FOURIER HARMONICS, SPERM HEAD SHAPE AND ITS RELATIONSHIP TO FERTILITY

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1 FOURIER HARMONICS, SPERM HEAD SHAPE AND ITS RELATIONSHIP TO FERTILITY INTRODUCTION Kilby Willenburg Reproquest Inc McKee Road, Fitchburg, WI USA Fourier harmonic analysis (FHA) is a computerized imaging system that describes the curvature of the perimeter of the sperm head. The sperm head is 90% DNA and the shape is based on the structure of the DNA. Any change in chromatin structure will be reflected by a change in sperm shape. This technique has described the size and curvature of mammalian sperm nucleus for over a decade. Bull, boar and stallion sperm have all been characterized with the nuclear shape of the bull and boar being related to fertility. Fourier harmonics has been used for identifying abnormal shaped sperm as well as boars representative of summer stress related problems. The following review details the relevance of FHA and how it can be a useful tool in the swine industry by citing data in multiple species with special interest in identifying boars with unacceptable fertility. Fourier Harmonics Analysis Fourier harmonic analysis requires staining the sperm cell nuclear material with Hoechst The cells are washed and dried on a microscope slide and then imaged. Finally, using statistical analysis perimeter coordinates are converted from Cartesian to polar coordinates and Fourier functions constructed and harmonic amplitudes (HA) of the functions determined. The size and shape of the sperm cell nucleus are characterized using harmonic amplitudes 0-5 (Figure 1). Harmonic amplitude 0 (HA0) is the overall size of the sperm where HA1 through 5 are component integers of HA0 that help to characterize HA0. Harmonic amplitude 1 describes the anterior portion of the nucleus, as this value increases so does the overall roundness of the cell. Elongation and width of the sperm cell nucleus is characterized with HA2 and 4, whereas the posterior half of the nucleus is represented by HA3 and 5. Ostermeier et al., (2001A) first described the bull sperm nucleus with FHA and demonstrated that abnormal sperm can be distinguished with FHA. Figure 1 from Ostermeier et al., (2001A, figure not shown) showed that FHA is able to differentiate sperm with different nuclear shapes (normal, macrocephalic and pyriform) which is particularly important since the evaluation of sperm morphology generally relies on subjective microscopic examination (Barth and Oko, 1989). Multiple observers can classify the same sperm differently depending on their interpretation of normal and abnormal morphology (Dunphy et al., 1989). Therefore accuracy and repeatability are important to identify sperm morphologies to ensure that poor quality ejaculates are discarded.

2 Fourier Harmonic Analysis and Summer Stress Pigs by nature are short day breeders and are capable of experiencing reproductive quiescence. The transition from outdoor to indoor housing has lessened this effect and allowed females to have multiple litters in a year (PigChamp). However, pigs are still susceptible to seasonal variation (Cameron and Blackshow, 1980) regardless of controlling for temperature and light. In boars, high ambient temperatures have been shown to decrease reproductive efficiency (Kunavongkrit et al., 1989). Temperatures above 30 C can affect spermatogenesis and cause testicular degeneration resulting in a lower sperm concentration and a decrease in semen volume (Kunavongkrit and Prateep, 1995), an increase in sperm abnormalities (McNitt and First, 1970) and the time interval for a boar to mount a collection dummy or sow (Claus and Weiler, 1985). The affects of summer infertility are real and come as a significant expense to producers (Cameron and Blackshow, 1980). The supplementary cost of maintenance for additional boars to compensate for the loss of viable sperm cell, labor and loss of productivity all come as an expense to the swine industry. So far identification of problematic boars is entirely retrospect and not noticed until there is a significant increase in sperm morphology or an increase in the number of sows returning to estrus. The ability to identify animals that are susceptible to the effects of heat and photoperiod would be a great economic advantage and save the industry millions of dollars. The following data describes the use of FHA as a diagnostic tool to identify changes in sperm nuclear shape in boars during the summer. We hypothesized that if boars were affected by summer stress then changes in sperm nuclear shape would be detected by FHA. This study used boars (n = 8) of proven fertility from a commercial stud in southern Wisconsin from May until the middle of October. The boars were collected weekly for stud use but FHA and all sperm measurements were performed biweekly. The temperature, humidity, semen volume, concentration, motility, viability and gross morphology (abnormal heads, tails, proximal and distal droplets) were analyzed along with HA0-5. There were differences in sperm nuclear size (HA0) three times during the summer (P < 0.001) that corresponded to an increase in temperature and humidity approximately 1 month prior. The average sperm size (HA0) was significantly decreased on June 23 rd, August 8 th and August 22 nd with a size of ± 0.030, ± and ± microns, respectively compared to an HA0 of ± microns in May when there was not a significant increase in temperature and humidity (Figure 2). Figure 3 represents this change in nuclear size from the average HA0 on May 22 nd compared to the average HA0 on August 8 th. Harmonic amplitude 4 was also significantly lower on July 24 th compared to the first measurement in May (0.175 ± vs ± microns). Interestingly, the effects on HA4 were observed approximately 3 weeks after the increase in temperature and humidity (Figure 4). There were also differences in sperm concentration, motility, viability, normal sperm and distal droplets on July 10 th and August 22 nd which were evident approximately 5 weeks after increases in temperature and humidity (P < 0.05, data not shown). The data shows the potential use of FHA as diagnostic tool to identify boars that have been affected by summer stress. Identification via harmonic amplitudes can occur 1-2 weeks prior to the increase in sperm abnormalities, which would

3 potentially allow producers to maintain a high level of fertility throughout the breeding herd without any significant profit loss. Fourier Harmonic Analysis and Fertility Identifying sub-fertile boars presents unique challenges to the swine industry. The industry is in need of an accurate, cost effective method to identify sub-fertile animals or ejaculates that would offset the use of pooled semen and allow the expression of specific traits from high indexing animals. Quantitative analysis of physiological aspects of sperm function is currently used in boar studs but may not be the best indicator of boar fertility. Saacke et al (1994) has suggested that there are two types of fertility defects in sperm that are responsible for reproductive failure. They have been termed compensable and uncompensable sperm characteristics (Saacke et al. 1994) based on whether reproductive performance improves with increasing sperm numbers. A dose of semen that has a large percentage of sperm with abnormalities is unable to reach the site of fertilization. However, increasing the number of sperm inseminated can overcome fertility losses and thus can be termed compensable (Saacke et al., 1994). Conversely, insemination doses unable to increase fertility levels despite containing ample numbers of sperm are known as uncompensable (Saacke et al., 1994). Thus, every dose of semen inseminated in the U.S. is compensable due to the high number of sperm (3x10 9 ) per dose. Regardless of supplementing semen for compensable sperm traits fertility is still limited. To date, the Sperm Chromatin Structure Assay (SCSA) has related to fertility in the bull (Ballachey et al., 1987), boar (Evenson et al., 1994), ram (Sailer et al., 1995) and human (Evenson et al., 1980) but is very costly and requires the use of a flow cytometer. Similarly, Fourier harmomic analysis, which accurately describes the perimeter of the sperm head, has been correlated with fertility in the bull (Ostermeier et al., 2001B) and boar (in publication). In a recent study, semen from boars (n = 94) from 5 different US studs with similar genetics was collected and related to fertility. The boars had a minimum of 50 single sire matings and were separated into two fertility groups (Acceptable and Unacceptable) based on three standard deviations from the mean for total born (TB) and adjusted farrowing rate (AFR). The average total born (TB) and adjusted farrowing rate (AFR) from all the boars was (8.40 to 14.90) and % (55.30 to ), respectively. The boars in the acceptable fertility group (n = 92) had an average TB = whereas the unacceptable fertility group (n = 2) had a TB = The boars (n = 91) in the AFR acceptable group had an average AFR of compared to for the unacceptable boars (n = 3). Table 1 shows that fertility groups differed in sperm nuclear shape (P < 0.05) and only HA1, HA2 and HA4 were different between the groups for TB and HA2 and 4 were different for AFR (P < 0.05). This supports FHA fertility data from the bull (Ostermeier et al., 2001B) and boar (preliminary trial) where HA 2 and 4 were different between acceptable and unacceptable fertility groups showing the similarities of low fertility animals regardless of species or genetics. Figure 5 and 6 show the average sperm shape for boars in the unacceptable and acceptable group for TB and AFR. Both figures are similar in shape with the unacceptable boars being longer and slimmer than the average

4 sperm shape of the acceptable boars. Finally a model was constructed to predict the fertility group membership of a boar. A boar can be classified in one of four different categories (true positive (TP, classifying an acceptable boar correctly), true negative (TN, classifying an unacceptable boar correctly), false positive (FP, classifying an unacceptable boar incorrectly) and false negative (FN, classifying an acceptable boar incorrectly)) based on the model created. The TB model with the fewest parameters and highest TP + TN value included HA 1, 2 and 4 with a TP + TN value of The AFR model consisted of HA2 and HA4 with a TP + TN value of The TB model correctly classified 94% of the boars, misclassifying 6 of the acceptable boars, whereas the AFR model correctly identified 90% of the boars misclassifying 9 of the acceptable boars. CONCLUSIONS The search for a single test or a combination of tests to predict fertility has been ongoing for decades (Amann, 1989). However, there does not appear to be a simple answer to this complex question or a single all encompassing test (Braundmeier and Miller, 2001). Fourier harmonics as described in this review has shown it can be a useful tool to identify bulls and boars with unacceptable fertility and perhaps as an indicator of boars that are heat stressed. The relatively high numbers of sperm (> 3 x 10 9 ) used in an AI dose in conjunction with the practice of semen pooling further confound the difficulty of identifying boar fertility as well as negate the potential of many tested fertility models. This conventional industry procedure eliminates the possibility of compensable seminal factors influencing fertility leaving AI doses with only uncompensable factors, which are most likely responsible for the DNA fragmentation tests being correlated with fertility. Furthermore, FHA would eliminate some of the boars with uncompensable fertility traits and increase reproductive efficiency by housing fewer boars and inseminating a lower number of sperm cells. Fourier harmonics is not a perfect or all encompassing fertility test but it can be a useful tool in the swine industry. Additional research is needed to fully test this technique and perhaps explore other tests that would complement FHA and improve the overall accuracy of diagnosis. REFERENCES Amann R.P Can the fertility potential of a seminal sample be predicted accurately. J. Androl. 10: Ballachey B.E., Hohenboken W.D., and Evenson D.P Heterogeneity of sperm nuclear chromatin structure and its relationship to bull fertility. Biol. Reprod. 36(4): Barth A.D and Oko R.J In: Barth A.D., oko R.J. eds. Abnormal Morphology of Bovine Spermatozoa. Ames: Iowa State University Press:

5 Braundmeier A.G. and Miller D.J The search is on: finding accurate molecular markers of male fertility. J. Dairy Sci. 84(9): Cameron R.D.A and Blackshaw A.W The effect of elevated ambient temperature on spermatogenesis in the boar. J. Reprod. Fertil. 59: Claus R. and Weiler U Influence of light and photoperiodicity on pig prolificacy. J. Reprod. Fertil. Suppl. 33: Dunphy B.C., Kay R., Barratt C.L.R. and Cooke I.D Quality control during the conventional analysis of semen, an essential exercise. J. Androl. 10: Evenson D.P., Darzynkiewicz Z., and Melamed M.R Relation of mammalian sperm chromatin heterogeneity to fertility. Science. 240: Evenson D.P., Thompson L., and Jost L.K Flow cytometric evaluation of boar semen by the sperm chromatin structure assay as related to cryopreservation and fertility. Theriogenology 41: Kunavongkrit A. and Prateep P Influence of ambient temperature on reproductive effieciency in pigs:(1) boar semen quality. Pig J. 35:43-7. Kunavongkrit A., Poomnsuwan P., and Chantaraprateep P Reproductive performance of sows in Thailand. Thai. J. Vet.Med. 19(4): McNitt J.I. and First N.L Effects of 72-hours heat stress on semen quality in boars. Int. J. Biometeorol. 14: Ostermeier C., Sargent G.A., Yandell B.S., and Parrish J.J. 2001A. Measurement of bovine sperm nuclear shape using Fourier harmonic amplitudes. J. Androl. 22: Ostermeier G.G., Sargent G.A., Yandell B.S., Evenson D.P., and Parrish J.J. 2001B. Relationship of bull fertility to sperm nuclear shape. J. Androl. 22(4): PigChamp. PigChamp home page Available at: Accessed Nov 19, Saacke R.G., Nadir S., and Nebel R.L Relationship of semen quality to sperm transport, fertilization, and embryo quality in ruminants. Theriogenology 41:45-50.

6 Sailer B.L., Jost L.K., and Evenson D.P Mammalian sperm DNA susceptibility to in situ denaturation associated with the presence of DNA strand breaks as measured by terminal deoxynucleotidyl transferase assay. J. Androl. 16: TABLE AND FIGURES Figure 1. The relationship between harmonic amplitude (HA0-5) and boar sperm nuclear shape.

7 Temp (F) Microns Figure 2. The relationship between daily maximum temperature and average sperm nuclear size A (HA0) for boars (n = 8) from May until October. Max Temp HA May June * * * July Aug Sept Oct A Values for the average sperm nuclear size are indicated via symbol X with their respective values on the secondary Y axis. * Indicates significance (P < 0.01) for June 23 rd, August 8 th and August 22 nd.

8 Figure 3. The average nuclear sperm size (μm) for all boars (n = 8) on May 22 nd and August 8 th.

9 Temp (F) Microns Figure 4. The relationship between daily heat index A values and average harmonic amplitude 4 B (HA4) for boars (n = 8) from May until October. Heat Index HA May June July * Aug Sept Oct A Heat index (HI) was calculated using the human HI formula by using the average daily temperatures and average daily humidity values. Heat Index values were calculated online from the Midwest Regional Climate Center (Champaign, IL). B Values for the average harmonic amplitude 4 are indicated via symbol X with their respective values on the secondary Y axis. * Indicates significance (P < 0.001) for July 24 th.

10 Figure 5. The average sperm nuclear size (μm) and shape between boars with acceptable (n = 92) and unacceptable (n = 2) fertility * for Total Born. * The boars had a minimum of 50 single sire matings. Boars in the unacceptable group were 3 standard deviations below the mean for total born.

11 Figure 6. The average sperm nuclear size (μm) and shape between boars with acceptable (n = 91) and unacceptable (n = 3) fertility * for Adjusted Farrowing Rate. * The boars had a minimum of 50 single sire matings. Boars in the unacceptable group were 3 standard deviations below the mean for Adjusted Farrowing Rate.

12 Table 1. Mean and standard error of the mean (SEM) for harmonic amplitudes (HA) measured in micrometers ( M) from the boars with acceptable and unacceptable fertility for both total born and adjusted farrowing rate models. Total Born 1 Adjusted Farrowing Rate 2 Acceptable Unacceptable P Value Acceptable Unacceptable P Value (μm) HA ± ± ± ± HA ± ± ± ± HA ± ± ± ± HA ± ± ± ± HA ± ± ± ± HA ± ± ± ± The boars had a minimum of 50 single sire matings. Boars in the unacceptable group (n = 2) were 3 standard deviations below the mean of the boars in the acceptable fertility group (n = 92). 2 The boars had a minimum of 50 single sire matings. Boars in the unacceptable group (n = 3) were 3 standard deviations below the mean of the boars in the acceptable fertility group (n = 91).