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. 2014 Oct 23;10(10):e1003911.
doi: 10.1371/journal.pcbi.1003911. eCollection 2014 Oct.

Lipid clustering correlates with membrane curvature as revealed by molecular simulations of complex lipid bilayers

Heidi Koldsø  1 , David Shorthouse  1 , Jean Hélie  1 , Mark S P Sansom  1
Affiliations

Lipid clustering correlates with membrane curvature as revealed by molecular simulations of complex lipid bilayers

Heidi Koldsø et al. PLoS Comput Biol. .

Abstract

Cell membranes are complex multicomponent systems, which are highly heterogeneous in the lipid distribution and composition. To date, most molecular simulations have focussed on relatively simple lipid compositions, helping to inform our understanding of in vitro experimental studies. Here we describe on simulations of complex asymmetric plasma membrane model, which contains seven different lipids species including the glycolipid GM3 in the outer leaflet and the anionic lipid, phosphatidylinositol 4,5-bisphophate (PIP2), in the inner leaflet. Plasma membrane models consisting of 1500 lipids and resembling the in vivo composition were constructed and simulations were run for 5 µs. In these simulations the most striking feature was the formation of nano-clusters of GM3 within the outer leaflet. In simulations of protein interactions within a plasma membrane model, GM3, PIP2, and cholesterol all formed favorable interactions with the model α-helical protein. A larger scale simulation of a model plasma membrane containing 6000 lipid molecules revealed correlations between curvature of the bilayer surface and clustering of lipid molecules. In particular, the concave (when viewed from the extracellular side) regions of the bilayer surface were locally enriched in GM3. In summary, these simulations explore the nanoscale dynamics of model bilayers which mimic the in vivo lipid composition of mammalian plasma membranes, revealing emergent nanoscale membrane organization which may be coupled both to fluctuations in local membrane geometry and to interactions with proteins.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Initial and final structures of the plasma membrane.
POPC is shown in light gray, POPE in red, Sph in green, GM3 in magenta, Chol in cyan, POPS in blue and PIP2 in yellow. (A) Side view of the plasma membrane at 5 µs. (B) View of the outer leaflet at 0 and 5 µs, with the GM3 cluster circled in the latter panel. (C) The inner leaflet at 0 and 5 µs.
Figure 2
Figure 2. Fractional interaction matrix of the outer and inner leaflet of the plasma membrane.
The matrix shows the fractional interaction as the relative number of contacts between lipids compared to all other contacts. If a lipid has more than one contact with another lipid this interaction is only counted once. Two lipids are defined as being in contact if the distance between the glycerol ester moiety and amino alcohols is less than 11 Å. Since cholesterol flip-flops between the leaflets during simulations it is not possible to assign these to specific leaflets and has therefore been omitted from this analysis. A fully random distribution of between four lipid types would result in a fraction of 0.25. (A) Fractional interaction of the lipids within the outer leaflet. (B) Fractional interaction of inner leaflet lipids.
Figure 3
Figure 3. Lipid organization within a protein containing plasma membrane model after of 5 µs of simulation.
(A+B) End state of simulations of a 1900 lipid plasma membrane containing sixteen membrane-spanning gp130 receptor proteins. The proteins are colored in different colors and represented by surfaces. The proteins were originally distributed on an evenly spaces grid with 60 Å between proteins. (A) Upper leaflet after 5 µs of simulations time. Proteins are shown in different colors and GM3 is shown in magenta spheres, while the rest of the lipids are shown in gray. (B) Inner leaflet after 5 µs of simulations. PIP2 is shown in yellow spheres and blue spheres illustrate sodium ions within 5 Å of PIP2. (C) Radial distribution functions of lipids around the protein.
Figure 4
Figure 4. Protein-lipid interactions within a plasma membrane model.
Interactions within 6 Å between protein and lipids head groups. (A) The average number of interactions between the protein and lipids mapped into the sequence. (B) Number of interactions between the PO3 bead of PIP2 and amino acid residues within the proteins. (C) Number of interactions between the ROH bead of cholesterol and the residues within the proteins. (D) The average number of contacts between the protein and PIP2 and cholesterol has been mapped into the protein structure. Interactions that are present in more than 50% of the entire simulations have been shown as surfaces.
Figure 5
Figure 5. Lipid organization and interactions between GM3 head groups in a 6000 lipid plasma membrane model.
(A) Plasma membrane composed of 6000 lipids. The same color scheme as Fig. 1 has been applied. (B) Zoom in (see white box of approximately 12 nm in (A)) on interactions between GM3 head groups within the lipid nano-domains. GM3s are represented as magenta coloured sticks. Water beads within 5 Å of GM3 have been shown in cyan and sodium ions within 5 Å of GM3 are shown in yellow. The entire membrane is shown as a white surface.
Figure 6
Figure 6. Membrane curvature and lipid distribution.
(A) Top view of the outer leaflet of the PM6000 membrane colored according the z-position of the interface between the tails and head groups. GM3 is shown in magenta. (B) Cross-correlation between the z-coordinate and the lipid composition of the PM6000 simulation illustrated in (A). (C) Schematic illustration of the correlations between local bilayer geometry and local lipid composition. Thus the concave (downwards) deflections of the bilayer are locally enriched in GM3 and to a lesser extent PE in the outer leaflet of the bilayer, whilst the concave (upwards) deflections are enriched in PIP2, and PE in the inner leaflet of the bilayer.
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