Motility assessment of ram spermatozoa utilising Flagellar Analysis and Sperm Tracking

Van de Hoek, Madelaine
University of Sydney
simon.degraaf@sydney.edu.au

Abstract

For successful fertilisation to occur, spermatozoa need to successfully migrate through the female reproductive tract and penetrate the oocyte. As such, sperm motility is the key to male fertility and one of the most important parameters used for semen quality evaluation in sheep artificial breeding programs. Computer-assisted sperm analysis (CASA) is an objective motility assessment method widely used in industry. CASA assesses sperm motility exclusively via tracing of the sperm head despite the sperm flagellum being the primary driver of sperm motion. As such it has been argued that this method may lack the mechanistic insight to accurately assess the underlying driver of sperm motility. In this study, we investigated a novel method of ram sperm motility assessment, Flagellar Analysis and Sperm Tracking (FAST). FAST provides high-throughput analysis of both traditional CASA head motility parameters and a new range of motion parameters, predominantly associated with patterns of flagellar movement. Analysis of the relationships between CASA motility parameters and the novel motion parameters provided by FAST, revealed limited correlations between the two methods of motility assessment. Besides FAST’s measure of Track centroid speed, (a measure of sperm progressiveness and the only FAST parameter based on head movement) all correlations found between the FAST and CASA kinematic parameters were moderate to low (r < 0.35). These results indicate that the movement of the sperm tail measured by FAST are largely unaccounted for by traditional sperm head motion measurements. As such, these novel measurements have the potential to reveal new information about sperm motility and improve measurement of sperm quality. Further experimentation to investigate the relationship between these motility parameters and ram fertility is required before the usefulness of these measures in predicting fertilisation success can be determined.