Speeding up drug susceptibility testing in Mycobacterium tuberculosis using RNA biomarkers.

IF 9.7 1区 医学 Q1 MEDICINE, RESEARCH & EXPERIMENTAL
EBioMedicine Pub Date : 2025-03-01 Epub Date: 2025-02-25 DOI:10.1016/j.ebiom.2025.105611
Amandine Sury, Margo Maex, Alain Baulard, Roby P Bhattacharyya, Stéphanie Depickère, Deborah T Hung, Paul Cos, Fadel Sayes, Wafa Frigui, Roland Brosch, Vanessa Mathys, Elizabeth M Streicher, Frederik De Keersmaeker, Leen Rigouts, Pieter-Jan Ceyssens, An Van den Bossche
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引用次数: 0

Abstract

Background: Efficient management of drug-resistant tuberculosis relies on fast diagnostics. To accelerate phenotypic drug susceptibility testing [pDST] for Mycobacterium tuberculosis [TB], we introduce TRACeR-TB, a test that infers drug resistance from antibiotic-specific mRNA biomarkers.

Methods: To develop TRACeR-TB, target genes were first identified through RNA sequencing experiments conducted on two drug-exposed, susceptible strains for four antitubercular drugs. Based on these findings, we designed drug-specific multiplex Quantigene panels to quantify mRNA levels of 8-9 biomarkers per drug (class), directly from crude cell lysates. The performance of TRACeR-TB was compared to the widely used Mycobacteria Growth Indicator Tube [MGIT] pDST by subjecting 238 strains with diverse drug resistance profiles to both methods, and aligning results to genotypic data. Furthermore, we explored TRACeR-TB's potential for evaluating molecules that enhance antibiotic efficacy, and investigated its applicability in macrophage models to assess Mtb's intracellular stress responses to drugs.

Findings: Antituberculosis drugs trigger distinct transcriptional stress responses in susceptible, but not resistant bacilli, enabling a differentiation of the antibiotic phenotype in only 6 h. Validation on 238 strains showed TRACeR-TB had 100% (95% CI: 93·1-100%) sensitivity and 89·5% (95% CI: 74·7-97·2%) specificity compared to, respectively, 82·3% (95% CI: 69·2%-91·5%) and 94·8% (95% CI: 81·9%-99·4%) for MGIT pDST. TRACeR-TB specificity is likely underestimated due to the inclusion of isolates harbouring uncharacterised mutations. TRACeR-TB demonstrated 100% concordance with MGIT for drugs with reliable MGIT outcomes (moxifloxacin and isoniazid). Additionally, its sensitivity outperformed current rifampicin testing, detecting resistance in all borderline-resistant strains that MGIT missed, and bedaquiline testing. Furthermore, the assay detected the predicted effect of a novel drug booster and the intracellular drug-induced stress in macrophage models, highlighting its potential for drug optimisation.

Interpretation: TRACeR-TB is a complementary addition to current DSTs and can have a substantial impact on the TB diagnostics field. This tool can also play a vital role in identifying resistance mutations, thereby closing gaps in genotypic knowledge, and contribute to drug discovery and development.

Funding: Institut Pasteur, Agence Nationale de la Recherche.

利用RNA生物标志物加快结核分枝杆菌药敏试验。
背景:耐药结核病的有效管理依赖于快速诊断。为了加速结核分枝杆菌的表型药敏试验[pDST],我们引入了TRACeR-TB,这是一种通过抗生素特异性mRNA生物标志物推断耐药性的测试。方法:为开发TRACeR-TB,首先对2株药物暴露、对4种抗结核药物敏感的菌株进行RNA测序实验,鉴定靶基因。基于这些发现,我们设计了药物特异性多重定量基因面板,直接从粗细胞裂解物中定量每种药物(类别)8-9个生物标志物的mRNA水平。将238株具有不同耐药谱的分枝杆菌生长指示管(mycobacterium Growth Indicator Tube [MGIT] pDST)与TRACeR-TB进行比较,并将结果与基因型数据进行比对。此外,我们探索了TRACeR-TB在评估增强抗生素疗效分子方面的潜力,并研究了其在巨噬细胞模型中的适用性,以评估结核分枝杆菌对药物的细胞内应激反应。结果:抗结核药物在敏感而非耐药杆菌中引发明显的转录应激反应,仅在6小时内就能分化出抗生素表型。对238株菌株的验证表明,TRACeR-TB具有100% (95% CI: 93.1 -100%)的敏感性和89.5% (95% CI: 74.5 - 97.2)的特异性,而MGIT pDST分别为82.3% (95% CI: 69.2 - 99.5%)和94.8% (95% CI: 89.1 - 99.4%)。TRACeR-TB的特异性可能被低估了,因为包含了含有未表征突变的分离株。对于具有可靠MGIT结果的药物(莫西沙星和异烟肼),TRACeR-TB显示与MGIT 100%一致。此外,它的灵敏度优于当前的利福平试验,检测出MGIT遗漏的所有临界耐药菌株的耐药性,以及贝达喹啉试验。此外,该分析还检测了一种新型药物增强剂的预测效果和巨噬细胞模型中细胞内药物诱导的应激,突出了其药物优化的潜力。解释:TRACeR-TB是对现有DSTs的补充,可以对结核病诊断领域产生重大影响。该工具还可以在鉴定耐药突变方面发挥重要作用,从而缩小基因型知识方面的差距,并有助于药物发现和开发。资助:巴斯德研究所,法国国家研究机构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
EBioMedicine
EBioMedicine Biochemistry, Genetics and Molecular Biology-General Biochemistry,Genetics and Molecular Biology
CiteScore
17.70
自引率
0.90%
发文量
579
审稿时长
5 weeks
期刊介绍: eBioMedicine is a comprehensive biomedical research journal that covers a wide range of studies that are relevant to human health. Our focus is on original research that explores the fundamental factors influencing human health and disease, including the discovery of new therapeutic targets and treatments, the identification of biomarkers and diagnostic tools, and the investigation and modification of disease pathways and mechanisms. We welcome studies from any biomedical discipline that contribute to our understanding of disease and aim to improve human health.
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