Project description:Clostridium sp. strain CT7 is a new emerging microbial cell factory with high butanol ratio owing to the non-traditional butanol fermentation mode with uncoupled acetone and 1,3-propanediol formation. Significant change of products profile was shown in glycerol- and glucose-fed strain CT7, especially much higher butanol and lower volatile fatty acids production from glycerol-fed one. However, the mechanism of this interesting phenomenon was still unclear. To better elaborate the bacterial response towards glycerol and glucose, the quantitative proteomic analysis through iTRAQ strategy was performed to reveal the regulated proteomic expression levels under different substrates. Proteomics data showed highly increased proteomic expression levels of proteins related with glycerol utilization and solvent generation under glycerol media. In addition, the up-regulation of hydrogenases, ferredoxins and electron-transferring proteins may attribute to the internal redox balance, while the earlier triggered sporulation response in glycerol-fed media may be associated with the higher butanol fermentation. This study will provide the platform for metabolic engineering of this emerging industrial microorganism for more efficient butanol production from glycerol.
Project description:Vitamin C is an essential water-soluble vitamin in humans, primates and a few other mammals, and is widely used in the pharmaceutical, food, cosmetics, and feed industries for its antioxidant capacity. To achieve large-scale industrial production, the precursor of Vc, 2-keto-L-gulonic acid is mainly produced using a classic two-step fermentation process. In the second step of the two-step fermentation process, the microbial consortium of Ketogulonicigenium vulgare and Bacillus strains is used to achieve 2-KLG production. However, the relationship between the two strains are still unclear.The purpose of our study was to determine cell-cell communication in a microbial consortium consisting of K. vulgare and Bacillus pumilus by iTRAQ-based proteomics.
