New Gene Markers of Exosomal Regulation Are Involved in Porcine Granulosa Cell Adhesion, Migration, and Proliferation.
Jakub KulusWieslawa KrancMagdalena KulusDorota BukowskaHanna Piotrowska-KempistyPaul E MozdziakBartosz KempistyPaweł AntosikPublished in: International journal of molecular sciences (2023)
Exosomal regulation is intimately involved in key cellular processes, such as migration, proliferation, and adhesion. By participating in the regulation of basic mechanisms, extracellular vesicles are important in intercellular signaling and the functioning of the mammalian reproductive system. The complexity of intercellular interactions in the ovarian follicle is also based on multilevel intercellular signaling, including the mechanisms involving cadherins, integrins, and the extracellular matrix. The processes in the ovary leading to the formation of a fertilization-ready oocyte are extremely complex at the molecular level and depend on the oocyte's ongoing relationship with granulosa cells. An analysis of gene expression from material obtained from a primary in vitro culture of porcine granulosa cells was employed using microarray technology. Genes with the highest expression (LIPG, HSD3B1, CLIP4, LOX, ANKRD1, FMOD, SHAS2, TAGLN, ITGA8, MXRA5, and NEXN) and the lowest expression levels (DAPL1, HSD17B1, SNX31, FST, NEBL, CXCL10, RGS2, MAL2, IHH, and TRIB2) were selected for further analysis. The gene expression results obtained from the microarrays were validated using quantitative RT-qPCR. Exosomes may play important roles regarding intercellular signaling between granulosa cells. Therefore, exosomes may have significant applications in regenerative medicine, targeted therapy, and assisted reproduction technologies.
Keyphrases
- cell adhesion
- gene expression
- induced apoptosis
- cell cycle arrest
- extracellular matrix
- poor prognosis
- dna methylation
- polycystic ovary syndrome
- stem cells
- genome wide
- mesenchymal stem cells
- oxidative stress
- type diabetes
- high resolution
- adipose tissue
- metabolic syndrome
- escherichia coli
- staphylococcus aureus
- skeletal muscle
- insulin resistance
- cystic fibrosis
- genome wide identification
- data analysis