Efficiency-corrected PCR quantification for identification of prevalence and load of respiratory disease-causing agents in feedlot cattle

RJ Barnewall, IB Marsh, TM Williams, PMV Cusack, N Sales, F Galea, AN Szentirmay, JC Quinn

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1 Citation (Scopus)
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Bovine respiratory disease (BRD) is the most prevalent disease in feedlot cattle worldwide with Bovine alphaherpesvirus 1 (BoAHV1), Histophilus somniMannheimia haemolyticaMycoplasma bovisPasteurella multocida and Trueperella pyogenes accepted to be common etiological agents associated with BRD. Although these agents are common in the upper and lower airways in clinical BRD cases, some also exist as normal flora suggesting their presence in the upper airways alone is not necessarily informative with respect to disease status or risk. To determine the relationship between presence, load and disease status, we investigated the relationship between load in the upper airways at induction and active BRD cases in feedlot cattle using efficiency-corrected PCR quantification. By this approach, we were able to accurately determine the prevalence and load of the key BRD agents in the upper respiratory tract showing that cattle in the hospital pen had a higher prevalence, and load, of these agents both singly and in combination compared to cattle sampled at feedlot induction. A combination of agents was the most accurate indicator of BRD risk with cattle with four or more agents detected in the upper airway more likely to be undergoing treatment for BRD than non-BRD ailments. In addition, Mbovis was rarely detected at feedlot induction but was identified at high prevalence in cattle in the hospital pen. These findings present a potential new technological approach for the investigation, analysis and identification of BRD-associated viral and bacterial agents for Australian feedlot systems as well as for BRD disease management and treatment.

Original languageEnglish
Pages (from-to)539-549
Number of pages11
JournalAustralian Veterinary Journal
Issue number11
Early online date18 Aug 2022
Publication statusPublished - Nov 2022


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