Department of Medicine, Rutgers New Jersey Medical School, Newark, New Jersey, USA.
Cepheid Inc., Sunnyvale, California, USA.
J Clin Microbiol. 2019 Dec 23;58(1). doi: 10.1128/JCM.00907-19.
Molecular surveillance of rifampin-resistant can help to monitor the transmission of the disease. The Xpert MTB/RIF Ultra assay detects mutations in the rifampin resistance-determining region (RRDR) of the gene by the use of melting temperature ( ) information from 4 probes which can fall in one of the 9 different assay-specified windows. The large amount of data generated by the assay offers the possibility of an RRDR genotyping approach more accessible than whole-genome sequencing. In this study, we developed an automated algorithm to specifically identify a wide range of mutations in the RRDR by utilizing the pattern of the of the 4 probes within the 9 windows generated by the Ultra assay. The algorithm builds a RRDR mutation-specific " signature" reference library from a set of known mutations and then identifies the RRDR genotype of an unknown sample by measuring the distances between the test sample and the reference values. Validated using a set of clinical isolates, the algorithm correctly identified RRDR genotypes of 93% samples with a wide range of single and double mutations. Our analytical approach showed a great potential for fast RRDR mutation identification and may also be used as a stand-alone method for ruling out relapse or transmission between patients. The algorithm can be further modified and optimized for higher accuracy as more Ultra data become available.
利福平耐药的分子监测有助于监测疾病的传播。Xpert MTB/RIF Ultra 检测通过使用来自 4 个探针的熔解温度()信息来检测基因中的利福平耐药决定区(RRDR)突变,这 4 个探针可以落入 9 个不同检测指定窗口中的一个。该检测产生的大量数据提供了一种比全基因组测序更容易获得的 RRDR 基因分型方法的可能性。在这项研究中,我们开发了一种自动化算法,通过利用 Ultra 检测中 9 个窗口内 4 个探针的模式,专门识别 RRDR 中的广泛突变。该算法从一组已知突变构建 RRDR 突变特异性“特征”参考库,然后通过测量测试样本与参考值之间的距离来确定未知样本的 RRDR 基因型。该算法使用一组临床分离株进行验证,正确识别了 93%具有广泛单突变和双突变的样本的 RRDR 基因型。我们的分析方法显示出快速 RRDR 突变识别的巨大潜力,也可作为排除患者之间复发或传播的独立方法。随着更多 Ultra 数据的出现,该算法可以进一步修改和优化以提高准确性。