Yu Ling-Shan, Rodriguez-Manzano Jesus, Moser Nicolas, Moniri Ahmad, Malpartida-Cardenas Kenny, Miscourides Nicholas, Sewell Thomas, Kochina Tatiana, Brackin Amelie, Rhodes Johanna, Holmes Alison H, Fisher Matthew C, Georgiou Pantelis
Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, United Kingdom.
Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, United Kingdom
J Clin Microbiol. 2020 Oct 21;58(11). doi: 10.1128/JCM.00843-20.
has widely evolved resistance to the most commonly used class of antifungal chemicals, the azoles. Current methods for identifying azole resistance are time-consuming and depend on specialized laboratories. There is an urgent need for rapid detection of these emerging pathogens at point-of-care to provide the appropriate treatment in the clinic and to improve management of environmental reservoirs to mitigate the spread of antifungal resistance. Our study demonstrates the rapid and portable detection of the two most relevant genetic markers linked to azole resistance, the mutations TR34 and TR46, found in the promoter region of the gene encoding the azole target 51A. We developed a lab-on-a-chip platform consisting of: (i) tandem-repeat loop-mediated isothermal amplification; (ii) state-of-the-art complementary metal-oxide-semiconductor microchip technology for nucleic acid amplification detection; and (iii) a smartphone application for data acquisition, visualization, and cloud connectivity. Specific and sensitive detection was validated with isolates from clinical and environmental samples from 6 countries across 5 continents, showing a lower limit of detection of 10 genomic copies per reaction in less than 30 min. When fully integrated with a sample preparation module, this diagnostic system will enable the detection of this ubiquitous fungus at the point-of-care, and could help to improve clinical decision making, infection control, and epidemiological surveillance.
已对最常用的一类抗真菌化学药物——唑类广泛产生耐药性。目前鉴定唑类耐药性的方法耗时且依赖专业实验室。迫切需要在护理点快速检测这些新出现的病原体,以便在临床中提供适当治疗,并改善对环境储存库的管理,以减轻抗真菌耐药性的传播。我们的研究展示了对与唑类耐药性相关的两个最关键基因标记——在编码唑类靶点51A的基因启动子区域发现的TR34和TR46突变的快速便捷检测。我们开发了一种芯片实验室平台,其包括:(i)串联重复环介导的等温扩增;(ii)用于核酸扩增检测的最先进的互补金属氧化物半导体微芯片技术;以及(iii)用于数据采集、可视化和云连接的智能手机应用程序。通过来自五大洲6个国家的临床和环境样本分离株验证了特异性和灵敏性检测,显示在不到30分钟内每个反应的检测下限为10个基因组拷贝。当与样品制备模块完全集成时,这种诊断系统将能够在护理点检测这种普遍存在的真菌,并有助于改善临床决策、感染控制和流行病学监测。