# Improving in vitro preantral follicle development using novel bioengineered culture systems and pre-theca-like cells as a strategy for assisted reproduction > **NIH NIH F31** · UNIVERSITY OF CALIFORNIA AT DAVIS · 2023 · $40,288 ## Abstract 1 PROJECT SUMMARY 2 Infertility has become a fundamental quality-of-life issue for young girls and women who have undergone 3 gonadotoxic cancer treatment. A highlighted approach to preserve fertility is capitalizing on the abundant 4 population of primary follicles found in the ovary without auto-transplanting possibly malignant tissue. However, 5 success rates of developing these follicles in vitro to yield mature oocytes is inefficient and limited in humans 6 and nonmurine model mammals. The long-term goal of this work is to establish a culture system to support the 7 study of in vitro primary follicle growth in the bovine as a translational model for human folliculogenesis. The 8 central hypothesis is that a biomimetic culture system using poly(ethylene glycol) (PEG) with degradable 9 crosslinker peptides and co-encapsulation with mesoderm-like cells (MLCs) that can give rise to theca-like cells 10 will better promote the primary follicle development. The rationale behind this work is that a dynamic three- 11 dimensional (3D) culture system that allows follicle-driven matrix degradation and is supplemented with cells 12 similar to the ovarian stroma (including theca cells) will recapitulate the native ovarian environment and better 13 support long-term folliculogenesis. The central aim of this proposal is to examine the ability of mesoderm-like 14 cells (MLCs) to become theca-like cells and promote development of bovine primary follicles comparable to the 15 inclusion of dissociated ovarian cells in a PEG hydrogel culture system. Previous research has shown that feeder 16 cells, such as adipose-derived stem cells, aid in the development of mouse preantral follicles in vitro. However, 17 MLCs reflect a cell identity similar to the mesoderm lineage, which is the developmental origin of ovary. 18 Additionally, they express follicle-responsiveness genes that are known to be essential for theca cell 19 differentiation and recruitment. Therefore, we hypothesize their addition in preantral follicle culture will add to the 20 creation of a microenvironment that better mimics the natural ovary, thus enhancing support of bovine preantral 21 follicle development. The novel aspect of this work is the translation of a bioengineered culture system, that has 22 only been used in short-term mouse in vitro follicle culture, to a new organism known to better model the long 23 and complex process of human folliculogenesis. Moreover, here we test the inclusion of stemness-derived cells 24 that express genes known to be responsive to follicle-secreted factors to create the theca-cell counterpart, thus 25 further emphasizing the novelty of the project. The significance of this work is that it will contribute to the 26 advancement of methods to grow primary follicles from a large mammal model species like the bovine, which 27 will be more directly translated into human. Overall, this project provides insight on using a culture system and 28 supplemental cel... ## Key facts - **NIH application ID:** 10749434 - **Project number:** 1F31HD111173-01A1 - **Recipient organization:** UNIVERSITY OF CALIFORNIA AT DAVIS - **Principal Investigator:** Juliana Candelaria - **Activity code:** F31 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2023 - **Award amount:** $40,288 - **Award type:** 1 - **Project period:** 2023-08-01 → 2024-07-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10749434 ## Citation > US National Institutes of Health, RePORTER application 10749434, Improving in vitro preantral follicle development using novel bioengineered culture systems and pre-theca-like cells as a strategy for assisted reproduction (1F31HD111173-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10749434. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*