Evaluation of AAICare®-TB sequence analysis tool for accurate diagnosis of drug-resistant tuberculosis: A comparative study with TB-Profiler and Mykrobe

IF 2.8 3区 医学 Q3 IMMUNOLOGY Tuberculosis Pub Date : 2024-05-08 DOI:10.1016/j.tube.2024.102515
Ritu Singhal , Smita Hingane , Manpreet Bhalla , Aniruddh Sharma , Sehnaz Ferdosh , Avlokita Tiwari , Praapti Jayaswal , Raj Narayan Yadav , Jyoti Arora , Ravindra Kumar Dewan , Sangeeta Sharma
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Abstract

A rapid and comprehensive drug susceptibility test is essential for eliminating drug resistant tuberculosis. Next generation sequencing (NGS) based susceptibility testing is being explored as a potential substitute for the conventional phenotypic and genotypic testing methods. However, the adoption of NGS based genotypic susceptibility testing depends on the availability of simple, accurate and efficient analysis tools. This preliminary study aimed to evaluate the performance of a Mycobacterium tuberculosis (Mtb) genome analysis pipeline, AAICare®-TB, for susceptibility prediction, in comparison to two widely used gDST prediction tools, TB-Profiler and Mykrobe. This study was performed in a National Reference Laboratory in India on presumptive drug-resistant tuberculosis (DR-TB) isolates. Whole genome sequences of the 120 cultured isolates were obtained through Illumina sequencing on a MiSeq platform. Raw sequences were simultaneously analysed using the three tools. Susceptibility prediction reports thus generated, were compared to estimate the total concordance and discordance. WHO mutation catalogue (1st edition, 2021) was used as the reference standard for categorizing the mutations. In this study, AAICare®-TB was able to predict drug resistance status for First Line (Streptomycin, Isoniazid, Rifampicin, Ethambutol and Pyrazinamide) and Second Line drugs (Fluoroquinolones, Second Line Injectables and Ethionamide) in 93 samples along with lineage and hetero-resistance as per the WHO guidelines.

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评估 AAICare®-TB 序列分析工具对耐药结核病的准确诊断:与 TB-Profiler 和 Mykrobe 的比较研究
快速、全面的药敏试验对于消除耐药性结核病至关重要。目前正在探索基于下一代测序(NGS)的药敏试验,以替代传统的表型和基因型试验方法。然而,能否采用基于 NGS 的基因型药敏试验取决于是否有简单、准确和高效的分析工具。这项初步研究旨在评估结核分枝杆菌(Mtb)基因组分析管道 AAICare®-TB 在药敏性预测方面的性能,并与两种广泛使用的 gDST 预测工具 TB-Profiler 和 Mykrobe 进行比较。这项研究是在印度国家参考实验室对推定耐药结核病(DR-TB)分离株进行的。通过在 MiSeq 平台上进行 Illumina 测序,获得了 120 个培养分离株的全基因组序列。同时使用三种工具对原始序列进行分析。对由此生成的敏感性预测报告进行比较,以估计总的一致性和不一致性。世界卫生组织突变目录(2021 年第 1 版)被用作突变分类的参考标准。在这项研究中,AAICare®-TB 能够根据世卫组织指南预测 93 份样本中一线药物(链霉素、异烟肼、利福平、乙胺丁醇和吡嗪酰胺)和二线药物(氟喹诺酮类、二线注射剂和乙胺)的耐药性状态,以及耐药谱系和异耐药性。
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来源期刊
Tuberculosis
Tuberculosis 医学-呼吸系统
CiteScore
4.60
自引率
3.10%
发文量
87
审稿时长
49 days
期刊介绍: Tuberculosis is a speciality journal focusing on basic experimental research on tuberculosis, notably on bacteriological, immunological and pathogenesis aspects of the disease. The journal publishes original research and reviews on the host response and immunology of tuberculosis and the molecular biology, genetics and physiology of the organism, however discourages submissions with a meta-analytical focus (for example, articles based on searches of published articles in public electronic databases, especially where there is lack of evidence of the personal involvement of authors in the generation of such material). We do not publish Clinical Case-Studies. Areas on which submissions are welcomed include: -Clinical TrialsDiagnostics- Antimicrobial resistance- Immunology- Leprosy- Microbiology, including microbial physiology- Molecular epidemiology- Non-tuberculous Mycobacteria- Pathogenesis- Pathology- Vaccine development. This Journal does not accept case-reports. The resurgence of interest in tuberculosis has accelerated the pace of relevant research and Tuberculosis has grown with it, as the only journal dedicated to experimental biomedical research in tuberculosis.
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