Breakthrough in Ovarian Mechanobiology from NUS Chan Lab

The Mechanobiology Institute (MBI) at the National University of Singapore (NUS) has once again pushed the boundaries of reproductive biology with a new study and accompanying protocol from the Chan Lab. Published on March 18, 2026, in STAR Protocols, the work introduces a detailed method to measure murine ovarian elasticity and composition in situ. This is complemented by a recent preprint detailing theca cell mechanosensing's role in follicular extracellular matrix (ECM) regulation.

Led by Principal Investigator Chii Jou Chan, the research leverages quantitative micro-elastography (QME), a cutting-edge imaging technique pioneered by the lab, to create three-dimensional maps of ovarian tissue stiffness. This innovation allows scientists to correlate mechanical properties directly with cellular and molecular features, offering unprecedented insights into ovarian follicle development and ageing.

Understanding the Chan Lab's Research Focus

Established at MBI, the Chan Lab investigates how mechanical forces and fluid pressures shape early mammalian development, particularly oogenesis and folliculogenesis. Chii Jou Chan, a biophysicist with a PhD from the University of Cambridge and postdoctoral experience at EMBL, has garnered over 2,000 citations for work bridging mechanics and biology. The lab's efforts center on ovarian tissue hydraulics, where tissue pressure and ECM stiffness influence oocyte quality and fertility.

Previous studies from the lab, such as 3D QME mapping of age-dependent ovarian changes, laid the groundwork. These revealed stiffer ovaries in aged mice, linked to ECM remodeling, highlighting mechanobiology's role in reproductive decline.

Quantitative Micro-Elastography: The Core Technology

Quantitative Micro-Elastography (QME) is an optical coherence tomography (OCT)-based method that measures tissue elasticity at micrometer resolution. It applies microscale compression via a compliant silicone layer and ring actuator, capturing strain fields to compute Young's modulus (in kPa). This non-destructive technique generates 3D elasticity maps of intact tissues like ovaries.

In ovarian applications, QME visualizes spatial stiffness gradients across follicles, corpora lutea, and stroma, revealing how mechanics guide follicle maturation. The method's precision—down to 4 μm strokes—surpasses traditional elastography, enabling in situ analysis without sectioning artifacts.

The New Protocol: Integrating QME with Multimodal Imaging

The STAR Protocols paper outlines a step-by-step workflow for combining QME with transmitted light (TL) microscopy and immunofluorescence (IF). Starting with fresh murine ovaries (from ICR mice aged 3 weeks to 12 months), tissues are embedded in low-gelling agarose, scanned via QME using an OCT system like Telesto II, fixed in paraformaldehyde, sectioned (60-75 μm), and imaged.

• Excision and Preparation: Ovaries encapsulated in 3D-printed molds for stability.
• QME Acquisition: Preload strain (10%) with compression, synchronized B-scans processed in MATLAB for elasticity.
• TL Segmentation: MosaicJ in Fiji identifies structures like follicles for co-registration.
• IF Staining: Antibodies for collagen-I/III, fibronectin, CD31 (endothelium), α-SMA (smooth muscle), imaged via confocal Zeiss LSM 980.
• Analysis: GitHub scripts (https://github.com/theia-dev/qme_if) for co-registration, volume/elasticity stats, QuPath cell counts, 3D Python visualization.

This pipeline links stiffness to composition, e.g., higher collagen-I correlating with stiffer regions in aged ovaries. Read the full protocol here.

Photo by Roaming Pictures on Unsplash

Preprint Insights: Theca Cells as Mechanical Regulators

The bioRxiv preprint (March 12, 2026) elucidates theca cell (TC) roles in ECM deposition. TCs, surrounding granulosa cells, form a stiff basement membrane and theca matrix that instruct TC proliferation via YAP signaling. Hyaluronic acid (HA), secreted by contractile TCs, scaffolds proliferation, motility, and follicle growth.

Key findings:

• Stiff substrates boost YAP nuclear localization in TCs.
• Stretch, packing, curvature modulate proliferation; TCs migrate to positive curvature.
• HA depletion halts follicle growth, underscoring mechanochemical feedback.

Implications for Fertility and Ovarian Ageing

Ovarian ageing features ECM stiffening, impairing folliculogenesis and oocyte quality—key infertility factors. The protocol enables precise mapping of these changes, potentially identifying therapeutic targets like HA modulation or YAP inhibitors. In Singapore, where fertility rates lag (1.1 births/woman), such research supports national reproductive health initiatives.

By revealing TC mechanics, the work paves ways for bioengineered matrices mimicking youthful ovaries, advancing IVF and anti-ageing therapies.

Technical Challenges and Innovations

Challenges included agarose-hydrogel matching for artifact-free imaging and co-registering 3D volumes with 2D sections. Innovations like custom compliant layers and open-source MATLAB/Python tools democratize the method. Adaptable to other tissues, it broadens mechanobiology applications.

NUS MBI's Contribution to Singapore's Biomedical Landscape

MBI, an MOE Research Centre of Excellence, fosters interdisciplinary research. The Chan Lab's outputs exemplify NUS's global standing (top 10 in biomed QS rankings). Supported by NRF and MOE, this bolsters Singapore's Smart Nation biotech hub, attracting talent and funding.

Collaborations with Duke-NUS and A*STAR amplify translational potential.

Photo by Galen Crout on Unsplash

Future Outlook and Research Horizons

Upcoming: Human ovarian applications, AI-enhanced segmentation, hydraulic models integrating pressure. Potential for fertility clinics via stiffness biomarkers. The lab seeks postdocs in mechanobiology—check NUS openings.

This work not only advances science but inspires Singapore's next-gen researchers in higher education and biomed.