Portable, precise, and RNA extraction-free: RT-RAA technology for rapid early RSV identification and prevention

The Respiratory Syncytial Virus (RSV) is a significant agent linked to respiratory infections, representing a considerable health risk for vulnerable populations, including infants, older adults, and those with weakened immune systems. This research successfully introduces an RNA extraction-free rapid detection technique for RSV utilizing real-time reverse transcription recombinase-aided amplification (RT-RAA) technology. Through the crafting of specific primers and probes, this approach enables precise identification of RSV without any interference from other prevalent respiratory viruses. Tests for sensitivity indicated that the detection threshold at a 95% confidence interval was 159 copies per reaction, while the visual detection limit was found to be 1,177 copies per reaction. Testing on clinical samples demonstrated a high degree of consistency with reverse transcription quantitative real-time PCR (RT-qPCR), achieving a Kappa value of 1, which signifies excellent correlation. Furthermore, the amplified products from RT-RAA can be seen with the aid of a portable blue light device, rendering this method appropriate for rapid detection in settings where resources are limited. A total of 265 clinical samples were tested, and the results showed 100% concordance with RT-qPCR. Compared with rapid antigen detection tests (RADTs), RT-RAA exhibited significantly higher sensitivity (100% <i>vs</i>. 93.8%). The rapid detection method for RSV using RT-RAA offers solid technical assistance for the early identification and prevention of RSV.

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Publication Details

Journal
Frontiers in Cellular and Infection Microbiology
Published
2025-09-02
DOI
https://doi.org/10.3389/fcimb.2025.1640503
Citations
1
Primary Topic
Respiratory viral infections research
Type
article
Field-Weighted Citation Impact
1.35
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article

Portable, precise, and RNA extraction-free: RT-RAA technology for rapid early RSV identification and prevention

Zhenfei Wang, Tingli Fan, Zhenyue Li, Jing Zhang et al.
1 citations
Frontiers in Cellular and Infection Microbiology
Respiratory viral infections research
1.35
article

Portable, precise, and RNA extraction-free: RT-RAA technology for rapid early RSV identification and prevention

Zhenfei Wang, Tingli Fan, Zhenyue Li, Jing Zhang, Kai Su, Xiao Dong He, Cheng Zhang, Chunming Wang, Zitong Yang
article en
1 citations

Abstract

The Respiratory Syncytial Virus (RSV) is a significant agent linked to respiratory infections, representing a considerable health risk for vulnerable populations, including infants, older adults, and those with weakened immune systems. This research successfully introduces an RNA extraction-free rapid detection technique for RSV utilizing real-time reverse transcription recombinase-aided amplification (RT-RAA) technology. Through the crafting of specific primers and probes, this approach enables precise identification of RSV without any interference from other prevalent respiratory viruses. Tests for sensitivity indicated that the detection threshold at a 95% confidence interval was 159 copies per reaction, while the visual detection limit was found to be 1,177 copies per reaction. Testing on clinical samples demonstrated a high degree of consistency with reverse transcription quantitative real-time PCR (RT-qPCR), achieving a Kappa value of 1, which signifies excellent correlation. Furthermore, the amplified products from RT-RAA can be seen with the aid of a portable blue light device, rendering this method appropriate for rapid detection in settings where resources are limited. A total of 265 clinical samples were tested, and the results showed 100% concordance with RT-qPCR. Compared with rapid antigen detection tests (RADTs), RT-RAA exhibited significantly higher sensitivity (100% <i>vs</i>. 93.8%). The rapid detection method for RSV using RT-RAA offers solid technical assistance for the early identification and prevention of RSV.

Frontiers in Cellular and Infection MicrobiologyVol. 15
Hebei Agricultural University (CN), Shandong University (CN), Cangzhou Normal University (CN)
Openalex Percentile: Top 16%
Respiratory viral infections research
1.35
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