Structure determination of membrane proteins by electron crystallography

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.