The Functional Antagonism between Eg5 and Dynein in Spindle Bipolarization Is Not Compatible with a Simple Push-Pull Model

The Functional Antagonism between Eg5 and Dynein in Spindle Bipolarization Is Not Compatible

with a Simple Push-Pull Model

Stefan Florian

1,2

and Thomas U. Mayerl,*

1

Department of Biology and Konstanz Research School Chemical Biology, University of Konstanz, Universitatsstrasse 10, 78457 Konstanz, Germany

2

Present address: Department of Systems Biology, Harvard Medical School, 200 Longwood Avenue, Warren Alpert Building 536, Boston, MA 02115, USA

'Correspondence: thomas.u.mayer@uni-konstanz.de

SUMMARY

During cell division, the molecular motor Eg5 cross- links overlapping anti parallel microtubules and pushes them apart to separate mitotic spindle poles.

Dynein has been proposed as a direct antagonist of Eg5 at the spindle equator, pulling on anti parallel microtubules and favoring spindle collapse. Some of the experiments supporting this hypothesis relied on end point quantifications of spindle pheno- types rather than following individual cell fates over time, Here, we present a mathematical model and proof-of-principle experiments to demonstrate that endpoint quantifications can be fundamentally misleading because they overestimate defective phenotypes. Indeed, live-cell imaging reveals that, while depletion of dyne in or the dynein binding protein Lis1 enables spindle formation in presence of an Eg5 inhibitor, the activities of dynein and Eg5 cannot be titrated against each other, Thus, dynein most likely antagonizes Eg5 indirectly by exerting force at different spindle locations rather than through a simple push-pull mechanism at the spindle equator.

INTRODUCTION

In mitosis, the equal distribution of chromosomes is mediated by the mitotic spindle, a microtubule-based structure whose bipolar shape results from the coordinated activities of microtu- bule-associated proteins and molecular motors (Compton, 2000; Scholey et aI., 2003; Heald and Walczak, 2008; Dumont and Mitchison, 2009). Within the spindle, microtubule minus ends converge at the poles and the plus ends pOint toward the spindle equator where they create a zone of overlapping, anti- parallel microtubules. Due to its homotetrameric structure and plus-end

-directed

motility, Eg5, a conserved member of the kinesin

-5 family, can crosslink these antiparallel microtubules

and push spindle poles apart (Sawin et aI., 1992; Kashina et aI., 1996; Kashina et aI., 1997; Sharp et aI., 1999; Kwok

408

et al., 2004; Kapoor and Mitchison, 2001

;

Feren

z

et aI., 2010). Consequently, in most systems studied so far, inactiva- tion of Eg5 results in spindle collapse and monopolar spindle formation. Dynein, a minus-end-directed motor, was suggested to be a direct antagonist of Eg5, which pulls spindle poles together and thus promotes spindle collapse (Mitchison et aI., 2005; Tanenbaum et aI., 2008; Ferenz et aI., 2009). The orches- tration of these two antagonistic forces is believed to be essential for bipolar spindle formation

. In allusion to the

actin/

myosin-based mechanism of force generation in muscle tissue, this model is called the "push-pull mitotic muscle" model (Mcintosh et aI., 1969; Kapitein et aI., 2005; van den Wildenberg et aI., 2008; Figures 1A and 18). A corollary of this model is that the activities of Eg5 and dynein are titratable, i.e., spindle collapse induced by reduced Eg5 activity should be rescued by lowering dynein activity resulting in the re-equilibration of forces acting within the spindle. Using a fixed-sample-based endpoint quantification, Tanenbaum et al. (2008) showed that (1) depletion of dynein heavy chain (DHC) increases the percentage of bipolar spindles in mitotic cells treated with low doses of

Eg5

inhibitor and that (2) the

efficiency of dynein

depletion to rescue spindle bipolarity indeed decreased with increasing inhibition of Eg5, showing no significant effect at saturating inhibitor concentrations. Thus, in line with a simple push-pull model, this study suggested that the activities of Eg5 and dynein at the spindle equator can be titrated against each other.

Here, we develop a mathematical model that explains why fixed

-cell

analyses are often not appropriate for the quanti- fication of cellular phenotypes, and we validate its predictions experimentally. Thus, we show that quantitative statements about the frequency of spindle phenotypes derived from single time point measurements are inaccurate and, without exception, synchronization protocols or live-cell imaging should be used to avoid this problem. Consequently, we apply live-cell imaging to revisit the push-pull antagonism of Eg5 and dynein and find that, in contradiction to previous results from fixed samples, Eg5 is not titratable against the activity of dynein or its binding protein Lis1

.

We conclude that the mechanism of bipolar spindle formation is not compatible with a simple push-pull model where Eg5 and dyne in act as direct antagonists.

First publ. in: Cell Reports ; 1 (2012), 5. - S. 408-416 DOI : 10.1016/j.celrep.2012.03.006

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Figure 1. The Push-Pull Mitotic Muscle Model

(A) Scheme of the role of Eg5 (red) and minus-end- directed motors (blue) in spindle pole separation.

(6) Experimental predictions of the push-pull model, which are tested in this study. Reduced Eg5 activity prevents pole separation and leads to the formation of monopolar spindles. Dynein depletion in cells with reduced (but not absent) Eg5 activity has been suggested to re-enable spindle bipolarization by lowering Eg5-antago- nizing forces.

(C) Representative movie stills and corresponding immunofluorescence images of GFP-H26-ex- pressing HeLa cells treated with VS83 (12,5 I.M), Mitotic cells were defined as featuring a bipolar spindle as soon as they had formed a metaphase plate (orange circle, last frame). The green circle highlights a cell failing to assemble a metaphase plate during the course of the experiment. After 18 hr of imaging, cells were fixed and stained with Hoechst 33258 (DNA) and antibodies against phospho-histone H3 and (J;-tubulin, In all following experiments, the percentage of mitotic cells that formed bipolar spindles over time was calculated from movies (NBc'u.'), In parallel, the percentage of bipolar spindles within the total mitotic population was assessed from fixed samples (Nfix) , Scale bars, 151.m,

(D) The spindle assembly checkpoint causes a delay in mitotic exit for defective spindles, Mitotic spindle lifetimes are values.derived from experiments treating HeLa cells with VS83,

types is still often performed

using

single-time-point microscopy on fixed cells. This approach is even more frequent in large-scale screening projects where live-cell imaging,

so-called

high- content screening, can become simply

IiiI unfeasible considering the amount of generated data. During experiments analyzing mitotic spindle phenotypes (Figure 1 C), we frequently noticed that there is a

strong

discrepancy between the prevalence of defective spindle phenotypes

in the mitotic cell population

at the end of

an

experiment and the actual frequency at which the phenotype emerges in mitotic cells during the exper- iment. This happens because normal and defective spindles have significantly

RESULTS different

lifetimes:

normal spindles are short-lived, transient

structures that quickly disappear as cells divide and exit mitosis, whereas defective spindles persist for much

longer periods of

time because they activate the

spindle-assembly

checkpoint (SAC), resulting in a mitotic delay (Varetti and Musacchio,

2008; Figure 1 D). Thus, in a single-time point experiment, defec-

tive spindles are overrepresented compared to intact spindles.

It

is important

to

know if this analytical bias results

in

only Endpoint Quantifications of Spindle Phenotype

Frequency Are Inherently Inaccurate

Live-cell microscopy has become increasingly popular because

of its potential to provide detailed, time-resolved insights into

cellular processes. However, analysis of the generated data is

time intensive, and, therefore, quantification of cellular pheno-

negligible quantitative or fundamental, even qualitative, errors. It is surprising that, in the context of mitosis research, th

is question

has not been addressed yet, and fixed-cell analyses are used as a routine method to determine the frequency of phenotypes. We tried to address this issue theoretically and derived a simple mathematical relationship, predicting the fraction of cells within the mitotic population displaying normal spindles at a given time point in fixed samples (N

fix)

from the fraction of cells forming normal spindles in mitosis during the experiment

(Nactua/)'

We defined the relationship as follows (more details and the exact derivation are provided in the Extended Experimental Procedures):

Nfix(t) = nnormaf-splndles(t)

n mitotic_cells

(t)

nnormaLspindfes (t)

n

n~rmal_splndles

(t)

+ ndefective _spindles (t) ,

where

nphenotype(t)

represents the number of mitotic cells with the indicated phenotype at a given time point. We further assumed (Figure 1 D) that (1) cells enter mitosis at a constant rate, (2) a frac- tion of mitotic cells

(Nactual)

forms bipolar spindles and exits mitosis after

tnormal

hours in metaphase, and (3) a fraction of 1 -

^Nactual

mitotic cells develop a defective spindle and exit mitosis after

tdefectlve

hours. Under these conditions, if the time of measurement, t, is longer than the times in mitosis of both the defective

(tdefective)

and the normal

(tnorma/)

mitotic population, the following equation applies:

Nfix(t) = Nactualtnormal . Nactualtnormal

+ (1 -

Nactua/)tdelective

According to this equation, Nfix , i.e., the percentage of mitotic cells displaying normal spindles at a given time point, depends not only on

Nactua"

i.e., the fraction of mitotic cells forming bipolar spindles, but also on two other variables:

tnormal

and

tdefective.

The.se are the average lifetimes of normal and defective spindles, which can both vary independently of

Nactua/.

Plotting N"x against

Nactual

for different values of

tnormal

and

tdefective

can help one to understand whether and when fixed-cell analyses are accurate enough to be useful (Figure 2A). To obtain accurate results from fixed samples, N"x should match

Nactual

as closely as possible, allowing us to directly estimate the

latter

from the former. According to the equation, this is the case if

^tnormal

equals

tdefective

(Figure 2A, green line). Because

tnormal

«

tdefective,

however, the actual function curve for a typical experiment involving spindle perturbations is highly distorted. Figure 2A shows a plot of the equation for

tnormal

= 0.25 hr and

tdefective

=

13.5 hr (yellow curve), both average values derived from experi

-

ments using the Eg5 inhibitor V883 (published half maximal effective concentration [EC

_50),

7.27 J.lM; 8arli et aI., 2005). For these values, the whole range of

^Nactual

from 0 to 0.75 corre- sponds to the range from 0 to 0.05 in Nfix , resulting in underesti- mation of changes in

Nactua/'

Reciprocally, for

Nactual

values between 0.8 and 1, small changes in

Nactual

cause huge increases in Nfix, thus tending to cause overestimation of effects.

In this situation, it is impossible to determine

Nactual

without prior knowledge of the lifetimes of individual spindle phenotypes

.

Notably, changes in experimental conditions might affect not only Na ctu.1 but also the lifetimes of spindle phenotypes implying that they have to be determined individually for each experi-

mental condition. Thus, in this case, live-cell analysis is the only appropriate approach to quantify cellular phenot ypes.

Experimental Evidence Confirms Inaccuracy of Fixed-Sample Quantifications

For all the experiments presented in this study, the same setup was used: Thirty hours or 54 hr after transfection of HeLa cells stably expressing green fluorescent protein (GFP)-tagged histone H2B with short interfering (si)RNA duplexes, Eg5 inhibi- tors were added and the time-lapse image acquisition was immediately started. At the end of time-lapse acquisition, cells were fixed and stained for immunofluorescence analysis (Fig- ure 1 C). We performed two proof-of-concept experiments to validate the predictions of our model and illustrate the impact of mitotic lifetimes on Nfix' First, we titrated V883 from 3.1

~tM

to 100 J.lM in control RNAi cells to gradually lower the fraction of cells forming bipolar spindles and quantified both

Nactual

and Nfix' As shown in Figure 2 (indicated with yellow squares in Figure 2A), the resulting data points for

^Nactual

(x axis) and N"x (y axis) were indeed in close match with the function curve (yellow) defined by the equation using

^{tnormal '"}

0.25 hr and

tdefectlve

= 13.5 hr. This confirms that, if

^tnorma/« tdefective,

values for Nfix and

^Nactual

differ substantially. Next, we wanted to demonstrate how a change in

lifetimes

affects experimental interpretation. To this end, we increased the lifetime of bipolar spindles by depleting 8hugoshin (8g01). Depletion of 8g01 induces premature loss of sister chromatid cohesion, resulting in 8AC activation regardless of spindle function (8alic et aI., 2004). Thus, by prolonging the lifetime of bipolar spindles, 8g01 depletion should result in

^tnormal "" tdefective

and, therefore, in a much better correlation of Nfix with

^Nactual

(Figure 2A, green line).

Indeed,

8g01 depletion caused a marked increase in N"x without actually rescuing bipolar spindle formation

(Nactua,) ,

as indicated in Figure 2 by the close-to-vertical connecting lines between control GL2-RNAi (yellow squares) and Sgo1

-RNAi

(green triangles) data points. Thus, without knowledge of the function of 8g01, analyses of fixed cells would result in the con-

. elusion that 8g01 antagonizes Eg5 function in spindle assembly,

an effect that, as live-cell imaging reveals, is entirely due to changes in mitotic timing. In summary, these proof-of-concept experiments confirm our mathematical model and its prediction that, because perturbations can unpredictably affect both

Nactual

and mitotic

lifetimes, estimation

of

Nactual

from fixed samples is impossible without the knowledge of

tnormal

and

tdefective-

Live-Cell Imaging Reveals that the Push-Pull Model Cannot Explain the Antagonism between Dynein and Eg5

Previous studies using fixed samples revealed that depletion of

DHC leads to a huge improvement in bipolar spindle formation

in cells treated with

low

doses of the Eg5 inhibitor 8-trityl-L-

cysteine (8TLC) (DeBonis et aI., 2004; 8koufias et aI.

, 2006) but

had a negligible effect at maximal Eg5 inhibition (Tanenbaum

et aI., 2008). Thus, residual amounts of Eg5 activity seemed to

be required to rescue spindle bipolarity in DHC-depleted cells,

supporting the idea that Eg5 and dynein are direct antagonists

whose activities can be titrated against each other. We repeated

A a

tnomw,NactUlJ' e uation plots

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,

"0 ^.3

/

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J

U ~~~A e2'p~!!..,!,~~!~ __ ... ___ . ______

1" _{.1 6.25J.1M / /} control RNAi "'8g01 RNAi 30h

"ii~ ^{$ .... ~,. .. ,d ..} numbers indicate conc. of V883

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. . . . _ ~ ... N ¥

o

.1 .2 .3 .4 .5 .6 .7 .8 .9 1 ~

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Vl

.9

Ill! 8go RNAi

o

control RNAi

=ai _CJ (J) .8

Q)

30h

~~

.7

'E ~.6

'019

c:

8.

.5

:fl~.4

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.3

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,,'I- <,<::>

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Figure 2. A Model Describing the Mathematical Relationship between Phenotype Frequency in Fixed and Live Samples

(A) A plot of the equation describing Nf/x (y axis) as a function of Nectue' (x axis) and mitotic spindle lifetimes (tnon"e' and (defective) based on the variables introduced in Figure 1 D. The green line (45·) would correspond to identical lifetimes for bipolar and defective spindles. The yellow line corresponds to realistic values for tno,mal

(0.25 hr) and (defective (13.5 hr) in an Eg5-inhibitor-treated cell population. Data points represent experimental results for Nf/x and Nac/usl for cells treated with control (GL2) or Sg01 siRNA. Black lines connect data points for GL2-and Sg01-RNAi cells treated with the same dose of VS83. Each data point represents the mean of at least two experiments.

(B and C) Original data for the experiments plotted in (A). HeLa cells were transfected with control (GL2) or Sg01 siRNA and incubated for 30 hr. Next, VS83 was added at the indicated concentrations, and time-lapse movies were acquired for 18 hr, followed by fixation and fixed-cell analysis. Then, Nox (B) and Nactusl

(C) were determined. Bars represent means ± SEM of at least two experiments.

the experiments

under precisely identical conditions but again analyzed in

para

llel

both live-cell and fi

xed samples,

i.e., the

same

cells studied live were analyzed by immunofluorescence microscopy after the completion of the movie. The efficiency of dyne in depletion was determined by immunoblotting for dyne in

intermediate chain

(Figure

3A),

w

hich was previously shown to

be degraded upon DHC depletion (Grigoriev et aI., 2007).

Indeed, fixed-cell

analyses confirmed that dynein depletion

significantly increased the percentage of mitotic cells displaying bipolar spi

ndles and, furthermore, that the effect of DHC

depletion (t., difference between DHC-

and control-RNAi cells)

is strongest when

EgS

is only slightly inhibited (Figure 38).

However,

the situation was different when we

analyzed the cor- responding

live-cell

movies

(Figure 3C). Specifically, while we could confirm that dynein depletion can rescue bipolar spindle

formation in EgS-inhibited cells, we observed that (1) DHC deple- tion had no significant

effect

on bipolar spindle formation at the lowest concentration of STLC (t. = 0.02) and (2) the rescue

efficiency of dynein depletion did not decrease with increasing

STLC concentrations but was actually maximal (t.

~

0.S6) at high inhibitor concentrations and plateaued up to 80 JlM STLC.

Notably, our live-cell analyses revea

led

that the EC

so

value of

STLC was slightly higher than 2

~LM

(Figure 3C),

suggesting

that dynein depletion efficiently rescued spindle bipolarization

even

under conditions

(~40

times the

EC_so)

when EgS was

maxima

lly inhibited. If our mathematical model is correct,

the

discrepancy

between

live and fixed samples must be caused

by the

effect of dynein depletion on mitotic

timing. To

confirm

this, we quantified mitotic

lifetimes for cells forming monopolar and bipolar spindles

in contro

l-

or DHC-RNAi cells treated with

A

54 h, 25 nM GL2 RNAi OHC RN Ai

Eg5

[ ::!\!J:m~:~""" . 113o

^kOa

Dynein Intermediate Chain

B

D

LI1!::.:cI!l_iIIW_· . _ _

-1~

^kOa

Hela cells

'l- "

STLC!JlMJ

control RNAi, 2 pM STLC

c

"'·"'"",'=!">'-=.!.-'T-"-'-'="=:;'="T==P"'-=''; III DHCRNAi

.1

~o

'l- "

STLC !JlMJ

OHC RNAi, 2 pM STLC

o control ANAl 54 h

.. rootaphase/

tjpolar

.prophasel

monopolar

10 t5 ^{10 t(h)}

Figure 3. Bipolar SpindJe Formation in Eg5-lnhibited and Dynein-Depleted Cells Does Not Fit to.a Push-Pull Mechanism (A) Fifty-four hours after transfection, control (Gl2) and DHC-RNAi cells were analyzed by immunoblotting as indicated.

(B and C) Quantification of N"x (B) and NBe/uB' (C) after transfection with DHC or control siRNA for 54 hr followed by addition of the Eg5 inhibitor STLC and imaging for an additional 18 hr at the indicated doses. Bars represent means ± SEM of triplicate experiments.

(D) Quantification of times in mitosis of bipolar and mono polar spindles at 2 ~IM STLC from one of the experiments shown in (C). Each horizontal bar represents a single cell. The length of the bars represents the time spent in a monopolar (blue) or bipolar (green) state. Note that this representation illustrates in an intuitive manner how N"x and Naetua, are related (see details in the Extended Experimental Procedures): The size of a population on the y axis corresponds to the actual frequency of the phenotype over time (e.g., Nae/ua' for normal spindles), while the total area of the bars of a population corresponds to its relative size in fixed samples (green area for the normal spindle, blue area for the mono polar spindle population). As summarized in the table included in the left panel, DHC depletion significantly changes tprophase. tnorma" and tdefective-

2 J.lM STLC. The results are plotted in Figure 3D, each horizontal bar representing a cell and the length of the bar representing its lifetime (blue = prophase/monopolar, green = bipolar). As shown before (Figure 3C), about 60% of mitotic control-RNAi cells treated with 2 J.lM STLc were able to form bipolar spindles, and, on average, these cells remained in prophase for about 0,93 hr before they formed a bipolar spindle and quickly exited mitosis

(tnormal

= 0.36 hr). Notably, consistent with its reported function in checkpoint inactivation (Howell

et aI., 2001),

dyne in depletion significantly slowed down metaphase progression of cells forming bipolar spindles from

^tnormal

= 0.36 hr to 1.15 hr.

Moreover, and unexpectedly,

tdefective

was dramatically

short-

ened from 9.32 hr to 2.9 hr because DHC-depleted cells with

monopolar spindles died much faster than control monopolar

cells, an effect that further aggravated the distortion of N

fix.

We

also found that DHC depletion prolongs the time that cells

spend in prophase before forming bipolar spindles (0.93 hr vs

.

1.53 hr). Thus, for 2 ,lM STLC, in addition to its effect on

^Nactual,

DHC depletion induces a

complex

change in lifetimes that

dramatically affects N

fix

and explains the differences between

fixed-sample and time-lapse imaging, We conclude that the

previous statement that dynein depletion rescues spindle

bipolarization most efficiently at low Eg5-inhibitor concentrations (Tanenbaum et aI., 2008) is incorrect because of the effect of dynein depletion on the lifetimes of bipolar and monopolar spin- dles. In contrast, our studies relying rigorously on live-cell imaging revealed that dynein depletion rescues spindle bipolarity most efficiently when Eg5 is maximally inhibited, strongly sug- gesting that the functional interrelationship between Eg5 and dynein is more complex than suggested by the simple push- pull model.

Time-Lapse Analysis of Lis1 Depletion Reveals an Effect on Bipolarization Similar to that of DHC1 Depletion

Lis1 (Mesngon et aI., 2006) stimulates the ATPase activity of the dynein complex, and its depletion was shown to promote bipolar spindle formation when Eg5 activity is slightly, but not maximally, inhibited, similar to the depletion of DHC (Tanenbaum et aI., 2008). Our fixed-sample analyses confirmed that Lis1

-depleted

cells (Figure 4A) displayed more bipolar spindles than control- RNAi cells over the whole range of STLC concentrations and that the rescue efficiency decreased with increasing inhibition of Eg5 (Figure 4B). Again, this trend could not be observed in time-lapse imaging. As shown in Figure 4C, at 1 /.lM STLC, already 93% of control-RNAi cells formed bipolar spindles and, therefore, Lis1 depletion could not significantly improve the situation, while the maximum rescue effect was consistently achieved at higher doses of Eg5 inhibitor. It was not surprising that the different outcome of fixed- and live-sample analyses was again due to changes in mitotic timing, as Lis1 depletion resulted in an even stronger mitotic delay of bipolar spindles than DHC depletion (Figure 4D, tnorma'). Similar to DHC depletion, Lis1 depletion also resulted in a reduction in

tdefective

from 9.51 hr to 7.66 hr due to accelerated death of cells with monopolar spindles. These results confirm that Lis1 depletion rescues spindle bipolarization. The pattern of rescue efficiency, however, strongly argues against the idea that the activities of dynein/Lis1 and Eg5 are titratable and is not compatible with a simple Eg5- dynein push-pull model.

DISCUSSION

The simple push

-pull model where the

effort of Eg5 to push spindle poles apart is continuously antagonized by dynein's inward acting force is intriguingly intuitive. The observation that the activities of Eg5 and dynein seemed to be titratable was an important cornerstone of the idea that Eg5 and dynein are direct antagonists acting both on antiparallel microtubules at the spindle equator. Clearly, our in-depth analyses reveal that dynein/Lis1 and Eg5 are not simply titratable against each other, as we did not observe a negative correlation between the efficiency of spindle bipolarization and the

level of Eg5

inhibition in DHC/Lis1

-depleted cells (Figure 4E). From these

data, we conclude that, while dynein antagonizes Eg5 function in bipolarization at the global cellular level, the molecular details of this antagonism are more complex than anticipated. This conclusion is supported by the fact that dynein localizes to multiple subcellular structures in mitosis where it fulfills diverse functions.

It

is involved in centrosome separation during prophase (Splinter et aI., 2010; Tanenbaum et aI., 2010);

connects astral microtubules to the cell cortex, possibly pulling spindle poles apart (Busson et aI., 1998; Gonczy et aI., 1999;

Grill and Hyman, 2005; Laan et aI., 2012); transports microtubule nucleation factors and spindle assembly checkpoint factors along kinetochore fibers from kinetochores to spindle poles (Ma et aI., 2010; Sivaram et aI., 2009; Chan et aI., 2009 and references therein); and is involved in pole focusing (Gaglio et aI., 1996; Shimamoto et aI., 2011). Taking these diverse func- tions into consideration, it is not surprising that depletion of a multifunctional protein such as dynein results in unexpected and highly complex patterns of spindle formation. In· addition to the study of Tanenbaum et al. (2008), the main evidence for a dynein-Eg5 antagonism in spindle bipolarization comes from Mitchison et al. (2005) and Ferenz et al. (2009). In frog extract, Mitchison et al. (2005) showed that addition of a dynein inhibitor enabled bipolarization

in

Eg5-inhibited extract. This is in full agreement with our observations, as this study did not address the titrability of Eg5 and dynein. Ferenz et al. (2009) used human cells but relied on a different approach from the one presented here. A dynein inhibitor was injected into Eg5-inhibited cells arrested with nocodazole, and spindle fate was scored depend- ing on the initial position of centrosomes after nocodazole releas· e. It was concluded that, in Eg5-inhibited cells, if the two spindle halves overlap, dynein exerts an inbound force, causing spindle collapse. Considering the very different experi- mental setups, it is hard to directly compare these results to our data. The main conclusion, however, is based on very

low cell

numbers (five dynein-inhibited cells), and most important, this publication observes an artificial spindle formation process after mitotic release from nocodazole, thus lacking a physiolog- ical prophase. Dynein and Eg5, however, are involved in centro- some separation in prophase (Splinter et aI., 2010; Tanenbaum et aI., 2010), and this fu.nction might explain the difference from our results, as we look at mitosis from prophase to telophase.

To definitively understand if dyne

in

is

involved

in a push-pull mechanism, direct visualization in living cells will be required.

Until future studies overcome the current technical obstacles to do so, we will have to rely on indirect observations of spindle morphology after molecular manipulations to understand the role of dynein at the spindle equator. However, as shown by our mathematical model and proof-of-concept experiments, these studies have to be performed using

live-cell

imaging, as fixed-cell analysi s results in wrong quantifications due to unpre- dictable effects of molecular manipulations on the lifetime of spindle phenotypes.

EXPERIMENTAL PROCEDURES

All experiments in this study were based on the following experimental protocol: RNAi transfection (25 nM final siRNA duplex concentration) was performed and followed by an incubation time of 30 hr (Sg01 RNAi) or 54 hr (all other experiments). Then, either cells were harvested and lysed for immunoblotting, or Eg5 inhibitor was added and time-lapse image acquisition was started immediately and continued for 18 hr. Finally, cells were fixed and stained for immunofluorescence analysis. For quantification of time-lapse data, only cells that entered mitosis at least 10 ·hr before the end of the experiment were included in the analysis to allow accurate determination of cell fate even for very long mitotic lifetimes. See Extended Experimental Procedures for a detailed description of reagents and protocols.

A

B

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E

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54 h, 25 nM GL2 RNAi Usl RNAi

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406312322526404 76B 516711461 593

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n(cells) 243 235 301 269 214 237 27B 206 225 242

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control RNAi, 21lM STLC

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Lis1 Eg5 predictions actual

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Lis1 RNAi, 21lM STLC

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Figure 4. Bipolar Spindle Formation in Eg5-lnhibited and Lis1-Depleted Cells Cannot Be Explained by a Push-Pull Mechanism (A) Immunoblot analyses for Eg5 and Lis1 of GL2-and Lis1-RNAi cells 54 hr after transfection of siRNAs.

(B and C) Quantification of Nf/x (B) and Nae•ua• (C) after transfection with Lis1 or control siRNA for 54 hr followed by addition of STLC and imaging for an additional 18 hr at the indicated doses. Bars represent means ± SEM of triplicate experiments.

(D) Quantification of times in mitosis of bipolar and monopolar spindles at 2 ~LM STLC from an experiment shown in (B). Mitotic lifetimes were plotted as in Figure 3~. Note the dramatic increase in

tno,ma'

caused by Lis1 depletion.

(E) Summary of the inconsistencies between the predictions of the push-pull model and our findings using live· cell imaging.

LICENSING INFORMATION

This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 Unported License (CC-BY-NC-ND; http://creativecommons.org/licenseslby-nc-nd/3.0/

legalcode).

ACKNOWLEDGMENTS

We thank Anna Brendel for essential help with data analyses, Allon Klein for generous help with the mathematical model, and Tim Mitchison for discus- sions and general support. We are indebted to Lucia Sironi and the Mayer lab for fruitful discussions and to Vasiliki Sarli for VS83. S.F. and T.U.M. were sup- ported by the EU-Research Training Network Fellowship ("Understanding the Dynamic of Cell Division," 512348) and by the CRC-969 "Chemical and Biological Principles of Cellular Proteostasis" of the Deutsche Forschungsge- meinschaft (DFG), respectively.

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