FEN1-Aided RPA (FARPA) Coupled with Autosampling Microfluidic Chip Enables Highly Multiplexed On-Site Pathogen Screening

化学 微流控芯片 微流控 炸薯条 病菌 纳米技术 多路复用 微生物学 电信 材料科学 计算机科学 生物
作者
Yi Ma,Yuanmeng Wang,Chen Chen,Liying Feng,Jingwen Shan,Likun Zhang,Xueping Ma,Yanan Chu,Haiping Wu,Guohua Zhou
出处
期刊:Analytical Chemistry [American Chemical Society]
标识
DOI:10.1021/acs.analchem.4c07015
摘要

A simple, rapid, low-cost, and multiplex detection platform is crucial for the diagnosis of infectious diseases, especially for on-site pathogen screening. However, current methods are difficult to satisfy the requirements for minimal instrument and multiplexed point-of-care testing (POCT). Herein, we propose a versatile and easy-to-use platform (FARPA-chip) by combining multiplex FARPA with an autosampling microfluidic chip. A pair of universal recombinase polymerase amplification (RPA) primers introduced during double-stranded cDNA (ds-cDNA) preparation are employed to amplify multiple targets, followed by amplicon-decoding with the chip, indicating no bias in amplifying different targets due to the universal RPA primers. FARPA-chip exhibits that as low as 10 copies of each target RNA in the starting sample can be sensitively detected by 12-plex detection of vector-borne viruses within 45 min and no cross-talk is observed between different targets. The feasibility of this platform is confirmed by designing a 9-plex FARPA-chip to detect 6 kinds of clinically common respiratory viruses from 16 clinical samples of nasopharyngeal swabs, and the results are completely consistent with RT-qPCR. Furthermore, by integrating quick extraction reagent, the turnaround time can be significantly decreased to <50 min, highlighting that our FARPA-chip enables a cost-effective on-site pathogen screening with a relatively high level of multiplexing. Depending on the number of chambers in the chip, the current design is theoretically capable of detecting up to 24 different pathogens, which should fulfill most clinical purposes. We believe that the proposed platform could provide an effective way for a series of healthcare-related applications in resource-limited settings.
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