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.Detection and mitigation of strain instability in industrial microbiology scale-up.