Table_2_PubMLST for Antigen Allele Mining to Inform Development of Gonorrhea Protein-Based Vaccines.XLSX
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
Neisseria gonorrhoeae (Ng) is a human-specific pathogen and the etiological agent of gonorrhea, a sexually transmitted infection with a significant global health burden. While often asymptomatic, untreated gonorrhea can lead to pelvic inflammatory disease, ectopic pregnancy, infertility, and increased transmission/acquisition of HIV. A protective gonorrhea vaccine may be the only way to control disease transmission in the future due to the inexorable development of antibiotic resistance. Subunit antigens are proven candidates for vaccine development due to their safety, cost-effectiveness, and rapid preparation. To inform protein-based gonorrhea vaccine design by including different antigen variants, herein we present bioinformatics mining of alleles and single nucleotide/amino acid polymorphisms using DNA/protein sequences of all Ng isolates deposited into the PubMLST database and MtrE and BamA as model antigens. We also present phylogenetic analyses that can be performed using sequence data to gain insights into the evolutionary relationships between the polymorphisms found among the population of isolates using a convenient tool: Molecular Evolutionary Genetics Analysis (MEGA) software. Finally, we perform antigen polymorphism mapping onto the MtrE and BamA structures. This methodology can be applied for rational vaccine design to increase vaccine coverage and cross-protection by heteroligand presentation achieved via inclusion of diverse antigen variants and is relevant to over 100 different species and genera deposited into the PubMLST family of databases.
Read the peer-reviewed publication