Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1189023 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR31432500_1.fastq.gz | Fastqsanger.gz | |||
| SRR31432600_1.fastq.gz | Fastqsanger.gz | |||
| SRR31432700_1.fastq.gz | Fastqsanger.gz | |||
| SRR31432501_1.fastq.gz | Fastqsanger.gz | |||
| SRR31432601_1.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.
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Project description:Here we map the molecular response of a synthetic community of 32 human gut bacteria to three non-antibiotic drugs by using five omics layers, namely 16S rRNA gene profiling, metagenomics, metatranscriptomics, metaproteomics, and metabolomics. Using this controlled setting, we find that all omics methods with species resolution in their readouts are highly consistent in estimating relative species abundances across conditions. Furthermore, different omics methods can be complementary in their ability to capture functional changes in response to the drug perturbations. For example, while nearly all omics data types captured that the antipsychotic drug chlorpromazine selectively inhibits Bacteroidota representatives in the community, the metatranscriptome and metaproteome suggested that the drug induces stress responses related to protein quality control and metabolomics revealed a decrease in polysaccharide uptake, likely caused by Bacteroidota depletion. Taken together, our study provides insights into how multi-omics datasets can be utilised to reveal complex molecular responses to external perturbations in microbial communities.
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Project description:The human gut microbiota is an important metabolic organ, yet little is known about how its individual species interact, establish dominant positions, and respond to changes in environmental factors such as diet. In this study, gnotobiotic mice were colonized with an artificial microbiota comprising 12 sequenced human gut bacterial species and fed oscillating diets of disparate composition. Rapid, reproducible, and reversible changes in the structure of this assemblage were observed. Time-series microbial RNA-Seq analyses revealed staggered functional responses to diet shifts throughout the assemblage that were heavily focused on carbohydrate and amino acid metabolism. High-resolution shotgun metaproteomics confirmed many of these responses at a protein level. One member, Bacteroides cellulosilyticus WH2, proved exceptionally fit regardless of diet. Its genome encoded more carbohydrate active enzymes than any previously sequenced member of the Bacteroidetes. Transcriptional profiling indicated that B. cellulosilyticus WH2 is an adaptive forager that tailors its versatile carbohydrate utilization strategy to available dietary polysaccharides, with a strong emphasis on plant-derived xylans abundant in dietary staples like cereal grains. Two highly expressed, diet-specific polysaccharide utilization loci (PULs) in B. cellulosilyticus WH2 were identified, one with characteristics of xylan utilization systems. Introduction of a B. cellulosilyticus WH2 library comprising >90,000 isogenic transposon mutants into gnotobiotic mice, along with the other artificial community members, confirmed that these loci represent critical diet-specific fitness determinants. Carbohydrates that trigger dramatic increases in expression of these two loci and many of the organism’s 111 other predicted PULs were identified by RNA-Seq during in vitro growth on 31 distinct carbohydrate substrates, allowing us to better interpret in vivo RNA-Seq and proteomics data. These results offer insight into how gut microbes adapt to dietary perturbations at both a community level and from the perspective of a well-adapted symbiont with exceptional saccharolytic capabilities, and illustrate the value of artificial communities. 116 samples total. In 26 of these samples, we evaluated community-wide gene expression using RNA isolated from the feces of a gnotobiotic mouse harboring an artificial community comprised of 12 human gut microbes. For these samples, we sought to determine the extent to which community gene expression is altered as a result of dietary oscillation. In the other 90 samples, we evaluated gene expression in a single species (B. cellulosilyticus WH2) grown in a defined medium supplemented with a single mono-, oligo-, or polysaccharide. For these samples, we sought to identify genes (particularly polysaccharide utilization loci) whose expression was significantly increased as a result of exposure to particular carbohydrates.
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