GENFIRE: A generalized Fourier iterative reconstruction algorithm for high-resolution 3D imaging

Tomography has made a radical impact on diverse fields ranging from the study of 3D atomic arrangements in matter to the study of human health in medicine. Despite its very diverse applications, the core of tomography remains the same, that is, a mathematical method must be implemented to reconstruct the 3D structure of an object from a number of 2D projections. In many scientific applications, however, the number of projections that can be measured is limited due to geometric constraints, tolerable radiation dose and/or acquisition speed. Thus it becomes an important problem to obtain the best-possible reconstruction from a limited number of projections. Here, we present the mathematical implementation of a tomographic algorithm, termed GENeralized Fourier Iterative REconstruction (GENFIRE). By iterating between real and reciprocal space, GENFIRE searches for a global solution that is concurrently consistent with the measured data and general physical constraints. The algorithm requires minimal human intervention and also incorporates angular refinement to reduce the tilt angle error. We demonstrate that GENFIRE can produce superior results relative to several other popular tomographic reconstruction techniques by numerical simulations, and by experimentally by reconstructing the 3D structure of a porous material and a frozen-hydrated marine cyanobacterium. Equipped with a graphical user interface, GENFIRE is freely available from our website and is expected to find broad applications across different disciplines.Comment: 18 pages, 6 figure

High-resolution ab initio three-dimensional X-ray diffraction microscopy

Coherent X-ray diffraction microscopy is a method of imaging non-periodic isolated objects at resolutions only limited, in principle, by the largest scattering angles recorded. We demonstrate X-ray diffraction imaging with high resolution in all three dimensions, as determined by a quantitative analysis of the reconstructed volume images. These images are retrieved from the 3D diffraction data using no a priori knowledge about the shape or composition of the object, which has never before been demonstrated on a non-periodic object. We also construct 2D images of thick objects with infinite depth of focus (without loss of transverse spatial resolution). These methods can be used to image biological and materials science samples at high resolution using X-ray undulator radiation, and establishes the techniques to be used in atomic-resolution ultrafast imaging at X-ray free-electron laser sources.Comment: 22 pages, 11 figures, submitte

Iterative projection algorithms and applications in x-ray crystallography

X-ray crystallography is a technique for determining the structure (positions of atoms in space) of molecules. It is a well developed technique, and is applied routinely to both small inorganic and large organic molecules. However, the determination of the structures of large biological molecules by x-ray crystallography can still be an experimentally and computationally expensive task. The data in an x-ray experiment are the amplitudes of the Fourier transform of the electron density in the crystalline specimen. The structure determination problem in x-ray crystallography is therefore identical to a phase retrieval problem in image reconstruction, for which iterative transform algorithms are a common solution method. This thesis is concerned with iterative projection algorithms, a generalized and more powerful version of iterative transform algorithms, and their application to macromolecular x-ray crystallography. A detailed study is made of iterative projection algorithms, including their properties, convergence, and implementations. Two applications to macromolecular crystallography are then investigated. The first concerns reconstruction of binary image and the application of iterative projection algorithms to determining molecular envelopes from x-ray solvent contrast variation data. An effective method for determining molecular envelopes is developed. The second concerns the use of symmetry constraints and the application of iterative projection algorithms to ab initio determination of macromolecular structures from crystal diffraction data. The algorithm is tested on an icosahedral virus and a protein tetramer. The results indicate that ab initio phasing is feasible for structures containing 4-fold or 5-fold non-crystallographic symmetry using these algorithms if an estimate of the molecular envelope is available

Three-dimensional reconstruction of Heterocapsa circularisquama RNA virus by cryo-electron microscopy

Heterocapsa circularisquama RNA virus is a non-enveloped icosahedral ssRNA virus infectious to the harmful bloom-forming dinoflagellate, H. circularisquama, and which is assumed to be the major natural agent controlling the host population. The viral capsid is constructed from a single gene product. Electron cryo-microscopy revealed that the virus has a diameter of 34 nm and T53 symmetry. The 180 quasi-equivalent monomers have an unusual arrangement in that each monomer contributes to a ‘bump’ on the surface of the protein. Though the capsid protein probably has the classic ‘jelly roll’ b-sandwich fold, this is a new packing arrangement and is distantly related to the other positive-sense ssRNA virus capsid proteins. The handedness of the structure has been determined by a novel method involving high resolution scanning electron microscopy of the negatively stained viruses and secondary electron detection

Extracting the Structure and Conformations of Biological Entities from Large Datasets

In biology, structure determines function, which often proceeds via changes in conformation. Efficient means for determining structure exist, but mapping conformations continue to present a serious challenge. Single-particles approaches, such as cryogenic electron microscopy (cryo-EM) and emerging diffract & destroy X-ray techniques are, in principle, ideally positioned to overcome these challenges. But the algorithmic ability to extract information from large heterogeneous datasets consisting of unsorted snapshots - each emanating from an unknown orientation of an object in an unknown conformation - remains elusive. It is the objective of this thesis to describe and validate a powerful suite of manifold-based algorithms able to extract structural and conformational information from large datasets. These computationally efficient algorithms offer a new approach to determining the structure and conformations of viruses and macromolecules. After an introduction, we demonstrate a distributed, exact k-Nearest Neighbor Graph (k-NNG) construction method, in order to establish a firm algorithmic basis for manifold-based analysis. The proposed algorithm uses Graphics Processing Units (GPUs) and exploits multiple levels of parallelism in distributed computational environment and it is scalable for different cluster sizes, with each compute node in the cluster containing multiple GPUs. Next, we present applications of manifold-based analysis in determining structure and conformational variability. Using the Diffusion Map algorithm, a new approach is presented, which is capable of determining structure of symmetric objects, such as viruses, to 1/100th of the object diameter, using low-signal diffraction snapshots. This is demonstrated by means of a successful 3D reconstruction of the Satellite Tobacco Necrosis Virus (STNV) to atomic resolution from simulated diffraction snapshots with and without noise. We next present a new approach for determining discrete conformational changes of the enzyme Adenylate kinase (ADK) from very large datasets of up to 20 million snapshots, each with ~104 pixels. This exceeds by an order of magnitude the largest dataset previously analyzed. Finally, we present a theoretical framework and an algorithmic pipeline for capturing continuous conformational changes of the ribosome from ultralow-signal (-12dB) experimental cryo-EM. Our analysis shows a smooth, concerted change in molecular structure in two-dimensional projection, which might be indicative of the way the ribosome functions as a molecular machine. The thesis ends with a summary and future prospects

Modeling Techniques for the High-Resolution Interpretation of Cryo-Electron Microscopy Reconstructions

Essential biological processes are governed by organized, dynamic interactions between multiple biomolecular systems. Complexes are thus formed to enable the biological function and get dissembled as the process is completed. Examples of such processes include the translation of the messenger RNA into protein by the ribosome, the folding of proteins by chaperonins or the entry of viruses in host cells. Understanding these fundamental processes by characterizing the molecular mechanisms that enable then, would allow the (better) design of therapies and drugs. Such molecular mechanisms may be revealed trough the structural elucidation of the biomolecular assemblies at the core of these processes. Various experimental techniques may be applied to investigate the molecular architecture of biomolecular assemblies. High-resolution techniques, such as X-ray crystallography, may solve the atomic structure of the system, but are typically constrained to biomolecules of reduced flexibility and dimensions. In particular, X-ray crystallography requires the sample to form a three dimensional (3D) crystal lattice which is technically di‑cult, if not impossible, to obtain, especially for large, dynamic systems. Often these techniques solve the structure of the different constituent components within the assembly, but encounter difficulties when investigating the entire system. On the other hand, imaging techniques, such as cryo-electron microscopy (cryo-EM), are able to depict large systems in near-native environment, without requiring the formation of crystals. The structures solved by cryo-EM cover a wide range of resolutions, from very low level of detail where only the overall shape of the system is visible, to high-resolution that approach, but not yet reach, atomic level of detail. In this dissertation, several modeling methods are introduced to either integrate cryo-EM datasets with structural data from X-ray crystallography, or to directly interpret the cryo-EM reconstruction. Such computational techniques were developed with the goal of creating an atomic model for the cryo-EM data. The low-resolution reconstructions lack the level of detail to permit a direct atomic interpretation, i.e. one cannot reliably locate the atoms or amino-acid residues within the structure obtained by cryo-EM. Thereby one needs to consider additional information, for example, structural data from other sources such as X-ray crystallography, in order to enable such a high-resolution interpretation. Modeling techniques are thus developed to integrate the structural data from the different biophysical sources, examples including the work described in the manuscript I and II of this dissertation. At intermediate and high-resolution, cryo-EM reconstructions depict consistent 3D folds such as tubular features which in general correspond to alpha-helices. Such features can be annotated and later on used to build the atomic model of the system, see manuscript III as alternative. Three manuscripts are presented as part of the PhD dissertation, each introducing a computational technique that facilitates the interpretation of cryo-EM reconstructions. The first manuscript is an application paper that describes a heuristics to generate the atomic model for the protein envelope of the Rift Valley fever virus. The second manuscript introduces the evolutionary tabu search strategies to enable the integration of multiple component atomic structures with the cryo-EM map of their assembly. Finally, the third manuscript develops further the latter technique and apply it to annotate consistent 3D patterns in intermediate-resolution cryo-EM reconstructions. The first manuscript, titled An assembly model for Rift Valley fever virus, was submitted for publication in the Journal of Molecular Biology. The cryo-EM structure of the Rift Valley fever virus was previously solved at 27Å-resolution by Dr. Freiberg and collaborators. Such reconstruction shows the overall shape of the virus envelope, yet the reduced level of detail prevents the direct atomic interpretation. High-resolution structures are not yet available for the entire virus nor for the two different component glycoproteins that form its envelope. However, homology models may be generated for these glycoproteins based on similar structures that are available at atomic resolutions. The manuscript presents the steps required to identify an atomic model of the entire virus envelope, based on the low-resolution cryo-EM map of the envelope and the homology models of the two glycoproteins. Starting with the results of the exhaustive search to place the two glycoproteins, the model is built iterative by running multiple multi-body refinements to hierarchically generate models for the different regions of the envelope. The generated atomic model is supported by prior knowledge regarding virus biology and contains valuable information about the molecular architecture of the system. It provides the basis for further investigations seeking to reveal different processes in which the virus is involved such as assembly or fusion. The second manuscript was recently published in the of Journal of Structural Biology (doi:10.1016/j.jsb.2009.12.028) under the title Evolutionary tabu search strategies for the simultaneous registration of multiple atomic structures in cryo-EM reconstructions. This manuscript introduces the evolutionary tabu search strategies applied to enable a multi-body registration. This technique is a hybrid approach that combines a genetic algorithm with a tabu search strategy to promote the proper exploration of the high-dimensional search space. Similar to the Rift Valley fever virus, it is common that the structure of a large multi-component assembly is available at low-resolution from cryo-EM, while high-resolution structures are solved for the different components but lack for the entire system. Evolutionary tabu search strategies enable the building of an atomic model for the entire system by considering simultaneously the different components. Such registration indirectly introduces spatial constrains as all components need to be placed within the assembly, enabling the proper docked in the low-resolution map of the entire assembly. Along with the method description, the manuscript covers the validation, presenting the benefit of the technique in both synthetic and experimental test cases. Such approach successfully docked multiple components up to resolutions of 40Å. The third manuscript is entitled Evolutionary Bidirectional Expansion for the Annotation of Alpha Helices in Electron Cryo-Microscopy Reconstructions and was submitted for publication in the Journal of Structural Biology. The modeling approach described in this manuscript applies the evolutionary tabu search strategies in combination with the bidirectional expansion to annotate secondary structure elements in intermediate resolution cryo-EM reconstructions. In particular, secondary structure elements such as alpha helices show consistent patterns in cryo-EM data, and are visible as rod-like patterns of high density. The evolutionary tabu search strategy is applied to identify the placement of the different alpha helices, while the bidirectional expansion characterizes their length and curvature. The manuscript presents the validation of the approach at resolutions ranging between 6 and 14Å, a level of detail where alpha helices are visible. Up to resolution of 12 Å, the method measures sensitivities between 70-100% as estimated in experimental test cases, i.e. 70-100% of the alpha-helices were correctly predicted in an automatic manner in the experimental data. The three manuscripts presented in this PhD dissertation cover different computation methods for the integration and interpretation of cryo-EM reconstructions. The methods were developed in the molecular modeling software Sculptor (http://sculptor.biomachina.org) and are available for the scientific community interested in the multi-resolution modeling of cryo-EM data. The work spans a wide range of resolution covering multi-body refinement and registration at low-resolution along with annotation of consistent patterns at high-resolution. Such methods are essential for the modeling of cryo-EM data, and may be applied in other fields where similar spatial problems are encountered, such as medical imaging

Aspects of phase retrieval in x-ray crystallography

X-ray crystallography is the primary technique for imaging the structures, or the positions of the atoms, of molecules. Knowledge of the geometrical atomic structures of molecules is key information in physics, chemistry, biology, geology and many other areas of science and technology. Structures are determinants of the properties of molecular systems. In the case of biology, knowledge of the structures of biological molecules provides essential information that allows us to understand the biological functionality of biomolecules and biomolecular systems. This knowledge is used to understand the fundamental molecular basis of biological function and processes, disease processes, and is also important in rational, or structure-based, drug design. X-ray crystallography involves irradiating a crystal specimen of the molecule under study with a beam of X-rays, and measuring the resulting pattern of diffracted X-rays. The data consisting of measured diffraction patterns is then inverted computationally to produce an image of the molecule. This is often referred to as computational imaging or computational microscopy. If both the phase and amplitude of the diffracted X- ray could be measured, then inversion of the data to produce the image would be straightforward. However, in practice, one can measure only the amplitude, but not the phase, of the diffracted X-rays. This results in the famous so-called “phase problem” in crystallography. A method of determining the phases must be devised before the structure can be calculated. The phase problem in crystallography has been studied for over one hundred years, and a number of clever methods have been devised for determining the phases in order for structures to be calculated. However, the phase problem is still an active area of research as current phasing techniques have significant limitations, and also because of the emergence of new kinds of instrumentation, specimens, and diffraction experiments. This thesis is concerned with the phase problem and phase retrieval algorithms for biological (macromolecular) crystallography that have arisen, in part, through the recent introduction of a new kind of X-ray source called an X-ray free-electron laser, and through new kinds of specimens that can be used with these sources. The thesis is divided into six chapters. The first chapter provides background information on diffraction imaging, X-ray crystallography, the phase problem, phase retrieval algorithms, and X-ray free-electron lasers and serial femtosecond crystallography. Original material is contained in Chapters 2 through 5. Concluding remarks are made in Chapter 6. Chapter 2 is concerned with properties of the phase problem for 3D crystals. New relationships are derived that more carefully formalise uniqueness for this problem, the problem for the case of an unknown molecular support is studied in detail and the theoretical results are supported by simulations, and the effects of crystallographic and noncrystallographic symmetry are elucidated. Chapters 3 and 4 form the first main part of the thesis and consider the phase problem for 2D crystals, a new kind of specimen that has been investigated with X-ray free-electron lasers. The two chapters are presented as two published journal papers for which the candidate is the primary author. In Chapter 3, the fundamental uniqueness properties of the phase problem for 2D crystals are derived, the nature of the solution set is elucidated, and the effects of various kinds of a priori information are evaluated by simulation. Chapter 4 follows up the results in Chapter 3, using simulations to investigate practical aspects of ab initio phase retrieval for 2D crystals using minimal molecular envelope information, and considering the characteristics of data available from X-ray free-electron laser sources. Chapter 5 forms the second main part of the thesis and develops a new kind of ab initio phasing technique called ab initio molecular replacement phasing. This method uses diffraction data from the same molecule crystallised in two or more crystal forms. Uniqueness of the solution for such a dataset is evaluated, and a suitable phase re- trieval algorithm is developed and tested by simulation using a small protein of known structure. Chapter 6 contains a brief summary of the outcomes of the thesis and suggestions for future research