Human gut metagenome
Ontology highlight
ABSTRACT:
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| DRR095587.fastq.gz | Fastqsanger.gz | |||
| DRR095588.fastq.gz | Fastqsanger.gz | |||
| DRR095589.fastq.gz | Fastqsanger.gz | |||
| DRR095590.fastq.gz | Fastqsanger.gz | |||
| DRR095591.fastq.gz | Fastqsanger.gz |
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Project description:This project contains raw data, intermediate files and results is a re-analysis of the publicly available dataset from the PRIDE dataset PXD005780. The RAW files were processed using ThermoRawFileParser, SearchGUI and PeptideShaker through standard settings (see ‘Data Processing Protocol’). This reanalysis work is part of the MetaPUF (MetaProteomics with Unknown Function) project, which is a collaboration between EMBL-EBI and the University of Luxembourg. The dataset was selected with the following conditions: 1. It has been made publicly available in PRIDE and focuses on metaproteomics of the human gut; 2. The corresponding metagenomics assemblies were also available from ENA (European Nucleotide Archive) or MGnify. The processed peptide reports for each sample are available to view at the contig level on the MGnify website. In total, the reanalysis identified 15,417 unique proteins from 15 samples.
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Project description:Host-microbiome-dietary interactions play crucial roles in regulating human health, yet direct functional assessment of their interplays, cross-regulations and downstream disease impacts remains challenging. We adopted metagenome-informed metaproteomics (MIM), in both mice and humans, to simultaneously explore host, dietary, and species-level microbiome interactions across diverse scenarios, including commensal and pathogen colonization, nutritional modifications, and antibiotic-induced perturbations. Implementation of MIM in murine auto-inflammation and in human IBD characterized a ‘compositional dysbiosis’ and a concomitant, species-specific ‘functional dysbiosis’ driven by suppressed commensal responses to inflammatory host signals. Microbiome transfers unraveled early-onset kinetics of these host-commensal cross-responsive patterns, while predictive analyses identified candidate fecal host-microbiome IBD biomarker protein pairs outperforming S100A8/S100A9 (calprotectin). Importantly, a simultaneous fecal nutrient assessment enabled determination of IBD-related consumption patterns, dietary treatment compliance and small-intestinal digestive aberrations. Collectively, a parallelized dietary-bacterial-host MIM assessment functionally uncovers trans-kingdom interactomes shaping gastrointestinal ecology, while offering personalized diagnostic and therapeutic insights into microbiome-associated disease.
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