Abstract

   Sperm motility is a key factor influencing male fertility and is
   associated with metabolic and lipid profiles across species. The aim of
   this study was to investigate the relationship between sperm motility
   and the seminal plasma lipid profile in Simmental bulls, and to
   identify key lipids potentially influencing sperm motility. Semen
   samples were collected from 26 healthy Simmental bulls with an average
   age of 4.9 years. Sperm quality was evaluated using computer-assisted
   sperm analysis (CASA). Based on motility, the samples were divided into
   two groups: high sperm motility (HSM > 65%) and low sperm motility (LSM
   < 65%). Compared to the LSM group, the HSM group exhibited
   significantly higher sperm viability, motility, straight-line velocity,
   beat-cross frequency, and sperm acrosome integrity, while the sperm
   malformation rate was lower (p < 0.05). Lipid profiles were determined
   using LC-MS/MS, and 40 differential lipids were identified by
   multivariate statistical analysis. Among them, 39 lipids were
   upregulated in the LSM group compared to the HSM group. They were
   primarily triglycerides and carnitines, mainly involved in four
   metabolic pathways related to glycerophospholipid and linoleic acid
   metabolism. Notably, PC (16:0/20:4; 14:0/18:3), LPC (22:4/0:0;
   22:6/0:0), and PE (14:0/18:1; 18:1/20:3) were diagnosed with great
   accuracy (AUC > 0.7), which means they may serve as potential
   biomarkers for sperm motility.

1. Introduction

   Sperm motility directly impacts fertility rates and embryo quality and
   is influenced by several environmental and genetic factors
   [[38]1,[39]2]. Research has confirmed a close relationship between
   seminal plasma and the regulation of sperm motility. Seminal plasma is
   mainly composed of proteins, nucleosides, lipids, vitamins, amino
   acids, and steroid hormones [[40]3]. Several studies have reported the
   effects of these components on sperm quality across various species.
   For example, in bulls, Therien et al. identified a specific correlation
   between apolipoprotein A-1 in seminal plasma and the regulation of
   sperm capacitation [[41]4]. Hansen et al. reported a negative
   relationship between seminal plasma clusterin levels and the number of
   normal sperm in beef cattle [[42]5]. In humans, Gilany et al. and Zhao
   et al. found metabolomic alterations in the Krebs cycle and energy
   metabolism pathways in the seminal plasma of patients with
   asthma-oligozoospermia [[43]6,[44]7]. In goats, Jia et al. demonstrated
   that 445 seminal plasma-derived proteins were significantly differed
   between high and low sperm motility groups [[45]1]. Additionally,
   potential fertility biomarkers in seminal plasma have been identified,
   such as oleic acid and palmitic acid in humans [[46]3], taurine,
   leucine, and isoleucine in bulls [[47]8], and ethanolamine in stallions
   [[48]9]. These findings highlight the complexity of the relationship
   between seminal plasma components and sperm motility, underscoring the
   need for further exploration in this area.

   Lipids are major components of sperm membranes and are involved in
   sperm motility, energy metabolism, membrane function, and fertilization
   [[49]10,[50]11]. Around 24% of the sperm proteome in both humans
   [[51]12] and horses [[52]13] is devoted to lipid metabolism. Several
   studies have explored the effects of lipids in seminal plasma on sperm
   quality. For example, Kathein et al. found that
   lysophosphatidylcholines, phosphatidylcholines, and sphingomyelins in
   the seminal plasma of healthy donors are involved in regulating sperm
   motility [[53]14]. Argov-Argaman et al. observed that impairments in
   the lipid composition of sperm tails during summer could result in
   reduced motility and velocity [[54]15]. Cheng et al. identified 12
   significant lipids, such as Lysophosphatidylserine (LPS) (20:4) and
   Lysophosphatidic Acid (LPA) (20:5), which influence the sperm acrosome
   response in humans [[55]16]. Lu et al. proposed a link between the
   defective motility of sperm and lipoprotein alterations [[56]17]. These
   findings underscore the critical role of lipid metabolism in seminal
   plasma for maintaining optimal sperm motility.

   Simmental cattle, renowned for their dual-purpose traits in milk and
   meat production, are characterized by their rapid growth potential,
   high meat quality, and adaptability to various environments. Over the
   past two decades, they have been widely used in crossbreeding with
   Chinese native beef breeds to improve production efficiency [[57]18].
   However, the effect of seminal plasma lipids on sperm motility and
   their associated mechanisms in Simmental bulls remain unclear.

   The objective of this study was to explore the relationship between
   sperm motility and the seminal plasma lipid profile in Simmental bulls,
   and to identify key lipids that potentially influence sperm motility.

2. Materials and Methods

2.1. Animals and Sample Collection

   Healthy Simmental bulls (n = 26) with an average age of 4.9 ± 0.8 years
   were enrolled from a livestock breeding center in Gansu province
   (Wuwei, China). Semen samples were collected using the artificial
   vagina method [[58]19] and were immediately transported to the
   laboratory for semen quality analysis within 10 min.

2.2. Evaluation of Sperm Quality Parameters

   The volume of semen was recorded, and sperm motility, concentration,
   and viability were evaluated using computer-assisted sperm analysis
   (CASA) (MDO605, ML-300; Mailang, Foshan, China) following a previously
   described method [[59]20]. CASA slides were loaded with 10 μL of each
   sperm sample, and a minimum of 200 sperm per sample was analyzed to
   determine overall motility, as recommended by the CASA software
   (MDO605, ML-300; Mailang, Foshan, China). Subsequently, the samples
   were grouped based on their motility into the high sperm motility group
   (HSM, >65%, N = 14) and the low sperm motility group (LSM, <65%, N =
   12). Further parameters were evaluated using CASA, including
   straight-line velocity (VSL), curvilinear velocity (VCL), averaged path
   velocity (VAP), amplitude of lateral head displacement (ALH),
   beat-cross frequency (BCF), straightness (STR), wobble coefficient
   (WOB), and malformation rate. Acrosome integrity was evaluated using
   the fluorescein isothiocyanate-conjugated peanut agglutinin (FITC-PNA)
   staining method, following the protocol of Sperm Morphology FITC-PNA
   staining kit (cat. no. [60]GMS14015.1.1; Genmed Scientifics, Shanghai,
   China), consistent with the detailed methods described by previous
   studies [[61]21,[62]22].

2.3. Collecting and Pretreating Seminal Plasma Samples

   All semen samples were centrifuged at 3000× g for 10 min at 4 °C, and
   the supernatant was collected and stored at −80 °C. When ready for use,
   the seminal plasma samples were thawed at 4 °C. Each sample was
   vortexed for 10 s and then centrifuged at 16,000× g for 5 min at 4 °C.
   Fifty microliters of each seminal plasma sample were placed into a
   centrifuge tube containing 1 mL of a methanol methyl tert-butyl ether
   (MTBE) mixed solution. An internal standard, dimethyl sulfoxide, was
   added to the MTBE extract solution. After vortexing for 2 min and
   ultrasonication for 5 min, 500 µL of water was added to the mixture.
   The samples were stirred for 1 min and centrifuged at 16,000× g for 10
   min at 4 °C. The supernatant (500 µL) was transferred to a centrifuge
   tube and dried under a stream of nitrogen. The resultant powder was
   dissolved in 100 µL of mobile phase B [acetoni-trile/isopropanol (10:90
   v:v), 0.04% acetic acid, and 5 mmol/L ammonium formate] prior to being
   stored at −80 °C. Before liquid chromatography–electrospray ionization
   ion trap mass spectrometry (LC-ESI-MS/MS) analysis, quality control
   samples were created by mixing an equal quantity of the supernatant to
   assess system stability.

2.4. LC-ESI-MS/MS Analysis

   The data acquisition instrument system consisted of ultra-performance
   liquid chromatography (UPLC; Shim-pack UFLC SHIMADZU CBM30A, Japan,
   [63]https://www.shimadzu.com/, accessed on 20 September 2023) and
   tandem mass spectrometry (MS/MS; QTRAP^® 6500+ System, Sciex, Fremont,
   California, USA, [64]https://sciex.com, accessed on 20 September 2023).
   The liquid phase analysis conditions were as follows: a Thermo C30 UPLC
   column (Thermo Scientific, Waltham, USA, 2.6 μm, 2.1 mm × 100 mm) was
   used. Solvent system A consisted of acetonitrile/water (60:40 v/v) with
   0.04% acetic acid and 5 mmol/L ammonium formate, and solvent system B,
   which was acetonitrile/isopropanol (10:90 v/v) with 0.04% acetic acid
   and 5 mmol/L ammonium formate. The gradient program was as follows: A/B
   80:20 v/v at 0 min, 50:50 v/v at 3 min, 35:65 v/v at 5 min, 25:75 v/v
   at 9 min, 10:90 v/v at 15.5 min; flow rate, 0.35 mL/min; temperature,
   45 °C; and sample volume, 2 µL. Mass spectrometry conditions were as
   follows: the electrospray ionization (ESI) temperature was 550 °C, the
   mass spectrometry voltage was 5500 v, the curtain gas pressure was 35
   psi, and collision-activated dissociation was set to medium. Linear ion
   trap (LIT) and triple quadrupole (QQQ) scans were acquired on a triple
   quadrupole–linear ion trap mass spectrometer (QTRAP; QTRAP^® 6500+
   LC-MS/MS, SCIEX, MA, USA) equipped with an ESI interface. The system
   was controlled by Analyst^® software (Sciex, Framingham, MA, USA,
   version 1.6.3) operating in Turbo Ion Spray mode.

2.5. The Lipidomic Data Quality Control

   The qualitative and quantitative analyses of lipids in the seminal
   plasma were conducted using Analyst^® software (version 1.6.3). After
   obtaining data from the samples, the extracted ion peaks of all lipids
   were individually integrated and corrected. The distinctive ions and
   signal intensities of each lipid were identified. The mass spectra of
   the samples were processed and corrected using MultiQuant software
   (version 3.0.3) (AB SCIEX, Concord, ON, Canada). The peak area was used
   to represent the relative abundance of each substance.

2.6. Statistical Analysis

   The sperm quality parameters were analyzed using IBM SPSS Statistics
   18.0 (IBM Corp., Armonk, NY, USA) and GraphPad Prism software (v6.0;
   GraphPad Software Inc., La Jolla, CA, USA). The fluorescence
   intensities of sperm acrosome integrity images were determined by using
   Image J software (version 1.8.0, National Institutes of Health,
   Bethesda, MD, USA), and the proportion of sperm with intact acrosome to
   the total sperm of individual image was calculated by Excel (version
   2019, Microsoft, Redmond, WA, USA) and analyzed with an unpaired t-test
   through IBM SPSS Statistics 18.0 (IBM Corp., Armonk, NY, USA). All data
   are presented as the mean ± standard error of the mean (SEM), and a
   value of p < 0.05 was considered statistically significant.

   Multivariate statistical analysis was conducted using the SIMCA-P
   program (V 14.0, Umetrics, Umea, Sweden), mainly including principal
   component analysis (PCA) and orthogonal correction partial least
   squares discriminant analysis (OPLS-DA). OPLS-DA models were verified
   based on the interpretation of the variation in Y (R^2Y) and forecast
   ability based on the model (Q^2). Cross-validation and permutation
   tests with 200 iterations showed the stability and reliability of the
   model at the condition of R^2Y > 0.4 and Q^2 > 0.4. Variable importance
   in a projection (VIP) value > 1 and the fold change (FC ≥ 2 or FC ≤
   0.5) in OPLS-DA, and p ≤ 0.05, respectively) were used as screening
   criteria. Significant differential lipids between the HSM and LSM
   groups were screened and used for metabolic pathway enrichment
   analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway
   analysis was performed using MetaboAnalyst 6.0
   ([65]http://www.metaboanalyst.ca, accessed on 20 September 2024)
   software. A receiver operating characteristics curve (ROC) analysis was
   performed by Origin 8.0 software (OriginPro 2021; OriginLab
   Corporation, Northampton, MA, USA).

3. Results

3.1. Sperm Functional Analysis in High and Low Sperm Motility Samples

   The semen quality parameters are shown in [66]Table 1. A total of 14
   samples were categorized into the HSM, while 12 samples were classified
   into the LSM group. There were no significant differences in semen
   volume or concentration between the two groups (p > 0.05, [67]Table 1).
   The sperm motility and viability were higher in the HSM group (77.45% ±
   1.86% and 87.42% ± 1.67%, respectively) compared to the LSM group
   (51.33% ± 4.67% and 59.81% ± 5.49%) (p < 0.05, [68]Table 1).

Table 1.

   Quality parameters of HSM and LSM group.
                                           Groups
           Parameters                HSM             LSM       p-Value
       Sperm collection/mL       5.90 ± 1.47     6.78 ± 2.58    0.32
   Sperm concentration (×10^8)   1.06 ± 4.70     1.05 ± 3.99    0.31
       Sperm motility (%)      77.45 ± 1.86 ^A 51.33 ± 4.67 ^B  <0.01
       Sperm viability (%)     87.42 ± 1.67 ^A 59.81 ± 5.49 ^B  <0.01
   [69]Open in a new tab

   Note: Comparison of sperm quality parameters between the HSM and LSM
   groups. Data are expressed as mean ± SEM. The absence of letters in the
   same row indicates no significant difference between treatments (p >
   0.05); (A/B) in the same row indicate a significant difference (p <
   0.01).

   The comparison of sperm movement parameters between the HSM and LSM
   groups is presented in [70]Figure 1. The VSL and BCF were higher in the
   HSM group (48.12 ± 1.12, 0.71 ± 0.03, respectively) compared to the LSM
   group (35.06 ± 3.84 and 0.63 ± 0.01, respectively) (p < 0.05,
   [71]Figure 1c,f). There were no significant differences observed in
   VCL, VAP, ALH, STR, or WOB between the two groups (p > 0.05, [72]Figure
   1d,e,g–i).

Figure 1.

   [73]Figure 1
   [74]Open in a new tab

   Comparison of sperm movement parameters between HSM and LSM groups.
   Images of sperm tracks in the HSM (a) and LSM (b) group. Red squares
   represent non-motile sperm, while green tracks represent motile sperm.
   The VSL, VCL, VAP, BCF, ALH, STR, and WOB parameters for the HSM and
   LSM groups are shown in panels (c–i), respectively. Data are expressed
   as the mean ± SEM. * and ** indicate p < 0.05 and p < 0.01,
   respectively, while “ns” represents no significant difference (p >
   0.05).

3.2. Differences in Sperm Malformation and Acrosome Integrity Between HSM and
LSM Groups

   The comparison of sperm malformation rates and acrosome integrity
   between the HSM and LSM groups is shown in [75]Figure 2 and [76]Figure
   3. In the HSM group, the rate of sperm malformation was decreased
   compared to the LSM group (40.60% ± 3.92% vs. 20.05% ± 1.56%) (p <
   0.05, [77]Figure 2a,b). Conversely, acrosome integrity was increased in
   the HSM group compared to the LSM group (81.69% ± 1.72% vs. 62.64% ±
   1.96%) (p < 0.05, [78]Figure 3a,b).

Figure 2.

   [79]Figure 2
   [80]Open in a new tab

   Comparison of sperm malformation between HSM and LSM groups. (a)
   Representative images of sperm morphology in the HSM and LSM groups.
   The “0” in green indicates normal sperm, and the “+” in purple
   represents the sperm with head abnormalities. (b) Comparison of the
   sperm malformation rates of the HSM and LSM groups, presented as mean ±
   standard deviation. Statistical significance is indicated, with ** p <
   0.01.

Figure 3.

   [81]Figure 3
   [82]Open in a new tab

   Comparative analysis of sperm acrosome integrity between the HSM and
   LSM groups. (a) Green fluorescence in the acrosomal region of the sperm
   head indicates intact acrosomes. (b) Quantitative assessment of
   acrosome integrity between the HSM and LSM groups, presented as mean ±
   standard deviation. Statistical significance is denoted by ** p < 0.01.
   The DIC image depicts the overall sperm morphology in bright field, the
   FITC fluorescence image represents the acrosome integrity. The merged
   image combines DIC and FITC images, allowing for precise correlation
   between the fluorescence signal and sperm morphology.

3.3. Lipid Profile Analysis Between HSM and LSM Groups

   The retention time and response intensity of each peak were overlaid,
   and the total ion chromatogram (TIC) peak shape was intact. The
   separation between adjacent peaks was distinct, demonstrating that the
   method was both reliable and stable. The PCA results revealed that the
   samples from both groups were within the 95% confidence interval,
   indicating good repeatability of the experiment ([83]Figure 4a). The
   OPLS-DA analysis showed significant differences in lipid content
   between the HSM and LSM groups. The model parameters, R^2Y (0.962) and
   Q^2 (0.503), indicated that the model was reliable and stable
   ([84]Figure 4b). Additionally, the parameters for model fitness (R^2)
   and predictive ability (Q^2) confirmed the predictability of the
   OPLS-DA model ([85]Figure 4c).

Figure 4.

   [86]Figure 4
   [87]Open in a new tab

   Data quality control. (a) Principal component analysis score plot for
   HSM and LSM sperm motility group samples; PC1 denotes the first
   principal component. PC2 denotes the second principal component. (b)
   Orthogonal partial least squares discriminant analysis score plot for
   the HSM and LSM group samples; t[1] = the first principal component,
   and t[2] = the second orthogonal component. (c) Permutation test plots
   for the HSM and LSM group samples.

3.4. Differential Lipids Analysis Between HSM and LSM Groups

   Forty differential lipids were identified in the seminal plasma between
   the HSM and LSM groups ([88]Figure 5a). Triglyceride (TG),
   phosphatidylethanolamine (PE), phosphatidylcholine (PC),
   lysophosphatidylcholine (LPC), free fatty acid (FFA), carnitine (CAR),
   diglyceride (DG), and ceramides (CER) were all upregulated, while
   phosphatidylserine (PS) was downregulated in the LSM group compared to
   the HSM group ([89]Figure 5a). Clustering analysis revealed that lipids
   enriched in the HSM group were present in lower abundance in the LSM
   group ([90]Figure 5b). Further chemical classification of these
   differential lipids showed that the majority were TGs (47.5%) and CARs
   (15%), followed by PEs, PCs, LPCs, FFAs, DGs, and CERs ([91]Figure 5c).

Figure 5.

   [92]Figure 5
   [93]Open in a new tab

   Screening and chemical classification of the differential lipids. (a)
   The bar graph represents the mean fold change values of differential
   lipids between HSM and LSM groups. Red indicates upregulated lipids,
   and green represents downregulated lipids. (b) Clustering heat map of
   the differential lipids of HSM and LSM groups. (c) Chemical
   classification of the differential lipids.

3.5. Pathway Enrichment Analysis and ROC Analysis of the Differential Lipids

   To further identify key lipids associated with sperm motility,
   metabolic pathway enrichment analysis was performed using MetaboAnalyst
   6.0. Four primary metabolic pathways were significantly enriched
   between the HSM and LSM groups (p < 0.05, [94]Figure 6a). These
   pathways included glycerophospholipid metabolism,
   glycosylphosphatidylinositol (GPI)—anchor biosynthesis, linoleic acid
   metabolism, and α-Linolenic acid metabolism. Six key differential
   lipids were involved in these pathways, including PC (16:0/20:4), PC
   (14:0/18:3), LPC (22:4/0:0), LPC (22:6/0:0), PE (14:0/18:1), and PE
   (18:1/20:3) ([95]Figure 6b). Subsequently, receiver operating
   characteristic (ROC) analysis demonstrated that these six key lipids
   exhibited high diagnostic accuracy (AUC > 0.7, [96]Figure 6c) and may
   serve as potential biomarkers for sperm motility.

Figure 6.

   [97]Figure 6
   [98]Open in a new tab

   Pathway enrichment analysis and ROC analysis of the differential
   lipids. (a) Metabolic pathway analysis. The y-axis represents −log10
   (P), and the x-axis represents the pathway impact score. The pathway
   impact scores are shown in circles, with darker rings indicating
   metabolite alterations in the relevant pathway. The dot plot
   illustrates the pathway impact score and the total number of
   metabolites in each enriched pathway (false discovery rate-adjusted p <
   0.05). (b) Sankey plot showing key lipids involved in significantly
   enriched pathways. (c) ROCs for 6 key lipids. The AUC (area under ROC)
   is a standard metric used to evaluate the performance of a
   classification model. An AUC > 0.7 indicates strong predictive
   performance.

4. Discussion

   Sperm motility, viability, and velocity are critical parameters used to
   evaluate the potential fertility of sperm [[99]23,[100]24,[101]25]. The
   VSL, VCL, VAP, and STR can assess sperm progression, while ALH and BCF
   are indicators of sperm viability [[102]26]. In this study, the VSL and
   BCF values were higher in the HSM group compared to the LSM group. A
   higher VSL provides a competitive advantage in sperm competition
   [[103]27]. Sloter et al. found that VSL values significantly decrease
   in 55-year-old men compared to those in 25-year-old men (50.5 vs. 45.4
   μm/s) [[104]28]. Additionally, VSL values are higher in fresh sperm
   compared to uncapacitated sperm [[105]29]. Therefore, the higher VSL
   values observed in the HSM group indicate enhanced sperm movement
   capability. The BCF value indicates the frequency of sperms crossing
   their average movement trajectory, and a high BCF value is a good
   indicator of sperm movement ability [[106]30,[107]31]. Adequate BCF is
   necessary for sperm to move through the oviduct mucus and other
   barriers during fertilization [[108]32]. The reduced BCF observed in
   the LSM group suggests a lower frequency of sperm movement along their
   trajectory path. Morphological abnormalities in spermatozoa are
   associated with reduced fertility [[109]33,[110]34]. Several studies
   have revealed a positive correlation between sperm viability and the
   percentage of live sperm with intact acrosomes [[111]35,[112]36]. In
   this study, the LSM group exhibited a higher percentage of sperm
   malformation and lower acrosome integrity compared to the HSM group.
   Therefore, high-motility sperm have higher VSL, BCF, and acrosome
   integrity, as well as a lower sperm malformation rate than low-motility
   sperm.

   There were significant differences in lipid species abundance between
   HSM and LSM groups, particularly in the levels of seminal plasma
   triglycerides (TGs) and carnitines (CARs), based on the chemical
   category classification in this study. TGs serve as metabolic energy
   sources for sperm and act as substrates for producing glycerol in
   mature boar sperm [[113]37]. Similarly, TGs are an energy source for
   the spermatozoa of sea urchin species [[114]38]. However, excessive TG
   levels may be harmful to sperm. For example, Diaz-Fontdevila et al.
   found that hypertriglyceridemia decreases the acrosome reaction in
   rabbit sperm [[115]39]. Mendoza et al. observed that the TG levels in
   men with abnormal spermatozoa were higher than those in healthy men
   [[116]40]. Furthermore, studies by Ergun et al. and Furse et al.
   reported a negative correlation between TG levels and sperm motility
   [[117]41,[118]42]. In this study, the LSM group exhibited higher TG
   concentrations in seminal plasma compared to the HSM group, consistent
   with previous findings. The excessive accumulation of TGs that cannot
   be utilized in time may lead to lipotoxicity, impairing sperm function
   [[119]42]. Therefore, elevated TG levels in seminal plasma may
   negatively impact sperm motility.

   CARs are essential carriers for sperm motility and capacitation,
   providing readily available energy for spermatozoa [[120]43]. This
   beneficial effect is mediated by the transport of long-chain fatty
   acids toward or across the inner mitochondrial membrane, facilitating
   β-oxidation [[121]44]. Supplementation with L-carnitine (LC) during the
   liquid storage of boar semen has shown no significant beneficial
   effects on the maintenance of sperm motility [[122]45]. Moreover, LC
   has been reported to inhibit sperm progressive motility in bovine and
   rooster sperm by reducing oxygen consumption in spermatozoa
   [[123]46,[124]47]. The epididymal tissue contains high levels of LC and
   acetyl-carnitine (ALC) [[125]48], and evidence has demonstrated a
   positive correlation between the ALC/LC ratio and sperm motility
   [[126]43]. Bartellini et al. found that samples characterized by
   asthenozoospermia exhibited higher LC and ALC levels but a
   significantly reduced ALC/LC ratio [[127]49]. In this study, compared
   to the HSM group, the concentrations of ALC and LC were elevated, while
   the ALC/LC ratio was reduced in the LSM group ([128]Figure 7). This
   finding aligns with previous studies [[129]49]. The reduction in the
   ALC/LC ratio could be explained by an impairment of the enzymatic
   system (carnitine transferase) that controls the reaction between LC
   and ALC, leading to defective spermatozoa motility [[130]43].
   Consequently, a decreased ALC/LC ratio in seminal plasma negatively
   impacts sperm motility.

Figure 7.

   [131]Figure 7
   [132]Open in a new tab

   The levels of ALC (a) and LC (b), and ALC: LC ratio (c) between HSM and
   LSM groups.

   Lipids that showed significant changes in glycerophospholipid
   metabolism included PC, LPC, and PE. LPC has been found to impact the
   acrosome reaction in spermatozoa by damaging the sperm membrane
   [[133]50]. Additionally, the level of LPC in seminal plasma has been
   shown to have a negative correlation with sperm motility [[134]51].
   Similarly, LPC (22:6) has been identified as a reliable marker of
   spermatozoa lipid oxidation [[135]52]. LPC is an inverted cone-shaped
   phospholipid that can form both curved bilayers and non-bilayers,
   potentially leading to unstable membrane domains [[136]53]. These
   findings indicated that elevated LPC levels in seminal plasma impair
   sperm motility by disrupting membrane structure.

   In addition, PCs and PEs are the most abundant phospholipids in
   mammalian cell membranes and participate in regulating oxidative stress
   by serving as methyl group donors [[137]54]. PCs are converted into PSs
   under the catalysis of phosphatidylserine synthase and subsequently
   converted into PEs by phosphatidylserine decarboxylase [[138]55]. The
   increased levels of PCs in chicken sperm have been reported to be
   negatively associated with fertility during aging [[139]56]. A study
   revealed that lower levels of PEs may contribute to the stabilization
   of the bilayer structure in cellular and acrosomal membranes [[140]51].
   In this study, the levels of PE (18:1/20:3), PE (14:0/18:1), PC
   (16:0/20:4), and PC (14:0/18:3) were increased in the LSM group
   compared to the HSM group. Consequently, we established a negative
   correlation between sperm motility and elevated levels of LPCs, PCs,
   and PEs in the seminal plasma.

5. Conclusions

   This study demonstrated that high-motility sperm has higher VSL, BCF,
   and acrosome integrity, as well as a lower sperm malformation rate,
   compared to low-motility sperm. The elevation of 39 differential lipids
   in seminal plasma, primarily enriched in glycerophospholipid and
   linoleic acid metabolism, was associated with a negative impact on
   sperm motility. Specifically, PC (16:0/20:4), PC (14:0/18:3), LPC
   (22:4/0:0), LPC (22:6/0:0), PE (14:0/18:1), and PE (18:1/20:3) appeared
   to be applicable as biomarkers of sperm motility. This study
   established correlations between sperm motility in bulls and lipid
   metabolism in seminal plasma, providing a reference for the evaluation
   of fertility in Simmental bulls.

Acknowledgments