SSBD:database

Detail of Fig1C

Tatsuo Shibata, Masatoshi Nishikawa, Satomi Matsuoka, Masahiro Ueda (2012) Modeling the self-organized phosphatidylinositol lipid signaling system in chemotactic cells using quantitative image analysis., Journal of cell science, Volume 125, Number Pt 21, pp. 5138-50

Published in 2012 Nov 1 (Electronic publication in Aug. 16, 2012, midnight )

• doi: 10.1242/jcs.108373
• pmid: 22899720
  

(Abstract) A key signaling event that is responsible for gradient sensing in eukaryotic cell chemotaxis is a phosphatidylinositol (PtdIns) lipid reaction system. The self-organization activity of this PtdIns lipid system induces an inherent polarity, even in the absence of an external chemoattractant gradient, by producing a localized PtdIns (3,4,5)-trisphosphate [PtdIns(3,4,5)P(3)]-enriched domain on the membrane. Experimentally, we found that such a domain could exhibit two types of behavior: (1) it could be persistent and travel on the membrane, or (2) be stochastic and transient. Taking advantage of the simultaneous visualization of PtdIns(3,4,5)P(3) and the enzyme phosphatase and tensin homolog (PTEN), for which PtdIns(3,4,5)P(3) is a substrate, we statistically demonstrated the inter-dependence of their spatiotemporal dynamics. On the basis of this statistical analysis, we developed a theoretical model for the self-organization of PtdIns lipid signaling that can accurately reproduce both persistent and transient domain formation; these types of formations can be explained by the oscillatory and excitability properties of the system, respectively.

• Algorithms
• Caffeine/pharmacology
• Cell Membrane Structures/drug effects
• Cell Membrane Structures/metabolism
• Cell Polarity
• Chemotaxis
• Computer Simulation
• Dictyostelium/cytology[major]
• Dictyostelium/drug effects
• Dictyostelium/metabolism
• Diffusion
• Models, Biological[major]
• Models, Statistical
• PTEN Phosphohydrolase/metabolism
• Phosphatidylinositol Phosphates/metabolism[major]
• Phospholipids/metabolism
• Second Messenger Systems[major]
• Single-Cell Analysis