Adaptive laboratory evolution for growth coupled microbial production
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(2020) 36:175
REVIEW
Adaptive laboratory evolution for growth coupled microbial production Avinash Godara1 · Katy C. Kao2 Received: 1 August 2020 / Accepted: 8 October 2020 © Springer Nature B.V. 2020
Abstract Adaptive laboratory evolution (ALE) is a powerful tool to select for strains with growth-coupled phenotypes. When coupled with next-generation sequencing and omic technologies, genotype-to-phenotype relationships and the molecular mechanisms underlying desired complex phenotypes can now be uncovered using ALE. However, in order for ALE to be effective in generating strains with increased productivity, the product-of-interest needs to be coupled with cellular growth or survival. Advances in computational metabolic modeling can now identify metabolic engineering strategies to force the coupling of desired product formation with growth for a wide range of different compounds. Such strategies can potentially be coupled with ALE to further enhance productivity of microbial hosts. In addition to metabolic strategies, if the compound of interest is known to impart beneficial traits to the host, such as stress tolerance, then an environment can be designed to allow product formation to be coupled with growth or survival. This mini-review will cover recent advances in both the metabolic and environmental engineering and synthetic biology strategies to couple production with microbial fitness, successful cases for the use of these strategies with ALE to improve product formation, discuss limitations, and future perspectives.
* Katy C. Kao [email protected] 1
Department of Chemical Engineering, Texas A&M University, College Station, Texas, USA
Department of Chemical and Material Engineering, San Jose State University, San Jose, California, USA
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World Journal of Microbiology and Biotechnology
(2020) 36:175
Graphic abstract
Keywords Growth-coupled production · Metabolic engineering · Computational strategy · ALE · Biotechnology; mini review
Introduction Microbial fermentation has been in existence for centuries in the food and beverage industry. Sustainable production of a wide variety of products using microbes has been a focus for the past few decades. Products like biofuels (Buijs et al. 2013), antibodies (Spadiut et al. 2014; Robinson et al. 2015), active pharmaceutical ingredients (Waters et al. 2010), nutraceuticals (Wang et al. 2016), and platform chemicals (Zeng and Sabra 2011), can now be produced using microbial hosts using metabolic and pathway engineering. In order to improve production, metabolic engineering leverages pathway optimization and computational algorithms to improve flux towards the product. Engineered strains using these strategies generally exhibit slower growth rates and higher metabolic burden (Glick et al. 1986; Hong et al. 1991; Heyland et al. 2011;). Complementary techniques like adaptive laboratory evolution (ALE) can be used to improve slow growth rate but may lead to loss of production (Conrad et al.
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2011). Coupling
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