Unit

UNIT 13.26 Metaproteomics: Extracting and Mining Proteome Information to Characterize Metabolic Activities in Microbial Communities

  1. Paul E. Abraham1,
  2. Richard J. Giannone1,
  3. Weili Xiong1,2,
  4. Robert L. Hettich1

Published Online: 17 JUN 2014

DOI: 10.1002/0471250953.bi1326s46

Current Protocols in Bioinformatics

Current Protocols in Bioinformatics

How to Cite

Abraham, P. E., Giannone, R. J., Xiong, W. and Hettich, R. L. 2014. Metaproteomics: Extracting and Mining Proteome Information to Characterize Metabolic Activities in Microbial Communities. Current Protocols in Bioinformatics. 46:13.26:13.26.1–13.26.14.

Author Information

  1. 1

    Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee

  2. 2

    Graduate School of Genome Science and Technology, University of Tennessee, Knoxville, Tennessee

Publication History

  1. Published Online: 17 JUN 2014

Abstract

Contemporary microbial ecology studies usually employ one or more “omics” approaches to investigate the structure and function of microbial communities. Among these, metaproteomics aims to characterize the metabolic activities of the microbial membership, providing a direct link between the genetic potential and functional metabolism. The successful deployment of metaproteomics research depends on the integration of high-quality experimental and bioinformatic techniques for uncovering the metabolic activities of a microbial community in a way that is complementary to other “meta-omic” approaches. The essential, quality-defining informatics steps in metaproteomics investigations are: (1) construction of the metagenome, (2) functional annotation of predicted protein-coding genes, (3) protein database searching, (4) protein inference, and (5) extraction of metabolic information. In this article, we provide an overview of current bioinformatic approaches and software implementations in metaproteome studies in order to highlight the key considerations needed for successful implementation of this powerful community-biology tool. Curr. Protoc. Bioinform. 46:13.26.1-13.26.14. © 2014 by John Wiley & Sons, Inc.

Keywords:

  • metaproteomics;
  • proteomics;
  • mass spectrometry;
  • shotgun proteomics;
  • protein database search;
  • protein inference;
  • metagenomics