Standardization of sperm motility analysis by using CASA-Mot for Atlantic salmon (Salmo salar), European eel (Anguilla anguilla) and Siberian sturgeon (Acipenser baerii)
Introduction
The marked decline of wild stocks of some diadromous fish species such as European eel (Jacoby and Gollock, 2014), Atlantic salmon (NASCO, 2016) and Sturgeon sp. (Ruban and Bin Zhu, 2010) due to construction of dams, pollution, poaching and overfishing, together with their economic importance and high commercial demand, aroused a great interest in their production in captivity. The efficacy of aquatic fertilization in captivity depends on the accurate evaluation of the sperm quality, which nowadays is the best way to define the fertility potential of each male (Kime et al., 2001; Rurangwa et al., 2004). For the assessment of sperm quality, it is needed to have available rapid and quantitative techniques as a useful tool for aquaculture purposes (Kime et al., 2001; Gallego and Asturiano, 2018a). Sperm motility is one of the most important parameters of sperm quality and is sensitive to biological and technical conditions during analysis (Rurangwa et al., 2004; Castellini et al., 2011).
Computer-assisted sperm analysis (CASA) is an accurate, reliable and objective technology which offer several spermatozoa quantitative parameters (Rurangwa et al., 2004; Caldeira et al., 2018). A complete CASA-Mot system, which is a CASA devoted to motility analysis (Soler et al., 2016; Holt et al., 2018), includes a software associated to a phase contrast microscope equipped with a video camera. However, in the market, there are a range of products or even different versions of the same product (Holt et al., 1994; Castellini et al. 2011). Besides the different CASA-Mot systems can follow the same general principle, each one has specific algorithms which can result in the incompatibility of results (Holt et al., 1994). This common principle consists in the individual measurement of spermatozoa motility based on the detection of spermatozoa head in consecutive images in order to obtain spermatozoa tracks (Mortimer et al., 1997; Bobe and Labbé, 2010; Fauvel et al., 2010). In addition, the sperm quality assessment is also sensitive to the hardware systems, such as the optical microscope, video camera and counting chambers (Castellini et al., 2011; Soler et al., 2012; Gallego et al., 2013; Del Gallego et al., 2017; Bompart et al., 2018).
The frequency of images used on the motility analysis can be a limiting factor (Acosta and Kruger, 1996) in the reconstruction of the trajectories and, consequently, some kinetic parameters are frame rate (FR) dependent for both mammals and fish (Morris et al., 1996; Castellini et al., 2011Boryshpolets et al., 2013; Valverde et al., 2018). Therefore, it is necessary to know the optimal frame rate that provides enough detail about spermatozoa trajectory avoiding redundant information (Castellini et al., 2011). Sperm trajectory and velocity can also be affected by counting chamber depth due to the natural movement of spermatozoa (Kraemer et al., 1998; Bompart et al., 2018). This issue depends on the different motility patterns, head shape and flagellum size and could be species-specific. In this respect, a reliable and standardized method to analyse the sperm quality is needed for each species. Thereby, it is important to enhance the reliability and comparability of data provided by different research groups through the application of a standard methodology for sperm analysis (Wilson-Leedy and Ingermann, 2007; Gallego et al., 2013).
The aim of this study was to evaluate different technical settings such as frame rate, counting chamber models and lens magnification to define a standard method for the analysis of sperm motility of these three endangered fish species (Anguilla anguilla, Salmo salar, Acipenser baerii) using a CASA system.
Section snippets
Sperm sampling
Sperm samples were collected from three fish species: European eel (A. Anguilla; n = 5), Atlantic salmon (S. salar; n = 5) and Siberian sturgeon (A. baerii; n = 3). Mature males were sampled during 2017 in different facilities, according to the reproduction season and the procedures specific to each species. Eel sperm samples were collected on March in the facilities of the Universitat Politècnica de València (Valencia, Spain; Herranz-Jusdado et al., 2018). Wild salmon males were sampled on
General results
The highest motility rate was found in sturgeon, whilst eel samples showed the lowest motility. Independent of species, the FR had no effect on the motility rate considering both magnification lens and chamber. However, some significant differences were observed between lens and chamber within the same FR (data not shown). Otherwise, other kinetic values were extremely affected by FR.
The most notable difference was registered in the sperm motility traits of each fish species (Fig. 1), with the
Discussion
Classical assessment of sperm quality was established following a subjective analysis based on the estimation of concentration and percentage of motility. This method introduces a great variability on the results (Rurangwa et al., 2004), reducing their reliability and, consequently, their biological significance and practical utility (Gallego et al., 2018). For this reason, CASA systems were developed about 30 years ago (Bompart et al., 2018). A computerised system is considered an objective
Conclusion
Computer-assisted sperm analysis systems are considered a valuable tool for quantitative analysis of sperm motility. At a practical level, this technique could be an indicator of high-quality breeders and can apply for the reproductive biology studies as well as for standard artificial insemination or assisted reproduction techniques for fish species (Gallego and Asturiano, 2018b). However, the optimization and standardization of the protocol at the technical level for each species is a
Acknowledgements
This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No [642893]. AV is granted by the CONICIT and MICITT, Costa Rica. The study was financially supported by the Ministry of Education, Youth and Sports of the Czech Republic - projects “CENAKVA” (No. CZ.1.05/2.1.00/01.0024), “CENAKVA II” (No. LO1205 under the NPU I program), project Biodiversity (CZ.02.1.01/0.0/0.0/16_025/0007370), by the Czech
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2019, AquacultureCitation Excerpt :We would like to emphasize that our results concerning sperm motility must be interpreted with caution, as two different CASA systems were used. It is well known that different systems (Boryshpolets et al., 2013) and settings (Caldeira et al., 2019) influence the values of sperm motility parameters. Due to the differences in hardware and algorithms, it is not possible to standardize the outcome values of different CASA systems (Amann and Waberski, 2014).