Matsumoto Yuki, Fukushima Kiyoharu, Zhang Shunran, Fauzyah Yuzy, Motooka Daisuke, Saito Haruko, Yamauchi June, Nitta Tadayoshi, Nii Takuro, Matsuki Takanori, Tsujino Kazuyuki, Miki Keisuke, Kida Hiroshi, Nakamura Shota
Department of Infection Metagenomics, Bioinformatics Center, Research Institute for Microbial Diseases (RIMD), Osaka University, Suita, Osaka, Japan.
Department of Clinical Laboratory, National Hospital Organization, Osaka Toneyama Medical Center, Toyonaka, Osaka, Japan.
Funct Integr Genomics. 2025 May 21;25(1):105. doi: 10.1007/s10142-025-01609-x.
The identification of mycobacteria, including Mycobacterium tuberculosis (MTB) and non-tuberculous mycobacteria (NTM), remains a critical challenge in clinical and public health settings due to their pathogenicity and increasing drug resistance. Traditional diagnostic methods, such as PCR and mass spectrometry, are limited by species detectability and prolonged culture requirements. To address these limitations, this study introduces a novel approach, named NALC-Seq, which integrates next-generation sequencing (NGS) and target capture sequencing for the direct and comprehensive identification of mycobacteria from sputum samples. A total of 54 patients were prospectively or retrospectively enrolled between April 6, 2021, and November 8, 2022, and sputum samples were subjected to next generation sequencing. The NALC-Seq methodology utilizes custom-designed RNA probes for targeted enrichment of mycobacterial DNA, coupled with species identification via the mlstverse-web system. This system integrates web, upload, head, and cloud nodes to streamline data management and analysis. Our evaluation demonstrated that NALC-Seq achieved high sensitivity (98.1%) and accuracy (83.3%) in detecting diverse mycobacterial species, including rare and drug-resistant subspecies. There were discrepancies with MGIT-Seq in nine samples. These samples exhibited low smear positivity rates, and the detection of environmental mycobacteria suggested potential contamination. Furthermore, real-time identification using the MinION device significantly reduced the turnaround time from 686 to 19 h.These findings highlight the potential of NALC-Seq and mlstverse-web as an integrated diagnostic solution for overcoming the limitations of current methods. The proposed approach offers a rapid, accurate, and comprehensive strategy for mycobacterial identification, with significant implications for clinical diagnostics and public health surveillance.
由于分枝杆菌具有致病性且耐药性不断增加，因此对包括结核分枝杆菌（MTB）和非结核分枝杆菌（NTM）在内的分枝杆菌进行鉴定，在临床和公共卫生环境中仍然是一项严峻挑战。传统诊断方法，如聚合酶链反应（PCR）和质谱分析，受到物种可检测性和长时间培养要求的限制。为解决这些局限性，本研究引入了一种名为NALC-Seq的新方法，该方法整合了下一代测序（NGS）和靶向捕获测序技术，用于直接、全面地从痰液样本中鉴定分枝杆菌。在2021年4月6日至2022年11月8日期间，共有54例患者被前瞻性或回顾性纳入研究，并对痰液样本进行下一代测序。NALC-Seq方法利用定制设计的RNA探针靶向富集分枝杆菌DNA，并通过mlstverse-web系统进行物种鉴定。该系统整合了网络、上传、头部和云节点，以简化数据管理和分析。我们的评估表明，NALC-Seq在检测包括罕见和耐药亚种在内的多种分枝杆菌物种时，具有较高的灵敏度（98.1%）和准确度（83.3%）。有9个样本与MGIT-Seq存在差异。这些样本涂片阳性率较低，环境分枝杆菌的检测表明可能存在污染。此外，使用MinION设备进行实时鉴定显著缩短了周转时间，从686小时降至19小时。这些发现突出了NALC-Seq和mlstverse-web作为克服现有方法局限性的综合诊断解决方案的潜力。所提出的方法为分枝杆菌鉴定提供了一种快速、准确且全面的策略，对临床诊断和公共卫生监测具有重要意义。
