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
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