Title |
Activity-driven relaxation of the cortical actomyosin II network synchronizes Munc18-1-dependent neurosecretory vesicle docking
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Published in |
Nature Communications, February 2015
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DOI | 10.1038/ncomms7297 |
Pubmed ID | |
Authors |
Andreas Papadopulos, Guillermo A. Gomez, Sally Martin, Jade Jackson, Rachel S. Gormal, Damien J. Keating, Alpha S. Yap, Frederic A. Meunier |
Abstract |
In neurosecretory cells, secretory vesicles (SVs) undergo Ca(2+)-dependent fusion with the plasma membrane to release neurotransmitters. How SVs cross the dense mesh of the cortical actin network to reach the plasma membrane remains unclear. Here we reveal that, in bovine chromaffin cells, SVs embedded in the cortical actin network undergo a highly synchronized transition towards the plasma membrane and Munc18-1-dependent docking in response to secretagogues. This movement coincides with a translocation of the cortical actin network in the same direction. Both effects are abolished by the knockdown or the pharmacological inhibition of myosin II, suggesting changes in actomyosin-generated forces across the cell cortex. Indeed, we report a reduction in cortical actin network tension elicited on secretagogue stimulation that is sensitive to myosin II inhibition. We reveal that the cortical actin network acts as a 'casting net' that undergoes activity-dependent relaxation, thereby driving tethered SVs towards the plasma membrane where they undergo Munc18-1-dependent docking. |
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Australia | 3 | 75% |
Canada | 1 | 25% |
Demographic breakdown
Type | Count | As % |
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Scientists | 2 | 50% |
Members of the public | 1 | 25% |
Practitioners (doctors, other healthcare professionals) | 1 | 25% |
Mendeley readers
Geographical breakdown
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Spain | 1 | 2% |
Germany | 1 | 2% |
Unknown | 48 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 14 | 27% |
Student > Master | 7 | 14% |
Researcher | 7 | 14% |
Professor | 6 | 12% |
Professor > Associate Professor | 3 | 6% |
Other | 8 | 16% |
Unknown | 6 | 12% |
Readers by discipline | Count | As % |
---|---|---|
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Biochemistry, Genetics and Molecular Biology | 10 | 20% |
Neuroscience | 9 | 18% |
Computer Science | 1 | 2% |
Psychology | 1 | 2% |
Other | 3 | 6% |
Unknown | 10 | 20% |