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. 2007 Nov;3(11):e220.
doi: 10.1371/journal.pcbi.0030220. Epub 2007 Sep 26.

Control of membrane fusion mechanism by lipid composition: predictions from ensemble molecular dynamics

Peter M Kasson  1 , Vijay S Pande
Affiliations

Control of membrane fusion mechanism by lipid composition: predictions from ensemble molecular dynamics

Peter M Kasson et al. PLoS Comput Biol. 2007 Nov.

Abstract

Membrane fusion is critical to biological processes such as viral infection, endocrine hormone secretion, and neurotransmission, yet the precise mechanistic details of the fusion process remain unknown. Current experimental and computational model systems approximate the complex physiological membrane environment for fusion using one or a few protein and lipid species. Here, we report results of a computational model system for fusion in which the ratio of lipid components was systematically varied, using thousands of simulations of up to a microsecond in length to predict the effects of lipid composition on both fusion kinetics and mechanism. In our simulations, increased phosphatidylcholine content in vesicles causes increased activation energies for formation of the initial stalk-like intermediate for fusion and of hemifusion intermediates, in accordance with previous continuum-mechanics theoretical treatments. We also use our large simulation dataset to quantitatively compare the mechanism by which vesicles fuse at different lipid compositions, showing a significant difference in fusion kinetics and mechanism at different compositions simulated. As physiological membranes have different compositions in the inner and outer leaflets, we examine the effect of such asymmetry, as well as the effect of membrane curvature on fusion. These predicted effects of lipid composition on fusion mechanism both underscore the way in which experimental model system construction may affect the observed mechanism of fusion and illustrate a potential mechanism for cellular regulation of the fusion process by altering membrane composition.

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Conflict of interest statement

Competing interests. The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Reaction Rates and Mechanisms for Vesicle Fusion
(A) Representative structures from unfused vesicles and each major fusion intermediate: unfused vesicles, a stalk-like state, a hemifused intermediate, and fully fused vesicles. Vesicles fuse either via a direct pathway from stalk-like to fully fused (i) or via an indirect pathway (ii) using a metastable hemifused intermediate. Surfaces rendered in gray represent solvent-accessible area; red and green spheres denote the inner-leaflet phosphate groups of each vesicle respectively. (B–D) Reaction rates in s−1 determined for each reaction pathway at each lipid composition. (B) Rate for pure POPE. (C) Rate for for 1:1 POPC:POPE. (D) Rate for for 2:1 POPC:POPE. Hemifused 1 and Hemifused 2 denote structurally similar late-hemifused states; kinetic differentiation of these states was determined by kinetic consistency analysis (see Methods). Hemifusion occupies a sufficiently large area of state space that inverconversion between some hemifused microstates is slow, resulting in kinetic differentiation.
Figure 2
Figure 2. Starting Structures for Vesicles at Three Different Lipid Compositions
(A) Pure POPE vesicles. (B) Vesicles composed of a 1:1 POPC:POPE mixture. (C) Vesicles composed of a 2:1 POPC:POPE mixture. POPE lipids are rendered in pink, POPC in purple. Rendered surfaces represent the solvent-accessible surface of the vesicle; spheres represent the phosphate groups of the vesicle inner leaflet lipids. Vesicles are linked by a single crosslinker molecule.
Figure 3
Figure 3. Kinetics of Vesicle Fusion Simulated at Different Lipid Compositions
The relative concentrations of fusion intermediates and fused vesicles are plotted for each time point of the simulation for (A) pure POPE, (B) a 1:1 POPC:POPE mixture, and (C) a 2:1 POPC:POPE mixture. Predictions are derived from MSM analysis of all fusion trajectories. Dotted lines represent 90% CIs.
Figure 4
Figure 4. POPC Content Associated with Decreased Formation and Decreased Stability of the Hemifused State
(A) The fraction of all trajectories that form a hemifused state is plotted for each vesicle composition. Vesicles with greater POPC content are less likely to form hemifused states. (B) The time-evolution of the hemifused state is plotted for each vesicle composition. In vesicles with greater POPC content, the hemifused state is less stable and decays more quickly to form fully fused vesicles. Dashed lines represent 90% CIs. Because vesicles containing a 2:1 ratio of POPC:POPE rarely form hemifused intermediates, the sampling uncertainty for the reaction of hemifused vesicles is proportionately greater.
Figure 5
Figure 5. Variation of Transition State Energy with Lipid Composition
Plotted are ΔΔG‡ values for transition state energies calculated with respect to fusion of pure POPE vesicles. Transition state energies are determined as specified in Table S2, and error bars represent 99% CIs determined via nonparametric analysis.
Figure 6
Figure 6. Dependence of Stalk Formation on Fraction POPC in Outer Leaflet
Plotted are average times for reaction of unfused vesicles to initiate a hemifusion stalk, as determined by analysis of simulations with differing inner and outer leaflet compositions. Stalk formation times are plotted for both 15 nm vesicles (diamonds) and 19 nm vesicles (triangles); single-exponential fits to the data are shown (r 2 = 0.88). Linear fits to the data yield r 2 values of 0.67 (0.79 with the 0% POPC datapoint omitted) and 0.81, respectively. Initial stalk formation is assessed here by mixing of >10 lipids between vesicle outer leaflets.
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