Mouse gut metagenome
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA215889 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR957634.fastq.gz | Fastqsanger.gz | |||
| SRR957635.fastq.gz | Fastqsanger.gz | |||
| SRR957636.fastq.gz | Fastqsanger.gz | |||
| SRR957637.fastq.gz | Fastqsanger.gz | |||
| SRR957638.fastq.gz | Fastqsanger.gz |
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Project description:The interrelationships between our diets and the structure and operations of our gut microbial communities are poorly understood. A model microbial community of ten sequenced human gut bacteria was introduced into gnotobiotic mice and changes in the abundance of each species were measured in response to randomized perturbations of four defined ingredients in the host diet. From the responses, we developed a statistical model that predicted over 50% of the variation in species abundance in response to the diet perturbations and were able to identify which factors in the diet best explained the changes seen for each community member. The community’s transcriptional response was driven by the absolute abundance of each species, as diet ingredient concentrations were not associated with significant changes in the transcription of individual community members.
2011-05-20 | GSE26687 | GEO
Project description:Background: More than 100 million Americans are living with metabolic syndrome, increasing their propensity to develop heart disease– the leading cause of death worldwide. A major contributing factor to this epidemic is caloric excess, often a result of consuming low cost, high calorie fast food. Several recent seminal studies have demonstrated the pivotal role of gut microbes contributing to cardiovascular disease in a diet-dependent manner. Given the central contributions of diet and gut microbiota to cardiometabolic disease, we hypothesized that novel microbial metabolites originating postprandially after fast food consumption may contribute to cardiometabolic disease progression. Methods: To test this hypothesis, we gave conventionally raised or antibiotic-treated mice a single oral gavage of a fast food slurry or a control rodent chow diet slurry and sacrificed the mice four hours later. Here, we coupled untargeted metabolomics in portal and peripheral blood, 16S rRNA gene sequencing, targeted liver metabolomics, and host liver RNA sequencing to identify novel fast food-derived microbial metabolites. Results: We successfully identified several metabolites that were enriched in portal blood, increased by fast food feeding, and essentially absent in antibiotic-treated mice. Strikingly, just four hours post-gavage, we found that fast food consumption resulted in rapid reorganization of the gut microbial community structure and drastically altered hepatic gene expression. Importantly, diet-driven reshaping of the microbiome and liver transcriptome was dependent on a non-antibiotic ablated gut microbial community. Conclusions: Collectively, these data suggest that single fast food meal is sufficient to reshape the gut microbial community yielding a unique signature of food-derived microbial metabolites. Future studies are warranted to determine if these metabolites are causally linked to cardiometabolic disease.
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Project description:The human gut microbiota is a metabolic organ whose cellular composition is determined by a dynamic process of selection and competition. To identify microbial genes required for establishment of human symbionts in the gut, we developed an approach (insertion-sequencing, or INSeq) based on a mutagenic transposon that allows capture of adjacent chromosomal DNA to define its genomic location. We used massively parallel sequencing to monitor the relative abundance of tens of thousands of transposon mutants of a saccharolytic human gut bacterium, Bacteroides thetaiotaomicron, as they established themselves in wild-type and immunodeficient gnotobiotic mice, in the presence or absence of other human gut commensals. In vivo selection transforms this population, revealing functions necessary for survival in the gut: we show how this selection is influenced by community composition and competition for nutrients (vitamin B12). INSeq provides a broadly applicable platform to explore microbial adaptation to the gut and other ecosystems. Keywords: Other 57 samples analyzed, 1 of these is the reference (input) sample
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