Alteration of the Metabolite Interconversion Enzyme in Sperm and Sertoli Cell of Non-Obstructive Azoospermia: A Microarray Data and In-Silico Analysis Publisher Pubmed



Hashemi Karoii D^{1, 2} ; Baghaei H³ ; Abroudi AS⁴ ; Djamali M⁵ ; Hasani Mahforoozmahalleh Z⁶ ; Azizi H² ; Skutella T⁷ Show Affiliations
Source: Scientific Reports Published:2024

Abstract

Numerous variables that regulate the metabolism of Sertoli cells and sperm have been identified, one of which is sex steroid hormones. These hormones play a vital role in maintaining energy homeostasis, influencing the overall metabolic balance of the human body. The proper functioning of the reproductive system is closely linked to energy status, as the reproductive axis responds to metabolic signals. The aim of this study was to investigate the gene expression patterns of metabolite interconversion enzymes in testicular cells (Sertoli cells and spermatogonia) of non-obstructive azoospermia (NOA) patients, as compared to normal controls, to understand the molecular mechanisms contributing to NOA. We used microarray and bioinformatics techniques to analyze 2912 genes encoding metabolite interconversion enzymes, including methyltransferase, monooxygenase, transmembrane reductase, and phosphohydrolase, in both testicular cells and normal samples. In sperm, the upregulation of MOXD1, ACAD10, PCYT1A, ARG1, METTL6, GPLD1, MAOA, and CYP46A1 was observed, while ENTPD2, CPT1C, ADC, and CYB5B were downregulated. Similarly, in the Sertoli cells of three NOA patients, RPIA, PIK3C3, LYPLA2, CA11, MBOAT7, and HDHD2 were upregulated, while NAA25, MAN2A1, CYB561, PNPLA5, RRM2, and other genes were downregulated. Using STRING and Cytoscape, we predicted the functional and molecular interactions of these proteins and identified key hub genes. Pathway enrichment analysis highlighted significant roles for G1/S-specific transcription, pyruvate metabolism, and citric acid metabolism in sperm, and the p53 signaling pathway and folate metabolism in Sertoli cells. Additionally, Weighted Gene Co-expression Network Analysis (WGCNA) and single-cell RNA sequencing (scRNA-seq) were performed to validate these findings, revealing significant alterations in gene expression and cellular distribution in NOA patients. Together, these results provide new insights into the molecular mechanisms underlying NOA and identify potential therapeutic targets. © The Author(s) 2024.