In Situ Cryo-Electron Tomography: A Post-Reductionist Approach to Structural Biology

Cryo-electron tomography is a powerful technique that can faithfully image the native cellular environment at nanometer resolution. Unlike many other imaging approaches, cryo-electron tomography provides a label-free method of detecting biological structures, relying on the intrinsic contrast of frozen cellular material for direct identification of macromolecules. Recent advances in sample preparation, detector technology, and phase plate imaging have enabled the structural characterization of protein complexes within intact cells. Here, we review these technical developments and outline a detailed computational workflow for in situ structural analysis. Two recent studies are described to illustrate how this workflow can be adapted to examine both known and unknown cellular complexes. The stage is now set to realize the promise of visual proteomics a complete structural description of the cell's native molecular landscape. (C) 2015 Elsevier Ltd. All rights reserved

Polarized Localization Microscopy (plm) Detects Nanoscale Membrane Curvature And Induced Budding By Cholera Toxin Subunit B (ctxb)

The curvature of biological membranes at the nanometer scale is critically important for vesicle trafficking, organelle morphology, and disease propagation. Many proteins and lipids interact with diverse curvature sensing and curvature generating mechanisms. Deciphering the molecular mechanisms of toxin-membrane interactions has been limited by the resolution and drawbacks of conventional experimental techniques. This study reveals the inherent membrane bending capability of cholera toxin subunit B (CTxB) through the development and implementation of Polarized Localization Microscopy (PLM). PLM is a pointillist optical imaging technique for the detection of nanoscale membrane curvature in correlation with single-molecule dynamics and molecular sorting. PLM combines polarized total internal reflection fluorescence microscopy and fluorescence localization microscopy to reveal membrane orientation without reducing localization precision by point spread function manipulation. Further, membrane curvature detection with PLM requires ≤19% of the localization density required with 3D fluorescence localization microscopy (e.g., PALM or STORM). Engineered hemispherical membrane curvature with varying radii of 24, 51, and 70 nm were detected with PLM while surrounded by planar supported lipid bilayers. Nanoscale membrane bud growth was spontaneously induced by CTxB on otherwise planar, quasi-one component lipid bilayers, revealing a mechanism of cholera immobilization and cellular internalization. The single lipid and single protein trajectories further quantified the effects of nanoscale membrane curvature and protein-lipid interactions. CTxB sorting to high membrane curvatures was detected and quantified. Nanoscale membrane budding and tubulation was mainly driven by CTxB valency and structure. We demonstrated that varying either GM1 or CTxB concentrations on the membrane affects the budding structures. The number of crosslinked GM1s to a single CTxB affected the toxin behavior and mechanism on the membrane. Changing the lipid structure altered the bending mechanism and the eventual size and density of induced buds. Through future incorporation of single-particle tracking and live cells, PLM is poised to image the diverse molecular mechanisms that regulate nanoscale membrane bending

ACME: Automated Cell Morphology Extractor for Comprehensive Reconstruction of Cell Membranes

The quantification of cell shape, cell migration, and cell rearrangements is important for addressing classical questions in developmental biology such as patterning and tissue morphogenesis. Time-lapse microscopic imaging of transgenic embryos expressing fluorescent reporters is the method of choice for tracking morphogenetic changes and establishing cell lineages and fate maps in vivo. However, the manual steps involved in curating thousands of putative cell segmentations have been a major bottleneck in the application of these technologies especially for cell membranes. Segmentation of cell membranes while more difficult than nuclear segmentation is necessary for quantifying the relations between changes in cell morphology and morphogenesis. We present a novel and fully automated method to first reconstruct membrane signals and then segment out cells from 3D membrane images even in dense tissues. The approach has three stages: 1) detection of local membrane planes, 2) voting to fill structural gaps, and 3) region segmentation. We demonstrate the superior performance of the algorithms quantitatively on time-lapse confocal and two-photon images of zebrafish neuroectoderm and paraxial mesoderm by comparing its results with those derived from human inspection. We also compared with synthetic microscopic images generated by simulating the process of imaging with fluorescent reporters under varying conditions of noise. Both the over-segmentation and under-segmentation percentages of our method are around 5%. The volume overlap of individual cells, compared to expert manual segmentation, is consistently over 84%. By using our software (ACME) to study somite formation, we were able to segment touching cells with high accuracy and reliably quantify changes in morphogenetic parameters such as cell shape and size, and the arrangement of epithelial and mesenchymal cells. Our software has been developed and tested on Windows, Mac, and Linux platforms and is available publicly under an open source BSD license (https://github.com/krm15/ACME)

G-CSC Report 2010

The present report gives a short summary of the research of the Goethe Center for Scientific Computing (G-CSC) of the Goethe University Frankfurt. G-CSC aims at developing and applying methods and tools for modelling and numerical simulation of problems from empirical science and technology. In particular, fast solvers for partial differential equations (i.e. pde) such as robust, parallel, and adaptive multigrid methods and numerical methods for stochastic differential equations are developed. These methods are highly adanvced and allow to solve complex problems.. The G-CSC is organised in departments and interdisciplinary research groups. Departments are localised directly at the G-CSC, while the task of interdisciplinary research groups is to bridge disciplines and to bring scientists form different departments together. Currently, G-CSC consists of the department Simulation and Modelling and the interdisciplinary research group Computational Finance

Detectors for Super-Resolution & Single-Molecule Fluorescence Microscopies

The resolution of light microscopy was thought to be limited to 250–300 nanometers based on the work of Ernest Abbe. This Abbe diffraction limit was believed to be insurmountable until the invention of Super-resolution microscopic techniques in the late 20th century. These techniques remove this limit and have provided unprecedented detail of cellular structures and dynamics down to several nanometers. An emerging goal in this field is to quantitatively measure individual molecules. Measurement of single-molecule dynamics, such as diffusion coefficients and complex stoichiometries, can be accomplished using fluorescence fluctuation techniques to reveal nanosecond-to-microsecond temporal reactions. These powerful complimentary experimental approaches are made possible by sensitive low-light photodetectors. In this chapter, an overview of the principles of super-resolution and single-molecule microscopies are provided. The different types of photodetectors employed in these techniques are explained. In addition, the advantages and disadvantages for these detectors are discussed, as well as the development of next generation detectors. Finally, example super-resolution and single-molecule cellular studies that take advantage of these detector technologies are presented

The promise and the challenges of cryo-electron tomography

Structural biologists have traditionally approached cellular complexity in a reductionist manner in which the cellular molecular components are fractionated and purified before being studied individually. This 'divide and conquer' approach has been highly successful. However, awareness has grown in recent years that biological functions can rarely be attributed to individual macromolecules. Most cellular functions arise from their concerted action, and there is thus a need for methods enabling structural studies performed in situ, ideally in unperturbed cellular environments. Cryo-electron tomography (Cryo-ET) combines the power of 3D molecular-level imaging with the best structural preservation that is physically possible to achieve. Thus, it has a unique potential to reveal the supramolecular architecture or 'molecular sociology' of cells and to discover the unexpected. Here, we review state-of-the-art Cryo-ET workflows, provide examples of biological applications, and discuss what is needed to realize the full potential of Cryo-ET

Fluorescence microscopy: Established and emerging methods, experimental strategies, and applications in immunology

Cutting-edge biophysical technologies including total internal reflection fluorescence microscopy, single molecule fluorescence, single channel opening events, fluorescence resonance energy transfer, high-speed exposures, two-photon imaging, fluorescence lifetime imaging, and other tools are becoming increasingly important in immunology as they link molecular events to cellular physiology, a key goal of modern immunology. The primary concern in all forms of microscopy is the generation of contrast; for fluorescence microscopy contrast can be thought of as the difference in intensity between the cell and background, the signal-to-noise ratio. High information-content images can be formed by enhancing the signal, suppressing the noise, or both. As improved tools, such as ICCD and EMCCD cameras, become available for fluorescence imaging in molecular and cellular immunology, it is important to optimize other aspects of the imaging system. Numerous practical strategies to enhance fluorescence microscopy experiments are reviewed. The use of instrumentation such as light traps, cameras, objectives, improved fluorescent labels, and image filtration routines applicable to low light level experiments are discussed. New methodologies providing resolution well beyond that given by the Rayleigh criterion are outlined. Ongoing and future developments in fluorescence microscopy instrumentation and technique are reviewed. This review is intended to address situations where the signal is weak, which is important for emerging techniques stressing super-resolution or live cell dynamics, but is less important for conventional applications such as indirect immunofluorescence. This review provides a broad integrative discussion of fluorescence microscopy with selected applications in immunology. Microsc. Res. Tech., 2007. © 2007 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/56150/1/20455_ftp.pd

Contributions To Automatic Particle Identification In Electron Micrographs: Algorithms, Implementation, And Applications

Three dimensional reconstruction of large macromolecules like viruses at resolutions below 8 Ã… - 10 Ã… requires a large set of projection images and the particle identification step becomes a bottleneck. Several automatic and semi-automatic particle detection algorithms have been developed along the years. We present a general technique designed to automatically identify the projection images of particles. The method utilizes Markov random field modelling of the projected images and involves a preprocessing of electron micrographs followed by image segmentation and post processing for boxing of the particle projections. Due to the typically extensive computational requirements for extracting hundreds of thousands of particle projections, parallel processing becomes essential. We present parallel algorithms and load balancing schemes for our algorithms. The lack of a standard benchmark for relative performance analysis of particle identification algorithms has prompted us to develop a benchmark suite. Further, we present a collection of metrics for the relative performance analysis of particle identification algorithms on the micrograph images in the suite, and discuss the design of the benchmark suite