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Journal Article

Semi-automatic determination of cell surface areas used in systems biology

MPS-Authors

Morath,  Volker
Max Planck Society;

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Deswal,  Sumit
Research Group and Chair of Molecular Immunology of the University of Freiburg, Max Planck Institute of Immunobiology and Epigenetics, Max Planck Society;

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Fiala,  Gina
Research Group and Chair of Molecular Immunology of the University of Freiburg, Max Planck Institute of Immunobiology and Epigenetics, Max Planck Society;

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Blumenthal,  Britta
Research Group and Chair of Molecular Immunology of the University of Freiburg, Max Planck Institute of Immunobiology and Epigenetics, Max Planck Society;

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Schamel,  Wolfgang Werner A.
Research Group and Chair of Molecular Immunology of the University of Freiburg, Max Planck Institute of Immunobiology and Epigenetics, Max Planck Society;

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Citation

Morath, V., Keuper, M., Rodriguez-Franco, M., Deswal, S., Fiala, G., Blumenthal, B., et al. (2013). Semi-automatic determination of cell surface areas used in systems biology. Frontiers in BioScience, 5, 533-545.


Cite as: http://hdl.handle.net/11858/00-001M-0000-002B-8951-6
Abstract
Quantitative biology requires high precision measurement of cellular parameters such as surface areas or volumes. Here, we have developed an integrated approach in which the data from 3D confocal microscopy and 2D high-resolution transmission electron microscopy were combined. The volumes and diameters of the cells within one population were automatically measured from the confocal data sets. The perimeter of the cell slices was measured in the TEM images using a semi-automated segmentation into background, cytoplasm and nucleus. These data in conjunction with approaches from stereology allowed for an unbiased estimate of surface areas with high accuracy. We have determined the volumes and surface areas of the cells and nuclei of six different immune cell types. In mast cells for example, the resulting cell surface was 3.5 times larger than the theoretical surface assuming the cell was a sphere with the same volume. Thus, our accurate data can now serve as inputs in modeling approaches in systems immunology.