title: Integrating multiple 'omics' analysis for microbial biology: application and methodologies.
abstract: 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.
authors.affiliation: Center for Ecogenomics, Biodesign Institute, Arizona State University, Tempe, AZ 85287-6501, USA.
authors.forename: Weiwen
authors.initials: W
authors.lastname: Zhang
authors.affiliation: Division of Biometrics II, Office of Biometrics/OTS/CDER/FDA, Silver Spring, MD 20993-0002, USA.
authors.forename: Feng
authors.initials: F
authors.lastname: Li
authors.affiliation: Division of Biometrics IV, Office of Biometrics/OTS/CDER/FDA, Silver Spring, MD 20993-0002, USA.
authors.forename: Lei
authors.initials: L
authors.lastname: Nie
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods; D016208:Databases, Factual; D023281:Genomics / Q000379:methods; D006801:Humans; D055432:Metabolomics; D008829:Microbiology; D040901:Proteomics / Q000379:methods; D012984:Software