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Key Role of Local Regulation in Chemosensing Revealed by a New Molecular Interaction-Based Modeling Method

Overview of attention for article published in PLoS Computational Biology, July 2006
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Title
Key Role of Local Regulation in Chemosensing Revealed by a New Molecular Interaction-Based Modeling Method
Published in
PLoS Computational Biology, July 2006
DOI 10.1371/journal.pcbi.0020082
Pubmed ID
Authors

Martin Meier-Schellersheim, Xuehua Xu, Bastian Angermann, Eric J Kunkel, Tian Jin, Ronald N Germain

Abstract

The signaling network underlying eukaryotic chemosensing is a complex combination of receptor-mediated transmembrane signals, lipid modifications, protein translocations, and differential activation/deactivation of membrane-bound and cytosolic components. As such, it provides particularly interesting challenges for a combined computational and experimental analysis. We developed a novel detailed molecular signaling model that, when used to simulate the response to the attractant cyclic adenosine monophosphate (cAMP), made nontrivial predictions about Dictyostelium chemosensing. These predictions, including the unexpected existence of spatially asymmetrical, multiphasic, cyclic adenosine monophosphate-induced PTEN translocation and phosphatidylinositol-(3,4,5)P3 generation, were experimentally verified by quantitative single-cell microscopy leading us to propose significant modifications to the current standard model for chemoattractant-induced biochemical polarization in this organism. Key to this successful modeling effort was the use of "Simmune," a new software package that supports the facile development and testing of detailed computational representations of cellular behavior. An intuitive interface allows user definition of complex signaling networks based on the definition of specific molecular binding site interactions and the subcellular localization of molecules. It automatically translates such inputs into spatially resolved simulations and dynamic graphical representations of the resulting signaling network that can be explored in a manner that closely parallels wet lab experimental procedures. These features of Simmune were critical to the model development and analysis presented here and are likely to be useful in the computational investigation of many aspects of cell biology.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 4%
Japan 2 2%
Mexico 1 1%
Unknown 77 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 31 37%
Professor > Associate Professor 17 20%
Student > Ph. D. Student 13 16%
Student > Bachelor 4 5%
Professor 4 5%
Other 9 11%
Unknown 5 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 37 45%
Physics and Astronomy 10 12%
Biochemistry, Genetics and Molecular Biology 9 11%
Computer Science 6 7%
Medicine and Dentistry 4 5%
Other 10 12%
Unknown 7 8%