Cristae undergo continuous cycles of membrane remodelling in a MICOS ‐dependent manner
2020; Springer Nature; Volume: 21; Issue: 3 Linguagem: Inglês
10.15252/embr.201949776
ISSN1469-3178
AutoresArun Kumar Kondadi, Ruchika Anand, Sebastian Hänsch, Jennifer Urbach, Thomas Zobel, Dane M. Wolf, Mayuko Segawa, Marc Liesa, Orian S. Shirihai, Stefanie Weidtkamp‐Peters, Andreas S. Reichert,
Tópico(s)ATP Synthase and ATPases Research
ResumoArticle18 February 2020Open Access Transparent process Cristae undergo continuous cycles of membrane remodelling in a MICOS-dependent manner Arun Kumar Kondadi Arun Kumar Kondadi orcid.org/0000-0002-5888-7834 Institute of Biochemistry and Molecular Biology I, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany Search for more papers by this author Ruchika Anand Ruchika Anand orcid.org/0000-0001-7337-6007 Institute of Biochemistry and Molecular Biology I, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany Search for more papers by this author Sebastian Hänsch Sebastian Hänsch Faculty of Mathematics and Natural Sciences, Center for Advanced Imaging, Heinrich Heine University Düsseldorf, Düsseldorf, Germany Search for more papers by this author Jennifer Urbach Jennifer Urbach orcid.org/0000-0002-6484-4160 Institute of Biochemistry and Molecular Biology I, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany Search for more papers by this author Thomas Zobel Thomas Zobel Faculty of Mathematics and Natural Sciences, Center for Advanced Imaging, Heinrich Heine University Düsseldorf, Düsseldorf, Germany Search for more papers by this author Dane M Wolf Dane M Wolf Department of Medicine, Nutrition and Metabolism Section, Evans Biomedical Research Center, Boston University School of Medicine, Boston, MA, USA Division of Endocrinology, Department of Medicine, Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA Search for more papers by this author Mayuko Segawa Mayuko Segawa Division of Endocrinology, Department of Medicine, Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA Search for more papers by this author Marc Liesa Marc Liesa orcid.org/0000-0002-5909-8570 Division of Endocrinology, Department of Medicine, Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA Molecular Biology Institute, University of California Los Angeles, Los Angeles, CA, USA Search for more papers by this author Orian S Shirihai Orian S Shirihai orcid.org/0000-0001-8466-3431 Department of Medicine, Nutrition and Metabolism Section, Evans Biomedical Research Center, Boston University School of Medicine, Boston, MA, USA Division of Endocrinology, Department of Medicine, Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA Search for more papers by this author Stefanie Weidtkamp-Peters Stefanie Weidtkamp-Peters Faculty of Mathematics and Natural Sciences, Center for Advanced Imaging, Heinrich Heine University Düsseldorf, Düsseldorf, Germany Search for more papers by this author Andreas S Reichert Corresponding Author Andreas S Reichert [email protected] orcid.org/0000-0001-9340-3113 Institute of Biochemistry and Molecular Biology I, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany Search for more papers by this author Arun Kumar Kondadi Arun Kumar Kondadi orcid.org/0000-0002-5888-7834 Institute of Biochemistry and Molecular Biology I, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany Search for more papers by this author Ruchika Anand Ruchika Anand orcid.org/0000-0001-7337-6007 Institute of Biochemistry and Molecular Biology I, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany Search for more papers by this author Sebastian Hänsch Sebastian Hänsch Faculty of Mathematics and Natural Sciences, Center for Advanced Imaging, Heinrich Heine University Düsseldorf, Düsseldorf, Germany Search for more papers by this author Jennifer Urbach Jennifer Urbach orcid.org/0000-0002-6484-4160 Institute of Biochemistry and Molecular Biology I, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany Search for more papers by this author Thomas Zobel Thomas Zobel Faculty of Mathematics and Natural Sciences, Center for Advanced Imaging, Heinrich Heine University Düsseldorf, Düsseldorf, Germany Search for more papers by this author Dane M Wolf Dane M Wolf Department of Medicine, Nutrition and Metabolism Section, Evans Biomedical Research Center, Boston University School of Medicine, Boston, MA, USA Division of Endocrinology, Department of Medicine, Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA Search for more papers by this author Mayuko Segawa Mayuko Segawa Division of Endocrinology, Department of Medicine, Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA Search for more papers by this author Marc Liesa Marc Liesa orcid.org/0000-0002-5909-8570 Division of Endocrinology, Department of Medicine, Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA Molecular Biology Institute, University of California Los Angeles, Los Angeles, CA, USA Search for more papers by this author Orian S Shirihai Orian S Shirihai orcid.org/0000-0001-8466-3431 Department of Medicine, Nutrition and Metabolism Section, Evans Biomedical Research Center, Boston University School of Medicine, Boston, MA, USA Division of Endocrinology, Department of Medicine, Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA Search for more papers by this author Stefanie Weidtkamp-Peters Stefanie Weidtkamp-Peters Faculty of Mathematics and Natural Sciences, Center for Advanced Imaging, Heinrich Heine University Düsseldorf, Düsseldorf, Germany Search for more papers by this author Andreas S Reichert Corresponding Author Andreas S Reichert [email protected] orcid.org/0000-0001-9340-3113 Institute of Biochemistry and Molecular Biology I, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany Search for more papers by this author Author Information Arun Kumar Kondadi1,†, Ruchika Anand1,†, Sebastian Hänsch2, Jennifer Urbach1, Thomas Zobel2,6, Dane M Wolf3,4,‡, Mayuko Segawa4,‡, Marc Liesa4,5, Orian S Shirihai3,4, Stefanie Weidtkamp-Peters2 and Andreas S Reichert *,1 1Institute of Biochemistry and Molecular Biology I, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany 2Faculty of Mathematics and Natural Sciences, Center for Advanced Imaging, Heinrich Heine University Düsseldorf, Düsseldorf, Germany 3Department of Medicine, Nutrition and Metabolism Section, Evans Biomedical Research Center, Boston University School of Medicine, Boston, MA, USA 4Division of Endocrinology, Department of Medicine, Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA 5Molecular Biology Institute, University of California Los Angeles, Los Angeles, CA, USA 6Present address: Münster Imaging Network, Cells in Motion Interfaculty Centre, Westfälische Wilhelms-Universität Münster, Münster, Germany † These first authors contributed equally to this work as first authors ‡ These coauthors contributed equally to this work *Corresponding author. Tel: +49 211 81 12707; Fax: +49 211 81 13029; E-mail: [email protected] EMBO Reports (2020)21:e49776https://doi.org/10.15252/embr.201949776 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 The mitochondrial inner membrane can reshape under different physiological conditions. How, at which frequency this occurs in living cells, and the molecular players involved are unknown. Here, we show using state-of-the-art live-cell stimulated emission depletion (STED) super-resolution nanoscopy that neighbouring crista junctions (CJs) dynamically appose and separate from each other in a reversible and balanced manner in human cells. Staining of cristae membranes (CM), using various protein markers or two lipophilic inner membrane-specific dyes, further revealed that cristae undergo continuous cycles of membrane remodelling. These events are accompanied by fluctuations of the membrane potential within distinct cristae over time. Both CJ and CM dynamics depended on MIC13 and occurred at similar timescales in the range of seconds. Our data further suggest that MIC60 acts as a docking platform promoting CJ and contact site formation. Overall, by employing advanced imaging techniques including fluorescence recovery after photobleaching (FRAP), single-particle tracking (SPT), live-cell STED and high-resolution Airyscan microscopy, we propose a model of CJ dynamics being mechanistically linked to CM remodelling representing cristae membrane fission and fusion events occurring within individual mitochondria. Synopsis Mitochondrial crista junctions and cristae membranes undergo continuous remodelling events in a MICOS-dependent manner. These findings, based on live-STED nanoscopy and complementary approaches, change the dogma of cristae being static invaginations of the inner membrane and open a novel, highly dynamic view on the internal structure of mitochondria. Crista junctions (CJs) and cristae membranes (CM) undergo dynamic remodelling at a time-scale of seconds in a reversible, balanced, and MICOS-dependent manner. MIC60 is the primary docking site for formation of the MICOS complex to ensure CJ formation in mammalian cells. The mitochondrial membrane potential is shown to dynamically fluctuate in distinct cristae, which is correlated to CM remodelling events. We propose a model of CJ-dynamics being mechanistically linked to CM remodelling representing cristae membrane fission and fusion events occurring within individual mitochondria. Introduction Mitochondria are vital organelles with key roles in energetics and metabolism of the cell. The ultrastructural morphology of this double-membrane-enclosed organelle is highly variable and altered in numerous human disorders 1, 2. The internal mitochondrial structure is characterized by invaginations of the inner membrane (IM) called cristae. The IM that closely remains apposed to the outer membrane (OM) is called the inner boundary membrane (IBM). The cristae membrane (CM) connects the IBM via a highly curved, circular or slit- or pore-like structures called crista junctions (CJs) 1, 3-7. CJs are structurally conserved with a diameter of 12–40 nm and were proposed to act as diffusion barriers for proteins or metabolites 8-11. Thus, the presence of CJs could create distinct mitochondrial subcompartments by separating IBM from CM and intermembrane space (IMS) from intracristal space (ICS). Indeed, the CM is enriched in proteins involved in oxidative phosphorylation (OXPHOS), mitochondrial protein synthesis or iron–sulphur cluster biogenesis, whereas the IBM mainly contains proteins involved in mitochondrial fusion and protein import 12. CJs could regulate bioenergetics by limiting the diffusion of ADP/ATP and affect the pH gradient across the IM 8-11. As early as 1966, isolated mitochondria were known to occur in different morphological states, condensed (matrix condensed, high ADP, state III) or an orthodox (matrix expanded, low ADP, state IV) state, depending on the bioenergetic status 13-15. Later, tomographic images of mitochondria undergoing this transition indicated that remodelling of the IM occurs in isolated mitochondria 10. Cristae exist in different shapes and sizes depending on the physiological, bioenergetic or developmental cues 1, 10, 16. Moreover, the general ability of cristae or CJs to dynamically remodel is well exemplified during apoptosis, where widening of CJs is observed, promoting cytochrome c release from the ICS into the cytosol 17, 18. However, molecular mechanisms for cristae and CJs remodelling in response to metabolic and physiological adaptations are not known. Aberrant and altered cristae are associated with several human diseases including neurodegeneration, cancer, diabetes and cardiomyopathies 1, 19, but their relevance to disease progression is unclear. The formation of CJs is likely to require an intricate partnership between phospholipids and scaffolding proteins 20-22. We identified that Fcj1 (formation of crista junction protein 1)/Mic60 resides preferentially at CJs in yeast, and its deletion leads to complete loss of CJs with cristae arranged as concentric stacks separate from the IBM. In addition, Fcj1/Mic60 and Su e/g (subunits of F1Fo-ATP synthase) act antagonistically to control F1Fo-ATP synthase oligomerization and thereby modulate formation of CJs and cristae tips 7. Several groups have identified a large oligomeric complex termed mitochondrial contact site and cristae organizing system (MICOS) which is required for the formation and maintenance of CJs and contact sites between IM and OM 23-25. The MICOS complex contains at least seven subunits in mammals: MIC10, MIC13, MIC19, MIC25, MIC26, MIC27 and MIC60 named after a uniform nomenclature 26. Mic60 and Mic10 are considered to be the core components of the MICOS complex in baker's yeast as their deletion causes complete loss of CJs. MIC60 has a binding interface for a variety of proteins including TOM complex, OPA1, SAM/TOB, Ugo1 (mammalian homolog SLC25A46), DnaJC11, CHCHD10, DISC1 (disrupted-in-schizophrenia 1) and is proposed to provide the scaffold for MICOS as well as contact between IM and OM 27-34. Mic10 contains conserved glycine motifs in its transmembrane domain that are crucial for MIC10 self-oligomerization and are required for the stability of CJs 35-37. Mic10 additionally interacts with the dimeric F1Fo-ATP synthase and promotes its oligomerization 38, 39. Both Mic60 and Mic10 have the capability to bend membranes 35, 40, 41. Using complexome profiling, we identified MIC26/APOO and MIC27/APOOL as bona fide subunits of the MICOS complex 42, 43. Depletion or overexpression of MIC26 or MIC27 led to altered cristae morphology and reduced respiration. MIC27 binds to cardiolipin, the signature lipid in mitochondria 42. The non-glycosylated form of MIC26 is a subunit of the MICOS complex, but not the glycosylated form 43. Recently, we and another group have discovered that MIC13/QIL1 is an essential component of the MICOS complex responsible for the formation of CJs 44, 45. Loss of MIC13 resulted in reduced levels of MIC10, MIC26 and MIC27, accompanied by impaired OXPHOS. The protein levels of MIC60, MIC19 and MIC25 remain unaltered, suggesting that MICOS comprises two subcomplexes: MIC60/25/19 and MIC10/13/26/27 with MIC13 acting as a bridge between both subcomplexes 44, 45. Altered levels of MICOS components and their interactors are associated with many human diseases such as epilepsy, Down syndrome, frontotemporal dementia–amyotrophic lateral sclerosis, optic atrophy, Parkinson's disease, diabetes and cardiomyopathy 2, 27, 46. Mutations in MIC60 have been found in Parkinson's disease 47. Mutations in MIC13/QIL1 lead to mitochondrial encephalopathy and hepatic dysfunction 48-51. Here, we studied cristae membrane remodelling in living cells and the role of MICOS complex in this context. To study systematically intramitochondrial dynamics of CJs and cristae, we devised a novel state-of-the-art method of live-cell STED super-resolution nanoscopy using the C-terminal SNAP-tagged versions of distinct mitochondrial proteins marking CJs and cristae. Within individual mitochondria MIC10- and MIC60-SNAP punctae marking CJs dynamically remodel to merge and split in a continuous and balanced manner. This occurred at a timescale of seconds and depends on the MICOS subunit MIC13. In conjunction, we observed that adjacent cristae marked by ATP5I-SNAP and COX8A-SNAP or by IM-specific dyes undergo repeated cycles of membrane remodelling in a similar timescale of seconds. Using different approaches, including live-cell STED after TMRM staining and photoactivation combined with high-resolution Airyscan fluorescence microscopy, we provide strong support that the spatial apposition between two adjacent cristae leads to an exchange of content and that cristae can transiently stay separated from other cristae or the IBM. Overall, by improved spatial (~60 nm) and temporal (~1.5–2.5 s) resolution using live-cell STED super-resolution nanoscopy in combination with the SNAP-tag technology and use of newly generated genetic cellular models lacking MICOS subunits, we resolved and characterized cristae membrane dynamics. Based on these findings, we propose a model linking CJ and CM dynamics and discuss the novel role of the MICOS complex and the physiological importance thereof. Results Mammalian MIC10 and MIC60 are required for cristae morphogenesis and cellular respiration MIC60 and MIC10 are the core subunits of the MICOS complex that are also evolutionarily well conserved 52, 53. To better understand the role of these subunits in mammalian cells, we obtained human MIC10 and MIC60 knockout (KO) HAP1 cells. MIC10 KO and MIC60 KO have 29-bp deletion in exon 1 and 10-bp deletion in exon 8, respectively, leading to a frameshift and subsequent loss of the respective proteins (Fig 1A). Analysis of electron micrographs from these cells revealed that CJs are virtually absent in MIC10 and MIC60 KO cells (Fig 1B and C). The cristae membrane (CM) appears as concentric rings detached from the IBM (Fig 1B), consistent with earlier observations in baker's yeast and mammalian cells 7, 23-25, 54, 55. In addition, the abundance of cristae per mitochondrial section is reduced (Fig 1D). While the knockout of MIC10 primarily causes a selective destabilization of the MICOS subcomplex comprising MIC13, MIC26 and MIC27, loss of MIC60 results in a clear destabilization of all subunits of the MICOS complex (Fig 1A), confirming its role as a main scaffolding subunit of MICOS. The basal and the maximal oxygen consumption rates of MIC10 and MIC60 KOs are significantly decreased compared to controls (Fig 1E and F), confirming the role of CJs in ensuring full bioenergetic capacity. Figure 1. MIC10 and MIC60 KO HAP1 cells show loss of crista junctions and impaired cellular respiration A. Western blot analysis of lysates from WT and MIC10 KO or MIC60 KO HAP1 cells. MIC10 KO cells show a drastic reduction in MIC13, MIC26 and MIC27 protein levels, while protein levels of other MICOS components remain unchanged. MIC60 KO cells show a drastic reduction in protein levels of all MICOS components. B. Representative electron micrographs of WT, MIC10 KO and MIC60 KO HAP1 cells. Scale bar 500 nm. C. Quantification of CJs per mitochondrial section from different mitochondria in WT, MIC10 and MIC60 KO HAP1 cells using EM represented as boxplots. Boxplots show median and interquartile range from 25 to 75 percentile, and whiskers represent minimum and maximum value. Data from n = 55–69 mitochondria (from two independent experiments) are shown as data points in the boxplots. ****P < 0.0001 (using unpaired Student's t-test). D. Quantification of cristae per mitochondrial section from different mitochondria in WT, MIC10 and MIC60 KO HAP1 cells using EM represented as boxplots. Boxplots show median and interquartile range from 25 to 75 percentile, and whiskers represent minimum and maximum value. Data from n = 55–69 mitochondria (from two independent experiments) are shown as data points in the boxplots. ****P < 0.0001 (using unpaired Student's t-test). E. Comparison of oxygen consumption rates (pmol O2/s, normalized for cell numbers by Hoechst staining) of basal, proton leak, maximum and non-mitochondrial respiration in WT and MIC10 KO cells obtained from three independent experiments. The data are normalized to basal respiration from HAP1 WT. Bar and error bar represent mean ± SEM from 3 independent experiments. *P = 0.034 for basal (using one-sample t-test) and *P = 0.018 for maximum respiration (using unpaired Student's t-test). F. Comparison of oxygen consumption rates (pmol O2/s, normalized for cell numbers by Hoechst staining) of basal, proton leak, maximum and non-mitochondrial respiration in WT and MIC60 KO cells obtained from three independent experiments. The data are normalized to basal respiration from HAP1 WT. Bar and error bar represent mean ± SEM from three independent experiments. *P = 0.01 for basal (using one-sample t-test), ***P = 0.0004 for maximum respiration and *P = 0.012 for non-mitochondrial respiration (using unpaired Student's t-test). Download figure Download PowerPoint CJs are dispensable for the regular arrangement of MIC60 in the IBM MICOS is a large oligomeric complex present at CJs. Using stimulated emission depletion (STED) super-resolution images of fixed WT HAP1 cells, we show a regularly spaced arrangement of MIC10 and MIC60 punctae along the IBM (Fig 2A) consistent with earlier reports 56, 57. We determined the median distance between consecutive punctae of MIC10 and MIC60 for each mitochondrion and called it interpunctae distance (IPD). The median mitochondrial IPD was around 280 nm for both MIC10 and MIC60 in WT HAP1 cells under standard growth conditions (Fig 2B). Since MIC60 deletion leads to reduction in all proteins of MICOS, while loss of MIC10 still preserves MIC60 (Fig 1A), we asked whether MIC10 is required for the punctae-like appearance of MIC60. Deletion of MIC10, albeit leading to a loss of CJs, did not disturb the regular arrangement of MIC60 punctae along the mitochondrial length (Fig 2A). In line with this, the median IPD per mitochondrion of MIC60 in control and MIC10 KO cells was not significantly different (Fig 2B). Since lack of CJs together with loss of the MIC10/13/26/27 subcomplex did not alter the spatial arrangement of MIC60, we conclude that CJs are not necessary for regular spacing of MIC60 in the IBM (Fig 2C). We further analysed whether loss of MIC10 impairs formation of contact sites between the IM and OM marked by colocalization of MIC60 and TOMM70; two protein markers reported to be present at the contact sites in baker's yeast 23. STED super-resolution nanoscopy after double immunostaining of HAP1 cells with antibodies against MIC60 and TOMM70 showed similar patterns of partial colocalization (Fig 2A, merge panel, arrowheads) in WT and MIC10 KO cells, suggesting that MIC60/TOMM70-positive contact sites are still formed and maintained in MIC10 KO cells. This supports the conclusion that MIC60 is positioned at uniform distances in the IBM, which are partially linked to the OM at contact sites, and that MIC60 represents a docking and scaffolding platform for other MICOS subunits (Fig 2C) such as MIC10 for CJ formation. This is consistent with an earlier report using confocal fluorescence microscopy in baker′s yeast 58. Figure 2. MIC60 assembles as regularly spaced punctae in the absence of CJs A. Representative STED super-resolution images of WT and MIC10 KO HAP1 cells immunostained with MIC60 or MIC10 antibodies (top panel) and TOMM70 (middle panel). Bottom panel shows merged images. Arrowheads show colocalization of MIC60 and TOMM70 punctae. Scale bar 500 nm. B. Quantification of median interpunctae distance (IPD) per mitochondrion between MIC60 and MIC10 punctae in indicated cell lines represented by boxplots. Boxplots show median and interquartile range from 25 to 75 percentile, and whiskers represent minimum and maximum value. Median IPD from n = 10–16 mitochondria (from two independent experiments) is shown as data points in the boxplots. ns, not significant, unpaired Student's t-test. C. Scheme shows MIC60 marking the nascent sites of CJ formation independent of MIC10 and presence of contact sites in WT and MIC10 KO HAP1 cells shown by colocalization of MIC60 and TOMM70. Download figure Download PowerPoint Crista junction proteins show a markedly reduced mobility in the inner membrane, and loss of MIC13 affects the mobility of distinct inner membrane proteins We asked how mobile the two core MICOS subunits, MIC60 and MIC10, are compared to other membrane proteins localized to different mitochondrial subcompartments. We constructed GFP-tagged versions of MIC60/MIC10, TOMM20, TIMM23 and ATP5I, established markers of CJs, OM, IBM and CM, respectively (Fig 3A), and performed fluorescence recovery after photobleaching (FRAP) experiments. For TOMM20, TIMM23 and ATP5I, we observed substantially shorter T1/2 recovery times, higher diffusion coefficients and higher mobile fractions than for MIC10 and MIC60, demonstrating that CJ proteins are more restricted in movement compared to membrane proteins of other mitochondrial complexes present in various subcompartments (Fig 3B, D and E, Appendix Fig S1F). In line with this, MIC60 was reported to show restricted diffusion in the IM compared to OM proteins in another study 59. To know whether the mobility of these proteins depends on the presence of a fully assembled MICOS complex, which is essential for formation of CJs, we generated MIC13 KO HeLa cells that are well suited for microscopy of mitochondria. Consistent with prior reports 44, 45, we observed a loss of MIC10, MIC26, MIC27, altered cristae morphology and loss of CJs in MIC13 KO HeLa cells (Fig EV1A–D). Upon deletion of MIC13, in particular the diffusion coefficients of TIMM23 and MIC10 were altered to a major extent but less for MIC60 (Fig 3C–E, Appendix Fig S1A, B, D and F). The latter is consistent with our finding that MIC60 can arrange in regularly spaced punctae in the absence of other MICOS subunits (Fig 2). Interestingly, the loss of MIC13 decreases the mobile fraction of TIMM23 considerably. As in baker's yeast, Tim23 was shown to dynamically redistribute between the CM and the IBM in a manner dependent on mitochondrial protein import 12, we propose that the decreased TIMM23 mobile fraction in cells lacking CJs is due to trapping of a fraction of TIMM23 in the CM providing experimental support for the role of CJs as "gates" between the CM and the IBM and acting as diffusion barriers. This view is also supported by a very recent study showing that cristae behave as independent units within a single mitochondrion and can even adopt distinct levels of membrane potential 60. Moreover, the mobility of MIC10 increases drastically in MIC13 KO HeLa cells compared to WT cells, in line with the view that MIC13 is required for specifically stabilizing MIC10 at the MICOS complex 44, 45. Figure 3. Mobility of crista junction proteins is restricted compared to proteins of other mitochondrial subcompartments, and loss of MIC13 affects the mobility of distinct IM proteins A. Scheme of investigated marker proteins, subjected to FRAP, located at different mitochondrial subcompartments. B, C. FRAP curves (curve fitted) of WT (B) and MIC13 KO HeLa cells (C) expressing GFP-tagged fusion proteins of MIC60 (CJs), MIC10 (CJs), TOMM20 (OM), TIMM23 (IBM) and ATP5I (CM). Average FRAP curves (intensities in arbitrary units) for each marker were obtained (three independent experiments, 6–10 mitochondria for each experiment). Error bars for each time point representing SEM are shown. D. Histogram showing average percentage of mobile fractions, obtained from curve fits of all mitochondria expressing GFP-tagged versions of MIC60 (CJs), MIC10 (CJs), TOMM20 (OM), TIMM23 (IBM) and ATP5I (CM) in WT and MIC13 KO HeLa cells (data calculated from FRAP curves shown in B and C that are obtained from three independent experiments, 6–10 mitochondria from each experiment). E. Diffusion coefficients of the above-mentioned proteins are shown in the table. Download figure Download PowerPoint Click here to expand this figure. Figure EV1. Deletion of MIC13 in HeLa cells leads to a loss of crista junctions A. Western blot analysis of WT and MIC13 KO HeLa cells showing a reduction in MIC10, MIC26 and MIC27 protein levels in MIC13 KOs. B. Representative electron micrographs of WT and MIC13 KO HeLa cells show loss of CJs in MIC13 KOs. Scale bar 500 nm. C. Boxplot showing quantification of CJs per mitochondrial section from different mitochondria in WT and MIC13 KO HeLa cells represented as boxplots. Boxplots show median and interquartile range from 25 to 75 percentile, and whiskers represent minimum and maximum value. Data from n = 70–90 mitochondria (from two independent experiments) are shown as data points in the boxplots. ****P < 0.0001 (WT versus MIC13 KO), unpaired Student's t-test. D. Boxplot showing quantification of cristae per mitochondrial section in WT and MIC13 KO HeLa cells represented as boxplots. Boxplots show median and interquartile range from 25 to 75 percentile, and whiskers represent minimum and maximum value. Data from n = 70–90 mitochondria (from two independent experiments) are shown as data points in the boxplots. ****P < 0.0001, unpaired Student's t-test. E. Representative STED super-resolution images of WT HeLa cells stained with anti-MIC13 antibody shows punctate distribution of MIC13. Scale bar 500 nm. Download figure Download PowerPoint To study the mobility of MIC10 and MIC60 by a different approach, we used single-particle tracking (SPT) technique (Fig 4). For this, we constructed the SNAP-tagged versions of MIC60 and MIC10 and confirmed their functionality as revealed by coimmunoprecipitation using anti-MIC13 antibodies (Fig EV2A and B), BN-PAGE analysis (Fig EV2C) and restoration of MIC13 levels upon MIC10 expression
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