Searching across hundreds of databases
Proteins contained on purified COPII vesicles were analyzed by matrix-assisted laser desorption ionization mass spectrometry combined with database searching. We identified four known vesicle proteins (Erv14p, Bet1p, Emp24p, and Erv25p) and an additional nine species (Yip3p, Rer1p, Erp1p, Erp2p, Erv29p, Yif1p, Erv41p, Erv46p, and Emp47p) that had not been localized to ER vesicles. Using antibodies, we demonstrate that these proteins are selectively and efficiently packaged into COPII vesicles. Three of the newly identified vesicle proteins (Erv29p, Erv41p, and Erv46p) represent uncharacterized integral membrane proteins that are conserved across species. Erv41p and Erv46p were further characterized. These proteins colocalized to ER and Golgi membranes and exist in a detergent-soluble complex that was isolated by immunoprecipitation. Yeast strains lacking Erv41p and/or Erv46p are viable but display cold sensitivity. The expression levels of Erv41p and Erv46p are interdependent such that Erv46p was reduced in an erv41Delta strain, and Erv41p was not detected in an erv46Delta strain. When the erv41Delta or ev46Delta alleles were combined with other mutations in the early secretory pathway, altered growth phenotypes were observed in some of the double mutant strains. A cell-free assay that reproduces transport between the ER and Golgi indicates that deletion of the Erv41p-Erv46p complex influences the membrane fusion stage of transport.
Pubmed ID: 11157978 RIS Download
Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.
NEURON 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
View all literature mentionsThe SciCrunch Infrastructure was developed as a cooperative data platform to be used by diverse communities in making data more FAIR.
scicrunch.org
