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Engineering improved ethylene production: Leveraging systems biology and adaptive laboratory evolution

Sophie Vaud, Nicole Pearcy, Marko Hanževački, Alexander M.W. Van Hagen, Salah Abdelrazig, Laudina Safo, Muhammad Ehsaan, Magda S. Jonczyk, Thomas Millat, Sean Craig, Edward Spence, James Fothergill, Rajesh Reddy Bommareddy, Pierre-Yves Colin, Jamie Twycross, Paul A. Dalby, Nigel P. Minton, Christof M. Jäger, Dong‐Hyun Kim, Jianping Yu, Pin‐Ching Maness, Sean Lynch, Carrie A. Eckert, Alex Conradie, Samantha J. Bryan

2021Metabolic Engineering20 citationsDOIOpen Access PDF

Abstract

contributing to climate change. The need for a sustainable alternative is therefore imperative. Ethylene is natively produced by several different microorganisms, including Pseudomonas syringae pv. phaseolicola via a process catalyzed by the ethylene-forming enzyme (EFE), subsequent heterologous expression of EFE has led to ethylene production in non-native bacterial hosts including Escherichia coli and cyanobacteria. However, solubility of EFE and substrate availability remain rate-limiting steps in biological ethylene production. We employed a combination of genome-scale metabolic modelling, continuous fermentation, and protein evolution to enable the accelerated development of a high efficiency ethylene producing E. coli strain, yielding a 49-fold increase in production, the most significant improvement reported to date. Furthermore, we have clearly demonstrated that this increased yield resulted from metabolic adaptations that were uniquely linked to EFE (wild type versus mutant). Our findings provide a novel solution to deregulate metabolic bottlenecks in key pathways, which can be readily applied to address other engineering challenges.

Topics & Concepts

Metabolic engineeringEthyleneHeterologousEscherichia coliBiologyFermentationSynthetic biologyBiochemical engineeringBiotechnologyBiochemistryComputational biologyEnzymeCatalysisEngineeringGeneMicrobial Metabolic Engineering and BioproductionBiofuel production and bioconversionGene Regulatory Network Analysis