title: Quantification of the number of EP3 receptors on a living CHO cell surface by the AFM.
abstract: The distribution of EP3 receptors on a living cell surface was quantitatively studied by atomic force microscopy (AFM). Green fluorescent protein (GFP) was introduced to the extracellular region of the EP3 receptor on a CHO cell. A microbead was used as a probe to ensure certain contact area, whose surface was coated with anti-GFP antibody. The interactions between the antibodies and GFP molecules on the cell surface were recorded to observe the distribution of the receptors. The result indicated that EP3 receptors were distributed on the CHO cell surface not uniformly but in small patches coincident with immunohistochemical observation. Repeated measurements on the same area of cell surface gave confirmation that it was unlikely that the receptors were extracted from the cell membrane during the experiments. The measurement of single molecular interaction between GFP and the anti-GFP antibody was succeeded on the cell surface using compression-free force spectroscopy. The value of separation work required to break a single molecular pair was estimated to be about 1.5 x 10(-18)J. The number of EP3 receptor on the CHO cell surface was estimated using this value to be about 1 x 10(4) under the assumption that the area of the cell surface was about 5,000 microm(2). These results indicated that the number of receptors on a living cell surface could be quantified through the force measurement by the AFM.
authors: Department of Life Science, Graduate School of Bioscience and Biotechnology, Tokyo Institute of Technology, Nagatsuta, Yokohama 226-8501, Japan. kim.bmi@tmd.ac.jp
authors: Hyonchol
authors: H
authors: Kim
authors: Hideo
authors: H
authors: Arakawa
authors: Noriyuki
authors: N
authors: Hatae
authors: Yukihiko
authors: Y
authors: Sugimoto
authors: Osamu
authors: O
authors: Matsumoto
authors: Toshiya
authors: T
authors: Osada
authors: Atsushi
authors: A
authors: Ichikawa
authors: Atsushi
authors: A
authors: Ikai