to a higher taxonomic level (genus to superkingdom), if more than 50% of their genes had the same annotation.<br><h2>Construction of the phylogenetic tree</h2><br>39 universal phylogenetic markers genes were extracted from the MSPs (or the corresponding genome if available) with fetchMGs. Then, the markers were separately aligned with MUSCLE. The 40 alignments were merged and trimmed with trimAl (parameters: -automated1). Finally, the phylogenetic tree was computed with FastTreeMP (parameters: -gamma -pseudo -spr -mlacc 3 -slownni).<h1>Mapping rate distribution across public cohorts</h1>We generated mapping rate distribution plots using Meteor2 (default parameters), comparing performance between: PRJNA46333 (cohort used in catalogue assembly) and PRJEB80549 (independent cohort not used in assembly).<p></p>
Human-derived fecal microbiota transplantation alleviates mitochondrial dysfunction and social deficits in the BTBR mouse model for autism
<p><span><span>Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition characterized by social communication deficiencies and stereotypic behaviors influenced by hereditary and/or environmental risk factors. There are currently no approved medications for treating the core symptoms of ASD. Human fecal microbiota transplantation (FMT) has emerged as a potential intervention to improve autistic symptoms, but the underlying mechanisms are not fully understood. </span></span><span><span><span><span>In this study, we evaluated the effects of human-derived FMT on behavioral and multi-omics profiles of the BTBR mice, an established model for ASD. FMT effectively alleviated the social deficits in the BTBR mice and normalized their distinct plasma metabolic profile, notably reducing the elevated long-chain acylcarnitines. Integrative analysis linked these phenotypic changes to specific <em>Bacteroides</em> species and vitamin B<sub>6</sub> metabolism. Indeed, vitamin B<sub>6</sub> supplementation improved the social behaviors in BTBR mice. Collectively, these findings shed new light on the interplay between FMT and vitamin B<sub>6</sub> metabolism and revealed a potential mechanism underlying the therapeutic role of FMT in ASD.</span></span></span></span></p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.