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DDC: 610 × Subject: article × Subject: fluorescence microscopy ×

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    Whole-Cell Analysis of Low-Density Lipoprotein Uptake by Macrophages Using STEM Tomography
    (San Francisco, CA : Public Library of Science, 2013) Baudoin, J.-P.; Jerome, W.G.; Kübel, C.; de Jonge, N.
    Nanoparticles of heavy materials such as gold can be used as markers in quantitative electron microscopic studies of protein distributions in cells with nanometer spatial resolution. Studying nanoparticles within the context of cells is also relevant for nanotoxicological research. Here, we report a method to quantify the locations and the number of nanoparticles, and of clusters of nanoparticles inside whole eukaryotic cells in three dimensions using scanning transmission electron microscopy (STEM) tomography. Whole-mount fixed cellular samples were prepared, avoiding sectioning or slicing. The level of membrane staining was kept much lower than is common practice in transmission electron microscopy (TEM), such that the nanoparticles could be detected throughout the entire cellular thickness. Tilt-series were recorded with a limited tilt-range of 80° thereby preventing excessive beam broadening occurring at higher tilt angles. The 3D locations of the nanoparticles were nevertheless determined with high precision using computation. The obtained information differed from that obtained with conventional TEM tomography data since the nanoparticles were highlighted while only faint contrast was obtained on the cellular material. Similar as in fluorescence microscopy, a particular set of labels can be studied. This method was applied to study the fate of sequentially up-taken low-density lipoprotein (LDL) conjugated to gold nanoparticles in macrophages. Analysis of a 3D reconstruction revealed that newly up-taken LDL-gold was delivered to lysosomes containing previously up-taken LDL-gold thereby forming onion-like clusters.
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    ColiCoords: A Python package for the analysis of bacterial fluorescence microscopy data
    (San Francisco, California, US : PLOS, 2019) Smit, Jochem H.; Li, Yichen; Warszawik, Eliza M.; Herrmann, Andreas; Cordes, Thorben; Gilestro, Giorgio F
    Single-molecule fluorescence microscopy studies of bacteria provide unique insights into the mechanisms of cellular processes and protein machineries in ways that are unrivalled by any other technique. With the cost of microscopes dropping and the availability of fully automated microscopes, the volume of microscopy data produced has increased tremendously. These developments have moved the bottleneck of throughput from image acquisition and sample preparation to data analysis. Furthermore, requirements for analysis procedures have become more stringent given the demand of various journals to make data and analysis procedures available. To address these issues we have developed a new data analysis package for analysis of fluorescence microscopy data from rod-like cells. Our software ColiCoords structures microscopy data at the single-cell level and implements a coordinate system describing each cell. This allows for the transformation of Cartesian coordinates from transmission light and fluorescence images and single-molecule localization microscopy (SMLM) data to cellular coordinates. Using this transformation, many cells can be combined to increase the statistical power of fluorescence microscopy datasets of any kind. ColiCoords is open source, implemented in the programming language Python, and is extensively documented. This allows for modifications for specific needs or to inspect and publish data analysis procedures. By providing a format that allows for easy sharing of code and associated data, we intend to promote open and reproducible research. The source code and documentation can be found via the project’s GitHub page.