Encircling granulosa cells protects against di-(2-ethylhexyl)phthalate-induced apoptosis in rat oocytes cultured in vitro.
Anima TripathiVivek PandeyA N SahuAlok K SinghPawan K DubeyPublished in: Zygote (Cambridge, England) (2019)
The present study investigated if the presence of encircling granulosa cells protected against di(2-ethylhexyl)phthalate (DEHP)-induced oxidative stress in rat oocytes cultured in vitro. Denuded oocytes and cumulus-oocyte complexes (COCs) were treated with or without various doses of DEHP (0.0, 25.0, 50.0, 100, 200, 400 and 800 μM) in vitro. Morphological apoptotic changes, levels of oxidative stress and reactive oxygen species (ROS), mitochondrial membrane potential, and expression levels of apoptotic markers (Bcl2, Bax, cytochrome c) were analyzed. Our results showed that DEHP induced morphological apoptotic changes in a dose-dependent manner in denuded oocytes cultured in vitro. The effective dose of DEHP (400 µg) significantly (P>0.05) increased oxidative stress by elevating ROS levels and the mitochondrial membrane potential with higher mRNA expression and protein levels of apoptotic markers (Bax, cytochrome c). Encircling granulosa cells protected oocytes from DEHP-induced morphological changes, increased oxidative stress and ROS levels, as well as increased expression of apoptotic markers. Taken together our data suggested that encircling granulosa cells protected oocytes against DEHP-induced apoptosis and that the presence of granulosa cells could act positively towards the survival of oocytes under in vitro culture conditions and may be helpful during assisted reproductive technique programmes.
Keyphrases
- induced apoptosis
- oxidative stress
- endoplasmic reticulum stress
- diabetic rats
- signaling pathway
- cell death
- dna damage
- reactive oxygen species
- cell cycle arrest
- ischemia reperfusion injury
- poor prognosis
- polycystic ovary syndrome
- endothelial cells
- anti inflammatory
- type diabetes
- adipose tissue
- machine learning
- high glucose
- staphylococcus aureus
- climate change
- big data
- artificial intelligence
- electronic health record
- risk assessment
- pseudomonas aeruginosa
- cystic fibrosis