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


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.

SUBMITTER: Cao J 

PROVIDER: S-EPMC8260622 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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

Cao Jicong J   Novoa Eva Maria EM   Zhang Zhizhuo Z   Chen William C W WCW   Liu Dianbo D   Choi Gigi C G GCG   Wong Alan S L ASL   Wehrspaun Claudia C   Kellis Manolis M   Lu Timothy K TK  

Nature communications 20210706 1


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.  ...[more]

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