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Combinatorial optimization of mRNA structure, stability, and translation for RNA-based therapeutics
Open accessPreprint — published as 10.1038/s41467-022-28776-w · Paper page
Abstract
SUMMARY: 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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Kim, H., Cordero, P., Das, R., & Yoon, S. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt501 · Cited by 31
Self-citationLeveraging mRNAs sequences to express SARS-CoV-2 antigens in vivoPreprint
Zeng, C., Hou, X., Yan, J., Zhang, C., Li, W., Zhao, W., Du, S., & Dong, Y. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.04.01.019877 · Cited by 29
Palusa, S. G., Ndaluka, C., Bowen, R. A., Wilusz, C. J., & Wilusz, J. (2012) · PLoS ONE · doi:10.1371/journal.pone.0033561 · Cited by 26
Updates to the RNA mapping database (RMDB), version 2
Yesselman, J. D., Tian, S., Liu, X., Shi, L., Li, J. B., & Das, R. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx873 · Cited by 23
Self-citationMie, M., Shimizu, S., Takahashi, F., & Kobatake, E. (2008) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2008.05.173 · Cited by 11
LinearDesign: Efficient Algorithms for Optimized mRNA Sequence DesignPreprint
Zhang, H., Zhang, L., Li, Z., Liu, K., Liu, B., Mathews, D. H., & Huang, L. (2020) · arXiv (Cornell University) · Cited by 8
Wang, H., Yu, Y., Liu, T., Pan, Y., Yan, S., & Wang, Y. (2015) · SpringerPlus · doi:10.1186/s40064-015-0973-z · Cited by 7
A mRNA-LNP vaccine against Dengue Virus elicits robust, serotype-specific immunity
Wollner, C. J., Richner, M., Hassert, M. A., Pinto, A. K., Brien, J. D., & Richner, J. M. (2021) · doi:10.1101/2021.01.05.425517 · Cited by 6
Flagged first, then by citations
7 of the 117 references couldn’t be matched to a known paper.
Research works printed but not linked: 3
- 10.1101/2020.08.22.262931 · DOI · Paper page
- 10.1101/2020.03.24.006486 · DOI
- 10.1101/2020.06.29.178343 · DOI
Cited by
Sorted by citations
mRNA-based therapeutics: powerful and versatile tools to combat diseases
Qin, S., Tang, X., Chen, Y., Chen, K., Fan, N., Xiao, W., Zheng, Q., Li, G., Teng, Y., Wu, M., et al. (2022) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-022-01007-w · Cited by 852
Mendes, B. B., Conniot, J., Avital, A., Yao, D., Jiang, X., Zhou, X., Sharf-Pauker, N., Xiao, Y., Adir, O., Liang, H., et al. (2022) · Nature Reviews Methods Primers · doi:10.1038/s43586-022-00104-y · Cited by 719
The landscape of mRNA nanomedicine
Huang, X., Kong, N., Zhang, X., Cao, Y., Langer, R., & Tao, W. (2022) · Nature Medicine · doi:10.1038/s41591-022-02061-1 · Cited by 511
Algorithm for optimized mRNA design improves stability and immunogenicity
Zhang, H., Zhang, L., Lin, A., Xu, C., Li, Z., Liu, K., Liu, B., Ma, X., Zhao, F., Jiang, H., et al. (2023) · Nature · doi:10.1038/s41586-023-06127-z · Cited by 531
mRNA vaccines for infectious diseases — advances, challenges and opportunities
Pardi, N., & Krammer, F. (2024) · Nature Reviews Drug Discovery · doi:10.1038/s41573-024-01042-y · Cited by 252
Metadata
- Authors
- 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., Participants, E., Barna, M., & Das, R.
- Affiliations
- Stanford University (US)
- Eterna Massive Open Laboratory (US)
- Nvidia (United States) (US)
- Corresponding author
- Barna, Maria
- Das, Rhiju
- ORCID
- Venue
- Nature Communications
- Publisher
- openRxiv
- Published
- 2021-03-30
- Volume
- 13
- Issue
- 1
- Pages
- 1536-1536
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC8940940
- OpenAlex
- W4220991830
- Cited by
- 399
- References
- 117
- Citations by year
- 2026: 88 · 2025: 127 · 2024: 99 · 2023: 53 · 2022: 23 · 2021: 8
- FWCI
- 24.66
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nature Communications (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (submittedVersion, cc-by-nc)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- National Science Foundation
- Damon Runyon Cancer Research Foundation (DRG-2237-15)
- Pfizer
- Oregon State University
- Baidu
- National Institutes of Health
- University of California, San Francisco
- Stanford Bio-X
- Chemistry, Engineering and Medicine for Human Health, Stanford University
- Canadian Institutes of Health Research
- National Cancer Institute (R21CA219847)
- National Institute of General Medical Sciences (R35GM122579)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (F30HD100123, R01HD086634)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Interference and Gene Delivery
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Keywords
- mRNA stability, mRNA structure, mRNA vaccines, RNA therapeutics, protein expression, hydrolytic degradation, pseudouridine modification, mRNA design, COVID-19 vaccines
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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