Issue 18, 2023

In situ measurement of viscoelastic properties of cellular monolayers via graphene strain sensing of elastohydrodynamic phenomena

Abstract

Recent advances recognize that the viscoelastic properties of epithelial structures play important roles in biology and disease modeling. However, accessing the viscoelastic properties of multicellular structures in mechanistic or drug-screening applications has challenges in repeatability, accuracy, and practical implementation. Here, we present a microfluidic platform that leverages elastohydrodynamic phenomena, sensed by strain sensors made from graphene decorated with palladium nanoislands, to measure the viscoelasticity of cellular monolayers in situ, without using chemical labels or specialized equipment. We demonstrate platform utility with two systems: cell dissociation following trypsinization, where viscoelastic properties change over minutes, and epithelial-to-mesenchymal transition, where changes occur over days. These cellular events could only be resolved with our platform's higher resolution: viscoelastic relaxation time constants of λ = 14.5 ± 0.4 s−1 for intact epithelial monolayers, compared to λ = 13.4 ± 15.0 s−1 in other platforms, which represents a 30-fold improvement. By rapidly assessing combined contributions from cell stiffness and intercellular interactions, we anticipate that the platform will hasten the translation of new mechanical biomarkers.

Graphical abstract: In situ measurement of viscoelastic properties of cellular monolayers via graphene strain sensing of elastohydrodynamic phenomena

Supplementary files

Article information

Article type
Paper
Submitted
26 May 2023
Accepted
10 Aug 2023
First published
14 Aug 2023
This article is Open Access
Creative Commons BY-NC license

Lab Chip, 2023,23, 4067-4078

In situ measurement of viscoelastic properties of cellular monolayers via graphene strain sensing of elastohydrodynamic phenomena

T. Guo, X. Zou, S. Sundar, X. Jia and C. Dhong, Lab Chip, 2023, 23, 4067 DOI: 10.1039/D3LC00457K

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