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 F. Xu; Do Soon Kim; Ved V. Topkar; Christian 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

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 F. Xu, Do Soon Kim, Ved V. Topkar, Christian 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 CaiPengbo Guo, Jiewei Wu, Fanyu Meng, Shuai Shi, Eterna Participants, Philip R. Dormitzer, Alicia Solórzano, Maria Barna, Rhiju Das

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109 Scopus citations

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 an 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 highly structured “superfolder” mRNAs can be designed to improve both stability and expression with further enhancement 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.

Original language	English
Article number	1536
Journal	Nature Communications
Volume	13
Issue number	1
DOIs	https://doi.org/10.1038/s41467-022-28776-w
State	Published - Dec 2022
Externally published	Yes

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Leppek, K., Byeon, G. W., Kladwang, W., Wayment-Steele, H. K., Kerr, C. H., Xu, A. F., Kim, D. S., Topkar, V. V., Choe, C., Rothschild, D., Tiu, G. C., Wellington-Oguri, R., Fujii, K., Sharma, E., Watkins, A. M., Nicol, J. J., Romano, J., Tunguz, B., Diaz, F., ... Das, R. (2022). Combinatorial optimization of mRNA structure, stability, and translation for RNA-based therapeutics. Nature Communications, 13(1), Article 1536. https://doi.org/10.1038/s41467-022-28776-w

@article{c1d488b969cc41bba3321e97235e9446,

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

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 an 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 highly structured “superfolder” mRNAs can be designed to improve both stability and expression with further enhancement 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.",

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

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s).",

year = "2022",

month = dec,

doi = "10.1038/s41467-022-28776-w",

language = "English",

volume = "13",

journal = "Nature Communications",

issn = "2041-1723",

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Leppek, K, Byeon, GW, Kladwang, W, Wayment-Steele, HK, Kerr, CH, Xu, AF, Kim, DS, Topkar, VV, Choe, C, Rothschild, D, Tiu, GC, Wellington-Oguri, R, Fujii, K, Sharma, E, Watkins, AM, Nicol, JJ, Romano, J, Tunguz, B, Diaz, F, Cai, H, Guo, P, Wu, J, Meng, F, Shi, S, Participants, E, Dormitzer, PR, Solórzano, A, Barna, M & Das, R 2022, 'Combinatorial optimization of mRNA structure, stability, and translation for RNA-based therapeutics', Nature Communications, vol. 13, no. 1, 1536. https://doi.org/10.1038/s41467-022-28776-w

TY - JOUR

T1 - Combinatorial optimization of mRNA structure, stability, and translation for RNA-based therapeutics

AU - Leppek, Kathrin

AU - Byeon, Gun Woo

AU - Kladwang, Wipapat

AU - Wayment-Steele, Hannah K.

AU - Kerr, Craig H.

AU - Xu, Adele F.

AU - Kim, Do Soon

AU - Topkar, Ved V.

AU - Choe, Christian

AU - Rothschild, Daphna

AU - Tiu, Gerald C.

AU - Wellington-Oguri, Roger

AU - Fujii, Kotaro

AU - Sharma, Eesha

AU - Watkins, Andrew M.

AU - Nicol, John J.

AU - Romano, Jonathan

AU - Tunguz, Bojan

AU - Diaz, Fernando

AU - Cai, Hui

AU - Guo, Pengbo

AU - Wu, Jiewei

AU - Meng, Fanyu

AU - Shi, Shuai

AU - Participants, Eterna

AU - Dormitzer, Philip R.

AU - Solórzano, Alicia

AU - Barna, Maria

AU - Das, Rhiju

PY - 2022/12

Y1 - 2022/12

N2 - 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 an 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 highly structured “superfolder” mRNAs can be designed to improve both stability and expression with further enhancement 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.

AB - 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 an 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 highly structured “superfolder” mRNAs can be designed to improve both stability and expression with further enhancement 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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U2 - 10.1038/s41467-022-28776-w

DO - 10.1038/s41467-022-28776-w

M3 - Article

C2 - 35318324

AN - SCOPUS:85126763405

SN - 2041-1723

VL - 13

JO - Nature Communications

JF - Nature Communications

IS - 1

M1 - 1536

ER -

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

Abstract

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