Analysis of Microbial Communities by Functional Gene Arrays

Chapter

Abstract

A major hurdle to the study of microbial communities is that only about 1% of microorganisms are cultivated (Whitman et al. 1998). As such, culture-­independent approaches are necessary in order to examine the vast majority of environmental microorganisms. Many molecular techniques are available for community analysis, and most of these techniques utilize phylogenetic markers such as the 16S rRNA or the DNA gyrase gene (gyrB) (Wilson et al. 1990; Yamamoto and Harayama 1995; Hugenholtz et al. 1998; Brodie et al. 2006). While the use of these genes provides information regarding phylogenic diversity and structure of a microbial community, they don’t provide much, if any information relating to the functional potential and/or activity of the community. Functional genes have been used to examine both phylogenetic and functional diversities (e.g., McDonald et al. 1995; Braker et al. 1998). However, even if multiple functional genes are examined, conventional molecular techniques only provide information on a small fraction of the community. This is because conserved PCR primers cannot be designed for many functional genes of interest due to a lack of sequence homology or a lack of a sufficient number of sequences. Consequently, conventional PCR-based approaches cannot be used to detect and quantify many functional genes of interest. As such, a more comprehensive technique is required to provide a full picture of microbial community activity and dynamics in a rapid, parallel, and high-through-put manner.

Keywords

Microbial Community Functional Gene Canonical Correspondence Analysis Stable Isotope Probe Variation Partitioning Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The effort for preparing this review was supported by the Virtual Institute for Microbial Stress and Survival (http://VIMSS.lbl.gov) supported by the U. S. Department of Energy, Office of Science, Office of Biological and Environmental Research, Genomics Program:GTL through contract DE-AC02-05CH11231 between Lawrence Berkeley National Laboratory and the U. S. Department of Energy, Environmental Remediation Science Program (ERSP), Office of Biological and Environmental Research, Office of Science, and Oklahoma Applied Research Support (OARS), Oklahoma Center for the Advancement of Science and Technology (OCAST), the State of Oklahoma through the Project AR062-034.

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© Springer Netherlands 2010

Authors and Affiliations

  1. 1.Department of Botany and Microbiology, Institute for Environmental GenomicsUniversity of OklahomaNormanUSA

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