[Frontiers in Bioscience E5, 533-545, January 1, 2013]
Semi-automatic determination of cell surface areas used in systems biology
Volker Morath1,2, Margret Keuper1,3, Marta Rodriguez-Franco4, Sumit Deswal1,2,5, Gina Fiala1,2,5, Britta Blumenthal1,2, Daniel Kaschek1,6, Jens Timmer1,6, Gunther Neuhaus4, Stephan Ehl7,8, Olaf Ronneberger1,3, Wolfgang Werner A. Schamel1,2,7
1BIOSS Centre for Biological Signaling Studies, University of Freiburg, Germany, 2Department of Molecular Immunology, Max Planck-Institute of Immunobiology and Institute of Biology III, Faculty of Biology, University of Freiburg, Germany, 3Computer Science Department, Technical Faculty, University of Freiburg, Germany, 4Department of Cell Biology, Faculty of Biology, University of Freiburg, Germany, 5Spemann Graduate School of Biology and Medicine, SGBM, University of Freiburg, Germany, 6Physics Institute, University of Freiburg, Germany, 7Centre for Chronic Immunodeficiency CCI, University Clinics Freiburg and Medical Faculty, University of Freiburg, Germany, 8Centre for Pediatrics and Adolescent Medicine, University Medical Center Freiburg
TABLE OF CONTENTS
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.