Towards correlative imaging of plant cortical microtubule arrays: combining ultrastructure with real-time microtubule dynamics

2009 ◽  
Vol 235 (3) ◽  
pp. 241-251 ◽  
Author(s):  
D.A. BARTON ◽  
J.C. GARDINER ◽  
R.L. OVERALL
2018 ◽  
Vol 14 (2) ◽  
pp. e1005959 ◽  
Author(s):  
Bandan Chakrabortty ◽  
Ikram Blilou ◽  
Ben Scheres ◽  
Bela M. Mulder

2017 ◽  
Vol 28 (19) ◽  
pp. 2543-2554 ◽  
Author(s):  
Swathi Ayloo ◽  
Pedro Guedes-Dias ◽  
Amy E. Ghiretti ◽  
Erika L. F. Holzbaur

The efficient transport of cargoes within axons and dendrites is critical for neuronal function. Although we have a basic understanding of axonal transport, much less is known about transport in dendrites. We used an optogenetic approach to recruit motor proteins to cargo in real time within axons or dendrites in hippocampal neurons. Kinesin-1, a robust axonal motor, moves cargo less efficiently in dendrites. In contrast, cytoplasmic dynein efficiently navigates both axons and dendrites; in both compartments, dynamic microtubule plus ends enhance dynein-dependent transport. To test the predictions of the optogenetic assay, we examined the contribution of dynein to the motility of an endogenous dendritic cargo and found that dynein inhibition eliminates the retrograde bias of BDNF/TrkB trafficking. However, inhibition of microtubule dynamics has no effect on BDNF/TrkB motility, suggesting that dendritic kinesin motors may cooperate with dynein to drive the transport of signaling endosomes into the soma. Collectively our data highlight compartment-specific differences in kinesin activity that likely reflect specialized tuning for localized cytoskeletal determinants, whereas dynein activity is less compartment specific but is more responsive to changes in microtubule dynamics.


2007 ◽  
Vol 104 (14) ◽  
pp. 5854-5859 ◽  
Author(s):  
S. DeBolt ◽  
R. Gutierrez ◽  
D. W. Ehrhardt ◽  
C. V. Melo ◽  
L. Ross ◽  
...  

2018 ◽  
Vol 13 (1) ◽  
pp. e1422468 ◽  
Author(s):  
Kouichi Soga ◽  
Kazuyuki Wakabayashi ◽  
Takayuki Hoson

Cell ◽  
1990 ◽  
Vol 62 (3) ◽  
pp. 579-589 ◽  
Author(s):  
L.D. Belmont ◽  
A.A. Hyman ◽  
K.E. Sawin ◽  
T.J. Mitchison

2017 ◽  
Author(s):  
Bandan Chakrabortty ◽  
Ben Scheres ◽  
Bela Mulder

AbstractPlant morphogenesis is strongly dependent on the directional growth and the subsequent oriented division of individual cells. It has been shown that the plant cortical microtubule array plays a key role in controlling both these processes. This ordered structure emerges as the collective result of stochastic interactions between large numbers of dynamic microtubules. To elucidate this complex self-organization process a number of analytical and computational approaches to study the dynamics of cortical microtubules have been proposed. To date, however, these models have been restricted to 2D planes or geometrically simple surfaces in 3D, which strongly limits their applicability as plant cells display a wide variety of shapes. This limitation is even more acute, as both local as well as global geometrical features of cells are expected to influence the overall organization of the array. Here we describe a framework for efficiently simulating microtubule dynamics on triangulated approximations of arbitrary three dimensional surfaces. This allows the study of microtubule array organization on realistic cell surfaces obtained by segmentation of microscopic images. We validate the framework against expected or known results for the spherical and cubical geometry. We then use it to systematically study the individual contributions of global geometry, edge-induced catastrophes and cell face-induced stability to array organization in a cuboidal geometry. Finally, we apply our framework to analyze the highly non-trivial geometry of leaf pavement cells of Nicotiana benthamiana and Hedera helix. We show that our simulations can predict multiple features of the array structure in these cells, revealing, among others, strong constraints on the orientation of division planes.


2017 ◽  
Vol 162 (1) ◽  
pp. 135-144 ◽  
Author(s):  
Kouichi Soga ◽  
Chiaki Yamazaki ◽  
Motoshi Kamada ◽  
Naoki Tanigawa ◽  
Haruo Kasahara ◽  
...  

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