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Review

Metaproteomic data analysis at a glance: advances in computational microbial community proteomics

, &
Pages 757-769 | Received 23 May 2016, Accepted 30 Jun 2016, Published online: 20 Jul 2016
 

ABSTRACT

Introduction: Within the last decade, the study of microbial communities has gained increasing research interest also driven by the recognition of the important role of these consortia in human health and disease. Metaproteomics, the analysis of the entire set of proteins from all microorganisms present in one ecosystem, has become a prominent technique for studying the relation between taxonomic diversity and functional profile of microbial communities.

Areas covered: The aim of this review is to address opportunities and challenges of metaproteomics from a computational perspective. Appealing to an audience of microbial ecologists and proteomic researchers alike, we provide an overview on state-of-the-art software and databases by which metaproteome data can be readily analyzed.

Expert commentary: While tailored protein databases, combined search algorithms and iterative workflows are means to improve the identification yield, software tools for taxonomic and functional analysis are challenged by the vast amount of unannotated sequences in metaproteomics.

Acknowledgments

The authors would like to thank Tobias Loka and Mathias Kuhring for critical reading of the manuscript.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Additional information

Funding

L Martens would like to acknowledge a IWT SBO grant. B Renard acknowledges financial support by Deutsche Forschungsgemeinschaft (DFG), grant number RE3474/2-1; IWT SBO grant ‘INSPECTOR’ [120025].

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