Interrogation of an ovine serum peptide spectral library to annotate ambiguous clinicopathological biomarkers using data-independent acquisition

Abstract

Background: The use of data-independent data acquisition mass spectrometry (DIA-MS) on biological samples from domestic animals is still uncommon. Here, sequential window acquisition of all theoretical mass spectra (SWATH-MS) – a variant of DIA-MS was used to analyse serum peptides of healthy sheep as compared with serum of sick sheep by interrogating a novel peptide spectral library (PSL). This approach enabled the detection and annotation of a wide range of proteins, than conventional clinical pathology protein assays. Methods: Serum samples from healthy sheep were obtained from a commercial source and normalised to represent a healthy sheep proteome background and then compared with serum samples of sheep suffering from a range of naturally-acquired illnesses submitted to The University of Queensland, Australia. Purified tryptic peptides were subjected to liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) on a quadrupole time-of-flight instrument (TripleTOF 5600+, SCIEX) set in a cyclic data-independent acquisition (DIA) mode using a generic (SWATH™, SCIEX) acquisition method. Data were processed using PeakView® v2.2 software with SWATH™ Acquisition MicroApp 2.0 (SCIEX) and MarkerView™ v1.3 software (SCIEX) pipeline to generate protein lists for downstream gene ontology annotation and pathway analysis of identified proteins. Results: There were distinct differences in peptide chromatographic features of sick sheep samples compared to those from healthy sheep. Healthy and sick sheep serum samples yielded 335 and 236 protein identifications (IDs), respectively. There were 96 protein IDs unique to sick sheep serum. A total of 431 protein IDs were annotated by combining healthy control and sick sheep protein IDs. Conclusions: SWATH analysis successfully aided in the detection some established clinicopathological serum biochemical analytes. This approach enabled the distinction of protein profiles of sick sheep samples from a healthy control sample, thereby providing a promising future perspective for the application of SWATH analysis in veterinary clinical use.