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From the * J.O. Almquist Research Center,
Department of Dairy and Animal Science, and
The Huck Institute of Life Sciences, The
Pennsylvania State University, University Park, Pennsylvania.
| Correspondence to: Dr Gary J. Killian, J.O. Almquist Research Center, Department of Dairy and Animal Science, The Pennsylvania State University, University Park, PA 16802 (e-mail: gkillian{at}psu.edu). |
| Received for publication May 5, 2005; accepted for publication August 2, 2005. |
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Abstract |
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0) or low- (PD < 0) fertility sires. The former were neither
less nor more homogeneous than the latter based on correlations of all matched
spots between pairs of AGF maps. However, high fertility of dairy bulls was
significantly associated with lower expression of 14-kDa spermadhesin Z13
isoforms and higher amounts of 55-kDa osteopontin and 58-kDa phospholipase
A2 (PLA2) isoforms. The average intensity of 5 spots
identified as BSP 30 kDa in the AGF gels had a quadratic association with
fertility indexes (R2 = .18; P = .03). PD values of bulls were
related (R2 = .56) to the quantity of spermadhesin, osteopontin,
and BSP 30 kDa in the AGF polypeptide maps. Bull fertility was also determined
by another equation (R2 = .53) with spermadhesin, BSP 30 kDa, and
PLA2 as independent variables. We conclude that interactions among
several proteins in accessory sex gland fluid explain a significant proportion
of the variation in fertility scores of mature dairy sires.
Key words: BSP 30 kDa, osteopontin, phospholipase A2, seminal plasma, spermadhesin
Previously, we utilized a technique to obtain secretions from the accessory sex glands and cauda epididymis by catheterization of the vas deferens (Henault et al, 1995). This unique model enables the collection of accessory gland fluid from living individuals, free of germ cells and components from the testis and epididymis. Although the surgically altered animal does not perfectly mimic the events that occur naturally, when secretions from accessory sex glands are mixed with spermatozoa and epididymal fluid at ejaculation, this model does make it possible to obtain for study a composite of accessory gland secretions mixed by the living animal. In the current study, we report the use of a proteomic approach to identify proteins in samples of accessory sex gland fluids from Holstein bulls of documented fertility and determine if relationships exist between their expression and fertility indexes.
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Materials and Methods |
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TopAbstractMaterials and MethodsResultsDiscussionReferences |
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Fertility Indexes of Bulls
Holstein bulls and information about nonreturn rates (NRRs) were provided
by artificial insemination (AI) cooperatives in the northeastern United
States. The number of services using frozen semen from each bull ranged from
269 to 77 321. Individual NRRs for each bull were based on the number of cows
that did not return to be inseminated within 60 days after the first
insemination, relative to the total number of cows that were inseminated. To
compensate for small variations among data sets obtained from different AI
centers, the fertility index of each bull was expressed as the percentage
point deviation (PD) of its NRR from the average NRR of all bulls in a given
AI center (Killian et al,
1993). Bulls used in the present study had PDs from the average of
+7.7% to -18.1%. There were 18 animals with PD 0 and 19 with PD <
0.
Electrophoresis
Samples of AGF were removed from liquid nitrogen, thawed at room
temperature, and centrifuged at 10 000 x g (60 minutes at
5°C). The supernatant was then assayed for protein content
(Lowry et al, 1951) using
bovine serum albumin as standards and aliquots, frozen at -80°C. When used
for electrophoresis, samples were thawed at room temperature and subjected to
2-dimensional electrophoresis (Killian et
al, 1993). Isoelectric focusing was carried out in tube gels (Bio
Rad, Rockville Centre, NY) containing a mixture of ampholytes with pH
3–7 (0.4 ml) and 3–10 (0.1 ml; Serva, Heideberg, Germany). Samples
of AGF containing 500 µg of protein were brought to a volume of 100 µL
using a solution of ß-mercaptoethanol, urea, and the same ampholytes used
in the gels. Gels were then subjected to 200 V for 15 minutes, 300 V for 30
minutes, 400 V for 30 minutes, 375 V for 16–18 hours, and 800 V for 1
hour. Following focusing, gels were removed from the tubes and placed on
stacking gels that had been prepared on the top of gels containing a linear
gradient of acrylamide (10%–17.5%). Standards from 66 to 14 kDa were
also used (Sigma Chemical Co, St Louis, Mo). Gels were stained with Coomassie
brilliant blue R-250; destained in a solution of methanol, acetic acid, and
deionized distilled H20; and scanned using a GS-670 imaging
densitometer (Bio Rad, Rockville Centre, NY). Images saved as TIFII files were
analyzed using PDQuest software, version 7.3.0 (Bio Rad). For the set of AGF
polypeptide maps, a single master gel was generated by the software, which
represented the best pattern of spots in the samples. Few additional spots
consistently present in some gels were also added to the master so that they
could be matched to all samples. Proteins in key regions of the gels were used
as landmarks and final matching of spots was achieved after several rounds of
extensive comparisons. Control of spot matches was done by checking each spot
in each gel with the respective pattern in the master. Protein quantities in
the gels were given as ppm of the total integrated optical density of the
spots, according to PDQuest.
Preliminary results revealed the presence of an unidentified
low–molecular-weight polypeptide in the AGF that was inversely related
to bull fertility scores. The molecular weight and pI for this peptide were
similar to those of a low-fertility protein (
16 kDa; pI 6.7) originally
described by Killian et al
(1993) in the seminal plasma
of another group of Holstein bulls. Therefore, to determine if these proteins
shared the same identity, seminal plasma from bulls used in Killian's original
study was thawed after storage in a -80°C freezer, subjected to
bidimensional electrophoresis, and three spots at 14 kDa and pIs
6.7–6.9 were analyzed by tandem mass spectrometry.
Protein Identification
Proteins separated by 2-dimensional SDS-PAGE and selected by PDQuest
software (Bio Rad) were subjected to in-gel trypsin digestion as described
elsewhere (Koc et al, 2001).
Excised gel pieces were washed three times with 100 µL of ammonium
bicarbonate (25 mM) and dehydrated with 100 µL of acetonitrile (50%), and
dried in a speed vacuum. They were then incubated overnight at 37°C with
trypsin (12.5 ng/µL in 25 mM ammonium bicarbonate). Peptides were then
extracted twice with 25 µL of formic acid (5%) for 20 minutes. The extracts
were dried in a speed vacuum again and resuspended in 10 µL of 5%
acetonitrile with formic acid (0.1%).
Tryptic digests were analyzed by capillary liquid chromatography-nanoelectrospray ionization-tandem mass spectrometry (CapLC-MS/MS). A Micromass Q-Tof API US mass spectrometer coupled with a Waters CapLC high-performance liquid chromatography (HPLC) unit (Waters Co, Milford, Mass) was used for the analysis (Abbas et al, 2005). The proteolytic digests (1–5 µL) were injected into solvent A (acetonitrile/water/formic acid, 5/95/0.1) supplied by the auxiliary pump of the capillary HPLC unit and trapped in a Waters Symmetry 300 column (C-18, 5 µm film; 0.3 mm x 5 mm) for on-line desalting and pre-concentration (Abbas et al, 2005). After washing for 3 minutes with solvent A at 20 µL/min, trapped peptides were then back flushed with the gradient solvent flow on to the analytical column, a Dionex PepMap fused-silica capillary column (C-18 5 µm, 0.075 mm x 150 mm), using a 10-port switching valve. The analytical column was run with a gradient (5%–42% solvent B; acetonitrile/water/formic acid; 95/5/0.2) in 44 minutes. The mass spectrometry was calibrated using Glu-Fib product ion fragments as needed to maintain mass accuracy within 10 ppm. The Q-Tof mass spectrometer was operated to acquire MS/MS of tryptic peptides in data-dependent acquisition mode for precursor ion selection using charge-state recognition and intensity threshold as selection criteria using MassLynx 4.0 SP1. In order to carry out the tandem mass spectrometric data acquisition, a survey scan (2 seconds) over the m/z of 400–1500 was performed. From each survey scan, up to 4 most intense precursor ions based on the selection criteria were selected for MS/MS to obtain the production spectra resulting from collision-induced dissociation in the presence of argon. The product ion spectra (6–8 seconds) collected were processed using Protein Lynx Global Server 2.1 and were converted to peak list text files for database searching. In order to identify the proteins, MS/MS ion searches were performed on the processed spectra against a locally maintained copy of the NCBI NR database using MAS-COT Daemon and search engine (Matrix Science, Inc, Boston, Mass). The searches were made with the assumption that there was 1 maximum missed trypsin cleavage and that peptides were monoisotropic and oxidized at methionine residues and carbamidomethylated at cysteine residues. Peptide mass tolerance and fragment mass tolerance were initially set to 1.2 and 0.6 Da, respectively, for MS/MS ion searching. However, peptide mass values were ensured to be within 0.1 Da (typically less than 0.05 Da) when manually reviewing MASCOT search results.
Statistical Analysis
Bulls were divided in 4 groups based on fertility scores (PD values): group
I (n = 6): -18.1 
PD -6.2; group II (n = 13): -5.9 PD -0.8;
group III (n = 12): 0.0 PD 2.6; group IV (n = 6): 2.9 PD
7.7. Differences in protein expression among these groups were evaluated by
Duncan statistical test (SAS,
2003). Protein quantities (estimated by PDQuest) that
significantly differed among bulls were used as independent variables in
regression models (SAS, 2003)
to predict the percentage PD of bull NNR.
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Results |
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0 (168
comparisons; average r = .84), 18 bulls with PD < 0 (190
comparisons; average r = .86) and pairs of high and low fertility
sires (342 comparisons; average r = .85). Correlations of matched
spots in pairs of AGF 2-dimensional maps also had similar patterns using bulls
from groups I (-18.1 PD -6.2), II (-5.9 PD -0.8), III (0.0
PD 2.6), and IV (2.9 PD 7.7).
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The percentage PD of the average NRR of sires was significantly associated with the amount of 4 proteins identified in the 2-dimensional maps of accessory sex gland fluid. The average intensity of two 14-kDa spermadhesins (spots 2202 and 2201; Figure 2) was higher in bulls of low fertility (Figure 4). Sires with fertility scores between -18.1 and -6.2 had 2.2 times more spermadhesin than did bulls with fertility scores from 2.9 to 7.7 (P < .05). Both spermadhesin isoforms (spots 2202 and 2201) showed practically the same type of association with fertility. The spots excised from the seminal plasma gels (spots 1, 2, and 3; Figure 5) also matched to spermadhesin Z13 and had similar pI values as the ones present in the AGF. The most basic isoform of AGF (spot 1201; Figure 2) is equivalent to the one originally found as an antifertility factor in the seminal plasma (spot 1; Figure 5). Information about protein identification by MS/MS is presented in Table 1.
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Bulls with the highest fertility scores (2.9 PD 7.7) had 2.3
times (P < .05) more of a 55-kDa osteopontin (spot 9802;
Figure 2) than bulls with
above-average fertility (0.0 PD 2.6) and at least 4 times
(P < .05) more than bulls with below average (-5.9 PD
-0.8) or with the lowest fertility indexes of all (-18.1 PD -6.2;
Figure 4). Intensity of two
58-kDa spots identified as phospholipase A2 (spots 3801 and 4801;
Figure 2) also showed
variations among groups of bulls with different fertility
(Figure 4), although changes
were less pronounced than those observed with spermadhesin and osteopontin.
Phospholipase A2 (PLA2) expression was similar in bulls
with the highest (2.9 PD 7.7) and above-average fertility (0 PD
2.6) and significantly different (P < .05) only when compared
with bulls with the lowest scores (-18.1 PD -6.2;
Figure 4). These 2 spots were
related to fertility in a similar manner and were part of a series of 4
PLA2 isoforms identified by CapLC-MS/MS
(Figure 2;
Table 1). Some of the spots
identified as BSP 30 kDa had a tendency to show either a negative or positive
association with fertility, but none of these associations was significant.
However, the average intensity of 5 BSP 30 kDa isoforms (spots
7303–8403; Figure 1) had
a quadratic association with fertility indexes (R2 = .18;
P = .03), as shown in the plot of
Figure 6.
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Given the variations of those 4 AGF proteins among bulls of known fertility, regression models were constructed using the intensity of their respective spots as independent variables. An equation that included spermadhesin isoforms, osteopontin, and BSP 30 kDa isoforms explained a significant proportion (R2 = .56; Table 2) of the variation in fertility scores. Bull fertility index was also related to the amount of 2 spermadhesins, BSP 30 kDa and PLA2 isoforms (R2 = .53, Table 2). A regression equation that included spermadhesin (average of 2 isoforms) as the single independent variable gave an R2 of .33, and models with spermadhesin and osteopontin only or spermadhesin and BSP 30 kDa only gave R2 values of .46 and .47, respectively.
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Discussion |
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Only 40.4% of the spots detected in the AGF maps were found in all samples. Despite the degree of variation in the number of spots among gels, we were unable to identify any protein that was expressed exclusively in either high-fertility or low-fertility bulls, even when we compared sires with the highest fertility (PD values from +2.9 to +7.7) with those with the lowest scores (PD values from -6.2 to -18.1). High-fertility bulls were neither less nor more homogeneous than low-fertility bulls based on correlations of all matched spots between pairs of AGF gels.
Bulls used in this study were reproductively normal, with semen parameters that were uniformly satisfactory for the AI industry. Although the sires studied were not selected for specific reproductive traits, they represent a population of bulls that possess acceptable fertility and good semen qualities and freezing characteristics as young sires. Dairy bulls not meeting these criteria are culled early in reproductive life. Thus, differences in fertility scores among proven dairy sires do not represent the full range of fertilities seen in an unselected population and could not be related to a large number of peptides expressed in the AGF. Consequently, proven dairy sires may not exhibit fertility-associated peptides that are expressed in the fluids from the accessory sex glands of males with extremely low fertility.
The expression of 4 AGF proteins had distinct patterns among groups of sires with different fertility, and empirical regression models were useful in explaining the significance of those proteins for prediction of fertility. In one model, we obtained an R2 of .56 based on the amount of 2 spermadhesins, osteopontin and isoforms of BSP 30 kD, and another regression model was obtained with a similar R2 (.53) when the intensity of spots identified as PLA2 were used as independent variables, along with that of the spermadhesins and BSP 30 kDa. Spermadhesin Z13 was the single factor that accounted for the greatest proportion of the variation in bull fertility (R2 = .33). A combination of this peptide with osteopontin or BSP 30 kDa gave almost identical R2 values (.46 and .47), suggesting that the contribution of PLA2 for explanation of fertility measured in vivo was small, although significant.
The intensity of spermadhesin Z13 in AGF showed an inverse relationship with fertility. Consistent with these observations, the low–molecular-weight antifertility peptide reported by Killian et al (1993) in the seminal plasma of another group of Holstein bulls was also identified as spermadhesin Z13. The isoform originally described in the seminal plasma by those authors appears to be more basic (pI 6.7) than the ones we found in the AGF as antifertility factors (pI 6.5 and 6.3). Aspects of the methodology used for identification and quantification of spot intensity could have accounted for those subtle differences. Also, alterations may occur when accessory sex gland proteins are mixed with other components of the seminal plasma. According to Tedeschi et al (2000), spermadhesin Z13 appears as two 13-kDa monomers in 2-dimensional gels of bovine seminal plasma, which are believed to originate from a 26-kDa dimer. Similarly, we identified a spermadhesin Z13 spot in the AGF gels at 29 kDa.
Spermadhesin Z13 is a peptide that displays 50% and 43% homology with the acidic seminal fluid protein and seminal plasma motility inhibitor (SPMI), respectively (Tedeschi et al, 2000). The former has positive effects on bovine sperm in vitro when at average concentrations, but it can inhibit both sperm motility and mitochondrial activity when at high levels (Schoneck et al, 1996). In humans and boars, SPMI decreases sperm movement by interfering with dynein ATPase (Iwamoto et al, 1995; Robert and Gagnon, 1996). Other types of spermadhesins isolated from boar seminal plasma, such as AQN-1, AQN-3, AWN, PSP-I, and II, also influence sperm motility (Centurion et al, 2003; Caballero et al, 2004) and its oocyte-penetrating capacity (Caballero et al, 2004), suggesting the existence of a complex mechanism played by those type of proteins in the male. Regarding the reason why spermadhesin Z13 related to low fertility in the bull, clues can be obtained from the studies conducted with human and porcine peptides that share some degree of amino acid homology. However, detailed experimental data have yet to describe the functional attributes of spermadhesin Z13 expressed in the bovine accessory sex glands.
The 55-kDa protein in AGF identified as osteopontin (OPN) was positively related to fertility, confirming earlier studies showing that OPN was more prevalent in the seminal plasma of higher fertility bulls (Killian et al, 1993; Cancel et al, 1997). While spermadhesin Z13 had a more linear (and inverse) distribution among groups of bulls with different fertility, OPN appeared as the most typical protein of bulls with the highest scores. In the present study, fertility data about Holstein sires were obtained when intrauterine inseminations (IUI) were performed using the usual number of sperm designed to give maximum fertility. This type of approach is obviously routine for the AI industry and makes perfect sense for most commercial uses of IUI. It is possible, however, that additional experiments designed to use only a limited number of sperm from bulls with similar characteristics, for instance 50% of the conventional dose, could reveal more detailed associations between AGF proteins and fertility. Effects of fertility and antifertility factors described here could have more pronounced influence on bulls' reproductive performance, either positive or negative, when sperm numbers are limited. Such a hypothesis needs to be tested in the future and supported by functional studies about those proteins.
Osteopontin was originally described by Senger et al (1979) in bone tissues, although its expression is also found in endothelial cells, macrophages, mammary gland, certain tumor cells (Liaw et al, 1998; Mazalli et al, 2002; Denhardt, 2004; Wai and Kuo, 2004), follicles, corpus luteum, trophoblasts, uterine epithelium (Nomura et al, 1988; Johnson et al, 2003), and testes (Cancel et al, 1999). Evidence from these studies suggests that OPN is associated with cell adhesion, tissue remodeling, bone mineralization, immune cell stimulation and chemotaxis, cell survival, intracellular signaling, and cytoskeleton dynamics. We have recently determined (Killian, unpublished results) that incubation of bovine oocytes with oviductal follicular fluid and antibodies against OPN inhibited sperm-oocyte binding, fertilization, and embryo development, and, in a study using the OPN knockout mouse, fetal size was reduced between gestational days 10.5 and 19.5 (Weintraub et al, 2004). It seems reasonable, therefore, that OPN influences sperm-oocyte interaction and events during early embryo development and this would explain, at least partially, its association with fertility indexes of bulls.
The amount of BSP 30 kDa isoforms in AGF was linked to bull fertility, following a quadratic pattern. Bovine seminal proteins (BSPs) are known to bind to phospholipids on sperm shortly after emission, stimulating cholesterol release from sperm membrane (Thérien et al, 1998; Visconti and Kopf, 1998). In the female reproductive tract, BSP-bound sperm interacts with oviductal components and stimulates a second cholesterol efflux, resulting in capacitation (Benoff et al, 1993; Thérien et al, 1998). Thus, a positive effect of BSP 30 kDa on fertility could be linked to its ability to mediate these events, which are crucial for successful fertilization. However, based on our model, while lower amounts of BSP 30 kDa may facilitate fertilization, higher amounts of BSP 30 kDa became detrimental to fertility. This empirical conclusion is in agreement with studies showing that exposure of sperm to increasing concentrations of BSP causes damage to the sperm membrane resulting from an excess of lipid influx (Manjunath et al, 2002). Although low-density lipoproteins present in extenders, such as egg yolk and milk, protect stored sperm against the detrimental effects of BSP (Manjunath et al, 2002; Bergeron et al, 2004), we suggest that this protective action is probably not sufficient in the case of bulls with high concentrations of BSP in the accessory sex gland fluid and, consequently, in the seminal plasma. Moreover, interactions among proteins, not detected by our statistical models, may occur in the milieu of the accessory gland fluid. BSP proteins, including the BSP 30 kDa, have been shown to inhibit the activity of sperm PLA2 in a concentration-dependent manner (Manjunath et al, 1994). We found that a secreted form of PLA2 present in the AGF was more prevalent in bulls of high fertility. These mechanisms may explain why a quadratic effect was observed with the amount of BSP 30 kDa detected in the AGF gels.
The isoforms of PLA2 identified in the AGF were similar to the secreted form of PLA2 that have been purified from bovine seminal plasma (60-kDa; pI 5.6 ± 0.07; Soubeyrand et al, 1997). Another low–molecular-weight form of PLA2 exists in membrane extracts of the bull sperm (Ronkko et al, 1991). The PLA2 anchored to sperm membranes synthesizes arachidonic acid, which is converted to prostaglandin E2, leading to events related to acrosome reaction (Breitbart and Spungin, 1997). Sperm PLA2 is also implicated in sperm-egg fusion (Riffo and Párraga, 1997; Yuan et al, 2003) and secreted PLA2 stimulates cytokine release by immune cells (Granata et al, 2005) and exerts a potent antimicrobial action in the seminal plasma (Weinrauch et al, 1996; Bourgeon et al, 2004). In general support of an association between PLA2 and fertility, a recent study reports that the PLA2ß-gene knockout mouse has sperm with impaired motility and reduced capacity to fertilize oocytes both in vitro and in vivo (Bao et al, 2004).
In summary, we determined that specific proteins expressed in the accessory sex gland fluid accounted for a significant proportion of the variation in fertility indexes of dairy sires. We confirmed earlier findings that osteopontin is related to bull fertility and identified spermadhesin, BSP 30 kDa, and phospholipase A2 as new markers of male fertility. Although known functional attributes of these proteins provide some understanding of how they may influence male reproductive performance, it was beyond the scope of the present study to test experimentally how these proteins affect sperm function and fertilization. These objectives will be pursued in future investigations.
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Footnotes |
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Supported by a Fellowship awarded by the Brazilian Research Council
(CAPES). 
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