Ontology highlight
ABSTRACT:
PROVIDER: PRJNA965883 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR24389100_1.fastq.gz | Fastqsanger.gz | |||
| SRR24389100_2.fastq.gz | Fastqsanger.gz | |||
| SRR24389101_1.fastq.gz | Fastqsanger.gz | |||
| SRR24389101_2.fastq.gz | Fastqsanger.gz | |||
| SRR24389102_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 96 |
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:The human colon contains an extensively diverse microbial ecosystem and one of the most numerous communities of immune cells. Studies have highlighted dynamic crosstalk between immune cells and commensals. While studies have demonstrated increasing diversity of microbiota from stomach to stool, whether and how immune cell heterogeneity and microbiota diversity change across the colon is undefined. Furthermore, whether these changes are co-depended in the healthy colon is unknown. Here, tissue samples are collected from caecum, transverse colon, sigmoid colon and mLN of cadaveric donors by the Cambridge Biorepository of Translational Medicine (CBTM). We use single cell RNA sequencing (10X genomics) to assess the dynamics of immune cell populations across the colon and in matching lymph nodes. Associated microbiome 16S sequencing data is available.
2020-01-01 | E-MTAB-8474 | biostudies-arrayexpress
Project description:The human colon contains an extensively diverse microbial ecosystem and one of the most numerous communities of immune cells. Studies have highlighted dynamic crosstalk between immune cells and commensals. While studies have demonstrated increasing diversity of microbiota from stomach to stool, whether and how immune cell heterogeneity and microbiota diversity change across the colon is undefined. Furthermore, whether these changes are co-depended in the healthy colon is unknown. Here, tissue samples are collected from caecum, transverse colon, sigmoid colon and mLN of cadaveric donors by the Cambridge Biorepository of Translational Medicine (CBTM). We use single cell RNA sequencing (10X genomics) to assess the dynamics of immune cell populations across the colon and in matching lymph nodes. Associated microbiome 16S sequencing data is available.
2020-01-01 | E-MTAB-8007 | biostudies-arrayexpress
Project description:The human colon contains an extensively diverse microbial ecosystem and one of the most numerous communities of immune cells. Studies have highlighted dynamic crosstalk between immune cells and commensals. While studies have demonstrated increasing diversity of microbiota from stomach to stool, whether and how immune cell heterogeneity and microbiota diversity change across the colon is undefined. Furthermore, whether these changes are co-depended in the healthy colon is unknown. Here, tissue samples are collected from caecum, transverse colon, sigmoid colon and mLN of cadaveric donors by the Cambridge Biorepository of Translational Medicine (CBTM). We use single cell RNA sequencing (10X genomics) to assess the dynamics of immune cell populations across the colon and in matching lymph nodes. Associated microbiome 16S sequencing data is available.
2020-01-01 | E-MTAB-8476 | biostudies-arrayexpress
Project description:The human colon contains an extensively diverse microbial ecosystem and one of the most numerous communities of immune cells. Studies have highlighted dynamic crosstalk between immune cells and commensals. While studies have demonstrated increasing diversity of microbiota from stomach to stool, whether and how immune cell heterogeneity and microbiota diversity change across the colon is undefined. Furthermore, whether these changes are co-depended in the healthy colon is unknown. Here, tissue samples are collected from caecum, transverse colon, sigmoid colon and mLN of cadaveric donors by the Cambridge Biorepository of Translational Medicine (CBTM). We use single cell RNA sequencing (10X genomics) to assess the dynamics of immune cell populations across the colon and in matching lymph nodes. Associated microbiome 16S sequencing data is available.
2020-01-01 | E-MTAB-8486 | biostudies-arrayexpress
Project description:The human colon contains an extensively diverse microbial ecosystem and one of the most numerous communities of immune cells. Studies have highlighted dynamic crosstalk between immune cells and commensals. While studies have demonstrated increasing diversity of microbiota from stomach to stool, whether and how immune cell heterogeneity and microbiota diversity change across the colon is undefined. Furthermore, whether these changes are co-depended in the healthy colon is unknown. Here, tissue samples are collected from caecum, transverse colon, sigmoid colon and mLN of cadaveric donors by the Cambridge Biorepository of Translational Medicine (CBTM). We use single cell RNA sequencing (10X genomics) to assess the dynamics of immune cell populations across the colon and in matching lymph nodes. Associated microbiome 16S sequencing data is available.
2020-01-01 | E-MTAB-8484 | biostudies-arrayexpress
Project description:Pancreatic cancer is the 3rd most prevalent cause of cancer related deaths in United states alone, with over 55000 patients being diagnosed in 2019 alone and nearly as many succumbing to it. Late detection, lack of effective therapy and poor understanding of pancreatic cancer systemically contributes to its poor survival statistics. Obesity and high caloric intake linked co-morbidities like type 2 diabetes (T2D) have been attributed as being risk factors for a number of cancers including pancreatic cancer. Studies on gut microbiome has shown that lifestyle factors as well as diet has a huge effect on the microbial flora of the gut. Further, modulation of gut microbiome has been seen to contribute to effects of intensive insulin therapy in mice on high fat diet. In another study, abnormal gut microbiota was reported to contribute to development of diabetes in Db/Db mice. Recent studies indicate that microbiome and microbial dysbiosis plays a role in not only the onset of disease but also in its outcome. In colorectal cancer, Fusobacterium has been reported to promote therapy resistance. Certain intra-tumoral bacteria have also been shown to elicit chemo-resistance by metabolizing anti-cancerous agents. In pancreatic cancer, studies on altered gut microbiome have been relatively recent. Microbial dysbiosis has been observed to be associated with pancreatic tumor progression. Modulation of microbiome has been shown to affect response to anti-PD1 therapy in this disease as well. However, most of the studies in pancreatic cancer and microbiome have remained focused om immune modulation. In the current study, we observed that in a T2D mouse model, the microbiome changed significantly as the hyperglycemia developed in these animals. Our results further showed that, tumors implanted in the T2D mice responded poorly to Gemcitabine/Paclitaxel (Gem/Pac) standard of care compared to those in the control group. A metabolomic reconstruction of the WGS of the gut microbiota further revealed that an enrichment of bacterial population involved in drug metabolism in the T2D group.
2020-11-30 | E-MTAB-8739 | biostudies-arrayexpress
Project description:The clinical importance of microbiomes to the chronicity of wounds is widely appreciated, yet little is understood about patient-specific processes shaping wound microbiome composition. Here, a two-cohort microbiome-genome wide association study is presented through which patient genomic loci associated with chronic wound microbiome diversity were identified. Further investigation revealed that alternative TLN2 and ZNF521 genotypes explained significant inter-patient variation in relative abundance of two key pathogens, Pseudomonas aeruginosa and Staphylococcus epidermidis. Wound diversity was lowest in Pseudomonas aeruginosa infected wounds, and decreasing wound diversity had a significant negative linear relationship with healing rate. In addition to microbiome characteristics, age, diabetic status, and genetic ancestry all significantly influenced healing. Using structural equation modeling to identify common variance among SNPs, six loci were sufficient to explain 53% of variation in wound microbiome diversity, which was a 10% increase over traditional multiple regression. Focusing on TLN2, genotype at rs8031916 explained expression differences of alternative transcripts that differ in inclusion of important focal adhesion binding domains. Such differences are hypothesized to relate to wound microbiomes and healing through effects on bacterial exploitation of focal adhesions and/or cellular migration. Related, other associated loci were functionally enriched, often with roles in cytoskeletal dynamics. This study, being the first to identify patient genetic determinants for wound microbiomes and healing, implicates genetic variation determining cellular adhesion phenotypes as important drivers of infection type. The identification of predictive biomarkers for chronic wound microbiomes may serve as risk factors and guide treatment by informing patient-specific tendencies of infection.
2020-04-25 | GSE149314 | GEO
Project description:Persistent mucosal inflammation and microbial infection are characteristic of Chronic Rhinosinusitis (CRS). Though mucosal microbiota dysbiosis is a characteristic feature of other chronic inflammatory diseases, the relationship between sinus microbiota composition and CRS is unknown. Here we demonstrate, using comparative microbiome profiling of a cohort of CRS patients and healthy subjects, that the sinus microbiota of CRS patients exhibit significantly reduced bacterial diversity. Characteristic of this community collapse is the depletion of multiple, phylogenetically distinct, Lactic Acid Bacteria and the concomitant increase in relative abundance of a single species, Corynebacterium tuberculostearicum. Recapitulating the conditions observed in our human cohort in a murine model confirmed the pathogenic potential of C. tuberculostearicum and the critical necessity for a replete mucosal microbiota to protect against this species. Moreover, we provide evidence that Lactobacillus sakei, identified from our comparative microbiome analyses as a potentially protective species, affords defense against C. tuberculostearicum sinus infection, even in the context of a depleted sinus bacterial community. These studies demonstrate that sinus mucosal health is highly dependent on the composition of the resident microbiota, and identifies a new sino-pathogen and a strong bacterial candidate for therapeutic intervention. A total of 14 samples were profiled for microbiome composition: 7 from non-sinusitis patients, and 7 from patients with clinically diagnosed chronic sinusitis.
2012-07-31 | E-GEOD-37850 | biostudies-arrayexpress
Project description:Genome scale metabolic model of Drosophila gut microbe Acetobacter fabarum
Abstract -
An important goal for many nutrition-based microbiome studies is to identify the metabolic function of microbes in complex microbial communities and their impact on host physiology. This research can be confounded by poorly understood effects of community composition and host diet on the metabolic traits of individual taxa. Here, we investigated these multiway interactions by constructing and analyzing metabolic models comprising every combination of five bacterial members of the Drosophila gut microbiome (from single taxa to the five-member community of Acetobacter and Lactobacillus species) under three nutrient regimes. We show that the metabolic function of Drosophila gut bacteria is dynamic, influenced by community composition, and responsive to dietary modulation. Furthermore, we show that ecological interactions such as competition and mutualism identified from the growth patterns of gut bacteria are underlain by a diversity of metabolic interactions, and show that the bacteria tend to compete for amino acids and B vitamins more frequently than for carbon sources. Our results reveal that, in addition to fermentation products such as acetate, intermediates of the tricarboxylic acid (TCA) cycle, including 2-oxoglutarate and succinate, are produced at high flux and cross-fed between bacterial taxa, suggesting important roles for TCA cycle intermediates in modulating Drosophila gut microbe interactions and the potential to influence host traits. These metabolic models provide specific predictions of the patterns of ecological and metabolic interactions among gut bacteria under different nutrient regimes, with potentially important consequences for overall community metabolic function and nutritional interactions with the host.IMPORTANCE Drosophila is an important model for microbiome research partly because of the low complexity of its mostly culturable gut microbiota. Our current understanding of how Drosophila interacts with its gut microbes and how these interactions influence host traits derives almost entirely from empirical studies that focus on individual microbial taxa or classes of metabolites. These studies have failed to capture fully the complexity of metabolic interactions that occur between host and microbe. To overcome this limitation, we reconstructed and analyzed 31 metabolic models for every combination of the five principal bacterial taxa in the gut microbiome of Drosophila This revealed that metabolic interactions between Drosophila gut bacterial taxa are highly dynamic and influenced by cooccurring bacteria and nutrient availability. Our results generate testable hypotheses about among-microbe ecological interactions in the Drosophila gut and the diversity of metabolites available to influence host traits.
2021-07-01 | MODEL2002040002 | BioModels