• DocumentCode
    3409601
  • Title

    Quantitative analysis of membrane protein localization and signaling

  • Author

    Kasson, Peter M. ; Huppa, Johannes B. ; Davis, Mark M. ; Brunger, Axel T.

  • Author_Institution
    Stanford Univ., CA, USA
  • fYear
    2004
  • fDate
    16-19 Aug. 2004
  • Firstpage
    540
  • Lastpage
    541
  • Abstract
    Fluorescence microscopy of labeled proteins yields a wealth of data on cell signaling processes. However, systems for quantitative analysis of such data have lagged behind the recent progress in data acquisition technology. As cellular protein redistribution plays a key role in proximal signaling and the establishment of cell polarity, quantitative information is critical for understanding many signaling networks. We have developed a robust automated system to analyze membrane protein redistribution based on datasets obtained via fluorescence video microscopy. Our system provides methods for cell surface segmentation and reconstruction, cell shape tracking, cell-surface parameterization, and cluster formation analysis. Our system is novel in both its integration and its surface-based approach, enabling model-free analysis of protein redistribution across the entire cell. We validate our system by measuring receptor clustering in T lymphocytes undergoing activation, obtaining clustering velocities consistent with the previously reported single-particle tracking data that serve as our reference standard. Our methods generalize to many cell-signaling phenomena, allowing quantitative measurement of these cell membrane processes and offering the ability to derive empiric parameters for spatial signaling network models.
  • Keywords
    biology computing; biomembranes; blood; cellular biophysics; fluorescence; pattern clustering; proteins; T lymphocytes; cell polarity; cell shape tracking; cell signaling; cell surface reconstruction; cell surface segmentation; cell-surface parameterization; cellular protein redistribution; cluster formation analysis; clustering velocities; data acquisition technology; fluorescence video microscopy; labeled proteins; membrane protein localization; receptor clustering; robust automated system; single-particle tracking data; Biomembranes; Cellular networks; Data acquisition; Data analysis; Fluorescence; Microscopy; Proteins; Signal analysis; Signal processing; Surface reconstruction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Systems Bioinformatics Conference, 2004. CSB 2004. Proceedings. 2004 IEEE
  • Print_ISBN
    0-7695-2194-0
  • Type

    conf

  • DOI
    10.1109/CSB.2004.1332489
  • Filename
    1332489