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Register a new userLiquid demixing in elastic networks: cavitation, permeation, or size selection?
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Demixing of multicomponent biomolecular systems via liquid-liquid phase separation (LLPS) has emerged as a potentially unifying mechanism governing the formation of several membrane-less intracellular organelles (condensates), both in the cytoplasm (e.g., stress granules) and in the nucleoplasm (e.g., nucleoli). While both in vivo experiments and studies of synthetic systems demonstrate that LLPS is strongly affected by the presence of a macromolecular elastic network, a fundamental understanding of the role of such networks on LLPS is still lacking. Here we show that, upon accounting for capillary forces responsible for network expulsion, small-scale heterogeneity of the network, and its nonlinear mechanical properties, an intriguing picture of LLPS emerges. Specifically, we predict that, in addition to the experimentally observed cavitated droplets which fully exclude the network, two other phases are thermodynamically possible: elastically arrested, size-limited droplets at the network pore scale, and network-including macroscopic droplets. In particular, pore size-limited droplets may emerge in chromatin networks, with implications for structure and function of nucleoplasmic condensates.
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Surface tension governed by differential adhesion can drive fluid particle mixtures to sort into separate regions, i.e., demix. Does the same phenomenon occur in confluent biological tissues? We begin to answer this question for epithelial monolayers with a combination of theory via a vertex model and experiments on keratinocyte monolayers. Vertex models are distinct from particle models in that the interactions between the cells are shape-based, as opposed to distance-dependent. We investigate whether a disparity in cell shape or size alone is sufficient to drive demixing in bidisperse vertex model fluid mixtures. Surprisingly, we observe that both types of bidisperse systems robustly mix on large lengthscales. On the other hand, shape disparity generates slight demixing over a few cell diameters, a phenomenon we term micro-demixing. This result can be understood by examining the differential energy barriers for neighbor exchanges (T1 transitions). Experiments with mixtures of wild-type and E-cadherin-deficient keratinocytes on a substrate are consistent with the predicted phenomenon of micro-demixing, which biology may exploit to create subtle patterning. The robustness of mixing at large scales, however, suggests that despite some differences in cell shape and size, progenitor cells can readily mix throughout a developing tissue until acquiring means of recognizing cells of different types.
The implementation of natural and artificial proteins with designer properties and functionalities offers unparalleled opportunity for functional nanoarchitectures formed through self-assembly. However, to exploit the opportunities offered we require the ability to control protein assembly into the desired architecture while avoiding denaturation and therefore retaining protein functionality. Here we address this challenge with a model system of fluorescent proteins. Using techniques of self-assembly manipulation inspired by soft matter where interactions between components are controlled to yield the desired structure, we show that it is possible to assemble networks of proteins of one species which we can decorate with another, whose coverage we can tune. Consequently, the interfaces between domains of each component can also be tuned, with applications for example in energy transfer. Our model system of fluorescent proteins eGFP and mCherry retain their fluorescence throughout the assembly process, thus demonstrating that functionality is preserved.
Liquid crystal networks exploit the coupling between the responsivity of liquid-crystalline mesogens, e.g., to electric fields, and the (visco)elastic properties of a polymer network. Because of this, these materials have been put forward for a wide array of applications, including responsive surfaces such as artificial skins and membranes. For such applications, the desired functional response must generally be realized under strict geometrical constraints, such as provided by supported thin films. To model such settings, we present a dynamical, spatially-heterogeneous Landau-type theory for electrically-actuated liquid crystal network films. We find that the response of the liquid crystal network permeates the film from top to bottom, and illustrate how this affects the time scale associated with macroscopic deformation. Finally, by linking our model parameters to experimental quantities, we suggest that the permeation rate can be controlled by varying the aspect ratio of the mesogens and their degree of orientational order when cross-linked into the polymer network, for which we predict a single optimum. Our results contribute specifically to the rational design of future applications involving transport or on-demand release of molecular cargo in liquid crystal network films.
Inspired by active shape morphing in developing tissues and biomaterials, we investigate two generic mechanochemical models where the deformations of a thin elastic sheet are driven by, and in turn affect, the concentration gradients of a chemical signal. We develop numerical methods to study the coupled elastic deformations and chemical concentration kinetics, and illustrate with computations the formation of different patterns depending on shell thickness, strength of mechanochemical coupling and diffusivity. In the first model, the sheet curvature governs the production of a contractility inhibitor and depending on the threshold in the coupling, qualitatively different patterns occur. The second model is based on the stress--dependent activity of myosin motors, and demonstrates how the concentration distribution patterns of molecular motors are affected by the long-range deformations generated by them. Since the propagation of mechanical deformations is typically faster than chemical kinetics (of molecular motors or signaling agents that affect motors), we describe in detail and implement a numerical method based on separation of timescales to effectively simulate such systems. We show that mechanochemical coupling leads to long-range propagation of patterns in disparate systems through elastic instabilities even without the diffusive or advective transport of the chemicals.
Understanding the interactions between viruses and surfaces or interfaces is important, as they provide the principles underpinning the cleaning and disinfection of contaminated surfaces. Yet, the physics of such interactions is currently poorly understood. For instance, there are longstanding experimental observations suggesting that the presence of air-water interfaces can generically inactivate and kill viruses, yet the mechanism underlying this phenomenon remains unknown. Here we use theory and simulations to show that electrostatics provides one such mechanism, and that this is very general. Thus, we predict that the free energy of an RNA virus should increase by several thousands of $k_BT$ as the virion breaches an air-water interface. We also show that the fate of a virus approaching a generic liquid-liquid interface depends strongly on the detailed balance between interfacial and electrostatic forces, which can be tuned, for instance, by choosing different media to contact a virus-laden respiratory droplet. We propose that these results can be used to design effective strategies for surface disinfection. Intriguingly, tunability requires electrostatic and interfacial forces to scale similarly with viral size, which naturally occurs when charges are arranged in a double-shell distribution as in RNA viruses like influenza and all coronaviruses.
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