Transcriptomics and proteomics analysis to explore the mechanism of Yishen Tongluo formula repairing sperm DNA damage in rats.
Chenming ZhangJianshe ChenXiao WeiLina ZhaoPeipei ZhaoXun LiJiaxin CuiSicheng MaZixue SunZulong WangPublished in: Andrologia (2022)
The sperm DNA fragmentation index (DFI) is an objective indicator of male fertility. Currently, effective treatments for high sperm DFI are limited and traditional Chinese medicine (TCM) has certain advantages in this aspect. Yishen Tongluo formula (YSTL), a TCM formula, has been found to reduce DFI in patients. To better understand the mechanisms underlying its activity, we used transcriptomics and proteomics to analyse the potential target gene YSTL repairing tripterygium glycosides (TGs)-mediated sperm DNA damage in rats, followed by validation analyses using RT-qPCR and western blotting, which showed that relative to the control group, DFI was markedly elevated in the TGs group, but markedly lower in the YSTL group relative to the TGs group. KEGG pathway analysis of 119 differentially expressed genes and 158 DEPs identified using trend analysis revealed that they were enriched for apoptosis and base excision repair at the transcriptomic level and for microRNAs in cancer and complement and coagulation cascades at the proteomic level. Ttr and Pnpla2 were identified as potential target genes for YSTL. Our data show that YSTL can protect rat sperm DNA from TGs-induced damage, which may be related to apoptosis, DNA repair and other pathways, and the possible target genes are Ttr and Pnpla2.
Keyphrases
- dna damage
- dna repair
- oxidative stress
- single cell
- genome wide
- diabetic rats
- genome wide identification
- mass spectrometry
- human milk
- end stage renal disease
- endoplasmic reticulum stress
- cell death
- ejection fraction
- rna seq
- circulating tumor
- single molecule
- newly diagnosed
- dna damage response
- cell free
- dna methylation
- human health
- label free
- cell cycle arrest
- genome wide analysis
- chronic kidney disease
- bioinformatics analysis
- copy number
- electronic health record
- prognostic factors
- papillary thyroid
- machine learning
- transcription factor
- young adults
- low birth weight
- artificial intelligence
- nucleic acid
- stress induced
- squamous cell