Abstract

During neurotransmitter release, curved synaptic vesicles fuse with un-curved pre-synaptic plasma membrane, leading to the merger of two lipid bilayers and the release of neurotransmitters. Our previous efforts to model this system have employed two populations of highly curved vesicles, while others have used two populations of vesicles having ill-defined but lower curvature. Here we examine poly ethylene glycol (PEG)-triggered fusion of highly curved (SUV) with relatively un-curved (LUV) vesicles, composed of a mixture of DOPC/DOPE/sphingomeylin/DOPS/cholesterol (32/25/15/8/20), which closely models the lipid composition of synaptic vesicles. Lipid mixing (LM), contents mixing (CM) and leakage (L) time courses were fitted globally to 3- or 4-state sequential models (Weinreb, Biophys. J., 2007), from which we obtained estimates of rate constants for conversion between states as well as probabilities of LM, CM and L for each state. As expected, un-curved LUV-LUV fusion was barely detectable, while highly curved SUV-SUV fusion was reasonably efficient, saturating at ∼50% LM and ∼40% CM. Remarkably, SUV-LUV fusion was decidedly more efficient, saturating at nearly 100% LM and CM. Analysis of the fusion kinetics at different temperatures (17°-42°C) revealed complex activation thermodynamics. The rate of the first fusion intermediate formation is decidedly faster in the highly curved (stressed) SUV-SUV system than in the mixed system, with increasing temperature shifting the probability of CM toward earlier steps; whereas the probability of CM in SUV-LUV fusion shifts towards fusion pore. This suggests that mismatched curvature promotes more efficient and productive fusion events. Supported by NIGMS grants GM000678 to UNC and GM32707 to BRL.

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