Department of Veterinary Microbiology and Pathology, College of Veterinary Medicine, Washington State University, Pullman 99164, WA, United States.
All India Institute of Medical Sciences, New Delhi 110029, India.
J Appl Microbiol. 2024 Jul 2;135(7). doi: 10.1093/jambio/lxae174.
Tuberculosis (TB) is a grave public health concern and is considered the foremost contributor to human mortality resulting from infectious disease. Due to the stringent clonality and extremely restricted genomic diversity, conventional methods prove inefficient for in-depth exploration of minor genomic variations and the evolutionary dynamics operating in Mycobacterium tuberculosis (M.tb) populations. Until now, the majority of reviews have primarily focused on delineating the application of whole-genome sequencing (WGS) in predicting antibiotic resistant genes, surveillance of drug resistance strains, and M.tb lineage classifications. Despite the growing use of next generation sequencing (NGS) and WGS analysis in TB research, there are limited studies that provide a comprehensive summary of there role in studying macroevolution, minor genetic variations, assessing mixed TB infections, and tracking transmission networks at an individual level. This highlights the need for systematic effort to fully explore the potential of WGS and its associated tools in advancing our understanding of TB epidemiology and disease transmission. We delve into the recent bioinformatics pipelines and NGS strategies that leverage various genetic features and simultaneous exploration of host-pathogen protein expression profile to decipher the genetic heterogeneity and host-pathogen interaction dynamics of the M.tb infections. This review highlights the potential benefits and limitations of NGS and bioinformatics tools and discusses their role in TB detection and epidemiology. Overall, this review could be a valuable resource for researchers and clinicians interested in NGS-based approaches in TB research.
结核病（TB）是一个严重的公共卫生问题，被认为是传染病导致人类死亡的首要原因。由于严格的克隆性和极其有限的基因组多样性，传统方法对于深入探索分枝杆菌（M.tb）种群中的微小基因组变异和进化动态效率不高。到目前为止，大多数综述主要侧重于阐述全基因组测序（WGS）在预测抗生素耐药基因、耐药菌株监测和 M.tb 谱系分类中的应用。尽管下一代测序（NGS）和 WGS 分析在结核病研究中的应用越来越广泛，但很少有研究全面总结了它们在研究宏观进化、微小遗传变异、评估混合结核病感染以及在个体水平上追踪传播网络方面的作用。这凸显了需要系统地努力来充分挖掘 WGS 及其相关工具在推进我们对结核病流行病学和疾病传播理解方面的潜力。我们深入探讨了最近的生物信息学管道和 NGS 策略，这些策略利用各种遗传特征和同时探索宿主-病原体蛋白表达谱，以破译 M.tb 感染的遗传异质性和宿主-病原体相互作用动态。本综述强调了 NGS 和生物信息学工具的潜在优势和局限性，并讨论了它们在结核病检测和流行病学中的作用。总的来说，对于对基于 NGS 的结核病研究方法感兴趣的研究人员和临床医生来说，这篇综述可能是一个有价值的资源。
