Abstract
Cholesterol and lipid unsaturation underlie a balance of opposing forces that features prominently in adaptive cell responses to diet and environmental cues. These competing factors have resulted in contradictory observations of membrane elasticity across different measurement scales, requiring chemical specificity to explain incompatible structural and elastic effects. Here, we demonstrate that – unlike macroscopic observations – lipid membranes exhibit a unified elastic behavior in the mesoscopic regime between molecular and macroscopic dimensions. Using nuclear spin techniques and computational analysis, we find that mesoscopic bending moduli follow a universal dependence on the lipid packing density regardless of cholesterol content, lipid unsaturation, or temperature. Our observations reveal that compositional complexity can be explained by simple biophysical laws that directly map membrane elasticity to molecular packing associated with biological function, curvature transformations, and protein interactions. The obtained scaling laws closely align with theoretical predictions based on conformational chain entropy and elastic stress fields. These findings provide unique insights into the membrane design rules optimized by nature and unlock predictive capabilities for guiding the functional performance of lipid-based materials in synthetic biology and real-world applications.
| Original language | English |
|---|---|
| Article number | 7024 |
| Journal | Nature Communications |
| Volume | 16 |
| Issue number | 1 |
| DOIs | |
| State | Published - Dec 2025 |
Funding
We thank Dr. Michihiro Nagao and Dr. Elizabeth Kelley for assistance with the NSE and SANS data acquisition at NIST. R.A. acknowledges support from the Jeffress Trust Award Program in Interdisciplinary Research and NSF Grants MCB-2137154 and DMR-2350336. M.F.B. acknowledges support by NIH Grant R01EY026041 and NSF Grants MCB-1817862, CHE-1904125, and DMR-2350337. M.D. was supported by a Ruth L. Kirschstein NIH Postdoctoral Fellowship, NIH Grant 1F32GM134704, and the SciLifeLab & Wallenberg Data Driven Life Science Program (grant KAW 2024.0159). G.K. gratefully acknowledges support from the 1923 Fund, and access to computational resources awarded through the COVID-19 High Performance Computing Consortium at the Center for Computational Innovations at the Rensselaer Polytechnic Institute. T.K. acknowledges partial support from the ORNL Neutron Scattering Graduate Research Program. The authors acknowledge the use of neutron-scattering facilities at NIST and ORNL. Access to the NIST NSE beamline was provided by the Center for High Resolution Neutron Scattering, a partnership between NIST and NSF under Agreement DMR-1508249. The SANS measurements performed on the Bio-SANS instrument utilized the Center for Structural Molecular Biology (FWP ERKP291), a Structural Biology Resource of the U.S. DOE Office of Biological and Environment Research. SAXS and NSE studies conducted at ORNL were facilitated by the Scientific User Facilities Division of the Department of Energy (DOE) Office of Science, Basic Energy Science (BES) Program, under Contract DE-AC05-00OR22725. Purchase of the Xenocs Xeuss 3.0 SAXS/WAXS instrument at Virginia Tech (used to obtain results included in this publication) was supported by NSF Grant DMR-MRI-2018258. This work benefited from the use of the SasView application, originally developed under NSF award DMR-0520547. SasView contains code developed with funding from the European Union’s Horizon 2020 research and innovation program under the SINE2020 project under Agreement No. 654000.