Tamrakar Vaibhav Kumar, Parihar Nitish Singh, Bhat Jyothi, Rajasubramaniam S
ICMR - National Institute of Research in Tribal Health, Jabalpur, Madhya Pradesh India.
Madhya Pradesh Medical Science University, Jabalpur, Madhya Pradesh India.
Indian J Microbiol. 2024 Jun;64(2):758-761. doi: 10.1007/s12088-023-01134-0. Epub 2023 Nov 30.
In India, drug-resistant tuberculosis (DR-TB) is a major public health issue and a significant challenge to stop TB program. An estimated 27% of new TB cases and 44% of previously treated TB cases are resistant to at least one anti-TB drug. The conventional methods for DR-TB diagnosis are time-consuming and have limitations, leading to delays in treatment initiation and the spread of the disease. Next-generation sequencing (NGS) based approaches have emerged as a promising tool for diagnosing DR-TB, simultaneously offering rapid and accurate detection of resistance mutations in multiple genes. NGS-based approaches generate a large amount of data, which requires efficient and reliable bioinformatics pipelines for data analysis. TBProfiler and Mykrobe are the bioinformatics pipelines that have been created to analyze NGS data for the diagnosis of DR-TB. These pipelines use reference-based and machine-learning approaches to detect resistance mutations and predict drug susceptibility, enabling clinicians to make informed treatment decisions. Implementing NGS-based approaches and bioinformatics pipelines for DR-TB diagnosis can potentially improve patient outcomes by facilitating early detection of drug resistance and guiding personalized treatment regimens. However, the widespread adoption of these approaches in India faces several challenges, including high costs, limited infrastructure, and a lack of trained personnel. Addressing these challenges requires concerted effort to ensure equitable access to and effective implementation of these innovative technologies.
在印度，耐多药结核病（DR-TB）是一个重大的公共卫生问题，也是结核病防治计划面临的一项重大挑战。据估计，27%的新发结核病病例和44%既往接受过治疗的结核病病例对至少一种抗结核药物耐药。传统的耐多药结核病诊断方法耗时且有局限性，导致治疗开始延迟和疾病传播。基于新一代测序（NGS）的方法已成为诊断耐多药结核病的一种有前景的工具，同时能快速准确地检测多个基因中的耐药突变。基于NGS的方法会生成大量数据，这需要高效且可靠的生物信息学流程来进行数据分析。TBProfiler和Mykrobe就是为分析用于诊断耐多药结核病的NGS数据而创建的生物信息学流程。这些流程使用基于参考的方法和机器学习方法来检测耐药突变并预测药物敏感性，使临床医生能够做出明智的治疗决策。实施基于NGS的方法和生物信息学流程用于耐多药结核病诊断，有可能通过促进耐药性的早期检测和指导个性化治疗方案来改善患者预后。然而，在印度广泛采用这些方法面临若干挑战，包括成本高昂、基础设施有限以及缺乏训练有素的人员。应对这些挑战需要共同努力，以确保公平获取并有效实施这些创新技术。
