In vitro evaluation of sperm quality

This paper highlights selected laboratory analyses that are currently used to evaluate sperm, and describes why results from these assays do not consistently correlate with sperm fertility. Reasons for the disconnect between the two are due in part to the definition and reliability of the fertility data collected, to the complexity of the spermatozoon itself, to imprecision of some measurements, and to uncontrollable factors not associated to either the laboratory analysis or the sperm sample. Each sperm must possess a number of different attributes to fertilize an oocyte, and individual laboratory assays measure only one or a few of these attributes. Current and past data, correlating laboratory assay data with sperm fertility are presented in an effort to determine which types of assays are important to conduct and when to conduct them. Even though laboratory assay results do not allow accurate evaluation of the fertilizing potential of a semen sample, these assays are important to enable culling of poor quality samples.     

流式细胞术在哺乳动物精液质量检测中的应用

精液检测的首要目标就是快速准确地确定精子的生育力。同时具备多种特性和功能完整的精子才能受精,因而只有同时客观地检测多个指标,才能更好地反映精子的生育力。精子检测的传统方法费时费力,检测精子数量少,指标单一,而且易受操作者的主观影响,不能准确地反映精子功能。流式细胞术(FCM)为精子功能研究提供了一种快速、客观、多指标、大通量的检测手段;利用FCM检测精子的质膜完整性、顶体状态、染色质结构、线粒体功能以及细胞凋亡等,可以得知精子功能的相关情况。随着新的荧光探针、染色方法的不断开发和改进,FCM为精液质量检测提供了一种新的检测平台,应用前景极其广阔。     

Can external quality control improve pig AI efficiency?

External quality control programmes carried out by central laboratories have been long established in human andrology with the aim of enhancing the accuracy and reproducibility of semen assessment. Compared to human, demands on boar semen assessment in AI stations are more complex, with the need both to identify boars with poor ejaculate quality and to monitor individual boar differences for semen storage. Additionally, appropriate assessment serves as a control instrument to ensure the security and efficiency of semen processing. Despite current limitations regarding the ability of sperm assays to estimate the potential fertility of males, it is evident that boar fertility is related to certain conventional semen tests, e.g. sperm morphology. In central studies carried out on stored semen from 11 AI stations, flow cytometric assessment of plasma and acrosome membrane integrity proved to be more sensitive in detecting sperm damage associated with ageing and temperature stress as compared to light microscopy. Membrane integrity of stored semen differed between AI stations indicating significant influences of semen processing on sperm quality. Thus external control of semen quality in reference laboratories may be useful to monitor the efficiency of internal semen quality control in individual AI stations, to identify males with lower semen quality and/or poor response to semen storage, and to verify the precision of sperm counting. The possibility that central laboratories with sufficient resources may be able to identify functionally different responding sperm subpopulations for better estimation of fertility is discussed. Ideally, external quality control schemes for AI stations would comprise application of validated tests with high relevance for fertility (including bacterial status), analysis of semen processing on the AI station, and training courses for laboratory personnel.     

Sperm factors related to in vitro and in vivo porcine fertility

The prediction of sperm fertilizing ability has great economic importance for breeding herds when artificial insemination is used. Classical methods of semen evaluation generally measure the sperm concentration, progressive motility, percentage of viable cells, and acrosome morphology. These assays are poor in predicting sperm fertility, because only the samples with markedly poor quality can be detected. The development of new sperm tests that measure certain sperm functions is an attempt to solve this problem. On the other hand, the binding and penetration of the zona pellucida is one of the most important barriers the spermatozoa must overcome in the fertilization process. Also, the interaction with the oocyte plasma membrane appears to explain much of the variability in sperm fertilizing potential among fertile boars. Thus, the study of the relationship between sperm factors and in vitro fertility may be a good strategy and assays that include a study of gamete interaction may lead to a better way to predict male fertility than the routine laboratory evaluation of semen. This review will discuss the relationships between sperm factors and fertility in vitro and in vivo (AI trial) with both diluted and frozen-thawed semen. We will also try to analyze the problems and limitations related to the interpretation of boar sperm tests.     

Naturally and stimulated levels of reactive oxygen species in cooled stallion semen destined for artificial insemination

The decrease in foaling rates after artificial insemination with cooled semen warrants the search for new predictors of fertility. The objectives were to investigate levels of naturally occurring reactive oxygen species (ROS) in cooled, stored stallion semen doses for artificial insemination (AI), and their relationship with parameters of semen quality and with pregnancy rate. Semen was collected from warmblood stallions (n=15) and used to prepare commercial semen doses for AI. Sperm quality was evaluated after cooled transport to the laboratory overnight. The results were correlated with observed foaling and pregnancy rates. Hydroethidine and dichlorodihydrofluorescein diacetate were used as indicators for the ROS superoxide and hydrogen peroxide, respectively. Sperm morphology, motility, plasma membrane integrity and chromatin integrity were also evaluated. These variables were correlated with each other and with pregnancy rates. We found a high inter-individual variation in the ROS levels between stallions. The proportion of live, hydrogen peroxide-negative spermatozoa was correlated with progressive motility, whereas live hydrogen peroxide-negative spermatozoa and chromatin damage were negatively correlated, indicating that low levels of hydrogen peroxide were correlated with good chromatin integrity. The percentage of dead hydrogen peroxide-positive sperm was negatively related to the foaling rate. The negative relationships were stronger when combining results from both assays for ROS. These results for stored semen samples indicate that high individual variation exists for superoxide and hydrogen peroxide measurements, and that ROS status can influence sperm quality. Thus, ROS may be some of the factors influencing fertility. Moreover, combinations of ROS variables improved the correlation with fertility, indicating the usefulness of including these variables in a future model for prediction of the fertility of a semen sample.     

In Vitro Evaluation of Frozen-Thawed Stallion Semen: A Review

The article reviews methods used for in vitro evaluation of sperm, with particular emphasis on frozen-thawed stallion sperm. The techniques, limitations of the methods and correlations with fertility results are discussed. Very few studies have tried to find correlation between fertility of frozen stallion semen and laboratory tests. It is difficult and expensive to inseminate an adequate number of mares to achieve statistically significant differences. Significant, but low correlations have been demonstrated between the foaling rate and subjective motility of sperm incubated for 2 h and 4 h at 37°C and hypoosmotic swelling test after 0 and 3 h of incubation. Significant correlations have been reported between the pregnancy rate and viability of propidium iodide-stained sperm assessed by flow cytometry as well as for glass wool and Sephadex filtration tests. No correlations have been detected between fertility and motility immediately after thawing. In spite of that, motility estimation by light microscope is the most commonly used method to evaluate frozen-thawed stallion sperm. Computer assisted automatic sperm analyzers have replaced light microscopy in research projects, but so far nobody has been able to demonstrate a correlation between fertility of frozen stallion semen and any of the motility parameters obtained by these instruments.     

Storage of ram semen

Storage of ram semen in liquid and frozen state, the diluents used for both methods, processing, cooling, freezing and thawing of semen are reviewed. Factors influencing the fertility of stored semen and methods used for improvement are discussed, and fertility results of long-term frozen stored ram semen are also given.     

The predictive value of routine semen evaluation and IVF technology for determining relative boar fertility

Practical techniques for assessing semen quality in order to predict male fertility are still needed. The principal objective of this experiment was to evaluate routine laboratory evaluation and in vitro fertilization (IVF) techniques as predictors of relative boar fertility using a low-dose AI protocol. Nine boars were evaluated during a 6.5+/-1 mo period, beginning at 29-32 wk of age. Ejaculates were evaluated for motility, morphology and concentration, diluted to 1.5 billion sperm in 50 mL extender, and used to breed 50+/-5 gilts over the same period. On nine occasions, a specific aliquot of the ejaculate's first sperm-rich fraction was evaluated using IVF procedures. Boars differed (P<0.001) consistently for pregnancy rate (from 73 to 98%), farrowing rate (71-98%) and total born (8.8-12.0). Routine semen evaluation and IVF parameters that presented significant differences between boars, but no differences in time and no boar by time interaction, were used to correlate in vivo fertility. A multiple regression model based on routine semen evaluation parameters accounted for up to 27 and 22% of the variation of fertility index and total piglets born, respectively, whereas male pronuclear formation rate was the IVF variable that accounted for 17 and 12% of the variation in farrowing rate and fertility index, respectively. Collectively, we inferred that the use of low sperm numbers for AI, determination of pregnancy rate at Day 30, motility of extended semen after 7 and 10d, and specific IVF parameters may be useful for identifying relatively infertile boars that are not currently excluded from use in existing commercial boar studs.     

Fertility prediction in dairy goats from Murciano-Granadina breed: The role of sperm evaluation and female traits

Fertility is one of the most economically important traits in farm animals, due to the direct and indirect costs associated to low pregnancy rates. Thus, one of the priority goals in animal reproduction is to predict the performance that the semen doses will have in vivo based on the quality values obtained in laboratory assays. Attempts have been made for getting a predictive model of fertility of frozen-thawed sperm in dairy goats, but similar studies have not been conducted for chilled goat buck sperm doses that are mostly used for artificial insemination in many countries including Spain. We study how parameters of in vitro sperm quality and characteristics of Murciano-Granadina dairy goats may affect the in vivo fertility obtained after artificial insemination with semen doses chilled at 4 °C. Moreover, this information was used for obtaining predictive models of the fertility. Sixty-three ejaculates from 13 males were used to prepare chilled doses for the insemination of 495 goats over 13 sessions. Fresh and chilled sperm were evaluated for motility and plasma membrane integrity with a computer-assisted sperm analysis system and flow cytometry, respectively. Fertility was determined at parturition, according to the kidding goats. Overall fertility was 59.6%. Pearson’s correlation coefficients between in vivo fertility and quality variables of fresh sperm were not significant and were low (below 0.34 in absolute value) for chilled sperm. Females’ characteristics had a low negative impact on fertility (correlation coefficients of ?0.19 with age, ?0.20 with parturitions and ?0.11 with total milk yield obtained in the best lactation). Fixed and mixed logistic regression procedures were used trying to explain the fertility results. None of the models accurately predicted fertility, but the best models included the percentage of total motile sperm or average path velocity from fresh semen, age of the females and the session effect (uncontrolled environmental effects). These analyses showed that primiparous goats were 2.42 times more likely to get pregnant than goats that had kidded four or more times. Our field assay data on fertility in Murciano-Granadina dairy goats highlighted the importance of making quality controls of sperm, of choosing the doses presenting high percentages of motile sperm exhibiting regular trajectories and of selecting the youngest goats for AI, after their first kidding. Efforts should continue to obtain better predictive models for improving fertility in goat dairy herds.     

Additional value of computer assisted semen analysis (CASA) compared to conventional motility assessments in pig artificial insemination

In order to obtain a more standardised semen motility evaluation, Varkens KI Nederland has introduced a computer assisted semen analysis (CASA) system in all their pig AI laboratories. The repeatability of CASA was enhanced by standardising for: 1) an optimal sample temperature (39 °C); 2) an optimal dilution factor; 3) optimal mixing of semen and dilution buffer by using mechanical mixing; 4) the slide chamber depth, and together with the previous points; 5) the optimal training of technicians working with the CASA system; and 6) the use of a standard operating procedure (SOP). Once laboratory technicians were trained in using this SOP, they achieved a coefficient of variation of < 5% which was superior to the variation found when the SOP was not strictly used. Microscopic semen motility assessments by eye were subjective and not comparable to the data obtained by standardised CASA. CASA results are preferable as accurate continuous motility dates are generated rather than discrimination motility percentage increments of 10% motility as with motility estimation by laboratory technicians. The higher variability of sperm motility found with CASA and the continuous motility values allow better analysis of the relationship between semen motility characteristics and fertilising capacity. The benefits of standardised CASA for AI is discussed both with respect to estimate the correct dilution factor of the ejaculate for the production of artificial insemination (AI) doses (critical for reducing the number of sperm per AI doses) and thus to get more reliable fertility data from these AI doses in return.     

Relationship between fertility in cattle and the number of inseminated spermatozoa

Five different two-parameter models were fitted to published data from 30 studies to identify an approximate mathematical form of the relationship between fertility in cattle and the number of inseminated spermatozoa. In all cases, the first parameter defines the maximum attainable fertility, and the second scales the dose according to the percentage of the maximum attained. The best model was the hyperbolic dose-response curve used in pharmacology to analyse the effect of drugs. There is evidence that the semen of individual bulls differs in both parameters of the models and that therefore the viability of semen may be multidimensional. This might explain why measures of semen quality have hitherto been found to correlate poorly with fertility. The hypothesis that spermatozoa are subject to the law of mass action at the ovum predicts these and some other aspects of fertility, and indicates that heterospermic inseminations may provide an efficient way of estimating the parameters of semen.     

Comparison of in vitro laboratory analyses with the fertility of cryopreserved stallion spermatozoa

Assessing the fertilizing potential of a semen sample is important for effective stallion management and for rapid progress in evaluating new cryopreservation technologies. Unfortunately, sperm motility does not estimate fertility well. These experiments established assays to measure cell viability, acrosomal integrity and mitochondrial function for cryopreserved stallion spermatozoa, using flow cytometry, and determined the variability associated with these assays. Correlations between results for these laboratory assays and stallion fertility were also determined. The inter-assay variability for visual motility, computer assisted motility, and sperm velocity, sperm viability, percent viable-acrosome intact cells and mitochondrial function of cells were all similar, however, intra-assay variability was lower for flow cytometric assays than for motility assays. The reliability of all assays were >0.72, except for sperm velocity (0.32). Although visual motility and the straightness of sperm motility conducted 90 min after thawing were correlated with seasonal fertility (0.56 and 0.55, respectively), data from no single assay were correlated with first-cycle fertility rates (P > 0.05). Best models using data from multiple assays explained 66 to 73, 76 to 89 and 79 to 94% of the variability in fertilizing potential, when two, three and four variables were included, respectively. Caution is required in interpreting these data, as only a few stallions were evaluated and relatively few mares were bred to each stallion, however, they do indicate that using a few rapid and inexpensive sperm assays, we can begin to understand factors important in stallion sperm fertilizing capacity, and we can use these assays to more effectively evaluate new methods for cryopreserving stallion spermatozoa.     

Identifying useable semen

The "predictors of useable semen" used in most commercial AI centers provide a very conservative estimate of the relative fertility of individual boars. Furthermore, the relatively high sperm numbers used in commercial AI practice (usually >3 x10(9) total sperm per dose of extended semen) usually compensate for reduced fertility, as can be demonstrated in some boars when lower numbers of sperm are used for AI. Differences in relative boar fertility are also masked by the widespread use of pooled semen for commercial AI in many countries. However, the need to continually improve the efficiency of pork production, suggests that commercial AI practice should involve increased use of boars with the highest genetic merit for important production traits. Necessarily, this must be linked to the use of fewer sperm per AI dose, fewer inseminations per sow bred, and hence more sows bred by these superior sires. In turn, this requires improved techniques for evaluating semen characteristics directly related to the fertilization process, such as IVM-IVF assays, analysis of seminal plasma protein markers, more discriminatory tests of sperm motility and morphology, with the goal of identifying high-index boars whose fertility is sustained when low numbers of sperm are used for AI. This paper reviews the current status of laboratory-based boar semen evaluation techniques that meet these criteria.     

Sperm yield after single layer centrifugation with Androcoll-E is related to the potential fertility of the original ejaculate

Many attempts have been made to identify laboratory tests that are predictive of sperm fertility, both to improve the quality of stallion semen doses for artificial insemination (AI) and to identify potential breeding sires if no fertility data are available. Sperm quality at the stud is mostly evaluated by assessing subjective motility, although this parameter can be poorly indicative of fertility. Sperm morphology and chromatin integrity in Swedish stallions are correlated to pregnancy rate after AI. Because single layer centrifugation (SLC) selects for spermatozoa with normal morphology and good chromatin, retrospective analysis was carried out to investigate whether sperm yield after SLC is linked to potential fertility. Commercial semen doses for AI from 24 stallions (five stallions with four ejaculates each, 19 stallions with three ejaculates each; n = 77) obtained during the breeding season were cooled, and sent overnight to the Swedish University of Agricultural Sciences in an insulated box for evaluation, with other doses being sent to studs for commercial AI. On arrival at Swedish University of Agricultural Sciences, the semen was used for SLC and also for evaluation of sperm motility, membrane integrity, chromatin integrity, and morphology. The seasonal pregnancy rates for each stallion were available. The yield of progressively motile spermatozoa after SLC (calculated as a proportion of the initial load) was found to be highly correlated with pregnancy rate (r = 0.75; P < 0.001). Chromatin damage was highly negatively correlated with pregnancy rate (r = −0.69; P < 0.001). Pregnancy rate was also correlated with membrane integrity (r = 0.58; P < 0.01), progressive motility (r = 0.63; P < 0.01), and normal morphology (r = 0.45; P < 0.05). In conclusion, these preliminary results show that sperm yield after SLC is related to the potential fertility of the original ejaculate, and could be an alternative indicator of stallion fertility if breeding data are not available. Single layer centrifugation is fast (30 minutes) and does not require expensive equipment, whereas other assays require a flow cytometer and/or specialist skills. An additional option could be to transport semen doses to a laboratory for SLC if the stud personnel do not want to perform the procedure themselves.     

Determining sample size for the morphological assessment of sperm

Morphologic assessment of spermatozoa is an integral component in the analysis of semen. Whether a technician rapidly screening semen quality at a commercial stud, a veterinarian performing breeding soundness examinations, a clinician at a reference andrology laboratory providing auditing or diagnostic services, or a researcher evaluating morphology as a part of a fertility study, it is important to make an informed decision regarding the number of spermatozoa to include in the morphology assessment. Application of basic statistical principles such as the nature of proportions, level of confidence in an observed value, and the interaction of sample size with precision, can and should be used in the decision process. This paper outlines in detail the application of these statistical principles in relation to the morphologic assessment of spermatozoa. Guidelines on how these principles can be utilized in practical situations are discussed. Additionally, methodologies for comparison of results within and between laboratories (an area easily prone to misinterpretation) are reviewed. It is hoped that through the use of these fundamental statistical principles, this paper will bring clarity and delineation to the science of quantifying the morphology of spermatozoa.     

Influence of Boars on the Relationship between Fertility and Post Thawing Sperm Quality of Deep Frozen Boar Spermatozoa*

The aim of this investigation was to evaluate the possibility of selecting boars for deep freezing by means of laboratory tests on frozen-thawed spermatozoa. Thirty-one randomly selected frozen ejaculates from four boars were investigated by a thermoresistance test after thawing in boar seminal plasma and in OLEP. Extracellular ASAT activity was measured in samples from 30 of the ejaculates after thawing in OLEP and in isotonic glucose solution. Twenty of the ejaculates were utilized for fertility tests by artificial insemination of 37 gilts preceding the laboratory investigation. Three of the boars proved fertile with frozen semen. One of these boars seemed to yield superior fertility to the other two boars. No fertility was obtained with frozen spermatozoa from the fourth boar. Prior to the freezing trial this boar had been used for fresh semen inseminations giving higher pregnancy rates than the average of Swedish A.I.-boars. This boar was therefore considered a case of “low freezability”. In the laboratory tests the samples from this boar showed the lowest motility after 3 hrs.’ storage at 37°C, the highest relative decrease of motility during the thermoresistance test, the highest release of ASAT after thawing in OLEP and the highest relative release of ASAT. Analyses of variance indicated significant and almost significant variation among boars in relative decrease of motility during the thermoresistance test and in relative release of ASAT. The results indicate that the boars were the main cause of variation in fertility as well as in outcome of the laboratory tests. These results do not permit a complete evaluation of the relationship between fertility and outcome of the applied laboratory tests. However, the results indicate a possibility of detecting boars producing spermatozoa with low freezability by means of laboratory tests.     

Thermoresistance sperm tests are not predictive of potential fertility for cryopreserved bull semen

Different studies demonstrate positive correlations between seminal variables determined in the laboratory and subsequent fertility after artificial insemination. It is clear, however, that there is still a deficiency in predicting in vivo fertility results of semen samples. The present study intended to verify the efficiency of rapid and slow thermoresistance tests in predicting fertility of frozen semen of bulls. Sperm from 64 ejaculates of 39 Nelore bulls (Bos indicus), aged 2-10 years, were cryopreserved in 0.5 mL straws. Thawed straws containing 30 x 10(6) sperm were analyzed for seminal variables in the laboratory and used to inseminate 4920 cows to evaluate fertility in the field. The ejaculates were frozen in a Tris-based extender and samples were evaluated for total motility after rapid (46 degrees C/30 min) and slow (38 degrees C/5h) thermoresistance tests by conventional and computerized (CASA) methods. Sperm samples were grouped according to their ability to retain motility after thermoresistance testing: group 0 (0% motility), group 1 (1-20% total motility), group 2 (21-40% total motility) and group 3 (>40% total motility). Correlation and association between these groups and fertility diagnosed by rectal palpation at 90 days were verified. Chi-square test demonstrated no association between motility groups and fertility (P>0.25) and both rapid and slow thermoresistance tests had a lesser correlation to fertility (r=0.11 and 0.14, respectively). These results demonstrated that these tests are not reliable in predicting in vivo behavior of bull frozen semen and are not effective to estimate fertility.     

Genetic markers for stallion fertility--lessons from humans and mice

Our knowledge on the many aspects of mammalian reproduction in general and equine reproduction in particular has greatly increased during the last 15 years. Advances in the understanding of the physiology, cell biology, and biochemistry of reproduction have facilitated genetic analyses of fertility. Currently, there are more than 200 genes known that are involved in the production of fertile sperm cells. The completion of a number of mammalian genome projects will aid in the investigation of these genes in different species. Great progress has been made in the understanding of genetic aberrations that lead to male infertility. Additionally, the first genetic mechanisms are being discovered that contribute to the quantitative variation of fertility traits in fertile male animals. As artificial insemination (AI) represents a widespread technology in horse breeding, semen quality traits may eventually become an additional selection criterion for breeding stallions. Current research activities try to identify genetic markers that correlate to these semen quality traits. Here, we will review the current state of genetic research in male fertility and offer some perspectives for future research in horses.     

Does attractiveness in men provide clues to semen quality?

The psychological mechanisms underlying attractiveness judgements in humans are thought to be evolved adaptations for finding a high quality mate. The phenotype-linked fertility hypothesis proposes that females obtain reliable information on male fertility from male expression of sexual traits. A previous study of Spanish men reported that facial attractiveness was positively associated with semen quality. We aimed to determine whether this effect was widespread by examining a large sample of Australian men. We also extended our study to determine whether cues to semen quality are provided by components of attractiveness: masculinity, averageness and symmetry. Each male participant was photographed and provided a semen sample that was analyzed for sperm morphology, motility and concentration. Two independent sets of women rated the male photographs for attractiveness, and three further sets of 12 women rated the photographs for masculinity, symmetry or averageness. We found no significant correlations between semen quality parameters and attractiveness or attractive traits. Although male physical attractiveness may signal aspects of mate quality, our results suggest that phenotype-linked cues to male fertility may not be general across human populations.     

Microscopic and flow cytometric semen assessment of Dutch AI-bucks: effect of semen processing procedures and their correlation to fertility

This study was done to determine the effects of processing techniques on the quality of semen from Dutch AI-bucks with the view on improving pregnancy rates after artificial insemination (AI) with liquid or frozen-thawed semen. Motility of spermatozoa was estimated under a microscope whereas the percentage live spermatozoa and the percentage live spermatozoa with intact acrosomes were determined by means of flow cytometry. Aspects of semen processing that were investigated are storage temperature of liquid semen (i), the effect of glycerol on liquid-stored semen (ii), removal of seminal plasma (iii) and type of extender (iv). The correlation between semen quality and fertility rates in inseminated does was also investigated. The percentage motile spermatozoa in semen stored in liquid form for 72 h progressively declined over time, irrespective of whether storage occurred at 4 or 18 degrees C. The percentage motile spermatozoa in semen stored at 18 degrees C was similar to that in semen stored at 4 degrees C if stored for 24 h but lower if stored for 48 h. Goats differ in the sensitivity of their spermatozoa to the deleterious effects of glycerol. Neither the removal of seminal plasma nor the type of extender had any effect on semen quality before freezing but semen frozen in a Tris-citric acid-glucose (TCG) buffer with egg yolk without removal of the seminal plasma had better quality after thawing than semen frozen in another diluent or after removal of seminal plasma. Remarkably no significant correlation between fertility and membrane integrity of spermatozoa could be found. Thus, although integrity assays for spermatozoa are useful to asses resistance to semen handling, the validity of these assays for predicting fertility is questioned.