A BRIEF STUDY ON BOAR SEMEN CRYOPRESERVATION AND PROTEOMICS
Ningthoukhongjam Linda 1* and Fazal Ali Ahmed 1
1Department of Animal Reproduction, Gynaecology & Obstetrics, C. V. Sc. & A. H., Central Agricultural University (CAU), Selesih, Aizawl, Mizoram, India – 796014.
ABSTRACT:
Proteomics is the study of proteins on a large scale, including quantitative expression, post-translational modifications (PTMs), and protein interactions. PTMs are post-synthesis modifications to a protein’s structure and functionality that are important for sperm function and potential fertility. Several proteomic approaches have recently been used to identify the sperm and seminal plasma (SP) proteins that could be used as potential biomarkers for sperm function, including fertilisation ability. In this review a brief overview of the proteomic technologies and workflows that can be used for sperm and seminal plasma proteomic analysis will be discussed.
Keywords: Boar, proteomics, spermatozoa
*Corresponding author, Email- ningthoukhongjamlinda@gmail.com
INTRODUCTION:
A spermatozoon is capable of completing a series of sequential and essential processes that eventually result in a viable embryo is required for an effective fertilisation like sperm capacitation, hyperactivation, cumulus mass penetration, adhesion and penetration through the zona pellucida (ZP), sperm-oocyte membrane fusion, and successful formation of interacting pronuclei. Proteins that surround the sperm membrane and interact with membrane structural proteins undergo changes in expression and/or configuration during epididymal maturation and ejaculation. Because these changes are linked to fertility outcomes, proteomic analysis of seminal plasma (SP) and spermatozoa has emerged as a critical tool for identifying potential fertility biomarkers (Gadella and Luna, 2014). Several animal studies have shown that SP and/or sperm proteins influence the response of ejaculates to sperm biotechnologies, ranging from the most basic, such as conventional artificial insemination (AI) with spermatozoa subjected to long term and liquid storage, to more sophisticated technologies such as freezing and/or sex-sorting, thereby assisting in the identification of potential markers for sperm resilience. The current review summarises existing research on the protein composition of spermatozoa and SP in pigs, with an emphasis on the use of high throughput proteomics. The described results, including our own, are discussed in particular in relation to the potential use of specific proteins as tools for improving boar sperm preservation (Szklarczyk et al., 2017).
PROTEOMIC ANALYSIS OF BOAR SPERMATOZOA AND SEMINAL PLASMA:
The first step in a proteomic study is the separation of extracted proteins, which is a critical for evaluating complex protein mixtures like SP. This separation can be done at the protein or peptide levels. At the protein level, sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) has traditionally been used to separate proteins based on either molecular weight (one-dimensional electrophoresis; 1DE) or both isoelectric charge and molecular weight (two-dimensional electrophoresis; 2DE). 2DE is more efficient than 1DE for quantitative and qualitative protein studies on complex samples, and it is particularly useful for visualising sperm protein PTMs (Druart and de Graaf, 2018). After enzymatic protein digestion, a better alternative is to fragment proteins at the peptide level using liquid chromatography (LC).
When compared to gel-based methods, LC separates peptides based on specific characteristics and significantly increases the number of proteins identified. As a result, LC is currently the most useful method for separating samples with complex protein compositions, such as SP, where abundant proteins typically mask other less abundant proteins these less-abundant proteins are frequently the most important in biological processes.
WORKFLOW OF BOAR SEMEN PROTEOMICS:
One possible workflow entails 1DE or 2DE, protein excision and digestion from the gel, and protein identification via matrix-assisted laser/desorption ionization-MS (MALDI91 MS) or tandem MS (MS/MS). Another workflow option is to generate peptides using a combination of LC and tandem MS (LC-MS/MS). Because both the methods produce complementary results, their combination has been proposed as ideal for identifying differentially expressed proteins. The final and most important step in proteomic analysis is bioinformatics. The Dataset for Annotation, Visualization, and Integrated Discovery (DAVID), the Protein ANalysis Through Evolutionary Relationships database (PANTHER), the UniProt Knowledgebase (UniProt KB), Ensembl, and the National Center for Biotechnology Information, non – redundant database are among the most commonly used proteomics databases (NCBI-nr) (Selvam and Agarwal, 2018). These databases are constantly updated, but information about domestic animals like Sus scrofa is still quite limited. This information gap highlights the importance of maintaining databases in order to better disclose and manage proteomics derived data. The use of comparative proteomics has resulted in impressive studies that identify proteins involved in boar sperm capacitation as valuable predictive biomarkers of boar fertility (Perez et al., 2019).
PROTEOMICS AND BOAR SEMEN CRYOPRESERVATION:
Proteins are potentially important factors in sperm cryosurvival and have thus been investigated as potential biomarkers for freezability. Individual protein levels such as acrosin, fibronectin, heat shock protein HSP90AA1 and voltage-dependent anion channel 2 are positively correlated with sperm cryotolerance, whereas N-acetyl-hexosaminidase and triosephosphate isomerase are negatively correlated, adding to the list of potential freezability markers (Hezavehei et al., 2018). To optimise the freezing process, additional studies evaluating the impact of cryopreservation on the entire sperm proteome are required. The researchers identified a panel of 41 proteins in boar spermatozoa from the SRF with specific expression changes during cryopreservation using iTRAQ-coupled 2D LC-MS/MS. Spermatozoa recovered from the SRF are more resistant to cryopreservation than those exposed to the SP of the total ejaculate (Guimaraes et al., 2017).
CONCLUSION:
It is critical to expand our understanding of the molecular basis of sperm functional regulation in order to optimise sperm handling and maintain fertility. Some sperm and SP proteins can be used effectively as biomarkers of sperm performance, allowing for accurate prediction of male fertility and the development of new strategies to improve sperm preservation. However, before these findings can be applied in the field, a validation step is required to rigorously confirm that the identified proteins can be used as biomarkers in a reliable manner.
REFERENCES:
- Druart X and de Graaf S. 2018. Seminal plasma proteomes and sperm fertility. Anim Reprod Sci, 194:33-40.
- Gadella BM and Luna C. 2014. Cell biology and functional dynamics of the mammalian sperm surface. Theriogenology, 81:74-84
- Guimaraes DB, Barros TB, Van Tilburg MF, Martins JAM, Moura AA, Moreno FB, Monteiro-Moreira AC, Moreira RA, Toniolli R. 2017. Sperm membrane proteins associated with the boar semen cryopreservation. Anim Reprod Sci, 183:27-38.
- Hezavehei M, Sharafi M, Kouchesfahani HM, Henkel R, Agarwal A, Esmaeili V, Shahverdi A. Sperm cryopreservation: A review on current molecular cryobiology and 481 advanced approaches. 2018. Reprod Biomed Online, 37:327-339.
- Perez PC, Li J, Barranco I, Martinez EA, Rodriguez-Martinez H, Roca J, Parrilla I. 2019. The proteome of frozen-thawed pig spermatozoa is dependent on the ejaculate fraction source. Sci Reports, 24, 9:705.
- Selvam MKP and Agarwal A. 2018. Update on the proteomics of male infertility: A systematic review. Arab J Urology, 103-112.
- Szklarczyk D, Morris JH, Cook H, Kuhn M, Wyder S, Simonovic M, Santos A, Doncheva NT, Roth A, Bork P, Jensen LJ, von Mering C. The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible. 2017. Nucleic Acid Res, 45: 362-368.
