A novel machine-learning aided platform for rapid detection of urine ESBLs and carbapenemases: URECA-LAMP.

IF 6.1 2区 医学 Q1 MICROBIOLOGY
Journal of Clinical Microbiology Pub Date : 2024-11-13 Epub Date: 2024-10-24 DOI:10.1128/jcm.00869-24
L Ricardo Castellanos, Ryan Chaffee, Hitendra Kumar, Biniyam Kahsay Mezgebo, Pawulos Kassau, Gisele Peirano, Johann D D Pitout, Keekyoung Kim, Dylan R Pillai
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引用次数: 0

Abstract

Pathogenic gram-negative bacteria frequently carry genes encoding extended-spectrum beta-lactamases (ESBL) and/or carbapenemases. Of great concern are carbapenem resistant Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Acinetobacter baumannii. 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 Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Acinetobacter baumannii. 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.

用于快速检测尿液中 ESBLs 和碳青霉烯酶的新型机器学习辅助平台:URECA-LAMP。
致病性革兰氏阴性菌经常携带编码广谱β-内酰胺酶(ESBL)和/或碳青霉烯酶的基因。耐碳青霉烯类的大肠埃希菌、肺炎克雷伯氏菌、铜绿假单胞菌和鲍曼不动杆菌最令人担忧。尽管全球都需要快速的 AMR 诊断,但目前的分子检测方法往往需要昂贵的设备和训练有素的人员。在此,我们介绍一种新型机器学习辅助平台,利用环路介导等温扩增(LAMP)技术快速检测 ESBLs 和碳青霉烯酶。该平台包括:(i) 用于样品裂解、LAMP 扩增和可视荧光检测的经济型设备;(ii) 用于检测最常见 ESBL 和碳青霉烯酶基因的 LAMP 筛选面板;(iii) 用于自动解读结果的智能手机应用程序。对临床分离物和尿液样本进行的验证研究表明,所有目标的阳性和阴性一致率均超过 95%。智能手机应用中部署的机器学习模型的准确度、精确度和召回值均超过 92%。这项研究提供了简化的工作流程、最少的操作培训和不到一小时的结果,证明了该平台在资源有限的环境中进行就近病人检测的可行性。重要意义扩展谱β-内酰胺酶(ESBL)和碳青霉烯酶使大肠埃希菌、肺炎克雷伯菌、铜绿假单胞菌和鲍曼不动杆菌等致病性革兰氏阴性菌对第三代头孢菌素和碳青霉烯类产生耐药性。传统的抗菌药敏感性检测以表型法为基础,需要几天时间才能得出结果。目前的基因型检测方法虽然快速,但需要昂贵的设备和训练有素的人员。在本研究中,我们提出了一种新型机器学习辅助平台,利用环路介导等温扩增法(LAMP)快速检测 ESBLs 和碳青霉烯酶。该平台的验证结果表明,所有目标的阳性和阴性一致率均超过 95%。新开发的平台简化了工作流程,只需极少的技术培训,不到一小时就能得出结果。这项研究证明了该平台在快速检测细菌和尿液标本中的 ESBL 和碳青霉烯酶方面的可行性。
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
Journal of Clinical Microbiology
Journal of Clinical Microbiology 医学-微生物学
CiteScore
17.10
自引率
4.30%
发文量
347
审稿时长
3 months
期刊介绍: The Journal of Clinical Microbiology® disseminates the latest research concerning the laboratory diagnosis of human and animal infections, along with the laboratory's role in epidemiology and the management of infectious diseases.
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