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Register a new userAtomic force microscopy (AFM) study of thick lamellar stacks of phospholipid bilayers
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Added by
Maikel Rheinstadter
Publication date
2007
fields
Physics
and research's language is
English
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We report an Atomic Force Microscopy (AFM) study on thick multi lamellar stacks of approx. 10 mum thickness (about 1500 stacked membranes) of DMPC (1,2-dimyristoyl-sn-glycero-3-phoshatidylcholine) deposited on silicon wafers. These thick stacks could be stabilized for measurements under excess water or solution. From force curves we determine the compressional modulus B and the rupture force F_r of the bilayers in the gel (ripple), the fluid phase and in the range of critical swelling close to the main transition. AFM allows to measure the compressional modulus of stacked membrane systems and values for B compare well to values reported in the literature. We observe pronounced ripples on the top layer in the Pbeta (ripple) phase and find an increasing ripple period Lambda_r when approaching the temperature of the main phase transition into the fluid Lalpha phase at about 24 C. Metastable ripples with 2Lambda_r are observed. Lambda_r also increases with increasing osmotic pressure, i.e., for different concentrations of polyethylene glycol (PEG).
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Droplet interface bilayers are a convenient model system to study the physio-chemical properties of phospholipid bilayers, the major component of the cell membrane. The mechanical response of these bilayers to various external mechanical stimuli is an active area of research due to implications for cellular viability and development of artificial cells. In this manuscript we characterize the separation mechanics of droplet interface bilayers under step strain using a combination of experiments and numerical modeling. Initially, we show that the bilayer surface energy can be obtained using principles of energy conservation. Subsequently, we subject the system to a step strain by separating the drops in a step wise manner, and track the evolution of the bilayer contact angle and radius. The relaxation time of the bilayer contact angle and radius, along with the decay magnitude of the bilayer radius were observed to increase with each separation step. By analyzing the forces acting on the bilayer and the rate of separation, we show that the bilayer separates primarily through the peeling process with the dominant resistance to separation coming from viscous dissipation associated with corner flows. Finally, we explain the intrinsic features of the observed bilayer separation by means of a mathematical model comprising of the Young-Laplace equation and an evolution equation. We believe that the reported experimental and numerical results extend the scientific understanding of lipid bilayer mechanics, and that the developed experimental and numerical tools offer a convenient platform to study the mechanics of other types of bilayers.
This paper develops a resolution enhancement method for post-processing the images from Atomic Force Microscopy (AFM). This method is based on deep learning neural networks in the AFM topography measurements. In this study, a very deep convolution neural network is developed to derive the high-resolution topography image from the low-resolution topography image. The AFM measured images from various materials are tested in this study. The derived high-resolution AFM images are comparable with the experimental measured high-resolution images measured at the same locations. The results suggest that this method can be developed as a general post-processing method for AFM image analysis.
We summarize and compare recent Molecular Dynamics simulations on the interactions of dipalmitoylphosphatidylcholine (DPPC) bilayers in the liquid crystalline phase with a number of small molecules including trehalose, a disaccharide of glucose, alcohols, and dimethylsulfoxide (DMSO). The sugar molecules tend to stabilize the structure of the bilayer as they bridge adjacent lipid headgroups. They do not strongly change the structure of the bilayer. Alcohols and DMSO destabilize the bilayer as they increase its area per molecule in the bilayer plane and decrease the order parameter. Alcohols have a stronger detrimental effect than DMSO. The observables which we compare are the area per molecule in the plane of the bilayer, the membrane thickness, and the NMR order parameter of DPPC hydrocarbon tails. The area per molecule and the order parameter are very well correlated whereas the bilayer thickness is not necessarily correlated with them.
We use a long, all-atom molecular dynamics (MD) simulation combined with theoretical modeling to investigate the dynamics of selected lipid atoms and lipid molecules in a hydrated diyristoyl-phosphatidylcholine (DMPC) lipid bilayer. From the analysis of a 0.1 $mu$s MD trajectory we find that the time evolution of the mean square displacement, [delta{r}(t)]^2, of lipid atoms and molecules exhibits three well separated dynamical regions: (i) ballistic, with [delta{r}(t)]^2 ~ t^2 for t < 10 fs; (ii) subdiffusive, with [delta{r}(t)]^2 ~ t^{beta} with beta<1, for 10 ps < t < 10 ns; and (iii) Fickian diffusion, with [delta{r}(t)]^2 ~ t for t > 30 ns. We propose a memory function approach for calculating [delta{r}(t)]^2 over the entire time range extending from the ballistic to the Fickian diffusion regimes. The results are in very good agreement with the ones from the MD simulations. We also examine the implications of the presence of the subdiffusive dynamics of lipids on the self-intermediate scattering function and the incoherent dynamics structure factor measured in neutron scattering experiments.
This paper reports all-atom computer simulations of five phospholipid membranes (DMPC, DPPC, DMPG, DMPS, and DMPSH) with focus on the thermal equilibrium fluctuations of volume, energy, area, thickness, and chain order. At constant temperature and pressure, volume and energy exhibit strong correlations of their slow fluctuations (defined by averaging over 0.5 nanosecond). These quantities, on the other hand, do not correlate significantly with area, thickness, or chain order. The correlations are mainly reported for the fluid phase, but we also give some results for the ordered (gel) phase of two membranes, showing a similar picture. The cause of the observed strong correlations is identified by splitting volume and energy into contributions from tails, heads, and water, and showing that the slow volume-energy fluctuations derive from van der Waals interactions of the tail region; they are thus analogous to the similar strong correlations recently observed in computer simulations of the Lennard-Jones and other simple van der Waals type liquids [U. R. Pedersen et al., Phys. Rev. Lett. 2008, 100, 015701]. The strong correlations reported here confirm one crucial assumption of a recent theory for nerve signal propagation proposed by Heimburg and Jackson [T. Heimburg and A. D. Jackson, Proc. Natl. Acad. Sci. 2005, 102, 9790-9795].
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