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Quantitative Analyses of Circadian Gene Expression in Mammalian Cell Cultures

Overview of attention for article published in PLoS Computational Biology, October 2006
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Title
Quantitative Analyses of Circadian Gene Expression in Mammalian Cell Cultures
Published in
PLoS Computational Biology, October 2006
DOI 10.1371/journal.pcbi.0020136
Pubmed ID
Authors

Mariko Izumo, Takashi R Sato, Martin Straume, Carl Hirschie Johnson

Abstract

The central circadian pacemaker is located in the hypothalamus of mammals, but essentially the same oscillating system operates in peripheral tissues and even in immortalized cell lines. Using luciferase reporters that allow automated monitoring of circadian gene expression in mammalian fibroblasts, we report the collection and analysis of precise rhythmic data from these cells. We use these methods to analyze signaling pathways of peripheral tissues by studying the responses of Rat-1 fibroblasts to ten different compounds. To quantify these rhythms, which show significant variation and large non-stationarities (damping and baseline drifting), we developed a new fast Fourier transform-nonlinear least squares analysis procedure that specifically optimizes the quantification of amplitude for circadian rhythm data. This enhanced analysis method successfully distinguishes among the ten signaling compounds for their rhythm-inducing properties. We pursued detailed analyses of the responses to two of these compounds that induced the highest amplitude rhythms in fibroblasts, forskolin (an activator of adenylyl cyclase), and dexamethasone (an agonist of glucocorticoid receptors). Our quantitative analyses clearly indicate that the synchronization mechanisms by the cAMP and glucocorticoid pathways are different, implying that actions of different genes stimulated by these pathways lead to distinctive programs of circadian synchronization.

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The data shown below were compiled from readership statistics for 176 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 1%
United States 2 1%
Italy 2 1%
France 1 <1%
Chile 1 <1%
Switzerland 1 <1%
Czechia 1 <1%
Brazil 1 <1%
Japan 1 <1%
Other 1 <1%
Unknown 163 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 41 23%
Researcher 32 18%
Student > Master 22 13%
Professor > Associate Professor 17 10%
Student > Bachelor 16 9%
Other 24 14%
Unknown 24 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 69 39%
Biochemistry, Genetics and Molecular Biology 31 18%
Neuroscience 14 8%
Medicine and Dentistry 10 6%
Engineering 8 5%
Other 17 10%
Unknown 27 15%