2009年
On the Synchrony of Morphological and Molecular Signaling Events in Cell Migration
ADVANCES IN NEURO-INFORMATION PROCESSING, PT I
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- 巻
- 5506
- 号
- PART 1
- 開始ページ
- 469
- 終了ページ
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- 記述言語
- 英語
- 掲載種別
- 研究論文(国際会議プロシーディングス)
- DOI
- 10.1007/978-3-642-02490-0_58
- 出版者・発行元
- SPRINGER-VERLAG BERLIN
This paper investigates the dynamics of cell migration, which is the movement of a cell towards a certain target area. More specifically, the objective is to analyze the causal interdependence between cellular-morphological events and molecular-signaling events. To this end, a novel data, analysis method is developed: first the local morphological changes and molecular signaling events are determined by means of edge evolution tracking (EET), next the interdependence of those events is quantified through the method of stochastic event synchrony (SES).
The proposed method is applied to time-lapse fluorescence resonance energy transfer (FRET) images of Rac1 activity in motile HT1080 cells; the protein Rac1 is well known to induce filamentous structures that enable cells to migrate. Results show a significant delay between local Rac1 activity events and morphological events. This observation provides new insights into the dynamic relationship between cellular-morphological change and molecular-signaling of migrating cells, and may pave the way to novel biophysical models of cell migration.
The proposed method is applied to time-lapse fluorescence resonance energy transfer (FRET) images of Rac1 activity in motile HT1080 cells; the protein Rac1 is well known to induce filamentous structures that enable cells to migrate. Results show a significant delay between local Rac1 activity events and morphological events. This observation provides new insights into the dynamic relationship between cellular-morphological change and molecular-signaling of migrating cells, and may pave the way to novel biophysical models of cell migration.
- リンク情報
- ID情報
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- DOI : 10.1007/978-3-642-02490-0_58
- ISSN : 0302-9743
- J-Global ID : 200902216265360070
- Web of Science ID : WOS:000272340200058