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

Autor: Cao J; Synthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA.; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.; Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA.; Broad Institute of MIT and Harvard, Cambridge, MA, USA., Novoa EM; Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA.; Center for Genomic Regulation (CRG), Barcelona, Spain., Zhang Z; Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA., Chen WCW; Synthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA.; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.; Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA., Liu D; Synthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA.; Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA., Choi GCG; Synthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA.; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.; Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA.; School of Biomedical Sciences, University of Hong Kong, Hong Kong, China., Wong ASL; Synthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA.; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.; Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA.; School of Biomedical Sciences, University of Hong Kong, Hong Kong, China., Wehrspaun C; Synthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA.; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.; Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA., Kellis M; Broad Institute of MIT and Harvard, Cambridge, MA, USA. manoli@mit.edu.; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA. manoli@mit.edu.; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA. manoli@mit.edu., Lu TK; Synthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA. timlu@mit.edu.; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. timlu@mit.edu.; Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA. timlu@mit.edu.; Broad Institute of MIT and Harvard, Cambridge, MA, USA. timlu@mit.edu.; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA. timlu@mit.edu.
Jazyk: angličtina
Zdroj: Nature communications [Nat Commun] 2021 Jul 06; Vol. 12 (1), pp. 4138. Date of Electronic Publication: 2021 Jul 06.
DOI: 10.1038/s41467-021-24436-7
Abstrakt: 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.
Databáze: MEDLINE
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