Overcoming genetic heterogeneity in industrial fermentations

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 dia...

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Veröffentlicht in:Nature biotechnology 2019-08, Vol.37 (8), p.869-876
Hauptverfasser: Rugbjerg, Peter, Sommer, Morten O. A.
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description 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. Detection and mitigation of strain instability in industrial microbiology scale-up.
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subjects 631/181/457
631/326/252
631/61/318
631/61/514/2254
Agriculture
Bioinformatics
Biomedical and Life Sciences
Biomedical Engineering/Biotechnology
Biomedicine
Biotechnology
Deoxyribonucleic acid
DNA
DNA sequencing
Error detection
Heterogeneity
Life Sciences
Metabolic engineering
Metabolism
Nonproducer cells
Organic chemistry
Perspective
Population genetics
Subpopulations
Toxicity
title Overcoming genetic heterogeneity in industrial fermentations
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