Enhanced Th1 Cellular Immunity Induced by an RSV-F mRNA Vaccine Rationally Designed Using NLP Algorithms

Background: Respiratory syncytial virus (RSV) is a leading cause of severe lower respiratory tract infections in infants, seniors, and immunocompromised individuals, contributing substantially to the global disease burden. Given the limited preventive options available, developing an effective and safe vaccine remains a public health priority. Methods: An mRNA vaccine encoding the RSV PreF protein was designed and prepared. Antigen properties were evaluated in silico, and the coding sequence was optimized using NLP algorithms. The stability and translational efficiency of the mRNA constructs were verified through in vitro and in vivo assays, followed by immunogenicity evaluation of the formulated mRNA vaccines in a BALB/c mouse model. Results: The optimized mRNA showed predicted improvements in structural stability and a lower free energy state, which were associated with increased translational efficacy in vitro. Correct antigen conformation and retention of key epitopes were confirmed by intracellular staining followed by flow cytometry. A balanced Th1-biased immune response was induced in mice, characterized by high levels of neutralizing antibodies and antigen-specific T-cell immunity, along with enhanced memory T-cell proliferation and differentiation, indicating long-term immunological memory. Conclusions: A novel RSV PreF mRNA vaccine was successfully developed via optimization of protein structure and mRNA sequence. Superior immunogenicity was demonstrated in the BALB/c mouse model, together with promising potential in terms of vaccine safety and immunological persistence. These findings represent a promising step forward in the pursuit of an effective RSV vaccine and suggest the potential of the developed mRNA vaccine to induce substantial immune responses that may correlate with protection in future challenge studies.