A Thermostable mRNA Vaccine against COVID-19.

There is an urgent need for vaccines against coronavirus disease 2019 (COVID-19) because of the ongoing SARS-CoV-2 pandemic. Among all approaches, a messenger RNA (mRNA)-based vaccine has emerged as a rapid and versatile platform to quickly respond to this challenge. Here, we developed a lipid nanoparticle-encapsulated mRNA (mRNA-LNP) encoding the receptor binding domain (RBD) of SARS-CoV-2 as a vaccine candidate (called ARCoV). Intramuscular immunization of ARCoV mRNA-LNP elicited robust neutralizing antibodies against SARS-CoV-2 as well as a Th1-biased cellular response in mice and non-human primates. Two doses of ARCoV immunization in mice conferred complete protection against the challenge of a SARS-CoV-2 mouse-adapted strain. Additionally, ARCoV is manufactured as a liquid formulation and can be stored at room temperature for at least 1 week. ARCoV is currently being evaluated in phase 1 clinical trials.

NanoMUD: Profiling of pseudouridine and N1-methylpseudouridine using Oxford Nanopore direct RNA sequencing.

Nanopore direct RNA sequencing provided a promising solution for unraveling the landscapes of modifications on single RNA molecules. Here, we proposed NanoMUD, a computational framework for predicting the RNA pseudouridine modification (Ψ) and its methylated analog N1-methylpseudouridine (m1Ψ), which have critical application in mRNA vaccination, at single-base and single-molecule resolution from direct RNA sequencing data. Electric signal features were fed into a bidirectional LSTM neural network to achieve improved accuracy and predictive capabilities. Motif-specific models (NNUNN, N = A, C, U or G) were trained based on features extracted from designed dataset and achieved superior performance on molecule-level modification prediction (Ψ models: min AUC = 0.86, max AUC = 0.99; m1Ψ models: min AUC = 0.87, max AUC = 0.99). We then aggregated read-level predictions for site stoichiometry estimation. Given the observed sequence-dependent bias in model performance, we trained regression models based on the distribution of modification probabilities for sites with known stoichiometry. The distribution-based site stoichiometry estimation method allows unbiased comparison between different contexts. To demonstrate the feasibility of our work, three case studies on both in vitro and in vivo transcribed RNAs were presented. NanoMUD will make a powerful tool to facilitate the research on modified therapeutic IVT RNAs and provides useful insight to the landscape and stoichiometry of pseudouridine and N1-pseudouridine on in vivo transcribed RNA species.

RBD trimer mRNA vaccine elicits broad and protective immune responses against SARS-CoV-2 variants.

With the rapid emergence and spread of SARS-CoV-2 variants, development of vaccines with broad and potent protectivity has become a global priority. Here, we designed a lipid nanoparticle-encapsulated, nucleoside-unmodified mRNA (mRNA-LNP) vaccine encoding the trimerized receptor-binding domain (RBD trimer) and showed its robust capability in inducing broad and protective immune responses against wild-type and major variants of concern (VOCs) in the mouse model of SARS-CoV-2 infection. The protectivity was correlated with RBD-specific B cell responses especially the long-lived plasma B cells in bone marrow, strong ability in triggering BCR clustering, and downstream signaling. Monoclonal antibodies isolated from vaccinated animals demonstrated broad and potent neutralizing activity against VOCs tested. Structure analysis of one representative antibody identified a novel epitope with a high degree of conservation among different variants. Collectively, these results demonstrate that the RBD trimer mRNA vaccine serves as a promising vaccine candidate against SARS-CoV-2 variants and beyond.