Mouse gut metagenome
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA832491 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:We compared the microbiota of paired mouse caecal contents and faeces by applying a multi-omic approach, including 16S rDNA sequencing, shotgun metagenomics, and shotgun metaproteomics. The aim of the study was to verify whether faecal samples are a reliable proxy for the mouse colonic luminal microbiota, as well as to identify changes in taxonomy and functional activity between caecal and faecal microbial communities, which have to be carefully considered when using stool as sample for mouse gut microbiota investigations.
2017-03-31 | PXD004911 | Pride
Project description:To explore the effects of gut microbiota of young (8 weeks) or old mice (18～20 months) on stroke, feces of young (Y1-Y9) and old mice (O6-O16) were collected and analyzed by 16s rRNA sequencing. Then stroke model was established on young mouse receive feces from old mouse (DOT1-15) and young mouse receive feces from young mouse (DYT1-15). 16s rRNA sequencing were also performed for those young mice received feces from young and old mice.
2021-10-15 | E-MTAB-10837 | biostudies-arrayexpress
Project description:To compare the similarities and differences in species diversity of the gut microbiota between the patients with melasma and healthy subjects. The feces were collected for 16S rRNA sequencing analysis of the gut microbiota.
2022-10-25 | GSE214430 | GEO
Project description:Analysis of breast cancer survivors' gut microbiota after lifestyle intervention, during the COVID-19 lockdown, by 16S sequencing of fecal samples.
2023-01-13 | E-MTAB-12486 | biostudies-arrayexpress
Project description:Gut microbiota were assessed in 540 colonoscopy-screened adults by 16S rRNA gene sequencing of stool samples. Investigators compared gut microbiota diversity, overall composition, and normalized taxon abundance among these groups.
| 2255499 | ecrin-mdr-crc
Project description:We used 16S V3/V4 region amplification to evaluate the composition of bacteria species in mouse fecal pellets. Fecel pellets were collected from young-adult (12 weeks old) wild type C57Bl/6 mice and aged (72 weeks old) wild type C57Bl/6 mice after 21 days of vehicle or antibiotics treatment (to induce gut microbiota depletion). In one sequencing round, we sequenced a total of 12 different fecal samples (3 young control, 3 aged control, 3 young depleted gut microbiota (ABX) and 3 aged depleted gut microbiota (ABX)). Amplicons were indexed using the Nextera XT Index Kit and pooled into a library for Illumina sequencing.
2020-11-03 | GSE160628 | GEO
Project description:In this study, we performed a comparative analysis of gut microbiota composition and gut microbiome-derived bacterial extracellular vesicles (bEVs) isolated from patients with solid tumours and healthy controls. After isolating bEVs from the faeces of solid tumour patients and healthy controls, we performed spectrometry analysis of their proteomes and next-generation sequencing (NGS) of the 16S gene. We also investigated the gut microbiomes of faeces from patientsand controls using 16S rRNA sequencing. Machine learning was used to classify the samples into patients and controls based on their bEVs and faecal microbiomes.
2024-08-08 | PXD047510 | Pride
Project description:Advanced age is associated with chronic low-grade inflammation, which is usually referred to as inflammaging. Elderly are also known to have an altered gut microbiota composition. However, whether inflammaging is a cause or consequence of an altered gut microbiota composition is not clear. In this study gut microbiota from young or old conventional mice was transferred to young germ-free mice. Four weeks after gut microbiota transfer immune cell populations in spleen, Peyer’s patches, and mesenteric lymph nodes from conventionalized germ-free mice were analyzed by flow cytometry. In addition, whole-genome gene expression in the ileum was analyzed by microarray. Gut microbiota composition of donor and recipient mice was analyzed with 16S rDNA sequencing. Here we show by transferring aged microbiota to young germ-free mice that certain bacterial species within the aged microbiota promote inflammaging. This effect was associated with lower levels of Akkermansia and higher levels of TM7 bacteria and Proteobacteria in the aged microbiota after transfer. The aged microbiota promoted inflammation in the small intestine in the germ-free mice and enhanced leakage of inflammatory bacterial components into the circulation was observed. Moreover, the aged microbiota promoted increased T cell activation in the systemic compartment. In conclusion, these data indicate that the gut microbiota from old mice contributes to inflammaging after transfer to young germ-free mice.
2018-02-14 | GSE104063 | GEO
Project description:16S rDNA Amplicon Sequencing of gut microbiota in mice
| PRJNA745400 | ENA
Project description:Gut microbiome research is rapidly moving towards the functional characterization of the microbiota by means of shotgun meta-omics. Here, we selected a cohort of healthy subjects from an indigenous and monitored Sardinian population to analyze their gut microbiota using both shotgun metagenomics and shotgun metaproteomics. We found a considerable divergence between genetic potential and functional activity of the human healthy gut microbiota, in spite of a quite comparable taxonomic structure revealed by the two approaches. Investigation of inter-individual variability of taxonomic features revealed Bacteroides and Akkermansia as remarkably conserved and variable in abundance within the population, respectively. Firmicutes-driven butyrogenesis (mainly due to Faecalibacterium spp.) was shown to be the functional activity with the higher expression rate and the lower inter-individual variability in the study cohort, highlighting the key importance of the biosynthesis of this microbial by-product for the gut homeostasis. The taxon-specific contribution to functional activities and metabolic tasks was also examined, giving insights into the peculiar role of several gut microbiota members in carbohydrate metabolism (including polysaccharide degradation, glycan transport, glycolysis and short-chain fatty acid production). In conclusion, our results provide useful indications regarding the main functions actively exerted by the gut microbiota members of a healthy human cohort, and support metaproteomics as a valuable approach to investigate the functional role of the gut microbiota in health and disease.
2017-07-19 | PXD005780 | Pride