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Lu H, Xiao L, Liao W, Yan X, Nielsen J. Cell factory design with advanced metabolic modelling empowered by artificial intelligence. Metab Eng 2024; 85:61-72. [PMID: 39038602 DOI: 10.1016/j.ymben.2024.07.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2024] [Revised: 07/06/2024] [Accepted: 07/06/2024] [Indexed: 07/24/2024]
Abstract
Advances in synthetic biology and artificial intelligence (AI) have provided new opportunities for modern biotechnology. High-performance cell factories, the backbone of industrial biotechnology, are ultimately responsible for determining whether a bio-based product succeeds or fails in the fierce competition with petroleum-based products. To date, one of the greatest challenges in synthetic biology is the creation of high-performance cell factories in a consistent and efficient manner. As so-called white-box models, numerous metabolic network models have been developed and used in computational strain design. Moreover, great progress has been made in AI-powered strain engineering in recent years. Both approaches have advantages and disadvantages. Therefore, the deep integration of AI with metabolic models is crucial for the construction of superior cell factories with higher titres, yields and production rates. The detailed applications of the latest advanced metabolic models and AI in computational strain design are summarized in this review. Additionally, approaches for the deep integration of AI and metabolic models are discussed. It is anticipated that advanced mechanistic metabolic models powered by AI will pave the way for the efficient construction of powerful industrial chassis strains in the coming years.
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Affiliation(s)
- Hongzhong Lu
- State Key Laboratory of Microbial Metabolism, School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, PR China.
| | - Luchi Xiao
- State Key Laboratory of Microbial Metabolism, School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, PR China
| | - Wenbin Liao
- State Key Laboratory of Microbial Metabolism, School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, PR China; Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai, 200237, PR China
| | - Xuefeng Yan
- Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai, 200237, PR China
| | - Jens Nielsen
- BioInnovation Institute, Ole Måløes Vej, DK2200, Copenhagen N, Denmark; Department of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, SE412 96, Gothenburg, Sweden.
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Sun X, Bi X, Li G, Cui S, Xu X, Liu Y, Li J, Du G, Lv X, Liu L. Combinatorial metabolic engineering of Bacillus subtilis for menaquinone-7 biosynthesis. Biotechnol Bioeng 2024. [PMID: 38965781 DOI: 10.1002/bit.28800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Revised: 06/07/2024] [Accepted: 06/27/2024] [Indexed: 07/06/2024]
Abstract
Menaquinone-7 (MK-7), a form of vitamin K2, supports bone health and prevents arterial calcification. Microbial fermentation for MK-7 production has attracted widespread attention because of its low cost and short production cycles. However, insufficient substrate supply, unbalanced precursor synthesis, and low catalytic efficiency of key enzymes severely limited the efficiency of MK-7 synthesis. In this study, utilizing Bacillus subtilis BSAT01 (with an initial MK-7 titer of 231.0 mg/L) obtained in our previous study, the glycerol metabolism pathway was first enhanced to increase the 3-deoxy-arabino-heptulonate 7-phosphate (DHAP) supply, which led to an increase in MK-7 titer to 259.7 mg/L. Subsequently, a combination of knockout strategies predicted by the genome-scale metabolic model etiBsu1209 was employed to optimize the central carbon metabolism pathway, and the resulting strain showed an increase in MK-7 production from 259.7 to 318.3 mg/L. Finally, model predictions revealed the methylerythritol phosphate pathway as the major restriction pathway, and the pathway flux was increased by heterologous introduction (Introduction of Dxs derived from Escherichia coli) and fusion expression (End-to-end fusion of two enzymes by a linker peptide), resulting in a strain with a titer of 451.0 mg/L in a shake flask and 474.0 mg/L in a 50-L bioreactor. This study achieved efficient MK-7 synthesis in B. subtilis, laying the foundation for large-scale MK-7 bioproduction.
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Affiliation(s)
- Xian Sun
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, China
- Science Center for Future Foods, Jiangnan University, Wuxi, China
- Food Laboratory of Zhongyuan, Jiangnan University, Wuxi, China
| | - Xinyu Bi
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, China
- Science Center for Future Foods, Jiangnan University, Wuxi, China
| | - Guyue Li
- Richen Bioengineering Co., Ltd., Nantong, China
| | - Shixiu Cui
- Jiaxing Institute of Future Food, Jiaxing, China
| | - Xianhao Xu
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, China
- Science Center for Future Foods, Jiangnan University, Wuxi, China
| | - Yanfeng Liu
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, China
- Science Center for Future Foods, Jiangnan University, Wuxi, China
| | - Jianghua Li
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, China
- Science Center for Future Foods, Jiangnan University, Wuxi, China
- Jiaxing Institute of Future Food, Jiaxing, China
| | - Guocheng Du
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, China
- Science Center for Future Foods, Jiangnan University, Wuxi, China
| | - Xueqin Lv
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, China
- Science Center for Future Foods, Jiangnan University, Wuxi, China
| | - Long Liu
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, China
- Science Center for Future Foods, Jiangnan University, Wuxi, China
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Gong Z, Chen J, Jiao X, Gong H, Pan D, Liu L, Zhang Y, Tan T. Genome-scale metabolic network models for industrial microorganisms metabolic engineering: Current advances and future prospects. Biotechnol Adv 2024; 72:108319. [PMID: 38280495 DOI: 10.1016/j.biotechadv.2024.108319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2023] [Revised: 01/04/2024] [Accepted: 01/18/2024] [Indexed: 01/29/2024]
Abstract
The construction of high-performance microbial cell factories (MCFs) is the centerpiece of biomanufacturing. However, the complex metabolic regulatory network of microorganisms poses great challenges for the efficient design and construction of MCFs. The genome-scale metabolic network models (GSMs) can systematically simulate the metabolic regulation process of microorganisms in silico, providing effective guidance for the rapid design and construction of MCFs. In this review, we summarized the development status of 16 important industrial microbial GSMs, and further outline the technologies or methods that continuously promote high-quality GSMs construction from five aspects: I) Databases and modeling tools facilitate GSMs reconstruction; II) evolving gap-filling technologies; III) constraint-based model reconstruction; IV) advances in algorithms; and V) developed visualization tools. In addition, we also summarized the applications of GSMs in guiding metabolic engineering from four aspects: I) exploring and explaining metabolic features; II) predicting the effects of genetic perturbations on metabolism; III) predicting the optimal phenotype; IV) guiding cell factories construction in practical experiment. Finally, we discussed the development of GSMs, aiming to provide a reference for efficiently reconstructing GSMs and guiding metabolic engineering.
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Affiliation(s)
- Zhijin Gong
- National Energy R&D Center for Biorefinery, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China; Beijing Key Laboratory of Bioprocess, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China
| | - Jiayao Chen
- National Energy R&D Center for Biorefinery, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China; Beijing Key Laboratory of Bioprocess, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China
| | - Xinyu Jiao
- National Energy R&D Center for Biorefinery, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China; Beijing Key Laboratory of Bioprocess, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China
| | - Hao Gong
- National Energy R&D Center for Biorefinery, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China; Beijing Key Laboratory of Bioprocess, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China; College of Mathematics and Physics, Beijing University of Chemical Technology, Beijing 100029, China
| | - Danzi Pan
- National Energy R&D Center for Biorefinery, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China; Beijing Key Laboratory of Bioprocess, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China; College of Mathematics and Physics, Beijing University of Chemical Technology, Beijing 100029, China
| | - Lingli Liu
- National Energy R&D Center for Biorefinery, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China; Beijing Key Laboratory of Bioprocess, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China; College of Mathematics and Physics, Beijing University of Chemical Technology, Beijing 100029, China
| | - Yang Zhang
- National Energy R&D Center for Biorefinery, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China; Beijing Key Laboratory of Bioprocess, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China
| | - Tianwei Tan
- National Energy R&D Center for Biorefinery, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China; Beijing Key Laboratory of Bioprocess, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China.
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Immanuel A, Yennamalli RM, Ulaganathan V. Targeting the Bottlenecks in Levan Biosynthesis Pathway in Bacillus subtilis and Strain Optimization by Computational Modeling and Omics Integration. OMICS : A JOURNAL OF INTEGRATIVE BIOLOGY 2024; 28:49-58. [PMID: 38315781 DOI: 10.1089/omi.2023.0277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
Levan is a fructan polymer with many industrial applications such as the formulation of hydrogels, drug delivery, and wound healing, among others. To this end, metabolic systems engineering is a valuable method to improve the yield of a specific metabolite in a wide range of bacterial and eukaryotic organisms. In this study, we report a systems biology approach integrating genomics data for the Bacillus subtilis model, wherein the metabolic pathway for levan biosynthesis is unpacked. We analyzed a revised genome-scale enzyme-constrained metabolic model (ecGEM) and performed simulations to increase levan biopolymer production capacity in B. subtilis. We used the model ec_iYO844_lvn to (1) identify the essential genes and bottlenecks in levan production, and (2) specifically design an engineered B. subtilis strain capable of producing higher levan yields. The FBA and FVA analysis showed the maximal growth rate of the organism up to 0.624 hr-1 at 20 mmol gDw-1 hr-1 of sucrose intake. Gene knockout analyses were performed to identify gene knockout targets to increase the levan flux in B. subtilis. Importantly, we found that the pgk and ctaD genes are the two target genes for the knockout. The perturbation of these two genes has flux gains for levan production reactions with 1.3- and 1.4-fold the relative flux span in the mutant strains, respectively, compared to the wild type. In all, this work identifies the bottlenecks in the production of levan and possible ways to overcome them. Our results provide deeper insights on the bacterium's physiology and new avenues for strain engineering.
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Affiliation(s)
- Aruldoss Immanuel
- Molecular Motors Lab, Department of Biotechnology, School of Chemical & Biotechnology, SASTRA Deemed to be University, Thanjavur, India
| | - Ragothaman M Yennamalli
- Department of Bioinformatics, School of Chemical & Biotechnology, SASTRA Deemed to be University, Thanjavur, India
| | - Venkatasubramanian Ulaganathan
- Molecular Motors Lab, Department of Biotechnology, School of Chemical & Biotechnology, SASTRA Deemed to be University, Thanjavur, India
- Department of Bioinformatics, School of Chemical & Biotechnology, SASTRA Deemed to be University, Thanjavur, India
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Qian J, Wang Y, Hu Z, Shi T, Wang Y, Ye C, Huang H. Bacillus sp. as a microbial cell factory: Advancements and future prospects. Biotechnol Adv 2023; 69:108278. [PMID: 37898328 DOI: 10.1016/j.biotechadv.2023.108278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 09/27/2023] [Accepted: 10/25/2023] [Indexed: 10/30/2023]
Abstract
Bacillus sp. is one of the most distinctive gram-positive bacteria, able to grow efficiently using cheap carbon sources and secrete a variety of useful substances, which are widely used in food, pharmaceutical, agricultural and environmental industries. At the same time, Bacillus sp. is also recognized as a safe genus with a relatively clear genetic background, which is conducive to the industrial production of target metabolites. In this review, we discuss the reasons why Bacillus sp. has been so extensively studied and summarize its advances in systems and synthetic biology, engineering strategies to improve microbial cell properties, and industrial applications in several metabolic engineering applications. Finally, we present the current challenges and possible solutions to provide a reliable basis for Bacillus sp. as a microbial cell factory.
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Affiliation(s)
- Jinyi Qian
- School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, Nanjing 210023, PR China
| | - Yuzhou Wang
- School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, Nanjing 210023, PR China
| | - Zijian Hu
- School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, Nanjing 210023, PR China
| | - Tianqiong Shi
- School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, Nanjing 210023, PR China.
| | - Yuetong Wang
- School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, Nanjing 210023, PR China.
| | - Chao Ye
- School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, Nanjing 210023, PR China.
| | - He Huang
- School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, Nanjing 210023, PR China.
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