In summary, we developed a new method to quantify the turnover of individual microtubules in spindles, accurately quantified spindle polymerization dynamics in the 4- to 20-s time scale for the first time and provided evidence that nonkinetochore microtubules are not measurably stabilized by proximity to chromosomes or by the spindle environment. Our measurements and conclusions apply to nonkinetochore microtubules, which comprise the majority in X. laevis
egg extract spindles, and not to kinetochore microtubules, which are known to be preferentially stabilized in many systems. Because only nonkinetochore microtubules are required for extract spindle assembly (Heald et al., 1996
), our data imply that anastral spindle assembly can occur without microtubule stabilization. This finding held when we analyzed all lifetimes (i.e., >4 s) and also when we restricted the analysis to lifetimes >30 s, to remove possible complication from microtubule tip dynamics that do not contribute to micrometer-scale growth and shrinkage. Mitotic spindles in mammalian somatic cells can also assemble without kinetochore microtubules, although in this case their structure is abnormal, with lower microtubule density and increased pole–pole distance (DeLuca et al., 2002
), so it is not clear to what extent our conclusion holds for astral, somatic mitotic spindles. More generally, spindles from different organisms—such as yeast, flies, humans, and frogs—are known to be different and results from one system might not extrapolate to other systems.
Our results contradict models proposing that microtubules are preferentially stabilized by the spindle environment, and this stabilization is the driving force for spindle assembly (Kirschner and Mitchison, 1986
; Karsenti and Vernos, 2001
). However, we view them as consistent with most direct observations of dynamics in spindles. For example, the classic finding from FRAP that the majority of spindle microtubules turn over in tens of seconds (Salmon et al., 1984
) hardly suggests that the spindle is a stabilizing environment. The widespread credence given to stabilization models may reflect the fact that students of the spindle tend to focus on kinetochore microtubules, which clearly are stabilized in many systems (Inoue and Salmon, 1995
). Stabilized microtubules also assemble in the midzone during cytokinesis, presumably in response to decreasing Cdk1 activity and relocalization of Aurora-B to the midzone (Eggert et al., 2006
), but there is no evidence for such a stabilized midzone population in metaphase.
Can we reconcile our findings with previous arguments that chromatin stabilizes microtubules in the egg extract system? In a recent experiment, the shape of asters was measured near chromatin in TPX2-inhibited egg extracts, and these data were interpreted as predicting an approximately three- to fourfold increase in the lifetime of microtubule with free plus ends in spindles (Athale et al., 2008
). Our data clearly reject this degree of stabilization for the majority of microtubules. In different experiments where dynamics were not perturbed we observed best-fit τ values that varied by <10%, which gives an approximate measure of the accuracy of our method. Even halving the amount of MCAK did not cause a three- to fourfold increase in stability. Adding constitutively active Ran to X. laevis
egg extracts promotes microtubule assembly (Carazo-Salas et al., 2001
) and stabilization (Caudron et al., 2005
). These data were interpreted as showing that Ran-GTP causes microtubule stabilization near chromatin in spindles, but other interpretations are possible. For example, Ran-GTP may promote nucleation but not stabilization, and/or it may selectively stabilize kinetochore microtubules. It is also possible that chromatin derived factors act locally in spindles to destabilize microtubules, opposing the stabilizing effects of the Ran-GTP and Aurora-B gradients, and these influences were missed in observations made outside true spindles. For example, the dynamics of microtubules in fully formed spindles—investigated here—might be substantially different from microtubule dynamics during the initial phases of spindle assembly, perhaps corresponding to the stabilization suggested by Athale et al. (2008)
. Overall, our data strongly rejects the idea that all spindle microtubules are stabilized three- to fourfold near chromatin in spindles. Our methods might fail to detect a small subset of microtubules that were selectively stabilized, if this population was <1% of the total, but we see no evidence of a longer lived tail in any of our lifetime distributions. We cannot rigorously rule out the existence of a structurally or biochemically differentiated, more stable, small subset of nonkinetochore microtubules, but we know of no data that support the existence of such a subset. A special subset of more stable microtubules, called the midzone array, does assemble near the cell equator during cytokinesis (discussed above), but there is no evidence that it exists during metaphase. It is possible that the pellicle-nucleated arrays we used to model the environment outside spindles somehow induce microtubule stabilization. Arguing against a major effect of this kind, the kinetics of single microtubule assembly from centrosomes in mitotic egg extract (Belmont et al., 1990
; Verde et al., 1992
) is consistent with the average microtubule lifetimes we infer in spindles.
Our data also speak strongly to the mechanism of rapid turnover of nonkinetochore microtubules in spindles that has been mysterious since it was discovered by Inoue in the 1950s (Inoue and Sato, 1967
). Our lifetime distribution was well fit by a model for first passage times of a biased random walk process, with an average lifetime of a microtubule of average length of 16 s. This fit is consistent with turnover occurring by a rapid, stochastic process at microtubule ends, most likely dynamic instability of free plus ends. We cannot rule out a contribution from some kind of stochastic dynamics at minus ends, or slow depolymerization from minus ends that makes little contribution to the lifetime distribution. Our data do argue strongly against a treadmilling model for turnover (Margolis et al., 1978
), because this class of model is expected to show a peak in the lifetime distribution, corresponding to the average length of time it takes a subunit incorporated at one end of the microtubules to be lost at the other. Also, the lack of effect on turnover rate of blocking microtubule sliding with FCPT shows that microtubule turnover and movement are mechanistically distinct processes. This argues strongly against feeder-chipper models for turnover, because these require translocation of microtubules into static depolymerase sites (Gadde and Heald, 2004
The biased random walk model is a phenomenological model that can quantitatively account for our lifetime data and provides a convenient means of parameterizing these data. Evaluating the validity of more detailed, microscopic models of microtubule dynamics will require additional data that this simple model cannot explain. Another widely used simple model of microtubule dynamics is the two-state model (Verde et al., 1992
; Dogterom and Leibler, 1993
), in which microtubules are taken to stochastically switch between phases of constant polymerization and constant depolymerization. These simple models ignore many features known to be present in real microtubules, such as nanoscale fluctuations (Schek et al., 2007
) and complex structural transitions at the polymer ends (Anrnal et al., 2000
). The two-state model predicts an exponential distribution of tubulin lifetimes in the absence of rescues (transitions from shrinking to growing; Bicout, 1997
). Our measured lifetime distributions are clearly nonexponential, but it is possible that the large turnover at short times is caused by fluctuations of the tubulin-GTP cap (Howard and Hyman, 2009
), whereas the turnover at longer times is dominated by the length changes of the microtubule. Although it would surely be possible to construct models of microtubule dynamics of that nature that are consistent with our measured lifetime distribution, because our data can already be accounted for by an even simpler model, we believe that it is more judicious to wait for additional data that demonstrate the deficiencies of the biased random walk model. As an additional precaution, we separately analyzed the lifetime data for times >30 s, which can be well fit to a single exponential, and all of the conclusion obtained from analyzing the full data set hold equally well when only this restrict subset is considered.
Our interpretation makes testable predictions about the average length and length distribution of spindle microtubules that are largely independent of the details of plus-end dynamics. If the spindle does not cause stabilization as we assert, nonkinetochore microtubules in spindles should have the same length distribution as microtubules grown from centrosomes in egg extracts, which is approximately exponential, with an average length of ~3 μm (Verde et al., 1992
). This proposed length distribution differs from published estimates using other methods. Correlated motions of individual tubulin molecules were used to infer a mean length of ~20 μm and a bell-shaped distribution (Yang et al., 2007
), but cross-linking might give rise to correlated motions of tubulin molecules in different microtubules, potentially complicating this analysis. A different length estimate based on measuring tubulin incorporation inferred an average length of ~14 μm (Burbank et al., 2006
). However, this technique used a number of unproven assumptions, such as the hypothesis that a microtubule's orientations can be definitively determined from its direction of motion, so the resulting estimate may be faulty. All of the current estimates of microtubule lengths in X. laevis
egg extract spindles are indirect, including our own, and direct measurements by electron microscopy will be necessary to unambiguously resolve this issue.
If the locally high concentration of microtubules in spindles is not caused by local stabilization, what does cause it? We postulate it is solely due to an increased rate of nucleation in the spindle compared with bulk cytoplasm, and furthermore, that understanding how nucleation is spatially regulated will be the key to understanding morphogenesis of meiotic spindles. Given that microtubule turnover is fast relative to transport, nucleation has to occur throughout the spindle, as proposed by others (Mahoney et al., 2006
). More specifically, during the metaphase steady state the pattern of nucleation must preserve local microtubule density and local microtubule polarity. Nucleation is globally controlled by the Ran pathway (Karsenti and Vernos, 2001
), but it is still unclear how this generates spindle structure and gives rise to a sharp boundary between the inside and outside of the spindle. Mechanisms in which pre-existing microtubules locally stimulate nucleation are a possibility (Clausen and Ribbeck, 2007
), as per the Arp2/3 complex for actin. One candidate mechanism might involve orientation of the γ-tubulin complex on microtubules by the augmin complex (Goshima et al., 2008
). It is also possible that nucleation occurs with random orientation, and newborn microtubules are rapidly reoriented by motor proteins. Measurements of tubulin turnover, such as those presented here and elsewhere in the literature, cannot be used to directly probe microtubule nucleation because the majority of tubulin is incorporated into preexisting microtubules in the spindle. Hopefully, new experimental techniques will be developed to characterize the nature and spatial regulation of microtubule nucleation in spindles.
Finally, our observation that the tubulin lifetime distribution in the complex environment of the spindle can be well described by a simple biased random walk model with a single freely adjustable parameter is encouraging for efforts to provide a quantitative basis for cytoskeleton biology. Similar methods may be useful in investigating different microtubule populations and the dynamics of other biological polymers.