题 目：Metabolic Engineering of Yeast for Production of Fuels and Chemicals
报告人：Jens Nielsen 院士
主持人： 庄英萍 教授
Jens Nielsen院士是代谢工程及合成生物学领域著名学者，国际代谢工程协会主席。曾获国际代谢工程奖、国际生化工程奖、Charles D. Scott奖等奖项。先后当选丹麦工程院、丹麦科学院、瑞典皇家工程院、瑞典皇家科学院院士以及美国微生物学会会士，美国工程院外籍院士；先后8次担任系统生物学及代谢工程领域国际会议主席；他还曾创办多家公司，其创办的Fluxome A/S公司利用代谢工程改造酵母生产紫杉醇，获得风险投资2000万欧元。学术方面至今已发表超过550篇研究论文，引用次数超过36000次（H因子达94），合著40余本著作，获授权发明专利50余项。
Metabolic Engineering relies on the Design-Build-Test cycle. This cycle includes technologies like mathematical modeling of metabolism, genome editing and advanced tools for phenotypic characterization. In recent years there have been advances in several of these technologies, which has enabled faster development of metabolically engineered strains that can be used for production of fuels and chemicals.
The yeast Saccharomyces cerevisiae is widely used for production of fuels, chemicals, pharmaceuticals and materials. Through metabolic engineering of this yeast a number of novel industrial processes have been developed over the last 10 years. Besides its wide industrial use, S. cerevisiae also serves as an eukaryal model organism, and many systems biology tools have therefore been developed for this organism. These tools can be used for detailed phenotypic characterization as well as for metabolic design.
In this lecture it will be demonstrated how the Design-Build-Test cycle of Metabolic Engineering has allowed for development of yeast cell factories for production of a range of different fuels and chemicals. Some examples of different technologies will be presented together with examples of metabolic engineering designs, in particular for development of platform strains that can be used for production of a fatty acid derived products, e.g. fatty alcohols and alkanes. It will be argued that with advancement in genome-editing technologies and novel methods for rapid phenotypic screening, advancement in the field is hampered by our design abilities, i.e. to predict genotype-phenotype connections. For this genome-scale metabolic modeling is a strong technology, and in the presentation recent advancements in mathematical modeling for cell factory design will be presented. Finally, the presentation will also demonstrate how the Design-Build-Test cycle can be expanded to incorporate adaptive laboratory evolution to identify targets for engineering complex traits, such as improved tolerance to toxic metabolites like elevated temperatures or low pH.