Summary of ssbd-repos-00033

SSBD:database
URL

Name
ssbd-repos-00033 (33-Yamao-MolDynRho)
URL
DOI
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Title
-
Description
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Submited Date
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Release Date
2017-10-03
Updated Date
2018-11-15
License
Funding information
-
File formats
Data size
805.3 MB

Organism
H. sapiens
Strain
HT-1080
Cell Line
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Genes
Cdc42, Rac1
Proteins
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GO Molecular Function (MF)
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GO Biological Process (BP)
cellular protein localization
GO Cellular Component (CC)
NA
Study Type
-
Imaging Methods
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Method Summary
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Related paper(s)

Masataka Yamao, Honda Naoki, Katsuyuki Kunida, Kazuhiro Aoki, Michiyuki Matsuda, Shin Ishii (2015) Distinct predictive performance of Rac1 and Cdc42 in cell migration., Scientific reports, Volume 5, pp. 17527

Published in 2015 Dec 4 (Electronic publication in Dec. 4, 2015, midnight )

(Abstract) We propose a new computation-based approach for elucidating how signaling molecules are decoded in cell migration. In this approach, we performed FRET time-lapse imaging of Rac1 and Cdc42, members of Rho GTPases which are responsible for cell motility, and quantitatively identified the response functions that describe the conversion from the molecular activities to the morphological changes. Based on the identified response functions, we clarified the profiles of how the morphology spatiotemporally changes in response to local and transient activation of Rac1 and Cdc42, and found that Rac1 and Cdc42 activation triggers laterally propagating membrane protrusion. The response functions were also endowed with property of differentiator, which is beneficial for maintaining sensitivity under adaptation to the mean level of input. Using the response function, we could predict the morphological change from molecular activity, and its predictive performance provides a new quantitative measure of how much the Rho GTPases participate in the cell migration. Interestingly, we discovered distinct predictive performance of Rac1 and Cdc42 depending on the migration modes, indicating that Rac1 and Cdc42 contribute to persistent and random migration, respectively. Thus, our proposed predictive approach enabled us to uncover the hidden information processing rules of Rho GTPases in the cell migration.
(MeSH Terms)

Contact(s)
Naoki Honda
Organization(s)
Kyoto University , Graduate School of Informatics
Image Data Contributors
Quantitative Data Contributors

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