Introduction
Annually, non-communicable diseases (NCDs) account for 41 million deaths, with 5 million attributable to diabetes, stroke, coronary heart disease and cancer (Das Reference Das2022). The majority of patients afflicted with and succumbing to NCDs are overweight (Peng et al. Reference Peng, Chen, Chen, Ma, Wang, Sun, Wang, Ding and Wang2024). Since 1990, global adult obesity rates have more than doubled, and adolescent obesity rates have tripled (Collaboration & N. C. D. Risk Factor, 2024; Peng et al. Reference Peng, Chen, Chen, Ma, Wang, Sun, Wang, Ding and Wang2024). In 2022, one in eight individuals worldwide was classified as obese, and 2.5 billion adults were overweight, with 890 million meeting the criteria for obesity (Collaboration & N. C. D. Risk Factor, 2024; Peng et al. Reference Peng, Chen, Chen, Ma, Wang, Sun, Wang, Ding and Wang2024). Furthermore, 37 million children under the age of 5 were overweight, while over 390 million children and adolescents aged 5–19 were overweight. Projections based on current trends indicate that by 2035, more than 750 million adolescents will be affected by overweight or obesity (Collaboration & N. C. D. Risk Factor, 2024; Peng et al. Reference Peng, Chen, Chen, Ma, Wang, Sun, Wang, Ding and Wang2024).
Obesity is closely associated with a wide range of diseases (Bluher Reference Bluher2019). The most common related diseases include endocrine diseases, cardiovascular diseases, angina, myocardial infarction, heart failure, arrhythmias, cerebral infarction, deep vein thrombosis, pulmonary embolism, digestive system diseases, infectious diseases, musculoskeletal diseases, respiratory diseases, malignant diseases, skin diseases, haematologic diseases, genitourinary system diseases and neurological diseases (Bluher Reference Bluher2019; Shaikh et al. Reference Shaikh, Beck, Alwarawrah and MacIver2024). With the increasing prevalence of obesity, there is a growing concern about its impact on reproductive health (Cao et al. Reference Cao, Zhang, Qi, Zhang, Ding, Meng, Zhao, Luo, Shen, Duan, Qin, Ye, Liu and Qu2024; Meng et al. Reference Meng, He, Cao, Zhang, Qi, Luo, Shen, Zhao, Xue, Qu and Liu2024; Lainez and Coss Reference Lainez and Coss2019). Research indicates that obesity can lead to reproductive dysfunction in men and may also adversely affect the health of subsequent generations (Wei et al. Reference Wei, Luo, Zhang, Li and Zhao2023; Carrageta et al. Reference Carrageta, Pereira, Ferreira, Monteiro, Oliveira and Alves2024).
Obesity affects endocrine hormones and reproductive organs, promotes chronic inflammation and oxidative stress, and leads to epigenetic changes in reproductive cells (Lainez and Coss Reference Lainez and Coss2019). Studies have demonstrated that obesity directly or indirectly results in decreased testosterone levels, impaired spermatogenesis, sexual dysfunction and an increased risk of reproductive-related diseases (Carrageta et al. Reference Carrageta, Pereira, Ferreira, Monteiro, Oliveira and Alves2024; Fui, Dupuis, and Grossmann Reference Fui, Dupuis and Grossmann2014). It induces both systemic and localized inflammation in the reproductive organs, thereby reducing sperm quality and significantly impacting the reproductive health of men of reproductive age. The related effects and mechanisms of obesity on male reproductive function are not yet fully understood (Carrageta et al. Reference Carrageta, Pereira, Ferreira, Monteiro, Oliveira and Alves2024; Fui, Dupuis, and Grossmann Reference Fui, Dupuis and Grossmann2014). Current research on obesity and reproduction primarily involves experimental animals such as mice. However, significant metabolic and immunological differences between mice and humans pose challenges for understanding obesity-related diseases that prominently involve metabolic and immune changes (Qu et al. Reference Qu, Rom, Li, Jia, Gao, Liu, Ding, Zhao, Wang, Chen, Xiong, Zhao, Xue, Zhao, Chu, Wen, Finney, Zheng, Cao, Zhao, Bai, Zhao, Sun, Zeng, Lin, Liu, Zheng, Zhang, Liu and Chen2023). This study includes mice, non-human primates and humans as research subjects. Through comparative analysis of single-cell sequencing data from testicular transcriptome datasets, the study aims to identify key genes responsible for obesity-induced damage to male reproductive function.
Material and methods
Animals
Male C57BL/6 mice were procured from the Laboratory Animal Centre of Xi’an Jiaotong University Health Science Centre (Xi’an, China). The mice were housed under a 12-hour light/12-hour dark cycle at a temperature of 23 ± 1°C and 55 ± 10% humidity. They were provided with a chow diet (D12450B, Research Diets, USA). At 12 months of age, mice weighing less than 25g were classified as the lean group, while those weighing more than 32g were classified as the obese group. All experimental procedures received approval from the Laboratory Animal Administration Committee of Xi’an Jiaotong University and were performed in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals (8th edition, 2011).
Real-time PCR
Real-time PCR was conducted using the CFX96 RT-PCR detection system (Bio-Rad, Hercules, CA, USA) with SYBR Premix Ex TaqTM II (TaKaRa, Tokyo, Japan). The thermocycling conditions were set as follows: an initial denaturation step of 1 min at 95°C, followed by 40 cycles of 5 s at 95°C and 30 s at 60°C, and a melting curve analysis ranging from 65°C to 95°C with 5-s increments per 0.5°C. Relative gene expression was measured by the 2-ΔΔCt method.
Testis-specific gene analysis
Data from testis-specific gene analysis were retrieved from the PaGenBase database (http://bioinf.xmu.edu.cn/PaGenBase/index.jsp) (Pan et al. Reference Pan, Hu, Shi, Cai, Li, Zou and Ji2013). For mice, ‘Mus musculus’ was selected for the Organism and ‘testis’ for the Tissue. The datasets included BIOGPS_GNF1MA, BIOGPS_MOE430A, GDS182, GDS3052 and GDS3142. For humans, ‘Homo sapiens’ was selected for the Organism and ‘testis’ for the Tissue. The datasets included GDS3113, BIOGPS_U133AGNF1HA, GDS1096, GDS181_TISSUE and GSE30611. As the PaGenBase database does not contain gene expression information for monkeys, a method similar to that of PaGenBase was employed to identify differentially expressed genes in monkey (macaca fascicularis) testis. Specifically, genes with expression levels in the testis, based on previous reported (Zhang et al. Reference Zhang, Qi, Zhao, Li, Zhang, Hu, Wei, Zhou, Qin, Qu, Cao and Liu2023), more than four times higher than those in the liver (Qu et al. Reference Qu, Rom, Li, Jia, Gao, Liu, Ding, Zhao, Wang, Chen, Xiong, Zhao, Xue, Zhao, Chu, Wen, Finney, Zheng, Cao, Zhao, Bai, Zhao, Sun, Zeng, Lin, Liu, Zheng, Zhang, Liu and Chen2023), were considered testis-specific genes.
Analysis of differential genes in high-fat diet
The testicular transcriptomes of mice on a high-fat diet (HFD) and a normal diet were analyzed using the GEO database (GSE44301) and processed with GEO2R employing DESeq2. The control diet (CD) group samples were GSM1082803, GSM1082804 and GSM1082807, while the HFD group samples were GSM1082805, GSM1082806 and GSM1082808. A significance level cut-off was set at 0.05 (FDR). Details of the two groups of mice were referenced from previous study (Grandjean et al. Reference Grandjean, Fourre, De Abreu, Derieppe, Remy and Rassoulzadegan2015). The mice, maintained on a C57BL/6 genetic background, were 3-week-old males divided into two groups: one on a standard chow diet and the other on a western diet comprising 17% casein, 0.3% DL-methionine, 34% sucrose, 14.5% cornstarch, 0.2% cholesterol, 5% cellulose, 7% CM 205B, 1% vit200 and 21% butter (Grandjean et al. Reference Grandjean, Fourre, De Abreu, Derieppe, Remy and Rassoulzadegan2015). Differential gene analysis of monkey testis from two groups was also conducted using DESeq2, with a significance level cut-off set at 0.05 (FDR). The monkey testis samples were obtained from a CD group (n = 5, with balanced diet) and an HFD group (n = 5), with details referenced from previous reported (Zhang et al. Reference Zhang, Qi, Zhao, Li, Zhang, Hu, Wei, Zhou, Qin, Qu, Cao and Liu2023).
Single-cell data analysis
The MaleHealthAtlas database (http://malehealthatlas.cn) was utilized for single-cell gene expression analysis of mouse and human testis (Zhao et al. Reference Zhao, Zhao, Yao, Dai, Li and Tang2023). For single-cell gene expression analysis of monkey testis, the Non-Human Primate Cell Atlas database (https://db.cngb.org/nhpca/cross_species) was employed (Han et al. Reference Han, Wei, Liu, Volpe, Zhuang, Zou, Wang, Pan, Yuan, Zhang, Fan, Guo, Lai, Lei, Liu, Yu, Shangguan, Lai, Deng, Liu, Wu, Shi, Yu, Huang, Cheng, Xu, Liu, Wang, Wang, Zhang, Xie, Yang, Yu, Zheng, Wei, Huang, Lei, Huang, Zhu, Lu, Wang, Wei, Chen, Yang, Du, Chen, Xu, An, Ward, Wang, Pei, Wong, Liu, Zhang, Liu, Qin, Schambach, Isern, Feng, Liu, Guo, Liu, Sun, Maxwell, Barker, Muñoz-Cánoves, Gu, Mulder, Uhlen, Tan, Liu, Yang, Wang, Hou, Xu, Esteban and Liu2022). Uniform manifold approximation and projection (UMAP) was used to visualize the expression levels of the SLC7A4 and SLC30A8 genes in testicular cells across the three species. Furthermore, within the MaleHealthAtlas, the expression levels of SLC7A4 and SLC30A8 genes in human testis were compared between individuals with low BMI and those with high BMI(Zhao et al. Reference Zhao, Zhao, Yao, Dai, Li and Tang2023).
Statistical analysis
Statistical analyses were performed using GraphPad Prism 8.0. All data were tested for normality and equal variance. If passed, Student’s t test was used to compare two groups. Otherwise, nonparametric tests (Mann-Whitney U test) were used. P value <0.05 was considered statistically significant. The differentially expressed genes (DEGs) of RNA-sequencing data were analyzed using R package DESeq2. Genes with adjusted FDR less than 0.05 and absolute fold change larger than 2 were identified as significant DEGs. Gene set enrichment analysis (GSEA) were used to identify significantly enriched pathways.
Results
1. Characteristics of Testicular Genes in Mice, Monkeys and Humans
By comparing the transcriptomes of the mice, monkey and human testes, 3,670 testis-specific genes in mice, 5,239 in humans and 5,284 in monkeys were identified (Figure 1A). Intersection analysis of the testis-specific genes from the three species revealed 730 genes that were testis-specific across all three species (Figure 1A). Additionally, there were 1,714 common testis-specific genes between humans and monkeys, which is significantly higher than the 1,084 shared between mice and humans (Figure 1A). Gene Ontology (GO) and KEGG pathway analysis were performed on these 730 genes. Based on significant differences (q-value < 0.05), the top 20 biological processes included: spermatogenesis, flagellated sperm motility, spermatid development, cell division, piRNA metabolic process, meiotic cell cycle, male meiosis I, cell differentiation, cilium assembly, male meiosis, fertilization, epithelial cilium movement, synaptonemal complex assembly, binding of sperm to the zona pellucida, mitotic spindle assembly checkpoint, sperm chromatin condensation, cilium movement, acrosome assembly, mitotic spindle organization and chromosome segregation. The top five cellular components were: acrosomal vesicle, sperm flagellum, motile cilium, centrosome and axoneme. The top five molecular functions were: ATP binding, microtubule binding, protein kinase activity, protein serine/threonine kinase activity and microtubule motor activity. The top five KEGG pathways were: oocyte meiosis, cell cycle, progesterone-mediated oocyte maturation, motor proteins and cellular senescence. The enrichment analysis from GO and KEGG indicated that the testis-specific genes shared across the three species were consistently associated with testicular biological functions (Figure 1B).
Characteristics of testicular genes in mice, monkeys, and humans. (A) Venn plot of testis-specific genes in mice, humans and monkeys. (B) Gene Ontology (GO) and KEGG analysis of overlapped testis-specific genes (730 genes).
2. Differential expressed Genes in Testes of High-Fat Diet Monkeys and Mice
To analyze the impact of a high-fat diet on testicular gene expression, we identified 367 differentially expressed genes (DEGs) from the mouse dataset and 1742 differential genes from the monkey dataset (Figure 2A). Compared to the CD groups, there were 27 genes that showed significant changes in both species after the high-fat diet (Figure 2A). Among these, GNG5, INHA, MSH5, SLC30A8 and SLC7A4 were significantly upregulated in both the HFD monkey group and the HFD mouse group compared to their respective CD groups (Figure 2B). Conversely, ADAMTSL3, AKAP8L, HERC4, PAFAH1B2, RNF139, RPL22L1, YLPM1 and ZDBF2 were significantly downregulated in the HFD monkey and mouse groups compared to their respective CD groups (Figure 2B). Protein-protein interaction network analysis of these 13 overlapped DEGs revealed no obvious interactions among them, except for only a predicted interaction between RPL22L1 and SLC7A4 (Figure 2C). SLC7A4, an important gene involved in metabolism, was significantly higher in the HFD monkey testis compared to the CD group, as shown by a bar chart (Figure 2D). Further analysis of the testicular transcriptomes of the two monkey groups using GSEA revealed significant activation of pathways related to spermatogenesis (Figure 3A), including DNA strand elongation (Figure 3B), initiation of nuclear envelope reformation, activation of ATR in response to replication stress, activation of the pre-replicative complex, G2M transition and BBSome-mediated cargo targeting to cilium. By intersecting the top 100 ranked genes from the GSEA with the overlap testis-specific genes (730 genes, from Figure 1A) and the overlap DEGs (27 genes, from Figure 2A) in humans and monkeys, SLC30A8 emerged as an unique gene across all three datasets (Figure 3C). SLC30A8, an important gene involved in metabolism, was significantly higher in the HFD monkey testis compared to the CD group, as indicated by the bar chart (Figure 3D).
Differential expressed genes (DEGs) in testes of high-fat diet monkeys and mice. (A) Venn plot of DEGs genes (high-fat diet vs chow diet) in testes of monkeys and mice. (B) Heatmap of the overlapped DEGs genes. (C) Protein-protein interaction network analysis of the overlapped DEGs genes. (D) Expression level of SLC7A4 in testes between monkeys (high-fat diet vs chow diet).
Alteration of pathway in testes of high-fat diet monkeys and mice. (A) Gene Set Enrichment Analysis (GSEA) of gene expression in testes of monkeys (high-fat diet vs chow diet). (B) The most significantly activated pathway in testes of high-fat diet monkeys. (C) Venn plot of the top 100 ranked genes from the GSEA, testis-specific genes, and overlapped DEGs. (D) Expression level of SLC30A8 in testes between monkeys (high-fat diet vs chow diet).
3. SLC7A4 and SLC30A8 were abnormally expressed in testis of obesity
Single-cell data analysis of testes revealed that SLC7A4 is primarily expressed in Sertoli cells of the testes in mice (Figure 4A), monkeys (Figure 4B) and humans (Figure 4C), with a conserved expression pattern across species. Single-cell data analysis showed that SLC30A8 was weakly expressed in SPG cells of the testes in mice (Figure 4D) and was relatively more highly expressed in SPG cells compared to other cells in monkeys (Figure 4E) and humans (Figure 4F). The expression levels of SLC7A4 and SLC30A8 in testis were analyzed in term with each type cell between low and high BMI individuals based on single-cell datasets of human testes. The results indicated that the expression levels of SLC7A4 were relatively higher in individuals with high BMI compared to those with low BMI in SC cells (Figure 4G). Additionally, there was a differential expression of SLC30A8 between low and high BMI individuals in SPG and SPC cells (Figure 4G).
SLC7A4 and SLC30A8 were abnormally expressed in testis of obesity. SLC7A4 expression in Sertoli cells of the testes in mice (Figure 4A), monkeys (Figure 4B), and humans (Figure 4C), and SLC30A8 expression in SPG cells of the testes in mice (Figure 4D), monkeys (Figure 4E) and humans (Figure 4F) were visualized with Umap of single-cell datasets. The expression levels of SLC7A4 and SLC30A8 in human testis between low and high BMI individuals based on single-cell datasets were visualized with Bubble chart; SPG: spermatogonia; SPC: spermatocyte, SPT: spermatids/sperm; SC: Sertoli cell; LC: Leydig cell; PTM: peritubular myoid cell; EC: Endothelial cells; SMC: vascular smooth muscle cel; MAC: Macrophage. (H) SLC7A4 and SLC30A8 expression level in mice testes (lean and obese groups) were determined with qPCR.
Mice at 12 months of age on a standard chow diet were divided into two groups based on body weight: a lean group (body weight < 25g, n = 6) and an obese group (body weight > 32g, n = 6). And qPCR analysis of testicular tissue from these two groups showed that SLC7A4 and SLC30A8 expression levels were significantly higher in the spontaneous obesity group compared to the lean group (Figure 4H).
Discussion
The testes are pivotal reproductive organs in male mammals, responsible for spermatogenesis, and secretion of androgens, essential for reproductive activities. With advancements in biological technologies, various omics techniques focusing on mRNA, miRNA, lncRNA and piRNA have garnered significant attention. Studies have demonstrated their crucial regulatory roles in organismal growth, development and apoptosis (Ozata et al. Reference Ozata, Gainetdinov, Zoch, O’Carroll and Zamore2019; Qin et al. Reference Qin, Qu, Hu, Cao, Liu, Zhang, Zhao, Nazira and Liu2021). Similar to other organs and tissues, normal testicular development and spermatogenesis are tightly regulated by both protein-coding genes and non-coding RNAs (Qin et al. Reference Qin, Qu, Hu, Cao, Liu, Zhang, Zhao, Nazira and Liu2021; Cao et al. Reference Cao, Zhang, Qi, Zhang, Ding, Meng, Zhao, Luo, Shen, Duan, Qin, Ye, Liu and Qu2024). Currently, sequencing studies primarily focusing on mRNA, miRNA, lncRNA and piRNA in mammalian testicular development and spermatogenesis have been extensively reported (Pan et al. Reference Pan, Hu, Shi, Cai, Li, Zou and Ji2013; Grandjean et al. Reference Grandjean, Fourre, De Abreu, Derieppe, Remy and Rassoulzadegan2015; Zhang et al. Reference Zhang, Qi, Zhao, Li, Zhang, Hu, Wei, Zhou, Qin, Qu, Cao and Liu2023). The development of RNA-seq technology has been particularly effective in revealing dynamic changes in mRNA profiles during mammalian testicular development. Studies have predominantly concentrated on animals such as mice, humans, pigs and cattle (Zhou et al. Reference Zhou, Zhang, Xu, Ding, Zheng and Liu2022; Du et al. Reference Du, Wang, Wang, Chen, He, Zhang, Xing, Su, Wang and Zhang2014; Wang et al. Reference Wang, Bu, Yun, Shi, Wang and Gao2023; Djureinovic et al. Reference Djureinovic, Fagerberg, Hallstrom, Danielsson, Lindskog, Uhlen and Ponten2014).
Mice serve as important model organisms for studying human diseases and have played significant roles in medical research both historically and presently. In the field of reproductive development, mice have also proven pivotal, pioneering crucial theories related to sperm and epigenetic changes induced by environmental stress. Despite their importance, it should be noted that mice are not perfect models and may not fully represent all human conditions. For instance, there are differences between mouse and human genomes, metabolic profiles and immune regulation networks, where monkeys, being closer to humans in these aspects, offer advantages (Qu et al. Reference Qu, Rom, Li, Jia, Gao, Liu, Ding, Zhao, Wang, Chen, Xiong, Zhao, Xue, Zhao, Chu, Wen, Finney, Zheng, Cao, Zhao, Bai, Zhao, Sun, Zeng, Lin, Liu, Zheng, Zhang, Liu and Chen2023). While extensive transcriptomic studies of testes across multiple mammalian species have been reported, there remains a lack of comparative analysis of testicular gene expression differences between species. In this study, we compared species-specifically expressed genes in the testes across mice, monkeys and humans, identifying 730 genes that are testis-specifically expressed in all three species. Gene function enrichment analysis revealed that these 730 genes are functionally related to testicular biology, underscoring the importance of these genes among species.
We found that monkeys share more differential genes with humans than with mice, suggesting that gene expression in monkey testes is more similar to humans. Research into the impact of obesity on male reproductive health has been widely reported (Carrageta et al. Reference Carrageta, Pereira, Ferreira, Monteiro, Oliveira and Alves2024; Fui, Dupuis, and Grossmann Reference Fui, Dupuis and Grossmann2014; Zhang et al. Reference Zhang, Qi, Zhao, Li, Zhang, Hu, Wei, Zhou, Qin, Qu, Cao and Liu2023). However, due to limitations in clinical samples from obese humans, data on testicular transcriptomes in obese individuals are limited and cannot fully elucidate the mechanisms underlying testicular cell damage caused by metabolic diseases. Therefore, most research strategies involve feeding animals a high-fat diet to analyze gene functions in animal testes (Sukur, Uysal, and Cinar Reference Sukur, Uysal and Cinar2023; Jarvis et al. Reference Jarvis, Gethings, Samanta, Pedroni, Withers, Gray, Plumb, Winston, Williamson and Bevan2020; Lv, Ling, and Chen Reference Lv, Ling and Chen2020). In this study, we analyzed the testicular transcriptomes of high-fat diet-induced mice and monkeys, revealing significant dysregulation of 13 genes (GNG5, INHA, MSH5, SLC30A8, SLC7A4 upregulated; ADAMTSL3, AKAP8L, HERC4, PAFAH1B2, RNF139, RPL22L1, YLPM1, ZDBF2 downregulated) in both high-fat diet groups compared to their respective controls. These genes are associated with metabolic and immune dysregulation observed in obesity, suggesting they may serve as important regulatory targets mediating testicular damage in obesity. Analyzing gene expression changes in the testes of high-fat diet monkeys independently also holds significant value due to their closer resemblance to humans. GSEA analysis revealed significant activation of pathways related to sperm production, such as DNA strand elongation, in obese monkeys. This suggests that obesity may affect normal testicular function through abnormal activation of these pathways.
While RNA-seq allows for efficient and cost-effective transcriptome analysis, bulk RNA-seq only provides an average expression level of each gene within a cell population, neglecting heterogeneity in gene expression among individual cells within a sample. This limitation is particularly pertinent in heterogeneous systems such as the testes, composed of various cell types including germ cells, supporting cells, stromal cells, vascular endothelial cells and immune cells. To overcome this limitation, a novel approach, scRNA-seq, was developed, allowing RNA-seq application at the single-cell level. Researchers have since completed single-cell sequencing of testes in species including mice (Cao et al. Reference Cao, Zhang, Qi, Zhang, Ding, Meng, Zhao, Luo, Shen, Duan, Qin, Ye, Liu and Qu2024), monkeys (Han et al. Reference Han, Wei, Liu, Volpe, Zhuang, Zou, Wang, Pan, Yuan, Zhang, Fan, Guo, Lai, Lei, Liu, Yu, Shangguan, Lai, Deng, Liu, Wu, Shi, Yu, Huang, Cheng, Xu, Liu, Wang, Wang, Zhang, Xie, Yang, Yu, Zheng, Wei, Huang, Lei, Huang, Zhu, Lu, Wang, Wei, Chen, Yang, Du, Chen, Xu, An, Ward, Wang, Pei, Wong, Liu, Zhang, Liu, Qin, Schambach, Isern, Feng, Liu, Guo, Liu, Sun, Maxwell, Barker, Muñoz-Cánoves, Gu, Mulder, Uhlen, Tan, Liu, Yang, Wang, Hou, Xu, Esteban and Liu2022) and humans (Zhao et al. Reference Zhao, Zhao, Yao, Dai, Li and Tang2023). Here, we conducted an analysis of the genes SLC30A8 and SLC7A4, which are likely to play crucial regulatory roles, at the single-cell level in testes. According to the Human Protein Atlas database (https://www.proteinatlas.org), immunohistochemical analysis did not detect SLC30A8 protein in human testes, whereas SLC30A8 mRNA was present. Both protein and mRNA of SLC30A8 were identified. SLC7A4 protein exhibited positive expression in elongated or late spermatids, Leydig cells and Sertoli cells. Our results showed that SLC7A4 is specifically expressed in Sertoli cells of the testes in mice, monkeys and humans, while SLC30A8 is predominantly expressed in SPG cells of the testes in these species, with more pronounced expression in SPG cells of monkeys and humans. Additionally, single-cell data indicated more pronounced expression changes of SLC7A4 in Sertoli cells and SLC30A8 in SPG cells of obese humans.
SLC30A8 functions as a zinc transporter that regulates intracellular zinc levels, which are essential for various cellular functions(Pound et al. Reference Pound, Sarkar, Cauchi, Wang, Oeser, Lee, Froguel, Hutton and O’Brien2011). Genetic variations in SLC30A8 have been associated with an increased risk of type 2 diabetes, underscoring its significance in glucose metabolism(Rutter and Chimienti Reference Rutter and Chimienti2015). SLC7A4, recognized as the cysteine transporter, is involved in cellular responses to oxidative stress and plays a role in immune function(Sperandeo et al. Reference Sperandeo, Borsani, Incerti, Zollo, Rossi, Zuffardi, Castaldo, Taglialatela, Andria and Sebastio1998). Research exploring the roles of SLC30A8 and SLC7A4 in testicular and embryonic development remains scarce. Here, results from qPCR analysis of non-diet-induced mouse testicular tissues further supported significantly upregulated expression of SLC30A8 and SLC7A4 in obese testes. These findings collectively underscore SLC30A8 and SLC7A4 as important genes mediating testicular function in obesity.
Conclusion
This study analyzed transcriptomic sequencing data from the testes of mice, monkeys and humans, identifying 730 genes with specific expression across mouse, monkey and human testes. The findings indicate that a high-fat diet leads to the upregulation of genes such as GNG5, INHA, MSH5, SLC30A8 and SLC7A4 in mouse and monkey testes. Additionally, single-cell data indicated that SLC30A8 and SLC7A4 may play important roles in mediating testicular function related to obesity across the three species.
Data availability
The data that support the study findings are available from the corresponding author upon reasonable request.
Acknowledgements
Not applicable.
Competing interests
The authors declare no conflict of interest.
Funding
This work was supported by Innovation Capability Support Program of Shaanxi (2024SF-YBXM-175).
Ethical standards
All animal protocols were reviewed and approved by the Xi’an Jiaotong University Animal Care and Use Committee. The experimental protocol was carried out in accordance with the National Institutes of Health Guide for Care.
