title: A multi-scale study of industrial fermentation processes and their optimization.
abstract: In this article problems in multi-scale industrial fermentation processes are discussed. The problems are generated virtually, by using computer simulation on three different scales--the molecular scale (genetics), the cellular scale (metabolic regulation), and the reactor engineering scale. Inter-scale observation and operation are deemed to be crucial in the optimization of bioprocesses. Bioreaction engineering based on metabolic flux analysis and control is further elucidated. Optimization methodology for study of multi-scale problems in a fermentation process, based on correlation of data, and the scale-up technique for regulation of several bioprocess parameters are generalized by investigation of two typical fermentation processes. A novel bioreactor system was designed to monitor mass flux (for example substrates and (by-)products) in a fermentation process. It was successfully applied to the optimization and scale-up of an industrial fermentation process for penicillin, erythromycin, chlortetracyclin, inosine, and guanosine, and for production of recombinant human serum albumin and a malaria vaccine by use of the Pichia expression system. Substantial improvement of industrial fermentation productivity was achieved.
authors.affiliation: State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China. siliangz@163.net
authors.forename: Siliang
authors.initials: S
authors.lastname: Zhang
authors.forename: Ju
authors.initials: J
authors.lastname: Chu
authors.forename: Yingping
authors.initials: Y
authors.lastname: Zhuang
mesh_terms: D019149:Bioreactors; D018929:Cell Culture Techniques / Q000379:methods*; D002455:Cell Division / Q000502:physiology; D002468:Cell Physiological Phenomena; D003198:Computer Simulation; D005285:Fermentation / Q000502:physiology*; D007218:Industrial Microbiology / Q000379:methods*; D008660:Metabolism / Q000502:physiology*; D008954:Models, Biological; D011786:Quality Control