Miro proteins coordinate microtubule‐ and actin‐dependent mitochondrial transport and distribution
2018; Springer Nature; Volume: 37; Issue: 3 Linguagem: Inglês
10.15252/embj.201696380
ISSN1460-2075
AutoresGuillermo López‐Doménech, Christian Covill‐Cooke, Davor Ivankovic, Els F. Halff, David F. Sheehan, Rosalind Norkett, Nicol Birsa, Josef T. Kittler,
Tópico(s)Microtubule and mitosis dynamics
ResumoArticle8 January 2018Open Access Source DataTransparent process Miro proteins coordinate microtubule- and actin-dependent mitochondrial transport and distribution Guillermo López-Doménech Guillermo López-Doménech orcid.org/0000-0002-3114-2082 Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK Search for more papers by this author Christian Covill-Cooke Christian Covill-Cooke Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK Search for more papers by this author Davor Ivankovic Davor Ivankovic Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK Search for more papers by this author Els F Halff Els F Halff Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK Search for more papers by this author David F Sheehan David F Sheehan Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK Search for more papers by this author Rosalind Norkett Rosalind Norkett Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK Search for more papers by this author Nicol Birsa Nicol Birsa Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK Search for more papers by this author Josef T Kittler Corresponding Author Josef T Kittler [email protected] orcid.org/0000-0002-3437-9456 Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK Search for more papers by this author Guillermo López-Doménech Guillermo López-Doménech orcid.org/0000-0002-3114-2082 Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK Search for more papers by this author Christian Covill-Cooke Christian Covill-Cooke Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK Search for more papers by this author Davor Ivankovic Davor Ivankovic Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK Search for more papers by this author Els F Halff Els F Halff Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK Search for more papers by this author David F Sheehan David F Sheehan Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK Search for more papers by this author Rosalind Norkett Rosalind Norkett Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK Search for more papers by this author Nicol Birsa Nicol Birsa Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK Search for more papers by this author Josef T Kittler Corresponding Author Josef T Kittler [email protected] orcid.org/0000-0002-3437-9456 Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK Search for more papers by this author Author Information Guillermo López-Doménech1, Christian Covill-Cooke1, Davor Ivankovic1, Els F Halff1, David F Sheehan1, Rosalind Norkett1, Nicol Birsa1 and Josef T Kittler *,1 1Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK *Corresponding author. Tel: +44 (0) 2076793218; E-mail: [email protected] The EMBO Journal (2018)37:321-336https://doi.org/10.15252/embj.201696380 PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract In the current model of mitochondrial trafficking, Miro1 and Miro2 Rho-GTPases regulate mitochondrial transport along microtubules by linking mitochondria to kinesin and dynein motors. By generating Miro1/2 double-knockout mouse embryos and single- and double-knockout embryonic fibroblasts, we demonstrate the essential and non-redundant roles of Miro proteins for embryonic development and subcellular mitochondrial distribution. Unexpectedly, the TRAK1 and TRAK2 motor protein adaptors can still localise to the outer mitochondrial membrane to drive anterograde mitochondrial motility in Miro1/2 double-knockout cells. In contrast, we show that TRAK2-mediated retrograde mitochondrial transport is Miro1-dependent. Interestingly, we find that Miro is critical for recruiting and stabilising the mitochondrial myosin Myo19 on the mitochondria for coupling mitochondria to the actin cytoskeleton. Moreover, Miro depletion during PINK1/Parkin-dependent mitophagy can also drive a loss of mitochondrial Myo19 upon mitochondrial damage. Finally, aberrant positioning of mitochondria in Miro1/2 double-knockout cells leads to disruption of correct mitochondrial segregation during mitosis. Thus, Miro proteins can fine-tune actin- and tubulin-dependent mitochondrial motility and positioning, to regulate key cellular functions such as cell proliferation. Synopsis Miro1 and Miro2 coordinate specific and overlapping functions to regulate microtubule- and actin-dependent mitochondrial trafficking. This coordination is critical to ensure correct mitochondrial segregation during cell division. Miro proteins are differentially required in different stages of embryonic development. Miro proteins are not essential for TRAK/kinesin-mediated anterograde mitochondrial movement. Miro1 regulates TRAK2-dependent mitochondrial retrograde transport. Miro proteins recruit and stabilize mitochondrial myosin Myo19 on the outer mitochondrial membrane to mediate actin-based mitochondrial movements. Miro proteins coordinate tubulin- and actin-mediated mitochondrial movement to regulate equal segregation of mitochondria during mitosis. Introduction Mitochondria are critical for ATP provision and play other essential roles in cells such as buffering calcium and lipid synthesis (MacAskill & Kittler, 2010; Sheng & Cai, 2012; Mishra & Chan, 2014). The tight regulation of mitochondrial transport and distribution is therefore crucial as it enables mitochondria to be delivered and localised to areas where they are needed. In order for mitochondria to move around the cell, they need to be coupled to motor proteins. Long-range mitochondrial transport is primarily mediated by the coupling of mitochondria to microtubule motors (kinesins and dynein), whereas the actin cytoskeleton and its associated myosin motors, notably Myosin-19 (Myo19), can mediate shorter-range mitochondrial movement and actin-dependent mitochondrial anchoring (Morris & Hollenbeck, 1995; Chada & Hollenbeck, 2003; Hirokawa & Takemura, 2005; Quintero et al, 2009). However, the regulatory overlap between the pathways of microtubule- and actin-dependent mitochondrial trafficking and positioning and its impact on key cellular functions remain poorly understood. The outer mitochondrial membrane (OMM) Miro (mitochondrial Rho) GTPases and the TRAK motor adaptors have emerged as key regulators of mitochondrial trafficking and distribution by coupling mitochondria to the kinesin- and dynein-dependent microtubule transport pathways (Stowers et al, 2002; Fransson et al, 2006; Birsa et al, 2013; van Spronsen et al, 2013). Miro proteins have a C-terminal transmembrane domain for OMM targeting and two GTPase domains flanking two Ca2+-sensing EF-hand domains (Birsa et al, 2013; Devine et al, 2016). The prevailing model proposes that Miro proteins regulate trafficking by acting as the essential receptors for mitochondrial recruitment of the TRAK adaptors to drive kinesin- and dynein-mediated movements (MacAskill & Kittler, 2010; Saxton & Hollenbeck, 2012; Schwarz, 2013; Maeder et al, 2014; Mishra & Chan, 2014; Sheng, 2014). Miro proteins are also important targets of Parkinson's disease associated mitophagy pathway, driven by the kinase PINK1 (PTEN-induced putative kinase 1) and the ubiquitin ligase Parkin, which work together to degrade damaged mitochondria (Youle & Narendra, 2011; Covill-Cooke et al, 2017). Upon mitochondrial damage, Miro is rapidly ubiquitinated and depleted to block the microtubule-dependent transport of damaged mitochondria (Wang et al, 2011; Birsa et al, 2014). In mammals, two Miro family members exist, Miro1 and Miro2, with 60% sequence similarity, but little is known regarding their specific roles in regulating mitochondrial dynamics. Moreover, whether Miro proteins are additionally involved in coordinating myosin motors and actin-dependent positioning of healthy or damaged mitochondria remains unclear. Correct mitochondrial positioning within cells has emerged as critical for many key cellular processes including cell division, migration, signalling and survival (Youle & van der Bliek, 2012; Mishra & Chan, 2014; Morlino et al, 2014). The symmetric partitioning of mitochondria through both actin- and microtubule-dependent processes has recently been shown to be important for cell division (Rohn et al, 2014; Chung et al, 2016). Through the microtubule binding protein CENPF, Miro1 can promote mitochondrial redistribution following cell division (Kanfer et al, 2015). However, the role of Miro proteins for symmetric partitioning of mitochondria to daughter cells remains unclear. Here, we use mouse knockout (KO) approaches to generate Miro KO embryos and mouse embryonic fibroblasts (MEFs) for Miro1, Miro2 or both proteins, allowing a detailed characterisation of their roles in regulating mitochondrial trafficking and motor adaptor recruitment. Using micropatterned substrates to normalise cell size, we dissect the different roles of Miro1 and Miro2 in mediating mitochondrial distribution. Unexpectedly, we find TRAK proteins can still localise to mitochondria in the complete absence of Miro, while Myo19 is critically dependent on Miro for its stability on the OMM. In addition, loss of both Miro proteins in Miro double-knockout (MiroDKO) cells leads to defects in mitosis and mitochondrial segregation to daughter cells. Our work supports a revised model for Miro function in regulating both microtubule- and actin-dependent mitochondrial positioning to regulate key cellular functions. Results Differential requirements for Miro1 and Miro2 during embryonic development We recently showed that Miro1 knockout (Miro1KO) animals die perinatally while Miro2 knockout (Miro2KO) animals were found to develop normally (Fig EV1A) and be viable until adulthood (Lopez-Domenech et al, 2016). Due to the high homology between Miro1 and Miro2 (Fransson et al, 2003), it is conceivable that both proteins show some degree of compensation, and thus, we wanted to investigate the consequences of deleting both Miro proteins on embryonic development. To this end, we crossed animals that were heterozygous for both genes (Miro1+/−; Miro2+/− × Miro1+/−; Miro2+/−) and analysed the litters at different stages (Table EV1). We observed that embryos harbouring only one copy of Miro2 (Miro1KO/Miro2het) were present until P0 but were not viable beyond this stage (Table EV1), like Miro1KO animals (Nguyen et al, 2014; Lopez-Domenech et al, 2016). In contrast, embryos with only one allele of Miro1 (Miro1het/Miro2KO) were only found to be viable until E12.5, indicating that only one copy of Miro1 is not enough to compensate the lack of Miro2 beyond E12.5 (Table EV1 and Fig 1A–C). Importantly, MiroDKO embryos were only found up to embryonic stage 10.5 (E10.5) and presented reduced size and developmental defects such as uncompleted neural tube closure (Fig 1D). Interestingly, yolk sac capillaries were absent, suggesting that the development of MiroDKO embryos stopped at a stage prior to vascularisation (Fig 1E). Indeed, MiroDKO embryos at an earlier stage (E8.5) were indistinguishable from their littermates (Table EV1). Click here to expand this figure. Figure EV1. Role of Miro1 and Miro2 proteins during mouse embryonic development A. Miro2KO embryos develop normally and are undistinguishable from WT embryos. Image of Miro2KO embryo is taken from Fig 1A. B, C. Quantification of Miro1 and Miro2 protein levels in E12.5 and E10.5 lysates. Miro1 and Miro2 gene doses are stated in the x-axis. (B) At E10.5, Miro1 protein shows a ˜30% increase in Miro2KO embryos. (C) Miro proteins do not show compensatory mechanisms in E12.5 embryos. All samples were obtained from six pregnant females (at E12.5) and from five pregnant females (at E10.5) and loaded together to allow comparisons (shown in Fig 1F and G). Error bars represent s.e.m. Statistical significance: *P < 0.05. Download figure Download PowerPoint Figure 1. Miro1 and Miro2 function is critical during early embryonic development A–C. Miro1het/Miro2KO embryos (with only one copy of Miro1) are not viable beyond day E12.5 of gestation as opposed to Miro2KO embryos (with two copies of Miro1). At E16.5 (A) and E14.5 (B), all embryos that were identified post hoc as heterozygotes for Miro1 and knock out for Miro2 were found in advanced state of reabsorption. At E12.5 (C), half of the embryos of this genotype were found to be indistinguishable from WT control animals. A viable embryo was selected as a control animal for comparison. See also Table EV1. D, E. MiroDKO embryos were found to be not viable from E10.5. (D) At this stage, they were very small and presented malformations and oedema in head and viscera compared with viable littermates. Neural tube closure was incomplete (arrowheads). (E) Further observation showed that MiroDKO embryos at E10.5 failed in generating the vasculature that irrigates the yolk sac (arrows). F. Western blot analysis of E10.5 heads (or whole body for MiroDKO embryos) showing the specificity of the different bands recognised by the antibody (anti-Miro1 from Atlas) and the complete depletion of Miro1 and Miro2 proteins in MiroDKO embryos. G. Western blot analysis of brains from E12.5 embryos showing that the protein levels correlate with the genetic dosage of Miro1 and Miro2. Quantification of Miro1 and Miro2 protein levels provided in Fig EV1. Source data are available online for this figure. Source Data for Figure 1 [embj201696380-sup-0008-SDataFig1.pdf] Download figure Download PowerPoint Thus, Miro1 function seems to be critical in late development, probably allowing the inflation of the lungs in neonates, a function that cannot be compensated by Miro2 (Nguyen et al, 2014; Lopez-Domenech et al, 2016). Conversely, two copies of Miro1 are necessary to overcome early stages of development by compensating a function of Miro2 that seems critical at early stages, around E12.5 (Fig 1A–C). Consistent with this view, we observed an increase in Miro1 protein levels in Miro2KO embryos at E10.5, suggesting that high levels of Miro1 protein may compensate the lack of Miro2 at this stage (Figs 1F and EV1B). Interestingly, no compensatory mechanisms seem to be in place at a later time point (E12.5) where Miro1 and Miro2 protein levels closely correlate with genetic dose (Figs 1G and EV1C). Miro1 and Miro2 cooperate to regulate key aspects of mitochondrial morphology and distribution To study the specific roles of Miro1 and Miro2 for mitochondrial morphology and distribution, we generated mouse embryonic fibroblast (MEF) cell lines from E8.5 embryos of all the different genetic outcomes of Miro1+/−; Miro2+/− × Miro1+/−; Miro2+/− crosses. The genotype of the different cell lines (confirmed by PCR amplification; Fig EV2A) correlated with the protein levels of Miro1 and Miro2 (Fig EV2B). No major change in protein content was observed across these cell lines in Western blots against actin, β-tubulin, the mitochondrial markers Tom20 or COX IV or the endoplasmic reticulum (ER) marker protein disulphide isomerase (PDI; Fig EV2B). To determine the impact on mitochondrial morphology of Miro1, Miro2 or Miro1/2 deletion, we imaged MitoTracker-labelled mitochondria in the different cell lines. We observed that Miro1KO and Miro2KO cells showed indistinguishable mitochondrial morphologies from those found in WT cells, whereas MiroDKO cells showed an increase in the fraction of cells with short and rounded mitochondria and a decrease in the fraction of cells with long, tubular and interconnected mitochondria (Fig 2A and B). Despite an impact on mitochondrial morphology, the maximal respiratory capacity of the electron transfer system (ETS), the normalised respiration flux (R/E) and the maximum capacity of complex IV (C-IV) were not significantly different among all genotypes either using glucose as a substrate (Fig EV2C) or with a non-glycolytic substrate (Fig EV2D), suggesting that Miro proteins are not critical in regulating respiration rate or overall energetic metabolic state of the cell. Click here to expand this figure. Figure EV2. Genetic and metabolic characterization of Miro1 and Miro2 single and double knockout MEF cell lines A, B. Genetic (A) and protein (B) characterisation of all MEF cell lines obtained from E8.5 embryos from matings between double heterozygote (Miro1het/Miro2het) animals. C. Respiration flux of the different MEF cell lines from the main genotypes in standard growing conditions (1,000 mg/l glucose). Units are picomoles of O2 per second per million cells. Values of electron transfer system (ETS) capacity, routine control ratio (R/ETS) and normalised complex IV activity ratio (C-IV/ETS) are given. Data obtained from three independent experiments (n = 3; ANOVA-NK). In each experiment, respiratory activity was analysed from two different cell lines per genotype. Error bars represent s.e.m. D. Respiratory flux of the different MEF cell lines growing in galactose (15 mM)-supplemented glucose-free medium. Units are picomoles of O2 per second per million cells. Values of electron transfer system (ETS) capacity, routine control ratio (R/ETS) and normalised complex IV activity ratio (C-IV/ETS) are given. Data obtained from four independent experiments (n = 4; ANOVA-NK). Error bars represent s.e.m. Source data are available online for this figure. Download figure Download PowerPoint Figure 2. Characterisation of mitochondrial morphology and distribution in mouse embryonic fibroblasts (MEFs) A, B. Analysis of mitochondrial morphology in Miro knockout MEFs. Examples of mitochondrial morphology in WT and MiroDKO cells (A). Cells were scored depending on the morphology of the majority of their mitochondrial population as elongated, short or intermediate. Graph in (B) shows that MiroDKO MEF cells exhibited more often short and less elongated mitochondria. Data pooled from three independent experiments (n = 3; ANOVA-NK). In each experiment, mitochondrial morphology was analysed from two different MEF cell lines per genotype. C. Confocal images showing cellular morphology (phalloidin, left panels) and mitochondrial distribution (MitoTracker, middle panels) from cells growing in "Y"-shaped micropatterns from the main Miro knockout cell lines. Mitochondrial distribution differences between cell lines are evident when constructing a reference cell (right panel and boxed detail) or "heat map" by projecting the signal from 10 cells from the same genotype. D. The cumulative distribution of mitochondrial signal or Mitochondrial Probability Map (MPM) is plotted for the different genotypes. A displacement to the left compared to WT indicates that mitochondrial signal is accumulated towards the centre of the cell. The grey dotted line represents the theoretical distribution of a homogeneously distributed signal. Analysis was performed from at least three independent experiments (number of experiments: WT 9; Miro1KO 6; Miro2KO 6; Miro1KO/Miro2het 3; Miro1het/Miro2KO 4; MiroDKO 9; ANOVA-NK) where at least 20 cells were analysed per genotype and experiment. Two different cell lines were used per genotype. E. Graph showing the calculated Mito95 values (95th percentile) which represent the distance from the cell centre at which 95% of the mitochondrial signal is found. Analysis was performed from at least three independent experiments (number of experiments: WT 9; Miro1KO 6; Miro2KO 6; Miro1KO/Miro2het 3; Miro1het/Miro2KO 4; MiroDKO 9; ANOVA-NK) where at least 20 cells were analysed per genotype and experiment. Two different cell lines were used per genotype. Data information: Error bars represent s.e.m. Statistical significance: *P < 0.05 and ***P < 0.001 compared to WT; ##P < 0.01 and ###P < 0.001 compared to MiroDKO. Download figure Download PowerPoint We noted that mitochondria in Miro1KO cells were accumulated near the nucleus and seemed unable to reach distal regions when compared to their WT controls in accordance with previous reports (Nguyen et al, 2014), an effect that was greatly accentuated in MiroDKO cells. To determine mitochondrial distribution in the different MEF lines with high accuracy, we controlled cell size and shape using printed micropattern adhesive cell substrates (see Materials and Methods; Fig EV3A). This allows quantification of cellular parameters over many cells with an identical size and shape, greatly reducing the large inherent variability of MEF cell morphology and, hence, mitochondrial distribution (Chevrollier et al, 2012; Fig 2C). To measure distribution of the mitochondrial network, we performed a Sholl-based analysis of mitochondrial signal (Lopez-Domenech et al, 2016; Fig EV3B and C) and plotted the cumulative distribution of mitochondrial signal as a function of distance from the cell centre or Mitochondrial Probability Map (MPM; Fig 2D). Using this approach, we could define the distance from the cell centre where different proportions of mitochondrial mass are found (Mito50 or 50th percentile; Mito90 or 90th percentile and Mito95 or 95th percentile) across the different genotypes (Figs 2E and EV3D–F). Using the Mito95 value, which showed more accuracy at describing differences in mitochondrial distribution, we observed that mitochondria in the Miro1KO cell lines showed a clear shift to the left in the MPM and a decreased Mito95 value, indicating that mitochondria were significantly more concentrated in proximal regions of the cell compared to either WT or Miro2KO cells (Fig 2C–E). Interestingly, MiroDKO cells showed a substantially more accentuated perinuclear accumulation of mitochondria when compared to Miro1KO cells, indicating that Miro2 also plays an important non-redundant role in regulating mitochondrial distribution [Fig 2C–E; Mito95: WT 22.16 ± 0.20, Miro1KO 19.54 ± 0.43, Miro2KO 21.43 ± 0.26 and MiroDKO 17.56 ± 0.27; ANOVA and post hoc Newman–Keuls (ANOVA-NK)]. Interestingly, MEF cell lines with only one allele of Miro1 or only one allele of Miro2 (Miro1het/Miro2KO or Miro1KO/Miro2het, respectively) presented a mitochondrial distribution indistinguishable from that of MiroDKO cells (Figs 2D and E, and EV3C, E and F), indicating that only one copy of Miro1 or Miro2 is not sufficient to maintain an appropriate mitochondrial distribution in the proximo-distal axis. In contrast, the distribution of the nucleus was unaffected in MiroDKO cells, indicating that the altered mitochondrial distribution in the different genotypes is not due to an altered position of the nucleus (Fig EV3G). Thus, Miro1 and Miro2 work together in coordinating the overall distribution of the mitochondrial network within cells. Click here to expand this figure. Figure EV3. Representation and quantification of mitochondrial distribution in the different MEF cell lines grown on micropatterned substrates A. MEF cells were seeded onto "Y"-shaped adhesive micropatterns restricting their growth to an obligate size and shape (triangular) to keep it constant over many cells. B, C. Schematic representation of Sholl analysis of mitochondrial signal (B). Concentric circles growing in diameter from the centre of the cell were used to obtain normalised profiles of mitochondrial distribution (C) in the proximo-distal axis of cells (centre to periphery). Grey dotted line represents the theoretical distribution of a homogeneously distributed signal. The cumulative distribution of these profiles or Mitochondrial Probability Map (MPM) was used to represent the distribution of mitochondria throughout the paper. D. Mito% values represent the distance from the centre of the cell at which a given fraction of mitochondria is found. All Mito% values were calculated by interpolation of the mitochondrial signal for each individual cell. E, F. Plotted Mito50 (median or 50th percentile) (E) and Mito90 (90th percentile) (F) values of the distribution of mitochondrial signal from the different genotypes. Data were obtained from at least three independent experiments (number of experiments: WT 9; Miro1KO 6; Miro2KO 6; Miro1KO/Miro2het 3; Miro1het/Miro2KO 4; MiroDKO 9; ANOVA-NK) where at least 20 cells were analysed per genotype and experiment. G. Nuc95 value or distance from the centre of the cell where 95% of nuclear signal is found was calculated and plotted from WT and MiroDKO cells. Data were obtained from three independent experiments. Two different cell lines were used per each genotype. Data information: Error bars represent s.e.m. Significance: **P < 0.01 and ***P < 0.001. Download figure Download PowerPoint Miro1 and Miro2 differentially regulate mitochondrial transport Miro1 is a key regulator of mitochondrial trafficking in neurons (Macaskill et al, 2009; Wang & Schwarz, 2009; Lopez-Domenech et al, 2016) and other cell types (Saotome et al, 2008; Morlino et al, 2014; Stephen et al, 2015; Schuler et al, 2017). The prevailing model of Miro function is that it acts as the essential receptor for recruiting the motor/adaptor complexes to the mitochondria to drive mitochondrial transport along the microtubule tracks (MacAskill & Kittler, 2010; Saxton & Hollenbeck, 2012; Schwarz, 2013; Maeder et al, 2014; Sheng, 2014). However, whether Miro1 and Miro2 have overlapping or complementary functions and whether the total absence of Miro could still permit any mitochondrial transport in mammalian cells have not been addressed. To address this question, we performed time-lapse imaging experiments in MEFs expressing mitochondrially targeted DsRed2 (MtDsRed) and determined mitochondrial displacement. Miro1KO and Miro2KO cells showed a significant reduction in mitochondrial displacements (the percentage of mitochondria that changed their position over a 10-s period) compared to WT. This decrease was even more drastic in MiroDKO MEFs (Fig 3A and B, and Movie EV1; mitochondrial displacement (% of area): WT 15.7 ± 0.8; Miro1KO 10.7 ± 0.3; Miro2KO 11.8 ± 0.6 and MiroDKO 8.4 ± 0.3, P < 0.05, ANOVA-NK), demonstrating that Miro1 and Miro2 can both regulate aspects of mitochondrial trafficking. In contrast, lysosomal displacement was unaffected in MiroDKO MEFs compared to WT (Appendix Fig S1A and B, and Movie EV2), indicating that the transport defects are specific to mitochondrial transport. Figure 3. Mitochondrial movement is reduced but not completely abolished in MiroDKO MEFs A, B. Mitochondrial displacement is reduced in all genotypes compared to WT. (A) Stills from movies showing the mitochondrial compartment from WT and MiroDKO MEFs at time = 0 (magenta) and the new area occupied by mitochondria 10 s later (mitochondrial area at t = 10 s − mitochondrial area at t = 0) (green). (B) Mitochondrial displacement at a given time point (tn) was calculated by subtracting mitochondrial area at two different time points separated by 10 s and normalised to total mitochondrial area from that given time point: (tn+10 − tn)/tn. The final displacement value was averaged over the 59 pairs of frames for each movie (59 pairs over a 61 frame movie). Data obtained from the indicated number of cells from six different experiments (n = number of cells; ANOVA-NK). C, D. Mitochondrial transport on microtubule tracks is not completely abolished in MiroDKO MEFs. The number of tubulin-dependent mitochondrial runs (C) was equally decreased (but not abolished) in Miro1KO and in MiroDKO cells but unaffected in Miro2KO cells when compared to WT (n = number of cells; ANOVA-NK; data obtained from the same cells as in B). Disrupting microtubules with vinblastine abolished mitochondrial runs. Data for vinblastine treatment obtained from three independent experiments (n = number of cells; WT = 14, Miro1KO = 6; Miro2KO = 6; MiroDKO = 14; t-test inside genotypes). (D) Stills from the movies quantified in (A) and (B) showing fast and directed mitochondrial movements (yellow arrows) in MiroDKO cells. E–G. TRAK1, TRAK2 and motor complex components are recruited to the mitochondria even in the absence of Miro. (E) Western blots showing that TRAK1, TRAK2 and kinesin heavy chain, P150/Glued and the dynein intermediate chain can be found in purified mitochondrial fractions even in MiroDKO MEFs (I: input; M: mitochondrial fraction; C: cytoplasmic fraction). (F) Quantification of mitochondrial enrichment (mitochondrial signal/cytoplasmic signal) of the indicated adaptor/motor components and normalised to WT. Data compiled from four independent subcellular fractionations (n = number of fractionations; ANOVA-NK). (G) Confocal micrographs showing that exogenous TRAK1GFP and TRAK2GFP (green) are also enriched in mitochondria (magenta) in MiroDKO cells. Data information: Error bars represent s.e.m. Statistical significance: *P < 0.05 and ***P < 0.001; ###P < 0.001. Source data are available online for this figure. Source Data for Figure 3 [embj201696380-sup-0009-SDataFig3.pdf] Download figure Download PowerPoint
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