Author
Listed:
- Jicong Cao
(Massachusetts Institute of Technology
Massachusetts Institute of Technology
Massachusetts Institute of Technology
Broad Institute of MIT and Harvard)
- Eva Maria Novoa
(Broad Institute of MIT and Harvard
Massachusetts Institute of Technology
Massachusetts Institute of Technology
Center for Genomic Regulation (CRG))
- Zhizhuo Zhang
(Broad Institute of MIT and Harvard
Massachusetts Institute of Technology
Massachusetts Institute of Technology)
- William C. W. Chen
(Massachusetts Institute of Technology
Massachusetts Institute of Technology
Massachusetts Institute of Technology)
- Dianbo Liu
(Massachusetts Institute of Technology
Broad Institute of MIT and Harvard
Massachusetts Institute of Technology)
- Gigi C. G. Choi
(Massachusetts Institute of Technology
Massachusetts Institute of Technology
Massachusetts Institute of Technology
University of Hong Kong)
- Alan S. L. Wong
(Massachusetts Institute of Technology
Massachusetts Institute of Technology
Massachusetts Institute of Technology
University of Hong Kong)
- Claudia Wehrspaun
(Massachusetts Institute of Technology
Massachusetts Institute of Technology
Massachusetts Institute of Technology)
- Manolis Kellis
(Broad Institute of MIT and Harvard
Massachusetts Institute of Technology
Massachusetts Institute of Technology)
- Timothy K. Lu
(Massachusetts Institute of Technology
Massachusetts Institute of Technology
Massachusetts Institute of Technology
Broad Institute of MIT and Harvard)
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.
Suggested Citation
Jicong Cao & Eva Maria Novoa & Zhizhuo Zhang & William C. W. Chen & Dianbo Liu & Gigi C. G. Choi & Alan S. L. Wong & Claudia Wehrspaun & Manolis Kellis & Timothy K. Lu, 2021.
"High-throughput 5′ UTR engineering for enhanced protein production in non-viral gene therapies,"
Nature Communications, Nature, vol. 12(1), pages 1-10, December.
Handle:
RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-24436-7
DOI: 10.1038/s41467-021-24436-7
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