Research Article
2187
Principles of the mitochondrial fusion and fission
cycle in neurons
Michal Cagalinec1, Dzhamilja Safiulina1, Mailis Liiv1, Joanna Liiv1, Vinay Choubey1, Przemyslaw Wareski1,
Vladimir Veksler1,2,3 and Allen Kaasik1,*
1
Department of Pharmacology, Centre of Excellence for Translational Medicine, University of Tartu, Ravila 19, Tartu, Estonia
INSERM, U-769, Châtenay-Malabry F-92296, France
Université Paris-Sud, Châtenay-Malabry F-92296, France
2
3
*Author for correspondence ([email protected])
Journal of Cell Science
Accepted 19 February 2013
Journal of Cell Science 126, 2187–2197
ß 2013. Published by The Company of Biologists Ltd
doi: 10.1242/jcs.118844
Summary
Mitochondrial fusion–fission dynamics play a crucial role in many important cell processes. These dynamics control mitochondrial
morphology, which in turn influences several important mitochondrial properties including mitochondrial bioenergetics and quality
control, 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 modern
visualisation techniques to provide a clear explanation of how fusion and fission correlate with mitochondrial length and motility in
neurons. 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 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. Taken
together, 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 of
mitochondrial-related neurodegenerative diseases.
Key words: Mitochondrial dynamics, Mitochondrial fusion, Neurons, Neurodegeneration
Introduction
Mitochondria 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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Journal of Cell Science 126 (10)
models of neurodegenerative diseases, we can rescue an impaired
mitochondrial phenotype by correcting mitochondrial motility.
Results
Visualisation of fusion and fission in neurons
Journal of Cell Science
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 cotransfected 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-KikumeGreen 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.
Principles of the mitochondrial fusion and fission cycle
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.
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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
Journal of Cell Science
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-toside 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
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 Pvalue). (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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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 shRNAencoding 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 1overexpressing 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.
whereas the other moved away. Interestingly, the active daughter
almost always followed the same direction as the active parent
had. We analysed 43 such events, and in 41 cases, the active
daughter continued in the same direction, and in only 2 cases, the
direction was reversed (P,0.0001, x2-test). These results suggest
that the ‘moving head’ of active mitochondria is conserved
before fusion and moves in the same direction after fission.
Fission rate is length dependent
Both fusion and fission change mitochondrial length. In
consideration of the alternating nature of these events, it is
reasonable to suggest that the negative feedback(s) controlling
the fusion and/or fission rates involves mitochondrial length. To
assess this hypothesis, we performed a ‘twin study’, where
daughter mitochondria originating from the same parent
mitochondrion were compared. We tracked 30 ‘families’ up to
the moment when one of the daughters underwent a second
fission. The results demonstrated that the average length of the
daughter undergoing a second fission was greater than twice the
length of its non-splitting twin (Fig. 2A). In addition, we
followed 42 pairs of twins until one of the daughters fused.
The average length of the fusing daughter matched perfectly the
length of the non-fusing daughter (Fig. 2B).
These results suggest that longer mitochondria enter fission
more readily. To confirm this conclusion, we next divided the
total population of mitochondria in cortical and cerebellar
granule neurons based on their length and determined the
fission and fusion rates for each subgroup. Fig. 2C demonstrates
that in both neuron types, the fission rate was very low in short
mitochondria; however, the fission rate increased dramatically in
long 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 shorter
mitochondria whereas the fission rate exceeded the fusion rate in
longer mitochondria. Thus, the fusion–fission balance shifted
towards fusion in shorter organelles and towards fission in longer
organelles. Therefore, a shorter mitochondrial length decreases
the probability of fission being the next event and consequently
increases the probability of fusion (supplementary material Table
S1). This finding suggests that the mitochondria of greatest
length 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. We
analysed particular cases to determine whether these ‘errors’
indeed correlated with mitochondrial size. The results depicted in
Fig. 3D,E show that post-fission mitochondria that entered an
‘erroneous’ cycle-breaking second fission were significantly
longer than ‘normal’ mitochondria that entered fusion. In
agreement with this observation, post-fusion mitochondria that
entered an erroneous second fusion were significantly shorter
than normal mitochondria that entered fission. Thus, this type of
feedback mechanism may serve as a quality control mechanism
to correct mitochondria that are excessively short or long.
Supplementary material Table S1 also demonstrates that postfusion mitochondria have a 3–4 times shorter lifetime that postfission mitochondria. This could be the reason why the duration
of the fusion–fission phase in the cycle is shorter and may also be
the reason why the majority of the mitochondrial population at
each timepoint is in a post-fission state (one post-fusion
mitochondrion gives rise to two post-fission mitochondria).
The next important question concerned the mechanism
underlying the fission rate–length relationship. This relationship
was quite steep (Fig. 2C), and its non-linearity suggested a
cooperative interaction between factors/molecules responsible for
fission provided that the number of these molecules increased
with mitochondrial length. To determine the putative role of
Drp1 in the fission rate–length relationship, we modified Drp1
expression in cortical neurons. As expected, overexpression of
Principles of the mitochondrial fusion and fission cycle
2191
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 rate
Journal of Cell Science
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 Mfn2overexpressing neurons. Coefficients were calculated for individual neurites
(27 in control and 12 in other groups) and then averaged. ***P,0.001
versus control.
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 wildtype (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
Fusion can only take place when two mitochondria meet.
However, not every contact results in fusion. In cortical
neurons, of 1187 analysed mitochondria from 66 separate
fields, the axonal mitochondria made an average of 0.4560.02
contacts per mitochondrion per min, and only 7.060.4% resulted
in fusion. However, in cerebellar neurons, axonal mitochondrial
made an average of 0.2460.03 contacts per mitochondrion, of
which 20% resulted in fusion. Higher fusion efficiency in
cerebellar neurons may be due to the 1.65-fold increase in Mfn2
expression (P50.014) that was observed in these cells compared
with cortical neurons.
We measured the average number of contacts made by
mitochondria and the number of fusions in a further 232
neurites. Not surprisingly, the number of fusions correlated
well with the number of contacts (Spearman r50.33, P,0.0001),
and a higher number of contacts increased the likelihood of
fusion.
Apparently, the number of contacts depends upon the number
of partners available, and the probability of a mitochondrion
meeting another is higher in crowded neurites. We compared the
contact rate in different axonal regions with different
mitochondrial densities. As expected, an increase in the density
of mitochondria was associated with an increase in contact rate
(Spearman r50.144, P50.020).
Motility determines fusion rate
It is clear that mitochondrial partners must approach each other for a
contact to occur, and therefore, a contact should depend upon
movement characteristics. Therefore, we measured the motility of
individual mitochondria and the number of contacts they made. As
expected, increased motility was associated with an increase in
contact rate (Spearman r50.482, P,0.0001). To confirm the
relationship between the motility and fusion rate, we analysed the
velocity of twin mitochondria where only one of the daughters
fused. The results showed that the fusing daughter had a
significantly higher velocity than its non-fusing twin (Fig. 5A). In
additional experiments, we inhibited mitochondrial motility by
suppressing Miro proteins, which are responsible for mitochondrial
attachment to molecular motors. Suppression of these proteins led to
a 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 of
mitochondrial motility by Miro shRNA also inhibited fusion and
decreased the average mitochondrial length (Fig. 5G), an effect that
was 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 important
determinant of mitochondrial fusion, we next studied the
velocity of single mitochondria during the course of a fusion–
fission cycle. We first traced the velocity of those mitochondria
that later entered fusion. Fig. 6A and B show that at ,10 min
before a fusion event, both the active and passive partners had the
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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 Miro2 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.
Fusion–fission dynamics in models of neurodegenerative
diseases
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-Httexpressing 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).
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
Discussion
Mitochondrial 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
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.
Journal of Cell Science
Principles of the mitochondrial fusion and fission cycle
2193
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.
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
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Journal of Cell Science 126 (10)
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.
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
Principles of the mitochondrial fusion and fission cycle
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Journal of Cell Science
the next event. This mechanism enables alternating fusion and
fission events and also explains why mitochondria spend
approximately a quarter of their time in a post-fusion state and
three-quarters of their time in a post-fission state. If fusion
occasionally leads to the formation of a mitochondrion that is too
short or a fission product that is too long, the cycle has been
compromised. Deviations from the cycle (two consecutive
fusions or two consecutive fissions) serve as quality control
mechanisms to correct small or oversized mitochondria. This
mechanism may have an important physiological relevance in the
maintenance of optimal mitochondrial size. Mitochondria that are
too long have been shown to exhibit a compromised bioenergetic
capacity (Benard et al., 2007) and may have difficulties in
delivering energy to the cell.
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.
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 in
mitochondrial 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
Mitochondrial fusion–fission dynamics in
neurodegenerative diseases
Recent reports suggest that mutant Huntingtin impairs the
balance in mitochondrial fission and fusion and thereby causes
neuronal injury. Mutant Huntingtin triggers mitochondrial
fragmentation in rat neurons and fibroblasts from individuals
with Huntington’s disease (Song et al., 2011). Increases in Drp1
and Fis1 and decreases in Mfn1 and Mfn2 expression have been
observed in cortical samples from HD patients (Shirendeb et al.,
2011).
Our experiments demonstrated that mutant Huntingtin
impaired mitochondrial fission–fusion balance by inhibiting
fusion activity. These data suggest that mutant Huntingtin may
also induce mitochondrial fragmentation indirectly by inhibiting
mitochondrial 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, which
would lead to mitochondrial shortening. Mutant Huntingtinmediated mitochondrial fragmentation, defects in the fusion and
fission rates, and a decrease in the number of contacts were
all rescued by increasing mitochondrial motility via the
overexpression of Miro1 protein. Interestingly, this effect was
not specific to mutant Huntingtin. Ebneth et al. reported that
overexpression of Tau resulted in a failure of the cell to transport
mitochondria to peripheral compartments, which may be of
relevance to Alzheimer’s disease (Ebneth et al., 1998). In our
settings, overexpression of wt Tau suppressed mitochondrial
motility and mitochondrial fusion and induced mitochondrial
fragmentation. Similar to mutant Huntingtin, all of these
parameters were restored following Miro-1 overexpression.
These results suggest that motility likely plays a key role in
mitochondrial fusion–fission dynamics and morphology, and its
restoration 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 and
motility (Fig. 8). This knowledge will provide better
understanding of the dynamic mitochondrial function in cellular
physiology and the pathogenesis of mitochondrial-related
neuronal diseases.
Materials and Methods
Neuronal 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
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Journal of Cell Science 126 (10)
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 with
Earle’s salts (BME) containing 10% heat-inactivated FBS, 25 mM KCl, 2 mM
glutamine and 100 mg/ml gentamicin, and then plated onto 35 mm glass-bottom
dishes (MatTek, MA, USA), which were pre-coated with poly-L-lysine, at a
density of ,106 cells/ml (2 ml of cell suspension per dish). After incubating for
3 h, the medium was changed to NeurobasalTMA medium containing B-27
supplement, 2 mM GlutaMAXTM-I and 100 mg/ml gentamicin. Over 60% of the
cells showed a neuronal phenotype when the described procedure was followed.
To prepare primary cultures of cerebellar granule cells, the cerebella from 8 dayold Wistar rats were dissociated by trypsinising in 0.25% trypsin at 35 ˚C for
15 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 plated
onto 35 mm glass-bottomed dishes that were pre-coated with poly-L-lysine at a
density of 1.36106 cells/ml. Ten mM cytosine arabinoside was added 24 h after
plating 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 the
culture media and supplements were obtained from Invitrogen (Carlsbad, CA,
USA).
Journal of Cell Science
Plasmids
Mitochondrial KikGR1 (mito-KikGR1) was constructed by PCR amplification of
the mitochondrial targeting signal from pdsRed2-Mito (Human COXVIIIa,
nucleotides 597–683) and cloning in-frame between the EcoRI and HindIII sites
of 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). Plasmids
expressing shRNA targeted against Drp1, Miro1 and Miro2 were from
SABiosciences (Frederick, MD, USA). Wild-type (wt) and dominant-negative
Mfn2DTM were generous gifts from Dr S. Hirose (Honda et al., 2005), Drp1 was
from 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. Aspenström (Fransson et al., 2003), Tau was from Dr
G. 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 using
LipofectamineTM 2000 (Invitrogen). Briefly, conditioned medium was collected
and 120 ml of Opti-MEMH I medium containing 2% LipofectamineTM 2000 and
1 mg of total DNA (1 mg of mito-KikumeGR1 in the control; 0.33 mg of mitoKikumeGR1 and 0.67 mg of the desired DNA in the other groups) were added
directly to cells grown on 35 mm glass-bottomed dishes, and the cells were then
incubated 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 granular
neurons) NeurobasalTM medium was added per dish. The cells were then cultured
for 3–4 days to enable expression of the transfected DNA with the exception of
120Q Htt (4–5 days), Tau wt (5–6 days) and Miro shRNA (8 days). During
acquisition, the cells were maintained in Krebs–Ringer solution supplemented with
calcium (1 mM) and glucose (15 mM).
Immunohistochemistry
Neurons were fixed using 4% paraformaldehyde solution in NeurobasalTMA
containing 5% sucrose for 10 min at 37 ˚C. Fixed cells were permeabilised using
0.3% Triton X-100 in PBS for 5 min and then blocked using 10% normal goat
serum and 3% BSA for 60 min at room temperature. The neurons were then
incubated with the primary antibodies mouse anti-FLAG (1:500, F1804, SigmaAldrich), rabbit anti-Mfn2 (1:100, ab50838, Abcam, USA), rabbit anti-TTC11
(1:100, ab71498, Abcam), rabbit anti-Myc (1:500, ab9106, Abcam), mouse antiDNML (1:250, ab56788, Abcam), rabbit anti-RHOT1 (1:50, HPA010687, SigmaAldrich, Germany), mouse anti-DRPLA-35Q (1:10, MW2, Developmental Studies
Hybridoma Bank at the University of Iowa, USA), or mouse anti-Tau (1:50, 5A6,
Developmental Studies Hybridoma Bank) in the presence of 3% normal goat
serum at 4 ˚C for 48 h. After washing, the cells were further incubated with
respective Alexa-Fluor-488- or Alexa-Fluor-594-conjugated secondary antibodies
at room temperature for 1 h and subsequently examined using confocal
microscopy.
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 on
ice. 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 probed
overnight 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 Group
Inc.). 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 (Media
Cybernetics, Bethesda, MD).
Image acquisition
A laser scanning confocal microscope (LSM 510 Duo, Zeiss) equipped with a LCI
Plan-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 emission
filters. 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 five
mitochondria 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 a
561-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 fusion
events, 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. For
colocalisation 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 and
then separated using a BP465–510 filter.
Image processing and analysis
The fate of all photoactivated mitochondria was followed throughout the timelapse 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 to
analyse fusion and fission cycle parameters, length dependency, and for twin
analysis. Mitochondria were further tracked for motility analysis using Retrack
version 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 were
performed 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-activated
mitochondria) 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 to
compare 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 different
from the expected distribution. P-values ,0.05 were considered statistically
significant.
Principles of the mitochondrial fusion and fission cycle
Acknowledgements
We thank Drs S. Hirose, N. Nakamura, E. Bampton, J.-C. Martinou,
A. van der Bliek, G. Szabadkai, A. Matus, P. Aspenström, A.
Fransson, G. Johnson and L. Hasholt for providing the plasmids. We
also thank Dr Miriam A. Hickey for her assistance with proofreading.
Author contributions
M.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., and
A.K. analyzed data; M.C., D.S., V.V. and A.K. wrote the paper.
Funding
This research was supported by an institutional research funding
grant from the Estonian Research Council [grant number IUT2-5 to
A.K.]; the Estonian Science Foundation [grant numbers 7991 to
A.K and 7175, 8810 to D.S.]; the European Community [grant
number 205773 to A.K.]; the European Regional Development
Fund grant number [grant number 3.2.0101.08-0008 to A.K.]; the
Estonian–French research program Parrot [to A.K. and V.V]; and
Mobilitas [grant number MJD35 to M.C.].
Supplementary material available online at
http://jcs.biologists.org/lookup/suppl/doi:10.1242/jcs.118844/-/DC1
Journal of Cell Science
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