Ontology highlight
ABSTRACT:
PROVIDER: PRJNA419083 | ENA |
REPOSITORIES: ENA
Similar Datasets
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:Xiangjiang River (Hunan, China) has been contaminated with heavy metal for several decades by surrounding factories. However, little is known about the influence of a gradient of heavy metal contamination on the diversity, structure of microbial functional gene in sediment. To deeply understand the impact of heavy metal contamination on microbial community, a comprehensive functional gene array (GeoChip 5.0) has been used to study the functional genes structure, composition, diversity and metabolic potential of microbial community from three heavy metal polluted sites of Xiangjiang River. Three groups of samples, A, B and C. Every group has 3 replicates.
2016-08-02 | E-GEOD-85064 | biostudies-arrayexpress
Project description:Xiangjiang River (Hunan, China) has been contaminated with heavy metal for several decades by surrounding factories. However, little is known about the influence of a gradient of heavy metal contamination on the diversity, structure of microbial functional gene in sediment. To deeply understand the impact of heavy metal contamination on microbial community, a comprehensive functional gene array (GeoChip 5.0) has been used to study the functional genes structure, composition, diversity and metabolic potential of microbial community from three heavy metal polluted sites of Xiangjiang River.
2016-08-02 | GSE85064 | GEO
Project description:Significant gut microbiota heterogeneity exists amongst UC patients though the clinical implications of this variance are unknown. European and South Asian UC patients exhibit distinct disease risk alleles, many of which regulate immune function and relate to variation in gut microbiota β-diversity. We hypothesized ethnically distinct UC patients exhibit discrete gut microbiotas with unique luminal metabolic programming that influence adaptive immune responses and relate to clinical status. Using parallel bacterial 16S rRNA and fungal ITS2 sequencing of fecal samples (UC n=30; healthy n=13), we corroborated previous observations of UC-associated depletion of bacterial diversity and demonstrated significant gastrointestinal expansion of Saccharomycetales as a novel UC characteristic. We identified four distinct microbial community states (MCS 1-4), confirmed their existence using microbiota data from an independent UC cohort, and show they co-associate with patient ethnicity and degree of disease severity. Each MCS was predicted to be uniquely enriched for specific amino acid, carbohydrate, and lipid metabolism pathways and exhibited significant luminal enrichment of metabolic products from these pathways. Using a novel in vitro human DC/T-cell assay we show that DC exposure to patient fecal water led to MCS -specific changes in T-cell populations, particularly the Th1:Th2 ratio, and that patients with the most severe disease exhibited the greatest Th2 skewing. Thus, based on ethnicity, microbiome composition, and associated metabolic dysfunction, UC patients may be stratified in a clinically and immunologically meaningful manner, providing a platform for the development of FMC-focused therapy. Fecal microbiome was assessed with Affymetrix PhyloChip arrays from patients with ulcerative colitis and healthy controls.
2016-07-25 | E-GEOD-78724 | biostudies-arrayexpress