Theoretical basis for stabilizing messenger RNA through secondary structure design
Open accessPreprint — published as 10.1093/nar/gkab764 · Paper page
Abstract
RNA hydrolysis presents problems in manufacturing, long-term storage, world-wide delivery, and in vivo stability of messenger RNA (mRNA)-based vaccines and therapeutics. A largely unexplored strategy to reduce mRNA hydrolysis is to redesign RNAs to form double-stranded regions, which are protected from in-line cleavage and enzymatic degradation, while coding for the same proteins. The amount of stabilization that this strategy can deliver and the most effective algorithmic approach to achieve stabilization remain poorly understood. Here, we present simple calculations for estimating RNA stability against hydrolysis, and a model that links the average unpaired probability of an mRNA, or AUP, to its overall hydrolysis rate. To characterize the stabilization achievable through structure design, we compare AUP optimization by conventional mRNA design methods to results from more computationally sophisticated algorithms and crowdsourcing through the OpenVaccine challenge on the Eterna platform. These computational tests were carried out on both model mRNAs and COVID-19 mRNA vaccine candidates. We find that rational design on Eterna and the more sophisticated algorithms lead to constructs with low AUP, which we term ‘superfolder’ mRNAs. These designs exhibit wide diversity of sequence and structure features that may be desirable for translation, biophysical size, and immunogenicity, and their folding is robust to temperature, choice of flanking untranslated regions, and changes in target protein sequence, as illustrated by rapid redesign of superfolder mRNAs for B.1.351, P.1, and B.1.1.7 variants of the prefusion-stabilized SARS-CoV-2 spike protein. Increases in in vitro mRNA half-life by at least two-fold appear immediately achievable. Significance statement: Messenger RNA (mRNA) medicines that encode and promote translation of a target protein have shown promising use as vaccines in the current SARS-CoV-2 pandemic as well as infectious diseases due to their speed of design and manufacturing. However, these molecules are intrinsically prone to hydrolysis, leading to poor stability in aqueous buffer and major challenges in distribution. Here, we present a principled biophysical model for predicting RNA degradation, and demonstrate that the stability of any mRNA can be increased at least two-fold over conventional design techniques. Furthermore, the predicted stabilization is robust to post-design modifications. This conceptual framework and accompanying algorithm can be immediately deployed to guide re-design of mRNA vaccines and therapeutics to increase in vitro stability.
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mRNA secondary structure design can be modified to improve mRNA stability against endonuclease cleavage and chemical degradation.
“Furthermore, mRNA secondary structure design can be modified to improve mRNA stability against endonuclease cleavage and chemical degradation (Wayment-Steele et al. 2021).”
From Modifications of mRNA vaccine structural elements for improving mRNA stability and translation efficiency (2022) · cites this paper as Wayment-Steele et al. 2021
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- [1]Wu F., Zhao S., Yu B., Chen Y. M., Wang W., Song Z. G., Hu Y., Tao Z. W., Tian J. H., Pei Y. Y., Yuan M. L., Zhang Y. L., Dai F. H., Liu Y., Wang Q. M., Zheng J. J., Xu L., Holmes E. C., and Zhang Y. Z.. 2020. A New Coronavirus Associated With Human Respiratory Disease in China. Nature 579(7798): 265– 269. 32015508 PMC7094943
- [2]Chauhan G., Madou M. J., Kalra S., Chopra V., Ghosh D., and Martinez-Chapa S. O.. Nanotechnology for COVID-19: Therapeutics and Vaccine Research. ACS Nano. 32571007
- [3]McKay P. F., Hu K., Blakney A. K., Samnuan K., Brown J. C., Penn R., Zhou J., Bouton C. R., Rogers P., Polra K., Lin P. J. C., Barbosa C., Tam Y. K., Barclay W. S., and Shattock R. J.. 2020. Self-amplifying RNA SARS-CoV-2 lipid nanoparticle vaccine candidate induces high neutralizing antibody titers in mice. Nature Communications 11(1): 3523. PMC7347890 32647131
- [4]Kaczmarek J. C., Kowalski P. S., and Anderson D. G.. 2017. Advances in the delivery of RNA therapeutics: from concept to clinical reality. Genome Medicine 9(1): 60. 28655327 PMC5485616
- [5]Erasmus J. H., and Fuller D. H.. 2020. Preparing for Pandemics: RNA Vaccines at the Forefront. Molecular Therapy 28(7): 1559– 1560. 32579882 PMC7309706
- [7]Zhao P., Hou X., Yan J., Du S., Xue Y., Li W., Xiang G., and Dong Y.. 2020. Long-term storage of lipid-like nanoparticles for mRNA delivery. Bioactive Materials 5(2): 358– 363. 32206737 PMC7078456
- [9]Zhang N.-N., Li X.-F., Deng Y.-Q., Zhao H., Huang Y.-J., Yang G., Huang W.-J., Gao P., Zhou C., Zhang R.-R., Guo Y., Sun S.-H., Fan H., Zu S.-L., Chen Q., He Q., Cao T.-S., Huang X.-Y., Qiu H.-Y., Nie J.-H., Jiang Y., Yan H.-Y., Ye Q., Zhong X., Xue X.-L., Zha Z.-Y., Zhou D., Yang X., Wang Y.-C., Ying B., and Qin C.-F.. 2020. A Thermostable mRNA Vaccine against COVID-19. Cell. PMC7377714 32795413
- [10]Markham R., and Smith J. D.. 1952. The structure of ribonucleic acids. 1. Cyclic nucleotides produced by ribonuclease and by alkaline hydrolysis. Biochem J 52(4): 552– 557. 13018277 PMC1198056
- [11]Oivanen M., Kuusela S., and Lönnberg H.. 1998. Kinetics and Mechanisms for the Cleavage and Isomerization of the Phosphodiester Bonds of RNA by Brønsted Acids and Bases. Chemical Reviews 98(3): 961– 990. 11848921
- [12]Cataldo F. 2006. Ozone Degradation of Biological Macromolecules: Proteins, Hemoglobin, RNA, and DNA. Ozone: Science & Engineering 28(5): 317– 328. Journal Article.
- [13]Baldridge K. C., Zavala J., Surratt J., Sexton K. G., and Contreras L. M.. 2015. Cellular RNA is chemically modified by exposure to air pollution mixtures. Inhalation Toxicology 27(1): 74– 82. Journal Article. 25600141
- [14]Li Y., and Breaker R. R.. 1999. Kinetics of RNA Degradation by Specific Base Catalysis of Transesterification Involving the 2’-Hydroxyl Group. J. Amer. Chem. Soc. 121(23): 5364– 5372. Journal Article.
- [15]Martick M., and Scott W. G.. 2006. Tertiary Contacts Distant From the Active Site Prime a Ribozyme for Catalysis. Cell 126(2): 309– 320. 16859740 PMC4447102
- [16]Kaukinen U., Lyytikäinen S., Mikkola S., and Lönnberg H.. 2002. The Reactivity of Phosphodiester Bonds Within Linear Single-Stranded Oligoribonucleotides Is Strongly Dependent on the Base Sequence. Nucleic Acids Res. 30(2). PMC99829 11788709
- [17]Mchedlov-Petrossyan N. O., Vodolazkaya N. A., Yakubovskaya A. G., Grigorovich A. V., Alekseeva V. I., and Savvina L. P.. 2007. A novel probe for determination of electrical surface potential of surfactant micelles: N,N’-di-n-octadecylrhodamine. Journal of Physical Organic Chemistry 20(5): 332– 344.
- [18]Clear K. J., Virga K., Gray L., and Smith B. D.. 2016. Using Membrane Composition to Fine-Tune the P Ka of an Optical Liposome pH Sensor. J. Mater. Chem. C. Mater. 4(14). PMC4830428 27087967
- [19]Geall A. J., Verma A., Otten G. R., Shaw C. A., Hekele A., Banerjee K., Cu Y., Beard C. W., Brito L. A., Krucker T., O’Hagan D. T., Singh M., Mason P. W., Valiante N. M., Dormitzer P. R., Barnett S. W., Rappuoli R., Ulmer J. B., and Mandl C. W.. 2012. Nonviral delivery of self-amplifying RNA vaccines. Proc. Natl. Acad. Sci. 109(36). PMC3437863 22908294
- [20]Brunelle J. L., and Green R.. 2013. Chapter Five - In Vitro Transcription from Plasmid or PCR-amplified DNA. Methods in Enzymology. Lorsch J., editor. Academic Press, pp. 101– 114. 24034317
- [21]Kisters K., Niedner W., Fafera I., and Zidek W.. 1990. Plasma and intracellular Mg2+ concentrations in pre-eclampsia. Journal of Hypertension 8(4). 2160486
- [22]Mikkola S., Kaukinen U., and Lönnberg H.. 2001. The Effect of Secondary Structure on Cleavage of the Phosphodiester Bonds of RNA. Cell Biochem. Biophys. 34(1). 11394443
- [23]Regulski E. E., and Breaker R. R.. 2008. In-line Probing Analysis of Riboswitches. Methods Mol. Biol. 419. 18369975
- [24]Lorenz R., Bernhart S. H., Honer Zu Siederdissen C., Tafer H., Flamm C., Stadler P. F., and Hofacker I. L.. 2011. ViennaRNA Package 2.0. Algorithms Mol Biol 6: 26. 22115189 PMC3319429
- [25]Zadeh J. N., Steenberg C. D., Bois J. S., Wolfe B. R., Pierce M. B., Khan A. R., Dirks R. M., and Pierce N. A.. 2011. NUPACK: Analysis and design of nucleic acid systems. J Comput Chem 32(1): 170– 173. 20645303
- [26]Reuter J. S., and Mathews D. H.. 2010. RNAstructure: software for RNA secondary structure prediction and analysis. BMC Bioinformatics 11: 129. 20230624 PMC2984261
- [27]Do C. B., Woods D. A., and Batzoglou S.. 2006. CONTRAfold: RNA secondary structure prediction without physics-based models. Bioinformatics 22(14): e90– 98. 16873527
- [28]Terai G., Kamegai S., and Asai K.. 2016. CDSfold: An Algorithm for Designing a Protein-Coding Sequence With the Most Stable Secondary Structure. Bioinformatics 32(6). 26589279
- [29]Zhang H., Zhang L., Li Z., Liu K., Liu B., Mathews D. H., and Huang L.. 2020. LinearDesign: Efficient Algorithms for Optimized mRNA Sequence Design. Arxiv.
- [30]Cohen B., and Skiena S.. 2003. Natural Selection and Algorithmic Design of mRNA. Journal of Computational Biology 10(3–4). 12935336
- [31]Chen S.-J. 2008. RNA folding: conformational statistics, folding kinetics, and ion electrostatics. Annual review of biophysics 37: 197– 214. PMC2473866 18573079
- [32]Zhao X., Li G., and Liang S.. 2013. Several Affinity Tags Commonly Used in Chromatographic Purification. J Anal Methods Chem 2013. PMC3893739 24490106
- [33]Sharp P. M., and Li W. H.. 1987. The codon Adaptation Index--a measure of directional synonymous codon usage bias, and its potential applications. Nucleic Acids Res 15(3): 1281– 1295. 3547335 PMC340524
- [34]Wayment-Steele H. K., Kladwang W., Participants E., and Das R.. 2020. RNA secondary structure packages ranked and improved by high-throughput experiments. bioRxiv. PMC9839360 36192461
- [35]Mauger D. M., Cabral B. J., Presnyak V., Su S. V., Reid D. W., Goodman B., Link K., Khatwani N., Reynders J., Moore M. J., and McFadyen I. J.. 2019. mRNA structure regulates protein expression through changes in functional half-life. Proc Natl Acad Sci U S A 116(48): 24075– 24083. 31712433 PMC6883848
- [36]Lee J., Kladwang W., Lee M., Cantu D., Azizyan M., Kim H., Limpaecher A., Yoon S., Treuille A., and Das R.. 2014. RNA design rules from a massive open laboratory. Proc Natl Acad Sci U S A 111(6): 2122– 2127. 24469816 PMC3926058
- [37]Kozak M. 1990. Downstream secondary structure facilitates recognition of initiator codons by eukaryotic ribosomes. Proceedings of the National Academy of Sciences 87(21): 8301. PMC54943 2236042
- [38]Mustoe A. M., Corley M., Laederach A., and Weeks K. M.. 2018. Messenger RNA Structure Regulates Translation Initiation: A Mechanism Exploited from Bacteria to Humans. Biochemistry 57(26): 3537– 3539. 29894169 PMC6398326
- [39]Hur S. 2019. Double-Stranded RNA Sensors and Modulators in Innate Immunity. Annu Rev Immunol 37: 349– 375. 30673536 PMC7136661
- [40]Yoffe A. M., Prinsen P., Gopal A., Knobler C. M., Gelbart W. M., and Ben-Shaul A.. 2008. Predicting the sizes of large RNA molecules. Proc Natl Acad Sci U S A 105(42): 16153– 16158. 18845685 PMC2570976
- [41]Gopal A., Egecioglu D. E., Yoffe A. M., Ben-Shaul A., Rao A. L. N., Knobler C. M., and Gelbart W. M.. 2014. Viral RNAs Are Unusually Compact. PLoS One 9(9): e105875. 25188030 PMC4154850
- [42]Karikó K., Ni H., Capodici J., Lamphier M., and Weissman D.. 2004. mRNA Is an Endogenous Ligand for Toll-like Receptor 3. J. Biol. Chem. 279(13): 12542– 12550. 14729660
- [43]Wrapp D., Wang N., Corbett K. S., Goldsmith J. A., Hsieh C.-L., Abiona O., Graham B. S., and McLellan J. S.. 2020. Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation. Science 367(6483): 1260. 32075877 PMC7164637
- [44]Wu K., Werner A. P., Moliva J. I., Koch M., Choi A., Stewart-Jones G. B. E., Bennett H., Boyoglu-Barnum S., Shi W., Graham B. S., Carfi A., Corbett K. S., Seder R. A., and Edwards D. K.. 2021. mRNA-1273 vaccine induces neutralizing antibodies against spike mutants from global SARS-CoV-2 variants. bioRxiv:2021.2001.2025.427948.
- [47]Tegally H., Wilkinson E., Giovanetti M., Iranzadeh A., Fonseca V., Giandhari J., Doolabh D., Pillay S., San E. J., Msomi N., Mlisana K., von Gottberg A., Walaza S., Allam M., Ismail A., Mohale T., Glass A. J., Engelbrecht S., Van Zyl G., Preiser W., Petruccione F., Sigal A., Hardie D., Marais G., Hsiao M., Korsman S., Davies M.-A., Tyers L., Mudau I., York D., Maslo C., Goedhals D., Abrahams S., Laguda-Akingba O., Alisoltani-Dehkordi A., Godzik A., Wibmer C. K., Sewell B. T., Lourenço J., Alcantara L. C. J., Pond S. L. K., Weaver S., Martin D., Lessells R. J., Bhiman J. N., Williamson C., and de Oliveira T.. 2020. Emergence and rapid spread of a new severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) lineage with multiple spike mutations in South Africa. medRxiv:2020.2012.2021.20248640.
- [48]Leppek K., Fujii K., Quade N., Susanto T. T., Boehringer D., Lenarčič T., Xue S., Genuth N. R., Ban N., and Barna M.. 2020. Gene- and Species-Specific Hox mRNA Translation by Ribosome Expansion Segments. Molecular Cell 80(6): 980– 995.e913. 33202249 PMC7769145
- [49]Ahmed S. F., Quadeer A. A., and McKay M. R.. 2020. Preliminary Identification of Potential Vaccine Targets for the COVID-19 Coronavirus (SARS-CoV-2) Based on SARS-CoV Immunological Studies. Viruses 12(3). PMC7150947 32106567
- [50]Qamar M. T. u., Rehman A., Ashfaq U. A., Awan M. Q., Fatima I., Shahid F., and Chen L.-L.. 2020. Designing of a next generation multiepitope based vaccine (MEV) against SARS-COV-2: Immunoinformatics and in silico approaches. bioRxiv. PMC7755200 33351863
- [51]Prachar M., Justesen S., Steen-Jensen D. B., Thorgrimsen S., Jurgons E., Winther O., and Bagger F. O.. 2020. COVID-19 Vaccine Candidates: Prediction and Validation of 174 SARS-CoV-2 Epitopes. bioRxiv. PMC7686376 33235258
- [52]Wrapp D., Wang N., Corbett K. S., Goldsmith J. A., Hsieh C.-L., Abiona O., Graham B. S., and McLellan J. S.. 2020. Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation. Science 367(6483): 1260– 1263. 32075877 PMC7164637
- [53]Liu H., Wu R., Yuan L., Tian G., Huang X., Wen Y., Ma X., Huang Y., Yan Q., Zhao Q., Cao S., and Wen X.. 2017. Introducing a Cleavable Signal Peptide Enhances the Packaging Efficiency of Lentiviral Vectors Pseudotyped With Japanese Encephalitis Virus Envelope Proteins. Virus research 229: 9– 16. 27993624
- [54]Kocsis L., and Szepesvári C.. 2006. Bandit Based Monte-Carlo Planning. Springer Berlin Heidelberg, Berlin, Heidelberg. 282– 293.
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- Authors
- Wayment-Steele, H. K., Kim, D. S., Choe, C. A., Nicol, J. J., Wellington-Oguri, R., Watkins, A. M., Sperberg, R. A. P., Huang, P.-S., Participants, E., & Das, R.
- Affiliations
- Eterna Massive Open Laboratory (US)
- Northwestern University (US)
- Stanford University (US)
- Corresponding author
- Das, Rhiju
- ORCID
- Venue
- Nucleic Acids Research
- Publisher
- openRxiv
- Published
- 2020-08-24
- Volume
- 49
- Issue
- 18
- Pages
- 10604-10617
- ISSN
- 0305-1048 (ISSN-L)
- PMC
- PMC7457604
- OpenAlex
- W3200792349
- Cited by
- 199
- References
- 0
- Citations by year
- 2026: 37 · 2025: 52 · 2024: 34 · 2023: 31 · 2022: 27 · 2021: 16 · 2020: 2
- FWCI
- 8.47
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nucleic Acids Research (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (submittedVersion, cc-by)
- Funders
- National Science Foundation
- Northwestern University
- Oregon State University
- National Institute of Advanced Industrial Science and Technology
- Baidu
- National Institutes of Health
- National Institute of General Medical Sciences (R35GM122579)
- 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 Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Interference and Gene Delivery
- Keywords
- mRNA stabilization, RNA hydrolysis, mRNA vaccines, mRNA therapeutics, SARS-CoV-2 spike protein, mRNA half-life
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