Transcriptomic profiling reveals estradiol and progesterone specific microRNA signatures differentially regulate mRNA targets in vaginal epithelial cells
Joshi, S.; Nazli, A.; Verschoor, C.; Kaushic, C.
Show abstract
Epithelial cells of the female reproductive tract (FRT) form a protective barrier and serve as the first line of defense against sexually transmitted infections (STIs). They recognize pathogens, release cytokines and initiate innate immune responses. Sex hormones 17{beta}-estradiol (E2) and progesterone (P4) fluctuate throughout the menstrual cycle and influence epithelial cell functions. Generally, E2 confers protection against viral STIs like HIV-1 and HSV-2, whereas P4 increases susceptibility. However, the underlying mechanisms remain incompletely understood. MicroRNAs, small non-coding RNAs that regulate gene expression by inhibiting translation of target mRNAs, significantly influence viral infections, by promoting or restricting viral pathogenesis. Here, we examined the effect of sex hormones on microRNA expression in vaginal epithelial cells (VECs), the first responders to pathogens in the FRT. Using next generation sequencing analysis, the effect of physiological concentrations of E2 or P4 on microRNA transcription profile of VECs grown in air-liquid interface cultures was characterized. Thirteen miRNAs were uniquely regulated by E2 and 102 by P4, with 29 miRNAs that overlapped between both. The top four differentially expressed miRNAs from both treatments were validated by RT-qPCR. The mRNA targets of unique E2-miRNAs were involved in adherens junction, tight junction and chemokine signaling pathways; whereas the mRNA targets of unique P4-miRNAs were involved in MAPK signaling pathway. Interestingly, several miRNAs regulated by E2- (eg. hsa-miR-9-3p, hsa-miR-200c- 5p, hsa-miR-548c-5p) and by P4 (eg. hsa-let-7f-5p, hsa-miR-16-5p, hsa-miR-27b-3p) targeted genes related to cell cycle pathway. Together, these findings indicate that microRNAs regulated by E2 and P4 influence mRNAs in the pathways associated with cell adhesion, cell growth and development and innate immune responses, critical for maintenance of epithelial barrier integrity and regulating pathogen susceptibility in the vaginal tract. These hormone-regulated miRNAs may serve as potential targets for therapeutic interventions.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Transcriptional profiling of mucus production and modification in rhesus macaque endocervical cells under hormonal regulation 93%
- Increased FOXL2 Expression Alters Uterine Structures and Functions 93%
- Irx3 Promotes Gap Junction Communication Between Uterine Stromal Cells to Regulate Vascularization during Embryo Implantation 93%
Similar papers in this journal
- Assessing the relationship between menstrual products and reproductive and urogenital tract infections (RUTIs): a systematic review evaluating the evidence and recommendations for future research 92%
- Recombinant production of rabbit β-Nerve Growth Factor and its biological effect on rabbit sperm 92%
- Uterine secretome initiates growth of gynecologic tissues in ectopic locations. 92%
Similar papers in this journal
- miRNA/mRNA analysis of increased TGF-β pathways drive epithelial-mesenchymal transition and regulatory T cell differentiation 95%
- Endocervical regulatory T cells are associated with decreased genital inflammation and lower HIV target cell abundance 93%
- Uterine NK cells underexpress receptors recognizing HLA-C2 and HLA-G in reproductive failure 92%
Similar papers in this journal
- Embryonic signals mediate extracellular vesicle biogenesis and trafficking at the embryo-maternal interface 93%
- Proteomic studies of human placentas reveal partnerships associated with preeclampsia, diabetes, gravidity, and labor 89%
- Cfap300 regulates the transdifferentiation of Corpuscle of Stannius cells in zebrafish 88%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.