Issue 11, 2022

A magnet-actuated microfluidic array chip for high-throughput pretreatment and amplification and detection of multiple pathogens

Abstract

The outbreak of global infectious diseases has posed a significant threat to public health, requiring the rapid and accurate diagnosis of pathogens promptly for the society to implement immediate control measures to prevent widespread pandemics. In this work, a magnet-actuated microfluidic array chip (MMAC) is developed with integrated sample processing and nucleic acid amplification for the rapid detection of multiple pathogens by loop-mediated isothermal amplification. In comparison to previous works, where fluid control was dependent on external equipment or finger-based manual pressing, the fluid control of the MMAC is realized by magnetically actuating a ferric oxide (Fe3O4) doped polydimethylsiloxane (PDMS) layer that separates the sample from the LAMP reagent in a high-throughput manner, which not only reduces the complexity of fluid control but also enhances the repeatability of detection by eliminating variations in operation by different users. Examination with a testing sample containing Salmonella typhimurium and Escherichia coli showed high specificity for pathogen detection without cross-contamination. The lowest detection concentration was 5.2 copies per μL for Salmonella typhimurium with a detection time of 60 min. The proposed method demonstrated the simultaneous detection of multiple pathogens, which is potentially helpful in applications of immediate diagnosis.

Graphical abstract: A magnet-actuated microfluidic array chip for high-throughput pretreatment and amplification and detection of multiple pathogens

Supplementary files

Article information

Article type
Paper
Submitted
11 Mar 2022
Accepted
10 Apr 2022
First published
27 Apr 2022

Analyst, 2022,147, 2433-2441

A magnet-actuated microfluidic array chip for high-throughput pretreatment and amplification and detection of multiple pathogens

M. Zhou, H. Su, B. Wang, C. Wan, W. Du, P. Chen, X. Feng and B. Liu, Analyst, 2022, 147, 2433 DOI: 10.1039/D2AN00430E

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