Development of a multiplex real-time PCR assay for predicting macrolide and tetracycline resistance associated with bacterial pathogens of bovine respiratory disease

Authors

Enakshy Dutta, University of Nebraska–LincolnFollow
John Loy, University of Nebraska-LincolnFollow
Caitlyn A. Deal, University of Nebraska–LincolnFollow
Emily L. Wynn, USDA ARS Roman L. Hruska U.S. Meat Animal Research CenterFollow
Michael L. Clawson, USDAFollow
Jennifer Clarke, University of Nebraska-LincolnFollow
Bing Wang, University of Nebraska-LincolnFollow

ORCID IDs

John Dustin Loy https://orcid.org/0000-0002-7282-096X

Michael L. Clawson https://orcid.org/0000-0002-3355-5390

Jennifer Clarke https://orcid.org/0000-0002-2723-7249

Bing Wang https://orcid.org/0000-0003-0174-2252

Document Type

Article

Date of this Version

1-1-2021

Citation

Dutta, E.; Loy, J.D.; Deal, C.A.;Wynn, E.L.; Clawson, M.L.; Clarke, J.;Wang, B. Development of a Multiplex Real-Time PCR Assay for Predicting Macrolide and Tetracycline Resistance Associated with Bacterial Pathogens of Bovine Respiratory Disease. Pathogens 2021, 10, 64. https://doi.org/10.3390/ pathogens10010064

Comments

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license

Abstract

Antimicrobial resistance (AMR) in bovine respiratory disease (BRD) is an emerging concern that may threaten both animal and public health. Rapid and accurate detection of AMR is essential for prudent drug therapy selection during BRD outbreaks. This study aimed to develop a multiplex quantitative real-time polymerase chain reaction assay (qPCR) to provide culture-independent information regarding the phenotypic AMR status of BRD cases and an alternative to the gold-standard, culture-dependent test. Bovine clinical samples (297 lung and 111 nasal) collected in Nebraska were subjected to qPCR quantification of macrolide (MAC) and tetracycline (TET) resistance genes and gold-standard determinations of AMR of BRD pathogens. Receiver operating characteristic curve analysis was used to classify AMR based on the qPCR results. For lung tissues, the qPCR method showed good agreement with the gold-standard test for both MACs and TETs, with a sensitivity of 67–81% and a specificity higher than 80%. For nasal swabs, qPCR results passed validation criteria only for TET resistance detection, with a sensitivity of 88%, a specificity of 80% and moderate agree-ment. The culture-independent assay developed here provides the potential for more rapid AMR characterization of BRD cases directly from clinical samples at equivalent accuracy and higher time efficiency compared with the gold-standard, culture-based test.