Gut metagenome
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA399686 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR5961500_1.fastq.gz | Fastqsanger.gz | |||
| SRR5961500_2.fastq.gz | Fastqsanger.gz | |||
| SRR5961501_1.fastq.gz | Fastqsanger.gz | |||
| SRR5961501_2.fastq.gz | Fastqsanger.gz | |||
| SRR5961494_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 16 |
Similar Datasets
Project description:In vitro gut microbiota models are often used to study drug-microbiome interaction. Similar to culturing individual microbial strains, the biomass accumulation of in vitro gut microbiota follows a logistic growth curve. Current studies on in vitro gut microbiome responses introduce drug stimulation during different growth stages, e.g. lag phase or stationary phase. However, in vitro gut microbiota in different growth phases may respond differently to a same stimuli. Therefore, in this study, we used a 96-deep well plate-based culturing model (MiPro) to culture the human gut microbiota. Metformin, as the stimulus, was added at the lag, log and stationary phases of growth. Microbiome samples were collected at different time points for optical density and metaproteomic functional analysis. Results show that in vitro gut microbiota responded differently to metformin added during different growth phases, in terms of the growth curve, alterations of taxonomic and functional compositions. The addition of drugs at log phase leads to the greatest decline of bacterial growth. Metaproteomic analysis suggested that the strength of the metformin effect on the gut microbiome functional profile was ranked as lag phase > log phase > stationary phase. Our results showed that metformin added at lag phase resulted in a significantly reduced abundance of the Clostridiales order as well as an increased abundance of the Bacteroides genus, which was different from stimulation during the rest of the growth phase. Metformin also resulted in alterations of several pathways, including energy production and conversion, lipid transport and metabolism, translation, ribosomal structure and biogenesis. Our results indicate that the timing for drug stimulation should be considered when studying drug-microbiome interactions in vitro.
2022-03-01 | PXD017390 | Pride
Project description:artificially reared Bar-headed goose gut metagenome Raw sequence reads
| PRJNA316560 | ENA
Project description:Gut microbiome research is rapidly moving towards the functional characterization of the microbiota by means of shotgun meta-omics. Here, we selected a cohort of healthy subjects from an indigenous and monitored Sardinian population to analyze their gut microbiota using both shotgun metagenomics and shotgun metaproteomics. We found a considerable divergence between genetic potential and functional activity of the human healthy gut microbiota, in spite of a quite comparable taxonomic structure revealed by the two approaches. Investigation of inter-individual variability of taxonomic features revealed Bacteroides and Akkermansia as remarkably conserved and variable in abundance within the population, respectively. Firmicutes-driven butyrogenesis (mainly due to Faecalibacterium spp.) was shown to be the functional activity with the higher expression rate and the lower inter-individual variability in the study cohort, highlighting the key importance of the biosynthesis of this microbial by-product for the gut homeostasis. The taxon-specific contribution to functional activities and metabolic tasks was also examined, giving insights into the peculiar role of several gut microbiota members in carbohydrate metabolism (including polysaccharide degradation, glycan transport, glycolysis and short-chain fatty acid production). In conclusion, our results provide useful indications regarding the main functions actively exerted by the gut microbiota members of a healthy human cohort, and support metaproteomics as a valuable approach to investigate the functional role of the gut microbiota in health and disease.
2017-07-19 | PXD005780 | Pride
Project description:chicken gut microbiome Raw sequence reads
| PRJNA375981 | ENA
Project description:human gut microbiome 16S raw sequence reads
| PRJNA294369 | ENA
Project description:Spodoptera littoralis gut microbiome Raw sequence reads
| PRJNA384148 | ENA