Combinatorial optimization of mRNA structure, stability, and translation for RNA-based therapeutics

Kathrin Leppek; Gun Woo Byeon; Wipapat Kladwang; Hannah K. Wayment-Steele; Craig H. Kerr; Adele Xu; Do Soon Kim; Ved V. Topkar; Christian A. Choe; Daphna Rothschild; Gerald C. Tiu; Roger Wellington-Oguri; Kotaro Fujii; Eesha Sharma; Andrew M. Watkins; John J. Nicol; Jonathan Romano; Bojan Tunguz; Fernando Diaz; Hui Cai; Pengbo Guo; Jiewei Wu; Fanyu Meng; Shuai Shi; Eterna Participants; Philip R. Dormitzer; Alicia Solórzano; Maria Barna; Rhiju Das

doi:10.1038/s41467-022-28776-w

Molecular BiologyNature CommunicationsMar 22, 2022

Peer-reviewed journal article

Combinatorial optimization of mRNA structure, stability, and translation for RNA-based therapeutics

Kathrin Leppek iD, Gun Woo Byeon iD, Wipapat Kladwang iD, Hannah K. Wayment-Steele iD, Craig H. Kerr iD, Adele Xu iD, Do Soon Kim iD, Ved V. Topkar iD, Christian A. Choe iD, Daphna Rothschild iD, Gerald C. Tiu iD, Roger Wellington-Oguri iD, Kotaro Fujii iD, Eesha Sharma iD, Andrew M. Watkins iD, John J. Nicol, Jonathan Romano iD, Bojan Tunguz, Fernando Diaz, Hui Cai iD, Pengbo Guo iD, Jiewei Wu iD, Fanyu Meng iD, Shuai Shi, Eterna Participants iD, , Rhiju Das iD

Abstract

Therapeutic mRNAs and vaccines are being developed for a broad range of human diseases, including COVID-19. However, their optimization is hindered by mRNA instability and inefficient protein expression. Here, we describe design principles that overcome these barriers. We develop a new RNA sequencing-based platform called PERSIST-seq to systematically delineate in-cell mRNA stability, ribosome load, as well as in-solution stability of a library of diverse mRNAs. We find that, surprisingly, in-cell stability is a greater driver of protein output than high ribosome load. We further introduce a method called In-line-seq, applied to thousands of diverse RNAs, that reveals sequence and structure-based rules for mitigating hydrolytic degradation. Our findings show that "superfolder" mRNAs can be designed to improve both stability and expression that are further enhanced through pseudouridine nucleoside modification. Together, our study demonstrates simultaneous improvement of mRNA stability and protein expression and provides a computational-experimental platform for the enhancement of mRNA medicines.

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