EXTRACELLULAR VESICLES IN FOLLICULAR FLUID OF SEXUALLY
MATURE GILTS’ OVARIAN ANTRAL FOLLICLES - IDENTIFICATION
AND PROTEOMIC ANALYSIS

Ovarian follicle development is coordinated by endocrine and intraovarian factors that regulate proliferation and differentiation of somatic cells (granulosa and theca) as well as oocyte growth and maturation (1). Importantly, an extensive cell-to-cell communication between different follicular cells, ensured by hormones, growth factors and biologically active molecules present in follicular fluid, is critical for the proper folliculogenesis and production of healthy oocytes (2).

Among factors secreted into follicular fluid, a population of nano-sized extracellular vesicles (EVs) has been recently found as a new mechanism of signaling within ovarian follicle in human and several animal species (3). EVs encompass different vesicle types, including exosomes (30 – 150 nm), microvesicles (150 nm – 1 µm) and apoptotic bodies (1 – 5 µm). Exosomes are the smallest population of EVs and originate from multivesicular bodies formed inside late endosomes, which are released into the extracellular space upon fusion with the cell membrane in the process of exocytosis (4). The growing interest in EVs arise from their important role in cell-to-cell communication by carrying a wide range of biomolecules (proteins, mRNA, microRNA, lipids) and transferring them to target cells (4).

By this time, EVs were isolated from follicular fluid of antral follicles of prepubertal gilts (5, 6), whereas no research was conducted on sexually mature pigs. Dynamics of follicular development in mature pigs is crucial due to the fact that different classes of antral follicles vary in cell proliferation and apoptosis, steroidogenesis and response to gonadotropins that determines successful ovulation (7). Thus, the extension of knowledge about molecular mechanism underlying follicle development in mature pigs seems to be reasonable. Since content of microRNAs in EVs derived from follicular fluid has been extensively discussed with regard to follicle growth and oocyte maturation (5, 6), there is little data providing a proteomic characterization of ovarian EVs. Therefore, the aim of the study was to identify and quantify EVs in follicular fluid of small, medium and large antral follicles of sexually mature gilts and conduct proteomic analysis of their cargo. The pig is an agriculturally important species, so understanding its follicular dynamics and accompanied proteomic events is critical to optimizing reproductive outcomes.

MATERIALS AND METHODS

Animals

Porcine ovaries were obtained from sexually mature cross-bred gilts (Large White × Polish Landrace; 90 – 100 kg body weight) at a local abattoir under veterinarian control, less than 20 min after slaughter. Stage of the estrous cycle was verified by ovarian and uterine morphology (8, 9). Immediately after the slaughter, ovaries in follicular phase were placed in phosphate-buffered saline (PBS, pH 7.4) supplemented with antibiotics (AAS, Sigma-Aldrich) and transported to the laboratory within ~1 hour.

Follicular fluid collection and extracellular vesicles isolation

Follicular fluid was collected with syringe from healthy porcine antral follicles: small (< 3 mm, SFs), medium (3 – 6.9 mm, MFs) and large (≥ 7 mm, LFs). Total number of follicles used in the present study was 150 per each class (SFs, MFs and LFs). Follicular fluid from 50 follicles of each class was pooled into one sample and used for a single EVs isolation. It was centrifuged at 2000 × g at 4ºC for 20 min and then at 12000 × g at 4ºC for 30 min, followed by filtration using 0.22-µm membrane to remove cells and debris. Next, exosomal fraction of EVs was isolated using a Total Exosome Isolation Reagent (Invitrogen, Carlsbad, CA, USA) according to manufacturer’s protocol and previous studies (5, 6). The pellets containing exosomal fraction were resuspended in 100 µl phosphate-buffered saline (PBS, pH 7.4) or RIPA buffer for further analyses. The experiment was performed three times for each analysis (n = 3).

Nanoparticle tracking analysis

To determine particle size and concentration, nanoparticle tracking analysis (NTA) was performed applying a Nanosight NS300 (Malvern Panalytical Ltd, Malvern, UK) outfitted with a LM14C laser. The Brownian movements of each particle present in the samples were visualized by a laser light scattering method (45 mW at 488 nm), recorded by a camera (sCMOSa) and converted into size and concentration parameters using the Stokes-Einstein equation (10). For each measurement, five 30-second videos were captured with a camera level of 16, shutter value 30/ms, at temperature 25ºC and syringe speed 10 µl/s. After capture, the videos were analyzed by the NanoSight Software NTA 3.3 Dev Build 3.3.104 with a detection threshold of 5. Each sample was diluted in PBS from 1:1000 to 1:10000 and analyzed three times to determine, in which dilution the concentration of particle is the most accurate. The final dilution chosen for NTA analysis was 1:10000 (11).

Western blot analysis

The abundance of CD9 and CD63 proteins (exosomal markers) (12) was determined by Western blot following protein extraction (10 µg protein per each sample) in RIPA buffer and electrophoresis in 12% SDS-PAGE (13). A primary mouse anti-CD9 (1:1000; cat no. AHS0902; lot no. 75131763A; Invitrogen) and mouse anti-CD63 (1:1000; cat no. 10628D; lot no. 00667939; Invitrogen) antibodies, and secondary horseradish peroxidase-conjugated anti-mouse IgG (1:10000; Jackson ImmunoResearch, Cambridge, UK) were used. Signals were detected using luminol reagent and visualized with ChemiDoc-It 410 Imaging System (UVP, Upland, CA, USA). Bands were densitometrically quantified and normalized to their corresponding β-actin bands. This semi-quantitative analysis was repeated three times.

Nano-liquid chromatography-matrix-assisted laser deposition/ionization time-of-flight mass spectrometry analysis and database search

EVs samples from MFs (chosen due to the highest particles concentration) were subjected to protein extraction and peptides digestion by trypsin as previously described (14, 15). Briefly, the chromatographic separation took place in a nano-flow system (EASY-nLC II, Bruker Daltonics) on a C18-reverse phase column with direct fraction collector (PROTEINEER fc II, Bruker Daltonics), and then fractions collected on MALDI type plates were subjected to analysis using a mass spectrometer type MALDI-TOF/TOF (ultrafleXtreme, Bruker Daltonics). Peptide identifications were performed with MASCOT server (v. 2.4.0, Matrix Science, London, UK) using mammalian database. The search included oxidation as a variable modification and carbidomethyl as a fixed modification. The threshold for detection was 100 ppm for peptide masses, and 0.7 Da for fragment ion masses. Individual peptide matches with scores higher than 30 that was determined based on the MASCOT result report for a peptide mass fingerprint search. Proteins identification was performed manually, based on two unique peptides with the probability less than 0.05. The protein classification was performed by means of a free algorithm applied in the PANTHER Classification System (v. 14.0, access data: 5 May, 2020) (16). This analysis was repeated three times.

Statistical analysis

Data were statistically analyzed by Statistica v.13.1 software (StatSoft Inc., Tulsa, OK, USA). To verify the normal distribution of data the Shapiro-Wilk and the Lilliefors tests were applied. Due to the lack of normality in results, the non-parametric Kruskal-Wallis test was applied and the differences between groups were determined by post hoc Dunn’s multiple comparison test (P < 0.05). All results were expressed as mean × standard error of the mean (SEM).

RESULTS

The current research revealed the presence of EVs in follicular fluid of all classes of porcine antral follicles harvested from sexually mature pigs that was shown by NTA (Fig. 1) and Western blot (Fig. 2) analyses. The highest (P = 0.0338) concentration of EVs was found in follicular fluid of MFs (7.03 ± 0.25 × 1012 particles/ml of follicular fluid), as compared to LFs (2.62 ± 0.14 × 1012 particles/ml of follicular fluid) and SFs (2.34 ± 0.16 × 1012 particles/ml of follicular fluid) (Fig. 1A).

Fig. 1. Extracellular vesicles (exosomal fraction) concentrations (A) and size distributions (B-D) in follicular fluid of (B) small (SFs; < 3 mm), (C) medium (MFs; 3 – 6.9 mm) and (D) large (LFs; ≥ 7 mm) antral follicles of sexually mature gilts measured by nanoparticle tracking analysis. The scatterplot represents concentration of particles expressed as × 1012 particles per ml of follicular fluid. Solid lines represent mean values. Different dot color reflects individual data point from three samples (A). Average size of particles shows mean of the triplicate measurement ± SEM expressed by red background (B-D). Dunn’s multiple comparison test (P < 0.05). n = 3 per each group.

In follicular fluid of all examined follicle classes, NTA analysis showed the existence of the population of EVs that resembles exosomes. In SFs, EVs size distribution ranged from 69 to 418 nm with a mean 101.8 ± 3.2 nm (Fig. 2B). In MFs, particles sized from 99 to 545 nm with a mean 122.6 ± 2.9 nm (Fig. 2C). In LFs, EVs size distribution ranged from 81 to 439 nm with a mean 110 ± 6.8 nm (Fig. 2D).

The presence of exosome-like vesicles in follicular fluid of porcine SFs, MFs and LFs was confirmed by Western blot analysis of tetraspanins CD9 and CD63 (Fig. 2). CD9 and CD63 proteins were found in all analyzed follicles (Fig. 2A). The abundance of CD9 protein was higher in SFs and MFs than in LFs (P = 0.0338), whereas the greatest CD63 protein abundance was found in MFs (P = 0.0412) (Fig. 2B).

Fig. 2. Relative expression of CD9 and CD63 proteins in extracellular vesicles (exosomal fraction) isolated from follicular fluid of small (SFs; < 3 mm), medium (MFs; 3 – 6.9 mm) and large (LFs; ≥ 7 mm) porcine antral follicles of sexually mature gilts using Western blot analysis. Representative Western blots are shown (A). The scatterplot represents relative expression of each protein evaluated with densitometry and expressed as the ratio relative to β-actin (B). Solid lines represent mean values. Different letter superscripts indicate statistical differences between groups (lowercases for CD9; uppercases for CD63). Dunn's multiple comparison test (P < 0.05). n = 3 per each group.

In EVs from MFs, the nano-LC-MALDI-TOF/TOF MS analysis allows to identify 249 proteins. They were analyzed by PANTHER classification system and classified into three categories (‘protein class’, ‘cellular component’ and ‘molecular function’) (Fig. 3A-3C). The largest classes of proteins were formed by enzymes converting metabolites and modifying proteins, as well as transporter proteins. Furthermore, nucleic acid binding proteins, protein-binding activity modulators, gene-specific transcriptional regulators, extracellular matrix (ECM) and cytoskeletal proteins were also abundant (Fig. 3A). Based on cellular component classification, most of the proteins were predicted to be localized in cell cytoplasm and built organelle (Fig. 3B). Regarding molecular function, the most abundant groups of proteins were predicted to be associated with binding and catalytic activity (Fig. 3C).

Fig. 3. Functional annotations of proteins identified by nano-liquid chromatography-matrix-assisted laser deposition/ionization time-of-flight mass spectrometry in extracellular vesicles (exosomal fraction) isolated from medium antral follicles of sexually mature gilts. The proteins were classified into ‘protein class’, ‘cellular component’ and ‘molecular function’ categories following PANTHER classification system.

To better understand, in which processes within porcine ovarian follicle the identified proteins are involved in, they were additionally analyzed by PANTHER classification system and categorized into ‘signaling pathway’. Categories with the highest number of annotated proteins included integrin signaling pathway, inflammation mediated by chemokine and cytokine signaling pathway, Wnt signaling pathway and blood coagulation (Table 1).

Table 1. Functional annotations of proteins identified by nano-liquid chromatography-matrix-assisted laser deposition/ionization time-of-flight mass spectrometry in extracellular vesicles (exosomal fraction) isolated from medium antral follicles of sexually mature gilts. The proteins were categorized into ‘signaling pathway’ following PANTHER classification system. Representative signaling pathways involving predominant abundance of proteins and respective proteins are presented.

DISCUSSION

Dynamics of antral follicle development in mature pigs involves cycling recruitment occurring under the control of follicle-stimulating hormone as well as selection and domination depending on intrafollicular estradiol production. These processes are critical and define the number of ovulatory follicles (17). It is worth notice, that recent studies reported a novel mechanism influencing follicle development and function through EVs (3). By this time, the presence of EVs was shown in human (18), equine (19), bovine (20) and porcine (5, 6) ovarian follicular fluid. However in pigs, EVs were isolated only form follicles of prepubertal gilts (5, 6), while no research was conducted on mature ones. Therefore, our present study is the first one demonstrating EVs existence in developing antral follicles (SFs, MFs and LFs) of sexually mature gilts. Applying NTA and Western blot analyses, the population of exosome-like particles was observed in all examined classes of follicles, whereas their greatest concentration was found in MFs. Follicle size-dependent changes in the number of EVs was also found in cows, in which the particle concentration decreased with the follicle growth (20). Furthermore, Navakanitworakul et al. (20) suggested the correlation between intrafollicular estradiol and EVs levels. In pigs, the greatest concentration of estradiol was observed in follicular fluid of MFs in comparison to SFs and LFs (21), that might be an explanation of findings presented herein. Thus, our results demonstrating the variable amount of EVs in follicular fluid of SFs, MFs and LFs indicate the relationship between EVs and processes taking place at different developmental stages of antral follicles in sexually mature gilts.

It is known that EVs regulate follicle development and oocyte maturation via transferred biomolecules such as microRNAs and proteins. Most of previous studies pointed to the role of miRNAs transported via EVs in ovarian follicles. In mare granulosa cells, the members of transforming growth factor (TGF)-β family, which are involved in follicle maturation, have been shown as microRNAs target genes (22). Furthermore, microRNAs of exosomes isolated from bovine small antral follicles (11) and antral follicles of prepubertal gilts (6) stimulate granulosa cell proliferation by Src kinase, mitogen-activated protein kinase (MAPK) and phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K) pathways. Referring to oocyte maturation, differentially expressed exosomal microRNAs have been found in ovaries of young and old mares that are a model to study age-related decline in oocyte quality (19). These molecules also induced critical for ovulation cumulus expansion in cattle (23), but not in pigs (5). On the contrary, there has been few reports about protein cargo of follicular EVs suggesting their involvement in physiological and pathological processes within the ovary (19, 24). To our knowledge, the current study is the first one demonstrating proteomic analysis of EVs from antral follicles of mature gilts.

Herein, in follicular fluid derived EVs we have identified proteins predominantly responsible for metabolite conversion, protein modification and transport following ‘protein class’ annotation. That was confirmed by ‘molecular function’ analysis, which showed that many of identified proteins were associated with binding function and catalytic activity. Most of them belong also to the group of cytoskeleton and ECM indicating their role in the building of cell components (‘cellular component’ annotation). That is consistent with prior study identifying membranous and cytosolic proteins in EVs isolated from follicular fluid of healthy mare follicles (19).

Development of ovarian follicle is accompanied with cell proliferation, differentiation, survival and proper steroidogenesis (7). It was shown that these processes are influenced by ECM proteins. Furthermore, the composition of ECM changes significantly during follicle growth and development as well as atresia and follicle rupture (25). In the present study, the ECM proteins such as laminin, collagen and fibronectin have been identified in EVs and predicted to be involved in predominant signaling pathway (integrin signaling pathway). Therefore, EVs might regulate porcine antral follicle development through intracellular pathways involving the ECM proteins.

The primary function of the ovary is to produce and release mature oocyte, which might undergo fertilization and further development supporting by uterine derived molecules (26). That is composed of a series of events including oocyte maturation and follicle rupture (27). The last process mainly depends on the degradation of ECM substances by proteolytic enzymes such as collagenase. According to one hypothesis, collagenase is activated by plasmin formed with plasminogen (28). Herein, plasminogen has been identified in follicular fluid derived EVs (categorized into ‘plasminogen activating cascade’ and ‘blood coagulation’ signaling pathways) suggesting their contribution to disruption of the follicle during ovulation in pigs.

Postovulatory follicle undergoes structural and functional changes resulted in corpus luteum formation that is accompanied with angiogenesis and blood vessel degradation (29). Following functional annotation of identified proteins, we have found angiogenesis as one of the predominant signaling pathway with categorized adenomatous polyposis coli protein. Recent study reported that mice with knockout of gene coding that protein performed reduced rate of ovulation and corpora lutea formation as well as impaired angiogenesis (30). Furthermore, we have also assigned adenomatous polyposis coli protein into Wnt signaling pathway that is well known regulator of ovarian function related to follicle development, corpus luteum formation, steroid production and fertility (31). Our current findings support the notion that EVs protein cargo plays crucial role in antral follicle development in mature gilts, including further corpus luteum formation.

We also demonstrated that identified proteins were associated with the process of inflammation mediated by chemokine and cytokine, and apoptosis. Transcription factor RelB was classified for both of these signaling pathways. It is a component of the non-canonical nuclear factor kappa B (NF-κB) signaling pathway important in ovarian tumorigenesis (32) and ovarian aging by inactivation of many transcription factors in cooperation with sirtuins (33). The activation of NF-κB signaling pathway through proteins identified in follicular fluid derived exosomes contributing to inflammation was also observed in women with polycystic ovary syndrome (24). It should be stressed that apart from ovarian pathologies, inflammation and apoptosis occur under physiological conditions such as ovulation and atresia (26, 27) that further confirmed proposed role of EVs proteins in follicle development and function in mature gilts.

The current study shows for the first time that EVs are present in follicular fluid of antral follicles obtained from sexually mature gilts and their concentration varies upon follicle developmental stage. Additionally, by means of the nano-LC-MALDI-TOF/TOF MS with functional analysis we identified 249 proteins as EVs cargo. Most of them are predicted to be associated with processes crucial for follicle development and function providing new directions for future analysis.

Acknowledgements: The nano-LC-MALDI-TOF/TOF MS analysis was performed in the Laboratory of Proteomics and Mass Spectrometry PAS, Cracow, Poland. The study was supported by a subvention N18/DBS/000006.

Conflict of interests: None declared.

REFERENCES

1. Thomas FH, Vanderhyden BC. Oocyte-granulosa cell interactions during mouse follicular development: regulation of kit ligand expression and its role in oocyte growth. Reprod Biol Endocrinol 2006; 4: 19. doi: 10.1186/1477-7827-4-19
2. Basuino L, Silveira CF. Human follicular fluid and effects on reproduction. JBRA Assist Reprod 2016; 20: 38-40.
3. Di Pietro C. Exosome-mediated communication in the ovarian follicle. J Assist Reprod Genet 2016; 33: 303-311.
4. Gyorgy B, Szabo TG, Pasztoi M, et al. Membrane vesicles, current state-of-the-art: emerging role of extracellular vesicles. Cell Mol Life Sci 2011; 68: 2667-2688.
5. Matsuno Y, Onuma A, Fujioka YA, et al. Effects of exosome-like vesicles on cumulus expansion in pigs in vitro. J Reprod Dev 2017; 63: 51-58.
6. Matsuno Y, Kanke T, Maruyama N, Fujii W, Naito K, Sugiura K. Characterization of mRNA profiles of the exosome-like vesicles in porcine follicular fluid. PLoS One 2019; 14(6): e0217760. doi: 10.1371/journal.pone.0217760.
7. LaVoie HA. Transcriptional control of genes mediating ovarian follicular growth, differentiation, and steroidogenesis in pigs. Mol Reprod Dev 2017; 84: 788-801.
8. Akins EL, Morrisette MC. Gross ovarian changes during estrus cycle of swine. Am J Vet Res 1968; 29: 1953-1957.
9. Leiser R, Zimmermann W, Sidler X, Christen A. Normal cyclical morphology of the endometrium and ovary of swine. Tierarztl Prax 1988; 16: 261-280.
10. Bachurski D, Schuldner M, Nguyen PH, et al. Extracellular vesicle measurements with nanoparticle tracking analysis - an accuracy and repeatability comparison between NanoSight NS300 and ZetaView. J Extracell Vesicles 2019; 8: 1596016. doi: 10.1080/20013078.2019.1596016
11. Hung WT, Navakanitworakul R, Khan T, et al. Stage-specific follicular extracellular vesicle uptake and regulation of bovine granulosa cell proliferation. Biol Reprod 2017; 97: 644-655.
12. Jamaludin NA, Thurston LM, Witek KJ, et al. Efficient isolation, biophysical characterisation and molecular composition of extracellular vesicles secreted by primary and immortalised cells of reproductive origin. Theriogenology 2019; 135: 121-137.
13. Grzesiak M, Knapczyk-Stwora K, Slomczynska M. Induction of autophagy in the porcine corpus luteum of pregnancy following anti-androgen treatment. J Physiol Pharmacol 2016; 67: 933-942.
14. Kasprzyk J, Stepien E, Piekoszewski W. Application of nano-LC-MALDI-TOF/TOF-MS for proteomic analysis of microvesicles. Clin Biochem 2017; 50: 241-243.
15. Gromotowicz-Poplawska A, Kasprzyk J, Marcinczyk N, Stepien E, Piekoszewski W, Chabielska E. The proteome analysis of rat platelet with nano-liquid chromatography-matrix-assisted laser desorption/ionization time-of-flight mass spectrometry technique. J Physiol Pharmacol 2018; 69: 963-968.
16. Mi H, Muruganujan A, Huang X, et al. Protocol Update for large-scale genome and gene function analysis with the PANTHER classification system (v.14.0). Nat Protoc 2019; 14: 703-721.
17. Knox RV. Recruitment and selection of ovarian follicles for determination of ovulation rate in the pig. Domest Anim Endocrinol 2005; 29: 385-397.
18. Santonocito M, Vento M, Guglielmino MR, et al. Molecular characterization of exosomes and their microRNA cargo in human follicular fluid: bioinformatic analysis reveals that exosomal microRNAs control pathways involved in follicular maturation. Fertil Steril 2014; 102: 1751-1761.
19. da Silveira JC, Veeramachaneni DN, Winger QA, Carnevale EM, Bouma GJ. Cell-secreted vesicles in equine ovarian follicular fluid contain miRNAs and proteins: a possible new form of cell communication within the ovarian follicle. Biol Reprod 2012; 86: 71. doi: 10.1095/biolreprod.111.093252
20. Navakanitworakul R, Hung WT, Gunewardena S, Davis JS, Chotigeat W, Christenson LK. Characterization and small RNA content of extracellular vesicles in follicular fluid of developing bovine antral follicles. Sci Rep 2016; 6: 25486. doi: 10.1038/srep25486
21. Liu J, Koenigsfeld AT, Cantley TC, Boyd CK, Kobayashi Y, Lucy MC. Growth and the initiation of steroidogenesis in porcine follicles are associated with unique patterns of gene expression for individual components of the ovarian insulin-like growth factor system. Biol Reprod 2000; 63: 942-952.
22. da Silveira JC, Carnevale EM, Winger QA. Bouma GJ. Regulation of ACVR1 and ID2 by cell-secreted exosomes during follicle maturation in the mare. Reprod Biol Endocrinol 2014; 12: 44. doi: 10.1186/1477-7827-12-44
23. Hung WT, Hong X, Christenson LK, McGinnis LK. Extracellular vesicles from bovine follicular fluid support cumulus expansion. Biol Reprod 2015; 93: 117. doi: 10.1095/biolreprod.115.132977
24. Li H, Huang X, Chang X, et al. S100-A9 protein in exosomes derived from follicular fluid promotes inflammation via activation of NF-κB pathway in polycystic ovary syndrome. J Cell Mol Med 2020; 24: 114-125.
25. Dziekonski M, Zmijewska A, Czelejewska W, Wojtacha P, Okrasa S. The effect of selective agonists of opioid receptors on in vitro secretion of steroid hormones by porcine endometrium during the estrous cycle and early pregnancy. J Physiol Parmacol 2018; 69: 727-735.
26. Woodruff TK, Shea LD. The role of the extracellular matrix in ovarian follicle development. Reprod Sci 2007; 14 (Suppl. 8): 6-10.
27. Russell DL, Robker RL. Molecular mechanisms of ovulation: coordination through the cumulus complex. Hum Reprod Update 2007; 13: 289-312.
28. Liu Y. Plasminogen activator/plasminogen activator inhibitors in ovarian physiology. Front Biosci 2004; 9: 3356-3373.
29. Lu E, Li C, Wang J, Zhang C. Inflammation and angiogenesis in the corpus luteum. J Obstet Gynaecol Res 2019; 45: 1967-1974.
30. Mohamed NE, Hay T, Reed KR, Smalley MJ, Clarke AR. APC2 is critical for ovarian WNT signalling control, fertility and tumour suppression. BMC Cancer 2019; 19: 677. doi: 10.1186/s12885-019-5867-y
31. Hernandez Gifford JA. The role of WNT signaling in adult ovarian folliculogenesis. Reproduction 2015; 150: R137-R148.
32. House CD, Jordan E, Hernandez L, et al. NFκB promotes ovarian tumorigenesis via classical pathways that support proliferative cancer cells and alternative pathways that support ALDH+ cancer stem-like cells. Cancer Res 2017; 77: 6927-6940.
33. Gorczyca G, Wartalski K, Tabarowski Z, Duda M. Effects of vinclozolin exposure on the expression and activity of SIRT1 and SIRT6 in the porcine ovary. J Physiol Pharmacol 2019; 70: 153-165.