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Three-Dimensional Characterization of Cell Clusters Using Synchrotron-Radiation-Based Micro-Computed Tomography

Published online by Cambridge University Press:  10 March 2006

Bert Müller ,
Marco Riedel  and
Philipp J. Thurner
Bert Müller
Affiliation:
Computer Vision Laboratory ETH Zürich, Gloriastrasse 35, CH-8092 Zürich, Switzerland
Marco Riedel
Affiliation:
ProBioGen, Sternwartstrasse 7, D-13086 Berlin, Germany
Philipp J. Thurner
Affiliation:
Computer Vision Laboratory ETH Zürich, Gloriastrasse 35, CH-8092 Zürich, Switzerland Swiss Federal Institute for Materials Testing and Research, Überlandstrasse 129, CH-8600 Dübendorf, Switzerland
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Abstract

Micro-computed tomography with the highly intense, monochromatic X rays produced by the synchrotron is a superior method to nondestructively measure the local absorption in three-dimensional space. Because biological tissues and cells consist mainly of water as the surrounding medium, higher absorbing agents have to be incorporated into the structures of interest. Even without X-ray optics such as refractive lens, one can uncover the stain distribution with the spatial resolution of about 1 μm. Incorporating the stain at selected cell compartments, for example, binding to the RNA/DNA, their density distribution becomes quantified. In this communication, we demonstrate that tomograms obtained at the beamlines BW2 and W2 (HASYLAB at DESY, Hamburg, Germany) and 4S (SLS, Villigen, Switzerland) clearly show that the RNA/DNA-stained HEK 293 cell clusters have a core of high density and a peripheral part of lower density, which correlate with results of optical microscopy. The inner part of the clusters is associated with nonvital cells as the result of insufficient oxygen and nutrition supply. This necrotic part is surrounded by (6 ± 1) layers of vital cells.

Keywords

micro-computed tomographysynchrotron radiationHEK 293 cell clusterDNA/RNA staining3D characterizationsegmentation
Type
BIOLOGICAL APPLICATIONS
Information
Microscopy and Microanalysis , Volume 12 , Issue 2 , April 2006 , pp. 97 - 105
Copyright
© 2006 Microscopy Society of America

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References

REFERENCES

Abbott, A. & Cyranoski, D. (2003). Biology's new dimension. Nature 424, 870–872.Google Scholar
Beckmann, F. (2001). Microtomography using synchrotron radiation as a user experiment at beamlines BW2 and BW5 of HASYLAB at DESY. In Developments in X-ray Tomography III, Bonse, U. (Ed.), pp. 34–41. San Diego: SPIE—The International Society for Optical Engineering.
Bernhardt, R., Scharnweber, D., Müller, B., Thurner, P., Schliephake, H., Wyss, P., Beckmann, F., Goebbels, J., & Worch, H. (2004). Comparison of microfocus- and synchrotron X-ray tomography for the analysis of osteointegration around Ti6Al4V-implants. Eur Cell Mater 7, 42–51.Google Scholar
Bonse, U. & Busch, F. (1996). X-ray computed microtomography (μCT) using synchrotron radiation. Prog Biophys Mol Biol 65, 133–169.Google Scholar
Bonse, U. & Hart, M. (1965a). An X-ray interferometer. Appl Phys Lett 6, 155–156.Google Scholar
Bonse, U. & Hart, M. (1965b). An X-ray interferometer with long separated interfering beam paths. Appl Phys Lett 7, 99–100.Google Scholar
Casciari, J.J., Sotirchos, S.V., & Sutherland, R.M. (1992). Mathematical modelling of microenvironment and growth in EMT6/Ro multicellular tumour spheroids. Cell Prolif 25, 1–22.Google Scholar
Hildebrand, T. & Rüegsegger, P. (1997). A new method for the model-independent assessment of thickness in three-dimensional images. J Microsc 185, 67–75.Google Scholar
Hoffman, R.M. (1993). To do tissue culture in two or three dimensions? That is the question. Stem Cells 11, 105–111.Google Scholar
Kak, A.C. & Slaney, M. (2001). Principles of Computerized Tomographic Imaging. Philadelphia, PA: The Society of Industrial and Applied Mathematics.
König, D., Carvajal-Gonzalez, S., Downs, A.M., Vassy, J., & Rigaut, J.P. (1991). Modelling and analysis of 3-D arrangements of particles by point processes with examples of application to biological data obtained by confocal scanning light microscopy. J Microsc 161, 405–433.Google Scholar
Laurent, M., Johannin, G., Gilbert, N., Lucas, L., Cassio, D., Petit, P.X., & Fleury, A. (1994). Power and limits of laser scanning confocal microscopy. Biol Cell 80, 229–240.Google Scholar
Levin-Zaidman, S., Frenkel-Krispin, D., Shimoni, E., Sabanay, I., Wolf, S.G., & Minsky, A. (2000). Ordered intracellular reca–DNA assemblies: A potential site of in vivo reca-mediated activities. Proc Natl Acad Sci USA 97, 6791–6796.Google Scholar
Liu, M., Xu, J., Souza, P., Tanswell, B., Tanswell, A.K., & Post, M. (1995). The effect of mechanical strain on fetal rat lung cell proliferation: Comparison of two- and three-dimensional culture systems. In Vitro Cell Dev Biol Anim 31, 858–866.Google Scholar
Marquardt, D.W. (1969). An algorithm for least-squares estimation of nonlinear parameters. J Soc Ind Appl Math 11, 431–441.Google Scholar
Müller, B., Beckmann, F., Huser, M., Maspero, F., Szekely, G., Ruffieux, K., Thurner, P., & Wintermantel, E. (2002). Non-destructive three-dimensional evaluation of a polymer sponge by micro-tomography using synchrotron radiation. Biomol Eng 19, 73–78.Google Scholar
Müller, B. & Wintermantel, E. (1999). Ein strukturkompatibler Werkstoff für die Leberzelltransplantation. Bulletin 274, 42–45.Google Scholar
Müller-Klieser, W. (1987). Multicellular spheroids. J Cancer Res Clin Oncol 113, 101–122.Google Scholar
Stampanoni, M., Wyss, P., Abela, R., Borchert, G., Vermeulen, D., & Rüegsegger, P. (2001). X-ray tomographic microscopy at the Swiss light source. In Developments in X-ray Tomography III, Bonse, U. (Ed.), pp. 42–53. San Diego: SPIE—The International Society for Optical Engineering.
Suzuki, K., Horiba, I., & Sugie, N. (2003). Linear-time connected-component labeling based on sequential local operations. Comput Vision Image Understand 89, 1–23.Google Scholar
Takezawa, T. (2003). A strategy for the development of tissue engineering scaffolds that regulate cell behavior. Biomaterials 24, 2267–2275.Google Scholar
Thurner, P., Beckmann, F., & Müller, B. (2004). An optimization procedure for spatial and density resolution in hard X-ray micro-computed tomography. Nucl Instrum Meth Phys Res B 225, 599–603.Google Scholar
Thurner, P., Müller, B., Beckmann, F., Weitkamp, T., Rau, C., Müller, R., Hubbell, J.A., & Sennhauser, U. (2003). Tomography study of human foreskin fibroblasts on polymer yarns. Nucl Instrum Meth Phys Res B 200, 397–405.Google Scholar
Weaver, V.M., Petersen, O.W., Wang, F., Larabell, C.A., Briand, P., Damsky, C., & Bissell, M.J. (1997). Reversion of the malignant phenotype of human breast cells in three-dimensional culture and in vivo by integrin blocking antibodies. J Cell Biol 137, 231–245.Google Scholar