A novel deep generative model for mRNA vaccine development: Designing 5' UTRs with N 1-methyl-pseudouridine modification

Xiaoshan Tang; Miaozhe Huo; Yuting Chen; Hai Huang; Shugang Qin; Jiaqi Luo; Zeyi Qin; Xin Jiang; Yongmei Liu; Xing Duan; Ruohan Wang; Lingxi Chen; Hao Li; Na Fan; Zhongshan He; Xi He; Bairong Shen; Shuai Cheng Li; Xiangrong Song

doi:10.1016/j.apsb.2023.11.003

A novel deep generative model for mRNA vaccine development: Designing 5' UTRs with N 1-methyl-pseudouridine modification

Acta Pharm Sin B. 2024 Apr;14(4):1814-1826. doi: 10.1016/j.apsb.2023.11.003. Epub 2023 Nov 5.

Authors

Xiaoshan Tang¹, Miaozhe Huo², Yuting Chen¹, Hai Huang¹, Shugang Qin¹, Jiaqi Luo², Zeyi Qin³, Xin Jiang¹, Yongmei Liu¹, Xing Duan¹, Ruohan Wang², Lingxi Chen², Hao Li¹, Na Fan¹, Zhongshan He¹, Xi He¹, Bairong Shen¹, Shuai Cheng Li², Xiangrong Song¹

Affiliations

¹ Institute of Systems Genetics, Department of Critical Care Medicine, Frontiers Science Center for Disease-related Molecular Network, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu 610000, China.
² Department of Computer Science, City University of Hong Kong, Hong Kong 99907, China.
³ Department of Biology, Brandeis University, Boston, MA 02453, USA.

Abstract

Efficient translation mediated by the 5' untranslated region (5' UTR) is essential for the robust efficacy of mRNA vaccines. However, the N1-methyl-pseudouridine (m1Ψ) modification of mRNA can impact the translation efficiency of the 5' UTR. We discovered that the optimal 5' UTR for m1Ψ-modified mRNA (m1Ψ-5' UTR) differs significantly from its unmodified counterpart, highlighting the need for a specialized tool for designing m1Ψ-5' UTRs rather than directly utilizing high-expression endogenous gene 5' UTRs. In response, we developed a novel machine learning-based tool, Smart5UTR, which employs a deep generative model to identify superior m1Ψ-5' UTRs in silico. The tailored loss function and network architecture enable Smart5UTR to overcome limitations inherent in existing models. As a result, Smart5UTR can successfully design superior 5' UTRs, greatly benefiting mRNA vaccine development. Notably, Smart5UTR-designed superior 5' UTRs significantly enhanced antibody titers induced by COVID-19 mRNA vaccines against the Delta and Omicron variants of SARS-CoV-2, surpassing the performance of vaccines using high-expression endogenous gene 5' UTRs.

Keywords: 5′ UTR; COVID-19; Machine learning; N1-Methyl-pseudouridine; SARS-CoV-2; Sequence design; mRNA design; mRNA vaccine.