Emergent membrane morphologies in relaxed and tense membranes in presence of reversible adhesive pinning interactions

Direct and cell-mediated EV-ECM interplay

Extracellular vesicles (EV) are a heterogeneous group of lipid particles excreted by cells. They play an important role in regeneration, development, inflammation, and cancer progression, together with the extracellular matrix (ECM), which they constantly interact with. In this review, we discuss direct and indirect interactions of EVs and the ECM and their impact on different physiological processes. The ECM affects the secretion of EVs, and the properties of the ECM and EVs modulate EVs' diffusion and adhesion. On the other hand, EVs can affect the ECM both directly through enzymes and indirectly through the modulation of the ECM synthesis and remodeling by cells. This review emphasizes recently discovered types of EVs bound to the ECM and isolated by enzymatic digestion, including matrix-bound nanovesicles (MBV) and tissue-derived EV (TiEV). In addition to the experimental studies, computer models of the EV-ECM-cell interactions, from all-atom models to quantitative pharmacology models aiming to improve our understanding of the interaction mechanisms, are also considered. STATEMENT OF SIGNIFICANCE: Application of extracellular vesicles in tissue engineering is an actively developing area. Vesicles not only affect cells themselves but also interact with the matrix and change it. The matrix also influences both cells and vesicles. In this review, different possible types of interactions between vesicles, matrix, and cells are discussed. Furthermore, the united EV-ECM system and its regulation through the cellular activity are presented.

Crowding-induced membrane remodeling: Interplay of membrane tension, polymer density, architecture

The plasma membrane hosts a wide range of biomolecules, mainly proteins and carbohydrates, that mediate cellular interactions with its environment. The crowding of such biomolecules regulates cellular morphologies and cellular trafficking. Recent discoveries have shown that the structure and density of cell surface polymers and hence the signaling machinery change with the state of the cell, especially in cancer progression. The alterations in membrane-attached glycocalyx and glycosylation of proteins and lipids are common features of cancer cells. The overexpression of glycocalyx polymers, such as mucin and hyaluronan, strongly correlates with cancer metastasis. Here, we present a mesoscale biophysics-based model that accounts for the shape regulation of membranes by crowding of membrane-attached biopolymer-glycocalyx and actin networks. Our computational model is based on the dynamically triangulated Monte Carlo model for membranes and coarse-grained representations of polymer chains. The model allows us to investigate the crowding-induced shape transformations in cell membranes in a tension- and graft polymer density-dependent manner. Our results show that the number of membrane protrusions and their shape depend on membrane tension, with higher membrane tension inducing more tubular protrusions than the vesicular shapes formed at low tension at high surface coverage of polymers. The shape transformations occur above the threshold density predicted by the polymer brush theory, but this threshold also depends on the membrane tension. Increasing the size of the polymer, either by changing the length or by adding side chains, is shown to increase the crowding-induced curvature. The effect of crowding is more prominent for flexible polymers than for semiflexible rigid polymers. We also present an extension of the model that incorporates properties of the actin-like filament networks and demonstrate how tubular structures can be generated by biopolymer crowding on the cytosolic side of cell membranes.

Data driven and biophysical insights into the regulation of trafficking vesicles by extracellular matrix stiffness

Biomechanical signals from remodeled extracellular matrix (ECM) promote tumor progression. Here, we show that cell-matrix and cell-cell communication may be inherently linked and tuned through mechanisms of mechanosensitive biogenesis of trafficking vesicles. Pan-cancer analysis of cancer cells' mechanical properties (focusing primarily on cell stiffness) on substrates of varied stiffness and composition elucidated a heterogeneous cellular response to mechanical stimuli. Through machine learning, we identified a fingerprint of cytoskeleton-related proteins that accurately characterize cell stiffness in different ECM conditions. Expression of their respective genes correlates with patient prognosis across different tumor types. The levels of selected cytoskeleton proteins indicated that cortical tension mirrors the increase (or decrease) in cell stiffness with a change in ECM stiffness. A mechanistic biophysical model shows that the tendency for curvature generation by curvature-inducing proteins has an ultrasensitive dependence on cortical tension. This study thus highlights the effect of ECM stiffness, mediated by cortical tension, in modulating vesicle biogenesis.

Quantification of Curvature Sensing Behavior of Curvature-Inducing Proteins on Model Wavy Substrates

Curvature-inducing proteins are involved in a variety of membrane remodeling processes in the cell. Several in vitro experiments have quantified the curvature sensing behavior of these proteins in model lipid systems. One such system consists of a membrane bilayer laid atop a wavy substrate (Hsieh in Langmuir 28:12838-12843, 2012). In these experiments, the bilayer conforms to the wavy substrate, and curvature-inducing proteins show preferential segregation on the wavy membrane. Using a mesoscale computational membrane model based on the Helfrich Hamiltonian, here we present a study which analyzes the curvature sensing characteristics of this membrane-protein system, and elucidates key physical principles governing protein segregation on the wavy substrate and other in vitro systems. In this article we compute the local protein densities from the free energy landscape associated with membrane remodeling by curvature-inducing proteins. In specific, we use the Widom insertion technique to compute the free energy landscape for an inhomogeneous system with spatially varying density and the results obtained with this minimal model show excellent agreement with experimental studies that demonstrate the association between membrane curvature and local protein density. The free energy-based framework employed in this study can be used for different membrane morphologies and varied protein characteristics to gain mechanistic insights into protein sorting on membranes.

Biophysical Considerations in the Rational Design and Cellular Targeting of Flexible Polymeric Nanoparticles

How nanoparticle (NP) mechanical properties impact multivalent ligand-receptor-mediated binding to cell surfaces, the avidity, propensity for internalization, and effects due to crowding remains unknown or unquantified. Through computational analyses, the effects of NP composition from soft, deformable NPs to rigid spheres, effect of tethers, the crowding of NPs at the membrane surface, and the cell membrane properties such as cytoskeletal interactions are addressed. Analyses of binding mechanisms of three distinct NPs that differ in type and rigidity (core-corona flexible NP, rigid NP, and rigid-tethered NP) but are otherwise similar in size and ligand surface density are reported; moreover, for the case of flexible NP, NP stiffness is tuned by varying the internal crosslinking density. Biophysical modeling of NP binding to membranes together with thermodynamic analysis powered by free energy calculations is employed, and it is shown that efficient cellular targeting and uptake of NP functionalized with targeting ligand molecules can be shaped by factors including NP flexibility and crowding, receptor-ligand binding avidity, state of the membrane cytoskeleton, and curvature inducing proteins. Rational design principles that confer tension, membrane excess area, and cytoskeletal sensing properties to the NP which can be exploited for cell-specific targeting of NP are uncovered.

Interorganelle communication and membrane shaping in the early secretory pathway

Biomolecules in the secretory pathway use membrane trafficking for reaching their final intracellular destination or for secretion outside the cell. This highly dynamic and multipartite process involves different organelles that communicate to one another while maintaining their identity, shape, and function. Recent studies unraveled new mechanisms of interorganelle communication that help organize the early secretory pathway. We highlight how the spatial proximity between endoplasmic reticulum (ER) exit sites and early Golgi elements provides novel means of ER-Golgi communication for ER export. We also review recent findings on how membrane contact sites between the ER and the trans-Golgi membranes can sustain anterograde traffic out of the Golgi complex.

Membrane signalosome: where biophysics meets systems biology

We opine on the recent advances in experiments and modeling of modular signaling complexes assembled on mammalian cell membranes (membrane signalosomes) in the context of several applications including intracellular trafficking, cell migration, and immune response. Characterizing the individual components of the membrane assemblies at the nanoscale, ranging from protein-lipid and protein-protein interactions, to membrane morphology, and the energetics of emergent assemblies at the subcellular to cellular scales pose significant challenges. Overcoming these challenges through the iterative coupling of multiscale modeling and experiment can be transformative in terms of addressing the gaps between structural biology and super-resolution microscopy, as it holds the key to the discovery of fundamental mechanisms behind the emergence of function in the membrane signalosome.

Multiscale modeling of protein membrane interactions for nanoparticle targeting in drug delivery

Nanoparticle (NP)-based imaging and drug delivery systems for systemic (e.g. intravenous) therapeutic and diagnostic applications are inherently a complex integration of biology and engineering. A broad range of length and time scales are essential to hydrodynamic and microscopic molecular interactions mediating NP (drug nanocarriers, imaging agents) motion in blood flow, cell binding/uptake, and tissue accumulation. A computational model of time-dependent tissue delivery, providing in silico prediction of organ-specific accumulation of NPs, can be leveraged in NP design and clinical applications. In this article, we provide the current state-of-the-art and future outlook for the development of predictive models for NP transport, targeting, and distribution through the integration of new computational schemes rooted in statistical mechanics and transport. The resulting multiscale model will comprehensively incorporate: (i) hydrodynamic interactions in the vascular scales relevant to NP margination; (ii) physical and mechanical forces defining cellular and tissue architecture and epitope accessibility mediating NP adhesion; and (iii) subcellular and paracellular interactions including molecular-level targeting impacting NP uptake.

Thermodynamic analysis of multivalent binding of functionalized nanoparticles to membrane surface reveals the importance of membrane entropy and nanoparticle entropy in adhesion of flexible nanoparticles

We present a quantitative model for multivalent binding of ligand-coated flexible polymeric nanoparticles (NPs) to a flexible membrane expressing receptors. The model is developed using a multiscale computational framework by coupling a continuum field model for the cell membrane with a coarse-grained model for the polymeric NPs. The NP is modeled as a self-avoiding bead-spring polymer chain, and the cell membrane is modeled as a triangulated surface using the dynamically triangulated Monte Carlo method. The nanoparticle binding affinity to a cell surface is mainly determined by the delicate balance between the enthalpic gain due to the multivalent ligand-receptor binding and the entropic penalties of various components including receptor translation, membrane undulation, and NP conformation. We have developed new methods to compute the free energy of binding, which includes these enthalpy and entropy terms. We show that the multivalent interactions between the flexible NP and the cell surface are subject to entropy-enthalpy compensation. Three different entropy contributions, namely, those due to receptor-ligand translation, NP flexibility, and membrane undulations, are all significant, although the first of these terms is the most dominant. However, both NP flexibility and membrane undulations dictate the receptor-ligand translational entropy making the entropy compensation context-specific, i.e., dependent on whether the NP is rigid or flexible, and on the state of the membrane given by the value of membrane tension or its excess area.