Experimental diabetes negatively affects the spermatogonial stem cells' self-renewal by suppressing GDNF network interactions.
Rozita AzarniadMazdak RaziShapour HasanzadehHassan MalekinejadPublished in: Andrologia (2020)
The present study was done to analyse the time-dependent effects of diabetes on Sertoli cells-spermatogonial stem cells' (SSCs) network interaction by focusing on glial cell line-derived neurotrophic factor (GDNF) and its special receptors, gfrα1 and c-RET as well as the Bcl-6b. In total, 40 Wistar rats were considered in; control, 20, 45 and 60 days diabetes-induced groups. An experimental diabetes was induced by STZ. The GDNF, gfrα1, c-RET and Bcl-6b expressions were evaluated. The serum level of testosterone, tubular repopulation (RI) and spermiogenesis (SPI) indices, general histological alterations, germ cells, mRNA damage, sperm count and viability were assessed. The diabetes, in a time-dependent manner, diminished mRNA and protein levels of GDNF, gfrα1, c-RET and Bcl-6b versus control group (p < .05), enhanced percentage of seminiferous tubules with negative RI, SPI, and diminished Leydig and Sertoli cells distribution, serum levels of testosterone, sperm count and viability. Finally, the number, percentage of cells and seminiferous tubules with normal mRNA content were significantly (p < .05) diminished. In conclusion, as a new data, we showed that the diabetes by inducing severe mRNA damage and suppressing GDNF, gfrα1, c-RET and Bcl-6b expressions, potentially affects the Sertoli-SSCs' network and consequently inhibits the SSCs' self-renewal process.
Keyphrases
- type diabetes
- induced apoptosis
- stem cells
- cardiovascular disease
- glycemic control
- cell cycle arrest
- oxidative stress
- binding protein
- endoplasmic reticulum stress
- signaling pathway
- diabetic rats
- machine learning
- mesenchymal stem cells
- metabolic syndrome
- cell death
- bone marrow
- spinal cord
- peripheral blood
- skeletal muscle
- endothelial cells
- high glucose
- spinal cord injury
- deep learning
- drug induced
- small molecule
- network analysis
- neuropathic pain
- amino acid
- weight loss
- insulin resistance