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Overcoming genetic heterogeneity in industrial fermentations

Abstract

Engineering the synthesis of massive amounts of therapeutics, enzymes or commodity chemicals can select for subpopulations of nonproducer cells, owing to metabolic burden and product toxicity. Deep DNA sequencing can be used to detect undesirable genetic heterogeneity in producer populations and diagnose associated genetic error modes. Hotspots of genetic heterogeneity can pinpoint mechanisms that underlie load problems and product toxicity. Understanding genetic heterogeneity will inform metabolic engineering and synthetic biology strategies to minimize the emergence of nonproducer mutants in scaled-up fermentations and maximize product quality and yield.

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Acknowledgements

We thank A. Porse, F. Lino and C. Hjort for helpful comments. The research leading to these results has received funding from the Novo Nordisk Foundation, Denmark, grant number NNF10CC1016517, and from the European Union Seventh Framework Programme (FP7-KBBE-2013-7-single-stage) under grant agreement 613745, Promys.

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P.R. and M.O.A.S. outlined and wrote the manuscript.

Correspondence to Morten O. A. Sommer.

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Competing interests

P.R. and M.O.A.S. are inventors of a pending patent application (WO2017055360) within product addiction filed by the Technical University of Denmark.

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Peer review information: Andy Marshall was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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Fig. 1: Evolution of populations during industrial fermentation.
Fig. 2: Causal factors and counterstrategies for genetic heterogeneity in large-scale biomanufacturing.
Fig. 3: Synthetic control solutions.