Metagenomic
Ontology highlight
ABSTRACT:
TISSUE(S): ['feces']
SUBMITTER: Cong Peng
PROVIDER: OEX00014943 | NODE | 2021-12-16
REPOSITORIES: NODE
Similar Datasets
Project description:Firs 1106 16S rDNA data for the Flemish Gut Flora Project
| EGAD00001001936 | EGA
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:Opioids such as morphine have many beneficial properties as analgesics, however, opioids may induce multiple adverse gastrointestinal symptoms. We have recently demonstrated that morphine treatment results in significant disruption in gut barrier function leading to increased translocation of gut commensal bacteria. However, it is unclear how opioids modulate the gut homeostasis. By using a mouse model of morphine treatment, we studied effects of morphine treatment on gut microbiome. We characterized phylogenetic profiles of gut microbes, and found a significant shift in the gut microbiome and increase of pathogenic bacteria following morphine treatment when compared to placebo. In the present study, wild type mice (C57BL/6J) were implanted with placebo, morphine pellets subcutaneously. Fecal matter were taken for bacterial 16s rDNA sequencing analysis at day 3 post treatment. A scatter plot based on an unweighted UniFrac distance matrics obtained from the sequences at OTU level with 97% similarity showed a distinct clustering of the community composition between the morphine and placebo treated groups. By using the chao1 index to evaluate alpha diversity (that is diversity within a group) and using unweighted UniFrac distance to evaluate beta diversity (that is diversity between groups, comparing microbial community based on compositional structures), we found that morphine treatment results in a significant decrease in alpha diversity and shift in fecal microbiome at day 3 post treatment compared to placebo treatment. Taxonomical analysis showed that morphine treatment results in a significant increase of potential pathogenic bacteria. Our study shed light on effects of morphine on the gut microbiome, and its role in the gut homeostasis.
2018-04-16 | E-MTAB-5546 | biostudies-arrayexpress
Project description:Morphine and its pharmacological derivatives are the most prescribed analgesics for moderate to severe pain management. However, chronic use of morphine reduces pathogen clearance and induces bacterial translocation across the gut barrier. The enteric microbiome has been shown to play a critical role in the preservation of the mucosal barrier function and metabolic homeostasis. Here, we show for the first time, using bacterial 16s rDNA sequencing, that chronic morphine treatment significantly alters the gut microbial composition and induces preferential expansion of the gram-positive pathogenic and reduction of bile-deconjugating bacterial strains. A significant reduction in both primary and secondary bile acid levels was seen in the gut, but not in the liver with morphine treatment. Morphine induced microbial dysbiosis and gut barrier disruption was rescued by transplanting placebo-treated microbiota into morphine-treated animals, indicating that microbiome modulation could be exploited as a therapeutic strategy for patients using morphine for pain management. In this study, we establish a link between the two phenomena, namely gut barrier compromise and dysregulated bile acid metabolism. We show for the first time that morphine fosters significant gut microbial dysbiosis and disrupts cholesterol/bile acid metabolism. Changes in the gut microbial composition is strongly correlated to disruption in host inflammatory homeostasis13,14 and in many diseases (e.g. cancer/HIV infection), persistent inflammation is known to aid and promote the progression of the primary morbidity. We show here that chronic morphine, gut microbial dysbiosis, disruption of cholesterol/bile acid metabolism and gut inflammation; have a linear correlation. This opens up the prospect of devising minimally invasive adjunct treatment strategies involving microbiome and bile acid modulation and thus bringing down morphine-mediated inflammation in the host.
2016-06-01 | E-MTAB-3722 | biostudies-arrayexpress
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:This study evaluated the biocontrol efficacy, growth-promoting potential, and molecular mechanisms of the actinomycete strain FJSM-07, identified via 16S rDNA sequencing as Streptomyces murinus.
2026-07-14 | GSE338066 | GEO
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:Six- to eight-week old CD1 male mice were sleep-deprived for 24 hours by placing them in a small platform in a water tank. Their ileum samples were harvested every 4 hours on the next day (time point: ZT1,ZT5,ZT9,ZT13,ZT17,ZT21). The ileum samples were subjected to 16s rDNA sequencing. Control group (C1,C5,C9,C13,C17,C21, n=36). SD group (SD1,SD5,SD9,SD13,SD17,SD21, n=36).
2025-08-29 | E-MTAB-15462 | biostudies-arrayexpress
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