Background: Identifying protein biomarkers helps in defining and predicting animal response to illness. We have developed a platform capable of detecting acute phase protein (APP) inflammation markers and their alterations in the liquid fraction of sheep blood using SWATH-MS. This approach is an attractive alternative to antibody ELISA technology which can be particularly costly and time consuming. A broader tool to measure plasma or serum levels of many different proteins using proteomics would be highly advantageous. It was hypothesised that every injury is accompanied by proteomic alterations in specific biomarkers. The main research objectives were to develop a feasible proteomic method to characterise the ovine acellular circulating proteome and apply it to samples from healthy and ill sheep to potentially detect candidate markers of inflammation.
Method: A novel encyclopaedic peptide spectral library was constructed from several hundred samples derived from the ovine acellular circulating proteome of sick and healthy sheep using a TripleTOF® 5600 instrument by shotgun proteomics. SWATH data extraction strategy was used alongside the library on the same platform to interrogate samples of an ovine model of intensive care in which the subjects were exposed to acute sepsis and inflammation.
Results: Over 700 protein alterations were detected, verified and quantitated between normal and endotoxaemic sheep plasma. It was confirmed that the subjects of the sheep model of intensive care study were phenotypically non-identical. Apart from over 50 APP, at least 75 other proteins were potentially endotoxin-specific candidate markers of inflammation.
Conclusion: Using SWATH and a novel sheep-specific peptide spectral library to this scale for the first time enabled the identification of a colossal number of plasma proteins and their alterations during inflammation. The potential applications for this approach are in veterinary pathology, animal welfare and screening laboratory animals before inclusion in experimental groups to minimise differences, for example.