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Metaproteomics: A New Approach for Studying Functional Microbial Ecology

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Abstract

In the postgenomic era, there is a clear recognition of the limitations of nucleic acid-based methods for getting information on functions expressed by microbial communities in situ. In this context, the large-scale study of proteins expressed by indigenous microbial communities (metaproteome) should provide information to gain insights into the functioning of the microbial component in ecosystems. Characterization of the metaproteome is expected to provide data linking genetic and functional diversity of microbial communities. Studies on the metaproteome together with those on the metagenome and the metatranscriptome will contribute to progress in our knowledge of microbial communities and their contribution in ecosystem functioning. Effectiveness of the metaproteomic approach will be improved as increasing metagenomic information is made available thanks to the environmental sequencing projects currently running. More specifically, analysis of metaproteome in contrasted environmental situations should allow (1) tracking new functional genes and metabolic pathways and (2) identifying proteins preferentially associated with specific stresses. These proteins considered as functional bioindicators should contribute, in the future, to help policy makers in defining strategies for sustainable management of our environment.

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Acknowledgements

The authors are grateful to K. Klein for helpful comments and correcting the English text.

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  1. UMR Microbiologie et Géochimie des Sols, INRA/Université de Bourgogne, CMSE, BP 86510, 17 rue de Sully, 21065, Dijon Cedex, France

    Pierre-Alain Maron, Lionel Ranjard, Christophe Mougel & Philippe Lemanceau

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  1. Pierre-Alain Maron
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  2. Lionel Ranjard
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  3. Christophe Mougel
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Correspondence to Philippe Lemanceau.

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Maron, PA., Ranjard, L., Mougel, C. et al. Metaproteomics: A New Approach for Studying Functional Microbial Ecology. Microb Ecol 53, 486–493 (2007). https://doi.org/10.1007/s00248-006-9196-8

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