Model

Genome-scale metabolic model (GSMM) of Escherichia coli

1 Introduction

In recent years, the occurrence of the COVID-19 has caused antiviral drugs to attract public attention. As an intermediate of antiviral drugs, shikimic acid has attracted our attention. Checking the literature, we found that there have been strains of Corynebacterium glutamicum, yeast and Escherichia coli researched on production to increase the yield of shikimic acid, but the results could not reach the industrial level. E. coli is an ideal host for the production of shikimic acid due to its characteristics such as fast growth rate and clear metabolic pathways[3]. Therefore, we wanted to use E. coli strain for the production of shikimic acid. In order to better clarify the experimental design ideas and which genes need to be modified, we made the following metabolic network system predictions.

2 Methods

The genome-scale metabolic model (GSMM) of Escherichia coli (iML1515) was used as foundation for screening the key gene targets of improving the shikimate biosynthesis in silico. Before conducting simulation, the SKMt2pp reaction in iML1515 was modified to reversible reaction, which enable shikimate transferring from cytoplasm to periplasm. A group of flux balance analysis (FBA) was conducted with shikimate output rate gradual increasing from 0 to 6 mmol/g DCW/h-1. The COBRAToolbox 2.0 was used to read and carry out the simulation program in the MATLAB environment[1]. GLPK, a linear programming solver, was used for performing FBA[2]. The glucose input rate and growth-associated maintenance (GAM) were set to 10 mmol/g DCW/h[3] and 44.55 mmol/g DCW/h-1[4], respectively. After FBAs, the fluxes value of all reactions were collected and normalized by a formula

3 Results and Discussion

To identify the key gene targets for improving the shikimate biosynthesis in the metabolic network, the iML1515 was used to analyze the flux variation of reactions in the network while increasing the shikimate output rate. When glucose was a substrate, 88 reactions were screened from all reactions in the metabolic network (Fig.1A). The normalized flux of these reactions showed a monotonous increasing trend, suggesting these reactions should be potential targets directly affecting the biosynthesis of shikimate. Based on metabolic pathways (Fig.1D) and non-normalized flux ranking (supplementary file 1), the reactions involved in the shikimate biosynthesis pathway (including aroE, aroD, aroG and aroB) showed a flux-increased trend with shikimate output rate, and the reactions involving in precursor phosphoenolpyruvate (PEP) accumulation (including tktA and talB) also have slightly increased in flux (Fig.1B), demonstrating that these targets should be enhanced in project of improving shikimate biosynthesis. Whereas, the reaction involved in the glucose phosphotransferase system (including ptsG, ptsH, ptsI), pyruvate dehydrogenase (coding by poxB gene) and shikimate kinase (coding by aroK and aroL) showed a deceased trend in flux variation (Fig1.C), which weakens the precursor PEP consumption pathway and shikimate consumption pathway.

Fig.1 In silico identification of key factors for shikimate production in Escherichia coli (A) presented the heapmap of the normalized flux trend of selection reaction during the shikimate output rate increasing. (B) presented the flux variation of the reaction corresponding to aroG, aroB, aroD, aroE, tktA, and talB. (C) presented the flux variation of the reaction corresponding to poxB, ptsGHI and talB. (D) Schematic diagram of the roles of the identified genes in silico.

4 Conclusion

Based on the model prediction results and metabolic pathways, the above eleven proteins were further classified into three modules (Figure 1D): (1) Enhancement of PEP production : (i) blocking the phosphate transporter pathway (PTS system) by knocking out the ptsG, ptsH, and ptsI genes, rendering PEP incapable of being converted to synthesize pyruvic acid; and (ii) blocking the PEP branching pathways including the lactic acid, acetic acid, and ethanol synthesis pathway (knockdown of poxB gene). (2) Increase E4P content: overexpression of tktA and talB genes; (3) Construction and optimization of shikimic acid synthesis pathway: (i) overexpression of aroG, aroB, aroD and aroE genes to enhance the metabolic flow of shikimic acid synthesized by PEP and E4P; (ii) knockdown of aroK and aroL gene to block the shikimic acid catabolic pathway.