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

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 fun...

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Bibliographic Details
Published in:Environmental Microbiology
Main Authors: Neufeld, Josh D., Yu, Zhongtang, Lam, Wan, Mohn, William W.
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2003
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Online Access:http://dx.doi.org/10.1046/j.1462-2920.2003.00547.x
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Summary: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 ( r 2 = 0.80) and division‐level distribution of RSTs ( r 2 = 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.