Detail of Fig1a_Rac1

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Project
Title
Time-lapse FRET microscopy images of Rac1 activity in human HT-1080 fibrosarcoma cels
Description
NA
Release, Updated
2017-10-03,
2018-11-15
License
CC BY
Kind
Image data based on Experiment
File Formats
Data size
480.5 MB

Organism
H. sapiens ( NCBI:txid9606 )
Strain(s)
HT-1080
Cell Line
-
Gene symbols
Rac1

Datatype
cell dynamics
Molecular Function (MF)
Biological Process (BP)
cellular protein localization ( GO:0034613 )
Cellular Component (CC)
-
Biological Imaging Method
XYZ Scale
XY: 0.4933 micrometer/pixel, Z: NA
T scale
10 minute for each time interval

Image Acquisition
Experiment type
FRET
Microscope type
ConfocalMicroscope
Acquisition mode
LaserScanningConfocalMicroscopy
Contrast method
Fluorescence
Microscope model
Olympus IX81
Detector model
Roper Scientific Cool SNAP-K4
Objective model
Olympus UPLANSAPO 60x O
Filter set

Summary of Methods
See details in Yamao et al. (2015) Scientific Reports, 5: 17527.
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
Naoki Honda , Kyoto University , Graduate School of Informatics
Contributors
Masataka Yamao, Honda Naoki, Katsuyuki Kunida, Kazuhiro Aoki, Michiyuki Matsuda, Shin Ishii

OMERO Dataset
OMERO Project
Source