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Related Experiment Video

Updated: Jun 5, 2026

A Clinical Metaproteomics Workflow Implemented within Galaxy Bioinformatics Platform to Analyze Host-Microbiome Interactions Underlying Human Disease
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A Clinical Metaproteomics Workflow Implemented within Galaxy Bioinformatics Platform to Analyze Host-Microbiome Interactions Underlying Human Disease

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An iterative workflow for mining the human intestinal metaproteome.

Koos Rooijers1, Carolin Kolmeder, Catherine Juste

  • 1Laboratory of Systems and Synthetic Biology, Wageningen University, Dreijenplein10, 6703 HB Wageningen, The Netherlands.

BMC Genomics
|January 7, 2011
PubMed
Summary

This study introduces an iterative workflow for analyzing complex microbial communities, significantly increasing identified spectra in metaproteomics. The method enhances shotgun proteomics for human gut microbiome research.

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Area of Science:

  • Proteomics
  • Metagenomics
  • Microbial Ecology

Background:

  • Shotgun proteomics relies on complete proteome databases for data analysis.
  • Complex samples like the human gut microbiome lack comprehensive proteome data due to unsequenced species.
  • Existing methods face limitations in analyzing metaproteomics from such diverse ecosystems.

Purpose of the Study:

  • To develop an iterative workflow for shotgun proteomics data analysis in complex microbial communities.
  • To overcome limitations posed by incomplete proteome databases in metaproteomics.
  • To enable accurate interpretation of spectra from samples like the human intestinal tract.

Main Methods:

  • Developed an iterative workflow using a synthetic metaproteome and developing metagenomic databases.
  • Applied liquid chromatography-mass spectrometry to analyze human fecal samples.
  • Benchmarked the new workflow against existing methods for metaproteome analysis.

Main Results:

  • The iterative workflow identified over 3,000 peptides per fecal sample.
  • Successfully circumvented the need for a complete, sample-specific proteome.
  • Avoided naive translation of metagenomes and cross-species peptide identification.

Conclusions:

  • The developed workflow achieved a two-fold increase in identified spectra at a 1% false discovery rate.
  • This method is applicable to metaproteomic studies of the human intestinal tract.
  • The approach is suitable for analyzing other complex ecosystems with limited genomic data.