Direct observation of individual tubulin dimers binding to growing microtubules

Mickolajczyk, Keith J.; Geyer, Elisabeth A.; Kim, Tae; Rice, Luke M.; Hancock, William O.

doi:10.1073/pnas.1815823116

Cited by 69 publications

(89 citation statements)

References 59 publications

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“…We found that EB1 dwell time distributions on our disrupted structure microtubules were best modeled as two exponential distributions (Fig S2C,D), including one with a short dwell time (~20 ms), which could be associated with edge-bound EB1. In evaluating this dwell time relative to the kinetics of αβ-tubulin association, in 10 µM tubulin, it has been estimated that a free tubulin subunit would arrive to the growing end of the microtubule as rapidly as every ~2 ms , or as slowly as every ~10 ms (Mickolajczyk et al, 2019). Therefore, even the relatively short dwell times of edge-bounded EB1 molecules would be long enough to allow for multiple tubulin subunit arrivals while EB1 is bound to a protofilament edge.…”

Section: Discussionmentioning

confidence: 99%

Structural state recognition facilitates tip tracking of EB1 at growing microtubule ends in cells

Reid

Coombes

Mukherjee

et al. 2019

Preprint

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The microtubule binding protein EB1 specifically targets the growing ends of microtubules in cells, where EB1 facilitates the interactions of cellular proteins with microtubule plus-ends.Microtubule end targeting of EB1 has been attributed to high affinity binding of EB1 to GTPtubulin that is present at growing microtubule ends. However, our 3D single-molecule diffusion simulations predicted a ~6000% increase in EB1 arrivals to open, tapered microtubule tip structures relative to closed lattice conformations. Using quantitative fluorescence, singlemolecule, and electron microscopy experiments, we found that the binding of EB1 onto opened, structurally disrupted microtubules was dramatically increased relative to closed, intact microtubules, regardless of hydrolysis state. Correspondingly, in cells, the conversion of growing microtubule ends from a tapered into a blunt configuration resulted in reduced EB1 targeting. Together, our results suggest that microtubule structural recognition, based on a fundamental diffusion-limited binding model, facilitates the tip tracking of EB1 at growing microtubule ends. P a g e | 3

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Section: Discussionmentioning

confidence: 99%

Structural state recognition facilitates tip tracking of EB1 at growing microtubule ends in cells

Reid

Coombes

Mukherjee

et al. 2019

Preprint

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“…We refined our prior algorithm (Ayaz et al , 2014; Piedra et al , 2016; Mickolajczyk et al , 2018) that used kinetic Monte Carlo (Gillespie, 1976; Gibson and Bruck, 2000) to simulate microtubule dynamics. The algorithm simulates one biochemical event (dimer association, dissociation, and GTP hydrolysis) at a time and therefore provides a ‘movie’ of microtubule dynamics.…”

Section: Resultsmentioning

confidence: 99%

“…In the present study, we sought to investigate the consequences of incorporating various candidates for “missing state/biochemistry” into a computational model, with the aim of better predicting the concentration-dependence of catastrophe. We elaborated a Monte Carlo-based algorithm developed in the lab (Ayaz et al , 2014; Piedra et al , 2016; Mickolajczyk et al , 2018) to test if incorporating a GDP.P i state or long-range coupling (reflecting conformational accommodation) improved predictions of microtubule catastrophe. We incorporated the GDP.P i state and conformational coupling separately for simplicity and to be able to assess the effect of each change in isolation.…”

Section: Introductionmentioning

confidence: 99%

A role for long-range, through-lattice coupling in microtubule catastrophe

Kim

Rice

2018

Preprint

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20Microtubules are cylindrical polymers of αβ-tubulin that play critical roles in fundamental 21 processes like chromosome segregation and vesicular transport. Microtubules display 22 dynamic instability, switching stochastically between growing and rapid shrinking as a 23 consequence of GTPase activity in the lattice. The molecular mechanisms behind 24 microtubule catastrophe, the switch from growing to rapid shrinking, remain poorly 25 defined. Indeed, two-state stochastic models that seek to describe microtubule 26 dynamics purely in terms of the biochemical properties of GTP-and GDP-bound αβ-27 tubulin incorrectly predict the concentration-dependence of microtubule catastrophe. 28 Recent studies provided evidence for three distinct conformations of αβ-tubulin in the 29 lattice that likely correspond to GTP, GDP.P i , and GDP. The incommensurate lattices 30 observed for these different conformations raises the possibility that in a mixed 31 nucleotide state lattice, neighboring tubulin dimers might modulate each other's 32 conformations and hence their biochemistry. We explored whether incorporating a 33 GDP.P i state or the likely effects of conformational accommodation can improve 34 predictions of catastrophe. Adding a GDP.P i intermediate did not improve the model. In 35 contrast, adding neighbor-dependent modulation of tubulin biochemistry improved 36 predictions of catastrophe. Conformational accommodation should propagate beyond 37 nearest-neighbor contacts, and consequently our modeling demonstrates that long-38 range, through-lattice effects are important determinants of microtubule catastrophe.39 40 41Microtubules (MTs) are hollow cylindrical polymers of αβ-tubulin that have essential 42 roles segregating chromosomes during cell division, organizing the cytoplasm, 43 establishing cellular polarity, and more (Desai and Mitchison, 1997). These 44 fundamental activities depend critically on dynamic instability, the stochastic 45 switching of MTs between phases of growing and rapid shrinking (Mitchison and 46 Kirschner, 1984). Dynamic instability is itself a consequence of αβ-tubulin GTPase 47 activity and how it affects interactions between αβ-tubulin in the lattice and at the 48 microtubule end. Although a predictive molecular understanding of catastrophe 49 remains elusive, the broad outlines of an understanding have been established 50 (Mitchison and Kirschner, 1984; VanBuren et al., 2002; Gardner et al., 2011b; 51 Bowne- Anderson et al., 2013; Brouhard, 2015; Duellberg et al., 2016; Brouhard and 52 Rice, 2018). Unpolymerized, GTP-bound αβ-tubulin subunits readily associate at the 53 growing tip of the MTs. Once incorporated into the lattice, αβ-tubulin GTPase activity 54 is accelerated. The assembly-dependence of GTPase activity results in a "stabilizing 55 cap" of GTP-or GDP.P i -bound αβ-tubulin near the end of the growing microtubules. 56Loss of this stabilizing cap triggers catastrophe, the switch from growing to rapid 57 shrinking, because it exposes the more labile GDP-bound micro...

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“…Finally, ATP motility buffer was introduced and incubated for 5 min to initiate movement, the flow cell was then transferred to the microscope. The iSCAT microscope used in the work was described previously 34 . Images were taken using custom written LabVIEW software.…”

Section: Methodsmentioning

confidence: 99%

Dynactin p150 promotes processive motility of DDB complexes by minimizing diffusional behavior of dynein

Feng

Gicking

Hancock

2019

Preprint

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1 9 2 0Cytoplasmic dynein is activated by forming a complex with dynactin and the adaptor 2 1 protein BicD2. We used Interferometric Scattering (iSCAT) microscopy to track dynein-2 2 dynactin-BicD2 (DDB) complexes in vitro and developed a regression-based algorithm 2 3to classify switching between processive, diffusive and stuck motility states. We find that 2 4 DDB spends 65% of its time undergoing processive stepping, 4% undergoing 1D 2 5 diffusion, and the remaining time transiently stuck to the microtubule. Although the p150 2 6 subunit was previously shown to enable dynactin diffusion along microtubules, blocking 2 7 p150 enhanced the proportion of time DDB diffused and reduced the time DDB 2 8 processively walked. Thus, DDB diffusive behavior most likely results from dynein 2 9switching into an inactive (diffusive) state, rather than p150 tethering the complex to the 3 0 microtubule. DDB -kinesin-1 complexes, formed using a DNA adapter, moved slowly 3 1 and persistently, and blocking p150 led to a 70 nm/s plus-end shift in the average 3 2 velocity, in quantitative agreement with the increase in diffusivity seen in isolated DDB. 3The data suggest a DDB activation model in which engagement of dynactin p150 with 3 4

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Direct observation of individual tubulin dimers binding to growing microtubules

Cited by 69 publications

References 59 publications

Structural state recognition facilitates tip tracking of EB1 at growing microtubule ends in cells

Structural state recognition facilitates tip tracking of EB1 at growing microtubule ends in cells

A role for long-range, through-lattice coupling in microtubule catastrophe

Dynactin p150 promotes processive motility of DDB complexes by minimizing diffusional behavior of dynein

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