Laboratory Validation of a Fully Automated Point-of-Care Device for High-Order Multiplexing Real-Time PCR Detection of Respiratory Pathogens
<b>Background/Objectives</b>: We have previously reported the engineering of a point-of-care (POC) system that fully automates the procedures for nucleic acid extraction and multiplexed real-time RT-PCR, with a major advantage of high-level multiplexing. In this study, we applied and validated the system in a respiratory tract infection setting. <b>Methods</b>: An automatic nested real-time RT-PCR assay was developed (POCm). It was a 40-plex assay that simultaneously detected 39 epidemiologically important respiratory pathogens in 1.5 h in the POC system. The analytical and clinical performance was evaluated. <b>Results</b>: The analytical sensitivities of the POCm assay were comparable to those of its single-plex counterparts performed manually on a bench-top. The minimum detectable concentrations ranged from 53 copies/mL to 5.3 × 10<sup>3</sup> copies/mL for all pathogen targets except hCoV-NL63 (5.3 × 10<sup>4</sup> copies/mL). The quantitative performance was demonstrated by the linear correlations between Ct values and input concentrations for all pathogen targets, with 24 of them demonstrating coefficients of correlation (r) greater than 0.9. The POCm assay was subsequently evaluated in 283 clinical samples. A high level of agreement (98.2-100%) was achieved for pathogen detection results between POCm and standard diagnostic methods. The POCm result was also fully concordant with the result of another commercial POC multiplex platform. For positive clinical samples, pairwise Ct values measured by POCm closely correlated with those of the bench-top reference method (r = 0.70). The feasibility of mutation genotyping of the viral subtype was further demonstrated. <b>Conclusions</b>: This study demonstrated the practicality of POCm for routine testing in clinical laboratories. Further clinical trials are being conducted to evaluate the clinical performance of the system.
Authors
- Parker Y. L. Tsang
- Lok Ting Lau (ORCID: https://orcid.org/0000-0001-7517-1486)
- Firaol Tamiru Kebede
- Anita Yee
- Kelvin Kai‐Wang To (ORCID: https://orcid.org/0000-0002-1921-5824)
- Deborah M. S. Tai
- Teresa Chung (ORCID: https://orcid.org/0000-0001-8113-2563)
- Johnson Y.N. Lau (ORCID: https://orcid.org/0000-0002-2118-297X)
- Pete Y. M. Leung
- Libby C. W. Li (ORCID: https://orcid.org/0000-0002-4507-5335)
- Cyril Chik‐Yan Yip (ORCID: https://orcid.org/0000-0002-9606-8506)
- Sunny L. H. Chu
- Jonathan Hon-Kwan Chen (ORCID: https://orcid.org/0000-0002-7510-1696)
- Carol Sze Ki Leung (ORCID: https://orcid.org/0000-0002-1545-7228)
- Nancy B. Y. Tsui (ORCID: https://orcid.org/0000-0002-7647-4304)
- Kwok-Yung Yuen (ORCID: https://orcid.org/0000-0001-8700-4570)
- Manson Fok
- Rosana Wing‐Shan Poon
- Brenda Leung
- Winston Wong
Institutions
- Macau University of Science and Technology (MO)
- Hong Kong Baptist University (HK)
- Hong Kong Polytechnic University (HK)
- University of Hong Kong (HK)
Publication Details
- Journal
- Diagnostics
- Published
- 2025-09-25
- DOI
- https://doi.org/10.3390/diagnostics15192445
- Citations
- 1
- Primary Topic
- Respiratory viral infections research
- Type
- article
- Field-Weighted Citation Impact
- 1.35
Funders
- Hong Kong Baptist University