BACKGROUND Mycobacterium tuberculosis resistance to anti-tuberculosis drugs is a major threat to global public health. Whole genome sequencing (WGS) is rapidly gaining traction as a diagnostic tool for clinical tuberculosis settings. To support this informatically, previous work led to the development of the widely used TBProfiler webtool, which predicts resistance to 14 drugs from WGS data. However, for accurate and rapid high throughput of samples in clinical or epidemiological settings, there is a need for a stand-alone tool and the ability to analyse data across multiple WGS platforms, including Oxford Nanopore MinION. RESULTS We present a new command line version of the TBProfiler webserver, which includes hetero-resistance calling and will facilitate the batch processing of samples. The TBProfiler database has been expanded to incorporate 178 new markers across 16 anti-tuberculosis drugs. The predictive performance of the mutation library has been assessed using > 17,000 clinical isolates with WGS and laboratory-based drug susceptibility testing (DST) data. An integrated MinION analysis pipeline was assessed by performing WGS on 34 replicates across 3 multi-drug resistant isolates with known resistance mutations. TBProfiler accuracy varied by individual drug. Assuming DST as the gold standard, sensitivities for detecting multi-drug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) were 94% (95%CI 93-95%) and 83% (95%CI 79-87%) with specificities of 98% (95%CI 98-99%) and 96% (95%CI 95-97%) respectively. Using MinION data, only one resistance mutation was missed by TBProfiler, involving an insertion in the tlyA gene coding for capreomycin resistance. When compared to alternative platforms (e.g. Mykrobe predictor TB, the CRyPTIC library), TBProfiler demonstrated superior predictive performance across first- and second-line drugs. CONCLUSIONS The new version of TBProfiler can rapidly and accurately predict anti-TB drug resistance profiles across large numbers of samples with WGS data. The computing architecture allows for the ability to modify the core bioinformatic pipelines and outputs, including the analysis of WGS data sourced from portable technologies. TBProfiler has the potential to be integrated into the point of care and WGS diagnostic environments, including in resource-poor settings.

中文翻译：

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结合信息学工具和便携式测序技术，快速检测抗结核药物耐药性。

背景结核分枝杆菌对抗结核药物的耐药性是对全球公共卫生的主要威胁。全基因组测序 (WGS) 作为临床结核病环境的诊断工具正迅速受到关注。为了在信息上支持这一点，之前的工作导致了广泛使用的 TBProfiler 网络工具的开发，该工具可以根据 WGS 数据预测对 14 种药物的耐药性。然而，为了在临床或流行病学环境中准确、快速地获得高通量样本，需要一个独立的工具以及跨多个 WGS 平台（包括 Oxford Nanopore MinION）分析数据的能力。结果 我们提出了 TBProfiler 网络服务器的新命令行版本，其中包括异质抗性调用并将促进样本的批处理。TBProfiler 数据库已扩展为包含 16 种抗结核药物的 178 个新标记。突变文库的预测性能已使用 > 17,000 种临床分离株以及 WGS 和基于实验室的药物敏感性测试 (DST) 数据进行评估。通过对 3 个具有已知耐药突变的多重耐药分离株的 34 次重复进行 WGS，评估了集成的 MinION 分析管道。TBProfiler 的准确性因个别药物而异。假设 DST 作为金标准，检测耐多药结核病 (MDR-TB) 和广泛耐药结核病 (XDR-TB) 的敏感性分别为 94% (95%CI 93-95%) 和 83% (95%) CI 79-87%)，特异性分别为 98% (95%CI 98-99%) 和 96% (95%CI 95-97%)。使用 MinION 数据，TBProfiler 仅遗漏了一个抗性突变，涉及插入编码卷曲霉素抗性的 tlyA 基因。与替代平台（例如 Mykrobe 预测因子 TB、CRyPTIC 库）相比，TBProfiler 展示了对一线和二线药物的卓越预测性能。结论 新版本的 TBProfiler 可以使用 WGS 数据快速准确地预测大量样本的抗结核药物耐药性概况。计算架构允许修改核心生物信息学管道和输出的能力，包括分析源自便携式技术的 WGS 数据。TBProfiler 有可能被集成到护理点和 WGS 诊断环境中，包括在资源贫乏的环境中。CRyPTIC 库），TBProfiler 展示了对一线和二线药物的卓越预测性能。结论 新版本的 TBProfiler 可以使用 WGS 数据快速准确地预测大量样本的抗结核药物耐药性概况。计算架构允许修改核心生物信息学管道和输出的能力，包括分析源自便携式技术的 WGS 数据。TBProfiler 有可能被集成到护理点和 WGS 诊断环境中，包括在资源贫乏的环境中。CRyPTIC 库），TBProfiler 展示了对一线和二线药物的卓越预测性能。结论 新版本的 TBProfiler 可以使用 WGS 数据快速准确地预测大量样本的抗结核药物耐药性概况。计算架构允许修改核心生物信息学管道和输出的能力，包括分析源自便携式技术的 WGS 数据。TBProfiler 有可能被集成到护理点和 WGS 诊断环境中，包括在资源贫乏的环境中。计算架构允许修改核心生物信息学管道和输出的能力，包括分析源自便携式技术的 WGS 数据。TBProfiler 有可能被集成到护理点和 WGS 诊断环境中，包括在资源贫乏的环境中。计算架构允许修改核心生物信息学管道和输出的能力，包括分析源自便携式技术的 WGS 数据。TBProfiler 有可能被集成到护理点和 WGS 诊断环境中，包括在资源贫乏的环境中。