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Improvement of l-arginine production by in silico genome-scale metabolic network model guided genetic engineering

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Abstract

Genome-scale metabolic network model (GSMM) is an important in silico tool that can efficiently predict the target genes to be modulated. A Corynebacterium crenatum argB-M4 Cc_iKK446_arginine model was constructed on the basis of the GSMM of Corynebacterium glutamicum ATCC 13032 Cg_iKK446. Sixty-four gene deletion sites, twenty-four gene enhancement sites, and seven gene attenuation sites were determined for the improvement of l-arginine production in engineered C. crenatum. Among these sites, the effects of disrupting putP, cgl2310, pta, and Ncgl1221 and overexpressing lysE on l-arginine production were investigated. Moreover, the strain CCM007 with deleted putP, cgl2310, pta, and Ncgl1221 and overexpressed lysE produced 24.85 g/L l-arginine. This finding indicated a 106.8% improvement in l-arginine production compared with that in CCM01. GSMM is an excellent tool for identifying target genes to promote l-arginine accumulation in engineered C. crenatum.

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Acknowledgements

This work was supported by the Natural Science Foundation of China (No. 31660019), “5511” Superior Technology Innovation Team Project of Jiangxi (No. 20165BCB19004) and the Natural Science Foundation of Jiangxi (No. 2016BAB204173).

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Authors and Affiliations

  1. Department of Life Science, Jiangxi Normal University, Nanchang, 330096, People’s Republic of China

    Mingzhu Huang, Yue Zhao, Rong Li, Weihua Huang & Xuelan Chen

  2. School of Life Science, Key Laboratory of Functional Small Organic Molecule of Ministry of Education, Jiangxi Normal University, 99 Ziyang Road, Nanchang, 330096, People’s Republic of China

    Mingzhu Huang & Xuelan Chen

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  1. Mingzhu Huang
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  2. Yue Zhao
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  3. Rong Li
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Correspondence to Xuelan Chen.

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Huang, M., Zhao, Y., Li, R. et al. Improvement of l-arginine production by in silico genome-scale metabolic network model guided genetic engineering. 3 Biotech 10, 126 (2020). https://doi.org/10.1007/s13205-020-2114-9

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