1
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He Y, Johnston APR, Pouton CW. Therapeutic applications of cell engineering using mRNA technology. Trends Biotechnol 2024:S0167-7799(24)00191-4. [PMID: 39153909 DOI: 10.1016/j.tibtech.2024.07.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 07/16/2024] [Accepted: 07/20/2024] [Indexed: 08/19/2024]
Abstract
Engineering and reprogramming cells has significant therapeutic potential to treat a wide range of diseases, by replacing missing or defective proteins, to provide transcription factors (TFs) to reprogram cell phenotypes, or to provide enzymes such as RNA-guided Cas9 derivatives for CRISPR-based cell engineering. While viral vector-mediated gene transfer has played an important role in this field, the use of mRNA avoids safety concerns associated with the integration of DNA into the host cell genome, making mRNA particularly attractive for in vivo applications. Widespread application of mRNA for cell engineering is limited by its instability in the biological environment and challenges involved in the delivery of mRNA to its target site. In this review, we examine challenges that must be overcome to develop effective therapeutics.
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Affiliation(s)
- Yujia He
- Monash Institute of Pharmaceutical Sciences, Monash University, Melbourne, VIC, Australia
| | - Angus P R Johnston
- Monash Institute of Pharmaceutical Sciences, Monash University, Melbourne, VIC, Australia
| | - Colin W Pouton
- Monash Institute of Pharmaceutical Sciences, Monash University, Melbourne, VIC, Australia.
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2
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Bicknell AA, Reid DW, Licata MC, Jones AK, Cheng YM, Li M, Hsiao CJ, Pepin CS, Metkar M, Levdansky Y, Fritz BR, Andrianova EA, Jain R, Valkov E, Köhrer C, Moore MJ. Attenuating ribosome load improves protein output from mRNA by limiting translation-dependent mRNA decay. Cell Rep 2024; 43:114098. [PMID: 38625793 DOI: 10.1016/j.celrep.2024.114098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 01/24/2024] [Accepted: 03/27/2024] [Indexed: 04/18/2024] Open
Abstract
Developing an effective mRNA therapeutic often requires maximizing protein output per delivered mRNA molecule. We previously found that coding sequence (CDS) design can substantially affect protein output, with mRNA variants containing more optimal codons and higher secondary structure yielding the highest protein outputs due to their slow rates of mRNA decay. Here, we demonstrate that CDS-dependent differences in translation initiation and elongation rates lead to differences in translation- and deadenylation-dependent mRNA decay rates, thus explaining the effect of CDS on mRNA half-life. Surprisingly, the most stable and highest-expressing mRNAs in our test set have modest initiation/elongation rates and ribosome loads, leading to minimal translation-dependent mRNA decay. These findings are of potential interest for optimization of protein output from therapeutic mRNAs, which may be achieved by attenuating rather than maximizing ribosome load.
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Affiliation(s)
| | - David W Reid
- Moderna, Inc, 325 Binney Street, Cambridge, MA 02142, USA
| | | | | | - Yi Min Cheng
- Moderna, Inc, 325 Binney Street, Cambridge, MA 02142, USA
| | - Mengying Li
- Moderna, Inc, 325 Binney Street, Cambridge, MA 02142, USA
| | | | | | - Mihir Metkar
- Moderna, Inc, 325 Binney Street, Cambridge, MA 02142, USA
| | - Yevgen Levdansky
- RNA Biology Laboratory, Center for Cancer Research, National Cancer Institute, Frederick, MD 21702, USA
| | - Brian R Fritz
- Moderna, Inc, 325 Binney Street, Cambridge, MA 02142, USA
| | | | - Ruchi Jain
- Moderna, Inc, 325 Binney Street, Cambridge, MA 02142, USA
| | - Eugene Valkov
- RNA Biology Laboratory, Center for Cancer Research, National Cancer Institute, Frederick, MD 21702, USA
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3
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Kim YA, Mousavi K, Yazdi A, Zwierzyna M, Cardinali M, Fox D, Peel T, Coller J, Aggarwal K, Maruggi G. Computational design of mRNA vaccines. Vaccine 2024; 42:1831-1840. [PMID: 37479613 DOI: 10.1016/j.vaccine.2023.07.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 06/23/2023] [Accepted: 07/10/2023] [Indexed: 07/23/2023]
Abstract
mRNA technology has emerged as a successful vaccine platform that offered a swift response to the COVID-19 pandemic. Accumulating evidence shows that vaccine efficacy, thermostability, and other important properties, are largely impacted by intrinsic properties of the mRNA molecule, such as RNA sequence and structure, both of which can be optimized. Designing mRNA sequence for vaccines presents a combinatorial problem due to an extremely large selection space. For instance, due to the degeneracy of the genetic code, there are over 10632 possible mRNA sequences that could encode the spike protein, the COVID-19 vaccines' target. Moreover, designing different elements of the mRNA sequence simultaneously against multiple objectives such as translational efficiency, reduced reactogenicity, and improved stability requires an efficient and sophisticated optimization strategy. Recently, there has been a growing interest in utilizing computational tools to redesign mRNA sequences to improve vaccine characteristics and expedite discovery timelines. In this review, we explore important biophysical features of mRNA to be considered for vaccine design and discuss how computational approaches can be applied to rapidly design mRNA sequences with desirable characteristics.
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Affiliation(s)
| | | | | | | | | | | | | | - Jeff Coller
- Johns Hopkins University, Baltimore, MD, USA
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4
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Gu X, Qi Y, El-Kebir M. DERNA Enables Pareto Optimal RNA Design. J Comput Biol 2024; 31:179-196. [PMID: 38416637 DOI: 10.1089/cmb.2023.0283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/01/2024] Open
Abstract
The design of an RNA sequence v that encodes an input target protein sequence w is a crucial aspect of messenger RNA (mRNA) vaccine development. There are an exponential number of possible RNA sequences for a single target protein due to codon degeneracy. These potential RNA sequences can assume various secondary structure conformations, each with distinct minimum free energy (MFE), impacting thermodynamic stability and mRNA half-life. Furthermore, the presence of species-specific codon usage bias, quantified by the codon adaptation index (CAI), plays a vital role in translation efficiency. While earlier studies focused on optimizing either MFE or CAI, recent research has underscored the advantages of simultaneously optimizing both objectives. However, optimizing one objective comes at the expense of the other. In this work, we present the Pareto Optimal RNA Design problem, aiming to identify the set of Pareto optimal solutions for which no alternative solutions exist that exhibit better MFE and CAI values. Our algorithm DEsign RNA (DERNA) uses the weighted sum method to enumerate the Pareto front by optimizing convex combinations of both objectives. We use dynamic programming to solve each convex combination in O ( | w | 3 ) time and O ( | w | 2 ) space. Compared with a CDSfold, previous approach that only optimizes MFE, we show on a benchmark data set that DERNA obtains solutions with identical MFE but superior CAI. Moreover, we show that DERNA matches the performance in terms of solution quality of LinearDesign, a recent approach that similarly seeks to balance MFE and CAI. We conclude by demonstrating our method's potential for mRNA vaccine design for the SARS-CoV-2 spike protein.
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Affiliation(s)
- Xinyu Gu
- Department of Computer Science and University of Illinois Urbana-Champaign, Urbana, Illinois, USA
| | - Yuanyuan Qi
- Department of Computer Science and University of Illinois Urbana-Champaign, Urbana, Illinois, USA
| | - Mohammed El-Kebir
- Department of Computer Science and University of Illinois Urbana-Champaign, Urbana, Illinois, USA
- Cancer Center at Illinois, University of Illinois Urbana-Champaign, Urbana, Illinois, USA
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5
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Zhang H, Zhang L, Lin A, Xu C, Li Z, Liu K, Liu B, Ma X, Zhao F, Jiang H, Chen C, Shen H, Li H, Mathews DH, Zhang Y, Huang L. Algorithm for optimized mRNA design improves stability and immunogenicity. Nature 2023; 621:396-403. [PMID: 37130545 PMCID: PMC10499610 DOI: 10.1038/s41586-023-06127-z] [Citation(s) in RCA: 58] [Impact Index Per Article: 58.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Accepted: 04/25/2023] [Indexed: 05/04/2023]
Abstract
Messenger RNA (mRNA) vaccines are being used to combat the spread of COVID-19 (refs. 1-3), but they still exhibit critical limitations caused by mRNA instability and degradation, which are major obstacles for the storage, distribution and efficacy of the vaccine products4. Increasing secondary structure lengthens mRNA half-life, which, together with optimal codons, improves protein expression5. Therefore, a principled mRNA design algorithm must optimize both structural stability and codon usage. However, owing to synonymous codons, the mRNA design space is prohibitively large-for example, there are around 2.4 × 10632 candidate mRNA sequences for the SARS-CoV-2 spike protein. This poses insurmountable computational challenges. Here we provide a simple and unexpected solution using the classical concept of lattice parsing in computational linguistics, where finding the optimal mRNA sequence is analogous to identifying the most likely sentence among similar-sounding alternatives6. Our algorithm LinearDesign finds an optimal mRNA design for the spike protein in just 11 minutes, and can concurrently optimize stability and codon usage. LinearDesign substantially improves mRNA half-life and protein expression, and profoundly increases antibody titre by up to 128 times in mice compared to the codon-optimization benchmark on mRNA vaccines for COVID-19 and varicella-zoster virus. This result reveals the great potential of principled mRNA design and enables the exploration of previously unreachable but highly stable and efficient designs. Our work is a timely tool for vaccines and other mRNA-based medicines encoding therapeutic proteins such as monoclonal antibodies and anti-cancer drugs7,8.
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Affiliation(s)
- He Zhang
- Baidu Research USA, Sunnyvale, CA, USA
- School of EECS, Oregon State University, Corvallis, OR, USA
| | - Liang Zhang
- Baidu Research USA, Sunnyvale, CA, USA
- School of EECS, Oregon State University, Corvallis, OR, USA
- Vaccine Center, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Ang Lin
- StemiRNA Therapeutics, Shanghai, China
- Vaccine Center, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | | | - Ziyu Li
- Baidu Research USA, Sunnyvale, CA, USA
| | - Kaibo Liu
- Baidu Research USA, Sunnyvale, CA, USA
- School of EECS, Oregon State University, Corvallis, OR, USA
| | - Boxiang Liu
- Baidu Research USA, Sunnyvale, CA, USA
- Department of Pharmacy, National University of Singapore, Singapore, Singapore
| | | | | | | | | | | | | | - David H Mathews
- Department of Biochemistry and Biophysics, University of Rochester Medical Center, Rochester, NY, USA.
- Center for RNA Biology, University of Rochester Medical Center, Rochester, NY, USA.
- Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, USA.
- Coderna.ai, Inc., Sunnyvale, CA, USA.
| | - Yujian Zhang
- StemiRNA Therapeutics, Shanghai, China.
- , Gaithersburg, MD, USA.
| | - Liang Huang
- Baidu Research USA, Sunnyvale, CA, USA.
- School of EECS, Oregon State University, Corvallis, OR, USA.
- Coderna.ai, Inc., Sunnyvale, CA, USA.
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6
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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. Combinatorial optimization of mRNA structure, stability, and translation for RNA-based therapeutics. Nat Commun 2022; 13:1536. [PMID: 35318324 PMCID: PMC8940940 DOI: 10.1038/s41467-022-28776-w] [Citation(s) in RCA: 97] [Impact Index Per Article: 48.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Accepted: 02/07/2022] [Indexed: 02/07/2023] Open
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. The authors develop an RNA sequencing-based platform, PERSIST-seq, to simultaneously delineate in-cell mRNA stability, ribosome load, and in-solution stability of a diverse mRNA library to derive design principles for improved mRNA therapeutics.
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Affiliation(s)
- Kathrin Leppek
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | - Gun Woo Byeon
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | - Wipapat Kladwang
- Department of Biochemistry, Stanford University, Stanford, CA, 94305, USA
| | | | - Craig H Kerr
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | - Adele F Xu
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | - Do Soon Kim
- Department of Biochemistry, Stanford University, Stanford, CA, 94305, USA
| | - Ved V Topkar
- Program in Biophysics, Stanford University, Stanford, CA, 94305, USA
| | - Christian Choe
- Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA
| | - Daphna Rothschild
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | - Gerald C Tiu
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | | | - Kotaro Fujii
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | - Eesha Sharma
- Department of Biochemistry, Stanford University, Stanford, CA, 94305, USA
| | - Andrew M Watkins
- Department of Biochemistry, Stanford University, Stanford, CA, 94305, USA
| | - John J Nicol
- Eterna Massive Open Laboratory, Stanford University, Stanford, CA, 94305, USA
| | - Jonathan Romano
- Eterna Massive Open Laboratory, Stanford University, Stanford, CA, 94305, USA.,Department of Computer Science and Engineering, State University of New York at Buffalo, Buffalo, New York, 14260, USA
| | - Bojan Tunguz
- Department of Biochemistry, Stanford University, Stanford, CA, 94305, USA.,NVIDIA Corporation, 2788 San Tomas Expy, Santa Clara, CA, 95051, USA
| | - Fernando Diaz
- Pfizer Vaccine Research and Development, Pearl River, NY, USA
| | - Hui Cai
- Pfizer Vaccine Research and Development, Pearl River, NY, USA
| | - Pengbo Guo
- Pfizer Vaccine Research and Development, Pearl River, NY, USA
| | - Jiewei Wu
- Pfizer Vaccine Research and Development, Pearl River, NY, USA
| | - Fanyu Meng
- Pfizer Vaccine Research and Development, Pearl River, NY, USA
| | - Shuai Shi
- Pfizer Vaccine Research and Development, Pearl River, NY, USA
| | - Eterna Participants
- Eterna Massive Open Laboratory, Stanford University, Stanford, CA, 94305, USA
| | - Philip R Dormitzer
- Pfizer Vaccine Research and Development, Pearl River, NY, USA.,GlaxoSmithKline, 1000 Winter St., Waltham, MA, 02453, USA
| | | | - Maria Barna
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA.
| | - Rhiju Das
- Department of Biochemistry, Stanford University, Stanford, CA, 94305, USA. .,Program in Biophysics, Stanford University, Stanford, CA, 94305, USA. .,Eterna Massive Open Laboratory, Stanford University, Stanford, CA, 94305, USA.
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7
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Kis Z. Stability Modelling of mRNA Vaccine Quality Based on Temperature Monitoring throughout the Distribution Chain. Pharmaceutics 2022; 14:430. [PMID: 35214162 PMCID: PMC8877932 DOI: 10.3390/pharmaceutics14020430] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2021] [Revised: 01/31/2022] [Accepted: 02/08/2022] [Indexed: 11/22/2022] Open
Abstract
The vaccine distribution chains in several low- and middle-income countries are not adequate to facilitate the rapid delivery of high volumes of thermosensitive COVID-19 mRNA vaccines at the required low and ultra-low temperatures. COVID-19 mRNA vaccines are currently distributed along with temperature monitoring devices to track and identify deviations from predefined conditions throughout the distribution chain. These temperature readings can feed into computational models to quantify mRNA vaccine critical quality attributes (CQAs) and the remaining vaccine shelf life more accurately. Here, a kinetic modelling approach is proposed to quantify the stability-related CQAs and the remaining shelf life of mRNA vaccines. The CQA and shelf-life values can be computed based on the conditions under which the vaccines have been distributed from the manufacturing facilities via the distribution network to the vaccination centres. This approach helps to quantify the degree to which temperature excursions impact vaccine quality and can also reduce vaccine wastage. In addition, vaccine stock management can be improved due to the information obtained on the remaining shelf life of mRNA vaccines. This model-based quantification of mRNA vaccine quality and remaining shelf life can improve the deployment of COVID-19 mRNA vaccines to low- and middle-income countries.
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Affiliation(s)
- Zoltán Kis
- Department of Chemical and Biological Engineering, The University of Sheffield, Mappin St., Sheffield S1 3JD, UK;
- The Sargent Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
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8
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Wayment-Steele HK, Kim DS, Choe CA, Nicol JJ, Wellington-Oguri R, Watkins AM, Parra Sperberg RA, Huang PS, Participants E, Das R. Theoretical basis for stabilizing messenger RNA through secondary structure design. Nucleic Acids Res 2021; 49:10604-10617. [PMID: 34520542 PMCID: PMC8499941 DOI: 10.1093/nar/gkab764] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 08/17/2021] [Accepted: 08/27/2021] [Indexed: 01/08/2023] Open
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. 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 a wide diversity of sequence and structure features that may be desirable for translation, biophysical size, and immunogenicity. Furthermore, their folding is robust to temperature, computer modeling method, 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.
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MESH Headings
- Algorithms
- Base Pairing
- Base Sequence
- COVID-19/prevention & control
- Humans
- Hydrolysis
- RNA Stability
- RNA, Double-Stranded/chemistry
- RNA, Double-Stranded/genetics
- RNA, Double-Stranded/immunology
- RNA, Messenger/chemistry
- RNA, Messenger/genetics
- RNA, Messenger/immunology
- RNA, Viral/chemistry
- RNA, Viral/genetics
- RNA, Viral/immunology
- SARS-CoV-2/genetics
- SARS-CoV-2/immunology
- Spike Glycoprotein, Coronavirus/genetics
- Spike Glycoprotein, Coronavirus/immunology
- Thermodynamics
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Affiliation(s)
- Hannah K Wayment-Steele
- Department of Chemistry, Stanford University, Stanford, CA 94305, USA
- Eterna Massive Open Laboratory
| | - Do Soon Kim
- Eterna Massive Open Laboratory
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL 60208, USA
- Department of Biochemistry, Stanford University, Stanford, CA 94305, USA
| | - Christian A Choe
- Eterna Massive Open Laboratory
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | | | | | - Andrew M Watkins
- Eterna Massive Open Laboratory
- Department of Biochemistry, Stanford University, Stanford, CA 94305, USA
| | | | - Po-Ssu Huang
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | | | - Rhiju Das
- Eterna Massive Open Laboratory
- Department of Biochemistry, Stanford University, Stanford, CA 94305, USA
- Department of Physics, Stanford University, Stanford, CA 94305, USA
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9
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Bhandari BK, Lim CS, Remus DM, Chen A, van Dolleweerd C, Gardner PP. Analysis of 11,430 recombinant protein production experiments reveals that protein yield is tunable by synonymous codon changes of translation initiation sites. PLoS Comput Biol 2021; 17:e1009461. [PMID: 34610008 PMCID: PMC8519471 DOI: 10.1371/journal.pcbi.1009461] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 10/15/2021] [Accepted: 09/19/2021] [Indexed: 12/16/2022] Open
Abstract
Recombinant protein production is a key process in generating proteins of interest in the pharmaceutical industry and biomedical research. However, about 50% of recombinant proteins fail to be expressed in a variety of host cells. Here we show that the accessibility of translation initiation sites modelled using the mRNA base-unpairing across the Boltzmann's ensemble significantly outperforms alternative features. This approach accurately predicts the successes or failures of expression experiments, which utilised Escherichia coli cells to express 11,430 recombinant proteins from over 189 diverse species. On this basis, we develop TIsigner that uses simulated annealing to modify up to the first nine codons of mRNAs with synonymous substitutions. We show that accessibility captures the key propensity beyond the target region (initiation sites in this case), as a modest number of synonymous changes is sufficient to tune the recombinant protein expression levels. We build a stochastic simulation model and show that higher accessibility leads to higher protein production and slower cell growth, supporting the idea of protein cost, where cell growth is constrained by protein circuits during overexpression.
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Affiliation(s)
- Bikash K. Bhandari
- Department of Biochemistry, School of Biomedical Sciences, University of Otago, Dunedin, New Zealand
| | - Chun Shen Lim
- Department of Biochemistry, School of Biomedical Sciences, University of Otago, Dunedin, New Zealand
| | - Daniela M. Remus
- Callaghan Innovation Protein Science and Engineering, University of Canterbury, Christchurch, New Zealand
| | - Augustine Chen
- Department of Biochemistry, School of Biomedical Sciences, University of Otago, Dunedin, New Zealand
| | - Craig van Dolleweerd
- Biomolecular Interaction Center, University of Canterbury, Christchurch, New Zealand
| | - Paul P. Gardner
- Department of Biochemistry, School of Biomedical Sciences, University of Otago, Dunedin, New Zealand
- Biomolecular Interaction Center, University of Canterbury, Christchurch, New Zealand
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10
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Wayment-Steele HK, Kim DS, Choe CA, Nicol JJ, Wellington-Oguri R, Watkins AM, Sperberg RAP, Huang PS, Participants E, Das R. Theoretical basis for stabilizing messenger RNA through secondary structure design. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2020.08.22.262931. [PMID: 32869022 PMCID: PMC7457604 DOI: 10.1101/2020.08.22.262931] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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.
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Affiliation(s)
- Hannah K Wayment-Steele
- Department of Chemistry, Stanford University, Stanford, CA, 94305
- Eterna Massive Open Laboratory. Consortium authors listed in Table S1
| | - Do Soon Kim
- Eterna Massive Open Laboratory. Consortium authors listed in Table S1
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, 60208
- Department of Biochemistry, Stanford University, Stanford, CA, 94305
| | - Christian A Choe
- Eterna Massive Open Laboratory. Consortium authors listed in Table S1
- Department of Bioengineering, Stanford University, Stanford, CA, 94305
| | - John J Nicol
- Eterna Massive Open Laboratory. Consortium authors listed in Table S1
| | | | - Andrew M Watkins
- Eterna Massive Open Laboratory. Consortium authors listed in Table S1
- Department of Biochemistry, Stanford University, Stanford, CA, 94305
| | | | - Po-Ssu Huang
- Department of Bioengineering, Stanford University, Stanford, CA, 94305
| | | | - Rhiju Das
- Eterna Massive Open Laboratory. Consortium authors listed in Table S1
- Department of Biochemistry, Stanford University, Stanford, CA, 94305
- Department of Physics, Stanford University, Stanford, CA, 94305
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11
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Churkin A, Retwitzer MD, Reinharz V, Ponty Y, Waldispühl J, Barash D. Design of RNAs: comparing programs for inverse RNA folding. Brief Bioinform 2018; 19:350-358. [PMID: 28049135 PMCID: PMC6018860 DOI: 10.1093/bib/bbw120] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Computational programs for predicting RNA sequences with desired folding properties have been extensively developed and expanded in the past several years. Given a secondary structure, these programs aim to predict sequences that fold into a target minimum free energy secondary structure, while considering various constraints. This procedure is called inverse RNA folding. Inverse RNA folding has been traditionally used to design optimized RNAs with favorable properties, an application that is expected to grow considerably in the future in light of advances in the expanding new fields of synthetic biology and RNA nanostructures. Moreover, it was recently demonstrated that inverse RNA folding can successfully be used as a valuable preprocessing step in computational detection of novel noncoding RNAs. This review describes the most popular freeware programs that have been developed for such purposes, starting from RNAinverse that was devised when formulating the inverse RNA folding problem. The most recently published ones that consider RNA secondary structure as input are antaRNA, RNAiFold and incaRNAfbinv, each having different features that could be beneficial to specific biological problems in practice. The various programs also use distinct approaches, ranging from ant colony optimization to constraint programming, in addition to adaptive walk, simulated annealing and Boltzmann sampling. This review compares between the various programs and provides a simple description of the various possibilities that would benefit practitioners in selecting the most suitable program. It is geared for specific tasks requiring RNA design based on input secondary structure, with an outlook toward the future of RNA design programs.
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Affiliation(s)
- Alexander Churkin
- Shamoon College of Engineering and Physics Department at Ben-Gurion University, Beer-Sheva, Israel
| | | | - Vladimir Reinharz
- Department of Computer Science, Ben-Gurion University, Beer-Sheva, Israel
- School of Computer Science, McGill University, Montréal QC, Canada
| | - Yann Ponty
- Laboratoire d’informatique, École Polytechnique, Palaiseau, France
| | | | - Danny Barash
- Department of Computer Science, Ben-Gurion University, Beer-Sheva, Israel
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