Design and validation of multi-stage expressing mRNA vaccine for Mycobacterium tuberculosis through computational technology

Tuberculosis (TB) is a disease which continues to challenge the global health system for decades. Despite several scientific interventions being carried out for its diagnosis and treatment, it is still the leading cause of mortality from any known infectious disease. Novel approaches for a promising TB vaccine necessitate identification of antigens that could confer protective immunity at all stages of infection and boosting immune response. mRNA vaccines are the vaccines of the future and offer a viable substitute for traditional vaccine techniques. Employing an immuno-informatics approach, we designed mRNA vaccine with T cell- epitopes expressed through different stages of TB infection. In-silico results using IEDB and NETMHC4.0 shows strong affinity of designed vaccine for both class I MHC restricted CD8 T cells and class II MHC restricted CD4 T cells. Our designed mRNA vaccine based on selected epitopes along with extra co-translational mRNA structural component was predicted to be highly stable in RNA fold webserver. Codon optimization led to the optimal translation of the mRNA in the host cell. Molecular docking in Patchdock revealed strong interaction of designed construct for immune receptors- TLR2 and TLR4 which is further confirmed by MD simulations using Gromacs server. Both these receptors establish specific Leucine-Rich-Repeats (LRR) regions interactions with the vaccine construct, implicating their strong binding affinity for these immune receptors. C-Immsim based immune simulation studies substantiated translated protein immunogenic nature as a promising vaccine. Our approach of immunoinformatic based designing, synthesis and experimental validation of mRNA vaccine could be a promising strategy to combat TB.