Abstract
Sperm capacitation is essential for fertilization and is characterized by a cascade of biochemical signaling and membrane remodeling events. This process is highly dependent on membrane composition. Profiling lipid alterations provides a critical window into the molecular underpinnings of capacitation and the regulatory influence of zinc ions (Zn2+). Metabolomic studies in boar sperm have shown that capacitation coincides with broad shifts in metabolite abundance and that extracellular zinc attenuates or redirects many of these changes, highlighting its role as a key modulator. To extend this framework to the lipidome, we profiled boar sperm under three conditions: non-capacitated (0 h), capacitated in vitro (4 h), and capacitated with extracellular zinc (4 h + Zn), using liquid chromatography–mass spectrometry and image-based flow cytometry to validate capacitation status. Relative to 0 h, capacitation was associated with altered abundances of 30 lipids (P < 0.05) spanning several lipid categories: fatty acyls (n = 8), sterol lipids (n = 7), sphingolipids (n = 1), glycerolipids (n = 3), glycerophospholipids (n = 4), and unannotated lipids (n = 9). When exogenous Zn2+ was supplemented during in vitro capacitation, 12 of these shifts were maintained at 0 h-like levels (P < 0.05), suggesting an inhibiting or stabilizing role. In 2 of 16 hits, exogenously supplemented Zn2+ enhanced the capacitation-associated change (P < 0.05), whereas in the remaining 14 it exerted no measurable effect (P > 0.05). When exogenous Zn2+ was supplemented during in vitro capacitation, distinct lipid shifts were identified and organized using Tukey’s lipid-pattern classification based on significance (P < 0.05) and directionality, organizing them into four categories: Type-1 lipids (capacitation-associated), Type-2 lipids (zinc-inhibited), Type-3 lipids (zinc-specific response), and Type-4 lipids (zinc-enhanced). These categories describe distinct modes of lipid regulation, where some species remained unaffected by zinc (Type-1, n = 16), others were stabilized or inhibited from progressing toward capacitation-associated levels (Type-2, n = 12), a subset responded exclusively to zinc independent of capacitation (Type-3, n = 4), and a small group exhibited amplified capacitation-linked shifts under zinc supplementation (Type-4, n = 2). Together, these data reveal a class-specific, zinc-dependent architecture of lipid remodeling that integrates metabolic and membrane regulation within the broader capacitation cascade.
Keywords: boar semen, capacitation, image-based flow cytometry, lipidomics, spermatozoa, zinc
Graphical abstract
Graphical Abstract.
Graphical Abstract Lipid species responses to in vitro capacitation with and without exogenous zinc. (a) Schematic representation of the sperm lipidome under non-capacitated conditions (0 h). The red sperm depicts uncapacitated spermatozoa, with the associated lipidome labeled as the non-capacitated sperm lipidome. Colored lipid symbols represent lipid species that were subsequently classified in panel (b) and are shown by lipid class as follows: fatty acyls (FA; light blue), glycerophospholipids (GP; dark blue), sterol lipids (SL; green), glycerolipids (GL; orange), and unannotated lipids (UA; purple). Lipid class abbreviations are embedded within each symbol to ensure clear identification independent of color. The distribution of colored symbols is representative and does not indicate absolute abundance. (b) Lipid response pattern classifications summarizing the distribution of differentially abundant lipids by zinc-response type, defined using Tukey’s honestly significant difference post hoc comparisons across 0 h, 4 h, and 4 h + Zn conditions. Type-1 lipids are zinc-uninhibited (16 of 34, purple). Type-2 lipids are zinc-inhibited (12 of 34, blue), with complete inhibition shown in light blue and partial inhibition in dark blue. Type-3 lipids are zinc-modulated and capacitation-independent (4 of 34, green). Type-4 lipids are zinc-enhanced (2 of 34, orange). Created in BioRender. Kerns, K. (2025) https://BioRender.com/2i6406v
Zinc fine-tunes lipid remodeling during boar sperm capacitation, stabilizing sterol-rich membrane regions while selectively reprogramming fatty-acid dynamics. These findings reveal zinc as a key regulator linking sperm membrane composition to fertilization readiness.
Introduction
Capacitation primes sperm for fertilization. In mammals, sperm residence in the female reproductive tract initiates a sequence of biochemical events that elevate intracellular pH and cAMP, reorganize the plasma membrane, and enable acrosomal exocytosis, producing hyperactivated motility and ultimately fertilizing capacity (Chang, 1951; Austin, 1952; Singer and Nicolson, 1972; Hillman et al., 2013). These hallmark changes provide the framework for interrogating molecules that track capacitation state, as they involve coordinated ion fluxes, protein phosphorylation, and structural remodeling of the sperm surface membranes (Visconti et al., 2011; Buffone et al., 2014). Capacitation entails concerted sterol efflux and cAMP/PKA signaling that reprogram the sperm plasma membrane. In the mouse, cholesterol removal by BSA or HDL triggers a PKA-dependent rise in protein tyrosine phosphorylation and supports capacitation in vitro (Visconti et al., 1999). In porcine systems, bicarbonate-driven membrane processing integrates with these events to reorganize lipids prior to zona binding (Gadella and Harrison, 2000; Harrison and Gadella, 2005; Leahy and Gadella, 2015).
The lipid architecture of the sperm membrane is central to these transitions. The plasma membrane is laterally heterogeneous and organized into fluid microdomains that govern diffusion, curvature, and compartmentalization for protein trafficking and fusion events (Singer and Nicolson, 1972; Wolfe et al., 1998; Kawano et al., 2011). Compositional lipid class diversity among lipid microdomains imparts regional variation in membrane rigidity, diffusion, and functional specialization, underpinning the compartmentalized architecture of the sperm surface (Agrawal et al., 1988; Wolf et al., 1990; Tanphaichitr et al., 1993). During sperm capacitation, raft-associated components concentrate in the apical head region of porcine sperm, and detergent-resistant fractions change accordingly, indicating a coordinated redistribution of membrane constituents (Van Gestel et al., 2005). Earlier porcine work also documented maturation-linked shifts in phospholipid classes and sterols in boar sperm membranes, reinforcing that membrane composition is dynamic across functional states (Nikolopoulou et al., 1985).
Zinc ions (Zn2+) act as a molecular gatekeeper of processes during sperm capacitation. High extracellular Zn2+, present at millimolar concentrations in seminal plasma (∼1–3 mM), stabilizes sperm membranes and blocks proton extrusion through the flagellar voltage-gated proton channel Hv1, preventing premature capacitation (Lishko et al., 2010; Lishko and Kirichok, 2010; Allouche-Fitoussi and Breitbart, 2020). During capacitation, Zn2+ efflux relieves this inhibition, driving proton extrusion, intracellular alkalinization, and calcium entry. Image-based flow cytometry (IBFC) has revealed discrete Zn2+ distribution patterns, termed zinc signatures, that reorganize during in vitro capacitation (IVC) and respond dynamically to chelation or supplementation (Kerns et al., 2018b). These signatures both reflect capacitation status, including sperm-oviduct interactions, with zinc efflux promoting release from the oviductal sperm reservoir and progression to downstream remodeling events (Kerns et al., 2020). At the proteome level, more than 1,700 zinc-interacting proteins (zincoproteins) have been identified in porcine sperm, with over 100 changing during capacitation, including matrix metallopeptidase 2 (MMP2), a zinc-dependent enzyme implicated in zona pellucida penetration (Zigo et al., 2022) with decreased activity in the presence of exogenous Zn2+ (Kerns et al., 2020). Together, these findings position zinc as an integrative regulator coupling proton fluxes, proteome remodeling, and membrane lipid dynamics.
Capacitation thus emerges as a coordinated process, integrating ion signaling, metabolic regulation, and membrane remodeling. Within this framework, Zn2+ flux emerges as a central node, intersecting both metabolic and lipid pathways. Recent metabolomic studies in boar sperm demonstrated zinc-dependent shifts in glycolytic intermediates, TCA cycle metabolites, and fatty acids during capacitation (Weide et al., 2024). These observations emphasize that capacitation cannot be fully understood without considering the plasma membrane, where lipid remodeling mediates many downstream effects. Lipids represent a specialized layer of the metabolome, governing compartmentalization, protein trafficking, and acrosomal exocytosis; thus, profiling the lipidome provides a focused window into Zn2+ modulation of sperm capacitation (Watson, 2006).
Unlike somatic cells, spermatozoa are transcriptionally and translationally quiescent. Spermatozoa rely entirely on post-translational modifications and their existing molecular inventory to respond to environmental signals. Lipids thus serve not only as structural components but also as active regulators of signaling and protein localization. High-throughput lipidomics, particularly with liquid chromatography–mass spectrometry (LC-MS), offers class- and species-level coverage well beyond earlier biochemical assays such as ether extractions or thin-layer chromatography, enabling comprehensive and quantitative profiling of lipid remodeling (Pang et al., 2021).
Therefore, we hypothesize that boar sperm capacitation entails class- and species-specific lipid remodeling, and that extracellular Zn2+ modulates a subset of these changes. Our objectives are to identify if and which lipids change during boar sperm capacitation and to define which of those changes are stabilized or modulated by Zn2+, thereby locating Zn2+ points of influence within the capacitation process.
Materials and Methods
Animal care and use statement
Boar semen samples were obtained through collaboration with industry partners and represented surplus material from routine commercial collection procedures, samples not explicitly collected for research purposes. All semen collection and handling followed standard industry practices and adhered to the Guide for the Care and Use of Agricultural Animals in Research and Teaching (Fourth Edition, FASS, 2020). Because no live animal procedures were performed and semen collection occurred as part of normal husbandry activities, the use of these samples qualified for exemption from Iowa State University Institutional Animal Care and Use Committee (IACUC) oversight under ISU policy. All procedures were conducted in compliance with applicable institutional, state, and federal animal welfare standards, including the Animal Welfare Act (USDA, 1966, as amended) and the Public Health Service Policy on the Humane Care and Use of Laboratory Animals (PHS, 2015), which together govern the ethical care, management, and use of vertebrate animals in research and teaching.
Experimental design
To investigate lipidomic changes associated with boar sperm capacitation, three treatment conditions were compared: non-capacitated (0 h), in vitro capacitated for four hours (4 h), and in vitro capacitated for four hours in the presence of 2 mM extracellular zinc (4 h + Zn). The zinc concentration was selected to approximate levels found in seminal plasma (∼1–3 mM) and to model the zinc-rich environment sperm encounter immediately post-ejaculation. Since zinc concentrations naturally decline to micromolar levels along the female reproductive tract, this design allowed us to evaluate how sustained Zn2+ availability influences the progression of capacitation-associated remodeling and the functional importance of zinc signature transitions (e.g., loss of Zn2+ during sperm capacitation). Together, these treatments were designed to characterize membrane lipid remodeling during capacitation and to determine the regulatory role of Zn2+ in modulating these processes. Semen from seven commercially housed Duroc boars was evaluated. Capacitation status was verified by image-based flow cytometry (IBFC), and LC-MS was used to perform lipidomic profiling after organic solvent-based lipid extraction.
Semen collection and processing
Semen was collected from seven Duroc boars (n = 7), housed individually at a commercial boar stud. Animals were maintained on a standard commercial boar diet and collected weekly using the two-gloved hand technique. Only ejaculates with ≥80% progressive motility were included. Immediately post-collection, semen was extended five-fold using Preserve Xtreme extender (≤2°C temperature differential from semen) and delivered to Iowa State University on the same day. Upon arrival, the sample temperature was recorded, and the semen was stored at 17 °C. Within 24 hours of collection, samples were evaluated using computer-assisted semen analysis (CASA) and diluted to a final working concentration of 10 × 106 sperm/mL.
Computer-assisted semen analysis
To assess sperm concentration and motility, a 1000 µL aliquot was equilibrated at 37 °C for 10 minutes. After thorough but gentle mixing to ensure even cell distribution, 3 µL of semen was loaded into a 20 µm disposable counting chamber (Minitube GmbH, Tiefenbach, Germany). Analyses were performed using a Zeiss Axioscope 5 microscope equipped with a Basler ace acA2440–75uc digital camera and a 10×/0.25 A-Plan negative phase objective lens. Motility parameters were quantified using Minitube AndroVision® software (Reference Module 12,500/1000). The condenser aperture diaphragm was set to position 1, and the six-position filter wheel was set to position 2 to optimize contrast for sperm detection.
Video sequences were acquired at 60 frames per second with a capture duration of 0.5 seconds per field. For each sample, a minimum of 600 spermatozoa were analyzed across at least four non-overlapping microscopic fields. Sperm head detection and tracking were performed using AndroVision’s automated object-recognition algorithms, which identify spermatozoa based on size, shape, and motion characteristics. Sperm head detection and tracking were performed using AndroVision’s proprietary object-recognition algorithms. Minimum object size and shape thresholds were defined by the manufacturer’s default boar sperm profile for a 10× objective and were not manually adjusted. Objects failing to meet these criteria were automatically excluded as debris.
Motility classification was determined using AndroVision decision-tree thresholds based on kinematic and trajectory parameters. Spermatozoa were classified as immotile when curvilinear velocity (VCL) was <24.0 µm/s and amplitude of lateral head displacement (ALH) was <1.0 µm, or when the head activity coefficient (HAC) was <0.033. Motile sperm were further subdivided, with locally motile sperm defined by straight-line velocity (VSL) <24.0 µm/s and VCL <48.0 µm/s. Progressively motile sperm were defined as those exhibiting forward or circular trajectories, including circular motility with a trajectory radius between 10.0 and 30.0 µm and rotation >0.7, or forward progressive movement characterized as slow progressive motility (VCL <120.0 µm/s) or fast progressive motility when slow criteria were exceeded. All CASA settings, thresholds, and gating parameters were applied consistently across treatments and boars to ensure comparability and reproducibility.
Capacitation media and treatment conditions
Porcine non-capacitation medium
The porcine non-capacitation medium (pNCM) media was prepared as previously described by Kerns et al. (2018a), and consisted of NaCl, KCl, NaH2PO4, Na-lactate, MgCl2·6H2O, TL-HEPES, Na-pyruvate, sorbitol, glucose, gentamicin, penicillin G, and polyvinyl alcohol (PVA), dissolved in 1000 mL deionized water. The solution was vacuum-filtered, adjusted to pH 7.20 ± 0.02, and stored at 4 °C until use.
Porcine capacitation medium
Capacitating medium was prepared fresh on the day of experimentation by supplementing 50 mL of pNCM with NaHCO3, pyruvic acid, CaCl2, and bovine serum albumin (BSA), as previously described by Kerns et al. (2018a).
Capacitation treatments
Each treatment condition (0 h, 4 h, 4 h + Zn) included 20 million spermatozoa. For the non-capacitated (0 h) group, sperm were centrifuged at 110 × g for 10 minutes, the supernatant was removed, and the pellet was resuspended in pNCM. Five million cells were aliquoted for IBFC, and the remaining cells were pelleted and stored at −80°C for lipid extraction.
For capacitated groups (4 h and 4 h + Zn), sperm were washed to remove seminal plasma and incubated for 4 hours at 37 °C in either porcine capacitation medium (pCM) alone (4 h) or pCM supplemented with 2 mM ZnCl2. Following incubation, sperm were washed once in pNCM. Five million cells were reserved for flow cytometry, and the remaining washed pellets were stored at –80°C for subsequent lipidomics analysis.
Image-based flow cytometry for capacitation verification
Reagents
The following fluorophores were used: FluoZin-3 (FZ3; Invitrogen) reconstituted in DMSO (500 μM stock), PNA-Alexa Fluor 647 (Invitrogen) reconstituted in deionized water (0.5 μg/mL stock), Hoechst 33342 (Calbiochem) in deionized water (18 mM stock), and propidium iodide (PI; Acros Organics) in deionized water (1 mg/mL stock).
Probe staining and incubation
For each sample, 5 million sperm were pelleted at 110 × g for 5 minutes and resuspended in 100 μL of pNCM containing the following dilutions: H33342 (1:1000), PI (1:1000), FZ3 (1:500), and PNA-AF647 (1:2000). Samples were incubated at room temperature in the dark for 30 minutes. After washing with PBS (NaN3-free), cells were incubated at 37 °C for an additional 30 minutes to permit complete de-esterification of intracellular FZ3-AM esters.
Flow cytometry acquisition
Data were acquired using a Cytek® Amnis® ImageStream®X MkII imaging flow cytometer fitted with a 40× objective and a maximum throughput of 2000 events/s. The instrument was set to collect images of the following channels (Ch): bright-field (Ch 1), FZ3 (Ch 2), PI (Ch 4), side scatter (SSC; Ch 6), H33342 (Ch 7), bright-field (Ch 9) and PNA-AF647 (Ch 11). Laser settings were: 405 nm at 10 mW (H33342), 488 nm at 60 mW (FZ3), 561 nm at 40 mW (PI), 642 nm at 25 mW (PNA-AF647), and 785 nm at 10 mW (SSC). SpeedBeads were used to ensure acquisition was in focus. Data were captured using INSPIRE® software v3.0.
Data analysis
Flow cytometry data were processed using IDEAS® v6.4 software. Standard gating for single, in-focus cells was applied. To improve sperm orientation specificity, the Feature Finder tool was used to exclude cells aligned laterally to the camera field as previously described (Kerns et al., 2018b).
Capacitation verification
Data collected using IBFC were used to verify capacitation status in spermatozoa from all 7 boars (Figure 1). Bright-field imaging (Ch 1-BF) was employed to ensure only morphologically intact cells were analyzed. The FluoZin-3 AM zinc probe (Ch 2-Zn) was used to evaluate Zn2+ distribution patterns, which have been correlated with distinct capacitation states (Kerns et al., 2018b; Zigo et al., 2022). Shifts in zinc signature classifications were monitored across treatment groups, and percentages of each zinc signature are provided in Supplementary Table S1 (see online supplementary material). Plasma membrane integrity was assessed using propidium iodide (Ch 4-PI), which permeates only non-viable or membrane-compromised cells. An increase in PI-positive sperm following IVC is indicative of membrane integrity change (Miyazaki et al., 1990) and reflective of capacitation-associated membrane remodeling (Ramu and Jeyendran, 2013) as presented in Supplementary Table S2 (see online supplementary material). Nuclear visualization was confirmed with Hoechst 33342 (Ch 7-H33342). Acrosomal status was assessed with PNA-Alexa Fluor 647 (Ch 11-PNA), a lectin probe that binds exposed acrosomal glycoproteins. Percent PNA staining patterns for all treatments were quantified and are presented in Supplementary Table S3 (see online supplementary material) (Cafe et al., 2020). Collectively, these multiparametric readouts verified that capacitation was successfully induced in vitro and was consistently observed across all seven boars.
Figure 1.
Image-based flow cytometry confirmation of in vitro capacitation in boar sperm. (a–c) Histogram overlays comparing fluorescence intensities at 0 hours (red, solid fill) and after 4 hours of in vitro capacitation (IVC; green, unfilled). (a) FluoZin-3 AM for Zn2+ localization, (b) propidium iodide (PI) for assessing plasma membrane integrity and remodeling, and (c) PNA-AlexaFluor 647 for acrosomal integrity and remodeling. Data shown are representative of Boar #2. (d-g) Representative single-cell images acquired using the Cytek® Amnis® ImageStream®X MkII flow cytometer (Fremont, CA, USA). Images are organized by fluorescence channel and corresponding marker: (1) Bright-field for morphology, (2) FluoZin-3 AM for Zn2+ localization, (4) PI for membrane integrity/remodeling, (7) Hoechst 33342 for nuclear visualization, and (11) PNA-Alexa Fluor 647 for acrosomal status. Panels illustrate examples of spermatozoa exhibiting (d) zinc signature 1, (e) zinc signature 2, (f) zinc signature 3, and (g) zinc signature 4.
Lipidomics analysis
Lipid extraction
Frozen boar sperm pellet samples were submitted to the Iowa State University W.M. Keck Metabolomics Research Laboratory (RRID: SCR_017911) for lipidomic analysis. Sample preparation followed a modified protocol based on Kimbara et al. (2013) and Okazaki et al. (2015). Briefly, 350 µL of extraction solvent (3:1 methyl tert-butyl ether: methanol with 1 μM 1,2-dilauroyl-sn-glycero-3-phosphoethanolamine as an internal standard; Avanti Polar Lipids, Birmingham, AL) was added to 75 mg of sample. After vortexing, samples were chilled on ice for 10 minutes, sonicated in a water bath for 10 minutes, and vortexed again for 10 minutes. Water (110 µL) was added, followed by vortexing for 3 minutes. Samples were centrifuged at 16,000 × g for 7 minutes, and ∼200 µL of the supernatant was transferred to glass vials and dried under nitrogen gas. Lipids were resuspended in 75 µL ethanol and vortexed for 10 minutes.
LC-MS acquisition
Extracts (120 µL) were filtered using 0.2 μm centrifugal filters (Millipore Sigma UFC30LG25) prior to LC-MS. Chromatography was performed on an Agilent 1290 Infinity UHPLC coupled to a 6540 UHD Accurate-Mass Q-TOF mass spectrometer (Agilent Technologies, Santa Clara, CA) using a Waters Acquity UPLC HSS T3 column (1.8 μm, 1.0 mm × 50 mm). Sample injection volume was 1.5 µL, column temperature 55 °C, and flow rate 0.150 mL/min. Solvents were LC-MS grade: (A) acetonitrile : water : 1 M ammonium acetate: formic acid (158 g : 800 g : 10 mL : 1 mL), and (B) acetonitrile : 2-propanol : 1 M ammonium acetate: formic acid (79 g : 711 g : 10 mL : 1 mL). The gradient was: 0 min, 35% B; 3 min, 70% B; 7 min, 85% B; 10 min, 90% B; 12 min, 90% B; 12.5 min, 35% B; followed by a 6 min post-run at 0% B. Ionization was achieved using electrospray in both positive and negative modes with the following settings: drying gas 11 L/min at 350 °C, nebulizing pressure 23 psi, sheath gas 11 L/min at 400 °C, capillary voltage 4000 V. The instrument was operated in high-resolution (4 GHz) mode, scanning m/z 100–1700 at 1.5 spectra/s. Continuous mass calibration used reference ions (positive: m/z 121.050873, 922.009698; negative: m/z 112.985587, 1033.988109). Data processing and feature detection were performed with Agilent MassHunter Qualitative Analysis v10.0 and Mass Profiler v8.0. Lipid identification was based on accurate mass matching to the METLIN database (Smith et al., 2005). Unannotated lipids were provisionally named according to their empirical formula, followed by retention time (RT) and exact mass, in the format “Chemical formula (RT, Mass)”. Unannotated lipids refer to LC-MS features that were reproducibly detected across samples but could not be confidently assigned to a specific lipid class or molecular identity based on accurate mass and retention time matching to the lipid databases queried in this study. These features are therefore reported by their mass-to-charge ratio (m/z) and retention time rather than a formal lipid name. This designation does not imply that these molecules are absent from the literature, but rather that their structural identities could not be resolved within the scope of the present non-targeted lipidomics workflow. Such features are commonly encountered in lipidomics and reflect the incompletely characterized nature of the lipidome, often referred to as part of the ‘dark lipidome.
Lipid abundances were quantified on a relative basis using class-specific internal standards for normalization. Absolute quantification was not performed, as external calibration curves were not employed.
Statistical analysis of non-targeted lipidomics
Statistical analysis of lipidome data was conducted using MetaboAnalyst v6.0, a web-based R platform for the interpretation of metabolomic and lipidomic data (Pang et al., 2021). Prior to analysis, raw peak intensities were normalized to internal standards and log-transformed to reduce heteroscedasticity (Supplementary Figure S1—see online supplementary material for a colour version of this figure). Univariate and multivariate statistical approaches were applied to evaluate treatment effects. One-way Analysis of Variance (ANOVA) with Benjamini-Hochberg FDR correction, with adjusted P < 0.05 considered statistically significant, followed by t-tests and Tukey’s Honestly Significant Difference (HSD) post hoc comparisons, all used to identify lipids that differed significantly among treatments. Principal Component Analysis (PCA) was additionally performed to visualize global variation and treatment-specific clustering among non-capacitated (0 h), 4 hours in vitro capacitated (4 h), and zinc-treated 4 hours in vitro capacitated (4 h + Zn) samples (Stacklies et al., 2007).
Statistical categorization of lipid shift patterns
Using Tukey’s lipid-pattern classification method (significance + directionality), we defined zinc-response classes from three prespecified pairwise contrasts among 0 h, 4 h, and 4 h + Zn. For each lipid, a one-way ANOVA was followed by Tukey’s HSD (familywise α = 0.05) to identify which contrasts were significant: C = 0 h vs 4 h (capacitation-associated shifts), Z = 0 h vs 4 h Zn (capacitation under Zn2+ influence), and M = 4 h vs 4 h + Zn (Zn2+ modulation of capacitation). Contrasts not listed in the post hoc output showed no significant abundance shifts. Directionality (“Increase”, “Decrease”, and “No Change”) was assigned based on group means, using the same analysis scale as the ANOVA. Lipids were then classified by a prespecified rule set using Tukey’s HSD significance results and directionality: Type-1 lipids, zinc-uninhibited if C was significant and M not significant; Type-2 lipids, zinc-inhibited if C and M were significant with opposite directions (subtyped complete inhibition when Z not significant, otherwise partial inhibition); Type-3 lipids, zinc-modulated, capacitation-independent if C was not significant but Z or M significant; Type-4 lipids, zinc-enhanced if C and M were significant with the same direction.
Results
Using LC-MS, we quantified lipidomic shifts across non-capacitated spermatozoa (0 h), IVC sperm (4 h), and IVC sperm with Zn2+ supplementation (4 h + Zn). Principal component analysis (PCA) plots revealed clear separation of treatment groups, indicating that capacitation and Zn2+ supplementation produced distinct global lipidomic profiles (Figure 2a). PC1 (40.5%) and PC2 (15.8%) captured most of the variance, with non-capacitated samples clustering separately from capacitated groups, while Zn2+ supplementation redirected capacitated sperm toward a distinct profile. To identify the lipid features contributing most strongly to these separations, we visualized the top 25 of the 34 differentially abundant lipids identified by one-way ANOVA in a heatmap (Figure 2b). A Tukey’s HSD test followed the one-way ANOVA; the results are shown in Supplementary Table S4 (see online supplementary material). A heatmap containing all 34 lipids is in Supplementary Figure S2 (see online supplementary material for a colour version of this figure). This representation highlights coordinated remodeling during capacitation and the ability of Zn2+ to constrain or shift subsets of these lipid changes, suggesting that zinc acts selectively rather than globally. Within the 34 differentially abundant lipids, 9 were unannotated. These unannotated features represent reproducible LC-MS signals that met stringent statistical thresholds but could not be confidently assigned to known lipid classes based on accurate mass and retention time matching to the databases queried in this study. As such, they were retained in downstream analyses to capture zinc-responsive lipid behavior at the feature level, while acknowledging that definitive structural identification was beyond the scope of the present non-targeted workflow. Feature identities are therefore reported using empirical formula, retention time, and exact mass, consistent with standard practice in discovery lipidomics. The LC-MS readouts for the unannotated lipids are shown in Supplementary Table S5 (see online supplementary material).
Figure 2.
Principal component analysis (PCA) and heatmap of lipidomic data from boar sperm across treatments. (a) PCA based on normalized lipid abundance values. Colored by treatment: non-capacitated (0 h, red circles), in vitro capacitated (4 h, green squares), and in vitro capacitated with zinc supplementation (4 h + Zn, blue triangles). PC1 (x-axis, 40.5%) and PC2 (y-axis, 15.8%) capture the majority of variance. Ellipses represent 95% confidence intervals. (b) Heatmap of the top 25 differentially abundant lipids (ANOVA). Columns represent individual boar samples grouped by treatment (0 h, red; 4 h, green; 4 h + Zn, blue). Rows represent individual lipids. Abundance values are Z-score normalized (blue = low, red = high). Figures generated in MetaboAnalyst 6.0.
Differential lipid abundances were next categorized by their zinc-response patterns across 0 h, 4 h, and 4 h + Zn using Tukey’s lipid-pattern classification method (see the section on “Statistical categorization of lipid shift patterns”; Supplementary Table S6—see online supplementary material). The distribution of the 34 significant features by lipid zinc-response type is summarized in Figure 3. Nearly half (47.1%) of the lipids that increased or decreased in abundance after 4 hours of in vitro capacitation were uninhibited by zinc (Type-1). More than a third (35.3%) of the lipids that underwent remodeling during capacitation, reflected by changes in abundance, were inhibited by zinc (Type-2), either fully or partially (as evidenced by relativity toward baseline at 0 h). Smaller subsets consisted of zinc-modulated, capacitation-independent lipids (Type-3, 11.8%) that changed only in the presence of zinc, and zinc-enhanced lipids (Type-4, 5.9%) in which zinc amplified the same directional abundance shifts observed during capacitation. This distribution indicates that while much of capacitation proceeds unaffected by zinc, a substantial fraction of lipid remodeling is either induced or reshaped by zinc.
Figure 3.
Distribution of differentially abundant lipids by zinc-response type. Type-1: zinc-uninhibited (16/34, purple). Type-2: zinc-inhibited (12/34, blue; complete inhibition = light blue, partial = dark blue). Type-3: zinc-modulated, capacitation-independent (4/34, green). Type-4: zinc-enhanced (2/34, orange). Classification criteria are detailed in the section on “Statistical categorization of lipid shift patterns”.
To assess the biochemical composition of capacitation-associated remodeling, we categorized the 30 differential lipids that changed from 0 h to 4 h (Figure 4). This comparison excluded the four zinc-specific responders, which remained at 0 h-like levels after 4 h but showed differential abundance only in the 4 h + Zn condition, indicating zinc-dependent rather than capacitation-driven shifts. Among these 30 lipids, 9 (30%) could not be annotated, while the remainder were distributed across fatty acyls (6/30; 20%), sterol lipids (7/30; 23%), Sphingolipids (1/30; 3%), glycerophospholipids (4/30; 13%), and glycerolipids (3/30; 10%). This distribution shows that capacitation-linked remodeling draws from multiple lipid classes.
Figure 4.
Distribution of capacitation-associated lipids across classes. The pie chart shows proportions: unannotated (purple, 30%), fatty acyls (light blue, 20%), sterol lipids (dark green, 23%), Sphingolipids (light green, 3%), glycerophospholipids (dark blue, 14%), and glycerolipids (orange, 10%). Classification based on Agilent MassHunter software identifications correlated with LIPID MAPS.
Lipid categories were compared across zinc-response classes to determine how different lipid types contributed to each response pattern (Figure 5). This comparison revealed that zinc-uninhibited lipids (n = 16) were most frequent, consisting primarily of unattributed (n = 7) and fatty acyls (n = 5) species, with smaller contributions from sterol lipids (n = 3) and glycerolipids (n = 1). Zinc-enhanced lipids (n = 2) comprised one sterol lipid and one unattributed feature. Zinc-specific lipids (n = 4) were composed entirely of fatty acyls. Zinc-inhibited lipids (n = 12) showed a distinct split between partial (n = 6) and complete inhibition (n = 6): partial inhibition included glycerophospholipids (n = 1), glycerolipids (n = 2), fatty acyls (n = 1), and unannotated (n = 1), while complete inhibition contained glycerophospholipids (n = 3) and sterol lipids (n = 3). These distributions indicate that zinc-responsive remodeling is not uniform across lipid categories, with sterols and phospholipids more often associated with inhibition, while fatty acyls dominate zinc-specific responses.
Figure 5.
Lipid-category composition within zinc-response classes. Each bar shows the within-class composition of capacitation-associated lipids defined by Tukey’s lipid-pattern rules (see the section on “Statistical categorization of lipid shift patterns”): Type-1, zinc-uninhibited (n = 16); Type-2, zinc-inhibited (n = 12), including partial inhibition (n = 6) and complete inhibition (n = 6); Type-3, zinc-specific (n = 4); Type-4, zinc-enhanced (n = 2). Segment heights indicate the proportion of lipid categories within each class; totals per class are shown beneath the bars. Unannotated (purple), glycerophospholipids (dark blue), glycerolipids (orange), sterol lipids (dark green), sphingolipids (light green), and fatty acyls are color coded as designated in figure key (light blue). Category assignments were based on Tukey’s HSD results found in MetaboAnalyst 6.0. Lipid classification was conducted using LIPID MAPS.
To characterize zinc-uninhibited remodeling, representative Type-1 lipids were examined (Figure 6). These species increased significantly from 0 h to 4 h, and this elevation persisted in 4 h + Zn, indicating that their capacitation-linked abundance changes proceed independently of zinc.
Figure 6.
Representative box plots of Type-1 (capacitation-associated, zinc-uninhibited) lipids, showing 4 of the 16 identified in this category. Four lipid species increased significantly (P < 0.05) in both 4 h and 4 h + Zn compared to 0 h, with no difference between capacitated groups. Twelve additional lipids were classified as Type-1, located in Supplementary Table S6. These represent characteristic capacitation-driven shifts not altered by zinc. Colors: red = 0 h, green = 4 h, blue = 4 h + Zn. Each point represents an individual boar; the yellow diamond indicates the group mean. Plots were generated in MetaboAnalyst 6.0.
Type-2 lipids, classified as zinc-inhibited, exhibited reversal of capacitation-induced abundance changes when exogenous Zn2+ was present after 4 h of IVC compared to 0 h (Figure 7). Two sub-patterns were observed: complete inhibition, in which Zn2+ maintained lipid levels at the 0 h baseline, and partial inhibition, in which Zn2+ did not fully counteract capacitation-associated shifts.
Figure 7.
Representative box plots of Type-2 (zinc-inhibited) lipids, showing 4 of the 12 identified in this category. (a) Complete inhibition: 0 h vs 4 h and 4 h vs 4 h + Zn differ significantly in opposite directions, while, in comparison, 0 h vs 4 h + Zn is not significant, indicating that zinc-maintained baseline abundance and prevented the capacitation-associated shift. (b) Partial inhibition: 0 h vs 4 h and 4 h vs 4 h + Zn differ significantly, but 4 h + Zn remains intermediate, showing that Zn2+ partially limited the capacitation effect. Colors: red = 0 h, green = 4 h, blue = 4 h + Zn. Boxes show median and IQR (whiskers = 1.5× IQR; points = samples). Plots were generated in MetaboAnalyst 6.0.
Type-3 lipids, classified as zinc-specific, responded exclusively to Zn2+ supplementation after 4 h IVC (Figure 8). These species were stable between 0 h and 4 h, but decreased markedly at 4 h + Zn, indicating a response uniquely attributable to zinc rather than to capacitation itself. This pattern reflects capacitation-independent zinc suppression of lipid abundance.
Figure 8.
Representative box plots of Type-3 (zinc-specific) lipids, showing all 4 lipids identified in this category. Shown are 11Z-Hentriacontene, 9Z-triacontene, 10Z-tricosene, and 14S-methyl-1-octadecene. All decreased significantly (P < 0.05) in 4 h + Zn relative to both 0 h and 4 h, indicating zinc-specific suppression. Colors: red = 0 h, green = 4 h, blue = 4 h + Zn. Plots were generated in MetaboAnalyst 6.0.
Type-4 lipids exhibited zinc-enhanced remodeling, where zinc amplified the direction of capacitation-associated changes (Figure 9). One lipid decreased stepwise across treatments, while another increased stepwise, demonstrating that zinc can act as both an amplifier of capacitation-driven increases and a promoter of progressive decreases.
Figure 9.
Representative box plots of Type-4 (zinc-enhanced) lipids, showing all 2 lipids identified in this category. C17H36N4O3P (1.04, 375.2525) decreased progressively in abundance (0 h > 4 h > 4 h + Zn; P < 0.05), while 16:0 cholesterol ester increased progressively in abundance (0 h < 4 h < 4 h + Zn; P < 0.05). By Tukey’s HSD, both 0 h vs 4 h and 4 h vs 4 h + Zn were significant in the same direction, showing zinc amplification of capacitation-driven remodeling. Colors: red = 0 h, green = 4 h, blue = 4 h + Zn. Boxes show median and IQR (whiskers = 1.5× IQR; points = samples). Plots were generated in MetaboAnalyst 6.0.
Discussion
Capacitation is a prerequisite for mammalian fertilization, integrating signaling, metabolism, and membrane remodeling into a coordinated transition that enables sperm to achieve fertilizing capacity. In this study, IBFC confirmed capacitation status after IVC, and LC-MS lipidomics revealed remodeling of the boar sperm lipidome following IVC and Zn2+ supplementation. Multivariate structure and class-level distributions showed clear treatment-dependent separation, supporting that capacitation reshapes the sperm membrane composition at the systems level. Collectively, our data demonstrate that capacitation remodels the boar sperm lipidome and that extracellular zinc modulates both the magnitude and direction of those changes.
Capacitation-associated lipid remodeling
Within the 34 significantly altered lipids identified, nearly half (47.1%) shifted consistently during capacitation regardless of zinc supplementation (Type-1). These included multiple cholesteryl esters such as 14:0, 15:0, and 17:0, as well as fatty acids like 18-hydroxystearic acid and polyunsaturated chains, including 3Z , 6Z , 9Z , 12Z , 15Z-pentacosapentaene.
Classical models describe free cholesterol efflux from the sperm plasma membrane as a hallmark of capacitation; however, our data likely reflect total sterol remodeling rather than surface depletion alone. Earlier work on boar sperm demonstrated that although free cholesterol declines during maturation, other sterol derivatives, such as desmosterol and cholesterol sulfate, increase (Nikolopoulou et al., 1985), indicating compositional reorganization rather than net sterol loss. The observed rise in cholesteryl ester abundance in this study represents intracellular sequestration or transformation of cholesterol, consistent with zinc-mediated stabilization of sterol pools rather than inhibition of efflux itself. These lipid class changes reinforce established models that capacitation reorganizes raft-associated components toward the apical head region while maintaining overall raft structure, a process linked to the redistribution of cholesterol and raft-associated proteins (Van Gestel et al., 2005).
Zinc as a regulator of remodeling
Extracellular Zn2+, simulating seminal fluid levels, selectively constrained or redirected subsets of capacitation-linked lipid shifts. Roughly one-third of differentially abundant lipids were zinc-inhibited, reflecting zinc’s stabilizing effect on membrane composition. Sterol and glycerophospholipid species were most strongly affected, with zinc preserving near-baseline lipid abundance levels in these categories. Partial inhibition of lipid shifts was observed across a wide range of lipid classes, including sphingolipids.
Mechanistically, these responses align with zinc’s known role in regulating capacitation via inhibiting the Hv1 proton channel, which restricts proton extrusion and thereby limits intracellular alkalinization, calcium influx, and downstream PKA activation (Lishko et al., 2010; Lishko & Kirichok, 2010). Beyond ionic control, zinc also modulates capacitation-associated protein remodeling through zinc-protein interactions, reducing the activity of acrosomal proteolytic enzymes implicated in zona pellucida penetration and zona digestion, including proacrosin, MMP2, and the 26S proteasome (Steven et al., 1982; Kerns et al., 2020; Zigo et al., 2022).
Such preservation of sterol- and PUFA-rich membrane domains is likely functionally relevant. Am-in et al. (2011) reported that boars with higher sperm motility have greater phospholipid and n-3 PUFA content, along with enhanced seminal fluid antioxidant capacity. These compositional and redox features correlated positively with sperm motility, morphology, and plasma-membrane integrity, indicating that the lipid species stabilized by zinc in our dataset are also associated functional competence in vivo. Accordingly, zinc’s inhibitory effect could be interpreted as a protective modulation that maintains oxidation-sensitive lipid domains and may help preserve membrane stability during capacitation.
Consistent with this interpretation, zinc frequently maintained 0 h-like sterol and phospholipid profiles, suggesting a stabilization of membrane domains that could delay or dampen the sterol efflux events associated with PKA-dependent maturation. Our findings align with prior reports demonstrating that zinc signatures progress during in vitro capacitation and can be maintained at prior-to-IVC profiles with Zn2+ supplementation during IVC (Kerns et al., 2018b).
Zinc-specific and zinc-enhanced effects
Beyond inhibition, a subset of lipids responded exclusively to Zn2+ supplementation. Four fatty acyls, including 10Z-tricosene and 14S-methyl-1-octadecene, were unchanged between 0 h and 4 h but decreased significantly only in the Zn2+ supplementation conditions, defining them as zinc-specific responders. Conversely, zinc enhanced the capacitation-associated shifts of two species: a cholesterol ester (CE(16:0)) and an unannotated lipid (C17H36N4O3P (1.04, 375.2525)). 16:0 cholesterol ester increased progressively from 0 h → 4 h → 4 h + Zn, whereas C17H36N4O3P (1.04, 375.2525) decreased across the same trajectory.
These dual effects reveal zinc’s capacity to both promote and restrain remodeling, functioning less as a binary block and more as a dynamic regulator of membrane lipid turnover. The zinc-enhanced rise in cholesteryl ester abundance suggests a shift toward sterol sequestration or redistribution rather than fatty-acid release, consistent with zinc’s known ability to stabilize membrane microdomains and limit excessive membrane fluidity during late capacitation. Such remodeling likely maintains optimal raft organization and receptor localization for signaling and acrosome-reaction readiness.
Collectively, these data indicate that Zn2+ modulates lipid remodeling not through generalized suppression but through class-specific steering, enhancing sterol ester accumulation while constraining turnover of unsaturated hydrocarbons. This selective influence may support the maintenance of membrane order required for zona-recognition and acrosomal competence during late capacitation. Notably, zinc signature progression differs among boars, with some advancing through capacitation signatures more rapidly than others. Such variability likely reflects intrinsic differences in baseline sterol composition and membrane responsiveness. We propose that zinc’s class-specific modulation of sterol and hydrocarbon remodeling may underlie these divergent capacitation kinetics, positioning lipid architecture as a determinant and zinc as a regulator of boar-specific capacitation tempo.
Implications for fertility and applied livestock reproduction
Beyond defining mechanistic lipid remodeling during capacitation, these findings have potential implications for fertility outcomes and applied livestock breeding technologies. Capacitation efficiency and timing are key determinants of fertilization success, particularly in artificial insemination and in vitro fertilization systems where sperm are removed from their native reproductive context and exposed to defined capacitating environments. Sterols, glycerophospholipids, and polyunsaturated fatty acyl-containing lipids are established regulators of sperm membrane fluidity and lateral organization, governing the formation and stability of membrane microdomains that coordinate signaling, receptor redistribution, and acrosomal competence during capacitation (Gadella and Harrison, 2000). In parallel, enrichment and turnover of polyunsaturated fatty acids influence membrane flexibility and susceptibility to remodeling events associated with hyperactivation and fertilization readiness. Prior work in boars has linked sperm lipid composition to functional competence and fertility outcomes, supporting the relevance of lipid remodeling to reproductive performance (Am-in et al., 2011; Leahy and Gadella 2015).
The zinc-modulated lipid remodeling observed here reflects shifts in biophysical membrane states that influence capacitation progression rather than fertilization. Stabilization of sterol- and phospholipid-rich membrane domains by zinc may preserve membrane integrity during storage or early capacitation, whereas premature loss of these lipid features could predispose sperm to accelerated capacitation or membrane destabilization. Such dynamics are particularly relevant for boar semen preservation, where variation in capacitation kinetics among ejaculates contributes to inconsistent fertility outcomes despite acceptable motility and morphology.
From an applied perspective, zinc-responsive lipid signatures may represent candidate biomarkers of capacitation control that extend beyond conventional motility-based assessments. Integrating lipidomic phenotypes with functional readouts such as image-based flow cytometry provides a path toward refining semen evaluation tools used in livestock breeding programs. Such approaches may help explain why some boars exhibit high fertility despite similar conventional semen parameter Integration of zinc-modulated lipid domains with capacitation signaling.
Integration of zinc-modulated lipid domains with capacitation signaling
Zinc-modulated lipid remodeling intersects with established capacitation regulators through coordinated effects on membrane organization and ion-channel signaling. Capacitation is driven by tightly coupled proton, calcium, and bicarbonate fluxes that activate soluble adenylyl cyclase and downstream cAMP/PKA signaling, processes that are inherently sensitive to the biophysical state of the sperm plasma membrane (Visconti et al., 1999; Buffone et al., 2014). In human spermatozoa, zinc has been shown to regulate capacitation upstream by inhibiting the Hv1 proton channel, thereby constraining intracellular alkalinization and limiting subsequent CatSper-mediated calcium entry (Lishko et al., 2010; Lishko and Kirichok, 2010). While these channel-level mechanisms have been most extensively characterized in human systems, they provide a well-established framework for understanding how zinc availability interfaces with conserved capacitation signaling pathways.
Membrane lipid composition plays a critical role within this regulatory axis, as sterol- and phospholipid-rich microdomains influence the localization, activity, and gating behavior of ion channels and associated signaling complexes during capacitation. Redistribution of cholesterol and associated lipid domains is a prerequisite for downstream signaling and acrosomal competence, and stabilization of these domains by extracellular zinc may therefore dampen or delay progression through ion-driven signaling cascades. Such effects are consistent with zinc-dependent preservation of membrane order observed in this study and with prior models in which capacitation proceeds through coordinated membrane reorganization rather than isolated molecular events (Gadella and Harrison, 2000; Leahy and Gadella, 2015).
In this context, zinc-modulated lipid domains may function as integrative platforms that coordinate membrane order with ion-channel regulation and kinase signaling, rather than acting as passive structural features. This coordination provides a mechanistic framework linking zinc-dependent lipid remodeling to the established capacitation cascade, wherein ion fluxes, second messenger signaling, and membrane reorganization proceed in a tightly regulated and temporally ordered manner. Together, these relationships position lipid remodeling as an intermediate regulatory layer through which zinc can shape capacitation dynamics without directly altering the core signaling machinery (Allouche-Fitoussi and Breitbart, 2020).
Lipid class distributions and global structure
Class-level annotation further resolved the architecture of zinc’s influence. Categorizing features into Types 1–4 provided a structured framework linking individual species. Fatty acyls represented the entire share of zinc-specific lipids, underscoring zinc’s intersection with dynamic fatty-acid metabolism. Sterols were enriched among zinc-inhibited species, reinforcing zinc’s role in delaying sterol efflux required for downstream membrane-fusion events. Glycerophospholipids such as PI(22:3(10Z,13Z,16Z)/18:3(9Z,12Z,15Z)) showed partial inhibition, consistent with fine-scale rather than absolute regulation.
Collectively, these class-wise patterns show that zinc does not simply blunt lipid turnover; it reorders the hierarchy of membrane responsiveness during capacitation. By preserving sterol and phospholipid domains while allowing selective remodeling of fatty acid pools, zinc maintains sperm head stability while permitting the generation of lipid-derived signaling intermediates. This dual control suggests that zinc functions as a dynamic coordinator of membrane remodeling, synchronizing membrane compositional change with the physiological timing of fertilization capacity.
This hierarchical lipid organization mirrors the broader capacitation signaling cascade, in which sterol efflux, ion fluxes, and kinase activation proceed in a defined temporal sequence. The class-resolved lipid responses, therefore, integrate seamlessly into this network, positioning Zn2+ as a coordinating hub that links ion-channel regulation, metabolic remodeling, and membrane architecture into a unified capacitation framework.
Integration with capacitation signaling and zinc biology
Our lipidomic results extend prior metabolomic findings that zinc modulates glycolytic and TCA intermediates during porcine sperm capacitation (Weide et al., 2024), revealing a parallel layer of Zn2+ control over membrane composition. Proteomic analyses identifying more than 1,700 zinc-interacting proteins, including over 100 that change during sperm capacitation, such as MMP2, position zinc as a possible key regulator linking ion flux, metabolism, proteostasis, and membrane remodeling (Zigo et al., 2022). Lipids occupy the intersection of these systems: they provide structural scaffolds for membrane rafts, serve as substrates for signaling mediators, and modulate membrane-protein topology. Hence, zinc’s modulatory role at the lipid level extends to broader physiological effects on sperm function.
Methodological considerations and future directions
While our design, consisting of three treatment conditions across seven boars with matched IBFC verification, supports robust group-level inference, several constraints warrant acknowledgment. (i) A single 4 h time point cannot resolve the temporal order of lipid transitions. (ii) The 2 mM ZnCl2 concentration, selected to approximate Zn2+ levels in seminal fluid, exceeds the micromolar concentrations found in the oviductal environment where capacitation physiologically occurs. This design intentionally modeled the zinc-rich seminal state to examine how sustained extracellular Zn2+ influences capacitation-associated lipid remodeling. By maintaining high Zn2+ availability, we effectively limited the normal progression of zinc signatures observed during capacitation, allowing evaluation of how zinc retention stabilizes sterol and phospholipid pools and constrains downstream remodeling events. (iii) Several lipid features could not be fully annotated using accurate mass and retention time matching alone, limiting pathway-level interpretation for this subset of zinc-responsive species. Importantly, these unannotated features displayed highly reproducible abundance patterns across boars and treatment conditions and contributed meaningfully to the zinc-response classifications reported here. Their inclusion therefore strengthens pattern-level inference regarding zinc modulation of membrane remodeling, even though molecular identities remain unresolved. Definitive structural elucidation of these features will require targeted MS/MS fragmentation and comparison against expanded spectral libraries and authentic standards in future studies. (iv) The IVC medium (BSA//Ca2+) imposes defined biophysical milieus that could bias raft dynamics and sterol flux.
Future work should (1) perform time-resolved lipidomics (0–6 h) with IBFC to determine whether sterol ester accumulation precedes fatty-acid reprogramming during capacitation; (2) employ targeted MS/MS and isotope tracing to quantify cholesterol trafficking and fatty-acid turnover under ±Zn2+, paired with pharmacologic modulation of ACAT, LCAT, and lipid-transfer proteins to resolve enzymatic control of sterol and acyl remodeling; and (3) directly test functional coupling by assessing zona-binding and AR induction thresholds in the same samples, linking zinc-stabilized sterol and phospholipid profiles to delayed capacitation and evaluating how zinc-specific fatty-acid responses contribute to membrane flexibility and acrosomal competence.
Conclusions
By mapping class-resolved lipid changes across capacitation states and overlaying zinc perturbation, we demonstrated that zinc stabilizes sterol and glycerophospholipid composition while reprogramming fatty-acid pools, and, in select cases, amplifies capacitation-linked features such as sterol. These results expand the known framework of zinc regulation of boar sperm beyond proteomic (Zigo et al., 2022) and metabolomic (Weide et al., 2024) findings showing that the lipidome itself is a direct target of zinc’s modulatory influence. Within the physiological context of Zn2+ efflux from seminal fluids to micromolar oviductal levels, the convergence of multivariate structure, class-level summaries, and IBFC-verified physiology supports a unified model of Zn2+ as a membrane-centric, state-dependent regulator of the porcine sperm lipidome, coordinating the timing and extent of capacitation to align molecular remodeling of the sperm membrane with the functional demands of fertilization.
Supplementary Material
Acknowledgments
The authors thank the W.M. Keck Metabolomics Research Laboratory at Iowa State University for assistance with LC-MS analyses and industry partners for providing semen samples. This project was supported by Agriculture and Food Research Initiative (AFRI) Competitive Grant no. 2022-67015-36298 (K.K.) from the USDA National Institute of Food and Agriculture (NIFA) and the Iowa Pork Producers Association Award no. 22015 (K.K.).
Glossary
Abbreviations:
- ANOVA
analysis of variance
- BSA
bovine serum albumin
- CASA
computer-assisted semen analysis
- CE
cholesteryl ester
- Ch
channel
- cAMP
cyclic adenosine monophosphate
- DMSO
dimethyl sulfoxide
- FDR
false discovery rate
- FZ3
FluoZin-3
- H33342
Hoechst 33342
- HSD
honestly significant difference
- IBFC
image-based flow cytometry
- IHC
immunohistochemistry (if used in supplement)
- IQR
interquartile range
- IUPAC
International Union of Pure and Applied Chemistry
- IVC
in vitro capacitation
- LC-MS
liquid chromatography–mass spectrometry
- LC-QTOF
liquid chromatography–quadrupole time-of-flight
- METLIN
Metabolite and Tandem MS Database
- MS
mass spectrometry
- PCA
principal component analysis
- PI
propidium iodide
- PKA
protein kinase A
- pNCM
porcine non-capacitation medium
- pCM
porcine capacitation medium
- PNA
peanut agglutinin
- PUFA
polyunsaturated fatty acid
- PVA
polyvinyl alcohol
- RT
retention time
- SSC
side scatter
- TCA
tricarboxylic acid
- Zn2+
zinc ion
Contributor Information
Ian J Shofner, Department of Animal Science, Iowa State University, Ames, IA 50011, USA.
Kayla Mills, AcuFast, Breese, IL 62230.
Tyler Weide, Department of Animal Science, Iowa State University, Ames, IA 50011, USA.
Matthew W Breitzman, W.M. Keck Metabolomics Research Laboratory, Iowa State University, Ames, IA 50011.
Karl Kerns, Department of Animal Science, Iowa State University, Ames, IA 50011, USA.
Author Contributions
Ian J. Shofner (Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing—original draft, Writing—review & editing), Kayla Mills (Resources, Supervision, Validation, Writing—original draft, Writing—review & editing), Tyler J. Weide (Conceptualization, Data curation, Formal analysis, Investigation, Writing—review & editing), Matthew W. Breitzman (Data curation, Investigation, Validation, Writing—review & editing), and Karl Kerns (Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Validation, Writing—original draft, Writing—review & editing)
Supplementary Data
Supplementary data are available at Journal of Animal Science online.
Conflict of interest statement: The authors declare no real or perceived conflicts of interest.
Data Availability
Data supporting the findings of this study are available from the corresponding author upon reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
Data supporting the findings of this study are available from the corresponding author upon reasonable request.










