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Computational Prediction of Essential Metabolic Genes Using Constraint-Based Approaches

  • Georg Basler
Part of the Methods in Molecular Biology book series (MIMB, volume 1279)

Abstract

In this chapter, we describe the application of constraint-based modeling to predict the impact of gene deletions on a metabolic phenotype. The metabolic reactions taking place inside cells form large networks, which have been reconstructed at a genome-scale for several organisms at increasing levels of detail. By integrating mathematical modeling techniques with biochemical principles, constraint-based approaches enable predictions of metabolite fluxes and growth under specific environmental conditions or for genetically modified microorganisms. Similar to the experimental knockout of a gene, predicting the essentiality of a metabolic gene for a phenotype further allows to generate hypotheses on its biological function and design of genetic engineering strategies for biotechnological applications. Here, we summarize the principles of constraint-based approaches and provide a detailed description of the procedure to predict the essentiality of metabolic genes with respect to a specific metabolic function. We exemplify the approach by predicting the essentiality of reactions in the citric acid cycle for the production of glucose from fatty acids.

Key words

Genome-scale metabolic networks Gene essentiality Metabolic network analysis Constraint-based approaches Flux balance analysis TCA cycle Glyoxylate cycle 

Notes

Acknowledgement

I thank Tino Krell and Juan Luis Ramos for critical reading of the manuscript. This research was supported by a Marie Curie Intra-European Fellowship within the 7th European Community Framework Programme.

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Department of Environmental Protection, Estación Experimental del ZaidínConsejo Superior de Investigaciones Científicas (CSIC)GranadaSpain

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