Taras Sych1,2,3,4, Thomas Schubert1,2,3,5, Romain Vauchelles4, Josef Madl1,2,3, Ramin Omidvar1,2,3, Roland Thuenauer1,2,3, Ludovic Richert4, Yves Mély4, Winfried Römer1,2,3. 1. Faculty of Biology, Albert Ludwigs University Freiburg, Schänzlestraße 1, Freiburg im Breisgau, Germany. 2. Synthetic Biology of Signalling Processes, Signalling Research Centres BIOSS and CIBSS, Albert Ludwigs University Freiburg, Schänzlestraße 18, Freiburg im Breisgau, Germany. 3. Freiburg Center for Interactive Materials and Bioinspired Technologies (FIT), Albert Ludwigs University Freiburg, Georges-Köhler-Allee 105, Freiburg im Breisgau, Germany. 4. Laboratory of Bioimaging and Pathologies, UMR 7021 CNRS, Faculty of Pharmacy, University of Strasbourg, 74 route du Rhin, Illkirch, France. 5. Toolbox Imaging Platform, Signalling Research Centres BIOSS and CIBSS, Albert Ludwigs University Freiburg, Schänzlestraße 18, Freiburg im Breisgau, Germany.
Abstract
MOTIVATION: Giant Unilamellar Vesicles (GUVs) are widely used synthetic membrane systems that mimic native membranes and cellular processes. Various fluorescence imaging techniques can be employed for their characterization. In order to guarantee a fast and unbiased analysis of imaging data, the development of automated recognition and processing steps is required. RESULTS: We developed a fast and versatile Fiji-based macro for the analysis of digital microscopy images of GUVs. This macro was designed to investigate membrane dye incorporation and protein binding to membranes. Moreover, we propose a fluorescence intensity-based method to quantitatively assess protein binding. AVAILABILITY AND IMPLEMENTATION: The ImageJ distribution package FIJI is freely available online: https://imagej.net/Fiji. The macro file GUV-AP.ijm is available at https://github.com/AG-Roemer/GUV-AP. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: Giant Unilamellar Vesicles (GUVs) are widely used synthetic membrane systems that mimic native membranes and cellular processes. Various fluorescence imaging techniques can be employed for their characterization. In order to guarantee a fast and unbiased analysis of imaging data, the development of automated recognition and processing steps is required. RESULTS: We developed a fast and versatile Fiji-based macro for the analysis of digital microscopy images of GUVs. This macro was designed to investigate membrane dye incorporation and protein binding to membranes. Moreover, we propose a fluorescence intensity-based method to quantitatively assess protein binding. AVAILABILITY AND IMPLEMENTATION: The ImageJ distribution package FIJI is freely available online: https://imagej.net/Fiji. The macro file GUV-AP.ijm is available at https://github.com/AG-Roemer/GUV-AP. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.