Efficiency-Corrected PCR Quantification For Identification Of Prevalence And Load Of Respiratory Disease-Causing Agents In Feedlot Cattle

From a veterinary diagnostic perspective, PCR is predominantly performed qualitatively, be it conventional or real-time. However, pathogen load
is becoming increasingly important in disease management. Quantitative PCR aims to measure the nucleic acid concentration of a specific target
based on the quantification cycle (Cq) value, derived from the sample amplification curve, plotted on a standard curve generated from purified
nucleic acid standards. Acceptance of the PCR run is often made using the statistical attributes of the standard curve only whilst ignoring similar
criteria from the samples. In doing so, the impact of the sample is often overlooked or underestimated. At best this approach might best be
described as semi-quantitative. Typically, qPCR assumes assays are 100% efficient, that is, produce a doubling of amplified product each cycle.
It could be argued this is rarely the case in a diagnostic assay.
To achieve a more meaningful quantitative result, we used the Cq value and efficiency derived from the sample amplification curve used in
conjunction with the efficiency value from a single calibrator standard (with a known target concentration), a process known as efficiency
corrected quantitative PCR (EC-qPCR). EC-qPCR was used in a recent study to investigate the agents involved in bovine respiratory disease on
cattle at induction to the feedlot. Bovine respiratory disease (BRD) is the most prevalent disease in feedlot cattle worldwide and considered one
of the most difficult and complicated cattle diseases, largely due to the number of agents involved. BRD is commonly attributed to Bovine
alphaherpesvirus 1 (BoAHV1), Histophilus somni, Mannheimia haemolytica, Mycoplasma bovis, Pasteurella multocida and Trueperella pyogenes.
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BRD disease investigation is often complicated by the fact that H. somni, M. haemolytica, P. multocida and T. pyogenes are considered normal
flora of cattle and therefore their presence in the upper airways alone is not necessarily informative with respect to disease status or risk. To get a
better understanding of the relationship between presence, load and disease status, we investigated these agents using EC-qPCR to accurately
determine the prevalence and load in the upper respiratory tract from newly inducted cattle were compared with cattle in the hospital pen of the
feedlot. EC-qPCR results and clinical data were combined to establish profiles to elucidate the combinations of agents and those animals’
experiencing proliferation of the agents verses normal levels. Using technology that can produce individual amplification efficiencies for each
sample and EC-qPCR to investigate, analyse and identify BRD-associated viral and bacterial agents represents a new opportunity for Australian
feedlot systems to manage and treat BRD. EC-qPCR opens the scope for any disease investigation where accurate qPCR results are required.