Decoupling of Growth from Production of Biochemicals and Proteins

With increasing awareness of sustainability in our current society, alternative approaches to produce fuels and petro-derived chemicals are required. Biofuels and biochemicals produced from microbial cell factories provide an alternative to current fossil based chemicals. Meanwhile, microbial cell factories have found their applications for producing a wide range of products, such as food additives, pharmaceuticals and industrial enzymes. However, for most of current microbial cell factories, the performance is far from sufficient to be used in an economic industrial fermentation process. One general problem for these cell factories is the un-controlled accumulation of biomass during fermentation, which significantly reduces the fraction of substrate that can be converted into products. Therefore, a method for controlling cell growth during production becomes desirable in order to improve the production of a range of interesting molecules. This thesis has aimed at developing various methods for controlling cell growth as well as to maintain their capacity for production, in order to improving the performance of microbial cell factories. Using the popular cell factory organism, E. coli, as our model system, three different strategies have been employed to explore the desired growth controlling methods. First, the cell growth was controlled by limiting nutrients or adding inhibitory chemicals in cultivation medium. Significant improvement of production yield and specific productivity, of both tyrosine and mevalonate, was achieved through this type of growth limitation. Second, rationally designed genetic growth switches, based on CRISPR interference (CRISPRi) systems, have been developed. By switching off cell growth during production, the production of biochemicals and proteins, exemplified by mevalonate and GFP, has been improved. Finally, a CRISPRi library, designed to search through the whole genome of E. coli, has been applied. Several novel target genes were identified to be efficient for growth control as well as maintaining protein production. These results demonstrate the possibility of decoupling cell growth from production, and they provide alternative and widely applicable approaches for improving the performance of cell factories. The library approach provides a novel strategy to identify targets for growth switches without prior knowledge, and the method can be applied to a range of other cell factory host cell organisms.