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Yeast Metabolic Engineering pp 281–294Cite as

Model-Guided Identification of Gene Deletion Targets for Metabolic Engineering in Saccharomyces cerevisiae

Part of the Methods in Molecular Biology book series (MIMB,volume 1152)

Abstract

Identification of metabolic engineering strategies for rerouting intracellular fluxes towards a desired product is often a challenging task owing to the topological and regulatory complexity of metabolic networks. Genome-scale metabolic models help tackling this complexity through systematic consideration of mass balance and reaction directionality constraints over the entire network. Here, we describe how genome-scale metabolic models can be used for identifying gene deletion targets leading to increased production of the desired product. Vanillin production in Saccharomyces cerevisiae is used as a case study throughout this chapter.

Key words

  • Metabolic engineering
  • Genome-scale metabolic reconstructions
  • Flux balance analysis
  • OptGene
  • Minimization of metabolic adjustment
  • Minimization of metabolite balance

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Author information

Authors and Affiliations

  1. Genome Biology Unit, European Molecular Biology Laboratory, Meyerhofstraße 1, Heidelberg, 69117, Germany

    Ana Rita Brochado

  2. Stuctural and Computational Biology, European Molecular Biology Laboratory, Meyerhofstraße 1, Heidelberg, 69117, Germany

    Kiran Raosaheb Patil

Authors
  1. Ana Rita Brochado
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  2. Kiran Raosaheb Patil
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Corresponding author

Correspondence to Kiran Raosaheb Patil .

Editor information

Editors and Affiliations

  1. Industrial Biotechnology, Chalmers University of Technology, Gothenburg, Sweden

    Valeria Mapelli

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Brochado, A.R., Patil, K.R. (2014). Model-Guided Identification of Gene Deletion Targets for Metabolic Engineering in Saccharomyces cerevisiae . In: Mapelli, V. (eds) Yeast Metabolic Engineering. Methods in Molecular Biology, vol 1152. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-0563-8_17

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  • DOI: https://doi.org/10.1007/978-1-4939-0563-8_17

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-0562-1

  • Online ISBN: 978-1-4939-0563-8

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