Kurniawan Ferry Dwi, Alia Dina, Shiraishi Mamoru, Higo Megumi, Inoue Yoshiaki, Hagiwara Koichi
Comprehensive Medicine I, Saitama Medical Center, Jichi Medical University, 1-847 Amanuma-cho, Omiya-ku, Saitama-shi, Saitama, 330-8503, Japan.
Department of Pulmonology and Respiratory Medicine, Faculty of Medicine, University of Syiah Kuala, Aceh, Indonesia.
Sci Rep. 2025 Aug 10;15(1):29253. doi: 10.1038/s41598-025-14841-z.
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.
超过一半的社区获得性肺炎病例是由几十种细菌引起的,准确识别这些病原体对于有效治疗至关重要。在本研究中,考虑到种内变异、区分肺炎链球菌与口腔α溶血性链球菌的需要以及适用于战场假说(该假说有助于区分真正的病原体与非致病共生生物),我们开发了一种使用16S核糖体RNA(16S rRNA)测序的可靠诊断方法。我们设计了特异性引物和一个BLAST包装程序Cheryblast + ob,以对37种引起肺炎的细菌和4种α溶血性链球菌进行分类。在涉及Genbank中41种细菌的16S rRNA共20309个拷贝的模拟实验中,该算法的灵敏度大于0.996,特异性为1.000。它对测序错误具有鲁棒性,并成功地将肺炎链球菌与密切相关的物种区分开来。在一项对含有10种细菌基因组DNA和人类DNA且比例呈两倍变化的人工混合物进行下一代测序的实验中,11个样本中有8个正确识别出拷贝数最高的物种,所有11个样本中都识别出了拷贝数排名前两位的物种。这种高性能方法为准确的肺炎诊断提供了一种有前景的工具,也可应用于必须可靠识别有限数量细菌物种的其他感染。