Header

UZH-Logo

Maintenance Infos

An integrated image analysis platform to quantify signal transduction in single cells


Pelet, Serge; Dechant, Reinhard; Lee, Sung Sik; van Drogen, Frank; Peter, Matthias (2012). An integrated image analysis platform to quantify signal transduction in single cells. Integrative Biology, 4:1274-82.

Abstract

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.

Abstract

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.

Statistics

Citations

13 citations in Web of Science®
12 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

45 downloads since deposited on 12 Sep 2013
17 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:Special Collections > SystemsX.ch
Special Collections > SystemsX.ch > Research, Technology and Development Projects > YeastX
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Date:2012
Deposited On:12 Sep 2013 10:31
Last Modified:07 Dec 2017 21:33
Publisher:RSC Publishing
ISSN:1757-9694
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1039/c2ib20139a

Download

Download PDF  'An integrated image analysis platform to quantify signal transduction in single cells'.
Preview
Filetype: PDF
Size: 7MB
View at publisher