Refining PCR-based serotyping for detection of vaccine-preventable Streptococcus pneumoniae
Abstract
Conventional multiplex PCR (cmPCR) reactions have been developed to monitor the most predominant serotypes of Streptococcus pneumoniae causing invasive pneumococcal disease (IPD). Since cmPCR assigns serotypes based on differences in the capsule biosynthesis (cps) loci, DNA extracted from clinical specimens can be used directly to monitor changes in serotype distribution and assess the impact of pneumococcal vaccines. Given that cmPCR can require up to eight reactions to assign a serotype, testing is often conducted in sequential algorithms. Sequential cmPCR reactions; however, may not be the most cost effective strategy to determine whether a S. pneumoniae serotype is vaccine-preventable. This study used oligonucleotide permutations in a modified set of cmPCR reactions (termed cmPCRmod) to reduce the number of PCR reactions required to identify S. pneumoniae serotypes covered by the 7- and 13-valent pneumococcal conjugate vaccines (PCV7 and PCV13, respectively) and the 23-valent pneumococcal polysaccharide vaccine (PPV23). While oligonucleotide permutations have previously been reported for regional differences in serotype distribution, the impact on assay performance had not been assessed. This study demonstrated that equivalent analytical sensitivity and specificity was seen when comparing cmPCR and cmPCRmod, and 100% concordance was seen when 308 clinical isolates of S. pneumoniae were evaluated. Compared to cmPCR, cmPCRmod reduced the number and reactions required to detect serotypes covered by PCV7, PCV13, and PPV23. This study demonstrated that conventional multiplex reactions can be reformulated for more efficient detection of vaccine-preventable serotypes, without compromising test performance characteristics. As such, cmPCRmod reactions could provide significant cost savings for large surveillance studies.
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PDFDOI: https://doi.org/10.5430/jer.v3n1p28
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Journal of Epidemiological Research
ISSN 2377-9306(Print) ISSN 2377-9330(Online)
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