scholarly journals Faculty Opinions recommendation of Rap1 controls cell adhesion and cell motility through the regulation of myosin II.

Author(s):  
Orion Weiner
2007 ◽  
Vol 176 (7) ◽  
pp. 1021-1033 ◽  
Author(s):  
Taeck J. Jeon ◽  
Dai-Jen Lee ◽  
Sylvain Merlot ◽  
Gerald Weeks ◽  
Richard A. Firtel

We have investigated the role of Rap1 in controlling chemotaxis and cell adhesion in Dictyostelium discoideum. Rap1 is activated rapidly in response to chemoattractant stimulation, and activated Rap1 is preferentially found at the leading edge of chemotaxing cells. Cells expressing constitutively active Rap1 are highly adhesive and exhibit strong chemotaxis defects, which are partially caused by an inability to spatially and temporally regulate myosin assembly and disassembly. We demonstrate that the kinase Phg2, a putative Rap1 effector, colocalizes with Rap1–guanosine triphosphate at the leading edge and is required in an in vitro assay for myosin II phosphorylation, which disassembles myosin II and facilitates filamentous actin–mediated leading edge protrusion. We suggest that Rap1/Phg2 plays a role in controlling leading edge myosin II disassembly while passively allowing myosin II assembly along the lateral sides and posterior of the cell.


1991 ◽  
Vol 115 (5) ◽  
pp. 1267-1274 ◽  
Author(s):  
S Eliott ◽  
P H Vardy ◽  
K L Williams

While the role of myosin II in muscle contraction has been well characterized, less is known about the role of myosin II in non-muscle cells. Recent molecular genetic experiments on Dictyostelium discoideum show that myosin II is necessary for cytokinesis and multicellular development. Here we use immunofluorescence microscopy with monoclonal and polyclonal antimyosin antibodies to visualize myosin II in cells of the multicellular D. discoideum slug. A subpopulation of peripheral and anterior cells label brightly with antimyosin II antibodies, and many of these cells display a polarized intracellular distribution of myosin II. Other cells in the slug label less brightly and their cytoplasm displays a more homogeneous distribution of myosin II. These results provide insight into cell motility within a three-dimensional tissue and they are discussed in relation to the possible roles of myosin II in multicellular development.


2019 ◽  
Vol 218 (12) ◽  
pp. 4093-4111 ◽  
Author(s):  
Panagiotis Mistriotis ◽  
Emily O. Wisniewski ◽  
Kaustav Bera ◽  
Jeremy Keys ◽  
Yizeng Li ◽  
...  

Cells migrate in vivo through complex confining microenvironments, which induce significant nuclear deformation that may lead to nuclear blebbing and nuclear envelope rupture. While actomyosin contractility has been implicated in regulating nuclear envelope integrity, the exact mechanism remains unknown. Here, we argue that confinement-induced activation of RhoA/myosin-II contractility, coupled with LINC complex-dependent nuclear anchoring at the cell posterior, locally increases cytoplasmic pressure and promotes passive influx of cytoplasmic constituents into the nucleus without altering nuclear efflux. Elevated nuclear influx is accompanied by nuclear volume expansion, blebbing, and rupture, ultimately resulting in reduced cell motility. Moreover, inhibition of nuclear efflux is sufficient to increase nuclear volume and blebbing on two-dimensional surfaces, and acts synergistically with RhoA/myosin-II contractility to further augment blebbing in confinement. Cumulatively, confinement regulates nuclear size, nuclear integrity, and cell motility by perturbing nuclear flux homeostasis via a RhoA-dependent pathway.


2020 ◽  
Vol 31 (20) ◽  
pp. 2234-2248
Author(s):  
Maha Abedrabbo ◽  
Shoshana Ravid

Here we show that Scribble (Scrib), Lethal giant larvae 1 (Lgl1), and myosin II form a complex in vivo and colocalize at the cell leading edge of migrating cells, and this colocalization is interdependent. Scrib and Lgl1 are required for proper cell adhesion, polarity, and migration.


1996 ◽  
Vol 175 (2) ◽  
pp. 218-226 ◽  
Author(s):  
Xiaoxin Susan Xu ◽  
Adam Kuspa ◽  
Danny Fuller ◽  
William F. Loomis ◽  
David A. Knecht

2015 ◽  
Vol 128 (23) ◽  
pp. 4317-4327 ◽  
Author(s):  
M. Kim ◽  
A. M. Shewan ◽  
A. J. Ewald ◽  
Z. Werb ◽  
K. E. Mostov

2010 ◽  
Vol 115 (5) ◽  
pp. 1137-1149 ◽  
Author(s):  
Alexandros A. Lavdas ◽  
Rodica Efrose ◽  
Vassilis Douris ◽  
Maria Gaitanou ◽  
Florentia Papastefanaki ◽  
...  

1998 ◽  
Vol 17 (2) ◽  
pp. 71-82 ◽  
Author(s):  
Josef Smolle

Objective:To develop an interpretation procedure which estimates simulation parameters (tumour cell motility, tumour cell adhesion, autocrine and paracrine growth control, stroma destruction) of simulated patterns solely based on morphometric features of the morphologic pattern.Methods:A cellular automaton computer simulation program was developed which produces morphologic patterns by growth of a seed of tumour cells. At the beginning of each simulation run certain simulation parameters are assigned to the tumour cells. After the run has been completed, the resulting pattern is evaluated by a set of morphometric features. Simulation parameters and resulting morphometric features of 27,800 simulations were stored in a database and were used for the evaluation of potential relationships.Results:Correlation analysis showed highly significant correlations between morphometric features on the one hand and the preset simulation parameters (tumour cell motility, tumour cell adhesion, autocrine and paracrine growth control, stroma destruction) on the other. Correlation coefficients, however, varied from 0.72 to 0.99. When only one simulation parameter varied while all others were kept constant, morphometric features yielded a highly reliable estimate of the particular simulation parameter. When variability was extended to 4 simulation parameters, morphometric features were less effective in estimating the setting of the parameters. Though in all patterns tested several possible simulation parameter constellations could be ruled out, morphometric features were usually compatible with more than one set of simulation parameters thus preventing a straightforward interpretation.Conclusions:Though simulation parameters significantly and reproducibly influence the resulting morphologic pattern as characterized by morphometric features, estimates of the simulation parameters based on morphometric features yield equivocal results.


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