Abstract
Bovine Parainfluenza Virus-3 (BPIV-3) is a major viral pathogen of the Bovine Respiratory Disease (BRD) complex, which is considered to be one of the most significant causes of economic loss in intensively reared cattle worldwide. Current diagnostic tests for BPIV-3 infection provide limited information on the health status of infected animals. Biomarker screening tools offer the potential for improving the diagnostic windows for infection and providing greater information on the disease or immune status of infected animals. By employing proteomic and metabolomic techniques this study has succeeded in identifying a number of markers in plasma capable of providing greater information on the immune status of infected animals, and a number of candidate markers for early infection diagnosis in vivo.An in vivo study was conducted in which male Holstein Friesian calves were vaccinated with Pfizer RISPOVAL-RS+PI3 and subsequently challenged with BPIV-3. Through the use of mass spectrometry based metabolomic analysis and multivariate statistical analysis 12 markers were selected throughout vaccination stages which differed significantly between vaccinated and non-vaccinated study groups at their respective sampling time-point. Furthermore, metabolomic analysis of plasma from calves post-infection identified 33 markers capable of differentiating between vaccinated and non- vaccinated animals infected with BPIV-3 as early as day 2 p.i. up until day 20 p.i. ‘Shotgun’ proteomic analysis of plasma also revealed a number of markers capable of differentiating between vaccinated and non-vaccinated animals infected with BPIV3 at day 6 p.i. The markers identified have been found to have immuno-modulatory properties in vitro and for the majority this project highlights the first observation of their altered abundance in vivo as a result of immunization/infection. Furthermore, using the combined panel of identified markers it is also possible to determine the stage of infection in vaccinated or non-vaccinated animals. Further investigations aimed to select candidate protein markers for BPIV-3 infection from in vitro culture models which could be applied as early markers of infection in vivo. No secretory proteins were identified in BPIV-3 infected foetal calf lung cells, however, due to their accumulation within infected cells Phosphoprotein P, T-complex protein 1 and 14-3-3 protein were selected as potential infection markers as they would be released from infected cells into circulating biofluids. A targeted MRM method was developed for the quantification of protein markers in plasma. Peptides originating from Phosphoprotein P and T-complex protein 1 subunit theta selected from the in vitro BPIV-3 infection model were present in plasma of BPIV-3 challenged animals, with levels differing between vaccinated and non-vaccinated animals. Upon further quantitative MRM analysis protein markers selected using ‘shotgun’ proteomics appeared to be artefacts of the depletion and fractionation sample processing procedures, however, variations in the plasma levels of peptides originating from Apolipoprotein B100 and Inter-alpha-trypsin inhibitor heavy chain HI were found to differ between vaccinate and non-vaccinated study groups at days 1 and 5 post-BPIV-3 challenge respectively.
The current rapid diagnostic tests for BRD cannot differentiate between vaccinated/non- vaccinated animals once infected. The markers selected throughout this project offer the ability to identify animals which have failed to respond to vaccine treatment in either the presence or absence of infection. The application of these markers to diagnostic testing could provide numerous benefits for the management of BPIV-3 infection at the herd level. This research highlights the potential of metabolomic and proteomic biomarker studies for improved management and diagnosis of agricultural diseases.
Date of Award | Jul 2014 |
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Original language | English |
Awarding Institution |
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Supervisor | Mark Mooney (Supervisor), Michael Welsh (Supervisor) & Christopher Elliott (Supervisor) |