Detection of five viruses commonly implicated with bovine respiratory disease using loop-mediated isothermal amplification

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Authors: Josiah Levi Davidson, Murali Kannan Maruthamuthu, Mohamed Kamel, S. Maddur Mohan, Ana Pascual-Garrigos, Andres Dextre, Ruth Eunice Centeno-Delphia, Jacquelyn P. Boerman, Deepti Pillai, Jennifer Koziol, Aaron C. Ault, Jon Patrick Schoonmaker
+2 more Timothy A. Johnson, Mohit S. Verma
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Abstract

Herein, we present novel quantitative loop-mediated isothermal amplification (qLAMP) and reverse-transcription qLAMP (RT-qLAMP) assays for the detection of five viruses implicated with the onset and progression of bovine respiratory disease (BRD): Bovine Alphaherpesvirus Type 1 (BHV-1), Bovine Adenovirus Type 3 (BAV-3), Bovine Respiratory Syncytial Virus (BRSV), Bovine Viral Diarrhea Virus Type 1 (BVDV-1), and Bovine Parainfluenza Virus Type 3 (BPIV-3). Using contrived samples spiked with whole viruses, our extraction-free assays have limits of detection between 30 and 1,057 copies per reaction (1.8% final sample concentration) with minimal sample processing. Using dual-tipped swabs and 1.4 mL resuspension volumes, limits of detection are on the order of 2 × 105 copies per swab for BAV-3 and BHV-1 and between 6.31 × 106 to 8.22 × 106 copies per swab for BPIV-3, BRSV, and BVDV-1. Analytical sensitivities ranged from 73 − 100% and analytical specificities ranged from 90 − 100%. Additionally, we introduced a streamlined pipeline to minimize the experimental workload to design, screen, select, and characterize LAMP performance for developing assays. Our assays support the development of colorimetric LAMP assays that enable the sensitive and specific detection of these viruses’ chute side to aid in diagnosing and treating BRD. The associated pipeline enables more rapid development of LAMP-based diagnostic tools targeting emerging pathogens.

Fields of Study & Subjects

Biosensors and Analytical Detection Animal Virus Infections Studies Microbial infections and disease research

Publication details

Journal / source
Figshare
Publication date
1 January 2026
Document type
Dataset