Computer-Aided Rational Design of Efficient NADPH Production System by Escherichia coli pgi Mutant Using a Mixture of Glucose and Xylose.

Yu Matsuoka,Hiroyuki Kurata

doi:10.3389/fbioe.2020.00277

Yu Matsuoka, Hiroyuki Kurata

Open Access

https://doi.org/10.3389/fbioe.2020.00277

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Abstract

Lignocellulosic biomass can be hydrolyzed into two major sugars of glucose and xylose, and thus the strategy for the efficient consumption of both sugars is highly desirable. NADPH is the essential molecule for the production of industrially important value-added chemicals, and thus its availability is quite important. Escherichia coli mutant lacking the pgi gene encoding phosphoglucose isomerase (Pgi) has been preferentially used to overproduce the NADPH. However, there exists a disadvantage that the cell growth rate becomes low for the mutant grown on glucose. This limits the efficient NADPH production, and therefore, it is quite important to investigate how addition of different carbon source such as xylose (other than glucose) effectively improves the NADPH production. In this study, we have developed a kinetic model to propose an efficient NADPH production system using E. coli pgi-knockout mutant with a mixture of glucose and xylose. The proposed system adds xylose to glucose medium to recover the suppressed growth of the pgi mutant, and determines the xylose content to maximize the NADPH productivity. Finally, we have designed a mevalonate (MVA) production system by implementing ArcA overexpression into the pgi-knockout mutant using a mixture of glucose and xylose. In addition to NADPH overproduction, the accumulation of acetyl-CoA (AcCoA) is necessary for the efficient MVA production. In the present study, therefore, we considered to overexpress ArcA, where ArcA overexpression suppresses the TCA cycle, causing the overflow of AcCoA, a precursor of MVA. We predicted the xylose content that maximizes the MVA production. This approach demonstrates the possibility of a great progress in the computer-aided rational design of the microbial cell factories for useful metabolite production.

Highlights

Microbial production of biofuels and biochemicals from renewable feedstocks has received considerable attention from environmental protection and energy production perspectives
NADPH can be produced at several metabolic sites such as the oxidative pentose phosphate (PP) pathway via glucose 6-phosphate dehydrogenase (G6PDH) and 6-phosphogluconate dehydrogenase (6PGDH), as well as isocitrate dehydrogenase (ICDH) in the TCA cycle, and malic enzyme (Mez), the oxidative PP (OPP) pathway is the dominant site in many organisms including Escherichia coli (Gvozdev et al, 1976; Jan et al, 2013)
The typical approach for the overproduction of NADPH is, to increase the flux through the OPP pathway by the disruption of pgi gene encoding phosphoglucose isomerase (Pgi) (and pfkA encoding phosphofructokinase (Pfk) but to a lesser extent), which forces the flux of the imported glucose toward the OPP pathway at the glucose 6posphate (G6P) node, which resulted in increased NADPH

Summary

Introduction

Microbial production of biofuels and biochemicals from renewable feedstocks has received considerable attention from environmental protection and energy production perspectives. The typical approach for the overproduction of NADPH is, to increase the flux through the OPP pathway by the disruption of pgi gene encoding phosphoglucose isomerase (Pgi) (and pfkA encoding phosphofructokinase (Pfk) but to a lesser extent), which forces the flux of the imported glucose toward the OPP pathway at the glucose 6posphate (G6P) node, which resulted in increased NADPH This strategy has been employed to produce several chemicals in practice (Kabir and Shimizu, 2003; Marx et al, 2003; Blombach et al, 2008; Wang et al, 2013; Park et al, 2014; Seol et al, 2014; Kim et al, 2015; Ng et al, 2015; Aslan et al, 2017; Sundara Sekar et al, 2017). In order to avoid the lower cell growth rate inherent in the pgi-knockout mutant, several attempts have been made by partially increasing the Pgi activity (Usui et al, 2012), by reducing the expression level of its gene via replacement of its start codon ATG with GTG without completely removing Pgi (Park et al, 2014; Kim et al, 2015), and by overexpressing the genes of the OPP pathway (Lim et al, 2002; Perez-Zabaleta et al, 2016)

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