Development of a novel multi-epitope subunit mRNA vaccine candidate to combat Acinetobacter baumannii

Abstract

Acinetobacter baumannii, an opportunistic bacterium prevalent in various environment, is a significant cause of nosocomial infections in ICUs. As the causative agent of pneumonia, septicemia, and meningitis, A. baumannii typically exhibits multidrug resistance and is associated with poor prognosis, thus led to a challenge for researchers in developing new treatment and prevention methods. This study involved the development of a novel multi-epitope mRNA vaccine for A. baumannii and validation of in silico approaches was conducted. We screened 11 immunodominant epitopes for cytotoxic T cells, 5 for helper T cells, and 10 for Linear B-cell based on promising candidate proteins omp33-36, ompA and ompW, the selection of these three proteins is based on reverse vaccinology screening and previous work by other researchers. All predicted epitopes demonstrated strong antigenicity, immunogenicity without posing any potential harm to humans. Additionally, high conservancy is required to cover different strains. All epitopes, as well as adjuvants, were constructed into a final vaccine, which was further assessed by calculating its physicochemical properties. Next, we docked the vaccine protein with immune receptors and analyzed the complexes with dynamic simulations to evaluate its affinity to receptors. At last, the constructed sequence is translated to an mRNA sequence. The results indicated the constructed vaccine is capability of eliciting robust humoral and cellular immune responses, making it a promising candidate for protection against the targeted pathogen.

Keywords: Acinetobacter baumannii; Molecular docking; Molecular dynamics; Multiepitope vaccine; mRNA vaccine.

Fig. 1

Analyze of core proteins of A. baumannii genome. (A) Core-Pan Plot of A. baumannii (B) COG distribution plot of A. baumannii. (C) Phylogenetic tree of OmpA (D) Phylogenetic tree of OmpW (E) Phylogenetic tree of Omp33-36.

Fig. 2

Construction of multi-epitope vaccine. (A) Vaccine sequence of MEV, purple: β-defensin sequence, red: CTL epitopes, blue: HTL epitopes and PADRE sequence, green: linear B cell epitopes, lighter blue: p30 sequence, black: linkers. (B) secondary structure of MEV sequence, blue for helix, red for sheet, purple for coil. (C) tertiary structure of MEV, purple: β-defensin sequence, red: CTL epitopes, blue: HTL epitopes and PADRE sequence, green: linear B cell epitopes, lighter blue: p30 sequence, grey: linkers. (D) ERRAT score plot. (E) Ramchandran plots. (F) Prosa analyze of overall model quality.

Fig. 3

Docking model of the vaccine with TLR2 molecule, blue represents the MEV molecule, and brown represents the TLR molecule.

Fig. 4

Docking model of the vaccine with TLR4 molecule, blue represents the MEV molecule, and brown represents the TLR molecule.

Fig. 5

Molecular dynamic simulation results. Blue for vaccine-TLR4 complex, red for vaccine-TLR2 complex. (A) RMSD (root mean square deviation) plots of vaccine-receptors, reflects the stability between the vaccine and receptor. (B) Radius of gyration (Rg) plots of vaccine-receptors complexes, suggesting the compactness of complexes. (C, D) RMSF (root mean square fluctuation) of vaccine-receptors, reflects the flexibility and fluctuation of the amino-acids residues in the side chain of docked complexes, vaccines’ RMSF(C) and receptors’ RMSF(D). (E) H-bonds formed in complexes.

Fig. 6

Immunological simulation analysis. (A) Antibody levels induced by three doses of vaccine injection. (B) Levels of cytokines such as IL2, IFN-γ induced. (C) Levels of B cells induced. (D) Levels of plasma cells. (E) Levels of helper T (TH) cells induced. (F) Levels of cytotoxic T (TC) cells induced. (G) Levels of dendritic (DC) cells induced. (H) Levels of natural killer (NK) cells induced. (I) Levels of dendritic (DC) cells in different states.