CrynodebJohne’s Disease, caused by Mycobacterium avium subsp. paratuberculosis (MAP), causes weight loss, diarrhoea and reduced milk yields in affected cattle. However, only 10% to 15% of MAP-infected cattle display clinical signs and the sensitivity of traditional diagnostic tests is dependent on the stage of infection. The application of metabolomic techniques is increasing due to their high-throughput capabilities and advancements in analytical methods. However, the application of metabolomics within MAP research is limited. This project aimed to identify novel biomarkers for MAP by examining sera and milk samples from naturally MAP-infected or MAP-challenged cattle, alongside control samples, using flow infusion electrospray ionizationhigh-resolution mass spectrometry (FIE-HRMS) on a Q Exactive hybrid quadrupole–Orbitrap mass spectrometer for high-throughput, sensitive, non-targeted metabolite fingerprinting. In addition to correlating the accumulation of identified metabolites to haematological and immunological parameters, as well as milk yield and milk composition. Firstly, sera from 20 healthy, Holstein-Friesian (HF) heifers aged from 2 weeks to 19 months of age were used to demonstrate the effects of physiological changes on the sera metabolite profile (Chapter 3). Time series analyses identified 45 metabolites associated with rumen development, weaning induced stress or growth. Our findings highlighted the role of acetic acid in rumen development and used correlation analysis to display the positive relationship between acetic acid accumulation and liveweight at 3 months of age. Furthermore, pathway analysis demonstrated the role of the alpha-linoleic acid and linoleic acid metabolism within the weaning induced stress response, as well as long-term growth and development. Next, sera from 9 MAP-challenged and 9 control HF steers, collected over 11 timepoints, up to 33 months post MAP-challenge were examined (Chapter 4). In total, 25 metabolites capable of distinguishing between experimental groups were identified. However, area under the curve (AUC) assessments suggested that these were time specific changes. Nevertheless, metabolite changes were better able to discriminate between experimental groups than the interferongamma (IFN-γ) release assay. Notably, correlations were observed between monocyte levels and the accumulation patterns of identified metabolites. Targeted metabolites suggested that amino acid and phosphocholine changes may reflect immune system activation, including macrophage activation. Furthermore, an analysis of sera samples derived from 10 naturally MAP-infected, faecal culture positive heifers compared to healthy controls between 2 weeks to 19 months of age highlighted potential biomarkers for MAP infections (Chapter 5). In total, 33 metabolites were identified, including 5 which were differentially accumulated throughout the study; leukotriene B4, bicyclo prostaglandin E2 (bicyclo PGE2), itaconic acid, 2-hydroxyglutaric acid and N6-acetylL-lysine. Additionally, the accumulation patterns of 6 additional metabolites demonstrated correlation with antibody responses to MAP antigens. In line with Chapter 4, these findings suggested that changes to bioenergetic pathways and amino acid accumulation may reflect immune system activation, as well as highlighting the role of eicosanoids in inflammation. These findings were reinforced using sera from 20 MAP-inoculated and 20 control heifers of similar ages (Chapter 6). Of the 34 identified metabolites, 11 metabolites were previously identified in Chapter 5, including; bicyclo PGE2 and leukotriene B4. Interestingly, 6 newly identified fatty acyls were able to differentiate between experimental groups irrespective of age. Furthermore, as also observed in Chapter 4, identified metabolites were better able to discriminate between experimental groups than faecal culture tests or serum enzyme-linked immunosorbent assays (ELISAs). These changes further suggest how omega-3 (n-3) poly unsaturated fatty acids (PUFAs) and omega-6 (n-6) PUFAs, alongside cyclooxygenase (COX)-dependent and lipoxygenase (LOX)-dependent metabolites, may influence the MAP induced immune system response. Finally, to assess the impact of the early lactation negative energy balance on the metabolite profile of milk from MAP-infected cattle, milk samples from 5 ELISA positive and 5 control multiparous lactating dairy cows which were 73.4 ± 3.79 (early lactation) and 143 ± 3.79 (mean ± SE) (mid-lactation) days post-calving were examined (Chapter 7). In total, 45 metabolites were identified, including 6 metabolites which were present throughout lactation. However,
the stage of lactation was a larger source of variation than MAP status. Nonetheless, pathway analysis highlighted the impact of MAP on the malate-aspartate shuffle and the targeted metabolites suggested that MAP may influence mitochondrial energy pathways. Overall, the project highlighted potential biomarkers for subclinical MAP infections and used correlation analysis to explore links between identified metabolites and immune system parameters. Future work could include extending these metabolomic assessments to include additional lactating dairy cows, as well as verifying the specificity of these metabolites to MAP.
|Noddwyr||Knowledge Economy Skills Scholarships|
|Goruchwyliwr||Luis Mur (Goruchwylydd) & Glyn Hewinson (Goruchwylydd)|