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High-throughput 5′ UTR engineering for enhanced protein production in non-viral gene therapies

Jicong Cao, Eva Maria Novoa, Zhizhuo Zhang, William C. W. Chen, Dianbo Liu, Gigi C.G. Choi, Alan S.L. Wong, Claudia C. Wehrspaun, Manolis Kellis, Timothy K. Lu

2021Nature Communications158 citationsDOIOpen Access PDF

Abstract

Despite significant clinical progress in cell and gene therapies, maximizing protein expression in order to enhance potency remains a major technical challenge. Here, we develop a high-throughput strategy to design, screen, and optimize 5' UTRs that enhance protein expression from a strong human cytomegalovirus (CMV) promoter. We first identify naturally occurring 5' UTRs with high translation efficiencies and use this information with in silico genetic algorithms to generate synthetic 5' UTRs. A total of ~12,000 5' UTRs are then screened using a recombinase-mediated integration strategy that greatly enhances the sensitivity of high-throughput screens by eliminating copy number and position effects that limit lentiviral approaches. Using this approach, we identify three synthetic 5' UTRs that outperform commonly used non-viral gene therapy plasmids in expressing protein payloads. In summary, we demonstrate that high-throughput screening of 5' UTR libraries with recombinase-mediated integration can identify genetic elements that enhance protein expression, which should have numerous applications for engineered cell and gene therapies.

Topics & Concepts

Computational biologyIn silicoUntranslated regionGeneRecombinaseBiologySynthetic biologyThree prime untranslated regionGeneticsMessenger RNARecombinationCRISPR and Genetic EngineeringVirus-based gene therapy researchViral Infectious Diseases and Gene Expression in Insects
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