Mao Xin, Wang Jingkai, Xu Junchi, Xu Ping, Hu Huijie, Li Li, Zhang Zhiqiang, Song Yizhi
Department of Chemistry, College of Sciences, Shanghai University, 99 Shangda Road, Baoshan District, Shanghai 200444, China.
Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, 88 Keling Road, Gaoxin District, Suzhou 215163, China.
J Appl Microbiol. 2025 May 2;136(5). doi: 10.1093/jambio/lxaf100.
Tuberculosis (TB), caused by Mycobacterium tuberculosis (MTB), remains a major global health threat, compounded by the rise of extensively drug-resistant (XDR) and multidrug-resistant (MDR) strains. This review critically examines the current landscape of laboratory diagnostic methods for MTB, encompassing both established techniques and recent advancements. We explore the growth and genetic characteristics of MTB that underpin drug resistance development and detection. We then provide a comparative analysis of smear microscopy, culture-based methods, antigen detection, molecular diagnostics (including nucleic acid amplification tests and whole-genome sequencing), spectroscopic techniques (such as Raman spectroscopy), and mass spectrometry-based approaches. Notably, this review focuses on pathogen-based diagnostic methods, excluding host immune response assays. The strengths and limitations of each method are evaluated in terms of sensitivity, specificity, turnaround time, cost-effectiveness, and suitability for resource-limited settings. Finally, we discuss the future of TB diagnostics, emphasizing the need for integrated, multi-modal platforms, the incorporation of artificial intelligence (AI) for enhanced data analysis, and the development of affordable, point-of-care testing to improve accessibility and impact in high-burden regions. Overcoming current diagnostic challenges is essential for improving patient outcomes and achieving global TB elimination goals.
由结核分枝杆菌（MTB）引起的结核病（TB）仍然是全球主要的健康威胁，广泛耐药（XDR）和多重耐药（MDR）菌株的出现使情况更加复杂。本综述批判性地审视了MTB实验室诊断方法的现状，涵盖了既定技术和最新进展。我们探讨了MTB的生长和遗传特征，这些特征是耐药性发展和检测的基础。然后，我们对涂片显微镜检查、基于培养的方法、抗原检测、分子诊断（包括核酸扩增试验和全基因组测序）、光谱技术（如拉曼光谱）和基于质谱的方法进行了比较分析。值得注意的是，本综述侧重于基于病原体的诊断方法，不包括宿主免疫反应检测。从灵敏度、特异性、周转时间、成本效益以及对资源有限环境的适用性等方面评估了每种方法的优缺点。最后，我们讨论了结核病诊断的未来，强调了对综合多模式平台的需求、纳入人工智能（AI）以加强数据分析，以及开发经济实惠的即时检测以提高高负担地区的可及性和影响力。克服当前的诊断挑战对于改善患者预后和实现全球结核病消除目标至关重要。
