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Genome-scale modeling for metabolic engineering

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Journal of Industrial Microbiology & Biotechnology

Abstract

We focus on the application of constraint-based methodologies and, more specifically, flux balance analysis in the field of metabolic engineering, and enumerate recent developments and successes of the field. We also review computational frameworks that have been developed with the express purpose of automatically selecting optimal gene deletions for achieving improved production of a chemical of interest. The application of flux balance analysis methods in rational metabolic engineering requires a metabolic network reconstruction and a corresponding in silico metabolic model for the microorganism in question. For this reason, we additionally present a brief overview of automated reconstruction techniques. Finally, we emphasize the importance of integrating metabolic networks with regulatory information—an area which we expect will become increasingly important for metabolic engineering—and present recent developments in the field of metabolic and regulatory integration.

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Acknowledgments

The authors gratefully acknowledge funding from the Luxembourg Centre for Systems Biomedicine (ES), and the DOE ARPA-E program (DE-AR0000426), an NIH Center for Systems Biology (2P50 GM076547) and the Camille Dreyfus Teacher-Scholar Program (NDP). We also thank Julie Bletz and Ben Heavner for critical readings of the manuscript, and James Eddy for assistance with the illustrations.

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Authors and Affiliations

  1. Institute for Systems Biology, 401 Terry Avenue, North Seattle, WA, 98109, USA

    Evangelos Simeonidis & Nathan D. Price

  2. Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 7, avenue des Hauts-Fourneaux, L-4362, Esch-Sur-Alzette, Luxembourg

    Evangelos Simeonidis

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  1. Evangelos Simeonidis
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  2. Nathan D. Price
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Correspondence to Nathan D. Price.

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Special Issue: Metabolic Engineering.

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Simeonidis, E., Price, N.D. Genome-scale modeling for metabolic engineering. J Ind Microbiol Biotechnol 42, 327–338 (2015). https://doi.org/10.1007/s10295-014-1576-3

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  • DOI: https://doi.org/10.1007/s10295-014-1576-3

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