Abstract
During ovulation, the apical wall of the preovulatory follicle breaks down to facilitate gamete release. In parallel, the residual follicle wall differentiates into a progesterone-producing corpus luteum. Disruption of ovulation, whether through contraceptive intervention or infertility, has implications for women’s health. In this study, we harness the power of an ex vivo ovulation model and machine-learning guided microdissection to identify differences between the ruptured and unruptured sides of the follicle wall. We demonstrate that the unruptured side exhibits clear markers of luteinization after ovulation while the ruptured side exhibits cell death signals. RNA-sequencing of individual follicle sides reveals 2099 differentially expressed genes (DEGs) between follicle sides without ovulation induction, and 1673 DEGs 12 h after induction of ovulation. Our model validates molecular patterns consistent with known ovulation biology even though this process occurs in the absence of the ovarian stroma, vasculature, and immune cells. We further identify previously unappreciated pathways including amino acid transport and Jag-Notch signaling on the ruptured side and glycolysis, metal ion processing, and IL-11 signaling on the unruptured side of the follicle. This study yields key insights into follicle-inherent, spatially-defined pathways that underlie follicle rupture, which may further understanding of ovulation physiology and advance women’s health.
Original language | English (US) |
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Article number | 1374 |
Journal | Communications Biology |
Volume | 7 |
Issue number | 1 |
DOIs | |
State | Published - Dec 2024 |
Funding
This work was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development of the National Institutes of Health under Award Number T32HD094699, the Histochemical Society\u2019s Graduate Medical Trainee and Graduate Student Cornerstone Grant, and the Bill & Melinda Gates Foundation Grant INV-003385. Under the grant conditions of the Bill & Melinda Gates Foundation, a Creative Commons Attribution 4.0 Generic License has already been assigned to the Author Accepted Manuscript version that might arise from this submission. B.A.G is supported in part through the Geisel School of Medicine at Dartmouth\u2019s Center for Quantitative Biology through a grant from the National Institute of General Medical Sciences (NIGMS, P20GM130454) of the NIH. We are also grateful for our discussions with the members of the Ovarian Contraceptive Discovery Initiative (OCDI), Dr. Stephen Ward, and Dr. Daniel Goldberg. The authors would also like to thank Stella Polyanne De Oliveira and Ian Gingerich for their technical support of this project. ELISA analysis was performed in the Analytical bioNanoTechnology Equipment Core Facility of the Simpson Querrey Institute for BioNanotechnology at Northwestern University. ANTEC receives partial support from the Soft and Hybrid Nanotechnology Experimental (SHyNE) Resource (NSF ECCS-2025633) and Feinberg School of Medicine, Northwestern University.
ASJC Scopus subject areas
- Medicine (miscellaneous)
- General Biochemistry, Genetics and Molecular Biology
- General Agricultural and Biological Sciences