[Frontiers in Bioscience, Elite, 5, 533-545, January 1, 2013] 533 Semi-automatic determination of cell surface areas used in systems biology Volker Morath 1,2 , Margret Keuper 1,3 , Marta Rodriguez-Franco 4 , Sumit Deswal 1,2,5 , Gina Fiala 1,2,5 , Britta Blumenthal 1,2 , Daniel Kaschek 1,6 , Jens Timmer 1,6 , Gunther Neuhaus 4 , Stephan Ehl 7,8 , Olaf Ronneberger 1,3 , Wolfgang Werner A. Schamel 1,2,7 1 BIOSS Centre for Biological Signaling Studies, University of Freiburg, Germany, 2 Department of Molecular Immunology, Max Planck-Institute of Immunobiology and Institute of Biology III, Faculty of Biology, University of Freiburg, Germany, 3 Computer Science Department, Technical Faculty, University of Freiburg, Germany, 4 Department of Cell Biology, Faculty of Biology, University of Freiburg, Germany, 5 Spemann Graduate School of Biology and Medicine, SGBM, University of Freiburg, Germany, 6 Physics Institute, University of Freiburg, Germany, 7 Centre for Chronic Immunodeficiency CCI, University Clinics Freiburg and Medical Faculty, University of Freiburg, Germany, 8 Centre for Pediatrics and Adolescent Medicine, University Medical Center Freiburg TABLE OF CONTENTS 1. Abstract 2. Introduction 3. Materials and methods 3.1 Cells 3.2 Flow cytometry 3.3 Confocal microscopy 3.4 Electron microscopy 3.5 Data processing 4. Results 4.1 Design of the study 4.2. Determination of the cellular and nuclear radii distributions 4.3. Acquisition of high resolution 2D images 4.4. Calculation of the stereological 3D parameters 5. Discussion 6. Acknowledgements 7. References 1. 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. 2. INTRODUCTION A mechanistic understanding of biological processes requires the generation of quantitative data sets and their description in mathematical terms. This approach has been extensively used in the last years for a detailed understanding of signal transduction pathways . As many mathematical models are based on ordinary differential equations, their calibration requires accurate data of as many reaction network components as possible. The experimental data that serve as an input to the models include kinetics or dose responses of protein phosphorylations (measured by intracellular flow cytometry, beads based assays, mass spectroscopy or Western blotting) or protein-protein interactions (quantified by immunoprecipitations followed by Western blotting, flow cytometry or mass spectroscopy) . Common parameters to be measured are reaction rates (measured by enzyme assays), association constants (determined by surface plasmon resonance or flow cytometry) and initial protein concentrations.