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Principles of the mitochondrial fusion and fissioncycle in neurons

Michal Cagalinec1, Dzhamilja Safiulina1, Mailis Liiv1, Joanna Liiv1, Vinay Choubey1, Przemyslaw Wareski1,Vladimir Veksler1,2,3 and Allen Kaasik1,*1Department of Pharmacology, Centre of Excellence for Translational Medicine, University of Tartu, Ravila 19, Tartu, Estonia2INSERM, U-769, Chatenay-Malabry F-92296, France3Universite Paris-Sud, Chatenay-Malabry F-92296, France

*Author for correspondence (allen.kaasik@ut.ee)

Accepted 19 February 2013Journal of Cell Science 126, 2187–2197� 2013. Published by The Company of Biologists Ltddoi: 10.1242/jcs.118844

SummaryMitochondrial fusion–fission dynamics play a crucial role in many important cell processes. These dynamics control mitochondrialmorphology, which in turn influences several important mitochondrial properties including mitochondrial bioenergetics and qualitycontrol, and they appear to be affected in several neurodegenerative diseases. However, an integrated and quantitative understanding of

how fusion–fission dynamics control mitochondrial morphology has not yet been described. Here, we took advantage of modernvisualisation techniques to provide a clear explanation of how fusion and fission correlate with mitochondrial length and motility inneurons. Our main findings demonstrate that: (1) the probability of a single mitochondrion splitting is determined by its length; (2) the

probability of a single mitochondrion fusing is determined primarily by its motility; (3) the fusion and fission cycle is driven by changesin mitochondrial length and deviations from this cycle serves as a corrective mechanism to avoid extreme mitochondrial length; (4)impaired mitochondrial motility in neurons overexpressing 120Q Htt or Tau suppresses mitochondrial fusion and leads to mitochondrial

shortening whereas stimulation of mitochondrial motility by overexpressing Miro-1 restores mitochondrial fusion rates and sizes. Takentogether, our results provide a novel insight into the complex crosstalk between different processes involved in mitochondrial dynamics.This knowledge will increase understanding of the dynamic mitochondrial functions in cells and in particular, the pathogenesis ofmitochondrial-related neurodegenerative diseases.

Key words: Mitochondrial dynamics, Mitochondrial fusion, Neurons, Neurodegeneration

IntroductionMitochondria are dynamic organelles that constantly fuse with

each other and then split apart (i.e. undergo fission). Fusion

serves to mix and unify the mitochondrial compartment whereas

fission generates morphologically and functionally distinct

organelles.

The balance of these two processes determines organelle

shape, size and number and is critical for organelle distribution

and bioenergetics. The latter is particularly important in neurons,

which have a unique bioenergetic profile due to their dependence

upon energy from mitochondria and their specialised,

compartmentalised energy needs. Beyond the control of

morphology, the mitochondrial fusion–fission cycle appears to

be also critical in regulating cell death and mitophagy.

Mitochondrial fission contributes to quality control by

favouring removal of damaged mitochondria via mitophagy

(Gomes et al., 2011) and may facilitate apoptosis in conditions of

cellular stress (Suen et al., 2008). Failure of mitochondrial

fusion–fission dynamics has been linked to several diseases.

Perturbations of the mitochondrial fusion–fission cycle cause

autosomal dominant optic atrophy and Charcot–Marie–Tooth

type 2A and appear to be involved in the pathogenesis of several

neurodegenerative diseases (Westermann, 2010).

The molecular mechanisms underlying mitochondrial fusion

and fission events are relatively well-known. The key molecules

responsible for fusion are Mitofusin-1 and -2 (Mfn1 and 2,

respectively), which are located in the outer mitochondrial

membrane, and OPA1, which is located in the inner

mitochondrial membrane. The outer membrane protein Fis1

and the cytoplasmic protein Drp1 are responsible for fission

events (for a review, see Knott et al., 2008). Recent papers have

also revealed interplay between fusion and fission; in most cases,

they appear to be sequential, cycle-forming events (Twig et al.,

2008; Wang, 2012). Nevertheless, despite these advances, there

remains no clear understanding of how mitochondrial fusion and

fission events interact at the cellular systems level. If the fusion

and fission events are cyclic then how do they sense each other?

How do the fusion or fission events sense mitochondrial size? Do

these events have feedback mechanisms to maintain the size of

the mitochondrial population? To what extent do they depend

upon mitochondrial motility or can they regulate mitochondrial

motility themselves? Perhaps most relevantly, to what extent is

this network of events affected in neurons known to be most

vulnerable to mitochondrial impairment?

To answer these questions, using living neurons, we examined

the dynamics in morphology of mitochondrial populations

together with fusion and fission characteristics. We reveal key

rules governing mitochondrial dynamics and show the role that

mitochondrial length and motility play in the feedback that

regulates mitochondrial homogeneity. Finally, we show that in

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models of neurodegenerative diseases, we can rescue an impaired

mitochondrial phenotype by correcting mitochondrial motility.

ResultsVisualisation of fusion and fission in neurons

For visualisation of fusion and fission events, we used

mitochondrially targeted KikGR1 protein. Mitochondrial

localisation of this protein was confirmed by its colocalisation

with the well-known mitochondrial markers mito-CFP (Fig. 1A)

or mito-pDsRED2 (data not shown). Mito-KikGR1 demonstrated

a relatively high mitochondrial/cytoplasmic intensity ratio (.30).

The photoconversion properties of KikGR1 remained unaltered

after mitochondrial targeting.

The fusion events between red (photoactivated) and green

(non-activated) mitochondria were easily recognizable because

the contacting mitochondria turn yellow after exchanging their

matrices (Fig. 1B; supplementary material Movie 1). The

exchange of matrix occurred quickly and to completion and

typically, was complete in less than 10 s. Fission events occurred

where mitochondria split and the daughter mitochondria moved

away from each other. During the 2 h observation period, we

detected up to nine sequential fusion or fission events of

photoactivated mitochondria and their progenies.

Fusion and fission events are cyclic

Mitochondrial fusion and fission rates were estimated in axons of

two morphologically distinct subtypes of neurons: cortical

neurons and cerebellar granule neurons. In both types of cell,

the fusion rate matched the fission rate perfectly although in

cortical neurons, these rates (0.02360.003 fusions/mitochondria/

min and 0.02360.003 fissions/mitochondria/min; n517 dishes)

were lower than in cerebellar granule neurons (0.04560.006

fusions/mitochondria/min, P50.001, and 0.03960.005 fissions/

mitochondria/min, P50.0072; n512 dishes).

We also attempted to measure the mitochondrial fusion rate in

the soma of cortical neurons. However, mitochondria are packed

very densely in the soma, and in the majority of cases, the laser

beam photoactivated mitochondria located in the vicinity of the

mitochondrion of interest. Nevertheless, we estimated the fusion

rate in soma of cortical neurons, which was significantly higher

(0.14960.021 fusion/mitochondria/min, n510; P,0.0001) than

in axons.

Our next aim was to determine whether the fusion and fission

events occurred randomly or in a regulated manner [for example,

cyclic, as suggested by Twig et al. (Twig et al., 2008)].

Theoretically, each fusion could be followed by fission or by a

secondary fusion, or similarly, each fission could be followed by

fusion or a secondary fission (Fig. 1C). Analysis of the

combinations of these events demonstrated that in cortical

neurons, a fusion was followed by a fission in 86.4% of cases

and by a second fusion in only 13.6% of the cases. In addition,

fission was followed by fusion in 83.5% of cases and by a second

fission in 16.5% of cases. We performed the same analysis using

cerebellar granule neurons and obtained similar results (Fig. 1C).

These data suggest that fusion and fission events are sequential

events that form a cycle rather than independent, randomly

Fig. 1. Fusion and fission are sequential events. (A) Photoactivation of

mito-Kikume-Green. Mitochondria expressing Kikume-Green were co-

transfected with mito-CFP and demonstrated clear colocalisation of both

proteins (left panels). Selected mitochondria (marked with a yellow

rectangle) were irradiated using a 405-nm laser line and mito-Kikume-

Green was converted into mito-Kikume-Red. Note that the neighbouring

mitochondria retained their green fluorescence. (B) A fusion event

between mito-Kikume-Green and photoactivated, mito-Kikume-Red

mitochondria. The fusion product became yellow after mixing of the

contents of the red and green mitochondrial matrices (see also

supplementary material Fig. S1). (C) Each fusion (left) was followed by a

fission or by a secondary fusion, and each fission (right) was followed by

a fusion or a secondary fission. To determine the extent of fusion and

fission events that were sequential, we analysed the number of event pairs

(111 event pairs starting with fusion and 103 starting with fission in

cortical neurons, and 63 pairs starting with fusion and 55 starting with

fission in cerebellar granule neurons). The number of each type of event

is shown. A x2-test was used to determine whether the observed

distribution was significantly different from the expected distribution.

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occurring events. However, an alternating fusion–fission cycle

was not consistently observed, and there were deviations from

this rule (fission–fission or fusion–fusion events) in 15% of the

cortical neurons and 24% of the cerebellar granule neurons.

We next measured the duration of the two components of the

fusion–fission cycle in cortical neurons. The mean time interval

between fusion and fission was 4.760.6 min, which was

significantly shorter than the interval between fission and the

next fusion (15.362.0 min; P,0.0001, Mann–Whitney U-test).

The duration of the entire cycle was ,20 min. It should be noted

that this analysis was only applied to the active subpopulation of

mitochondria, which may explain why the cycle duration found

here was shorter than that calculated from the fusion or fission

rates of the total mitochondrial population (,43 min).

Nevertheless, these values suggest that mitochondria spend

approximately a quarter of their time in between fusion and

fission events and three-quarters of their time in between fission

and the next fusion event.

Rules governing mitochondrial fusion and fission

Fusions almost always occurred between stationary (or passive)

and moving (or active) mitochondria. Indeed, of 34 fusion events

analysed, 28 events (82%) showed clearly recognisable active

and passive partners, 3 events (9%) occurred between two active

mitochondria, and 3 events (9%) occurred between two passive

mitochondria.

To further study how the mitochondria are juxtaposed at the

beginning of fusion, we performed fast time-course experiments

with 250-ms intervals between frames. This approach enabled

accurate examination of the exact positions of two mitochondria

relative to each other. Although we expected that the head of the

active partner would collide with the passive partner to merge the

matrices of each mitochondrion, this movement was not

common. Such head-on fusions were only observed in 2% of

all cases (2 of 89 analysed events) whereas in most cases, the

active partner passed the passive partner, which led to side-to-

side fusions (43%) or rear-end fusions (55%). It should be

mentioned that the moving head passed the body of the passive

mitochondrion in 88% of all cases (68 out of 77 analysed events)

and remained behind the head of the passive mitochondrion in

only 12% of cases (P,0.0001, x2-test).

This complicated behaviour of fusing mitochondria may be

related to the localisation and/or activity of fusion-controlling

proteins. We investigated the distribution of Mfn2 in

mitochondria and found that its localization was indeed focal

and non-homogenous and localized to specific spots (Fig. 3A)

(Karbowski et al., 2006).

The passing process itself was often sophisticated and

comprised numerous stops including nudging, turn-aways and

unexpected returns that ended with fusion. The movies show two

examples (supplementary material Movies 2, 3) where after the

initial contact, the active partner moved away from the passive

one and then turned back to make the final contact. The duration

of these dances was very variable with some interactions being

very short and others lasting up to a few minutes (mean value

5564 s, n5171). The dance ended with a firm grip between the

partners that lasted between 10 and 80 s (mean value 5864 s,

n5172) and ended with an exchange of matrix. The duration of

the grip appeared to be controlled by proteins responsible for

fusion because in neurons transfected with a dominant negative

Mfn2, this parameter was prolonged (100614 s, P50.001

compared with control).

When fused mitochondria subsequently underwent fission, in

most cases, one of the resulting daughters remained passive

Fig. 2. Mitochondrial fission is length dependent. (A,B) Mitochondrial

twin analysis. Comparison of mitochondrial length within families, where one

of the daughters underwent fission (A) or fusion (B) after the primary fission

(n530 and 45, respectively; the Wilcoxon test was used to calculate the P-

value). (C) Length dependency of mitochondrial fusion (black circles) and

fission (red circles) rates. Mitochondria from cortical neurons (1277) and

cerebellar granule neurons (413) were sub-grouped based on their lengths, and

the fission and fusion rates were determined for each sub-group. (D) Length

of the post-fission mitochondria entering either fusion (normal cycle, n586)

or fission (erroneous, cycle-breaking, n517, Mann–Whitney test). (E) Length

of the post-fusion mitochondria entering either a fission (normal cycle, n596)

or fusion event (erroneous, cycle-breaking, n515, Mann–Whitney test).

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whereas the other moved away. Interestingly, the active daughteralmost always followed the same direction as the active parenthad. We analysed 43 such events, and in 41 cases, the activedaughter continued in the same direction, and in only 2 cases, the

direction was reversed (P,0.0001, x2-test). These results suggestthat the ‘moving head’ of active mitochondria is conservedbefore fusion and moves in the same direction after fission.

Fission rate is length dependent

Both fusion and fission change mitochondrial length. Inconsideration of the alternating nature of these events, it is

reasonable to suggest that the negative feedback(s) controllingthe fusion and/or fission rates involves mitochondrial length. Toassess this hypothesis, we performed a ‘twin study’, where

daughter mitochondria originating from the same parentmitochondrion were compared. We tracked 30 ‘families’ up tothe moment when one of the daughters underwent a second

fission. The results demonstrated that the average length of thedaughter undergoing a second fission was greater than twice thelength of its non-splitting twin (Fig. 2A). In addition, wefollowed 42 pairs of twins until one of the daughters fused.

The average length of the fusing daughter matched perfectly thelength of the non-fusing daughter (Fig. 2B).

These results suggest that longer mitochondria enter fission

more readily. To confirm this conclusion, we next divided thetotal population of mitochondria in cortical and cerebellargranule neurons based on their length and determined thefission and fusion rates for each subgroup. Fig. 2C demonstrates

that in both neuron types, the fission rate was very low in shortmitochondria; however, the fission rate increased dramatically inlong mitochondria. Therefore, in contrast to the fission rate, the

fusion rate appears to be relatively independent of length.

Globally, the fusion rate exceeded the fission rate in shortermitochondria whereas the fission rate exceeded the fusion rate in

longer mitochondria. Thus, the fusion–fission balance shiftedtowards fusion in shorter organelles and towards fission in longer

organelles. Therefore, a shorter mitochondrial length decreasesthe probability of fission being the next event and consequentlyincreases the probability of fusion (supplementary material Table

S1). This finding suggests that the mitochondria of greatestlength after fission are more likely to undergo secondary,‘corrective’ fission. In contrast, post-fusion mitochondria that

are too short are more likely to undergo secondary fusion. Weanalysed particular cases to determine whether these ‘errors’indeed correlated with mitochondrial size. The results depicted inFig. 3D,E show that post-fission mitochondria that entered an

‘erroneous’ cycle-breaking second fission were significantlylonger than ‘normal’ mitochondria that entered fusion. Inagreement with this observation, post-fusion mitochondria that

entered an erroneous second fusion were significantly shorterthan normal mitochondria that entered fission. Thus, this type offeedback mechanism may serve as a quality control mechanism

to correct mitochondria that are excessively short or long.

Supplementary material Table S1 also demonstrates that post-fusion mitochondria have a 3–4 times shorter lifetime that post-fission mitochondria. This could be the reason why the duration

of the fusion–fission phase in the cycle is shorter and may also bethe reason why the majority of the mitochondrial population ateach timepoint is in a post-fission state (one post-fusion

mitochondrion gives rise to two post-fission mitochondria).

The next important question concerned the mechanismunderlying the fission rate–length relationship. This relationship

was quite steep (Fig. 2C), and its non-linearity suggested acooperative interaction between factors/molecules responsible forfission provided that the number of these molecules increased

with mitochondrial length. To determine the putative role ofDrp1 in the fission rate–length relationship, we modified Drp1expression in cortical neurons. As expected, overexpression of

Fig. 3. Manipulation of fusion proteins

but not fission proteins alters the fusion–

fission dynamics. (A) Overexpressed Mfn–

FLAG (detected using an anti-FLAG

antibody, green) is located in the ends of

mito-DsRed-expressing mitochondria.

(B) Expression of a specific shRNA-

encoding plasmid suppressed Drp1 levels in

PC12 cells by 93%. (C) Overexpressed

Drp1 (anti-Dnml) demonstrates classical

cytoskeletal localisation.

(D) Overexpressed Fis1 (anti-TTC11,

green) was homogenously distributed

throughout the mitochondrial membrane

(mito-DsRed). (E) Fusion and fission rates

and lengths of mitochondria in control,

wild-type (wt) Mfn2-, dominant negative

(dn) Mfn2-, wt Mfn1-, wt Drp1 + wt Fis 1-

overexpressing and Drp1-suppressed

neurons (see also supplementary material

Fig. S2). Data are means 6 s.e.m.

*P,0.05, **P,0.01 and ***P,0.001

versus control. The number of dishes

analysed (for fusion and fission rate) or the

number of mitochondria analysed (for

length) is shown in brackets.

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Drp1 together with Fis1 led to mitochondrial shortening whereas

Drp1 silencing was associated with dramatic mitochondrial

elongation (Fig. 3). Interestingly, neither Drp1 silencing nor

Drp1 and Fis1 overexpression led to consistent changes in fission

or fusion rates. Analysis of the fission rate–length relationship

demonstrated that Drp1 and Fis1 overexpression increased the

sensitivity of the fission rate to mitochondrial length whereas

Drp1 silencing (using specific shRNAs) led to a dramatic drop in

this sensitivity (Fig. 4A). The role of Drp1 was specific because

no change was observed following the overexpression of wild-

type (wt) Mfn2 or dominant negative Mfn2.

Impairment of the feedback mechanism in Drp1-suppressed

neurons was associated with high variability in mitochondrial

length. The coefficient of variation for length was considerably

higher in Drp1 shRNA-expressing neurons compared with

control (Fig. 4B). Importantly, Mfn2-overexpression-mediated

elongation of mitochondria did not affect length variability.

Together, these results suggest that the length–fission feedback

loop is Drp1 dependent.

Fission rate adapts itself to the fusion rate

The efficiency of this feedback control mechanism was assessed

in experiments that studied the adaptation of the fission rate to a

switched fusion rate and vice versa. We first overexpressed wt

Mfn2 and found that it induced a 76% increase in mitochondrial

fusion rate (Fig. 3E). This finding was accompanied by a 68%

increase in fission rate but a relatively modest 36% increase in

mitochondrial length. Because Mfn2 has also been implicated in

mitochondrial transport (Misko et al., 2010), we also performed a

separate experiment that showed that overexpression of Mfn1

induced similar effects to those of Mfn2 (Fig. 3E). Inversely,

inhibition of the mitochondrial fusion rate by overexpressing

dominant negative Mfn2 decreased the fusion rate to half that of

the control level. This effect was accompanied by almost

perfectly matched changes in the fission rate and a 29%

decrease in mitochondrial length. These results demonstrate

that the fission rate adapts to the fusion rate; i.e. augmented or

decreased fusion rates favour the formation of longer or shorter

mitochondria, that are either more or less likely to enter fission,respectively.

Fusion depends on the contact rateFusion can only take place when two mitochondria meet.However, not every contact results in fusion. In cortical

neurons, of 1187 analysed mitochondria from 66 separatefields, the axonal mitochondria made an average of 0.4560.02contacts per mitochondrion per min, and only 7.060.4% resulted

in fusion. However, in cerebellar neurons, axonal mitochondrialmade an average of 0.2460.03 contacts per mitochondrion, ofwhich 20% resulted in fusion. Higher fusion efficiency in

cerebellar neurons may be due to the 1.65-fold increase in Mfn2expression (P50.014) that was observed in these cells comparedwith cortical neurons.

We measured the average number of contacts made by

mitochondria and the number of fusions in a further 232neurites. Not surprisingly, the number of fusions correlatedwell with the number of contacts (Spearman r50.33, P,0.0001),

and a higher number of contacts increased the likelihood offusion.

Apparently, the number of contacts depends upon the number

of partners available, and the probability of a mitochondrionmeeting another is higher in crowded neurites. We compared thecontact rate in different axonal regions with different

mitochondrial densities. As expected, an increase in the densityof mitochondria was associated with an increase in contact rate(Spearman r50.144, P50.020).

Motility determines fusion rateIt is clear that mitochondrial partners must approach each other for a

contact to occur, and therefore, a contact should depend uponmovement characteristics. Therefore, we measured the motility ofindividual mitochondria and the number of contacts they made. Asexpected, increased motility was associated with an increase in

contact rate (Spearman r50.482, P,0.0001). To confirm therelationship between the motility and fusion rate, we analysed thevelocity of twin mitochondria where only one of the daughters

fused. The results showed that the fusing daughter had asignificantly higher velocity than its non-fusing twin (Fig. 5A). Inadditional experiments, we inhibited mitochondrial motility by

suppressing Miro proteins, which are responsible for mitochondrialattachment to molecular motors. Suppression of these proteins led toa proportional inhibition of mitochondrial velocity and contact rate,which in turn was associated with a reduction in fusion rate

(Fig. 5B–F). These results showed that motility, at least in part,determines the rate of fusion (Fig. 5B–F). Inhibition ofmitochondrial motility by Miro shRNA also inhibited fusion and

decreased the average mitochondrial length (Fig. 5G), an effect thatwas similar to the effect of dominant negative Mfn2. Similarly,overexpression of the axonal docking protein syntaphilin inhibited

mitochondrial motility and fusion rate (data not shown).

Mitochondrial motility during the fusion–fission cycle

Considering that mitochondrial velocity is an importantdeterminant of mitochondrial fusion, we next studied thevelocity of single mitochondria during the course of a fusion–

fission cycle. We first traced the velocity of those mitochondriathat later entered fusion. Fig. 6A and B show that at ,10 minbefore a fusion event, both the active and passive partners had the

Fig. 4. Knockdown of Drp1 abolishes the length dependency of

mitochondrial fission. (A) The length dependency of mitochondrial fission in

Drp1 shRNA- (red line), Drp1- and Fis 1-expressing (black line), and control

(dashed line) neurons. Mitochondria (513) from the Drp1 shRNA group and

Drp1 and Fis 1 (531) groups were analysed. (B) The average coefficient of

variability of mitochondrial length in control, Drp shRNA- and Mfn2-

overexpressing neurons. Coefficients were calculated for individual neurites

(27 in control and 12 in other groups) and then averaged. ***P,0.001

versus control.

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same mean low velocity. However, later, the velocity of the

active partner increased progressively up to the moment of

fusion whereas no change was observed in the velocity of the

passive partner. Remarkably, the fusion event induced a dramatic

drop in mitochondrial motility, and the fusion product was

relatively immobile compared with the active parent. In contrast

to the pre-fusion state, no change in mitochondrial velocity was

observed in the pre-fission state. Interestingly, after fission, the

velocity of the active daughter that moved away was similar to

that of the active partner prior to fusion (Spearman r50.425 and

P50.0062). However, the high velocity slowed rapidly but was

nevertheless higher than the velocity of the second daughter for a

period of time (Fig. 6C,D). Thus, the fusion–fission cycle is

associated with clear changes in the velocity of individual

mitochondria.

Fusion–fission dynamics in models of neurodegenerative

diseases

Recent reports demonstrate that overexpression of mutant

Huntingtin (Trushina et al., 2004; Chang et al., 2006; Song

et al., 2011) and Tau (Ebneth et al., 1998) impair mitochondrial

dynamics. To test whether the fusion and fission dynamics are

altered in these disease models, we first overexpressed the first

exon of mutant Huntingtin, containing 120 polyglutamines

(120Q-Htt), in cortical neurons. As expected, expression of this

construct led to a decrease (by 4067%) in average mitochondrial

velocity and a concomitant reduction (by 3569%) in the number

of contacts between mitochondria. Importantly, these changes

were associated with decrease in fusion and fission rates (by

5766% and 46610%, respectively). Similar to the reduced

motility induced by suppression of Miro protein, the reduced

fusion rate was related to mitochondrial shortening (Fig. 7).

To test the causal relationship between reduced motility and

fragmentation, we next tried to increase the motility in 120Q-Htt-

expressing neurons using Miro-1. The results depicted in Fig. 7

demonstrate that Miro-1 overexpression restored mitochondrial

velocity completely in addition to the rate of mitochondrial

contacts. These changes were followed by a recovery in fusion

rate and an amelioration of the mitochondrial fragmented

phenotype.

Finally, we overexpressed Tau protein, which is also known to

inhibit mitochondrial motility in neurons. Similar to the results

obtained following 120Q-Htt overexpression, Tau overexpression

reduced mitochondrial motility and led to a decreased contact

rate. It was also associated with a decrease in fusion rate that led

to mitochondrial shortening. The co-expression of Miro-1 and

Tau improved mitochondrial motility, contact and fusion rates

and rescued the mitochondrial phenotypes (Fig. 7).

DiscussionMitochondrial fission and fusion are often viewed as being in a

finely-tuned balance within cells; however, an integrated and

quantitative understanding of how these processes interact with each

other and with mitochondrial motility and morphology has yet to be

formulated. Our main findings demonstrate that: (1) the probability

of a single mitochondrion splitting is determined by its length; (2)

the probability of a single mitochondrion fusing is determined

primarily by its motility; (3) the fusion and fission cycle is driven by

changes in mitochondrial length – an increase in mitochondrial

length after fusion increases the probability of fission whereas a

Fig. 5. Fusion is correlated with mitochondrial motility.

(A) Motility analysis of twin mitochondria from families where

one of the daughters fused during the observation time. The bar

graph show the mean mitochondrial motility for fusing and

non-fusing daughters. (B) Both Miro-1 shRNA (left) and Miro-

2 shRNA (right) effectively suppressed the expression of

endogenous Miro-s. (C) Kymograms derived from movies of

control and Miro-silenced neurons. The upper panels show the

starting point and the lower panels show the movement of

mitochondria (red or green) over the following 10 min. A

fusion event led to the formation of a yellow signal, and the

movement of fission products is designated by the dotted line.

(D–G) Parameters of mitochondrial dynamics and morphology

in control and Miro-silenced neurons. Data are means 6 s.e.m.

*P,0.05, **P,0.01 and *** P,0.001 versus control. See also

supplementary material Fig. S3.

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decrease in mitochondrial length after fission reduces this

probability; (4) deviations from the fusion and fission cycle serve

as a corrective mechanism to avoid extreme mitochondrial length;

(5) impaired mitochondrial motility in neurons overexpressing 120Q

Htt or Tau suppresses mitochondrial fusions and leads to

mitochondrial shortening; stimulation of mitochondrial motility by

overexpressing Miro-1 restores mitochondrial fusion rates and sizes

under these conditions.

Self-regulation of mitochondrial length

Our major novel finding was that mitochondrial length controls

the rate of mitochondrial fission. Longer mitochondria enter

fission more readily than shorter mitochondria. For example, a

5-mm mitochondrion showed a 10-fold higher fission rate than a

2-mm mitochondrion. Similar results were also observed in our

‘twin study’ that minimised the involvement of other factors,

such as different DNA or protein composition, or cytoplasmic

environment, which may affect the fission rate independent of

length. Regardless of the molecular mechanism underlying the

observed length–fission relationship, this phenomenon appears to

control mitochondrial length in neurons and also appears to be

the main feedback tool enabling neurons to sense and correct

mitochondrial length.

This type of control also explains why the fission rate is related

to the fusion rate such that these two rates are balanced perfectly.

None of the interventions used in our experiments changed

the fusion rate/fission rate ratio significantly. On average,

mitochondria in axons of cortical neurons underwent fusion or

fission 33 times per day. The slightest imbalance (one fusion less

or more per day) should therefore eventually lead to complete

mitochondrial fragmentation or the formation of a few

megamitochondria in the cell; however, this was not the case.

Overexpression of wt Mfn2 doubled the fusion and fission rates

and led to only a slight increase in mitochondrial length. It is

most likely that increased fusion activity induced a slight

elongation in mitochondria, which in turn activated the fission

machinery that attempted to block a further increase in

mitochondrial length.

In addition, these findings provide a clear explanation as to

why manipulations of fission machinery failed to change the

fission rate. For example, Drp1 upregulation did not increase the

rate of fusion although it did lead to mitochondrial shortening. An

attempt to increase the fission rate and thereby shorten

mitochondria is likely to be counterbalanced by an inhibition of

the fission machinery by that same mitochondrial shortening.

Suppression of the fission rate by inhibition of Drp1 induced the

Fig. 6. Mitochondrial motility changes at different stages of the mitochondrial fusion and fission cycle. (A) Mitochondrial velocity starting at 10 min prior to

the fusion event up to 10 min after the fusion event. (B) The mean mitochondrial velocity measured 10 min prior to the fusion event, immediately before the

fusion event and immediately after the fusion event. (C) The mitochondrial velocity from 10 min before the fission event up to 30 min after the fission event.

(D) The mean mitochondrial velocity measured immediately before the fission event, immediately after the fission event and 20 min after the fission event.

*P,0.05, **P,0.01 and *** P,0.001.

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opposite effect, which leads to mitochondrial elongation that in

turn activates fission machinery. Mitochondrial length is thus

self-regulated via Drp1-dependent fission.

Fusion rate is determined by the availability of partners –‘it takes two to tango’

Fusion can only take place when two mitochondria meet. The

number of contacts a mitochondrion makes depends on its

motility and the number of mitochondria in the vicinity. Higher

motility increases the likelihood of a mitochondrion finding a

partner and consequently the fusion rate. In turn, lower motility

decreases the number of contacts and the fusion rate. The latter

conclusion is consistent with previous findings that inhibition of

mitochondrial movement by nocodazol and vasopressin in H9c2

cells also inhibited mitochondrial fusion (Liu et al., 2009).

Similarly, a recent study by Twig et al. suggested that

mitochondrial motility facilitates mitochondrial fusion in H9c2

and INS1 cells (Twig et al., 2010). Our results support this

hypothesis with quantitative data demonstrating that

mitochondria entering fusion show twofold higher motility

compared with their nonfusing sisters. Moreover, our results

demonstrate that direct slowing of mitochondrial motility by

suppressing mitochondrial Miro proteins [required for

mitochondrial antero- and retrograde transport (Russo et al.,

2009)] or by overexpressing the axonal docking protein

syntaphilin inhibit the rate of mitochondrial fusion.

Obviously, the interaction between mitochondrial motility

and fusion/fission dynamics is rather sophisticated. The velocity

of mitochondria that are about to fuse begins to increase

several minutes prior to the fusion and increases progressively

to the point of fusion. It is unclear whether this increase in

motility reflects an intrinsic ‘intention to fuse’ or whether the

fusion is a simple consequence of the higher motility. Recent

research has demonstrated that Mfn2 interacts with Miro-2

protein and is required for mitochondrial transport (Misko et al.,

2010), which suggests that the Mfn–Miro interaction is used by

mitochondria to inform the transport machinery of the readiness

to fuse.

It is also relevant to note that after the fusion event, the new

mitochondrion remains relatively immobile. This cannot be

explained by its increased length because we did not observe any

correlation between mitochondrial length and motility. It is more

likely that passive mitochondria are anchored so strongly that

they will also hold the moving mitochondria. However, after

Fig. 7. Miro-1 restores mitochondrial dynamics in 120Q-Htt and Tau-expressing neurons. (A) Overexpressed 120Q-Htt–EGFP co-localised with staining for

an anti-Htt antibody (red) in the cytoplasm and showed typical inclusion bodies in the nucleus (stained using DAPI, blue). (B) Overexpression of wt Tau (anti-tau

5A6, red) in neurons expressing the microtubule marker MAP2c–EGFP. (C) Overexpression of Miro-1 was confirmed using an anti-Rhot1 antibody (green).

Miro-1 was distributed homogenously in mitochondria (mito-DsRed). (D) The suppression of mitochondrial motility, contact rate, fusion rate and mitochondrial

length in neurons overexpressing 120Q-Htt were all reversed following the co-expression of wt Miro-1 (Htt + Miro). (E) The suppression of mitochondrial

motility, contact rate, fusion rate and mitochondrial length in neurons overexpressing wtTau wt was reversed following the co-expression of wt Miro-1 (Tau +

Miro). *P,0.05, **P,0.01 and ***P,0.001 compared with control and #P,0.05, ##P,0.01 and ###P,0.001 compared with Htt or Tau group.

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fission, the mitochondria that formed from a previously active

segment move away and slow down. Thus, the velocity of

individual mitochondria changes with the phase of the fusion/

fission cycle (Fig. 6).

Another factor that may increase the mitochondrial fusion rate

is the number of surrounding mitochondria. For example, the

fusion rate in a neuronal soma, which shows a higher

mitochondrial density, is greater than fivefold that of axons

(where mitochondrial density is relatively low). This finding

could be one of the reasons why the fusion rate changes between

different neuronal compartments and may explain why

mitochondria in the soma are 50% (1 mm) longer than in the

periphery. Nevertheless, we cannot rule out the possibility that

the increased fusion rate is also caused by the higher accessibility

or activity of the fusion–fission proteins.

The fusion–fission cycle is driven by changes inmitochondrial length

In their paper, Twig et al. elegantly demonstrated that fusion and

fission, typically, are sequential events that form a cycle (Twig

et al., 2008). However, in a recent report, Wang et al. showed that

the fusion and fission events were not always sequential (35% of

events in HeLa cells and 40% of the events in MEF cells were not

cyclic) (Wang et al., 2012). We have shown that in neurons, the

fusion and fission events were also not always sequential: 15% of

events in cortical neurons and 25% in cerebellar neurons were not

cyclic. Importantly, the dependency of the fission rate on length

discovered in our study provides a very simple explanation as to

why mitochondrial fusion and fission alternate and why these

events are not always cyclic. After each fusion, the mitochondrial

length doubles. This doubling causes an 8-fold increase in

the probability of fission and predicts a short lifetime for the

post-fusion mitochondrion. In contrast, fission halves the

mitochondrial length and therefore diminishes the likelihood of

a secondary fission and increases the probability of a fusion being

the next event. This mechanism enables alternating fusion andfission events and also explains why mitochondria spend

approximately a quarter of their time in a post-fusion state andthree-quarters of their time in a post-fission state. If fusion

occasionally leads to the formation of a mitochondrion that is tooshort or a fission product that is too long, the cycle has been

compromised. Deviations from the cycle (two consecutivefusions or two consecutive fissions) serve as quality control

mechanisms to correct small or oversized mitochondria. Thismechanism may have an important physiological relevance in the

maintenance of optimal mitochondrial size. Mitochondria that aretoo long have been shown to exhibit a compromised bioenergetic

capacity (Benard et al., 2007) and may have difficulties indelivering energy to the cell.

Mitochondrial fusion–fission dynamics inneurodegenerative diseases

Recent reports suggest that mutant Huntingtin impairs the

balance in mitochondrial fission and fusion and thereby causesneuronal injury. Mutant Huntingtin triggers mitochondrial

fragmentation in rat neurons and fibroblasts from individualswith Huntington’s disease (Song et al., 2011). Increases in Drp1

and Fis1 and decreases in Mfn1 and Mfn2 expression have beenobserved in cortical samples from HD patients (Shirendeb et al.,

2011).

Our experiments demonstrated that mutant Huntingtin

impaired mitochondrial fission–fusion balance by inhibitingfusion activity. These data suggest that mutant Huntingtin may

also induce mitochondrial fragmentation indirectly by inhibitingmitochondrial motility (Trushina et al., 2004; Chang et al., 2006).This effect could inhibit the number of contacts between

mitochondria and consequently reduce the rate of fusion, whichwould lead to mitochondrial shortening. Mutant Huntingtin-

mediated mitochondrial fragmentation, defects in the fusion andfission rates, and a decrease in the number of contacts were

all rescued by increasing mitochondrial motility via theoverexpression of Miro1 protein. Interestingly, this effect was

not specific to mutant Huntingtin. Ebneth et al. reported thatoverexpression of Tau resulted in a failure of the cell to transport

mitochondria to peripheral compartments, which may be ofrelevance to Alzheimer’s disease (Ebneth et al., 1998). In our

settings, overexpression of wt Tau suppressed mitochondrialmotility and mitochondrial fusion and induced mitochondrial

fragmentation. Similar to mutant Huntingtin, all of theseparameters were restored following Miro-1 overexpression.

These results suggest that motility likely plays a key role inmitochondrial fusion–fission dynamics and morphology, and itsrestoration may constitute a new treatment option for

Huntington’s and Alzheimer’s disease.

Together, our results provide a novel insight into the complex

crosstalk between mitochondrial fusion and fission, length andmotility (Fig. 8). This knowledge will provide better

understanding of the dynamic mitochondrial function in cellularphysiology and the pathogenesis of mitochondrial-related

neuronal diseases.

Materials and MethodsNeuronal culture

Primary cultures of rat cortical cells were prepared from neonatal Wistar rats.Briefly, cortices were dissected in ice-cold Krebs–Ringer solution (135 mM NaCl,5 mM KCl, 1 mM MgSO4, 0.4 mM K2HPO2, 15 mM glucose and 20 mM HEPES,pH 7.4) containing 0.3% BSA and then trypsinised in 0.8% trypsin for 10 min at

Fig. 8. Summarised principles of the feedback that controls

mitochondrial length in neurons. Mitochondrial number and motility

positively correlates with the kiss or contact rate, which in turn, acts as a

pacemaker for fusions. The fusion rate may also be affected by the expression

or activity of fusion proteins. Increases or decreases in the fusion rate in turn

leads to a corresponding increase or decrease in mitochondrial length,

respectively, which controls the fission rate. Alterations in the expression or

activity of fission proteins also influences mitochondrial length, which

balances the fission rate via feedback. These controls enable the equilibration

of fusion and fission rates.

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37 C. The cells were then triturated in a 0.008% DNase solution containing 0.05%soybean trypsin inhibitor. Cells were resuspended in Basal Medium Eagle withEarle’s salts (BME) containing 10% heat-inactivated FBS, 25 mM KCl, 2 mMglutamine and 100 mg/ml gentamicin, and then plated onto 35 mm glass-bottomdishes (MatTek, MA, USA), which were pre-coated with poly-L-lysine, at adensity of ,106 cells/ml (2 ml of cell suspension per dish). After incubating for3 h, the medium was changed to NeurobasalTMA medium containing B-27supplement, 2 mM GlutaMAXTM-I and 100 mg/ml gentamicin. Over 60% of thecells showed a neuronal phenotype when the described procedure was followed.

To prepare primary cultures of cerebellar granule cells, the cerebella from 8 day-old Wistar rats were dissociated by trypsinising in 0.25% trypsin at 35 C for15 min followed by trituration in a 0.004% DNase solution containing 0.05%soybean trypsin inhibitor. Cells were resuspended in BME containing 10% FBS,25 mM KCl, 2 mM glutamine and 100 mg/ml gentamicin. Neurons were platedonto 35 mm glass-bottomed dishes that were pre-coated with poly-L-lysine at adensity of 1.36106 cells/ml. Ten mM cytosine arabinoside was added 24 h afterplating to prevent the proliferation of glial cells.

The PC12 cell line was maintained in RPMI medium supplemented with 10%horse serum and 5% FBS on collagen IV (Sigma)-coated plastic dishes. All of theculture media and supplements were obtained from Invitrogen (Carlsbad, CA,USA).

Plasmids

Mitochondrial KikGR1 (mito-KikGR1) was constructed by PCR amplification ofthe mitochondrial targeting signal from pdsRed2-Mito (Human COXVIIIa,nucleotides 597–683) and cloning in-frame between the EcoRI and HindIII sitesof the Kikume vector, which was obtained from Amalgaam Co. (Tokyo, Japan).The plasmid expressing mito-CFP was obtained from Evrogen (Moscow, Russia),and mitochondrial-pDsRed2 was obtained from Clontech (CA, USA). Plasmidsexpressing shRNA targeted against Drp1, Miro1 and Miro2 were fromSABiosciences (Frederick, MD, USA). Wild-type (wt) and dominant-negativeMfn2DTM were generous gifts from Dr S. Hirose (Honda et al., 2005), Drp1 wasfrom Dr G. Szabadkai (Szabadkai et al., 2004), Fis1 was from Dr J.-C. Martinou(Mattenberger et al., 2003), Map2c-EGFP was from Dr A. Matus (Kaech et al.,1996), Miro1 was from Dr P. Aspenstrom (Fransson et al., 2003), Tau was from DrG. Johnson (Krishnamurthy and Johnson, 2004), and mutant Htt was from Dr L.Hasholt (Hasholt et al., 2003).

Transfections

Cultures were transiently transfected on the second day after plating usingLipofectamineTM 2000 (Invitrogen). Briefly, conditioned medium was collectedand 120 ml of Opti-MEMH I medium containing 2% LipofectamineTM 2000 and1 mg of total DNA (1 mg of mito-KikumeGR1 in the control; 0.33 mg of mito-KikumeGR1 and 0.67 mg of the desired DNA in the other groups) were addeddirectly to cells grown on 35 mm glass-bottomed dishes, and the cells were thenincubated for 3 h at 37 C in a humidified atmosphere containing 5% CO2/95% air.At the end of this incubation, 2 ml of fresh (or conditioned medium for granularneurons) NeurobasalTM medium was added per dish. The cells were then culturedfor 3–4 days to enable expression of the transfected DNA with the exception of120Q Htt (4–5 days), Tau wt (5–6 days) and Miro shRNA (8 days). Duringacquisition, the cells were maintained in Krebs–Ringer solution supplemented withcalcium (1 mM) and glucose (15 mM).

Immunohistochemistry

Neurons were fixed using 4% paraformaldehyde solution in NeurobasalTMAcontaining 5% sucrose for 10 min at 37 C. Fixed cells were permeabilised using0.3% Triton X-100 in PBS for 5 min and then blocked using 10% normal goatserum and 3% BSA for 60 min at room temperature. The neurons were thenincubated with the primary antibodies mouse anti-FLAG (1:500, F1804, Sigma-Aldrich), rabbit anti-Mfn2 (1:100, ab50838, Abcam, USA), rabbit anti-TTC11(1:100, ab71498, Abcam), rabbit anti-Myc (1:500, ab9106, Abcam), mouse anti-DNML (1:250, ab56788, Abcam), rabbit anti-RHOT1 (1:50, HPA010687, Sigma-Aldrich, Germany), mouse anti-DRPLA-35Q (1:10, MW2, Developmental StudiesHybridoma Bank at the University of Iowa, USA), or mouse anti-Tau (1:50, 5A6,Developmental Studies Hybridoma Bank) in the presence of 3% normal goatserum at 4 C for 48 h. After washing, the cells were further incubated withrespective Alexa-Fluor-488- or Alexa-Fluor-594-conjugated secondary antibodiesat room temperature for 1 h and subsequently examined using confocalmicroscopy.

Western blotting

For western blotting, cells were lysed in a buffer containing 50 mM Tris-HCl,1 mM EDTA, 150 mM NaCl, 1% NP-40, 1 mM Na3VO4, 1 mM NaF, 0.25%sodium deoxycholate and 5% protease inhibitor cocktail (Roche) for 30 min onice. Equivalent amounts of total protein were separated by SDS-PAGE on 10%polyacrylamide gels and then transferred to Hybond-P PVDF transfer membranes(Amersham Biosciences, UK) in 0.1 M Tris-base, 0.192 M glycine and 10% (v/v)

methanol. The membranes were blocked with 5% (w/v) non-fat dried milk in TBS

containing 0.1% (v/v) Tween-20 at room temperature for 1 h and then probedovernight with mouse monoclonal anti-b-actin (1:4000, Sigma), mouse

monoclonal anti-DNM1L (1:2000, Abcam), mouse monoclonal anti-RHOT1

(1:2000, Abcam), or rabbit polyclonal anti-RHOT2 (1:1000, ProteinTech GroupInc.). The membranes were then incubated with appropriate HRP-conjugated

secondary antibodies (1:4000, Pierce, USA) for 1 h at room temperature.

Immunoreactive bands were detected by enhanced chemiluminescence (ECL,Amersham Biosciences, UK) using medical X-ray film blue (Agfa, Belgium). The

probed blots were analysed by densitometry using MicroImage software (MediaCybernetics, Bethesda, MD).

Image acquisition

A laser scanning confocal microscope (LSM 510 Duo, Zeiss) equipped with a LCIPlan-Neofluar 636/1.3 immersion-corrected DIC M27 objective was used in this

study. The temperature was maintained at 37 C using a climate chamber.Mitochondrial fusion and fission events were followed using photoconvertible

mitochondrial-targeted mito-KikGR1. Mitochondria labelled with mito-KikGR1

were first visualised using a 488-nm Argon laser line and BP 505–550 emissionfilters. Selected green-emitting mitochondria were then photoconverted to red

using a 405-nm Diode laser (50 mW, 1.5% power, 20 iterations). For the images,

which typically comprised 10–20 mitochondria per neurite, four to fivemitochondria were photoactivated using two separate bleaching regions to

facilitate detection of fusion events. All mitochondria were then illuminated

using the 488 nm Argon laser (for green mitochondria; 30 mW, 1.5% power) and a561-nm DPSS laser (for red mitochondria; 15 mW, 7% power). Images were

acquired simultaneously to avoid movement distortions during scanning using a

BP 505–550 and LP575 filters to separate green- and red-emitting mitochondria,respectively.

For cycle analysis, images were taken every 10 s for 2 h. To study the fusionevents, fast time-lapse experiments were conducted where images taken in

,250 ms intervals were acquired over 10 mins. To compare the different

transfection conditions, images were taken at 10-s intervals for 10 min. Forcolocalisation studies of mito-KikGR1 and mito-CFP, mito-CFP fluorescence after

excitation with a 458-nm argon laser line (1% power) was split using HFT458 andthen separated using a BP465–510 filter.

Image processing and analysis

The fate of all photoactivated mitochondria was followed throughout the time-lapse and the fusion and fission events recorded. Changes in mitochondrial lengths

were measured using LSM5 Duo version 4.2 software (Carl Zeiss MicroImaging

Gmbh, and EMBL Heidelberg, Germany). The resulting database was then used toanalyse fusion and fission cycle parameters, length dependency, and for twin

analysis. Mitochondria were further tracked for motility analysis using Retrackversion 2.10.05 (freeware provided by Nick Carter).

In experiments that compared different conditions, four fields per dish were

imaged and four dishes per condition were used, and all experiments wereperformed in at least duplicate. Thus, the mitochondrial population presented

always originates from at least 32 different neurons. The number of fusions,fissions and contacts with other mitochondria of an photoactivated mitochondrion

was summarised per dish and then averaged over 8–24 dishes. To compare the

mitochondrial velocities, 10–20 mitochondria per neurite (including non-activatedmitochondria) were tracked and the dish medians averaged.

Length analysis was performed using MicroImage software (Media Cybernetics,Bethesda, MD, USA) and also included other non-activated mitochondria from

studied axons. The presented images and movies were 2D deblurred and

deconvoluted using the AutoDeblur and Autovisualise X software package(Media Cybernetics Inc., Bethesda, MD, USA).

Calculation of average lifetime and probability of fusion

The average lifetime for post-fusion and post-fission mitochondria was calculated

as: lifetime51/(fusion rate+fission rate).

The probability of fusion as a next event was calculated as: fusion

probability5fusion rate/(fusion rate + fission rate), and the probability of

fission as a next event as: fission probability5fission rate/(fusion rate + fission

rate).

Statistics

The D’Agostino–Pearson omnibus test was used to test for normality. The Mann–Whitney U-test, Student’s t-test, one-way ANOVAs followed by Newman-Keul’s

post-hoc tests or Kruskal–Wallis tests followed by Dunn’s test were used tocompare differences between experimental and control groups. Correlations

were calculated using either the Spearman or Pearson tests. The x2-test was

used to determine whether the observed distribution was significantly differentfrom the expected distribution. P-values ,0.05 were considered statistically

significant.

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AcknowledgementsWe thank Drs S. Hirose, N. Nakamura, E. Bampton, J.-C. Martinou,A. van der Bliek, G. Szabadkai, A. Matus, P. Aspenstrom, A.Fransson, G. Johnson and L. Hasholt for providing the plasmids. Wealso thank Dr Miriam A. Hickey for her assistance with proofreading.

Author contributionsM.C., D.S., V.V. and A.K. designed research; M.C., D.S., M.L., J.L.,V.C. and P.W. performed research; M.C., D.S., M.L., J.L., V.V., andA.K. analyzed data; M.C., D.S., V.V. and A.K. wrote the paper.

FundingThis research was supported by an institutional research fundinggrant from the Estonian Research Council [grant number IUT2-5 toA.K.]; the Estonian Science Foundation [grant numbers 7991 toA.K and 7175, 8810 to D.S.]; the European Community [grantnumber 205773 to A.K.]; the European Regional DevelopmentFund grant number [grant number 3.2.0101.08-0008 to A.K.]; theEstonian–French research program Parrot [to A.K. and V.V]; andMobilitas [grant number MJD35 to M.C.].

Supplementary material available online at

http://jcs.biologists.org/lookup/suppl/doi:10.1242/jcs.118844/-/DC1

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