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An Adaptive Laboratory Evolution Method to Accelerate Autotrophic Metabolism

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Synthetic Metabolic Pathways

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1671))

Abstract

Adaptive laboratory evolution (ALE) is an approach enabling the development of novel characteristics in microbial strains via the application of a constant selection pressure. This method is also an efficient tool to acquire insights on molecular mechanisms responsible for specific phenotypes. ALE experiments have mainly been conducted with heterotrophic microbes to study, for instance, cell metabolism with different multicarbon substrates, tolerance to solvents, pH variation, and high temperature. Here, we describe employing an ALE method to generate Sporomusa ovata strains growing faster autotrophically and reducing CO2 into acetate more efficiently. Strains developed via this ALE method were also used to gain knowledge on the autotrophic metabolism of S. ovata as well as other acetogenic bacteria.

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Author information

Authors and Affiliations

  1. School of Chemistry, Chemical Engineering and Life Science, Wuhan University of Technology, Wuhan, 430070, People’s Republic of China

    Tian Zhang & Pier-Luc Tremblay

  2. The Novo Nordisk Foundation Center for Biosustainablity, Technical University of Denmark, Hørsholm, Denmark

    Tian Zhang & Pier-Luc Tremblay

Authors
  1. Tian Zhang
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  2. Pier-Luc Tremblay
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Corresponding author

Correspondence to Tian Zhang .

Editor information

Editors and Affiliations

  1. The Novo Nordisk Foundation, Center for Biosustainability, Technical University of Denmark, Kongens Lyngby, Denmark

    Michael Krogh Jensen

  2. Joint BioEnergy Institute, Emeryville, California, USA

    Jay D. Keasling

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Zhang, T., Tremblay, PL. (2018). An Adaptive Laboratory Evolution Method to Accelerate Autotrophic Metabolism. In: Jensen, M.K., Keasling, J.D. (eds) Synthetic Metabolic Pathways. Methods in Molecular Biology, vol 1671. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7295-1_10

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  • DOI: https://doi.org/10.1007/978-1-4939-7295-1_10

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7294-4

  • Online ISBN: 978-1-4939-7295-1

  • eBook Packages: Springer Protocols

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