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Wan-Sheng Liu, Yaqi Zhao, Chen Lu, Gang Ning, Yun Ma, Francisco Diaz and Michael O'Connor

Preferentially expressed antigen in melanoma (PRAME) is a cancer/testis antigen that is predominantly expressed in normal testicular tissues and a variety of tumors. The function of the PRAME family in spermatogenesis remains unknown. This study was designed to characterize the Y-linked PRAME (PRAMEY) protein during spermatogenesis in cattle. We found that PRAMEY is a novel male germ cell-specific, and a germinal granule-associated protein that is expressed in spermatogenic cells during spermatogenesis. The intact PRAMEY protein (58 kDa) was detected in different ages of testes but not in epididymal spermatozoa. A PRAMEY isoform (30 kDa) was highly expressed only in testes after puberty and in epididymal spermatozoa. This isoform interacts with PP1γ2 and is likely the mature protein present in the testes and sperm. Immunofluorescent staining demonstrated that PRAMEY was located predominantly in the acrosome granule of spermatids, and in acrosome and flagellum of spermatozoa. Immunogold electron microscopy further localized the PRAMEY protein complex to the nucleus and several cytoplasmic organelles, including the rough endoplasmic reticulum, some small vesicles, the intermitochondrial cement, the chromatoid body and the centrioles, in spermatogonia, spermatocytes, spermatids and/or spermatozoa. PRAMEY was highly enriched in and structurally associated with the matrix of the acrosomal granule (AG) in round spermatids, and migrated with the expansion of the AG during acrosomal biogenesis. While the function of PRAMEY remains unclear during spermatogenesis, our results suggest that PRAMEY may play an essential role in acrosome biogenesis and spermatogenesis.

Free Chinese abstract: A Chinese translation of this abstract is freely available at http://www.reproduction-online.org/content/153/6/847/suppl/DC2

Spanish abstract: A Spanish translation of this abstract is freely available at http://www.reproduction-online.org/content/153/6/847/suppl/DC3

Free access

Zi-gang Shen, Wei He, Ji Zhang, Hai-yang He, Xia Yang, Zheng-qiong Chen, Ping Yang, Jian Li, Zhi-qing Liang, Yu-zhang Wu and Jin-tao Li

SPINLW1 (previously known as eppin (epididymal protease inhibitor)) is a target under intense scrutiny in the study of male contraceptive vaccines. B-cell-dominant epitopes are now recognized as key parts of the induction of humoral immune responses against target antigens. The generation of robust humoral responses in vivo has become a crucial problem in the development of modern vaccines. In this study, we developed a completely novel B-cell-dominant-epitope-based mimovirus vaccine, which is a kind of virus-size particulate antigen delivery system. The mimovirus successfully self-assembled from a cationic peptide containing a cell-penetrating peptide of TAT49–57 and a plasmid DNA encoding both three SPINLW1 (103–115) copies and adjuvant C3d3. The male mice were immunized with the epitope-based mimovirus vaccine, which resulted in a gradual elevation of specific serum IgG antibody levels. These reached a peak at week 4. Mating for the fertility assay showed that the mimovirus vaccine had accomplished a moderate fertility inhibition effect and investigation into the mechanism of action showed that it did so by interfering with the reproductive function of the sperm but that it did not damage the structures of the testes or cause serum testosterone to decline. Our results suggest an ideal protocol for suppressing fertility in mice by an engineered mimovirus vaccine.

Free access

Rui-Song Ye, Meng Li, Chao-Yun Li, Qi-En Qi, Ting Chen, Xiao Cheng, Song-Bo Wang, Gang Shu, Li-Na Wang, Xiao-Tong Zhu, Qing-Yan Jiang, Qian-Yun Xi and Yong-Liang Zhang

FSH plays an essential role in processes involved in human reproduction, including spermatogenesis and the ovarian cycle. While the transcriptional regulatory mechanisms underlying its synthesis and secretion have been extensively studied, little is known about its posttranscriptional regulation. A bioinformatics analysis from our group indicated that a microRNA (miRNA; miR-361-3p) could regulate FSH secretion by potentially targeting the FSHB subunit. Herein, we sought to confirm these findings by investigating the miR-361-3p-mediated regulation of FSH production in primary pig anterior pituitary cells. Gonadotropin-releasing hormone (GnRH) treatment resulted in an increase in FSHB synthesis at both the mRNA, protein/hormone level, along with a significant decrease in miR-361-3p and its precursor (pre-miR-361) levels in time- and dose-dependent manner. Using the Dual-Luciferase Assay, we confirmed that miR-361-3p directly targets FSHB. Additionally, overexpression of miR-361-3p using mimics significantly decreased the FSHB production at both the mRNA and protein levels, with a reduction in both protein synthesis and secretion. Conversely, both synthesis and secretion were significantly increased following miR-361-3p blockade. To confirm that miR-361-3p targets FSHB, we designed FSH-targeted siRNAs, and co-transfected anterior pituitary cells with both the siRNA and miR-361-3p inhibitors. Our results indicated that the siRNA blocked the miR-361-3p inhibitor-mediated upregulation of FSH, while no significant effect on non-target expression. Taken together, our results demonstrate that miR-361-3p negatively regulates FSH synthesis and secretion by targeting FSHB, which provides more functional evidence that a miRNA is involved in the direct regulation of FSH.

Open access

Renjie Wang, Wei Pan, Lei Jin, Yuehan Li, Yudi Geng, Chun Gao, Gang Chen, Hui Wang, Ding Ma and Shujie Liao

Artificial intelligence (AI) has experienced rapid growth over the past few years, moving from the experimental to the implementation phase in various fields, including medicine. Advances in learning algorithms and theories, the availability of large datasets and improvements in computing power have contributed to breakthroughs in current AI applications. Machine learning (ML), a subset of AI, allows computers to detect patterns from large complex datasets automatically and uses these patterns to make predictions. AI is proving to be increasingly applicable to healthcare, and multiple machine learning techniques have been used to improve the performance of assisted reproductive technology (ART). Despite various challenges, the integration of AI and reproductive medicine is bound to give an essential direction to medical development in the future. In this review, we discuss the basic aspects of AI and machine learning, and we address the applications, potential limitations and challenges of AI. We also highlight the prospects and future directions in the context of reproductive medicine.