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      Varying label density allows artifact-free analysis of membrane-protein nanoclusters

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          Abstract

          We present a new method to robustly discriminate clustered from random distributions of molecules detected with single molecule localization microscopy-based techniques like PALM and STORM. The approach is based on the deliberate variation of the labeling density, e.g. by titration of fluorescent antibody, combined with quantitative cluster analysis. It thereby circumvents the problem of cluster artifacts generated by overcounting of blinking fluorophores.

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          Direct stochastic optical reconstruction microscopy with standard fluorescent probes.

          Sebastian van de Linde, Anna Löschberger, Teresa Klein … (2011)
          Direct stochastic optical reconstruction microscopy (dSTORM) uses conventional fluorescent probes such as labeled antibodies or chemical tags for subdiffraction resolution fluorescence imaging with a lateral resolution of ∼20 nm. In contrast to photoactivated localization microscopy (PALM) with photoactivatable fluorescent proteins, dSTORM experiments start with bright fluorescent samples in which the fluorophores have to be transferred to a stable and reversible OFF state. The OFF state has a lifetime in the range of 100 milliseconds to several seconds after irradiation with light intensities low enough to ensure minimal photodestruction. Either spontaneously or photoinduced on irradiation with a second laser wavelength, a sparse subset of fluorophores is reactivated and their positions are precisely determined. Repetitive activation, localization and deactivation allow a temporal separation of spatially unresolved structures in a reconstructed image. Here we present a step-by-step protocol for dSTORM imaging in fixed and living cells on a wide-field fluorescence microscope, with standard fluorescent probes focusing especially on the photoinduced fine adjustment of the ratio of fluorophores residing in the ON and OFF states. Furthermore, we discuss labeling strategies, acquisition parameters, and temporal and spatial resolution. The ultimate step of data acquisition and data processing can be performed in seconds to minutes.
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            Modelling Spatial Patterns

            B. Ripley (1977)
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              Quantitative evaluation of software packages for single-molecule localization microscopy.

              Daniel P. Sage, Hagai Kirshner, Thomas Pengo … (2015)
              The quality of super-resolution images obtained by single-molecule localization microscopy (SMLM) depends largely on the software used to detect and accurately localize point sources. In this work, we focus on the computational aspects of super-resolution microscopy and present a comprehensive evaluation of localization software packages. Our philosophy is to evaluate each package as a whole, thus maintaining the integrity of the software. We prepared synthetic data that represent three-dimensional structures modeled after biological components, taking excitation parameters, noise sources, point-spread functions and pixelation into account. We then asked developers to run their software on our data; most responded favorably, allowing us to present a broad picture of the methods available. We evaluated their results using quantitative and user-interpretable criteria: detection rate, accuracy, quality of image reconstruction, resolution, software usability and computational resources. These metrics reflect the various tradeoffs of SMLM software packages and help users to choose the software that fits their needs.
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                Author and article information

                Journal
                Journal ID (nlm-journal-id): 101215604
                Journal ID (pubmed-jr-id): 32338
                Journal ID (nlm-ta): Nat Methods
                Journal ID (iso-abbrev): Nat. Methods
                Title: Nature methods
                ISSN (Print): 1548-7091
                ISSN (Electronic): 1548-7105
                Publication date Nihms-submitted: 19 May 2016
                Publication date (Electronic): 13 June 2016
                Publication date (Print): August 2016
                Publication date PMC-release: 07 March 2019
                Volume: 13
                Issue: 8
                Pages: 661-664
                Affiliations
                [1 ]Institute of Applied Physics, TU Wien, Vienna, Austria
                [2 ]School of Engineering and Environmental Sciences, University of Applied Sciences Upper Austria, Wels, Austria
                [3 ]Institute for Hygiene and Applied Immunology, Medical University of Vienna, Vienna, Austria
                Author notes
                [* ]correspondence should be addressed to Florian Baumgart ( baumgart@ 123456iap.tuwien.ac.at ) or Gerhard J. Schütz ( schuetz@ 123456iap.tuwien.ac.at )
                Article
                Manuscript ID: EMS68505
                DOI: 10.1038/nmeth.3897
                PMC ID: 6404959
                PubMed ID: 27295310
                SO-VID: c8c125bb-67d9-43a9-8873-bac68d2a44d8
                License:

                Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

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                ScienceOpen disciplines: Life sciences

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