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Therefore, the aim of this study was to use a combination of <jats:italic>in silico<\/jats:italic> and <jats:italic>in vitro<\/jats:italic> 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 <jats:italic>in silico<\/jats:italic> to determine the sensitivity and specificity of assays for seven recommended gene targets: <jats:italic>lytA<\/jats:italic>, <jats:italic>piaB<\/jats:italic>, <jats:italic>ply<\/jats:italic>, <jats:italic>psaA<\/jats:italic>, Spn9802, SP2020 and Xisco. These <jats:italic>in silico<\/jats:italic> findings were used to design new diagnostic assays for two targets, Xisco and SP2020. The new assays were evaluated <jats:italic>in vitro<\/jats:italic> using three sets of isolates, one of which was selected based upon evidence for sequence diversity from a second <jats:italic>in silico<\/jats:italic> 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 <jats:italic>lytA<\/jats:italic> and <jats:italic>piaB<\/jats:italic>. The <jats:italic>in vitro<\/jats:italic> specificity was 100% (95% CI, 98.7\u2013100%) across all assays. The <jats:italic>in vitro<\/jats:italic> sensitivity was 100% (95% CI, 98.5\u2013100%) for <jats:italic>lytA<\/jats:italic>, SP2020_new and the Xisco assays and 99.6% (95% CI, 97.8\u2013100%) for <jats:italic>piaB<\/jats:italic>. 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 <jats:italic>in silico<\/jats:italic> genomic analyses of diagnostic targets, followed by <jats:italic>in vitro<\/jats:italic> testing that was specifically designed to account for global pneumococcal population-level diversity.<\/jats:p>","DOI":"10.1099\/mgen.0.001418","type":"journal-article","created":{"date-parts":[[2025,6,9]],"date-time":"2025-06-09T15:16:12Z","timestamp":1749482172000},"source":"Crossref","is-referenced-by-count":4,"title":["Utilizing large and diverse bacterial genome datasets to improve the detection and identification of Streptococcus pneumoniae via PCR-based diagnostics"],"prefix":"10.1099","volume":"11","author":[{"given":"Femke M.","family":"Ahlers","sequence":"first","affiliation":[{"name":"Nuffield Department of Population Health, University of Oxford, Oxford, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David 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