Longitudinal serum proteomics analyses reveal biomarkers for porcine influenza and coronavirus infections

Abstract

Respiratory virus infections affect both humans and livestock, causing considerable mortality and morbidity. While respiratory pathogens such as swine influenza A virus (pH1N1) and porcine respiratory coronavirus (PRCV) often present with overlapping clinical symptoms, their pathological trajectories and outcomes differ. Given the propensity for pathogen spillover and the use of pigs as a physiologically relevant large-animal translational model, we aimed to characterise host serum protein signatures that detect and differentiate pH1N1 from PRCV, enabling improved disease monitoring and control. Using high-resolution mass spectrometry- based proteomics, we identified 162 serum proteins that were significantly dysregulated across 3 infection timepoints (1, 5, and 12 days post-infection (DPI)), with signatures correlating with viral shedding and lung pathology as early as 1 DPI. Notably, multiplexed targeted analysis of a subset of proteins in an independent cohort from a different breed and geographic location demonstrated detection, femtomole-level targeted quantitation, and validation of SRGN as a diagnostic marker for pH1N1 and PRCV (AUC=0.85). Further, SOD1 was validated as an early marker for PRCV, increasing as early as 1 DPI (AUC= 0.9). Finally, a multi-peptide signature composed of SRGN, SOD1, and RAN demonstrated reasonable predictive power for pH1N1 (AUC=0.75) and PRCV (AUC=0.65) at 1 DPI. Our data validate the proteomic screening, provide insights into the role of early protein markers in distinguishing respiratory viral infections, and pave the way for the development of point-of-care diagnostics and targeted prevention strategies, enhancing preparedness against emerging zoonotic threats.