Abstract
Bordetella pertussis is a Gram-negative bacterium that causes respiratory infections in humans. Ongoing molecular surveillance of B. pertussis acellular vaccine (aP) antigens is critical for understanding the interaction between evolutionary pressures, disease pathogenesis, and vaccine effectiveness. Methods currently used to characterize aP components are relatively labor-intensive and low throughput. To address this challenge, we sought to derive aP antigen genotypes from minimally processed short-read whole-genome sequencing data generated from 40 clinical B. pertussis isolates and analyzed using the SRST2 bioinformatic package. SRST2 was able to identify aP antigen genotypes for all antigens with the exception of pertactin, possibly due to low read coverage in GC-rich low-complexity regions of variation. Two main genotypes were observed in addition to a singular third genotype that contained an 84-bp deletion that was identified by SRST2 despite the issues in allele calling. This method has the potential to generate large pools of B. pertussis molecular data that can be linked to clinical and epidemiological information to facilitate research of vaccine effectiveness and disease severity in the context of emerging vaccine antigen-deficient strains.