A brief evaluation of the concepts of omics, genomics, proteomics and metabolomics in terms of sperm cell

The ability to live things to transfer their genetic heritage to future generations in a healthy way forms the basis of the science of reproduction. In this sense, understanding the structure and functions of the sperm cell, which is one of the sexual cells, is one of the important issues that should be emphasized. Methods such as omics, genomics, proteomics, and metabolomics, which have been found in research in recent years, are also used to evaluate the functions of the sperm cell.

Omics aims to perform structural and functional analyses on the sperm cell model as a biological component, including molecular gene level (genomics), transcript level (transcriptomics), protein level (proteomics), and metabolite level (metabolomics) [1].

Omics studies have many application areas and potentials today and since more than one molecule can be studied at the same time, it paves the way for the discovery of new biomarkers [2].

Genomics enables the identification of all functional genomes and genes present in all living organisms, the interaction of genes with each other and with the environment, as well as the determination of their activation in time, place and amount [3].

Genomics allows comparing the genetic information of different organisms or evaluating the genes of a cell or tissue. Genomic studies are divided into two different groups, structural and functional genomics, according to their fields. Structural genomics includes the study of genome mapping and DNA sequencing by showing the locations of genes on chromosomes. Apart from understanding the functions of genes, functional genomics is concerned with the study of gene expression, the study of genes at the genome level, and helping to make sense of the organism [4].

The proteome is all protein encoded by the genome that is present or expressed in a living thing [5]. Proteomics examines the amount of proteome, its functions, and the mechanism of interaction with other proteins and macromolecules. Together, the genome and proteome allow us to obtain a complementary information set [3].

Using transcriptomic analyses, researchers can characterize transcriptional activity (coding and noncoding), focus on a subset of target genes and their associated transcripts, or profile thousands of genes simultaneously to build an overall picture of cell function. The purpose of the transcriptomic analysis is to gain insight into gene expression that influences certain phenotypic characteristics of an individual. Sperm transcriptional activity occurs in the phase of spermiogenesis until round spermatozoa are formed. The gene expression process begins with the transcription of the genetic information stored in DNA molecules and then produces three types of RNA molecules: messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA) [6].

Whole transcriptome analyses have determined that a large portion of the living genome also transcribes non-protein-coding transcripts, including lncRNAs (long non-coding RNAs), miRNAs (microRNAs) and circRNAs (circular RNAs) [7].

In contrast to the use of transcriptomics, the preference for proteomics in spermatozoon biology plays a unique and arguably very important role not found in any other cell type. Therefore, the sperm cell is an excellent material for proteomic analysis [8].

Metabolomics is the determination of low molecular weight metabolites from metabolism products (in physiological fluids; carbohydrates, vitamins, hormones, etc.). Metabolic evaluation of body fluids is important and has a wide range of applications [9].

Single-cell multi-omics studies

Advances in experimental technologies and data methods related to single-cell multi-omics analysis reveal that molecules that play a role in the pathogenesis of diseases are of critical importance. The dynamic process of pathogenesis is associated with molecular mechanisms at the single-cell level, as well as multiple collective omics data. These molecular mechanisms may have potential strategies for the diagnosis and treatment of diseases [10-14].

Biomarkers

Biomarkers are used to have an idea about the healthy or diseased cells, tissues, or general state of the organism. Today, biomarkers are mostly genes, proteins, metabolites, glycans and other molecular factors that can be used for disease diagnosis, prognosis, prediction of therapeutic responses, and therapeutic development [15-18].

Sperm omics

Biochemical studies called the omics revolution have also included spermatology. Omics studies include studies such as genomics, proteomics, and metabolomics, and also help to determine the effects of the presence of other metabolites and changes among themselves on the cell. Studies such as molecular and cell biology, proteomics, and genomics are beneficial in protecting and controlling the reproduction of animals and endangered creatures [1].

With the initiation of omics studies, genomics, trans-criptomics, proteomics, and metabolomics play an important role in the recognition and identification of the causes involved in the pathogenesis of male infertility [1].

Certain biomarkers that have historically been used to determine the etiology of the causes of male infertility have led to the discovery of markers that are easy to use, cost-effective, and can determine fertility outcomes. Following the mapping of the human genome, studies in the field of genetic medicine have increased with treatment modalities tailored to the specific genetic makeup of a patient. Genomic studies such as epigenetics, metabolomics, and proteomics offer hope for the intended diagnosis of male infertility [19].

Sperm genomics and proteomics

Genomic studies and mapping methods are useful methods for finding diseases or disorders transmitted by genes. It has an important place in the regulation of the cloned parts by enabling the determination of the genes that make up the DNA [3].

Identification of biomarkers of semen and various biological fluids with proteomic and genomic studies is important for fertility prediction. Studies on these biomarkers in terms of fertility are expressed to be effective in increasing the insemination ability of male animals, pregnancy rates of female animals, and offspring intake [20].

Spermatozoa can be analyzed by evaluating processes such as epididymal maturation, capacitation, acrosome reaction, and fertilization. Proteomic studies are emerging methods to determine male fertility and semen defect rates [21].

In one study, the concentration of major seminal plasma proteins, which function as surface proteins in spermatozoa, was determined in adult bull semen. In addition, increased proteins in young bull spermatozoa are considered to be associated with cell development [22].

Sperm metabolomics

It has been shown that sperm metabolites can directly or indirectly control signaling pathways such as signaling related to sperm motility, hyperactivation, and energy acquisition [23].

In recent years, spermatozoa and seminal plasma meta-bolomics have been used to identify biomarkers, mostly in humans [3] and also in bulls [20].

While studies of proteomic and metabolomic markers of sperm and semen remain a minimally invasive marker for diagnosing infertility phenotypes, the application of these studies in the field is limited due to the wide range of proteins and peptides, and because they are metabolites found in semen that can be affected by various environmental factors that may occur due to individual diversity. Much more work needs to be done before these markers can be applied [19].

Proteomic information has an important place in genetic, genomic, transcriptomic and metabolomic databases and there is still a long way to go in proteomic sperm cell studies.

Applied to semen cell research, proteomics has led to the creation of variants of thousands of proteins so far found in the testicles and testicles [24]. In addition, as a result of extensive research, the epigenetic material in the male gamete was better understood when genomic and proteomic analyzes of sperm chromatin were performed [25].

Omics-based applications combined with computational and bioinformatic methods play an important role in terms of biomarkers and are widely used to facilitate diagnostic and therapeutic developments in many diseases, especially cancers [18].

- On the other hand, in recent years, an approach has been developed regarding omics data by making use of artificial intelligence, which is a current field; AI-based models, methods, and software for processing, analysis, visualization, and interpretation of Omics data;

- AI-based algorithms for analysis of clinical and health data;

- AI-based platforms to improve disease diagnosis and patient care;

- AI-based approaches for protein structure prediction, gene function prediction, and drug discovery [26].

The determination of unwanted genetic defects or various biomarkers by proteomic and genomic studies after the examinations to be made with the samples taken will constitute an important place for fertility prediction.

As a result, we can provide the opportunity to obtain the desired fertility much better by avoiding the directions from the past.

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