Strain-resolved community proteomics reveals recombining genomes of acidophilic bacteria

Ian Lo, Vincent J. Denef, Nathan C. VerBerkmoes, Manesh B. Shah, Daniela Goltsman, Genevieve DiBartolo, Gene W. Tyson, Eric E. Allen, Rachna J. Ram, J. Chris Detter, Paul Richardson, Michael P. Thelen, Robert L. Hettich, Jillian F. Banfield

    Research output: Contribution to journalArticlepeer-review

    186 Scopus citations

    Abstract

    Microbes comprise the majority of extant organisms, yet much remains to be learned about the nature and driving forces of microbial diversification. Our understanding of how microorganisms adapt and evolve can be advanced by genome-wide documentation of the patterns of genetic exchange, particularly if analyses target coexisting members of natural communities. Here we use community genomic data sets to identify, with strain specificity, expressed proteins from the dominant member of a genomically uncharacterized, natural, acidophilic biofilm. Proteomics results reveal a genome shaped by recombination involving chromosomal regions of tens to hundreds of kilobases long that are derived from two closely related bacterial populations. Inter-population genetic exchange was confirmed by multilocus sequence typing of isolates and of uncultivated natural consortia. The findings suggest that exchange of large blocks of gene variants is crucial for the adaptation to specific ecological niches within the very acidic, metal-rich environment. Mass-spectrometry-based discrimination of expressed protein products that differ by as little as a single amino acid enables us to distinguish the behaviour of closely related coexisting organisms. This is important, given that microorganisms grouped together as a single species may have quite distinct roles in natural systems and their interactions might be key to ecosystem optimization. Because proteomic data simultaneously convey information about genome type and activity, strain-resolved community proteomics is an important complement to cultivation-independent genomic (metagenomic) analysis of microorganisms in the natural environment.

    Original languageEnglish
    Pages (from-to)537-541
    Number of pages5
    JournalNature
    Volume446
    Issue number7135
    DOIs
    StatePublished - Mar 29 2007

    Funding

    Acknowledgements We thank T. W. Arman, President, Iron Mountain Mines and R. Sugarek, EPA, for site access, and R. Carver for on-site assistance. We thank D. B. Johnson, University of Wales, Bangor, for assistance with culturing; and F. Larimer and M. Land of the ORNL Genome Analysis and System Modeling Group for computational resources for proteomic analysis. DNA sequencing was carried out at the DOE Joint Genome Institute. Funding was provided by the DOE Genomics:GTL Program (Office of Science), the NSF Biocomplexity Program and the NASA Astrobiology Institute.

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