James W. Brown

Associate Professor & Undergraduate Coordinator
Department of Microbiology, NC State University

North Carolina American Society for Microbiology Branch Meeting, Oct 7, 2005, Raleigh, NC

IN SILICO: A software suite for the rapid identification of microbial communities.

J. Christopher Ellis* and James W. Brown

Department of Microbiology, North Carolina State University, Raleigh, NC 27695-7615

Microbiologists traditionally surveyed microbial communities using cultivation methods, but the organisms accessible by this approach represent a trivial fraction of the original community. A variety of molecular phylogenetic approaches based on ribosomal RNA sequences have been used in attempt to obtain a more realistic view of microbial communities, but the most promising emerging method is terminal restriction fragment length polymorphism (t-RFLP) analysis. By performing T-RFLP in conjunction with clone library construction researchers have demonstrated the technique’s utility and validity.

T-RFLP involves PCR amplification of rDNA from DNA extracted from microbial communities using a fluorescently-labeled primer, followed by digestion with multiple restriction endonucleases and high-resolution gel electrophoresis. By comparing the fluorescently labeled band pattern sizes from the high-resolution gel to a small ribosomal fragment database generated in silico it is possible to infer the entire microbial community.

Although already useful to some extent, the general usefulness of t-RFLP has been limited most by the small fragment databases generated in silico currently available. Additionally, primers and restriction enzymes are chosen based on empirical observation, rather than experimental optimization. The lack of tools for rational design of these critical aspects in conjunction with small available fragment databases has limited the techniques broader application.

IN SILICO is a suite of software tools designed to overcome these limitations with t-RFLP experiments.  Included are tools for the evaluation of primer sequences and a large fragment database used to infer microbial communities. These tools and database allow researchers to infer microbial communities quickly and cost effectively.

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