A detailed analysis of 3D subcellular signal localization

Abstract

Detection and localization of fluorescent signals in relation to other subcellular structures is an important task in various biological studies. Many methods for analysis of fluorescence microscopy image data are limited to 2D. As cells are in fact 3D structures, there is a growing need for robust methods for analysis of 3D data. This article presents an approach for detecting point-like fluorescent signals and analyzing their subnuclear position. Cell nuclei are delineated using marker-controlled (seeded) 3D watershed segmentation. User-defined object and background seeds are given as input, and gradient information defines merging and splitting criteria. Point-like signals are detected using a modified stable wave detector and localized in relation to the nuclear membrane using distance shells. The method was applied to a set of biological data studying the localization of Smad2-Smad4 protein complexes in relation to the nuclear membrane. Smad complexes appear as early as 1 min after stimulation while the highest signal concentration is observed 45 min after stimulation, followed by a concentration decrease. The robust 3D signal detection and concentration measures obtained using the proposed method agree with previous observations while also revealing new information regarding the complex formation. ' 2008 International Society for Advancement of Cytometry Key terms3D image analysis; fluorescence signal segmentation; subcellular positioning; Smad detection THE subcellular location of a protein or a protein complex is directly related to its function. This makes the detection and localization of protein complexes in relation to other subcellular structures an important task in biological studies. Highly specific staining methods and fluorescent markers emitting light at different wavelengths together with fluorescence microscopy allow for detailed studies of the spatial distribution and localization of biomolecules. Exact localization of fluorescent signals can be challenging as biological samples are three-dimensional (3D), and thus, the signals are often spread across a 3D volume.There are a number of techniques for 3D biological fluorescence microscopy, and the performance of these methods has been studied in recent literature (1). Wide-field fluorescence microscopy is one such commonly used technique. Images acquired by a wide-field microscope provide clear lateral information, but limited axial information. Methods like deconvolution are used with wide-field microscopes to reduce this problem (2). Another approach is to use techniques like spot scanning/laser scanning or spinning disk confocal microscopy. Use of such confocal techniques for volumetric (3D) imaging is the most common approach in many biological applications today.Localization of fluorescence signals from in situ detected proteins within their cellular compartments has been an active research field over the years (3,4). A comparison of image analysis-based methods for determination of intracellular location of fluorescent-labeled ...

Automated organelle‐based colocalization in whole‐cell imaging

“…Because of the difference in scales of the pixel resolution to distance between slices typical in fluorescent imaging we choose to segment each slice individually, though methods have been developed to segment anisotropic 3D data (see, for instance (10,12)). However, other segmentation strategies could readily be utilized within OBCOL.…”

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Telling one from another

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Going into lengths and widths, and depths—Microscopic cytomics quantifying cell function and cell communication

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