Proceedings of the National Academy of Sciences · 2014 · 285 citations · 30 references
EngineeringBiotechnologyEvolutionary BiologyDirected EvolutionGenetic EngineeringMetabolic EngineeringEvolution Of Metabolic PathwaysFlux Balance AnalysisMetabolic Pathway EngineeringMutagenesis StrategiesPathway EngineeringSynthetic Pathway ConstructionArtificial SelectionBiosynthetic Pathway ConstructionBiosynthetic Pathway OptimizationGenome-wide MutagenesisGlucaric Acid ProductionMetabolic Flux Balance AnalysisMetabolic Pathway OptimizationNegative Selection
Engineering biosynthetic pathways for chemical production demands extensive optimization of host metabolism, often requiring many pathway variants to be constructed and evaluated. The authors present a general strategy that combines targeted genome‑wide mutagenesis with evolution to enrich for rare high‑producer variants. They convert intracellular target chemical levels into a fitness advantage using a chemical‑responsive sensor that drives a survival reporter, and employ a negative selection scheme to remove cheaters while preserving library diversity, enabling multiple rounds of evolution on ~10⁹ cells per round and targeted mutagenesis of pathway genes identified by flux balance analysis. After up to four evolution rounds, production of naringenin and glucaric acid increased 36‑fold and 22‑fold, respectively, with naringenin reaching 61 mg L⁻¹—more than double the previous highest titer—and whole‑genome sequencing revealed untargeted mutations that likely further enhance production.
Engineering biosynthetic pathways for chemical production requires extensive optimization of the host cellular metabolic machinery. Because it is challenging to specify a priori an optimal design, metabolic engineers often need to construct and evaluate a large number of variants of the pathway. We report a general strategy that combines targeted genome-wide mutagenesis to generate pathway variants with evolution to enrich for rare high producers. We convert the intracellular presence of the target chemical into a fitness advantage for the cell by using a sensor domain responsive to the chemical to control a reporter gene necessary for survival under selective conditions. Because artificial selection tends to amplify unproductive cheaters, we devised a negative selection scheme to eliminate cheaters while preserving library diversity. This scheme allows us to perform multiple rounds of evolution (addressing ∼10(9) cells per round) with minimal carryover of cheaters after each round. Based on candidate genes identified by flux balance analysis, we used targeted genome-wide mutagenesis to vary the expression of pathway genes involved in the production of naringenin and glucaric acid. Through up to four rounds of evolution, we increased production of naringenin and glucaric acid by 36- and 22-fold, respectively. Naringenin production (61 mg/L) from glucose was more than double the previous highest titer reported. Whole-genome sequencing of evolved strains revealed additional untargeted mutations that likely benefit production, suggesting new routes for optimization.
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