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PreprintCited by 39RNA and protein synthesis mechanismsRNA Interference and Gene DeliveryRNA modifications and cancer

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Deep Generative Optimization of mRNA Codon Sequences for Enhanced Protein Production and Therapeutic Efficacy

Open access
Xie, Zhi, Li, Yupeng, Wang, Fan, Yang, Jiaqi, Han, Zirong, Chen, Linfeng, Jiang, Wenbing, Zhou, Hao, Li, Tong, Tang, Zehua, Deng, Jianxiang, He, Xin, Zha, Gaofeng, He, Yao·2024·Nature Communications
DOI 10.21203/rs.3.rs-5040961/v1PMC PMC12612108

Preprint — published as 10.1038/s41467-025-64894-x · Paper page

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Abstract

Messenger RNA (mRNA) therapeutics show immense promise, but their efficacy is limited by suboptimal protein expression. Here, we present RiboCode, a deep learning framework that generates mRNA codon sequences for enhanced protein production. RiboCode introduces several advances, including direct learning from large-scale ribosome profiling data, context-aware mRNA optimization and generative exploration of a large sequence space. In silico analysis demonstrate RiboCode’s robust predictive accuracy for unseen genes and cellular environments. In vitro experiments show substantial improvements in protein expression, with up to a 72-fold increase, significantly outperforming past methods. In addition, RiboCode achieves cell-type specific expression and demonstrates robust performance across different mRNA formats, including m 1 Ψ-modified and circular mRNAs, an important feature for mRNA therapeutics. In vivo mouse studies show that optimized influenza hemagglutinin mRNAs induce ten times stronger neutralizing antibody responses against influenza virus compared to the unoptimized sequence. In an optic nerve crush model, optimized nerve growth factor mRNAs achieve equivalent neuroprotection of retinal ganglion cells at one-fifth the dose of the unoptimized sequence. Collectively, RiboCode represents a paradigm shift from rule-based to data-driven, context-sensitive approach for mRNA therapeutic applications, enabling the development of more potent and dose-efficient treatments.

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Metadata

Authors
Xie, Z., Li, Y., Wang, F., Yang, J., Han, Z., Chen, L., Jiang, W., Zhou, H., Li, T., Tang, Z., Deng, J., He, X., Zha, G., & He, Y.
Affiliations
  • Sun Yat-sen University (CN)
  • State Key Laboratory of Ophthalmology (CN)
  • Sun Yat-sen University
Corresponding author
  • Xie, Zhi
  • He, Yao
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2024-11-05
Volume
16
Issue
1
Pages
9957-9957
ISSN
2041-1723 (ISSN-L)
DOI
10.21203/rs.3.rs-5040961/v1
PMC
PMC12612108
OpenAlex
W4416142807
Cited by
39
References
3
Citations by year
2026: 35 · 2025: 3 · 2024: 1
FWCI
11.36
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by-nc-nd)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • Research Square (acceptedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
National Natural Science Foundation of China (32470705, 2022YFF1203100)
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 modifications and cancer
Keywords
mRNA therapeutics, deep generative models, ribosome profiling, mRNA translation efficiency, protein expression, neutralizing antibodies, nerve growth factor, optic nerve crush, retinal ganglion cell neuroprotection, mRNA vaccines, protein replacement therapy
MeSH terms
Animals, Codon, Humans, Mice, Inbred C57BL, Orthomyxoviridae Infections, Ribosomes, RNA, Messenger, Protein Biosynthesis, Mice, Antibodies, Neutralizing

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