Open Veterinary Journal, (2026), Vol. 16(4): 2352-2359

Research Article

10.5455/OVJ.2026.v16.i4.35

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Molecular weight profile of sperm proteins and their association with Kinematic motility in different buck breeds

Fuad Hasan¹, Armyn Hakim Daulay¹, Pirda Parida Permadani Pertiwi², Muhammad Fajar Amrullah², Hikmayani Iskandar² and Tulus Maulana²

¹Department of Animal Science, Faculty of Agriculture, Universitas Sumatera Utara, Medan, Indonesia

²Research Center for Applied Zoology, National Research and Innovation Agency (BRIN), Bogor, Indonesia

*Corresponding Author: Fuad Hasan. Department of Animal Science, Faculty of Agriculture, Universitas Sumatera Utara, Medan, Indonesia. Email:harahap.fuadhasan [at] usu.ac.id

Submitted: 24/09/2025 Revised: 28/02/2026 Accepted: 16/03/2026 Published: 30/04/2026

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ABSTRACT

Background: Reproductive efficiency in bucks is a critical determinant of genetic improvement and livestock development programs, particularly in smallholder farming systems where bucks contribute substantially to household income and food security.

Aim: This study aimed to characterize the molecular weight profiles of sperm proteins and their association with kinematic motility parameters in frozen–thawed semen from Anglonubian, Ettawa Cross, Boer, and Saanen bucks.

Method: Frozen semen samples were collected from 16 bucks representing the 4 breeds. Sperm motility and kinematic parameters, including total motility, progressive motility, velocity parameters (VAP, velocity, VSL), linearity (LIN), straightness (STR), amplitude of lateral head displacement (ALH), and beat cross frequency, were analyzed using computer-assisted semen analysis. Sperm proteins were extracted, quantified, and separated using sodium dodecyl sulfate-polyacrylamide gel electrophoresis to determine their molecular weight profiles. ANOVA and Pearson correlation tests were used in this study.

Results: All breeds produced frozen-thawed semen with acceptable motility parameters for artificial insemination. Boer bucks exhibited significantly lower motility than Ettawa Cross and Saanen breeds (p < 0.05). Saanen bucks exhibited a significant decrease in sperm protein concentrations. SDS-PAGE analysis revealed 8–10 protein bands per breed, with prominent high-intensity bands at 15, 50, and 70 kDa. Correlation analysis demonstrated significant associations between ALH and total motility, progressive motility, STR, and LIN, whereas total sperm protein concentration was not correlated with any of the kinematic traits.

Conclusion: Variations in sperm protein molecular weight profiles and kinematic motility were evident among buck breeds, suggesting the presence of potential breed-specific markers. These findings provide a foundation for the identification of molecular determinants of fertility and support the development of selection strategies for superior sires in buck breeding programs.

Keywords: Buck semen, Kinematic motility, Molecular weight profile, Sperm protein.

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Introduction

Reproductive efficiency in bucks is a critical determinant of genetic improvement and livestock development programs, particularly in smallholder farming systems where bucks contribute substantially to household income and food security (Manirakiza et al., 2021; Van Tassel et al., 2023). Male fertility is largely assessed through semen quality, with sperm motility being recognized as a primary indicator of fertilization potential (Baharun et al., 2023). Although routinely applied, conventional semen evaluation techniques provide only limited information regarding the functional and dynamic properties of spermatozoa. Advances in computer-assisted semen analysis have enabled detailed kinematic assessments, including curvilinear velocity (VCL), straight-line velocity (VSL), linearity (LIN), and lateral head displacement (ALH) amplitude. These parameters offer a more precise characterization of sperm motility patterns and have been shown to enhance fertility outcomes’ predictive accuracy compared with traditional subjective evaluations (Aghazarian et al., 2021).

Intrinsic cellular factors play a central role in the regulation of sperm motility, with sperm protein composition increasingly recognized as a critical determinant of functional capacity (Chakraborty and Saha, 2022). Sperm proteins are essential for preserving plasma membrane integrity, regulating energy metabolism, and coordinating axonemal and flagellar motion, all of which underpin effective motility (Liang et al., 2022). Alterations in protein expression, structural conformation, or post-translational modifications can significantly influence sperm function and ultimately determine fertilization success (Samanta et al., 2016; Brohi and Ho, 2017). Profiling sperm proteins, particularly through molecular weight distribution analysis, provides an important approach for identifying candidate proteins associated with motility regulation and may reveal biomarkers predictive of male fertility (Pinto et al., 2019).

Previous studies have demonstrated associations between specific sperm proteins, including dynein, tubulin, and outer dense fiber proteins, and sperm motility characteristics in several mammalian species, including cattle, swine, and humans (Vilagran et al., 2016; Parab et al., 2017; Lestari et al., 2018; Zhao et al., 2018). Furthermore, differential proteomic analyses have shown that sperm protein expression variations are closely linked to semen quality and fertility outcomes (Karunakaran et al., 2012; Deori et al., 2016). Despite these advances, most investigations have emphasized the identification of individual candidate proteins rather than evaluating broader patterns of molecular weight distribution. In addition, limited research has addressed the direct relationship between sperm protein molecular weight profiles and detailed kinematic motility parameters, particularly across different buck breeds (Jia et al., 2021; Said et al., 2024).

Owing to the distinct genetic backgrounds, physiological adaptations, and reproductive traits of buck breeds (Blässe et al., 2012), interbreed variation in sperm protein composition is likely to contribute to differences in motility performance. Integrative studies combining molecular characterization of sperm proteins with detailed kinematic motility analyses across buck breeds remain limited. Therefore, this study aimed to characterize the molecular weight profiles of sperm protein and evaluate their association with kinematic motility parameters in frozen-thawed semen from Anglonubian, Ettawa Cross, Boer, and Saanen bucks.

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Materials and Methods

Semen collection

The frozen semen samples used in this study were collected from 16 bucks representing four breeds: Anglonubian, Ettawa Cross, Boer, and Saanen, which were maintained at the National Artificial Insemination Center, West Java, Indonesia. Semen was collected using an artificial vagina during mid-morning after an extended period of routine weekly collections. The semen qualities evaluated before cryopreservation included ejaculate volume, sperm concentration, motility, and morphological abnormality. Only ejaculates that met the minimum criteria established in the Indonesian National Standard for frozen semen, ≥70% total motility, and ≥80% morphologically normal sperm, as specified in SNI 4869-3:2023 (BSN, 2023), were included in this study.

Progressive motility

Sperm kinematics were objectively assessed using a computer-assisted sperm analysis system. The microscope (Axioo-Scope A1, Carl Zeiss, Germany) was set to 200 × phase contrast magnification and connected to the SpermVision^TM 3.7.8 software (Minitube, Germany). An aliquot (5 μl) of semen was deposited on a warmed microscope slide at 37°C and covered with a coverslip (18 × 18 mm). Sperm images in 8 fields were digitized for kinematic pattern analysis using the SpermVision software. The mean values for each of the following parameters were calculated based on approximately 1,000 spermatozoa (Maulana et al., 2024).

Sperm protein extraction and molecular weight profiling by sodium dodecyl sulfate-polyacrylamide gel electrophoresis

Sperm protein extraction and molecular weight profiling were performed following the protocol of Iskandar et al. (2022), with minor modifications. Each frozen semen straw (~0.25 ml) was thawed and washed with 1 ml of phosphate-buffered saline (PBS, pH 7.4) at 4°C and centrifuged at 6,500 rpm for 10 minutes to separate spermatozoa from the extender. The frozen semen was processed using the AndroMed® commercial extender (Minitüb GmbH, Germany). The resulting sperm pellets were extracted using PRO-PREP™ Protein Extraction Solution (iNtRON Biotechnology, Korea) according to the manufacturer’s instructions. Protein concentrations were determined using the bicinchoninic acid protein assay (Thermo Scientific™, USA). Handling was minimized, and repeated centrifugation was avoided to prevent sperm protein degradation and maintain integrity.

SDS-PAGE was performed to resolve sperm proteins according to their molecular weight. One-dimensional electrophoresis was conducted using SurePAGE™ Bis-Tris gels (10 cm × 8 cm, 12 wells, 4%–20% gradient; M00656, GenScript, Hong Kong) with a Broad Multi Color Pre-Stained Protein Standard (M00624, GenScript) covering a molecular weight range of ~6.5–240 kDa. Tris-MOPS-SDS running buffer (M00138, GenScript) was used for electrophoresis at 200 V and 100 mA for 40 minutes. Protein bands were visualized by Coomassie Brilliant Blue R-250 staining (Bio-Rad, USA).

Statistical analysis

Data analysis was performed using Statistical Minitab version 18.1 (Minitab for Windows, Minitab, Inc. USA). Due to the normal distribution and different homogeneity of the data, the one-factor variance analysis (ANOVA) test was used to continue the process. The Fisher’s test was then performed to analyze whether there were differences between the variables examined in the study. The correlation between frozen semen characteristics and sperm protein was analyzed using Pearson’s correlation coefficient and Graphad Prism v.9.41 (Graphpad Software). USA). All study data were presented in the form of Mean ± SD.

Ethical approval

The frozen semen used in this study was from the Lembang AI Center. Starting from the management of bucks, every procedure (i.e., the collection of fresh semen and its freezing until ready to be marketed) was in accordance with Indonesia’s operational standards, namely, SNI ISO 9001: 2015 No. 824 100 16072, and was supervised by a veterinarian. Each stage of this study considered every aspect of animal welfare and met the requirements for ethical clearance by the Animal Care and Uses Committee.

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Results

Frozen-thawed sperm kinematics and sperm protein concentration

Frozen-thawed semen from all buck breeds exhibited quality parameters within the acceptable range for artificial insemination. Sperm motility analysis revealed that Boer bucks had significantly lower motility (p < 0.05) than Ettawa Cross and Saanen bucks. No significant interbreed differences were observed in the velocity parameters (VAP, VCL, and VSL). The ALH was significantly higher in Boer than in Anglonubian and Ettawa Cross (PE) bucks (p < 0.05). Conversely, beat cross frequency (BCF) was significantly higher in Saanen than in Anglonubian and Ettawa Cross (p < 0.05) (Table 1).

Table 1. Bucks sperm kinematics motility.

Protein concentration analysis showed that Saanen bucks had the lowest sperm protein concentration (59.82 ± 15.7 µg/ml), which was significantly lower (p < 0.05) than that of Anglonubian (94.88 ± 3.86 µg/ml), Boer (100.93 ± 7.5 µg/ml), and Ettawa Cross (107.06 ± 18.04 µg/ml) bucks (Table 2).

Table 2. Protein concentration

Correlation between sperm protein levels and sperm characteristics

SDS-PAGE revealed 8–10 distinct protein bands among the 4 analyzed buck breeds (Table 3). Several proteins were consistently detected across all breeds, including tubulin beta-5 chain isoform 1 (50 kDa), acrosomal protein SP-10 isoform 2 (28–30 kDa), ferritin heavy chain (20 kDa), calmodulin (16 kDa), spermadhesin-1 (15 kDa), HSPE1 (10–11 kDa), an uncharacterized protein of ~9.5 kDa, and protamine 1 (PRM1, 6.5 kDa), each present in 100% of samples. A protein band of ~70 kDa was identified in Anglonubian, Ettawa Cross, and Boer bucks, but it was absent in Saanen. AQP7 (35–36 kDa) was detected only in the Ettawa Cross and Boer samples, with an overall frequency of 50%. The total number of protein bands varied by breed, with Boer and Ettawa Cross exhibiting the highest expression (10 bands), followed by Anglonubian (9 bands) and Saanen (8 bands) (Fig. 1).

Fig. 1. Sperm protein profile of different bucks. kDa=kilodaltons; M=marker; Ang1=Anglonubian; PE1=Etawa Cross 2; BR1=Boer; SA1=Saanen.

Table 3. Electrophoretic profiles of sperm protein.

Correlation between sperm kinematics and protein levels

Pearson correlation analysis revealed strong positive associations between total and progressive motility (r=0.92), as well as between the velocity parameters VAP and VCL (r=0.95). ALH was significantly positively correlated with total motility (r=0.73), progressive motility (r=0.86), LIN (r=0.93), and STR (r=0.94), indicating a strong relationship with overall sperm movement patterns. In contrast, sperm protein concentration did not exhibit significant correlations with any of the kinematic parameters, suggesting that protein abundance alone may not directly influence motility traits (Fig. 2).

Fig. 2. Pearson correlation heatmap between sperm kinematics and protein concentrations.

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Discussion

This study demonstrated that frozen-thawed semen from different buck breeds retained motility parameters suitable for artificial insemination and fulfilled the Indonesian National Standard for post-thaw motility (SNI 4869–2:2021; ≥40%), despite the presence of inter-breed variability. Boer bucks exhibited reduced motility compared with Ettawa Cross and Saanen bucks, consistent with earlier findings that reported inferior semen quality in Boer bucks (Sitepu et al., 2018; Sharma and Sood, 2019). The motility values obtained in this study were higher than those previously reported for Sirohi bucks (Anand and Yadav, 2016), indicating that genetic factors, adaptability to environmental conditions, and reproductive management practices strongly influence semen cryosurvival. Breed-specific differences in freezing tolerance may also arise from variations in sperm plasma membrane lipid composition, antioxidant defense capacity, and ability to cope with cryo-induced osmotic stress, as demonstrated in cattle and buffalo (Ugur et al., 2020).

Sperm motility remains a central determinant of male fertility and is tightly linked to ATP availability, which is derived from glycolysis and mitochondrial oxidative phosphorylation (Lv et al., 2020; Jia et al., 2021). Inhibition of mitochondrial respiration has been shown to markedly reduce sperm motility (St. John et al., 2005), underscoring the critical role of metabolomic efficiency in maintaining sperm function. The observed interbreed variations in ALH and BCF reflect differences in mitochondrial performance, osmotic stress tolerance, and ion homeostasis, which together modulate flagellar activity (Blässe et al., 2012; Sun et al., 2023). Elevated ALH values are characteristic of hyperactivated motility, a specialized pattern essential for zona pellucida penetration and successful oocyte fertilization (Yanagimachi, 2011).

The significantly lower protein concentration observed in Saanen bucks may indicate reduced secretory activity of accessory sex glands or a diminished capacity of seminal proteins to bind the sperm membrane. Seminal plasma proteins are key regulators of semen quality, contributing to membrane stabilization, preventing premature capacitation, and protecting against oxidative damage during cryopreservation (Rodríguez-Martínez et al., 2011). Reduced protein concentrations may compromise these protective functions, thereby lowering post-thaw sperm quality. Previous studies in bulls and buffalo have demonstrated that seminal proteins, particularly BSP proteins, are closely associated with cryotolerance and fertility potential (Kasimanickam et al., 2019). Collectively, these findings suggest that both quantitative and qualitative variations in seminal protein composition across breeds may influence sperm motility and functionality, which are important indicators of potential fertility. However, direct artificial insemination trials are necessary to confirm breed-specific fertility outcomes.

Correlation analysis identified ALH as a particularly informative parameter, showing positive associations with total motility, LIN, and STR. This finding is consistent with the established role of ALH as a biomarker of capacitation and hyperactivation, processes that are essential for successful fertilization (Galián et al., 2023). In contrast, sperm protein concentration did not correlate with kinematic traits. This suggests that the functional impact of proteins is determined not only by their abundance but also by their structural properties, subcellular localization, and Post-Translational Modifications (Samanta et al., 2016; Brohi and Ho, 2017). These results emphasize the need for advanced proteomic approaches, such as LC-MS/MS, to identify fertility-associated proteins beyond bulk concentration measurements.

Molecular profiling by SDS-PAGE revealed consistent expression of protein bands at 15, 50, and 70 kDa across all breeds, suggesting conserved roles in sperm physiology. Proteins within these molecular weight ranges include PRM1, which mediates chromatin condensation; spermadhesin, which facilitates sperm–oocyte interactions; calmodulin, a regulator of calcium signaling; ferritin heavy chain, an antioxidant defense protein; and acrosomal protein SP-10, which contributes to fertilization. Low-molecular-weight proteins (~14–18 kDa) are particularly noteworthy because of their involvement in zona pellucida binding (Nawangwulan et al., 2020). In addition, heparin-binding proteins (28–31 kDa) act as fertility-associated antigens and have been validated as reliable fertility markers in cattle, even when conventional semen quality parameters are within normal ranges (Karunakaran et al., 2019; Sprott et al., 2000). Collectively, these findings strengthen the evidence that sperm protein molecular weight profiles may serve as valuable fertility biomarkers in bucks.

Breed-specific variations in sperm motility traits and protein expression patterns are biologically relevant and may serve as potential fertility molecular markers. Integrating kinematic motility assessment with proteomic profiling provides a robust framework for identifying fertility-associated biomarkers. Such biomarkers hold promise for precision-based sire selection, thereby improving buck breeding programs’ efficiency and strengthening reproductive management strategies (Karunakaran et al., 2019; Iskandar et al., 2022). These results also advance the understanding of the molecular mechanisms underlying sperm function in bucks and contribute to the broader field of reproductive biotechnology and livestock fertility enhancement.

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Conclusion

In conclusion, distinct variations in sperm protein molecular weight profiles and kinematic motility parameters were observed among buck breeds, indicating potential breed-specific fertility markers. These results highlight the value of integrating molecular profiling with kinematic analyses to uncover reproductive performance-associated biomarkers. Such biomarkers could serve as reliable tools for precision-based sire selection, thereby enhancing the efficiency of AI programs and contributing to the genetic improvement of buck populations. Beyond practical applications, the findings provide fundamental insights into the molecular determinants of sperm function and establish a foundation for future studies to validate fertility-associated proteins in caprine species.

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Acknowledgments

None.

Conflict of interest

The authors have no conflicts of interest to declare.

Funding

This study was supported by Lembaga Penelitian Universitas Sumatera Utara through Penelitian Terapan No : 263/UN5.2.3.1/PPM/KP-TALENTA/R/2023.

Authors' contributions

Conceptualization: FH, HI, and TM. Data curation: PPPP, MFA, AHD, FH, HI, and TM. Investigation: FH, HI, and TM Methodology: FH, HI, and TM. Resources: PPPP, MFA, AHD, FH, HI, and TM Supervision: FH, HI, and TM. Writing–original draft: FH, HI, and TM. All authors have read and approved the final version of the manuscript.

Data availability

All data were provided in the manuscript.

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