Dilyana Georgieva

Heterogeneous nucleation of three-dimensional protein nanocrystals.

Nucleation is the rate-limiting step in protein crystallization. Introducing heterogeneous substrates may in some cases lower the energy barrier for nucleation and thereby facilitate crystal growth. To date, the mechanism of heterogeneous protein nucleation remains poorly understood. In this study, the nucleating properties of fragments of human hair in crystallization experiments have been investigated. The four proteins that were tested, lysozyme, glucose isomerase, a polysaccharide-specific Fab fragment and potato serine protease inhibitor, nucleated preferentially on the hair surface. Macrocrystals and showers of tiny crystals of a few hundred nanometres thickness were obtained also under conditions that did not produce crystals in the absence of the nucleating agent. Cryo-electron diffraction showed that the nanocrystals diffracted to at least 4 A resolution. The mechanism of heterogeneous nucleation was studied using confocal fluorescent microscopy which demonstrated that the protein is concentrated on the nucleating surface. A substantial accumulation of protein was observed on the sharp edges of the hairs cuticles, explaining the strong nucleating activity of the surface.

Unit-cell determination from randomly oriented electron-diffraction patterns

An algorithm is described that calculates the most likely primitive unit cell given a set of randomly oriented electron-diffraction patterns with unknown angular relationships.

A novel approximation method of CTF amplitude correction for 3D single particle reconstruction

The typical resolution of three-dimensional reconstruction by cryo-EM single particle analysis is now being pushed up to and beyond the nanometer scale. Correction of the contrast transfer function (CTF) of electron microscopic images is essential for achieving such a high resolution. Various correction methods exist and are employed in popular reconstruction software packages. Here, we present a novel approximation method that corrects the amplitude modulation introduced by the contrast transfer function by convoluting the images with a piecewise continuous function. Our new approach can easily be implemented and incorporated into other packages. The implemented method yielded higher resolution reconstructions with data sets from both highly symmetric and asymmetric structures. It is an efficient alternative correction method that allows quick convergence of the 3D reconstruction and has a high tolerance for noisy images, thus easing a bottleneck in practical reconstruction of macromolecules.

Image processing and lattice determination for three-dimensional nanocrystals.

Three-dimensional nanocrystals can be studied by electron diffraction using transmission cryo-electron microscopy. For molecular structure determination of proteins, such nanosized crystalline samples are out of reach for traditional single-crystal X-ray crystallography. For the study of materials that are not sensitive to the electron beam, software has been developed for determining the crystal lattice and orientation parameters. These methods require radiation-hard materials that survive careful orienting of the crystals and measuring diffraction of one and the same crystal from different, but known directions. However, as such methods can only deal with well-oriented crystalline samples, a problem exists for three-dimensional (3D) crystals of proteins and other radiation sensitive materials that do not survive careful rotational alignment in the electron microscope. Here, we discuss our newly released software AMP that can deal with nonoriented diffraction patterns, and we discuss the progress of our new preprocessing program that uses autocorrelation patterns of diffraction images for lattice determination and indexing of 3D nanocrystals.

Protein Crystal Growth

The biological activity of most proteins is determined by their 3D structure. For instance, a substantial number of molecular diseases are caused by protein structural alterations, which are genetically encoded. Drugs operate by binding to proteins, inducing alteration of their functional structure and thereby affecting their biological activity. Hence the design and improvement of drugs is greatly facilitated by knowledge of the 3D structures of their macromolecular targets. In the light of these considerations, it is clear that elucidation of the 3D structure of proteins is of prime importance for understanding the underlying mechanisms of molecular diseases. It was initially believed that any protein that could be made soluble and could be purified would be relatively easy to crystallize. However, the results have indicated that solubility and purity of proteins, although being important factors, do not secure a yield of useful crystals. The crystallization behavior of proteins turns out to be very complex. In an effort to identify the naturally occurring protein folds, large structural genomics consortia were set up. The somewhat disappointing outcome of these efforts is that only about 3% of all proteins that were targeted by these consortia yielded a crystal structure (http://targetdb.pdb.org/statistics/TargetStatistics.html), despite massive investments in high-throughput, automated protein production, purification and crystallization. It is clear that in order to improve the current situation, better strategies for protein crystallization are required, combined with techniques that allow the use of smaller nano-crystalline material.

Evaluation of Medipix2 detector for recording electron diffraction data in low dose conditions

The drive for elucidation of important macromolecular structures to high resolution in their 3D native or near-native state places continuously higher demands on the quality of the experimental data. For instance, recording of diffraction patterns good enough for structural studies from cryo-preserved bio-macromolecules at low dose conditions remains challenging and highly desirable. The emergence of hybrid pixel detectors opens up new possibilities for direct electron detection and superior detector performance. Here, we report on the characteristics of the Medipix2 detector in diffraction studies, with a special focus on the reliability of the intensities acquired in very low dose conditions. Diffraction data recorded on a Medipix2 detector were assessed in refinement analysis. R-factors lower than 10% were obtained from data recorded at electron dose of 0.05 el/A2. The reproducibility of the data was also shown to be high, given the correlation coefficient of the intensities being higher than 0.9970. The contrast that could be achieved at very low dose conditions was at least an order of magnitude better than that of image plates, based on a direct comparison.

EDIFF: a program for automated unit‐cell determination and indexing of electron diffraction data

EDIFF is a new user-friendly software suite for unit-cell determination of three-dimensional nanocrystals from randomly oriented electron diffraction patterns with unknown independent orientations. It can also be used for three-dimensional cell reconstruction from diffraction tilt series. In neither case is exact knowledge of the angular relationship between the patterns required. The unit cell can be validated and the crystal system assigned. EDIFF can index the reflections in electron diffraction patterns. Thus, EDIFF can be employed as a first step in reconstructing the three-dimensional atomic structure of organic and inorganic molecules and of proteins from diffraction data. An example illustrates the viability of the EDIFF approach.

An Intelligent Peak Search Program for Digital Electron Diffraction Images of 3D Nano-Crystals

Electron diffractograms are lattice images of crystalline samples taken in transmission electron microscopy for molecular structure determination studies. Electron diffraction is a technique widely used in material science and recently it is gaining significance also in life science for studying 2D and 3D organic crystals. However, often the images suffer from strong background noise, masking the data points. Moreover, they suffer also from the strong center beam exposure or a big beam- stop which covers a lot of useful information. This paper presents a user-friendly peak search program in which an autocorrelation algorithm is utilized creatively to intensify the signal and to center the image in the particular regular lattice. An adaptive background removal algorithm is designed to remove the central beam and to reduce the background noise. The latter algorithm can be used for a wide range of applications, such as 2D spectral analysis in physics, NMR Analysis, stars recognition of aerospace photographs.

Electron Diffraction of Protein 3D Nanocrystals

Protein crystallography, being one of the most established methods for structure determination of biomacromolecules, relies on the diffraction analysis using X-rays for 3D (micro-)crystals. Electron diffraction is only employed for single layer 2D nano-crystals. However, there is no established method for analysing multi-layered 3D nano-sized protein crystals. Electron diffraction may fill this important niche, but several problems have to be surmounted for this method to become mainstream. Our group aims tackling some of the bottlenecks, and although our work is still very much in progress, we can report advances in some important areas. Here we summarise improvements in (i) the induction of growth of (nano-)crystals, (ii) electron diffraction data collection using the Medipix quantum area detector, (iii) unit cell determination using single, non- oriented diffraction patterns, (iv) integration of diffraction data and (v) phasing of electron diffraction data.

3D electron diffraction of protein crystals: data collection, cell determination and indexing

Relative to the number of elastic scattering events, X-rays are three orders of magnitude more damaging to organic molecules than electrons, so for structure determination of 3D nano-crystals of proteins and other damage-prone molecules, electron diffraction should be an attractive alternative. For 2D protein crystals, electron diffraction is the only option. For 3D protein crystals, limitations in collecting diffraction data of sufficient quality and dynamical scattering have so far frustrated the promise electrons hold in this respect. Here we report that these problems could, to a certain extent, be overcome by combining modern flash-freezing techniques, low dose diffraction techniques (microdiffraction) and precession of the electron beam. Our procedures, specifically aimed at gathering high-resolution, 3D reciprocal space data, allowed electron diffraction up to 2.1 A resolution of 3D protein nano-crystals (lysozyme, see figure 1) and even beyond 1 A resolution for nano-crystals of complex organic pharmaceuticals. The resulting diffraction patterns of non-oriented crystals could be indexed.