Seminal plasma AnnexinA2 protein is a relevant biomarker for stallions which require removal of seminal plasma for sperm survival upon refrigeration†.

Some stallions yield ejaculates that do not tolerate conservation by refrigeration prior to artificial insemination (AI), showing improvement after removal of most of the seminal plasma (SP) by centrifugation. In this study, the SP-proteome of 10 different stallions was defined through high-performance liquid chromatography with tandem mass spectrometry and bioinformatic analysis in relation to the ability of the ejaculates to maintain semen quality when cooled and stored at 5°C. Stallions were classified into three groups, depending on this ability: those maintaining good quality after direct extension in a commercial extender (good), stallions requiring removal of seminal plasma (RSP) to maintain seminal quality (good-RSP), and stallions, unable to maintain good semen quality even after RSP (poor). Pathway enrichment analysis of the proteins identified in whole equine SP using human orthologs was performed using g: profiler showing enriched Reactome and the Kyoto Encyclopedia of Genes and Genomes pathways related to hexose metabolism, vesicle mediated transport, post translational modification of proteins and immune response. Specific proteins overrepresented in stallions tolerating conservation by refrigeration included a peroxiredoxin-6 like protein, and transcobalamin-2, a primary vitamin B12-binding, and transport protein. Also, the protein involved in protein glycosylation, ST3 beta-galactoside alpha-2,3-sialyltransferase 1 was present in good stallions. These proteins were nearly absent in poor stallions. Particularly, annexinA2 appeared as to be the most powerful discriminant variable for identification of stallions needing RSP prior to refrigeration, with a P = 0.002 and a q value = 0.005. Overall this is the first detailed study of the equine SP-proteome, showing the potential value of specific proteins as discriminant bio-markers for clinical classification of stallions for AI.