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Microbiology 156 (2010), 287-301; DOI  10.1099/mic.0.034793-0IMMEDIATE OPEN ACCESS ARTICLE
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Microbiology 156 (2010), 287-301; DOI  10.1099/mic.0.034793-0
© 2010 Society for General Microbiology

Integrating multiple ‘omics’ analysis for microbial biology: application and methodologies

Weiwen Zhang1, Feng Li2 and Lei Nie3

1 Center for Ecogenomics, Biodesign Institute, Arizona State University, Tempe, AZ 85287-6501, USA
2 Division of Biometrics II, Office of Biometrics/OTS/CDER/FDA, Silver Spring, MD 20993-0002, USA
3 Division of Biometrics IV, Office of Biometrics/OTS/CDER/FDA, Silver Spring, MD 20993-0002, USA

Recent advances in various ‘omics’ technologies enable quantitative monitoring of the abundance of various biological molecules in a high-throughput manner, and thus allow determination of their variation between different biological states on a genomic scale. Several popular ‘omics’ platforms that have been used in microbial systems biology include transcriptomics, which measures mRNA transcript levels; proteomics, which quantifies protein abundance; metabolomics, which determines abundance of small cellular metabolites; interactomics, which resolves the whole set of molecular interactions in cells; and fluxomics, which establishes dynamic changes of molecules within a cell over time. However, no single ‘omics’ analysis can fully unravel the complexities of fundamental microbial biology. Therefore, integration of multiple layers of information, the multi-‘omics’ approach, is required to acquire a precise picture of living micro-organisms. In spite of this being a challenging task, some attempts have been made recently to integrate heterogeneous ‘omics’ datasets in various microbial systems and the results have demonstrated that the multi-‘omics’ approach is a powerful tool for understanding the functional principles and dynamics of total cellular systems. This article reviews some basic concepts of various experimental ‘omics’ approaches, recent application of the integrated ‘omics’ for exploring metabolic and regulatory mechanisms in microbes, and advances in computational and statistical methodologies associated with integrated ‘omics’ analyses. Online databases and bioinformatic infrastructure available for integrated ‘omics’ analyses are also briefly discussed.

Correspondence
Weiwen Zhang
Weiwen.Zhang{at}asu.edu






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