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High content image-based cytometry for nuclear fingerprinting


Cytomics aims at understanding the functional relationships between cellular phenotypes (cytome) and metabolic pathways (proteome) that result from a combination of genetically defined mechanisms (genome) and environmental conditions [1,2]. Although flow-cytometry is able to measure the optical properties of single cells at a rate of >1000 cells per minute it has a limited capability of mapping individual events. To accurately quantify (sub-) cellular characteristics within a natural context there is a fast-growing need for image-based cytometry. Images, obtained with fluorescence microscopy, provide the exact information on signal intensity, location and distribution of specific molecules within intact cell systems (tissue or monolayers) and allow for investigating cellular properties in relation to the cell-ecological context [3]. Previously, we have developed a cytometric approach for scoring DNA lesion endpoints in confocal images of murine fibroblasts [3]. We now present a generalized approach for multivariate phenotypic profiling of individual nuclei using automated fluorescence mosaic microscopy and optimized digital image processing tools for imageJ. An indefinite number of fields, z-slices and channels can be analyzed; the only prerequisite is the presence of a nuclear counterstain, which is used for the generation of masks. To anticipate for erroneous segmentation of clustered nuclei in dense cell cultures we implemented an iterative conditional segmentation algorithm that uses both morphological and intensity information from the image. Subsequent analysis of subnuclear features is optimized to cater for a broad range of intensities and shapes. Our method is insensitive to scaling, illumination heterogeneity and variability or non-uniformity of staining. We have successfully applied our system in cell cycle analysis, scoring of transfection efficiency and assessment of (localized) DNA damage in response to genotoxic stress and ionizing radiation.

cytometry, high content screening, segmentation

Winnok de Vos



Short Biography
Education: Bio-engineer Competences: Specialized in advanced light microscopy and image processing Work: High content cytometry, CLEM, Telomere biology, DNA damage.

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