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A Chemical Genetics Approach Reveals H,K-ATPase-Mediated Membrane Voltage Is Required for Planarian Head Regeneration

Overview of attention for article published in Cell Chemical Biology, January 2011
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Title
A Chemical Genetics Approach Reveals H,K-ATPase-Mediated Membrane Voltage Is Required for Planarian Head Regeneration
Published in
Cell Chemical Biology, January 2011
DOI 10.1016/j.chembiol.2010.11.012
Pubmed ID
Authors

Wendy S. Beane, Junji Morokuma, Dany S. Adams, Michael Levin

Abstract

Biophysical signaling is required for both embryonic polarity and regenerative outgrowth. Exploiting endogenous ion transport for regenerative therapies will require direct regulation of membrane voltage. Here, we develop a pharmacological method to target ion transporters, uncovering a role for membrane voltage as a key regulator of anterior polarity in regenerating planaria. Utilizing the highly specific inhibitor, SCH-28080, our data reveal that H(+),K(+)-ATPase-mediated membrane depolarization is essential for anterior gene expression and brain induction. H(+),K(+)-ATPase-independent manipulation of membrane potential with ivermectin confirms that depolarization drives head formation, even at posterior-facing wounds. Using this chemical genetics approach, we demonstrate that membrane voltage controls head-versus-tail identity during planarian regeneration. Our data suggest well-characterized drugs (already approved for human use) might be exploited to control adult stem cell-driven pattern formation during the regeneration of complex structures.

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Mendeley readers

The data shown below were compiled from readership statistics for 153 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 3%
United Kingdom 1 <1%
Germany 1 <1%
Unknown 147 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 35 23%
Researcher 26 17%
Student > Bachelor 24 16%
Student > Master 14 9%
Professor > Associate Professor 11 7%
Other 22 14%
Unknown 21 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 63 41%
Biochemistry, Genetics and Molecular Biology 33 22%
Medicine and Dentistry 11 7%
Neuroscience 6 4%
Engineering 3 2%
Other 11 7%
Unknown 26 17%