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<p>Over half of community-acquired pneumonia cases are caused by a few dozen bacterial species, and accurate identification of these pathogens is essential for effective treatment. In this study, we developed a reliable diagnostic method using 16S ribosomal RNA (16S rRNA) sequencing, considering intra-species variation, the need to differentiate <i>Streptococcus pneumoniae</i> from oral α-hemolytic <i>streptococci</i>, and applicability to the battlefield hypothesis, which helps distinguish true pathogens from commensal organisms that are not causative pathogens. We designed specific primers and a BLAST wrapper program, Cheryblast + ob, to classify 37 pneumonia-causing bacteria and 4&#xa0;α-hemolytic <i>streptococci</i>. In simulation experiments involving a total of 20,309 copies of the 16S rRNA from 41 species of bacteria deposited in Genbank, the algorithm achieved a sensitivity greater than 0.996 and a specificity of 1.000. It was robust against sequencing errors and successfully distinguished <i>S. pneumoniae</i> from closely related species. In an experiment using next-generation sequencing on artificial mixtures containing genomic DNA from 10 bacterial species and human DNA at varying two-fold ratios, the species with the highest copy number was correctly identified in 8 out of 11 samples, and the top two species by copy number were identified in all 11 samples. This high-performance method offers a promising tool for accurate pneumonia diagnosis and could also be applied to other infections in which a limited number of bacterial species must be reliably identified.</p>

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A systematic algorithm using 16S ribosomal RNA for accurate diagnosis of pneumonia pathogens

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月10日

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  • Ferry Dwi Kurniawan,
  • Dina Alia,
  • Mamoru Shiraishi,
  • Megumi Higo,
  • Yoshiaki Inoue,
  • Koichi Hagiwara

摘要

Over half of community-acquired pneumonia cases are caused by a few dozen bacterial species, and accurate identification of these pathogens is essential for effective treatment. In this study, we developed a reliable diagnostic method using 16S ribosomal RNA (16S rRNA) sequencing, considering intra-species variation, the need to differentiate Streptococcus pneumoniae from oral α-hemolytic streptococci, and applicability to the battlefield hypothesis, which helps distinguish true pathogens from commensal organisms that are not causative pathogens. We designed specific primers and a BLAST wrapper program, Cheryblast + ob, to classify 37 pneumonia-causing bacteria and 4 α-hemolytic streptococci. In simulation experiments involving a total of 20,309 copies of the 16S rRNA from 41 species of bacteria deposited in Genbank, the algorithm achieved a sensitivity greater than 0.996 and a specificity of 1.000. It was robust against sequencing errors and successfully distinguished S. pneumoniae from closely related species. In an experiment using next-generation sequencing on artificial mixtures containing genomic DNA from 10 bacterial species and human DNA at varying two-fold ratios, the species with the highest copy number was correctly identified in 8 out of 11 samples, and the top two species by copy number were identified in all 11 samples. This high-performance method offers a promising tool for accurate pneumonia diagnosis and could also be applied to other infections in which a limited number of bacterial species must be reliably identified.