Metabolic modeling with Big Data and the gut microbiome.

Appl Transl Genom

Center for Individualized Medicine, Microbiome Program, Mayo Clinic, Rochester, MN 55905, USA; Department of Surgery, Mayo Clinic, Rochester, MN 55905, USA; Department of Biomedical Engineering, Mayo College, Rochester, MN 55905, USA.

Published: September 2016

The recent advances in high-throughput omics technologies have enabled researchers to explore the intricacies of the human microbiome. On the clinical front, the gut microbial community has been the focus of many biomarker-discovery studies. While the recent deluge of high-throughput data in microbiome research has been vastly informative and groundbreaking, we have yet to capture the full potential of omics-based approaches. Realizing the promise of multi-omics data will require integration of disparate omics data, as well as a biologically relevant, mechanistic framework - or metabolic model - on which to overlay these data. Also, a new paradigm for metabolic model evaluation is necessary. Herein, we outline the need for multi-omics data integration, as well as the accompanying challenges. Furthermore, we present a framework for characterizing the ecology of the gut microbiome based on metabolic network modeling.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5025471PMC
http://dx.doi.org/10.1016/j.atg.2016.02.001DOI Listing

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