3 research outputs found

    Structure determination of membrane proteins by electron crystallography

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    A fundamental principle of life is the separation of environments into different compartments. Prokaryotes shield their interior from the environment by a plasma membrane and in some cases also by a cell wall. Eukaryotes refine this compartmentalization by building different organelles for different parts of the cell metabolism. Nevertheless, these different compartments are dependent on each other and are interconnected by membrane proteins that transport specific nutrients, hormones, ions, water and waste products across the membrane and facilitate signal transmission between different compartments. Understanding the structure and function of membrane proteins can therefore allow an enormous insight into the regulation of different metabolic pathways. The electron microscope (EM) proved itself a great tool for studying membrane proteins, offering the unique opportunity to image membrane proteins within a lipid bilayer as close to the natural conditions as possible. Processing of images acquired by an electron microscope poses a challenging task for both scientist and processing hardware. Newly developed and optimized algorithms are needed to improve the image processing to a level that allows atomic resolution to be achieved regularly. Membrane proteins pose a difficult challenge for a structural biologist. To crystallize membrane proteins into well ordered two dimensional (2D) or three dimensional (3D) crystals is one of the most important prerequisites for structural analysis at the atomic level, yet membrane proteins are notoriously difficult to crystallize. One exception may be bacteriorhodopsin, which forms near-perfect crystals already in its native membrane. This may explain the fact that the first 2D electron crystallographic structure determined at 7 Å resolution by Henderson and Unwin[20][43] in 1975 was the structure of bacteriorhodopsin. In 1990 the structure of Br was determined to atomic resolution by Henderson et al.[19], being the first atomic structure of a membrane protein. The structure determination of Br was also the starting point for the mrc program suite, which is widely used at the moment in the, albeit small, 2D electron crystallography community. Using the mrc software Kühlbrandt et al.[26] solved the structure of the light-harvesting chlorophyll a/b-protein complex in 1994. For recording the images they used the spot scan technique developed by Downing in 1991[9]. The first aquaporin water channel determined was aquaporin 1, resolved by Walz et al. in 1997[45] at 6 Å resolution, and subsequently solved to atomic resolution by Murata et al. in 2000[29]. Recently, several more aquaporin structures were determined by 2D electron crystallographic methods, aquaporin-0 (AQP0) by Gonen et al. in 2004[14] at 3 Å and in 2005[13] at 1.9 Å and aquaporin-4 (AQP4) by Hiroaki et al. in 2006[22]. Interestingly, AQP4 shows exactly the same monomer arrangement as SoPIP2;1. The recent publications show that the trend goes from recording solely images to the recording of diffraction data in combination with images or even to recording diffraction data exclusively, and then using methods developed for x-ray crystallography to obtain the phase information. Given the fact that the software available for processing of 2D electron diffraction patterns is less evolved than the one for processing images, and given this new development of increased usage of diffraction patterns, it only makes sense to focus on implementing new and improved programs for 2D electron diffraction processing. In this work I would like to present the advances I achieved in the structural determination of aquaporin 2, as well as my contribution to other projects, in particular the structural investigations of SoPIP2;1 and KdgM. I will also explain the modified sample preparation methods which made data recording at high tilt angles more reliable and achieved an improvement in resolution of the measured data. A second, equally important and detailed part of my thesis is the work invested in improving and extending the image processing to a point where a user, not adept in programming in several languages, can use it and produce good results. For this I improved the functionality and performance at several points, including a strong emphasis on user friendliness and ease of maintenance

    Assembling of Subpictures using Approximate Junctions

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