Model-driven DBTL cycle acceleration with broad-host-range bacterial CRISPRa/i circuits

Abstract

CRISPR-Cas gene regulatory tools have revolutionized biological network programming. Recently, we developed CRISPR gene activation (CRISPRa) tools that demonstrate broad applicability across various bacteria. With thorough characterization of bacterial CRISPRa, we found that the design rules for effective CRISPRa are stringent and highly context-dependent. Thus, we developed numerous strategies to overcome existing limitations — including DNA context engineering, utilization of engineered proteins to bypass target sites requirements, and characterization of multiple bacterial CRISPRa systems for alternative design rules. Implementation of CRISPRa tools in chemical bioproduction enabled synthesis of p-aminocinnamic acid, a precursor to various functional polymer materials, which was previously difficult to synthesize through conventional routes. In combination with CRISPR gene interference (CRISPRi), we further explore the capability of a combined CRISPRa/i platform to regulate expression of both foreign genes and native genes intricately involved in bacterial metabolism. Since programmability of CRISPRa/i relies on guide RNA sequence, we found that multiple guide RNAs could be implemented simultaneously to regulate multiple genes in the same system. Engineering at the RNA level could also provide tunable regulation for each gene target. Furthermore, when combined with genome-scale metabolic models, this system accelerates the Design-Build-Test-Learn (DBTL) process for microbial strain optimization, bypassing stepwise genetic reconstruction through the use of trans-acting CRISPRa/i circuits. The resulting constructs can be comprehensively investigated using a multi-omics platform, providing detailed information to improve subsequent DBTL cycles. By coupling programmable and tunable gene regulatory tools with large metabolic models informed by omics data, our platform establishes a foundation for non-canonical microbial strain engineering that benefits diverse disciplines from industrial biotechnology to therapeutic discovery.