Utilizing large and diverse bacterial genome datasets to improve the detection and identification of via PCR-based diagnostics.

The accurate identification of (pneumococcus) is crucial for diagnostics and surveillance but is complicated by the use of molecular assays that may also detect non-pneumococcal (NPS) species. Therefore, the aim of this study was to use a combination of and analyses to evaluate PCR assays for the molecular detection and identification of pneumococci. A diverse dataset of over 9,300 pneumococcal and NPS genomes was investigated to determine the sensitivity and specificity of assays for seven recommended gene targets: , , , , Spn9802, SP2020 and Xisco. These findings were used to design new diagnostic assays for two targets, Xisco and SP2020. The new assays were evaluated using three sets of isolates, one of which was selected based upon evidence for sequence diversity from a second investigation of over 6,000 pneumococcal genomes sequenced by the United Kingdom Health Security Agency. Experimentally, the new Xisco and SP2020 assays were compared to published assays for and . The specificity was 100% (95% CI, 98.7-100%) across all assays. The sensitivity was 100% (95% CI, 98.5-100%) for , SP2020_new and the Xisco assays and 99.6% (95% CI, 97.8-100%) for . The new assays were found to be highly sensitive and specific and able to detect as few as two pneumococcal genome copies per quantitative PCR reaction. Overall, this study demonstrated the value of performing large-scale genomic analyses of diagnostic targets, followed by testing that was specifically designed to account for global pneumococcal population-level diversity.