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Oscillatory Dynamics of Cell Cycle Proteins in Single Yeast Cells Analyzed by Imaging Cytometry

Overview of attention for article published in PLOS ONE, October 2011
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Title
Oscillatory Dynamics of Cell Cycle Proteins in Single Yeast Cells Analyzed by Imaging Cytometry
Published in
PLOS ONE, October 2011
DOI 10.1371/journal.pone.0026272
Pubmed ID
Authors

David A. Ball, Julie Marchand, Magaly Poulet, William T. Baumann, Katherine C. Chen, John J. Tyson, Jean Peccoud

Abstract

Progression through the cell division cycle is orchestrated by a complex network of interacting genes and proteins. Some of these proteins are known to fluctuate periodically during the cell cycle, but a systematic study of the fluctuations of a broad sample of cell-cycle proteins has not been made until now. Using time-lapse fluorescence microscopy, we profiled 16 strains of budding yeast, each containing GFP fused to a single gene involved in cell cycle regulation. The dynamics of protein abundance and localization were characterized by extracting the amplitude, period, and other indicators from a series of images. Oscillations of protein abundance could clearly be identified for Cdc15, Clb2, Cln1, Cln2, Mcm1, Net1, Sic1, and Whi5. The period of oscillation of the fluorescently tagged proteins is generally in good agreement with the inter-bud time. The very strong oscillations of Net1 and Mcm1 expression are remarkable since little is known about the temporal expression of these genes. By collecting data from large samples of single cells, we quantified some aspects of cell-to-cell variability due presumably to intrinsic and extrinsic noise affecting the cell cycle.

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Geographical breakdown

Country Count As %
United States 1 1%
China 1 1%
Germany 1 1%
Unknown 81 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 32%
Researcher 17 20%
Student > Master 12 14%
Student > Bachelor 9 11%
Professor 8 10%
Other 9 11%
Unknown 2 2%
Readers by discipline Count As %
Agricultural and Biological Sciences 42 50%
Biochemistry, Genetics and Molecular Biology 21 25%
Engineering 3 4%
Mathematics 2 2%
Chemical Engineering 2 2%
Other 8 10%
Unknown 6 7%