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用于集成式自动无标记病原体检测的自干扰数字光流体基因分型

Self-Interference Digital Optofluidic Genotyping for Integrated and Automated Label-Free Pathogen Detection.

作者信息

Zhou Tianqi, Fu Rongxin, Hou Jialu, Yang Fan, Chai Fengli, Mao Zeyin, Deng Anni, Li Fenggang, Guan Yanfang, Hu Hanqi, Li Hang, Lu Yao, Huang Guoliang, Zhang Shuailong, Xie Huikai

机构信息

School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China.

Zhengzhou Research Institute, Beijing Institute of Technology, Zhengzhou, Henan 450000, China.

出版信息

ACS Sens. 2024 Dec 27;9(12):6411-6420. doi: 10.1021/acssensors.4c01520. Epub 2024 Nov 19.

DOI:10.1021/acssensors.4c01520
PMID:39561298
Abstract

Pathogen, prevalent in both natural and human environments, cause approximately 4.95 million deaths annually, ranking them among the top contributors to global mortality. Traditional pathogen detection methods, reliant on microscopy and cultivation, are slow and labor-intensive and often produce subjective results. While nucleic acid amplification techniques such as polymerase chain reaction offer genetic accuracy, they necessitate costly laboratory equipment and skilled personnel. Consequently, isothermal amplification methods like recombinase polymerase amplification (RPA) have attracted interest for their rapid and straightforward operations. However, these methods face challenges in specificity and automated sample processing. In this study, we introduce a self-interferometric digital optofluidic platform incorporating asymmetric direct solid-phase RPA for real-time, label-free, and automated pathogen genotyping. By integration of digital microfluidics with a DNA monolayer detection method using hyperspectral interferometry, this platform enables rapid, specific, and sensitive pathogen detection without the need for exogenous labeling or complex procedures. The system demonstrated high sensitivity (10 CFU·mL), specificity (differentiating four species), detection efficiency (fully automated within 50 min for Gram-negative bacteria), and throughput (simultaneous detection of four indices). This integrated approach to pathogen quantitation on a single microfluidic chip represents a significant advancement in rapid pathogen diagnostics, providing a practical solution for timely pathogen detection and analysis.

摘要

病原体在自然环境和人类环境中都很普遍,每年导致约495万人死亡,是全球死亡率的主要贡献因素之一。传统的病原体检测方法依赖显微镜检查和培养,速度慢且劳动强度大,结果往往主观。虽然聚合酶链反应等核酸扩增技术具有基因准确性,但需要昂贵的实验室设备和技术人员。因此,重组酶聚合酶扩增(RPA)等温扩增方法因其操作快速简便而受到关注。然而,这些方法在特异性和自动化样品处理方面面临挑战。在本研究中,我们引入了一种自干涉数字光流体平台,该平台结合不对称直接固相RPA,用于实时、无标记和自动化病原体基因分型。通过将数字微流控与使用高光谱干涉测量的DNA单层检测方法相结合,该平台无需外源标记或复杂程序即可实现快速、特异和灵敏的病原体检测。该系统具有高灵敏度(10 CFU·mL)、特异性(区分四种物种)、检测效率(革兰氏阴性菌在50分钟内完全自动化)和通量(同时检测四个指标)。这种在单个微流控芯片上进行病原体定量的集成方法代表了快速病原体诊断的重大进展,为及时的病原体检测和分析提供了切实可行的解决方案。

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