S5E6

Abstract

In a diversity of physiological contexts, eukaryotic cells adhere to an extracellular matrix (ECM), a disordered network with complex nonlinear mechanics. Such cells can perform mechanosensation: using local force probing they can measure their substrate’s mechanical properties and respond accordingly. Yet, given the combination of inherent structural heterogeneity and the pronounced nonlinear elastic response of the ECM, it is not clear how cells robustly mechanosense the stiffness of their matrix environment.

Using a theoretical framework for disordered fiber networks and microrheology experiments, we find that the extreme mechanical heterogeneity that cells can locally sense with small probing forces is strongly reduced with increasing force: cells can dramatically enhance the accuracy of mechanosensation by using probe forces that trigger elastic nonlinearities. We show that nonlinear mechanosensation allows cells to average the response of disordered networks over an enlarged region, thereby ensuring a reliable local estimate of the mechanical properties of the disordered matrix.

Our nonlinear mechanosensing model offers a conceptual framework for mechanical sensing. This strategy generally applies to any probing device which locally measures the mechanical response in a fibrous environment, independently of the constitutive details of the micromechanics of these fibers. I will show with an example how a cell can use this nonlinear mechanosensation to infer the macroscopic mechanical properties of a disordered ECM using local measurements.

Introduction of speaker

Estelle Berthier is a Marie Skłodowska-Curie Individual Fellow in the group of Prof. Broedersz at LMU München. She received her Engineering and Master degrees in Material Sciences from the National Institute of Applied Sciences (Lyon, France) in 2012. She obtained her doctorate in Mechanics in 2015 at UPMC (Paris, France), working in the group of Prof. Ponson on damage and quasi-brittle failure of disordered materials. She then joined the group of Prod. Daniels at NCSU (Raleigh, USA) in 2017 where she experimentally studied the failure behavior of disordered networks. Her current research aims at theoretically understanding cell-matrix mechanical interactions.

Abstract

Fluids conveyed in deformable conduits are often encountered in microfluidic applications, which makes fluid-structure interactions (FSIs) an inherent feature of these systems. Previous experiments reported the existence of FSI-induced instabilities in microchannel flows at low Reynolds number (Re). This observation suggests new strategies to enhance mixing at the microscale, where mixing is diffusion limited. To provide new understanding of these phenomena, we formulate an unsteady reduced model of flow in a common long, shallow rectangular microchannel with a compliant top wall. Going beyond the usual lubrication approximation invoked in the microchannel flows, we consider finite fluid inertia and couple the reduced flow equations to a novel reduced one-dimensional (1D) wall deformation equation. Importantly, we have found the critical conditions under which the FSI-induced non-uniform base state is linearly unstable. Numerical simulations of the reduced model show that the unstable cases correspond to self-sustained oscillations of the channel wall, with frequencies close to the natural frequency of the wall. The behaviors of the proposed model show qualitative agreement with experimental observations, capturing several key effects. Our modeling framework can be applied to other microfluidic systems with similar geometric scale separation under different operation conditions.

Introduction of speaker

Dr. Xiaojia Wang is a Postdoctoral Assistant Professor in the Department of Mathematics at University of Michigan. She earned her PhD in Mechanical Engineering at Purdue University, with her doctoral thesis focused on microscale fluid—structure interactions. Dr. Wang’s research combines physical intuitions, mathematical analysis and numerical simulations to promote the understanding of fundamental flow problems.