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      Targeted volumetric single-molecule localization microscopy of defined presynaptic structures in brain sections

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          Abstract

          Revealing the molecular organization of anatomically precisely defined brain regions is necessary for refined understanding of synaptic plasticity. Although three-dimensional (3D) single-molecule localization microscopy can provide the required resolution, imaging more than a few micrometers deep into tissue remains challenging. To quantify presynaptic active zones (AZ) of entire, large, conditional detonator hippocampal mossy fiber (MF) boutons with diameters as large as 10 µm, we developed a method for targeted volumetric direct stochastic optical reconstruction microscopy ( dSTORM). An optimized protocol for fast repeated axial scanning and efficient sequential labeling of the AZ scaffold Bassoon and membrane bound GFP with Alexa Fluor 647 enabled 3D- dSTORM imaging of 25 µm thick mouse brain sections and assignment of AZs to specific neuronal substructures. Quantitative data analysis revealed large differences in Bassoon cluster size and density for distinct hippocampal regions with largest clusters in MF boutons.

          Abstract

          Pauli et al. develop targeted volumetric dSTORM in order to image large hippocampal mossy fiber boutons (MFBs) in brain slices. They can identify synaptic targets of individual MFBs and measured size and density of Bassoon clusters within individual untruncated MFBs at nanoscopic resolution.

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          Fiji: an open-source platform for biological-image analysis.

          Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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            Imaging intracellular fluorescent proteins at nanometer resolution.

            We introduce a method for optically imaging intracellular proteins at nanometer spatial resolution. Numerous sparse subsets of photoactivatable fluorescent protein molecules were activated, localized (to approximately 2 to 25 nanometers), and then bleached. The aggregate position information from all subsets was then assembled into a superresolution image. We used this method--termed photoactivated localization microscopy--to image specific target proteins in thin sections of lysosomes and mitochondria; in fixed whole cells, we imaged vinculin at focal adhesions, actin within a lamellipodium, and the distribution of the retroviral protein Gag at the plasma membrane.
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              The ImageJ ecosystem: An open platform for biomedical image analysis.

              Technology in microscopy advances rapidly, enabling increasingly affordable, faster, and more precise quantitative biomedical imaging, which necessitates correspondingly more-advanced image processing and analysis techniques. A wide range of software is available-from commercial to academic, special-purpose to Swiss army knife, small to large-but a key characteristic of software that is suitable for scientific inquiry is its accessibility. Open-source software is ideal for scientific endeavors because it can be freely inspected, modified, and redistributed; in particular, the open-software platform ImageJ has had a huge impact on the life sciences, and continues to do so. From its inception, ImageJ has grown significantly due largely to being freely available and its vibrant and helpful user community. Scientists as diverse as interested hobbyists, technical assistants, students, scientific staff, and advanced biology researchers use ImageJ on a daily basis, and exchange knowledge via its dedicated mailing list. Uses of ImageJ range from data visualization and teaching to advanced image processing and statistical analysis. The software's extensibility continues to attract biologists at all career stages as well as computer scientists who wish to effectively implement specific image-processing algorithms. In this review, we use the ImageJ project as a case study of how open-source software fosters its suites of software tools, making multitudes of image-analysis technology easily accessible to the scientific community. We specifically explore what makes ImageJ so popular, how it impacts the life sciences, how it inspires other projects, and how it is self-influenced by coevolving projects within the ImageJ ecosystem.
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                Author and article information

                Contributors
                m.sauer@uni-wuerzburg.de
                heckmann@uni-wuerzburg.de
                Siren_A@ukw.de
                Journal
                Commun Biol
                Commun Biol
                Communications Biology
                Nature Publishing Group UK (London )
                2399-3642
                25 March 2021
                25 March 2021
                2021
                : 4
                : 407
                Affiliations
                [1 ]GRID grid.8379.5, ISNI 0000 0001 1958 8658, Department for Neurophysiology, Institute for Physiology, , Julius-Maximilians-University Würzburg, ; Würzburg, Germany
                [2 ]GRID grid.411760.5, ISNI 0000 0001 1378 7891, Department of Neurosurgery, , University Hospital of Würzburg, ; Würzburg, Germany
                [3 ]GRID grid.8379.5, ISNI 0000 0001 1958 8658, Center for Computational and Theoretical Biology, , Julius-Maximilians-University Würzburg, ; Würzburg, Germany
                [4 ]GRID grid.8379.5, ISNI 0000 0001 1958 8658, Department of Biotechnology and Biophysics, Biocenter, , Julius-Maximilians-University Würzburg, ; Würzburg, Germany
                Author information
                http://orcid.org/0000-0001-8205-160X
                http://orcid.org/0000-0003-3063-164X
                http://orcid.org/0000-0002-8049-6186
                http://orcid.org/0000-0002-1692-3219
                http://orcid.org/0000-0002-2217-0081
                Article
                1939
                10.1038/s42003-021-01939-z
                7994795
                33767432
                23aab0da-ad73-442a-a8d7-debaf1b71b42
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 6 May 2019
                : 3 March 2021
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft (German Research Foundation);
                Award ID: TRR 166 ReceptorLight, project A04
                Award ID: TRR 166 ReceptorLight, project B06
                Award ID: TRR 166 ReceptorLight, project B06
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100009379, Interdisziplinäres Zentrum für Klinische Forschung, Universitätsklinikum Würzburg (Interdisciplinary Center for Clinical Research, University Hospital of Würzburg);
                Award ID: N-229
                Award ID: N-229
                Award Recipient :
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                © The Author(s) 2021

                synaptic vesicle exocytosis,fluorescence imaging

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