Building variant ribosomes offers opportunities to reveal fundamental principles underlying ribosome biogenesis and to make ribosomes with altered properties. However, cell viability limits mutations that can be made to the ribosome. To address this limitation, the in vitro integrated synthesis, assembly and translation (iSAT) method for ribosome construction from the bottom up was recently developed. Unfortunately, iSAT is complex, costly, and laborious to researchers, partially due to the high cost of reaction buffer containing over 20 components. In this study, we develop iSAT in Escherichia coli BL21Rosetta2 cell lysates, a commonly used bacterial strain, with a cost-effective poly sugar and nucleotide monophosphate-based metabolic scheme. We achieved a 10-fold increase in protein yield over our base case with an evolutionary design of experiments approach, screening 490 reaction conditions to optimize the reaction buffer. The computationally guided, cell-free, high-throughput technology presented here augments the way we approach multicomponent synthetic biology projects and efforts to repurpose ribosomes.
Keywords: evolutionary design of experiments; iSAT; in vitro; machine learning; metabolism; ribosomes; synthetic biology; systems biology.