Mesoscale simulations: An indispensable approach to understand biomembranes

Modeling membranes in situ

Molecular dynamics simulations of cellular membranes have come a long way-from simple model lipid bilayers to multicomponent systems capturing the crowded and complex nature of real cell membranes. In this opinionated minireview, we discuss the current challenge to simulate the dynamics of membranes in their native environment, in situ, with the prospect of reaching the level of whole cells and cell organelles using an integrative modeling framework.

The diffuse interface description of fluid lipid membranes captures key features of the hemifusion pathway and lateral stress profile

Topological transitions of lipid membranes are ubiquitous in key biological processes for cell life, like neurotransmission, fertilization, morphogenesis, and viral infections. Despite this, they are not well understood due to their multiscale nature, which limits the use of molecular models and calls for a mesoscopic approach such as the celebrated Canham-Helfrich one. Unfortunately, such a model cannot handle topological transitions, hiding the crucial involved forces and the appearance of the experimentally observed hemifused intermediates. In this work, we describe the membrane as a diffuse interface preserving the Canham-Helfrich elasticity. We show that pivotal features of the hemifusion pathway are captured by this mesoscopic approach, e.g. a (meta)stable hemifusion state and the fusogenic behavior of negative monolayer spontaneous curvatures. The membrane lateral stress profile is calculated as a function of the elastic rigidities, yielding a coarse-grained version of molecular models findings. Insights into the fusogenic mechanism are reported and discussed.

There and back again: bridging meso- and nano-scales to understand lipid vesicle patterning

We describe a complete methodology to bridge the scales between nanoscale molecular dynamics and (micrometer) mesoscale Monte Carlo simulations in lipid membranes and vesicles undergoing phase separation, in which curving molecular species are furthermore embedded. To go from the molecular to the mesoscale, we notably appeal to physical renormalization arguments enabling us to rigorously infer the mesoscale interaction parameters from its molecular counterpart. We also explain how to deal with the physical timescales at stake at the mesoscale. Simulating the as-obtained mesoscale system enables us to equilibrate the long wavelengths of the vesicles of interest, up to the vesicle size. Conversely, we then backmap from the meso- to the nano-scale, which enables us to equilibrate in turn the short wavelengths down to the molecular length-scales. By applying our approach to the specific situation of patterning a vesicle membrane, we show that macroscopic membranes can thus be equilibrated at all length-scales in achievable computational time offering an original strategy to address the fundamental challenge of timescale in simulations of large bio-membrane systems.

Lattice-based mesoscale simulations and mean-field theory of cell membrane adhesion

Adhesion of cell membranes involves multi-scale phenomena, ranging from specific molecular binding at Angstrom scale all the way up to membrane deformations and phase separation at micrometer scale. Consequently, theory and simulations of cell membrane adhesion require multi-scale modeling and suitable approximations that capture the essential physics of these phenomena. Here, we present a mesoscale model for membrane adhesion which we have employed in a series of our recent studies. This model quantifies, in particular, how nanoscale lipid clusters physically affect and respond to the intercellular receptor-ligand binding that mediates membrane adhesion. The goal of this Chapter is to present all details and subtleties of the mean-field theory and Monte Carlo simulations of this mesoscale model, which can be used to further explore physical phenomena related to cell membrane adhesion.

Mesoscale simulation of biomembranes with FreeDTS

We present FreeDTS software for performing computational research on biomembranes at the mesoscale. In this software, a membrane is represented by a dynamically triangulated surface equipped with vertex-based inclusions to integrate the effects of integral and peripheral membrane proteins. Several algorithms are included in the software to simulate complex membranes at different conditions such as framed membranes with constant tension, vesicles and high-genus membranes with various fixed volumes or constant pressure differences and applying external forces to membrane regions. Furthermore, the software allows the user to turn off the shape evolution of the membrane and focus solely on the organization of proteins. As a result, we can take realistic membrane shapes obtained from, for example, cryo-electron tomography and backmap them into a finer simulation model. In addition to many biomembrane applications, this software brings us a step closer to simulating realistic biomembranes with molecular resolution. Here we provide several interesting showcases of the power of the software but leave a wide range of potential applications for interested users.

The local variation of the Gaussian modulus enables different pathways for fluid lipid vesicle fusion

Viral infections, fertilization, neurotransmission, and many other fundamental biological processes rely on membrane fusion. Straightforward calculations based on the celebrated Canham-Helfrich elastic model predict a large topological energy barrier that prevents the fusion process from being thermally activated. While such high energy is in accordance with the physical barrier function of lipid membranes, it is difficult to reconcile with the biological mechanisms involved in fusion processes. In this work, we use a Ginzburg-Landau type of free energy that recovers the Canham-Helfrich model in the limit of small width-to-vesicle-extension ratio, with the additional ability to handle topological transitions. We show that a local modification of the Gaussian modulus in the merging region both dramatically lowers the elastic energy barrier and substantially changes the minimal energy pathway for fusion, in accordance with experimental evidence. Therefore, we discuss biological examples in which such a modification might play a crucial role.