Activation-induced cytidine deaminase-basedin vivocontinuous evolution system enables rapid protein engineering

Abstract

Directed evolution is a powerful tool to modify the properties of proteins. However, due to multi-round and stage combinations, directed evolution usually requires time- and labor-intensive manual intervention, which limits the efficiency of protein modification to some extent. Therefore,in vivocontinuous evolution system is highly preferred because it can couple the multiple rounds and steps of direction evolution with the host growth cycle, leading to the advantages of effort-saving and accuracy. However, the existing types of this kind of systems can not meet the booming demand. Herein, this paper describes promotedEscherichia coli-assisted continuous evolution (PEACE) that allows forin vivocontinuous evolution of target genes. This system polymorphisms the target gene by activation-induced cytidine deaminase-T7 RNA polymerase (AID-T7 PNAP) fusion protein, then it couples the enzymatic properties of desired variants with the expression of antitoxins to achieve efficient growth-coupled screen using the toxin-antitoxin system (TAS). In this study, T7 RNAP was finally employed for validation of PEACE system, and its specificity to the promoter was successfully altered. These results demonstrated the feasibility and further application potential of PEACE.

CRISPR base editor-based targeted random mutagenesis (BE-TRM) toolbox for directed evolution

“…In synthetic biology, DE is extensively applied to create or improve biological molecules for various applications, including drug discovery, protein engineering, and metabolic engineering. In particular, the applications of DE tools in synthetic biology range from developing enzymes with improved functions to designing novel proteins, biosensors, and genetic circuits ( 51 , 58 ). BE-TRM tools provide efficient means to diversify biomolecules of interest through random mutagenesis, followed by iterative rounds of screening or selection to identify variants with the desired properties.…”

“…The major challenge in the continuous evolution field is linking genotype to phenotype. To tackle this issue, the combined use of automation and machine learning at different stages in DE will be instrumental in reducing time and cost unlike manual operations ( 59 ), as validated in the PEACE system ( 58 ). Indeed, the “design-build-test-learn” cycle operating under in vivo continuous DE conditions automatically manner would enable the evolution of any chosen genetic element.…”