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2,708 results for “microbiota”
Immune-mediated hematological disease in dogs is associated with alterations of the fecal microbiota: a pilot study
<div> <h3>Background</h3> <p>The dog is the most popular companion animal and is a valuable large animal model for several human diseases. Canine immune-mediated hematological diseases, including immune-mediated hemolytic anemia (IMHA) and immune thrombocytopenia (ITP), share many features in common with autoimmune hematological diseases of humans. The gut microbiome has been linked to systemic illness, but few studies have evaluated its association with immune-mediated hematological disease. To address this knowledge gap, 16S rRNA gene sequencing was used to profile the fecal microbiota of dogs with spontaneous IMHA and ITP at presentation and following successful treatment. In total, 21 affected and 13 healthy control dogs were included in the study.</p> <h3>Results</h3> <p>IMHA/ITP is associated with remodeling of fecal microbiota, marked by decreased relative abundance of the spirochete <em>Treponema</em> spp., increased relative abundance of the pathobionts <em>Clostridium septicum</em> and <em>Escherichia coli</em>, and increased overall microbial diversity. Logistic regression analysis demonstrated that <em>Treponema</em> spp. were associated with decreased risk of IMHA/ITP (odds ratio [OR] 0.24–0.34), while Ruminococcaceae UCG-009 and Christensenellaceae R-7 group were associated with increased risk of disease (OR =&thinsp;6.84 [95% CI 2–32.74] and 8.36 [95% CI 1.85–71.88] respectively).</p> <h3>Conclusions</h3> <p>This study demonstrates an association of immune-mediated hematological diseases in dogs with fecal dysbiosis, and points to specific bacterial genera as biomarkers of disease. Microbes identified as positive or negative risk factors for IMHA/ITP represent an area for future research as potential targets for new diagnostic assays and/or therapeutic applications.</p> </div>
Temporal patterns of gut microbiota in lemurs (Eulemur rubriventer) living in intact and disturbed habitats.
<p>This data set includes the R scripts (combined into one R markdown document) and input files needed to create the main text figures and major analyses for the paper "Grieneisen L, Hays A, Cook E, Blekhman R, and Tecot S. 2024. Temporal patterns of gut microbiota in lemurs (<em>Eulemur rubriventer</em>) living in intact and disturbed habitats. American Journal of Primatology." </p>
Distinct oral-associated gastric microbiota and Helicobacter pylori communities for spatial microbial heterogeneity in gastric cancer
<p><span>STROBE Statement—Checklist of items that should be included in reports of <strong><em>case-control studies</em></strong> </span></p>
Figure 1 in Effect of Moringa olifera leaves on growth and gut microbiota of Nile tilapia (Oreochromis niloticus)
Figure 1. Growth performance parameters.
Infection of mice by the enteroaggregative E. coli strain 042 and two mutant derivatives overexpressing virulence factors: impact on disease markers, gut microbiota and concentration of SCFAs in feces
<p>This dataset contains raw sequencing data from the microbiota analysis conducted in the enteroaggregative E. coli strain 042 study. The data includes FASTQ files generated from Illumina sequencing, along with metadata describing the sample collection and processing methods.</p>
Oral microbiota composition and its relationship with epidemiological, clinical and microbiological variables of SARS-CoV-2 infection in children and adults under strict home confinement in Barcelona, Spain
Open the record for dataset details and reuse information.
Figure 4 in Prevalence of Spiroplasma and interaction with wild Glossina tachinoides microbiota
Figure 4. Prevalence of co-infection Spiroplasma-Trypanosoma in wild G. tachinoides.
Dynamic Crosstalk Between Female Gonadal Hormones and Vaginal Microbiota Across Various Reproductive Phases
<p>Vaginal samples for 16S rRNA sequencing are collected from 150 healthy women across five reproductive phases: follicular phase, luteal phase, early pregnancy, lactation, and menopause, with 30 samples per group.</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>
Data for: Soil domestication by rice cultivation results in plant-soil feedback through shifts in soil microbiota
<p>This repository contains the data for the manuscript entitled "Soil domestication by rice cultivation results in plant-soil feedback through shifts in soil microbiota." Analysis scripts can be found at <a href="https://github.com/bulksoil/SoilDomestication">https://github.com/bulksoil/SoilDomestication</a></p>
Figure 2 in Diversity of the aerobic cloacal microbiota of syntopic lizard species (Reptilia: Sauria) from a low-mountain area in Western Bulgaria
Figure 2. Composition of the cloacal microbiota of each lizard species.
Data from "Exploring Gut Microbiota Profile Induced by Antipsychotics in Schizophrenic Patients: Insights from an Eastern European Pilot Study", Nita (Ilie) et al. 2025
<p>Dataset containing raw demultiplexed FASTQ files of the sequenced samples, generated by the Illumina MiSeq platform. </p> <p>MiSeq_demultiplexed-V3_V4-HC_SCZ.zip - MiSeq raw sequences of the V3-V4 region 16S rRNA gene from subject fecal material. This ZIP file contains the FASTQ files of the paired-end reads (R1: forward reads; R2: reverse reads) produced for each sample using the MiSeq platform.</p> <p>metadata-HC_SCZ.csv - The list of sequenced samples and associated metadata.</p>
Figure 1 in Prevalence of Spiroplasma and interaction with wild Glossina tachinoides microbiota
Figure 1. Geographical locations of tsetse samples in Africa.
Data supporting the article: "Comparative analysis of fecal microbiota between adolescents with early-onset psychosis and adults with schizophrenia"
<p>This dataset supports the article titled <em>"Comparative analysis of fecal microbiota between adolescents with early-onset psychosis and adults with schizophrenia.", </em>available at<em> <a href="https://doi.org/10.3390/microorganisms12102071">https://doi.org/10.3390/microorganisms12102071</a></em><em>.</em></p> <p>The dataset includes fecal microbiota sequencing data from adolescent patients with early-onset psychosis, adult patients with schizophrenia, and non-psychotic controls. The data were generated using 16S rRNA gene sequencing and analyzed with QIIME2 and PICRUSt2 to assess microbial diversity and functional pathways. Variables such as age, diagnosis, and medication use are included.</p> <p>The dataset contains:</p> <ul> <li><strong>Processed results</strong> from fecal microbiota analysis (OTUs and taxonomic classifications)</li> <li><strong>Metadata</strong> associated with each sample (age, diagnosis, medication)</li> <li><strong>Results from diversity analysis</strong> (alpha and beta diversity metrics)</li> <li><strong>Functional analysis</strong> of microbial pathways (PICRUSt2)</li> </ul> <p>These data are essential for reproducing the findings discussed in the article. Note that the raw sequencing data are available upon request.</p>
Skin autonomous antibody production regulates host-microbiota interactions
<p>Supplemental Tables containing bulk BCR-sequencing clonotype results for all samples and for sequences with somatic hypermutations. Data, analysis and results are described in more detail in the accompaning publication Gribonika et al., "Host-microbiota interaction is regulated by autonomous skin-intrinsic germinal centers", Nature, 2024</p>
Drivers of change and stability in the gut microbiota of an omnivorous avian migrant exposed to artificial food supplementation
<p>Human activities shape resources available to wild animals, impacting diet and likely altering their microbiota and overall health. We examined drivers shaping microbiota profiles of common cranes (Grus grus) in agricultural habitats by comparing gut microbiota and crane movement patterns (GPS-tracking) over three periods of their migratory cycle, and by analyzing the effect of artificially-supplemented food provided as part of a crane-agriculture management program. We sampled fecal droppings in Russia (non-supplemented, pre-migration) and in Israel in late fall (non-supplemented, post-migration) and winter (supplemented and non-supplemented, wintering). As supplemented food is typically homogenous, we predicted lower microbiota diversity and different composition in birds relying on supplementary feeding. We did not observe changes in microbial diversity with food supplementation, as diversity differed only in samples from non-supplemented wintering sites. However, both food supplementation and season affected bacterial community composition and led to increased abundance of specific genera (mostly Firmicutes). Cranes from the non-supplemented groups spent most of their time in agricultural fields, likely feeding on residual grain when available, while food-supplemented cranes spent most of their time at the feeding station. Thus, non-supplemented and food-supplemented diets likely diverge only in winter, when crop rotation and depletion of anthropogenic resources may lead to a more variable diet in non-supplemented sites. Our results support the role of diet in structuring bacterial communities and show that they undergo both seasonal and human-induced shifts. Movement analyses provide important clues regarding host diet and behavior towards understanding how human-induced changes shape the gut microbiota in wild animals.</p>
Deciphering the low abundance microbiota of presumed aseptic hip and knee implants
<p><strong>Deciphering the low abundance microbiota of presumed aseptic hip and knee implants</strong></p> <p>This data set includes input files and results associated with our work "Deciphering the low abundance microbiota of presumed aseptic hip and knee implants".</p> <p><strong>Contents</strong></p> <p><em>aitch_dist.txt</em>: Aitchison distance matrix</p> <p><em>clinical_envfit.RData</em>: envfit results for clinical information</p> <p><em>contam_by_freq_0.2.txt</em>: decontam results (identifying contaminants by frequency)</p> <p><em>contam_by_prev_0.2.txt</em>: decontam results (identifying contaminants by prevalence)</p> <p><em>counts.txt</em>: counts table resulting from reads processed with custom demultiplexing script</p> <p><em>cutadapt_counts.txt</em>: counts table resulting from reads processed with cutadapt</p> <p><em>cutadapt_meta.txt</em>: metadata table accompanying <em>cutadapt_counts.txt</em></p> <p><em>cutadapt_tax.txt</em>: taxonomy table resulting from reads processed with cutadapt</p> <p><em>cutadapt_track.txt</em>: table summarizing retention of reads processed with cutadapt throughout the DADA2 pipeline</p> <p><em>dna_concs.txt</em>: DNA concentrations per sample</p> <p><em>extraction_aldex2.txt</em>: ALDEx2 results for comparison of DNA extraction methodologies</p> <p><em>extraction_envfit_and_pca.RData</em>: envfit results and PCA biplot for DNA extraction methodologies</p> <p><em>extraction_shannon_diversity.txt</em>: Shannon diversity and extraction methodology per sample</p> <p><em>fwd_barcodes.fasta</em>: forward barcodes for use by cutadapt</p> <p><em>meta.txt</em>: metadata table accompanying <em>counts.txt</em></p> <p><em>meta_clinical.txt</em>: metadata table for clinical information</p> <p><em>meta_st.txt</em>: metadata for use by SourceTracker</p> <p><em>not_contam_0.05.txt</em>: decontam results (identifying non-contaminants)</p> <p><em>pt_oac_aldex2.txt</em>: ALDEx2 results for comparison of sample type, controlling for the effect of DNA extraction methodology</p> <p><em>pt_oac_envfit_and_pca.RData</em>: envfit results and PCA biplot for sample type </p> <p><em>pt_oac_shannon_diversity.txt</em>: Shannon diversity, sample type, and extraction methodology per sample</p> <p><em>rev_barcodes.fasta</em>: reverse barcodes for use by cutadapt</p> <p><em>spike_1_dists.txt</em>: Aitchison distances between spike 1 samples and other samples on the same plate</p> <p><em>spike_2_dists.txt</em>: Aitchison distances between spike 1 samples and other samples on the same plate</p> <p><em>tax.txt</em>: taxonomy table resulting from reads processed with custom demultiplexing script</p> <p><em>track.txt</em>: table summarizing retention of reads processed with custom demultiplexing script throughout the DADA2 pipeline</p> <p><strong>Code Availability</strong></p> <p>Scripts to process and produce these data are available at https://github.com/charlie-carr/implant_microbiota</p> <p><strong>Citation</strong></p> <p>Carr C, Wilcox H, Burton JP, Menon S, Al KF, O’Gorman D, et al. (2021) Deciphering the low abundance microbiota of presumed aseptic hip and knee implants. PLoS ONE 16(9): e0257471. https://doi.org/10.1371/journal.pone.0257471</p>
16S processed data and shell processing scripts for "Epithelial-myeloid exchange of MHCII constrains immunity and microbiota composition"
<p>Main repo for MHCII on IECs 16S processing code.</p>
Drivers and Determinants of Strain Dynamics Following Faecal Microbiota Transplantation
<p>Faecal microbiota transplantation (FMT) is an efficacious therapeutic intervention, but its clinical mode of action and underlying microbiome dynamics remain poorly understood. Here, we analysed the metagenomes associated with 142 FMTs, in a time series-based meta-study across five disease indications. We quantified strain-level dynamics of 1,089 microbial species based on their pangenome, complemented with 47,548 newly constructed metagenome-assembled genomes. Using subsets of procedural-, host- and microbiome-based variables, LASSO-regularised regression models accurately predicted the colonisation and resilience of donor and recipient microbes, as well as turnover of individual species. Linking this to putative ecological mechanisms, we found these sets of variables to be informative of the underlying processes that shape the post-FMT gut microbiome. Recipient factors and complementarity of donor and recipient microbiomes, encompassing entire communities to individual strains, were the main determinants of individual strain population dynamics, and mostly independent of clinical outcomes. Recipient community state and the degree of residual strain depletion provided a neutral baseline for donor strain colonisation success, in addition to inhibitive priority effects between species and conspecific strains, as well as putatively adaptive processes. Our results suggest promising tunable parameters to enhance donor flora colonisation or recipient flora displacement in clinical practice, towards the development of more targeted and personalised therapies.</p>
Does ivermectin treatment for endemic hookworm infection alter the gut microbiota of endangered Australian sea lion pups?
<p>The gut microbiota is essential for the development and maintenance of the hosts' immune system. Disturbances to the gut microbiota in early life stages can result in long-lasting impacts on host health. This study aimed to determine if topical ivermectin treatment for endemic hookworm (Uncinaria sanguinis) infection in endangered Australian sea lion (Neophoca cinerea) pups resulted in gut microbial changes. The gut microbiota was characterised for untreated (control) (n = 23) and treated (n = 23) Australian sea lion pups sampled during the 2019 and 2020/21 breeding seasons at Seal Bay, Kangaroo Island. Samples were collected pre- and post-treatment on up to four occasions over a four-to-five-month period. The gut microbiota of untreated (control) and treated pups in both seasons were dominated by five bacterial phyla, Fusobacteria, Firmicutes, Proteobacteria, Actinobacteria, and Bacteroides. A significant difference in alpha diversity between treatment groups was seen in pups sampled during the 2020/21 breeding season (p = 0.008), with higher richness and diversity in treated pups. Modeling the impact of individual pup identification (ID), capture, pup weight (kg), standard length (cm), age, and sex on beta diversity revealed that pup ID accounted for most of the variation (35% in 2019 and 42% in 2020/21), with pup ID, capture, and age being the only significant contributors to microbial variation (p < 0.05). There were no statistically significant differences in the composition of the microbiota between treatment groups in both the 2019 and 2020/21 breeding seasons, indicating that topical ivermectin treatment did not alter the composition of the gut microbiota. To our knowledge, this is the first study to characterise the gut microbiota of free-ranging Australian pinniped pups, compare the composition across multiple time points, and consider the impact of parasitic treatment on the overall diversity and microbial composition of the gut microbiota. Importantly, the lack of compositional changes in the gut microbiota with topical ivermectin treatment supports the utility of topical ivermectin as a safe and minimally invasive management strategy to enhance pup survival in this endangered species. </p>
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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.