The National Institute for Health Research (NIHR) Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, United Kingdom
Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
J Clin Microbiol. 2018 Jan 24;56(2). doi: 10.1128/JCM.01480-17. Print 2018 Feb.
Use of whole-genome sequencing (WGS) for routine mycobacterial species identification and drug susceptibility testing (DST) is becoming a reality. We compared the performances of WGS and standard laboratory workflows prospectively, by parallel processing at a major mycobacterial reference service over the course of 1 year, for species identification, first-line resistance prediction, and turnaround time. Among 2,039 isolates with line probe assay results for species identification, 74 (3.6%) failed sequencing or WGS species identification. Excluding these isolates, clinically important species were identified for 1,902 isolates, of which 1,825 (96.0%) were identified as the same species by WGS and the line probe assay. A total of 2,157 line probe test results for detection of resistance to the first-line drugs isoniazid and rifampin were available for 728 complex isolates. Excluding 216 (10.0%) cases where there were insufficient sequencing data for WGS to make a prediction, overall concordance was 99.3% (95% confidence interval [CI], 98.9 to 99.6%), sensitivity was 97.6% (91.7 to 99.7%), and specificity was 99.5% (99.0 to 99.7%). A total of 2,982 phenotypic DST results were available for 777 complex isolates. Of these, 356 (11.9%) had no WGS comparator due to insufficient sequencing data, and in 154 (5.2%) cases the WGS prediction was indeterminate due to discovery of novel, previously uncharacterized mutations. Excluding these data, overall concordance was 99.2% (98.7 to 99.5%), sensitivity was 94.2% (88.4 to 97.6%), and specificity was 99.4% (99.0 to 99.7%). Median processing times for the routine laboratory tests versus WGS were similar overall, i.e., 20 days (interquartile range [IQR], 15 to 31 days) and 21 days (15 to 29 days), respectively ( = 0.41). In conclusion, WGS predicts species and drug susceptibility with great accuracy, but work is needed to increase the proportion of predictions made.
全基因组测序(WGS)用于常规分枝杆菌菌种鉴定和药物敏感性测试(DST)正在成为现实。我们通过在主要分枝杆菌参考服务机构进行为期 1 年的平行处理,前瞻性地比较了 WGS 和标准实验室工作流程的性能,以评估菌种鉴定、一线耐药预测和周转时间。在有线性探针检测结果的 2039 株分离株中,有 74 株(3.6%)测序或 WGS 菌种鉴定失败。排除这些分离株,对 1902 株临床重要的分离株进行了菌种鉴定,其中 1825 株(96.0%)通过 WGS 和线性探针检测鉴定为同一菌种。共有 2157 个用于检测一线药物异烟肼和利福平耐药性的线探针检测结果可用于 728 株复杂分离株。排除 216 例(10.0%)因 WGS 测序数据不足无法进行预测的病例,总体符合率为 99.3%(95%置信区间[CI],98.9 至 99.6%),敏感性为 97.6%(91.7 至 99.7%),特异性为 99.5%(99.0 至 99.7%)。共有 2982 个表型 DST 结果可用于 777 株复杂分离株。其中,由于测序数据不足,有 356 株(11.9%)没有 WGS 对照,有 154 株(5.2%)由于发现新的、以前未描述的突变,WGS 预测不确定。排除这些数据,总体符合率为 99.2%(98.7 至 99.5%),敏感性为 94.2%(88.4 至 97.6%),特异性为 99.4%(99.0 至 99.7%)。常规实验室检测与 WGS 的总体处理时间相似,分别为 20 天(四分位距[IQR],15 至 31 天)和 21 天(15 至 29 天)( = 0.41)。总之,WGS 对菌种和药物敏感性的预测具有很高的准确性,但需要做更多工作以提高预测的比例。