Evaluation of Frozen Semen: Traditional and New Approaches

Summary

Subjective evaluation of sperm motility post-thaw is the single mostly used parameter to determine the quality of bull semen intended for AI. Albeit being a good indicator for sperm viability and of relevance for fertility, post-thaw motility is not a good predictor of the fertility level of the AI-semen dose. Such levels are determined by the AI of several hundreds or thousands of females. This costly procedure has encouraged world-wide research looking for alternative, or at least complementary, in vitro assessment methods. Such methods are hereby reviewed, particularly those evaluating multiple functions of frozen-thawed bull AI semen, and their relationship with AI-fertility. The combined outcome of a set of sperm functional parameters post-thaw; such as sperm linear motility, total concentration and concentration of motile spermatozoa after swim-up, the frequency of uncapacitated spermatozoa and their readiness to acrosome react when exposed to ionophores, their degree of chromatin stability as well as their ability to bind homologous zona pellucida (zona pellucida binding assay, ZBA) and to fertilize in vitro (IVF) has been significantly related (retrospectively) to the observed fertility of sires after AI. Furthermore, a predicted fertility value has been obtained by in vitro evaluation of frozen-thawed semen, indicating it is possible to eliminate sub-fertile bulls before their semen enter an AI program.

Artificial Insemination (AI): The Most Successful Reproductive Biotechnology in cattle

AI plays a dual role in cattle breeding. Firstly, it prevents spreading of venereal diseases and, secondly, it effectively disseminates desirable genetic material from proven sires onto a female population, thus improving their health status and the genetic gain of major populations (>150 million cows inseminated annually worldwide with frozen-thawed semen). To warrant the highest possible outcome of AI, those sires genetically selected for breeding are monitored andrologically for soundness and their semen is periodically examined for normality and processed using the best known handling procedures including freezing and thawing. Ultimately, the processed semen is deposited by AI taking care that sperm deposition is done as close as possible to expected ovulation. Besides all these efforts the fertility after first AI is considered acceptable when the non-return to oestrus rate after 56 days of AI (56d-NRR) is ≥60%. Although many factors can account for AI-fertility, the fertilizing ability of the frozen-thawed semen is, probably, the most important.

Fertilizing Ability is Affected by Freezing-Thawing

Spermatozoa are terminal cells, whose major role is to carry a genome/centriole package to the oocyte. For this task, spermatozoa are equipped with a setup of specialized structures (a domain-marked plasma membrane, diverse organelles such as mitochondria, a flagellum, an acrosome) that ensures a particular interaction with the female genital tract and the oocyte. Their cellular viability decreases substantially within a short time after ejaculation. Cryopreservation, which attempts to ensure their survival, imposes however, irreversible damage to the sperm membranes that causes either cell death [1] or capacitation-like changes in the plasmalemma [2], hampering their ability to fertilize. In order to maximize the number of AI´s that can be performed with a single ejaculate from a proven sire, the AI industry has steadily decreased the number of spermatozoa per frozen semen AI-dose and figures of 7.5-10 million are nowadays common [3]. With freezing-thawing affecting a large proportion of the spermatozoa there is, for each individual sire, a threshold number of viable spermatozoa per AI-dose which, ultimately, expresses a certain fertility level. Below this threshold sperm number, the fewer the viable spermatozoa inseminated the greater the risk fertility drops [4]. A significant relation has been shown between sperm number and achieved AI-fertility, which follows linearly the fertility level of an individual sire [3, 5]. Considering the biological and economical importance of knowing the potential fertility of the AI-semen prior to insemination, major efforts have been made worldwide to design in vitro method/s that could explore aspects of sperm structure and function and be, due to their relation to fertility, applied to a sub-population of processed bull semen in order to determine their potential fertility if inseminated to a female bovine.

Traditional Evaluation of Frozen-Thawed Bull Semen

To warrant the fertility of frozen semen in cattle AI, and thus promote the efficient dissemination of desirable genetic material from proven sires onto a female population, the cryopreserved ejaculates from AI bulls are solely evaluated for their levels of post-thaw sperm motility. Evaluation is mostly done subjectively, by visual assessment on a microscope equipped with phase-contrast optics, thus relying entirely on the ability and experience of the operator. The method is simple, easy and quick and remains the parameter of choice to determine the degree of sperm damage inflicted by the cryopreservation procedure, specially under industrial conditions. Although it is reported that there is a significant relationship between subjectively assessed motility and field fertility [6]; such relationship is not strong (particularly when motility values are within ranges around 50% or above) [7] and not always found in different cattle populations [8,9]. More and more bull stations are now incorporating Computer-Assisted Semen Analyzers (CASA), aiming at a higher objectivity and the analyses of certain patterns of sperm motility. Linearity, for instance, appears significantly correlated with field fertility [10,11]. ATP-determinations by luminometry can indirectly measure the number of viable spermatozoa, more accurately than by visual assessment of sperm motility [12] but does not correlate to AI-fertility [4]. Sperm morphology evaluation is a major component of the spermiogramm and indicates testicular and epididymal pathologies [9,13]. It can also provide some clues regarding the ability of spermatozoa to sustain freezing-thawing such as membrane (acrosomes) and tail damage (single bent tails) [14] and thus let us refrain from using a certain processed semen.

New Approaches for Evaluation of Bull Frozen-Thawed Semen

As mentioned above, bull spermatozoa have a well-defined structure specially differentiated for achieving fertilization of the oocyte. The assessment of the integrity and functionality of different sperm parameters, considered pre-requisites for fertilization due to their role in the interaction sperm-genital tract or sperm-oocyte [8] has, therefore, been a priority.

Evaluation of Sperm Viability

The integrity of the plasma membrane has been one of the most studied parameters, for its major role in acting as cell boundary and in cell-cell interactions, both in terms of morphological integrity as well as for its functional intactness (Reviewed by 15]. Morphological evaluation, either using optical enhancement (as with differential interference contrast optics; Nomarski), staining (supravital stains, such as fast green/eosin, eosin/aniline blue, trypan blue/giemsa or naphtol yellow/erythrosin) for light microscopical examination or both scanning (SEM) and transmission (TEM) electron microscopes has been of value. However, most of these techniques provide either partial information or are time consuming, expensive, or both. Furthermore, even when some morphological techniques provide insight into details of the plasma membrane injuries they are not correlated with the fertility of the sire, unless major damage is present. The frequency of frozen thawed bull spermatozoa with intact plasma membranes can be easily determined using simple and practical osmotic resistance tests (ORT) based up on their behaviour when exposed to hypo-osmotic solutions [16,17]. Unfortunately, the outcome of the assay does not always correlate with the fertility of the samples investigated. A major breakthrough to functionally assess frozen-thawed bull spermatozoa has been the development of fluorescent probes for DNA, intracytoplasmic enzymes, lectins or membrane potential [15]. Particularly the use of fluorophores (as single or combinations of probes] have proven highly valuable to determine the integrity of the various subcellular sperm compartments (mitochondrial function [Rhodamine 123], plasmalemmal integrity [fluoresceins, DNA-markers]). Fluorophores have been used in connection with operator-screened fluorescent microscopy. Although inexpensive, only a few hundred spermatozoa are assayed per sample, making this technique less accurate than flow cytometry (FACS Analyzers), a technology that examines thousands of spermatozoa within minutes, but whose high cost still represents a hindrance for its application in AI enterprises. As an alternative to assess sperm viability, fluorometry can be used to read fluorescence in large sperm numbers per sample, being sufficiently accurate and rather quickly and could, therefore, be applied for routine evaluation of semen quality [11]. The assessment of membrane integrity in large sperm populations is reflected in a relation to fertility (albeit of low significance, 11], a relation that was not present when fluorescent microscopy was used [18]. The integrity of the acrosome post-thaw can also be determined morphologically, usually at the light microscopical level, in unstained samples or with different empirical stains (Giemsa being among the most often used), with acrosome status being retrospectively and significantly related to the fertility of frozen-thawed spermatozoa [19]. Fluorophores or lectins have also been applied at this level with good correlations with fertility [20,21]. Acrosome integrity post-thaw in the bull can also be assessed indirectly by measuring enzyme leakage (such as amidases, acrosin or lactic dehydrogenases [22].

Evaluation of Sperm Chromatin Status

Concerning sperm chromatin status, evaluation of the degree of DNA denaturation using flow cytometry (the so-called SCSA method, 23) appear to be a valuable complement for the routinely practiced microscopic evaluation of sperm morphology of semen from bulls in regular production schedules, since some of the parameters tested relate to bull fertility [11].

Relationship with fertility after AI

As seen above, few single sperm viability parameters show a significant relation with the fertility of the assayed frozen-thawed semen sample, specially if it lies within accepted ranges of normality [24]. Therefore, functional in vitro tests e.g. able to disclose the ability of frozen-thawed spermatozoa to undergo complicated processes as capacitation, binding to the zona pellucida (ZP), acrosome reaction, to fertilize oocytes (IVF), and to induce embryo development in vitro have been designed and explored for their relation with the fertility achieved after AI.

Assessment of Capacitation-Like Changes and the Induction of the Acrosome Reaction

Sperm capacitation (and acrosome reaction) can be indirectly visualized by incubation of spermatozoa with the antibiotic chlortetracycline(CTC), which fluoresces while monitoring Ca++ displacement in the sperm head membrane. Analyses of frozen-thawed bull spermatozoa confirmed previous findings that cryopreservation induces capacitation-like changes [2], which in AI-bulls with known fertility occurred in up to 30 - 40 % of their processed spermatozoa [25]. Furthermore, the percentage of uncapacitated (unreacted) spermatozoa in an AI-semen batch correlated positively with its fertility after AI [25]. The acrosome reaction (AR) could be induced in vitro by exposure to glycosaminoglycans (GAGs) such as heparin [21,26]. The degree of AR after exposing frozen-thawed bull spermatozoa to heparin was significantly correlated with in vivo fertility [21]. Acrosome-reactions can also be induced by treatment with calcium ionophores (as the Hoescht A23187), and significant correlations have been found between the degree of induced AR and the NRRs of the bulls [27] even to a predictive status [20].

Sperm Ability to Bind to the Zona Pellucida (Sperm-ZP Binding Assays, ZBA)

Two types of sperm-ZP binding assays have been proven for bull spermatozoa, one using intact (not cleaved) homologous oocytes [28,29] and the other using bisected hemizonae (hemizona binding assay, HZA) [30], where each matching half is incubated with test vs control spermatozoa, respectively. Significant correlations with AI-fertility have been found using both types of ZP-binding assays [30,31] (Fig. 1). The latter method (ZBA) appears, however, much easier, less time-consuming and accurate than HZA, provided that a large number of oocytes are included per test [29].

Figure 1. Correlation (r=0.50, P=0.02, n=22) between the mean numbers of bull spermatozoa bound to the ZP and the fertility (56-d NRR) of the bulls tested (modified, from 31). The inner lines mark a threshold of fertility and a median of sperm numbers bound.

Relationship Between IVF-Embryo Development and AI-Fertility

The use of spermatozoa from a given bull affects IVF results, albeit a relationship between in vitro and in vivo fertility was not always found [32-39]. Retrospective studies of frozen-thawed semen from bulls with a large range of AI-fertility have demonstrated a significant positive correlation between cleavage rates in vitro and 56 d-NRRs [38] (Fig. 2). Pursuing a later end point of the IVF (e.g. blastocyst production), a correlation with NRR decreased owing to the higher dependence of the early embryo development on the conditions of culture than on the sperm source.

Figure 2. Relationship between percentages of cleaved oocytes 48 h post-IVF and AI-fertility (56-d non-return rates, NRR), 2-4 freezing batches/bull, 15 bulls (modified, from 38).

Prognostic value of the in vitro tests

As stated above, few single sperm parameters assessed in vitro relate to in vivo fertility. However, combining the outcome of some sperm assays in a multiple regression analysis has shown that some of these provide a discriminative, albeit retrospective, relationship with fertility [8,11,38,40] (Fig. 3). Despite this, correlation analyses are retrospective and not prospective, that is they are not predictive per se. In vitro assays including ZP-binding and IVF as above mentioned were used to calculate an expected fertility for frozen-thawed semen from young AI bulls e.g. the different outcomes were combined to calculate corrected NRRs before the actual field fertility was known [41]. When the actual 56d-NNRs for the young AI-bulls were later obtained, the calculated NNRs showed a strong relationship with AI-fertility (Fig. 4), indicating it was possible to use a combination of laboratory tests to determine semen quality and to give a prognosis on the potential fertility of an AI-bull. This appears to be an effective tool for screening semen from young AI-bulls aiming to exclude those (see Fig. 4) with a potential lower fertility from further progeny testing in an AI-program, thus allowing the restricted fertility and progeny testing space available for young bulls to be used more efficiently, with obvious economic savings.

Figure 3. Relationship between NRRs predicted by the equation based on combination of four sperm parameters (post-thaw sperm motility, linear motility (CASA), frequency of spermatozoa with denatured DNA (SCSA) and percentage of damaged spermatozoa (fluorometry) assessed in vitro and the observed field fertility (56-d NRR) of the batches tested (r=0.75, P<0.001). Line shows the trend in the data (from 11).

Figure 4. Predictive relationship (r=0.944, P=0.0001) between in vitro predicted NRRs (calculated from the testing in vitro of 3 frozen batches/bull combining 7 sperm parameters/batch) and the actual bull total AI-fertility (as 56d-NRRs). When the cut-off of sub-fertility was set at 62 % (lines) the prognosis revealed a single clear case, with most other bulls at a similar level of fertility (around 65%) (modified, from 41).

Acknowledgements

The author's own studies have been supported by grants from the Swedish Council for Forestry and Agricultural Research (SJFR), and the Swedish Farmer's Foundation for Agricultural Research (SLF), Sweden.