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Sheremetieva M, Anufriev K, Khlebodarova T, Kolchanov N, Yanenko A. Rational metabolic engineering of Corynebacterium glutamicum to create a producer of L-valine. Vavilovskii Zhurnal Genet Selektsii 2022; 26:743-757. [PMID: 36694718 PMCID: PMC9834717 DOI: 10.18699/vjgb-22-90] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Revised: 10/26/2022] [Accepted: 10/26/2022] [Indexed: 01/06/2023] Open
Abstract
L-Valine is one of the nine amino acids that cannot be synthesized de novo by higher organisms and must come from food. This amino acid not only serves as a building block for proteins, but also regulates protein and energy metabolism and participates in neurotransmission. L-Valine is used in the food and pharmaceutical industries, medicine and cosmetics, but primarily as an animal feed additive. Adding L-valine to feed, alone or mixed with other essential amino acids, allows for feeds with lower crude protein content, increases the quality and quantity of pig meat and broiler chicken meat, as well as improves reproductive functions of farm animals. Despite the fact that the market for L-valine is constantly growing, this amino acid is not yet produced in our country. In modern conditions, the creation of strains-producers and organization of L-valine production are especially relevant for Russia. One of the basic microorganisms most commonly used for the creation of amino acid producers, along with Escherichia coli, is the soil bacterium Corynebacterium glutamicum. This review is devoted to the analysis of the main strategies for the development of L- valine producers based on C. glutamicum. Various aspects of L-valine biosynthesis in C. glutamicum are reviewed: process biochemistry, stoichiometry and regulation, enzymes and their corresponding genes, export and import systems, and the relationship of L-valine biosynthesis with central cell metabolism. Key genetic elements for the creation of C. glutamicum-based strains-producers are identified. The use of metabolic engineering to enhance L-valine biosynthesis reactions and to reduce the formation of byproducts is described. The prospects for improving strains in terms of their productivity and technological characteristics are shown. The information presented in the review can be used in the production of producers of other amino acids with a branched side chain, namely L-leucine and L-isoleucine, as well as D-pantothenate.
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Affiliation(s)
| | - K.E. Anufriev
- NRC “Kurchatov Institute”, Kurchatov Genomic Center, Moscow, Russia
| | - T.M. Khlebodarova
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, RussiaKurchatov Genomic Center of ICG SB RAS, Novosibirsk, Russia
| | - N.A. Kolchanov
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, RussiaKurchatov Genomic Center of ICG SB RAS, Novosibirsk, Russia
| | - A.S. Yanenko
- NRC “Kurchatov Institute”, Kurchatov Genomic Center, Moscow, Russia
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Golubyatnikov V, Akinshin A, Ayupova N, Minushkina L. Stratifications and foliations in phase portraits of gene network models. Vavilovskii Zhurnal Genet Selektsii 2022; 26:758-764. [PMID: 36694713 PMCID: PMC9837163 DOI: 10.18699/vjgb-22-91] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 09/20/2022] [Accepted: 09/21/2022] [Indexed: 01/06/2023] Open
Abstract
Periodic processes of gene network functioning are described with good precision by periodic trajectories (limit cycles) of multidimensional systems of kinetic-type differential equations. In the literature, such systems are often called dynamical, they are composed according to schemes of positive and negative feedback between components of these networks. The variables in these equations describe concentrations of these components as functions of time. In the preparation of numerical experiments with such mathematical models, it is useful to start with studies of qualitative behavior of ensembles of trajectories of the corresponding dynamical systems, in particular, to estimate the highest likelihood domain of the initial data, to solve inverse problems of parameter identification, to list the equilibrium points and their characteristics, to localize cycles in the phase portraits, to construct stratification of the phase portraits to subdomains with different qualities of trajectory behavior, etc. Such an à priori geometric analysis of the dynamical systems is quite analogous to the basic section "Investigation of functions and plot of their graphs" of Calculus, where the methods of qualitative studies of shapes of curves determined by equations are exposed. In the present paper, we construct ensembles of trajectories in phase portraits of some dynamical systems. These ensembles are 2-dimensional surfaces invariant with respect to shifts along the trajectories. This is analogous to classical construction in analytic mechanics, i. e. the level surfaces of motion integrals (energy, kinetic moment, etc.). Such surfaces compose foliations in phase portraits of dynamical systems of Hamiltonian mechanics. In contrast with this classical mechanical case, the foliations considered in this paper have singularities: all their leaves have a non-empty intersection, they contain limit cycles on their boundaries. Description of the phase portraits of these systems at the level of their stratifications, and that of ensembles of trajectories allows one to construct more realistic gene network models on the basis of methods of statistical physics and the theory of stochastic differential equations.
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Affiliation(s)
- V.P. Golubyatnikov
- Sobolev Institute of Mathematics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, RussiaNovosibirsk State University, Novosibirsk, Russia
| | - A.A. Akinshin
- Huawei Russian Research Institute, St. Petersburg, Russia
| | - N.B. Ayupova
- Sobolev Institute of Mathematics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, RussiaNovosibirsk State University, Novosibirsk, Russia
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Liu J, Liu M, Shi T, Sun G, Gao N, Zhao X, Guo X, Ni X, Yuan Q, Feng J, Liu Z, Guo Y, Chen J, Wang Y, Zheng P, Sun J. CRISPR-assisted rational flux-tuning and arrayed CRISPRi screening of an L-proline exporter for L-proline hyperproduction. Nat Commun 2022; 13:891. [PMID: 35173152 PMCID: PMC8850433 DOI: 10.1038/s41467-022-28501-7] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 01/24/2022] [Indexed: 02/07/2023] Open
Abstract
Development of hyperproducing strains is important for biomanufacturing of biochemicals and biofuels but requires extensive efforts to engineer cellular metabolism and discover functional components. Herein, we optimize and use the CRISPR-assisted editing and CRISPRi screening methods to convert a wild-type Corynebacterium glutamicum to a hyperproducer of L-proline, an amino acid with medicine, feed, and food applications. To facilitate L-proline production, feedback-deregulated variants of key biosynthetic enzyme γ-glutamyl kinase are screened using CRISPR-assisted single-stranded DNA recombineering. To increase the carbon flux towards L-proline biosynthesis, flux-control genes predicted by in silico analysis are fine-tuned using tailored promoter libraries. Finally, an arrayed CRISPRi library targeting all 397 transporters is constructed to discover an L-proline exporter Cgl2622. The final plasmid-, antibiotic-, and inducer-free strain produces L-proline at the level of 142.4 g/L, 2.90 g/L/h, and 0.31 g/g. The CRISPR-assisted strain development strategy can be used for engineering industrial-strength strains for efficient biomanufacturing.
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Affiliation(s)
- Jiao Liu
- Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.,National Technology Innovation Center of Synthetic Biology, Tianjin, 300308, China
| | - Moshi Liu
- Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.,National Technology Innovation Center of Synthetic Biology, Tianjin, 300308, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Tuo Shi
- Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.,National Technology Innovation Center of Synthetic Biology, Tianjin, 300308, China
| | - Guannan Sun
- Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.,National Technology Innovation Center of Synthetic Biology, Tianjin, 300308, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Ning Gao
- Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.,National Technology Innovation Center of Synthetic Biology, Tianjin, 300308, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xiaojia Zhao
- Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.,National Technology Innovation Center of Synthetic Biology, Tianjin, 300308, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xuan Guo
- Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.,National Technology Innovation Center of Synthetic Biology, Tianjin, 300308, China
| | - Xiaomeng Ni
- Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.,National Technology Innovation Center of Synthetic Biology, Tianjin, 300308, China
| | - Qianqian Yuan
- Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.,National Technology Innovation Center of Synthetic Biology, Tianjin, 300308, China
| | - Jinhui Feng
- Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.,National Technology Innovation Center of Synthetic Biology, Tianjin, 300308, China
| | - Zhemin Liu
- Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.,National Technology Innovation Center of Synthetic Biology, Tianjin, 300308, China
| | - Yanmei Guo
- Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.,National Technology Innovation Center of Synthetic Biology, Tianjin, 300308, China
| | - Jiuzhou Chen
- Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.,National Technology Innovation Center of Synthetic Biology, Tianjin, 300308, China
| | - Yu Wang
- Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China. .,National Technology Innovation Center of Synthetic Biology, Tianjin, 300308, China. .,University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Ping Zheng
- Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China. .,National Technology Innovation Center of Synthetic Biology, Tianjin, 300308, China. .,University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Jibin Sun
- Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.,National Technology Innovation Center of Synthetic Biology, Tianjin, 300308, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
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Nie Z, Liu P, Wang Y, Guo X, Tan Z, Shen J, Tang Z, Lin J, Sun J, Zheng P, Zhu L. Directed Evolution and Rational Design of Mechanosensitive Channel MscCG2 for Improved Glutamate Excretion Efficiency. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2021; 69:15660-15669. [PMID: 34928605 DOI: 10.1021/acs.jafc.1c07086] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Mechanosensitive amino acid exporters have drawn increasing attention due to their important roles in extracellular accumulation of the target amino acids. Protein engineering is a powerful approach to tailor the properties of amino acid exporters and illustrate structure-function relationships. Here we report the first protein engineering effort on the mechanosensitive glutamate exporter MscCG2 from Corynebacterium glutamicum for improved excretion efficiency of glutamate and understanding of the structure-function relationship. MscCG2 was engineered through directed evolution and computer-assisted design with a coupled assay in microtiter plate format. Improved MscCG2 variants were identified with up to 2.5-fold increase in the level of glutamate excretion in the early stage of fermentation and 1.5-fold in the late stage of fermentation under experimental conditions. Furthermore, the identified variants exhibited enhanced efflux of 4-fluoroglutamate (4-FG), an analog of glutamate. Structure analysis employing homology modeling and molecular dynamics (MD) simulation reveal that identified amino acid substitutions enlarge the size of the seven portals on the equator of MscCG2 and expand the narrowest rim of its inner channel, respectively. This study demonstrates the great potential of protein engineering in improving the secretion efficiency of exporters for enhanced bioproduction.
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Affiliation(s)
- Zhihua Nie
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
- National Technology Innovation Center of Synthetic Biology, Tianjin 300308, China
| | - Pi Liu
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
- National Technology Innovation Center of Synthetic Biology, Tianjin 300308, China
| | - Yu Wang
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
- National Technology Innovation Center of Synthetic Biology, Tianjin 300308, China
| | - Xuan Guo
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
- National Technology Innovation Center of Synthetic Biology, Tianjin 300308, China
| | - Zijian Tan
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
- National Technology Innovation Center of Synthetic Biology, Tianjin 300308, China
| | - Jie Shen
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
- National Technology Innovation Center of Synthetic Biology, Tianjin 300308, China
| | - Zijing Tang
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
- National Technology Innovation Center of Synthetic Biology, Tianjin 300308, China
| | - Jianping Lin
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
- National Technology Innovation Center of Synthetic Biology, Tianjin 300308, China
| | - Jibin Sun
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
- National Technology Innovation Center of Synthetic Biology, Tianjin 300308, China
| | - Ping Zheng
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
- National Technology Innovation Center of Synthetic Biology, Tianjin 300308, China
| | - Leilei Zhu
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
- National Technology Innovation Center of Synthetic Biology, Tianjin 300308, China
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