The objectives were to separate canine seminal plasma proteins (with SDS-PAGE) and to determine the correlation between specific proteins and semen characteristics. Three ejaculates from 20 mixed-breed dogs, of unknown fertility, were collected by digital manipulation. Ejaculate volume and color, sperm motility, sperm vigor, percentage of morphologically normal spermatozoa, and membrane integrity (hypoosmotic swelling test and fluorescent staining) were assessed. For each dog, seminal plasma was pooled from all three ejaculates and proteins were separated with SDS-PAGE, using polyacrylamide concentrations of 13% and 22% in the separation gels. After staining, gel images were digitized to estimate molecular weights (MW) and integrated optical density (IOD) of each lane and of individual bands. Total seminal plasma protein concentration was 2.19+/-1.56 g/dL (mean+/-SD; range 1.12-5.19 g/dL). A total of 37 protein bands were identified (although no dog had all 37 bands). In the 13% gel, molecular weights ranged from 100.6 to 17.1 kDa, with four bands (49.7, 33.2, 26.4, and 19.5 kDa) present in samples from all dogs. In the 22% gel, molecular weights ranged from 15.6 to 3.6 kDa, with nine bands (15.6, 13.5, 12.7, 11.7, 10.5, 8.7, 7.8, 5.6, and 4.9 kDa) present in samples from all dogs. Combined for both gels, the majority of bands (85%) had molecular weights <17 kDa, with B20 (15.6 kDa) in high concentrations in samples from all dogs. There were positive correlations (P < or = 0.01) between two bands, B4 (67 kDa) and B5 (58.6 kDa), and sperm motility (r=0.66 and r=0.46), sperm vigor (r=0.56 and r=0.66), percentage of morphologically normal spermatozoa (r=0.55 and r=0.59), the hypoosmotic swelling test (r=0.76 and r=0.68), and fluorescent staining (r=0.56 and r=0.59), respectively. In conclusion, 37 proteins were identified in seminal plasma; two were significantly correlated with semen characteristics.

No abstract

Bovine follicular fluid (FF) constitutes the microenvironment of follicles and includes various biologically active proteins. We performed a study involving 18 healthy nonlactating Holstein cows to determine the protein expression profile of FF at key stages of follicular development. Follicles were individually aspirated in vivo at predeviation (F1 ∼ 7.0 mm), deviation (F1 ∼ 8.5 mm), postdeviation (F1 ∼ 12.0 mm), and preovulatory stages of follicle development, which were confirmed by measurement of follicular estradiol and progesterone concentrations. The FFs from nine cows were selected for proteomic analysis. After albumin depletion, triplicates of pooled FF were reduced, alkylated, and digested with trypsin. The resulting peptides were labeled with TMTsixplex and quantified using liquid chromatography-mass spectrometry/mass spectrometry. A total of 143 proteins were identified and assigned to a variety of biological processes, including response to stimulus and metabolic processes. Twenty-two differentially (P < 0.05) expressed proteins were found between stages indicating intrafollicular changes over development, with expected deviation time critical to modulate the protein expression. For instance, high concentrations of follistatin, inhibin, serglycin, spondin-1, fibrinogen, and anti-testosterone antibody were found during early stages of follicular development. In contrast, apolipoprotein H, alpha-2-macroglobulin, plasminogen, antithrombin-III, and immunoglobulins were increased after deviation. Among the differentially abundant proteins, 19 were found to be associated with steroidogenesis. Pathway analysis identified proteins that were mainly associated with the acute phase response signaling, coagulation system, complement system, liver/retinoid X receptor activation, and biosynthesis of nitric oxide and reactive oxygen. The differentially expressed proteins provide insights into the size-dependent protein changes in the ovarian follicle microenvironment that could influence follicular function.

The objective of the present study was to describe the proteins from the seminal plasma of buffalo and correlate these proteins with sperm motility. Ejaculates from sixteen Murrah buffalo were used. Semen collection was performed by electroejaculation, and the ejaculate was evaluated by macroscopic (volume) and microscopic analysis (subjective motility and vigor, as well as sperm concentration). After the analysis, the samples were centrifuged (800g for 10 min and 10,000 for 30 min at 4 °C), and the supernatant (seminal plasma) was used to determine total protein concentration by the Bradford method. Based on total protein concentration, an aliquot (50 μg) was taken to conduct protein in-solution digestion for nano-LC-ESI-Q-TOF mass spectrometry analysis. Samples were divided into two groups, minimal (little sperm motility) and greater (typical sperm motility), based on non-hierarchical clustering considering motility and emPAI protein value. The data were analyzed by multivariate statistical analysis using principal component analysis (PCA) and partial analysis of minimum squares discrimination (PLS-DA). Forty-eight proteins were detected in the seminal plasma, and fifteen were common to two groups. There were six proteins that were significantly different between the groups. The main functions of proteins in seminal plasma were catalytic and binding activity. Spermadhesin protein, ribonuclease, 14-3-3 protein zeta/delta and acrosin inhibitor were in greater amounts in seminal plasma from the group with greater sperm motility; prosaposin and peptide YY were in greater amounts in the group with little sperm motility. The proteins detected in the greater motility group were correlated with sperm protection, including protection against oxidative stress, lipid peroxidation, protease inhibition and prevention of premature capacitation and acrosome reaction. In the group with little sperm motility, one of the identified proteins is considered to be an antifertility factor, whereas the function of other identified protein is not definitive. Results from the present study add to the knowledge base about the molecular processes related with sperm motility, and these findings can be used for determining potential markers of semen quality.