Stability of Biological Membranes upon Mechanical Indentation

Unusual Robustness of Neurotransmitter Vesicle Membranes against Serotonin-Induced Perturbations

Nature confines hundreds of millimolar of amphiphilic neurotransmitters, such as serotonin, in synaptic vesicles. This appears to be a puzzle, as the mechanical properties of lipid bilayer membranes of individual major polar lipid constituents of synaptic vesicles [phosphatidylcholine (PC), phosphatidylethanolamine (PE), and phosphatidylserine (PS)] are significantly affected by serotonin, sometimes even at few millimolar concentrations. These properties are measured by atomic force microscopy, and their results are corroborated by molecular dynamics simulations. Complementary ²H solid-state NMR measurements also show that the lipid acyl chain order parameters are strongly affected by serotonin. The resolution of the puzzle lies in the remarkably different properties displayed by the mixture of these lipids, at molar ratios mimicking those of natural vesicles (PC:PE:PS:Cholesterol = 3:5:2:5). Bilayers constituting of these lipids are minimally perturbed by serotonin, and show only a graded response at physiological concentrations (>100 mM). Significantly, the cholesterol (up to 33% molar ratio) plays only a minor role in dictating these mechanical perturbations, with PC:PE:PS:Cholesterol = 3:5:2:5 and 3:5:2:0 showing similar perturbations. We infer that nature uses an emergent mechanical property of a specific mixture of lipids, all individually vulnerable to serotonin, to appropriately respond to physiological serotonin levels.

A new method for the construction of coarse-grained models of large biomolecules from low-resolution cryo-electron microscopy data

The rapid development of cryo-electron microscopy (cryo-EM) has led to the generation of significant low-resolution electron density data of biomolecules. However, the atomistic details of huge biomolecules usually cannot be obtained because it is very difficult to construct all-atom models for MD simulations. Thus, it is still a challenge to make use of the rich low-resolution cryo-EM data for computer simulation and functional study. In this study, we proposed a new method called Convolutional and K-means Coarse-Graining (CK-CG) for the efficient coarse-graining of large biological systems. Using the CK-CG method, we could directly map the cryo-EM data into coarse-grained (CG) beads. Furthermore, the CG beads were parameterized with an empirical harmonic potential to construct a new CG model. We subjected the CK-CG models of the fibrillar protein assemblies F-actin and collagen to external forces in pulling dynamic simulations to assess their mechanical response. The agreement between the estimated tensile stiffness between CG models and experiments demonstrates the validity of the CK-CG method. Thus, our method provides a practical strategy for the direct construction of a structural model from low-resolution data for biological function studies.

Curvature-driven adsorption of cationic nanoparticles to phase boundaries in multicomponent lipid bilayers

Understanding the interactions between surface-functionalized gold nanoparticles (NPs) and lipid bilayers is necessary to guide the design of NPs for biomedical applications. Recent experiments found that cationic NPs adsorb more strongly to phase-separated multicomponent lipid bilayers than single-component liquid-disordered bilayers, suggesting that phase separation affects NP-bilayer interactions. In this work, we use coarse-grained molecular dynamics simulations to investigate the effect of lipid phase behavior on the adsorption of small cationic NPs. We first determined the free energy change for adsorbing a NP to one-phase liquid-disordered and one-phase liquid-ordered bilayers. The simulations indicate that NP adsorption depends on a competition between favorable NP-lipid interactions and the unfavorable curvature deformation of the bilayer, resulting in stronger interactions with the liquid-disordered bilayer due to its lower bending modulus. We then measured the free energy change associated with moving a NP across the surface of a phase-separated bilayer and identified a free energy minimum at the phase boundary. The free energy minimum is attributed to the thickness gradient between the two phases that enables favorable NP-lipid interactions without necessitating large curvature deformations. The simulation results thus indicate that the intrinsic curvature present at phase boundaries drives preferential interactions with surface-adsorbed NPs, providing new insight into the forces that drive NP behavior at multicomponent, phase-separated lipid bilayers.