Point-of-Care Multiplex Detection of Respiratory Viruses

The COVID-19 pandemic, in addition to the co-occurrence of influenza virus and respiratory syncytial virus (RSV), has emphasized the requirement for efficient and reliable multiplex diagnostic methods for respiratory infections. While existing multiplex detection techniques are based on reverse transcription quantitative polymerase chain reaction (RT-qPCR) and extraction and purification kits, the need for complex instrumentation and elevated cost limit their scalability and availability. In this study, we have developed a point-of-care (POC) device based on reverse transcription loop-mediated isothermal amplification (RT-LAMP) that can simultaneously detect four respiratory viruses (SARS-CoV-2, Influenza A, Influenza B, and RSV) and perform two controls in less than 30 min, while avoiding the use of the RNA extraction kit. The system includes a disposable microfluidic cartridge with mechanical components that automate sample processing, with a low-cost and portable optical reader and a smartphone app to record and analyze fluorescent images. The application as a real point-of-care platform was validated using swabs spiked with virus particles in nasal fluid. Our portable diagnostic system accurately detects viral RNA specific to respiratory pathogens, enabling deconvolution of coinfection information. The detection limits for each virus were determined using virus particles spiked in chemical lysis buffer. Our POC device has the potential to be adapted for the detection of new pathogens and a wide range of viruses by modifying the primer sequences. This work highlights an alternative approach for multiple respiratory virus diagnostics that is well-suited for healthcare systems in resource-limited settings or at home.

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Publication Details

Journal
ACS Sensors
Published
2024-08-05
DOI
https://doi.org/10.1021/acssensors.4c00992
Citations
18
Primary Topic
Respiratory viral infections research
Type
article
Field-Weighted Citation Impact
6.96

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Point-of-Care Multiplex Detection of Respiratory Viruses

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ACS Sensors
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article

Point-of-Care Multiplex Detection of Respiratory Viruses

Janice Mihyun Baek, Л. А. Хаертдинова, N. Minh, Katherine Koprowski, Victoria Kindratenko, Enrique Valera, Rashid Bashir, Robert A. Stavins, William P. King, Alicia Y. Kim, Jongwon Lim, Trung-Hieu Hoang, Nhat Xuan
article en
18 citations

Abstract

The COVID-19 pandemic, in addition to the co-occurrence of influenza virus and respiratory syncytial virus (RSV), has emphasized the requirement for efficient and reliable multiplex diagnostic methods for respiratory infections. While existing multiplex detection techniques are based on reverse transcription quantitative polymerase chain reaction (RT-qPCR) and extraction and purification kits, the need for complex instrumentation and elevated cost limit their scalability and availability. In this study, we have developed a point-of-care (POC) device based on reverse transcription loop-mediated isothermal amplification (RT-LAMP) that can simultaneously detect four respiratory viruses (SARS-CoV-2, Influenza A, Influenza B, and RSV) and perform two controls in less than 30 min, while avoiding the use of the RNA extraction kit. The system includes a disposable microfluidic cartridge with mechanical components that automate sample processing, with a low-cost and portable optical reader and a smartphone app to record and analyze fluorescent images. The application as a real point-of-care platform was validated using swabs spiked with virus particles in nasal fluid. Our portable diagnostic system accurately detects viral RNA specific to respiratory pathogens, enabling deconvolution of coinfection information. The detection limits for each virus were determined using virus particles spiked in chemical lysis buffer. Our POC device has the potential to be adapted for the detection of new pathogens and a wide range of viruses by modifying the primer sequences. This work highlights an alternative approach for multiple respiratory virus diagnostics that is well-suited for healthcare systems in resource-limited settings or at home.

ACS SensorsVol. 9(8)
University of Illinois Urbana-Champaign (US), Illinois College (US)
Health Care Engineering Systems Center, University of Illinois
Good health and well-being
Openalex Percentile: Top 2%
Respiratory viral infections research
6.96
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