Intracellular metabolism analysis of Clostridium cellulovorans via modeling integrating proteomics, metabolomics and fermentation. (February 2020)

• Record Type: Journal Article
• Authors: Ou, Jianfa; Bao, Teng; Ernst, Patrick; Si, Yingnan; Prabhu, Sumanth D.; Wu, Hui; Zhang, Jianyi (Jay); Zhou, Lufang; Yang, Shang-Tian; Liu, Xiaoguang (Margaret)
• Is Part Of: Process biochemistry. Volume 89(2020)
• Page Start: 9
• Page End: 19
• Publication Date: 2020-02
• Subjects: Clostridium cellulovorans -- Cellulosic n-butanol fermentation -- Proteomics and metabolomics -- Dynamic model -- Metabolic control analysis; Biochemical engineering -- Periodicals; Biotechnology -- Periodicals; Biochemistry -- periodicals; Biotechnology -- periodicals; Chemical Engineering -- periodicals; Génie biochimique -- Périodiques; Biotechnologie -- Périodiques; Biochemical engineering; Biotechnology; Periodicals; 660.63
• DOI: 10.1016/j.procbio.2019.10.032
• Languages: English
• ISSNs: 1359-5113

Abstract

Graphical abstract: Highlights: The intracellular metabolism of cellulosic butanol formation was investigated. Dynamic model was developed by integrating Omics and fermentation data. Cell and process regulators were identified via metabolic control analysis. Rational metabolic engineering strategies were proposed. Abstract: A consolidated bioprocess for cellulosic n -butanol production has been developed by engineering Clostridium cellulovorans to overexpress a bifunctional aldehyde/alcohol dehydrogenase. Rational metabolic engineering is important to further improve butanol production. This study aimed to investigate intracellular metabolism and identify the key regulators of cellulosic butanol formation in C. cellulovorans via integrated Omics and fermentation kinetics data analysis. First, comparative proteomics and metabolomics analyses of wild type and n -butanol producing mutant strain were conducted, which quantified 624 host cell proteins and 474 primary and secondary metabolites. Compared to wild type, most cellulases in cellulolysis were up-regulated, but three glycolysis enzymes and three enzymes in central pathway were down-regulated in the n -butanol producing strain. Second, a dynamic model integrating Omics and fermentation data was developed to identify key regulators in butanol biosynthesis, which were ranked by further metabolic control analysis. Finally, rational metabolic engineering was performed in C. cellulovorans by overexpressing two genes ( thl and hbd ) identified as important factors limiting butanol biosynthesis, which improved butanol yield and C4/C2 ratio. This study demonstrated a research approach to integrate multi-Omics and fermentation data of C. cellulovorans and guide its rational metabolic engineering, which can also be applied to other microorganisms.