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Sarcomeric Pattern Formation by Actin Cluster Coalescence

Overview of attention for article published in PLoS Computational Biology, June 2012
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Title
Sarcomeric Pattern Formation by Actin Cluster Coalescence
Published in
PLoS Computational Biology, June 2012
DOI 10.1371/journal.pcbi.1002544
Pubmed ID
Authors

Benjamin M. Friedrich, Elisabeth Fischer-Friedrich, Nir S. Gov, Samuel A. Safran

Abstract

Contractile function of striated muscle cells depends crucially on the almost crystalline order of actin and myosin filaments in myofibrils, but the physical mechanisms that lead to myofibril assembly remains ill-defined. Passive diffusive sorting of actin filaments into sarcomeric order is kinetically impossible, suggesting a pivotal role of active processes in sarcomeric pattern formation. Using a one-dimensional computational model of an initially unstriated actin bundle, we show that actin filament treadmilling in the presence of processive plus-end crosslinking provides a simple and robust mechanism for the polarity sorting of actin filaments as well as for the correct localization of myosin filaments. We propose that the coalescence of crosslinked actin clusters could be key for sarcomeric pattern formation. In our simulations, sarcomere spacing is set by filament length prompting tight length control already at early stages of pattern formation. The proposed mechanism could be generic and apply both to premyofibrils and nascent myofibrils in developing muscle cells as well as possibly to striated stress-fibers in non-muscle cells.

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The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
France 1 2%
Brazil 1 2%
Unknown 51 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 33%
Student > Ph. D. Student 13 24%
Student > Master 7 13%
Lecturer 3 6%
Professor 3 6%
Other 5 9%
Unknown 5 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 35%
Physics and Astronomy 12 22%
Engineering 8 15%
Mathematics 2 4%
Biochemistry, Genetics and Molecular Biology 2 4%
Other 5 9%
Unknown 6 11%