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GenoMycAnalyzer:一个基于网络的工具,用于预测分枝杆菌基因组的物种和耐药性。

GenoMycAnalyzer: a web-based tool for species and drug resistance prediction for Mycobacterium genomes.

机构信息

Department of Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea, Seoul, Korea.

Integrated Research Center for Genomic Polymorphism, Precision Medicine Research Center, College of Medicine, The Catholic University of Korea, Seoul, Korea.

出版信息

BMC Genomics. 2024 Apr 20;25(1):387. doi: 10.1186/s12864-024-10320-3.

Abstract

BACKGROUND

Drug-resistant tuberculosis (TB) is a major threat to global public health. Whole-genome sequencing (WGS) is a useful tool for species identification and drug resistance prediction, and many clinical laboratories are transitioning to WGS as a routine diagnostic tool. However, user-friendly and high-confidence automated bioinformatics tools are needed to rapidly identify M. tuberculosis complex (MTBC) and non-tuberculous mycobacteria (NTM), detect drug resistance, and further guide treatment options.

RESULTS

We developed GenoMycAnalyzer, a web-based software that integrates functions for identifying MTBC and NTM species, lineage and spoligotype prediction, variant calling, annotation, drug-resistance determination, and data visualization. The accuracy of GenoMycAnalyzer for genotypic drug susceptibility testing (gDST) was evaluated using 5,473 MTBC isolates that underwent phenotypic DST (pDST). The GenoMycAnalyzer database was built to predict the gDST for 15 antituberculosis drugs using the World Health Organization mutational catalogue. Compared to pDST, the sensitivity of drug susceptibilities by the GenoMycAnalyzer for first-line drugs ranged from 95.9% for rifampicin (95% CI 94.8-96.7%) to 79.6% for pyrazinamide (95% CI 76.9-82.2%), whereas those for second-line drugs ranged from 98.2% for levofloxacin (95% CI 90.1-100.0%) to 74.9% for capreomycin (95% CI 69.3-80.0%). Notably, the integration of large deletions of the four resistance-conferring genes increased gDST sensitivity. The specificity of drug susceptibilities by the GenoMycAnalyzer ranged from 98.7% for amikacin (95% CI 97.8-99.3%) to 79.5% for ethionamide (95% CI 76.4-82.3%). The incorporated Kraken2 software identified 1,284 mycobacterial species with an accuracy of 98.8%. GenoMycAnalyzer also perfectly predicted lineages for 1,935 MTBC and spoligotypes for 54 MTBC.

CONCLUSIONS

GenoMycAnalyzer offers both web-based and graphical user interfaces, which can help biologists with limited access to high-performance computing systems or limited bioinformatics skills. By streamlining the interpretation of WGS data, the GenoMycAnalyzer has the potential to significantly impact TB management and contribute to global efforts to combat this infectious disease. GenoMycAnalyzer is available at http://www.mycochase.org .

摘要

背景

耐药结核病(TB)是对全球公共卫生的重大威胁。全基因组测序(WGS)是一种用于物种鉴定和耐药预测的有用工具,许多临床实验室正在将 WGS 转化为常规诊断工具。然而,需要用户友好且高可信度的自动化生物信息学工具来快速识别结核分枝杆菌复合体(MTBC)和非结核分枝杆菌(NTM),检测耐药性,并进一步指导治疗选择。

结果

我们开发了 GenoMycAnalyzer,这是一种基于网络的软件,集成了识别 MTBC 和 NTM 物种、谱系和 spoligotype 预测、变体调用、注释、耐药性确定和数据可视化的功能。使用经过表型 DST(pDST)的 5473 株 MTBC 分离株评估了 GenoMycAnalyzer 用于基因型药物敏感性测试(gDST)的准确性。GenoMycAnalyzer 数据库用于使用世界卫生组织突变目录预测 15 种抗结核药物的 gDST。与 pDST 相比,GenoMycAnalyzer 对一线药物的药物敏感性的敏感性范围为 95.9%(利福平,95%CI 94.8-96.7%)至 79.6%(吡嗪酰胺,95%CI 76.9-82.2%),而二线药物的敏感性范围为 98.2%(左氧氟沙星,95%CI 90.1-100.0%)至 74.9%(卷曲霉素,95%CI 69.3-80.0%)。值得注意的是,四个耐药相关基因的大片段缺失的整合提高了 gDST 的敏感性。GenoMycAnalyzer 对药物敏感性的特异性范围为 98.7%(阿米卡星,95%CI 97.8-99.3%)至 79.5%(乙胺丁醇,95%CI 76.4-82.3%)。合并的 Kraken2 软件准确识别了 1284 种分枝杆菌物种,准确率为 98.8%。GenoMycAnalyzer 还可以完美预测 1935 株 MTBC 的谱系和 54 株 MTBC 的 spoligotype。

结论

GenoMycAnalyzer 提供了基于网络和图形用户界面的功能,这可以帮助那些访问高性能计算系统有限或生物信息学技能有限的生物学家。通过简化 WGS 数据的解释,GenoMycAnalyzer 有可能对结核病管理产生重大影响,并为全球抗击这种传染病的努力做出贡献。GenoMycAnalyzer 可在 http://www.mycochase.org 上获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50ff/11031912/762e7c95ca70/12864_2024_10320_Fig1_HTML.jpg

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