PreprintCited by 399RNA and protein synthesis mechanismsRNA Interference and Gene DeliveryRNA Research and Splicing

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

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Leppek, Kathrin, Byeon, Gun Woo, Kladwang, Wipapat, Wayment-Steele, Hannah K., Kerr, Craig H., Xu, Adele F., Kim, Do Soon, Topkar, Ved V., Choe, Christian, Rothschild, Daphna, Tiu, Gerald C., Wellington-Oguri, Roger, Fujii, Kotaro, Sharma, Eesha, Watkins, Andrew M., Nicol, John J., Romano, Jonathan, Tunguz, Bojan, Participants, Eterna, Barna, Maria, Das, Rhiju·2021·Nature Communications

DOI 10.1101/2021.03.29.437587PMC PMC8940940

Preprint — published as 10.1038/s41467-022-28776-w · Paper page

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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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Martin, M. (2011) · EMBnet.journal · doi:10.14806/ej.17.1.200 · Cited by 33,889
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Polack, F. P., Thomas, S. J., Kitchin, N., Absalon, J., Gurtman, A., Lockhart, S., Perez, J. L., Pérez Marc, G., Moreira, E. D., Zerbini, C., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2034577 · Cited by 14,592
Efficacy and Safety of the mRNA-1273 SARS-CoV-2 Vaccine
Baden, L. R., El Sahly, H. M., Essink, B., Kotloff, K., Frey, S., Novak, R., Diemert, D., Spector, S. A., Rouphael, N., Creech, C. B., et al. (2021) · New England Journal of Medicine · doi:10.1056/nejmoa2035389 · Cited by 10,119
Global quantification of mammalian gene expression control
Schwanhäusser, B., Busse, D., Li, N., Dittmar, G., Schuchhardt, J., Wolf, J., Chen, W., & Selbach, M. (2011) · Nature · doi:10.1038/nature10098 · Cited by 6,566
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ViennaRNA Package 2.0
Lorenz, R., Bernhart, S. H., Höner zu Siederdissen, C., Tafer, H., Flamm, C., Stadler, P. F., & Hofacker, I. L. (2011) · Algorithms for Molecular Biology · doi:10.1186/1748-7188-6-26 · Cited by 5,098
An analysis of 5'-noncoding sequences from 699 vertebrate messenger RNAs
Kozak, M. (1987) · Nucleic Acids Research · doi:10.1093/nar/15.20.8125 · Cited by 5,090
mRNA vaccines — a new era in vaccinology
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Sharp, P. M., & Li, W.-H. (1987) · Nucleic Acids Research · doi:10.1093/nar/15.3.1281 · Cited by 3,992

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Peiter, N., Einert, A., Just, P., Jannasch, F., Najdovska, M., & Rother, M. (2025) · RNA Biology · doi:10.1080/15476286.2025.2472448 · Cited by 2
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Li, Y., Meagher, R. B., & Lin, X. (2025) · PLoS Pathogens · doi:10.1371/journal.ppat.1013091 · Cited by 1
A More Efficient Dynamic Programming Algorithm for Designing a Coding Sequence by Jointly Optimizing Its Structural Stability and Codon Usage
Ju, Y.-R., Cho, L.-S., & Lu, C. L. (2025) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbbio.2025.3596771 · Cited by 1
Innovations in mRNA-Based Nanoparticle for the Treatment of Ocular Disorders: A Comprehensive Review
Sharma, K. K., Durgapal, S., Tyagi, S. J., Varshney, P. K., & Kumar, G. (2025) · Current Pharmaceutical Design · doi:10.2174/0113816128391408250804231522 · Cited by 1
Molecular Genetics and Epigenetics Regulatory Role of miRNAs on Adipogenesis and Intramuscular Fat Development in Beef Cattle: In the Context of Meat Quality
Jilo, D. D., Abebe, B. K., Wang, J., Guo, J., Liu, H., Liang, Q., Li, A., & Zan, L. (2025) · Molecular Biotechnology · doi:10.1007/s12033-025-01514-5 · Cited by 1
mRNA-based immunotherapy platform targeting endometrial cancer
Freyberg, M., Dierks, M., Naß, N., George, C., Geffken, M., Ignatov, A., Kalinski, T., & Ignatova, Z. (2025) · Journal of Translational Medicine · doi:10.1186/s12967-025-07497-w · Cited by 2
SOSHI-seq: a high-throughput screening assay to test the functionality of putative response elements for nuclear hormone receptors
Wu, S., Guyot, R., Zekri, Y., Jiang, W., & Flamant, F. (2025) · Scientific Reports · doi:10.1038/s41598-025-29970-8 · Cited by 1
Scaling Peptide-Barcode Approach for Parallel Evaluation of Protein Expression from Multiple mRNA Variants
Kumano, S., Tanaka, K., Kawakami, S., Yamamoto, M., Akahori, R., & Nojima, A. (2025) · Analytical Chemistry · doi:10.1021/acs.analchem.5c02991 · Cited by 1
Designing 5′ UTR sequences improves the capacity of mRNA therapeutics in preclinical models of aging and obesity
Yoon, S., Cho, H.-G., Lee, J., Ha, S., Lee, S., Lee, Y., Cho, Y., Ha, D., Oh, A., Lee, S., et al. (2026) · Molecular Therapy · doi:10.1016/j.ymthe.2025.12.060 · Cited by 4
A gold nanostars-based electrochemical biosensor for sensitive detection of RNA pseudouridine
Huang, L., Cheng, X., Cao, H., Dong, S., Weng, X., Wang, H., Li, Y., & Wang, F. (2026) · Sensors and Actuators B Chemical · doi:10.1016/j.snb.2026.139450 · Cited by 1
Consequences of mRNA Secondary Structure on Stability against both Hydrolysis and Aggregation: The Role of Electrostatic, π–π Stacking, and Thermal Effects
Jarand, C. W., Deng, Z., Brader, M. L., & Reed, W. F. (2026) · ACS Omega · doi:10.1021/acsomega.5c10266 · Cited by 2
Brain-Inspired Chaotic Graph Backpropagation for Combinatorial Optimization
Tao, P., Aihara, K., & Chen, L. (2026) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2025.3650570 · Cited by 1
Multi-seed searching algorithm for integrated codon optimization of mRNA stability and translational efficiency in vaccine design
Bo, Y., Liu, B., Huang, S., Liu, Y., Deng, L., Zhang, D., & Zhang, J. (2026) · Briefings in Bioinformatics · doi:10.1093/bib/bbag047 · Cited by 1
Developability assessments with four mRNA-LNP vaccine formulations comparing mouse immunogenicity, structural attributes, and stability profiles
Fairlamb, M. S., Kumru, O. S., Hickey, J. M., Elbaz, N. M., Bevernaegie, R., Straeten, A. V., Vandekerckhove, K., Ingham, D. J., Neuenswander, S. A., Douglas, J. T., et al. (2026) · Journal of Pharmaceutical Sciences · doi:10.1016/j.xphs.2026.104199 · Cited by 1
Challenges and opportunities in adapting high-throughput functional assays for in vivo neuroscience
Selmanovic, D., & Selmanovic, D. (2026) · Trends in Neurosciences · doi:10.1016/j.tins.2026.01.008 · Cited by 1
Recent Progress in Sequence Optimization of mRNA Vaccine: Biological Mechanism, Quantitative Metrics, and Computational Model
Wang, Y., Cai, Y., Wu, Z., Zhang, J., Turtle, L. C. W., & Meng, J. (2026) · Bioinformatics and Biology Insights · doi:10.1177/11779322261431255 · Cited by 1
Systematic evaluation of transposon vector elements to establish high-producing stable CHO cell pools achieving > 10 g/L monoclonal antibody titers
Tsachaki, M., Peltret, M., Laplace, T. B., Vaxelaire-Hily, E., Mosbaoui, F., Aillerie, C., Schmid, A., Galea, A., Contarin, F., Duarte, L., et al. (2026) · New Biotechnology · doi:10.1016/j.nbt.2026.03.008 · Cited by 1
Controlling In Vitro mRNA Polyadenylation by Monitoring Poly(A) Polymerase Consumption of ATP
Skok, J., Tiwari, P. M., Seravalli, T. V., Lebar, S., Budihna, A. F., Celjar, A. M., Megušar, P., Povh, M., Mencin, N., Bawage, S. S., et al. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27072928 · Cited by 1
Deep learning model for predicting mRNA half-life based on 3′UTR sequences
Jin, X., Wang, W., Wang, A., Zhang, Y., Mao, Y., & Zhang, D. (2026) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2026.153691 · Cited by 1
VaxLab: integrated platform for rapid multistrategy mRNA vaccine design
Kim, J., Han, Y., Kwon, C. Y., & Chang, H. (2026) · Experimental & Molecular Medicine · doi:10.1038/s12276-026-01637-y · Cited by 1
Structure-driven function of plant lncRNAs: conserved RNA architectures in transcriptional and post-transcriptional regulation
Shen, Y., Dong, Q., Ding, Y., & Zhang, H. (2026) · RNA Biology · doi:10.1080/15476286.2026.2664959 · Cited by 1
A circular RNA vaccine induces durable and cross-protective immunity against Neisseria meningitidis serogroup B in mice
Zhang, Q., Niu, D., Jia, Y., Lu, L., Qu, C., Qu, C., Sun, Z., Li, S., Liu, Z., Lv, J., et al. (2026) · PLoS Pathogens · doi:10.1371/journal.ppat.1013741 · Cited by 1
Metabolic–Epigenetic Crosstalk and Traditional Chinese Medicine in Polycystic Kidney Disease
Cao, X., Zhang, L., & Chen, Y. (2026) · Integrative Medicine in Nephrology and Andrology · doi:10.1097/imna-d-24-00026 · Cited by 1
A 28-nm Fully-Integrated Reconfigurable CMOS Simulated Coherent Ising Machine With Dynamic Pump-Rate Control and Spin Freezing
Fu, Q., Zhou, Y., Cai, Q., An, W., Li, R., Liao, L., & Chen, Z. (2026) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2026.3696716 · Cited by 1
Tunable Lipid Coatings Enable Cytoplasmic siRNA Delivery by DNA Origami
Hendrickx, P. B. M., Rieux, A. D., & Bastings, M. M. C. (2026) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.6c03188 · Cited by 2
Bacterial mRNA Vaccines: Programming Immunity Against Antimicrobial Resistance
Liao, R., Mingxing, L., Yang, F., Xu, L., Zhang, J., Zhang, W., Guan, S., Zhang, Y. M., Luo, P., Cheng, P., et al. (2026) · Drug Development Research · doi:10.1002/ddr.70335 · Cited by 1

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: Leppek, Kathrin
Byeon, Gun Woo
Kladwang, Wipapat
Wayment-Steele, Hannah K.
Kerr, Craig H.
Xu, Adele F.
Kim, Do Soon
Topkar, Ved V.
Choe, Christian
Rothschild, Daphna
Tiu, Gerald C.
Wellington-Oguri, Roger
Fujii, Kotaro
Sharma, Eesha
Watkins, Andrew M.
Romano, Jonathan
Participants, Eterna
Barna, Maria
Das, Rhiju
Venue: Nature Communications
Publisher: openRxiv
Published: 2021-03-30
Volume: 13
Issue: 1
Pages: 1536-1536
ISSN: 2041-1723 (ISSN-L)
DOI: 10.1101/2021.03.29.437587
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: cc-by
creativecommons.org/licenses/by-nc/4.0/ (vor)
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

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

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