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Pore models of membrane fusion postulate that cylinders of integral membrane proteins can initiate a fusion pore after conformational rearrangement of pore subunits. In the fusion of yeast vacuoles, V-ATPase V0 sectors, which contain a central cylinder of membrane integral proteolipid subunits, associate to form a transcomplex that might resemble an intermediate postulated in some pore models. We tested the role of V0 sectors in vacuole fusion. V0 functions in fusion and proton translocation could be experimentally separated via the differential effects of mutations and inhibitory antibodies. Inactivation of the V0 subunit Vph1p blocked fusion in the terminal reaction stage that is independent of a proton gradient. Deltavph1 mutants were capable of docking and trans-SNARE pairing and of subsequent release of lumenal Ca2+, but they did not fuse. The Ca2+-releasing channel appears to be tightly coupled to V0 because inactivation of Vph1p by antibodies blocked Ca2+ release. Vph1 deletion on only one fusion partner sufficed to severely reduce fusion activity. The functional requirement for Vph1p correlates to V0 transcomplex formation in that both occur after docking and Ca2+ release. These observations establish V0 as a crucial factor in vacuole fusion acting downstream of trans-SNARE pairing.
Pubmed ID: 12876274 RIS Download
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View all literature mentionsNEURON is a simulation environment for modeling individual neurons and networks of neurons. It provides tools for conveniently building, managing, and using models in a way that is numerically sound and computationally efficient. It is particularly well-suited to problems that are closely linked to experimental data, especially those that involve cells with complex anatomical and biophysical properties. NEURON has benefited from judicious revision and selective enhancement, guided by feedback from the growing number of neuroscientists who have used it to incorporate empirically-based modeling into their research strategies. NEURON's computational engine employs special algorithms that achieve high efficiency by exploiting the structure of the equations that describe neuronal properties. It has functions that are tailored for conveniently controlling simulations, and presenting the results of real neurophysiological problems graphically in ways that are quickly and intuitively grasped. Instead of forcing users to reformulate their conceptual models to fit the requirements of a general purpose simulator, NEURON is designed to let them deal directly with familiar neuroscience concepts. Consequently, users can think in terms of the biophysical properties of membrane and cytoplasm, the branched architecture of neurons, and the effects of synaptic communication between cells. * helps users focus on important biological issues rather than purely computational concerns * has a convenient user interface * has a user-extendable library of biophysical mechanisms * has many enhancements for efficient network modeling * offers customizable initialization and simulation flow control * is widely used in neuroscience research by experimentalists and theoreticians * is well-documented and actively supported * is free, open source, and runs on (almost) everything
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