Titre
An integrated image analysis platform to quantify signal transduction in single cells.
Type
article
Institution
Externe
Périodique
Auteur(s)
Pelet, S.
Auteure/Auteur
Dechant, R.
Auteure/Auteur
Lee, S.S.
Auteure/Auteur
van Drogen, F.
Auteure/Auteur
Peter, M.
Auteure/Auteur
Liens vers les personnes
ISSN
1757-9708
Statut éditorial
Publié
Date de publication
2012
Volume
4
Numéro
10
Première page
1274
Dernière page/numéro d’article
1282
Langue
anglais
Résumé
Microscopy can provide invaluable information about biological processes at the single cell level. It remains a challenge, however, to extract quantitative information from these types of datasets. We have developed an image analysis platform named YeastQuant to simplify data extraction by offering an integrated method to turn time-lapse movies into single cell measurements. This platform is based on a database with a graphical user interface where the users can describe their experiments. The database is connected to the engineering software Matlab, which allows extracting the desired information by automatically segmenting and quantifying the microscopy images. We implemented three different segmentation methods that recognize individual cells under different conditions, and integrated image analysis protocols that allow measuring and analyzing distinct cellular readouts. To illustrate the power and versatility of YeastQuant, we investigated dynamic signal transduction processes in yeast. First, we quantified the expression of fluorescent reporters induced by osmotic stress to study noise in gene expression. Second, we analyzed the dynamic relocation of endogenous proteins from the cytoplasm to the cell nucleus, which provides a fast measure of pathway activity. These examples demonstrate that YeastQuant provides a versatile and expandable database and an experimental framework that improves image analysis and quantification of diverse microscopy-based readouts. Such dynamic single cell measurements are highly needed to establish mathematical models of signal transduction pathways.
PID Serval
serval:BIB_02F9CC58668C
PMID
Date de création
2012-12-05T12:00:08.171Z
Date de création dans IRIS
2025-05-20T19:59:07Z