# Self-assembled DNA elastic networks for measuring membrane tension in live cells

> **NIH NIH R21** · YALE UNIVERSITY · 2022 · $209,375

## Abstract

Project Summary
Many cellular processes, such as spreading, motility, division, and morphogenesis generate membrane tension
gradients. Such gradients drive membrane flows, which relax the initial gradients. In addition, quiescent cells
maintain a constant surface area and a relatively stable membrane tension, 𝜎, by balancing the rates at which
membrane is added (via exocytosis) and removed (via endocytosis) to and from the cell surface. Changes in 𝜎
have been proposed to provide rapid, long-range cellular signaling. Yet, how the plasma membrane flows and
how gradients of 𝜎 relax are very poorly understood, with estimates of membrane tension equilibration times in
cells ranging from milliseconds to tens of minutes. One of the major reasons underlying this dearth of
knowledge is the lack of suitable methods for measuring membrane tension changes in live cells. In the past,
two classes of membrane tension measurements have been developed, but both have severe limitations. The
first class is based on changes in optical properties of small molecules. These sensors probe local properties of
cell membranes. Due to large heterogeneities in biological membranes, and potential interactions of the probes
with various membrane components, correlating 𝜎 with the local properties probed by these small molecule
sensors is not straightforward. The second approach relies on pulling a thin membrane tether from the cell
surface and measuring the tether force using optical trapping or atomic force microscopy. The tether force is
related to the in-line membrane tension, membrane bending modulus, and the adhesion energy between the
plasma membrane and the cytoskeleton. This approach allows a "true" membrane tension to be measured, but
requires specialized equipment, is very difficult to implement when cells undergo physiological changes when
tension gradients are most likely to arise, and only provides a local measurement. Thus, despite the urgent
need, there are no direct and convenient probes to quantify membrane tension gradients during cellular
processes. We propose to close this gap by developing a radically new class of membrane tension
sensors based on DNA-based self-assembly of an elastic network over cell surfaces, called
LEMONADE, for Lego-like membrane tension analyzer based on self-assembled DNA elastic networks.
We aim to 1) develop a library of DNA tiles and connector-springs that self-assemble on cell
surfaces into a network with tunable properties. A variety of DNA tile and connector-spring designs
will be generated and optimized for self-assembly on membranes. The connectivity and elasticity of the
network will be tunable by substitution of components with different properties. Expansion or contraction of
the network due to changes in membrane area will be detected using FRET dye pairs located on the connector-
spring modules. 2) Characterize the response of the DNA-based membrane tension sensor to
controlled membrane tension perturbations in various ...

## Key facts

- **NIH application ID:** 10405097
- **Project number:** 5R21GM141669-02
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** ERDEM KARATEKIN
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $209,375
- **Award type:** 5
- **Project period:** 2021-06-01 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10405097

## Citation

> US National Institutes of Health, RePORTER application 10405097, Self-assembled DNA elastic networks for measuring membrane tension in live cells (5R21GM141669-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10405097. Licensed CC0.

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