Serial analysis of ribosomal sequence tags (SARST): a high-throughput method for profiling complex microbial communities

Authors

  • Josh D. Neufeld,

    1. Department of Microbiology and Immunology, University of British Columbia, 6174 University Boulevard, Vancouver, British Columbia, V6T 1Z3, Canada.
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  • Zhongtang Yu,

    1. Department of Animal Sciences (Microbiology), The Ohio State University, 2027 Coffey Road, Columbus, Ohio, 43210, USA.
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  • Wan Lam,

    1. British Columbia Cancer Research Center, 601 West 10th Avenue, Vancouver, British Columbia, V5Z 1L3, Canada.
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  • William W. Mohn

    Corresponding author
    1. Department of Microbiology and Immunology, University of British Columbia, 6174 University Boulevard, Vancouver, British Columbia, V6T 1Z3, Canada.
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E-mail wmohn@interchange.ubc.ca; Tel. (+1) 604 822 4285; Fax (+1) 604 822 6041.

Summary

Two decades of culture-independent studies have confirmed that microbial communities represent the most complex and concentrated pool of phylogenetic diversity on the planet. There remains a need for innovative molecular tools that can further our knowledge of microbial diversity and its functional implications. We present the method and application of serial analysis of ribosomal sequence tags (SARST) as a novel tool for elucidating complex microbial communities, such as those found in soils and sediments. Serial analysis of ribosomal sequence tags uses a series of enzymatic reactions to amplify and ligate ribosomal sequence tags (RSTs) from bacterial small subunit rRNA gene (SSU rDNA) V1-regions into concatemers that are cloned and sequenced. This approach offers a significant increase in throughput over traditional SSU rDNA clone libraries, as up to 20 RSTs are obtained from each sequencing reaction. To test SARST and measure the bias associated with this approach, RST libraries were prepared from a defined mixture of pure cultures and from duplicate arctic soil DNA samples. The actual RST distribution reflected the theoretical composition of the original defined mixture. Data from duplicate soil libraries (1345 and 1217 RSTs, with 525 and 505 unique RSTs, respectively) indicated that replication provides a strongly correlated RST profile (r2 = 0.80) and division-level distribution of RSTs (r2 = 0.99). Using sequence data from abundant soil RSTs, we designed specific primers that successfully amplified a larger portion of the SSU rDNA for further phylogenetic analysis. These results suggest that SARST is a powerful approach for reproducible high-throughput profiling of microbial diversity amenable to medical, industrial or environmental microbiology applications.

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