title: Adaptive fluorescence microscopy by online feedback image analysis.
abstract: Obtaining sufficient statistics in quantitative fluorescence microscopy is often hampered by the tedious and time-consuming task of manually locating comparable specimen and repeatedly launching the same acquisition protocol. Recent advances in combining fluorescence microscopy with online image analysis tackle this problem by fully integrating the task of identifying and locating the specimen of interest in an automated acquisition workflow. Here, we describe the general requirements and specific microscope control and image analysis software solutions for implementing such automated online feedback microscopy. We demonstrate the power of the method by two selected applications addressing high-throughput 3D imaging of sparsely parasite-infected tissue culture cells and automated fluorescence recovery after photobleaching experiments to quantify the turnover of vesicular coat proteins at ER exit sites.
authors: European Molecular Biology Laboratory, Heidelberg, Germany.
authors: Christian
authors: C
authors: Tischer
authors: European Molecular Biology Laboratory, Heidelberg, Germany.
authors: Volker
authors: V
authors: Hilsenstein
authors: Instituto de Medicina Molecular, Lisboa, Portugal.
authors: Kirsten
authors: K
authors: Hanson
authors: European Molecular Biology Laboratory, Heidelberg, Germany.
authors: Rainer
authors: R
authors: Pepperkok
mesh_terms: D000818:Animals; D004721:Endoplasmic Reticulum / Q000648:ultrastructure; D036681:Fluorescence Recovery After Photobleaching; D006367:HeLa Cells; D056945:Hep G2 Cells; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008856:Microscopy, Fluorescence / Q000379:methods; D010962:Plasmodium berghei / Q000502:physiology; D021381:Protein Transport
keywords: Fluorescence microscopy; automation; fluorescence recovery after photobleaching (FRAP); high throughput microscopy; image analysis; siRNA screening; systems biology