(360b) Acceleration of Microbial Metabolic Engineering with Crispri
AIChE Annual Meeting
2016
2016 AIChE Annual Meeting
Food, Pharmaceutical & Bioengineering Division
Industrial Applications of Metabolic Engineering
Tuesday, November 15, 2016 - 12:48pm to 1:06pm
The field of metabolic engineering is entering a new era in which readily addressable synthetic transcription factors like RNA-guided dCas9 are opening new possibilities for dynamic regulation and for rapid assessment of multiplexed genetic interventions to alter the metabolic landscape in both workhorse and previously intractable microbes. Toward this end, our group has focused on several applications of CRISPRi-enabled metabolic engineering. Previously, we developed a modular assembly method for traditional restriction-ligation cloning of type II-A CRISPR array libraries for multiplex, combinatorial dCas9-mediated transcriptional repression. Importantly, we demonstrated for the first time that dCas9 can be utilized for metabolic engineering in E. coli, leading to enhancement of flavonoid titers through simultaneous repression of an endogenous transcription factor and several central carbon enzymes, including partial downregulation of a synthetic lethal pair. Furthermore, we showed that this system could be utilized to generate complex phenotypes, and we also demonstrated that a single plasmid can be used to attenuate virulence genes in disparate E. coli lineages by repressing capsular polysaccharide secretion in both probiotic strain Nissle 1917 and pathogenic strain K5. Expanding upon this work, we have recently developed a novel, streamlined cloning strategy to assemble natural type II-A CRISPR arrays, enabling simultaneous repression of combinations of genetic targets in only a few days. We showcase this method by improving production of a panel of natural products through repression of several novel knockdown targets. Comparison of CRISPRi strains with analogous deletion strains shows that CRISPRi can lead to production improvements comparable to gene deletions, potentially obviating the role of cumbersome combinatorial gene deletions during hypothesis testing stages early in the strain development pipeline.