Evaluation of RT-LAMP for SARS-CoV-2 Detection in Animal Feces
The wide host range, potential lethality, and zoonotic potential of SARS-CoV-2 infection in animals highlights the need for additional surveillance strategies. We validated a commercial, pH-based, colorimetric RT-LAMP assay for the detection of SARS-CoV-2 RNA in animal feces. The comparator assay was rRT-PCR. The limit of detection of the RT-LAMP assay was 72 genome copies per reaction. RT-LAMP was highly specific for SARS-CoV-2 and did not detect other human or animal coronaviruses. RT-LAMP was robust, with valid results generated for incubation lengths of 30 to 45 min, incubation temperatures of 60 to 70 °C, and reaction volumes of 10 to 25 µL. The diagnostic sensitivity was 100% for clinical fecal samples with high viral loads (Ct ≤ 25), 97.4% for samples with moderate to high viral loads (Ct ≤ 33), and 62% overall (Ct ≤ 40). The diagnostic specificity was 97.9%. Blinded method testing organized by an independent laboratory confirmed the satisfactory reproducibility of the assay. To our knowledge, this study represents the first validation of RT-LAMP for SARS-CoV-2 detection in animals. RT-LAMP testing could detect SARS-CoV-2 infection more rapidly and at the point of care in animals with moderate to high viral loads, allowing for earlier implementation of control measures.
Authors
- Karen A. Terio (ORCID: https://orcid.org/0000-0003-4924-5503)
- Aimee Pepper
- Megan R. Miller (ORCID: https://orcid.org/0000-0003-2139-817X)
- Leyi Wang (ORCID: https://orcid.org/0000-0001-5813-9505)
- Jake Guag (ORCID: https://orcid.org/0000-0002-7633-7262)
- Andriy Tkachenko
- Sandipty Kayastha
- Matthew C. Allender (ORCID: https://orcid.org/0000-0001-9067-1964)
Institutions
- Center for Veterinary Medicine (US)
- United States Food and Drug Administration (US)
- University of Illinois Urbana-Champaign (US)
- Illinois College (US)
Publication Details
- Journal
- Viruses
- Published
- 2025-05-29
- DOI
- https://doi.org/10.3390/v17060783
- Citations
- 2
- Primary Topic
- Biosensors and Analytical Detection
- Type
- article
- Field-Weighted Citation Impact
- 1.35