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评估 AAICare®-TB 序列分析工具在耐药结核病准确诊断中的应用:与 TB-Profiler 和 Mykrobe 的比较研究。

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

机构信息

Department of Microbiology, National Institute of Tuberculosis and Respiratory Diseases, New Delhi, 110030, India.

AarogyaAI® Innovations Pvt. Ltd., No. 677, 1st Floor, Suite 918, 13th Cross, Sector 1, HSR Layout, Bangalore, 560102, Karnataka, India.

出版信息

Tuberculosis (Edinb). 2024 Jul;147:102515. doi: 10.1016/j.tube.2024.102515. Epub 2024 May 8.

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.

摘要

快速全面的药敏试验对于消除耐药结核病至关重要。下一代测序(NGS)基于药敏试验正在探索作为传统表型和基因型检测方法的潜在替代品。然而,基于 NGS 的基因型药敏试验的采用取决于简单、准确和高效的分析工具的可用性。本初步研究旨在评估一种结核分枝杆菌(Mtb)基因组分析管道 AAICare®-TB 的性能,用于药敏预测,与两种广泛使用的 gDST 预测工具 TB-Profiler 和 Mykrobe 进行比较。该研究在印度的一个国家参考实验室进行,针对疑似耐药结核病(DR-TB)分离株。通过 MiSeq 平台上的 Illumina 测序获得了 120 个培养分离株的全基因组序列。使用三种工具同时分析原始序列。生成的药敏预测报告用于比较以估计总一致性和不一致性。将世界卫生组织(WHO)突变目录(第一版,2021 年)用作分类突变的参考标准。在这项研究中,AAICare®-TB 能够根据世卫组织指南预测 93 个样本中一线(链霉素、异烟肼、利福平、乙胺丁醇和吡嗪酰胺)和二线药物(氟喹诺酮类药物、二线注射剂和乙硫异烟胺)的耐药状态,以及谱系和异质性耐药。

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