Putative novel B-cell vaccine candidates identified by reversevaccinology and genomics approaches to control Acinetobacterbaumannii serotypes

Background and Aim : In the last decade, Multi-drug resistance (MDR)-associated infections ofAcinetobacter baumannii have grown worldwide. A cost-effective preventative strategy againstthis bacterium is vaccination.Methods : This study has presented five novel vaccine candidates against A. baumannii producedusing the reverse vaccinology method. BLASTn was done to identify the most conserved antigens.PSORTb ۳.۰.۲ was run to predict the subcellular localization of the proteins. The initial screeningand antigenicity evaluation were performed using Vaxign. The ccSOL omics was also employedto predict protein solubility. The cross-membrane localization of the protein was predicted usingPRED-TMBB. B cell epitope prediction was made for immunogenicity using the IEDB andBepiPred-۲.۰ database. Eventually, BLASTp was done to verify the extent of similarity to thehuman proteome to exclude the possibility of autoimmunity.Results : Proteins failing to comply with the set parameters were filtered at each step. In silico,potential vaccines against ۲۱ A. baumannii strains were identified using reverse vaccinology andsubtractive genomic techniques. Based on the above criteria, out of the initial ۱۵ A. baumanniiproteins selected for screening, nine exposed/secreted/membrane proteins, i.e., Pfsr, LptE, OmpH,CarO, CsuB, CdiB, MlaA, FhuE, and were the most promising candidates. Their solubility andantigenicity were also examined and found to be more than ۰.۴۵ and ۰.۶, respectively.Conclusion : Based on the results, LptE was selected with the highest average antigenic score of۱.۰۴۳ as the best protein, followed by FimF and Pfsr with scores of ۱.۰۲۲ and ۱.۰۱۴, respectively.In the end, five proteins were verified as promising candidates. Overall, the targets identifiedherein may be utilized in future strategies to control A. baumannii worldwide.

کلیدواژه ها:

Putative vaccine ، Acinetobacter baumannii ، In silico ، Genomics approaches