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      Extracting quantitative information from single-molecule super-resolution imaging data with LAMA – LocAlization Microscopy Analyzer

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      Author(s): a , 1 , b , 1
      Publication date (Electronic):
      Journal: Scientific Reports
      Publisher: Nature Publishing Group

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          Abstract

          Super-resolution fluorescence microscopy revolutionizes cell biology research and provides novel insights on how proteins are organized at the nanoscale and in the cellular context. In order to extract a maximum of information, specialized tools for image analysis are necessary. Here, we introduce the LocAlization Microscopy Analyzer (LAMA), a comprehensive software tool that extracts quantitative information from single-molecule super-resolution imaging data. LAMA allows characterizing cellular structures by their size, shape, intensity, distribution, as well as the degree of colocalization with other structures. LAMA is freely available, platform-independent and designed to provide direct access to individual analysis of super-resolution data.

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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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            A simple method to estimate the average localization precision of a single-molecule localization microscopy experiment.

            Ulrike Endesfelder, Sebastian Malkusch, Franziska Fricke … (2014)
            The localization precision is a crucial and important parameter for single-molecule localization microscopy (SMLM) and directly influences the achievable spatial resolution. It primarily depends on experimental imaging conditions and the registration potency of the algorithm used. We propose a new and simple routine to estimate the average experimental localization precision in SMLM, based on the nearest neighbor analysis. By exploring different experimental and simulated targets, we show that this approach can be generally used for any 2D or 3D SMLM data and that reliable values for the localization precision σ SMLM are obtained. Knowing σ SMLM is a prerequisite for consistent visualization or any quantitative structural analysis, e.g., cluster analysis or colocalization studies.
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              Coordinate-based colocalization analysis of single-molecule localization microscopy data.

              Sebastian Malkusch, Ulrike Endesfelder, Justine Mondry … (2012)
              Colocalization of differently labeled biomolecules is a valuable tool in fluorescence microscopy and can provide information on biomolecular interactions. With the advent of super-resolution microscopy, colocalization analysis is getting closer to molecular resolution, bridging the gap to other technologies such as fluorescence resonance energy transfer. Among these novel microscopic techniques, single-molecule localization-based super-resolution methods offer the advantage of providing single-molecule coordinates that, rather than intensity information, can be used for colocalization analysis. This requires adapting the existing mathematical algorithms for localization microscopy data. Here, we introduce an algorithm for coordinate-based colocalization analysis which is suited for single-molecule super-resolution data. In addition, we present an experimental configuration for simultaneous dual-color imaging together with a robust approach to correct for optical aberrations with an accuracy of a few nanometers. We demonstrate the potential of our approach for cellular structures and for two proteins binding actin filaments.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Sci Rep
                Journal ID (iso-abbrev): Sci Rep
                Title: Scientific Reports
                Publisher: Nature Publishing Group
                ISSN (Electronic): 2045-2322
                Publication date (Electronic): 05 October 2016
                Publication date Collection: 2016
                Volume: 6
                Electronic Location Identifier: 34486
                Affiliations
                [1 ]Single Molecule Biophysics, Institute of Physical and Theoretical Chemistry, Goethe-University Frankfurt, Germany
                Author notes
                Article
                Publisher Item ID: srep34486
                DOI: 10.1038/srep34486
                PMC ID: 5050494
                PubMed ID: 27703238
                SO-VID: e6162f94-0141-4e98-807d-d16d95a60456
                Copyright © Copyright © 2016, The Author(s)
                License:

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                Date received : 13 April 2016
                Date accepted : 14 September 2016
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                Subject: Article

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