Department of Biochemistry and Molecular Biology, Bio21 Institute, University of Melbourne, Victoria, 3010, Australia.
Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, 3004, VIC, Australia.
Sci Rep. 2020 Oct 22;10(1):18120. doi: 10.1038/s41598-020-74648-y.
Rifampicin resistance is a major therapeutic challenge, particularly in tuberculosis, leprosy, P. aeruginosa and S. aureus infections, where it develops via missense mutations in gene rpoB. Previously we have highlighted that these mutations reduce protein affinities within the RNA polymerase complex, subsequently reducing nucleic acid affinity. Here, we have used these insights to develop a computational rifampicin resistance predictor capable of identifying resistant mutations even outside the well-defined rifampicin resistance determining region (RRDR), using clinical M. tuberculosis sequencing information. Our tool successfully identified up to 90.9% of M. tuberculosis rpoB variants correctly, with sensitivity of 92.2%, specificity of 83.6% and MCC of 0.69, outperforming the current gold-standard GeneXpert-MTB/RIF. We show our model can be translated to other clinically relevant organisms: M. leprae, P. aeruginosa and S. aureus, despite weak sequence identity. Our method was implemented as an interactive tool, SUSPECT-RIF (StrUctural Susceptibility PrEdiCTion for RIFampicin), freely available at https://biosig.unimelb.edu.au/suspect_rif/ .
利福平耐药是一个主要的治疗挑战，特别是在结核病、麻风病、铜绿假单胞菌和金黄色葡萄球菌感染中，它是通过基因 rpoB 中的错义突变发展而来的。此前，我们已经强调过，这些突变会降低 RNA 聚合酶复合物内的蛋白质亲和力，从而降低核酸亲和力。在这里，我们利用这些见解开发了一种计算性利福平耐药预测器，即使在定义明确的利福平耐药决定区（RRDR）之外，也可以使用临床结核分枝杆菌测序信息来识别耐药突变。我们的工具成功地正确识别了高达 90.9%的结核分枝杆菌 rpoB 变体，具有 92.2%的灵敏度、83.6%的特异性和 0.69 的 MCC，优于当前的金标准 GeneXpert-MTB/RIF。我们表明，尽管序列同一性较弱，我们的模型可以转化为其他临床相关的生物体：麻风分枝杆菌、铜绿假单胞菌和金黄色葡萄球菌。我们的方法被实现为一个交互式工具，名为 SUSPECT-RIF（用于利福平的结构易感性预测），可在 https://biosig.unimelb.edu.au/suspect_rif/ 上免费获得。
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