36 research outputs found

    Single-molecule imaging to characterise the transport mechanism of the Nuclear Pore Complex

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    In the eukaryotic cell, a large macromolecular channel, known as the Nuclear Pore Complex (NPC), mediates all molecular transport between the nucleus and cytoplasm. In recent years, single-molecule fluorescence (SMF) imaging has emerged as a powerful tool to study the molecular mechanism of transport through the NPC. More recently, techniques such as Single-Molecule Localisation Microscopy (SMLM) have enabled the spatial and temporal distribution of cargos, transport receptors and even structural components of the NPC to be determined with nanometre accuracy. In this protocol, we describe a method to study the position and/or motion of individual molecules transiting through the NPC with high spatial and temporal precision

    Using enhanced number and brightness to measure protein oligomerization dynamics in live cells

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    Protein dimerization and oligomerization are essential to most cellular functions, yet measurement of the size of these oligomers in live cells, especially when their size changes over time and space, remains a challenge. A commonly used approach for studying protein aggregates in cells is number and brightness (N&B), a fluorescence microscopy method that is capable of measuring the apparent average number of molecules and their oligomerization (brightness) in each pixel from a series of fluorescence microscopy images. We have recently expanded this approach in order to allow resampling of the raw data to resolve the statistical weighting of coexisting species within each pixel. This feature makes enhanced N&B (eN&B) optimal for capturing the temporal aspects of protein oligomerization when a distribution of oligomers shifts toward a larger central size over time. In this protocol, we demonstrate the application of eN&B by quantifying receptor clustering dynamics using electron-multiplying charge-coupled device (EMCCD)-based total internal reflection microscopy (TIRF) imaging. TIRF provides a superior signal-to-noise ratio, but we also provide guidelines for implementing eN&B in confocal microscopes. For each time point, eN&B requires the acquisition of 200 frames, and it takes a few seconds up to 2 min to complete a single time point. We provide an eN&B (and standard N&B) MATLAB software package amenable to any standard confocal or TIRF microscope. The software requires a high-RAM computer (64 Gb) to run and includes a photobleaching detrending algorithm, which allows extension of the live imaging for more than an hour

    Three-dimensional super-resolution structured illumination microscopy with maximum a posteriori probability image estimation

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    We introduce and demonstrate a new high performance image reconstruction method for super-resolution structured illumination microscopy based on maximum a posteriori probability estimation (MAP-SIM). Imaging performance is demonstrated on a variety of fluorescent samples of different thickness, labeling density and noise levels. The method provides good suppression of out of focus light, improves spatial resolution, and allows reconstruction of both 2D and 3D images of cells even in the case of weak signals. The method can be used to process both optical sectioning and super-resolution structured illumination microscopy data to create high quality super-resolution images. (C) 2014 Optical Society of Americ

    Investigating hepatitis C virus infection using super-resolution microscopy

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    Super-resolution microscopy (SRM) can provide a window on the nanoscale events of virus replication. Here we describe a protocol for imaging hepatitis C virus-infected cells using localization SRM. We provide details on sample preparation, immunostaining, data collection, and super-resolution image reconstruction. We have made all efforts to generalize the protocol to make it accessible to all budding super-resolution microscopists

    Stochastic Micro-Pattern for Automated Correlative Fluorescence - Scanning Electron Microscopy

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    Studies of cellular surface features gain from correlative approaches, where live cell information acquired by fluorescence light microscopy is complemented by ultrastructural information from scanning electron micrographs. Current approaches to spatially align fluorescence images with scanning electron micrographs are technically challenging and often cost or time-intensive. Relying exclusively on open-source software and equipment available in a standard lab, we have developed a method for rapid, software-assisted alignment of fluorescence images with the corresponding scanning electron micrographs via a stochastic gold micro-pattern. Here, we provide detailed instructions for micro-pattern production and image processing, troubleshooting for critical intermediate steps, and examples of membrane ultra-structures aligned with the fluorescence signal of proteins enriched at such sites. Together, the presented method for correlative fluorescence – scanning electron microscopy is versatile, robust and easily integrated into existing workflows, permitting image alignment with accuracy comparable to existing approaches with negligible investment of time or capital
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