Department of Pathology & Laboratory Medicine, Medicine, and Microbiology, Immunology and Infectious Diseases, University of Calgary, Calgary, Alberta, Canada.
Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, Alberta, Canada.
J Clin Microbiol. 2024 Nov 13;62(11):e0086924. doi: 10.1128/jcm.00869-24. Epub 2024 Oct 24.
Pathogenic gram-negative bacteria frequently carry genes encoding extended-spectrum beta-lactamases (ESBL) and/or carbapenemases. Of great concern are carbapenem resistant , , and . Despite the need for rapid AMR diagnostics globally, current molecular detection methods often require expensive equipment and trained personnel. Here, we present a novel machine-learning-aided platform for the rapid detection of ESBLs and carbapenemases using Loop-mediated isothermal Amplification (LAMP). The platform consists of (i) an affordable device for sample lysis, LAMP amplification, and visual fluorometric detection; (ii) a LAMP screening panel to detect the most common ESBL and carbapenemase genes; and (iii) a smartphone application for automated interpretation of results. Validation studies on clinical isolates and urine samples demonstrated percent positive and negative agreements above 95% for all targets. Accuracy, precision, and recall values of the machine learning model deployed in the smartphone application were all above 92%. Providing a simplified workflow, minimal operation training, and results in less than an hour, this study demonstrated the platform's feasibility for near-patient testing in resource-limited settings.IMPORTANCEExtended-spectrum beta-lactamases (ESBL) and carbapenemases confer resistance to third-generation cephalosporins and carbapenems in pathogenic Gram-negative bacteria such as , , and . Conventional antimicrobial susceptibility testing is based on phenotypic methods, and results can take several days to be obtained. Current genotypic detection methods can be rapid but require expensive equipment and trained personnel. In this study, we present a novel machine learning-aided platform for the rapid detection of ESBLs and carbapenemases using Loop-mediated isothermal Amplification (LAMP). The validation of the platform demonstrated percent positive and negative agreements above 95% for all targets. The newly developed platform provided a simplified workflow, minimal technical training, and results in less than an hour. This study demonstrated the platform's feasibility for rapid testing of ESBL and carbapenemases in bacteria and urine specimens.
致病革兰氏阴性菌经常携带编码超广谱β-内酰胺酶(ESBL)和/或碳青霉烯酶的基因。令人担忧的是耐碳青霉烯的 、 、 。尽管全球都需要快速的 AMR 诊断,但目前的分子检测方法通常需要昂贵的设备和经过培训的人员。在这里,我们提出了一种使用环介导等温扩增(LAMP)快速检测 ESBL 和碳青霉烯酶的新型机器学习辅助平台。该平台包括(i)用于样品裂解、LAMP 扩增和可视化荧光检测的经济实惠的设备;(ii)用于检测最常见的 ESBL 和碳青霉烯酶基因的 LAMP 筛选面板;(iii)用于自动解释结果的智能手机应用程序。对临床分离株和尿液样本的验证研究表明,所有靶标阳性和阴性的符合率均超过 95%。部署在智能手机应用程序中的机器学习模型的准确性、精密度和召回率均高于 92%。该研究证明,该平台在资源有限的环境中具有用于床边检测的可行性,提供了简化的工作流程、最少的操作培训,并且在不到一个小时内即可获得结果。