Programmed mitophagy is essential for the glycolytic switch during cell differentiation

Article2 May 2017free access Source DataTransparent process Programmed mitophagy is essential for the glycolytic switch during cell differentiation Lorena Esteban-Martínez Department of Cellular and Molecular Biology, Centro de Investigaciones Biológicas, CSIC, Madrid, Spain Search for more papers by this author Elena Sierra-Filardi Department of Cellular and Molecular Biology, Centro de Investigaciones Biológicas, CSIC, Madrid, Spain Search for more papers by this author Rebecca S McGreal Departments of Genetics, Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, Bronx, NY, USA Search for more papers by this author María Salazar-Roa Cell Division and Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain Search for more papers by this author Guillermo Mariño Departamento de Biología Fundamental, Universidad de Oviedo, Fundación para la Investigación Sanitaria del Principado de Asturias (FINBA), Oviedo, Spain Search for more papers by this author Esther Seco Department of Cellular and Molecular Biology, Centro de Investigaciones Biológicas, CSIC, Madrid, Spain Search for more papers by this author Sylvère Durand Metabolomics and Molecular Cell Biology Platforms, Gustave Roussy, Villejuif, France Search for more papers by this author David Enot Metabolomics and Molecular Cell Biology Platforms, Gustave Roussy, Villejuif, France Search for more papers by this author Osvaldo Graña Bioinformatics Unit and Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Madrid, Spain Search for more papers by this author Marcos Malumbres orcid.org/0000-0002-0829-6315 Cell Division and Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain Search for more papers by this author Ales Cvekl Departments of Genetics, Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, Bronx, NY, USA Search for more papers by this author Ana María Cuervo orcid.org/0000-0002-0771-700X Department of Developmental and Molecular Biology, Institute for Aging Studies, Albert Einstein College of Medicine, Bronx, NY, USA Search for more papers by this author Guido Kroemer Metabolomics and Molecular Cell Biology Platforms, Gustave Roussy, Villejuif, France Equipe 11 labellisée par la Ligue Nationale contre le cancer, Centre de Recherche des Cordeliers, Paris, France INSERM, U1138, Paris, France Université Paris Descartes, Sorbonne Paris Cité, Paris, France Université Pierre et Marie Curie, Paris, France Pôle de Biologie, Hôpital Européen Georges Pompidou, AP-HP, Paris, France Department of Women's and Children's Health, Karolinska Institute, Karolinska University Hospital, Stockholm, Sweden Search for more papers by this author Patricia Boya Corresponding Author [email protected] orcid.org/0000-0003-3045-951X Department of Cellular and Molecular Biology, Centro de Investigaciones Biológicas, CSIC, Madrid, Spain Search for more papers by this author Lorena Esteban-Martínez Department of Cellular and Molecular Biology, Centro de Investigaciones Biológicas, CSIC, Madrid, Spain Search for more papers by this author Elena Sierra-Filardi Department of Cellular and Molecular Biology, Centro de Investigaciones Biológicas, CSIC, Madrid, Spain Search for more papers by this author Rebecca S McGreal Departments of Genetics, Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, Bronx, NY, USA Search for more papers by this author María Salazar-Roa Cell Division and Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain Search for more papers by this author Guillermo Mariño Departamento de Biología Fundamental, Universidad de Oviedo, Fundación para la Investigación Sanitaria del Principado de Asturias (FINBA), Oviedo, Spain Search for more papers by this author Esther Seco Department of Cellular and Molecular Biology, Centro de Investigaciones Biológicas, CSIC, Madrid, Spain Search for more papers by this author Sylvère Durand Metabolomics and Molecular Cell Biology Platforms, Gustave Roussy, Villejuif, France Search for more papers by this author David Enot Metabolomics and Molecular Cell Biology Platforms, Gustave Roussy, Villejuif, France Search for more papers by this author Osvaldo Graña Bioinformatics Unit and Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Madrid, Spain Search for more papers by this author Marcos Malumbres orcid.org/0000-0002-0829-6315 Cell Division and Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain Search for more papers by this author Ales Cvekl Departments of Genetics, Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, Bronx, NY, USA Search for more papers by this author Ana María Cuervo orcid.org/0000-0002-0771-700X Department of Developmental and Molecular Biology, Institute for Aging Studies, Albert Einstein College of Medicine, Bronx, NY, USA Search for more papers by this author Guido Kroemer Metabolomics and Molecular Cell Biology Platforms, Gustave Roussy, Villejuif, France Equipe 11 labellisée par la Ligue Nationale contre le cancer, Centre de Recherche des Cordeliers, Paris, France INSERM, U1138, Paris, France Université Paris Descartes, Sorbonne Paris Cité, Paris, France Université Pierre et Marie Curie, Paris, France Pôle de Biologie, Hôpital Européen Georges Pompidou, AP-HP, Paris, France Department of Women's and Children's Health, Karolinska Institute, Karolinska University Hospital, Stockholm, Sweden Search for more papers by this author Patricia Boya Corresponding Author [email protected] orcid.org/0000-0003-3045-951X Department of Cellular and Molecular Biology, Centro de Investigaciones Biológicas, CSIC, Madrid, Spain Search for more papers by this author Author Information Lorena Esteban-Martínez1, Elena Sierra-Filardi1, Rebecca S McGreal2, María Salazar-Roa3, Guillermo Mariño4, Esther Seco1, Sylvère Durand5, David Enot5, Osvaldo Graña6, Marcos Malumbres3, Ales Cvekl2, Ana María Cuervo7, Guido Kroemer5,8,9,10,11,12,13 and Patricia Boya *,1 1Department of Cellular and Molecular Biology, Centro de Investigaciones Biológicas, CSIC, Madrid, Spain 2Departments of Genetics, Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, Bronx, NY, USA 3Cell Division and Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain 4Departamento de Biología Fundamental, Universidad de Oviedo, Fundación para la Investigación Sanitaria del Principado de Asturias (FINBA), Oviedo, Spain 5Metabolomics and Molecular Cell Biology Platforms, Gustave Roussy, Villejuif, France 6Bioinformatics Unit and Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Madrid, Spain 7Department of Developmental and Molecular Biology, Institute for Aging Studies, Albert Einstein College of Medicine, Bronx, NY, USA 8Equipe 11 labellisée par la Ligue Nationale contre le cancer, Centre de Recherche des Cordeliers, Paris, France 9INSERM, U1138, Paris, France 10Université Paris Descartes, Sorbonne Paris Cité, Paris, France 11Université Pierre et Marie Curie, Paris, France 12Pôle de Biologie, Hôpital Européen Georges Pompidou, AP-HP, Paris, France 13Department of Women's and Children's Health, Karolinska Institute, Karolinska University Hospital, Stockholm, Sweden *Corresponding author. Tel: +34 91 8373112 Ext 4369; E-mail: [email protected] EMBO J (2017)36:1688-1706https://doi.org/10.15252/embj.201695916 See also: A Deczkowska & M Schwartz (June 2017) 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 Retinal ganglion cells (RGCs) are the sole projecting neurons of the retina and their axons form the optic nerve. Here, we show that embryogenesis-associated mouse RGC differentiation depends on mitophagy, the programmed autophagic clearance of mitochondria. The elimination of mitochondria during RGC differentiation was coupled to a metabolic shift with increased lactate production and elevated expression of glycolytic enzymes at the mRNA level. Pharmacological and genetic inhibition of either mitophagy or glycolysis consistently inhibited RGC differentiation. Local hypoxia triggered expression of the mitophagy regulator BCL2/adenovirus E1B 19-kDa-interacting protein 3-like (BNIP3L, best known as NIX) at peak RGC differentiation. Retinas from NIX-deficient mice displayed increased mitochondrial mass, reduced expression of glycolytic enzymes and decreased neuronal differentiation. Similarly, we provide evidence that NIX-dependent mitophagy contributes to mitochondrial elimination during macrophage polarization towards the proinflammatory and more glycolytic M1 phenotype, but not to M2 macrophage differentiation, which primarily relies on oxidative phosphorylation. In summary, developmentally controlled mitophagy promotes a metabolic switch towards glycolysis, which in turn contributes to cellular differentiation in several distinct developmental contexts. Synopsis Retinal ganglion cell differentiation and M1 macrophage polarization depend on metabolic reprogramming towards glycolysis, which is triggered by hypoxia-induced autophagic degradation of mitochondria (mitophagy). Programmed mitophagy eliminates mitochondria during mouse retinal development. Hypoxia-induces NIX-dependent mitophagy. Mitophagy allows for a glycolytic shift required for retinal ganglion cell differentiation. Mitophagy also regulates metabolic reprogramming during M1 macrophage polarization. Introduction Autophagy is a catabolic pathway that mediates the degradation and recycling of intracellular components, including whole organelles, to sustain cell homeostasis (Boya et al, 2013). Autophagy is the sole mechanism that allows for the degradation of entire mitochondria, a process commonly known as mitophagy. While mitophagy primarily eliminates damaged or dysfunctional mitochondria (Ashrafi & Schwarz, 2013), this pathway can also mediate the degradation of mitochondria in developmental contexts, a process known as programmed mitophagy (Ney, 2015). BCL2/adenovirus E1B 19-kDa-interacting protein 3-like (BNIP3L), also known as NIX, is an essential regulator of programmed mitophagy during reticulocyte maturation (Aerbajinai et al, 2003; Diwan et al, 2007; Schweers et al, 2007; Sandoval et al, 2008). During programmed mitophagy, NIX is mainly regulated at the transcriptional level and acts as a mitophagy receptor, mediating autophagic sequestration of mitochondria by interacting with LC3 via its LIR domain (Novak et al, 2010). Metabolic reprogramming is a process by which cells shift their metabolism from oxidative phosphorylation towards glycolysis and convert glucose into lactate even in the presence of oxygen. This phenomenon was first described in cancer cells, but has since been observed in other cell types, including embryonic stem cells, proinflammatory M1 macrophages and cells of the adult retina, and it is thought to be essential to fulfill the metabolic requirements of those cells (Galvan-Pena & O'Neill, 2014; Ng et al, 2015; Chandel et al, 2016). Hypoxia also triggers metabolic shift towards glycolysis. This type of metabolism is also observed in stem cells and is thought to constitute an adaptation to the hypoxic conditions present in vivo during development, in adult stem cell niches and in the inflamed tissue (Suda et al, 2011; Escribese et al, 2012). Interestingly, hypoxia is a strong inductor of mitophagy (Zhang et al, 2008). How the complex functionality of the nervous system arises from a pool of undifferentiated neuroepithelial cells is one of the more fascinating aspects of embryonic development (Valenciano et al, 2008). These neuroepithelial cells undergo marked changes to generate differentiated neurons and glial cells. Cell proliferation requires nutrients, energy and biosynthetic activity to duplicate all macromolecular components during each passage of the cell cycle. Differentiation requires profound changes in cellular components and a shift in metabolic activity. Indeed, metabolic pathways may be controlled by the same signals that control cell differentiation (Agathocleous & Harris, 2013). The retina, a model organ for the study of the central nervous system, is a three-layered structure composed of one glial and six distinct neuronal cell types, which arise from a pool of multipotent retinal progenitor cells (Stenkamp, 2015). In mice, retinal neurogenesis is an orderly process that starts with the differentiation of retinal ganglion cells (RGCs) and is followed by that of other neuronal cell types. During retinal development, cell differentiation follows a central-to-peripheral gradient, with the result that the central retina is more developmentally advanced than the peripheral retina (Stenkamp, 2015). We have previously shown that autophagy genes are essential for the generation of mature neurons from olfactory bulb neural stem cells (Vazquez et al, 2012). Moreover, blockade of autophagy in the embryonic chick retina results in decreased ATP levels and hampers the elimination of apoptotic cells generated during neurogenesis (Mellén et al, 2008, 2009). Interestingly, both these phenotypes are restored by supplying pyruvate as a cell-permeable precursor (methyl pyruvate), suggesting a connection between autophagy and cell metabolism during neuronal differentiation (Boya et al, 2016). Moreover, cancer cells engage mitophagy to promote metabolic reprogramming towards glycolysis during prolonged mitotic arrest (Domenech et al, 2015). Here, we show that NIX- and Atg5-dependent mitophagy mediates a metabolic shift towards glycolysis that allows RGC generation in the embryonic mouse retina. Furthermore, we describe a mitophagy-dependent metabolic shift that occurs during the polarization of macrophages towards a proinflammatory and more glycolytic M1 phenotype. Taken together, our data show that programmed mitophagy triggers metabolic reprogramming towards glycolysis during cellular differentiation. Results Mitochondrial rarefaction during embryonic RGC differentiation In the mouse retina, neurogenesis starts around day E12.5 with the differentiation of RGCs, the first neurons to be generated. As expected, immunofluorescence analyses revealed the presence of the RGC-specific transcription factor Brn3a and γ-synuclein (another RGC marker) from E13.5, with levels peaking at E15.5 in the RGC layer of mouse retinal flatmounts (Fig 1A and B, and Appendix Figs S1 and S2). In the same retinas, immunostaining for the mitochondrial protein TOMM20 decreased after E13.5 (Fig 1C and D, insets below, and Appendix Fig S1C). This decrease in the number of mitochondria during retinal embryonic development was corroborated by labelling dissociated retinas at different embryonic stages with the mitochondrion-specific dye MitoTracker Deep Red (MTDR), which was quantified by flow cytometry (Fig 1E and F). This decrease in mitochondrial number could not be attributed to decreased expression of genes involved in mitochondrial biogenesis, such as Ppargc1a and Tfam, as their expression remained unchanged during the embryonic stages assessed (Fig EV1A). Moreover, electron microscopy analyses revealed that at E15.5 the number of mitochondria in each RGC was reduced as compared with that of proliferating neuroblasts (Fig 1G and H). Mitochondria from neuroblasts (Nbs) were large and displayed well-organized cristae, indicative of a high metabolic rate, while those from RGCs were comparatively smaller and contained fewer cristae (Fig 1I). Together these data suggest that programmed elimination of mitochondria occurs during RGC development. Figure 1. Mitochondrial mass decreases during embryonic retinal development A. Immunostaining of the retinal ganglion cell (RCG)-specific transcription factor Brn3a (cyan) in the RGC layer of mouse retinal flatmounts at the indicated embryonic days (E). The maximal projection in the RGC layer is shown. Scale bar, 50 μm. B. Quantification of RGC density per mm2 at the indicated embryonic stages in retinas stained as in (A) (n = 6 per group). Data are presented as mean ± SEM. ***P < 0.001 (Mann-Whitney U-test). C. Immunostaining with the mitochondrial marker TOMM20 (red) in the RGC layer of the same retinas as in (A). Scale bar, 50 μm. Insets show TOMM20 staining (red) and nuclei labelled with DAPI (blue) in a confocal plane in the indicated region. Scale bar, 20 μm. D. TOMM20-positive pixel staining at the indicated embryonic stages labelled as in (C) (n = 6 per group). Data are presented as mean ± SEM. ***P < 0.001 (Mann-Whitney U-test). E, F. Flow cytometry histograms and percentage mean fluorescence intensity (% MitoTracker) in dissociated retinas, corresponding to different embryonic stages, stained with MitoTracker Deep Red (MTDR) (n = 5–12 retinas per group). Data are presented as mean ± SEM. **P < 0.01, ***P < 0.001 (Mann-Whitney U-test). G. Ultrastructural analysis of neuroblast (Nb) and RGC from an E15.5 mouse retina. Scale bar, 1 μm. Arrows indicate mitochondria. H. Quantification of the number of mitochondria per cell in G (n = 12–14 cells per group). Data are presented as mean ± SEM. *P < 0.05 (Mann-Whitney U-test). I. Mitochondrial morphology (m) in retinal Nb and RGC at E15.5. Scale bars, 500 nm. J. Immunoblot of retinas at different embryonic stages incubated for 3 h in the absence (−) or presence (+) of hydroxychloroquine to block autophagic flux. K. Autophagosomal membrane (AP) surrounding a mitochondrion (arrows in left-hand image) in an E15.5 mouse retina in the presence of HCQ to block lysosomal degradation. Scale bar, 500 nm. Insets of the indicated areas show four adjacent membranes (right). L. Increase in the number of mitochondrial per nm2 in RGCs from E15.5 mouse retinas in the presence of HCQ (n = 12 per group). Data are presented as mean ± SEM. ***P < 0.001 (Mann-Whitney U-test). Source data are available online for this figure. Source Data for Figure 1 [embj201695916-sup-0003-SDataFig1.pdf] Download figure Download PowerPoint Click here to expand this figure. Figure EV1. The increase in mitochondrial number is autophagy- and mitophagy dependent mRNA expression, determined by qRT–PCR, of the mitochondrial biogenesis regulators Ppargc1a and Tfam (n = 2–3 pools of retinas per group). Data are presented as mean ± SEM. TOMM20 immunostaining at the indicated developmental stages in flat-mounted retinas incubated for 6 h in the presence of 5 μM CsA or 10 mM 3-MA. The maximal projection of the z-stack is shown. Scale bar, 50 μm. COX-IV immunostaining in flat-mounted retinas (E15.5) incubated for 6 h with 3-MA or CsA. Maximal projections are shown on the left (scale bar, 50 μm) and single confocal planes from the boxed insets are shown on the right. COX-IV immunostaining is shown in green and DAPI-stained nuclei in blue. Scale bar in insets, 20 μm. COX-IV immunoblotting of E15.5 retinas incubated for 6 h in 3-MA or CsA. Tubulin was used as a loading control. Percentage of mean fluorescence intensity (% MitoTracker) in E15.5 retinas incubated with 3-MA, CsA or a combination of both (n = 6–22 retinas per group). Data are presented as mean ± SEM. *P < 0.05 (Student's t-test). Source data are available online for this figure. Download figure Download PowerPoint Mitophagy-mediated elimination of mitochondria during RGC development Since autophagy is the only known catabolic pathway capable of mediating the degradation of entire mitochondria, we analysed autophagic activity during embryonic development in the mouse retina. The autophagy-associated lipidation of microtubule-associated proteins 1A/1B light chain 3 (MAP1LC3, better known as LC3), which gives rise to an increase in the electrophoretic mobility of LC3 (LC3-II), was increased during retinal development (Fig 1J). Consistently, incubation of retinal explants for 3 h with the lysosomal inhibitor hydroxychloroquine (HCQ) further increased LC3-II accumulation, indicating that basal autophagic flux is enhanced during the early stages of development of the embryonic mouse retina (Fig 1J). Transmission electron microscopy revealed the presence of mitochondria inside autophagosomes in RGCs at E15.5 in these conditions (Fig 1K) and the number of mitochondria was increased after inhibition of lysosomal degradation (Fig 1L), suggesting that the decrease in mitochondrial mass during retinal development is mediated by autophagy. Next, we incubated retinas at different embryonic stages with the general autophagy inhibitor 3-methyladenine (3-MA) or with cyclosporine A (CsA), an inhibitor of mitochondrial cyclophilin D that suppresses mitophagy in many different cell types and experimental conditions (Kim et al, 2007; Carreira et al, 2010; Domenech et al, 2015; Mauro-Lizcano et al, 2015). Inhibition of either autophagy or mitophagy for 6 h prevented the decrease in TOMM20 labelling (Figs 2A and B, and EV1B) and resulted in increased MTDR staining, as measured by flow cytometry (Fig 2C and D). Corroborating these results, immunofluorescence and immunoblot analyses revealed increased expression of the mitochondria respiratory chain component COX-IV (Fig EV1C and D). Incubation of E15.5 retinas with a combination of 3-MA and CsA failed to further increase mitochondrial number compared with either compound alone, suggesting that both inhibitors act on the same signalling pathway (Fig EV1E). Together, these results indicate that the autophagy-dependent elimination of mitochondria during retinal development occurs specifically at E15.5. Figure 2. A mitophagy-dependent metabolic shift towards glycolysis occurs during embryonic retinal development A. Mitochondrial labelling by TOMM20 immunostaining in flat-mounted retinas (E15.5) incubated for 6 h in the presence of 5 μM CsA or 10 mM 3-MA. TOMM20 immunostaining is shown in red and DAPI-stained nuclei in blue. A single confocal plane is shown and corresponds to the inset from the lower magnification images displayed in Fig EV1B. Scale bar, 20 μm. B. Quantification of TOMM20 immunostaining in retinas cultured as in (A) at the indicated embryonic stages (n = 4–16 retinas per group). Data are presented as mean ± SEM. *P < 0.05, **P < 0.01 (Mann-Whitney U-test). C, D. Quantification of the percentage mean fluorescence intensity (% MitoTracker) and representative flow cytometry histograms at the indicated embryonic stages in retinal explants cultured as in (A) and stained with MTDR (n = 6–57 retinas per group). Data are presented as mean ± SEM. *P < 0.05 (Mann-Whitney U-test and Student's t-test). E. Heat map indicating expression of glycolysis-related metabolites in mouse retinas at different developmental stages. P0, Postnatal day 0. F, G. Extracellular acidification rate (ECAR) in embryonic retinas at the indicated developmental stages (F) (n = 19–49 pools of retinas per group) and in E15.5 retinas incubated for 6 h in the presence of 3-MA or CsA (G) (n = 15–19 pools of two retinas per group). Data are presented as mean ± SEM. *P < 0.05 (Mann-Whitney U-test (F) and Student's t-test (G)). H. Heat map showing the relative mRNA expression of glycolysis regulators as determined by transcriptomic analyses in mouse retinas at the indicated developmental stages. I. mRNA expression of glycolysis regulators in E15.5 retinas incubated for 6 h with 3-MA or CsA (n = 3 pools of two retinas per group). Data are presented as mean ± SEM. *P < 0.05, **P < 0.01 (Mann-Whitney U-test). Download figure Download PowerPoint Mitophagy-dependent metabolic reprogramming in retinal development Our previous findings in cell lines suggest that high levels of mitophagy may result in a shift from an oxidative to a glycolytic metabolic profile (Domenech et al, 2015). We next used mass spectrometry to measure the levels of selected metabolites during mouse retinal development. Levels of glycolytic metabolites, including lactate, increased from E15.5, but subsequently decreased at birth (Fig 2E). In agreement, cellular metabolic analyses using Seahorse technology revealed that the extracellular acidification rate (ECAR), which is an indirect measurement of glycolysis, increased at E15.5, but decreased at later developmental stages (Fig 2F). This increase in ECAR was prevented by incubation for 6 h with 3-MA or CsA (Fig 2G). As expected, mitochondrial respiration decreased at E15.5 and increased in retinas treated with 3-MA or CsA (Appendix Fig S3A and B). RNA transcriptome analyses showed a dramatic increase in mRNA expression of multiple genes encoding glycolytic enzymes (Hk2, Pfkfb3 and Gapdh) and glucose transporters (Scla2a1 and Scla2a3) beginning at E15.5 (Fig 2H). Interestingly, treatment of E15.5 retinal explants with 3-MA or CsA significantly reduced mRNA expression of these enzymes, implicating mitophagy in the metabolic shift towards glycolysis during embryonic retinal development (Fig 2I). Mitophagy-dependent metabolic reprogramming and differentiation of macrophages We next investigated whether mitophagy could also play a critical role in other differentiation pathways associated with increased glycolysis. Metabolic reprogramming towards glycolysis has been well described during M1 macrophage activation (O'Neill & Pearce, 2016). Macrophages can be broadly classified into two groups. M1 macrophages, generated in response to proinflammatory conditions such as TLR agonists in combination with IFN-γ, play important roles in the elimination of bacterial infections and are considered more inflammatory (O'Neill & Pearce, 2016). IL-4-activated (M2) macrophages participate in tissue repair and have anti-inflammatory properties (O'Neill & Pearce, 2016). M1 and M2 macrophages also differ in their metabolic signatures. M1 macrophages display a glycolytic profile, characterized by increased expression of several glycolytic regulators and enhanced lactate production, while M2 macrophages show high levels of oxidative phosphorylation (Rodriguez-Prados et al, 2010; Izquierdo et al, 2015; Jha et al, 2015). Crucially, macrophages can be reprogrammed by targeting their metabolism (Izquierdo et al, 2015; Mills & O'Neill, 2016). To explore the potential role of mitophagy in M1 macrophage polarization, we induced the differentiation of peritoneal macrophages into either the M1 or M2 phenotype by incubation with LPS/INF-γ and IL-4/IL-13, respectively (Fig EV2A). M1 macrophages showed decreased MTDR staining as compared with M2 macrophages, indicating a reduction in mitochondrial mass (Fig EV2B). MTDR levels dramatically increased when M1, but not M2, macrophages were cultured in the presence of 3-MA or CsA (Fig EV2C and D). 3-MA and CsA treatment altered cell morphology from the round shape characteristic of the M1 phenotype to the more elongated shape associated with the M2 activation state (Fig EV2E and F). Moreover, mRNA expression of M1 markers such as Tnf, Nos2 and Il1b, as well as expression of several glycolytic enzymes, was reduced when M1 macrophages were incubated in the presence of autophagy or mitophagy inhibitors (Fig EV2G). Together, these data indicate that mitophagy regulates the glycolytic shift associated with cellular differentiation in several cell types. Click here to expand this figure. Figure EV2. Mitophagy sustains glycolysis in M1 macrophages A. Schematic showing experimental design. B. Mouse peritoneal macrophages were isolated from adult mice treated for 4 days with thioglycolate and were then incubated in the presence of LPS and IFN-γ to induce M1 polarization or with IL-4/IL-13 to induce the M2 phenotype. Cells were then stained with MitoTracker and assessed by flow cytometry (n = 12 per group). Data are presented as mean ± SEM. ***P < 0.001 (Mann-Whitney U-test). C, D. M1 (C) or M2 (D) macrophages were incubated for 6 h with 10 mM 3-MA or 5 μM CsA, and MitoTracker staining was assessed by flow cytometry (C, n = 6–9 per group; D, n = 6–9 per group). Data are presented as mean ± SEM. *P < 0.05, **P < 0.01 (Mann-Whitney U-test). E, F. Representative images of M1 macrophages (E) after incubation with 3-MA or CsA and M2 macrophages (F). Scale bars, 50 μm. G. mRNA expression of the indicated genes in M1 macrophages cultured in the presence of 10 mM 3-MA or 5 μM CsA (n = 6 per group). Data are presented as mean ± SEM. *P < 0.05, **P < 0.01 (ANOVA). Download figure Download PowerPoint Autophagy-dependent metabolic reprogramming regulates RGC differentiation We next investigated whether mitophagy and the concomitant metabolic shift observed during retinal development are implicated in the neuronal differentiation of RGCs. Inhibition of autophagy or mitophagy with CsA or 3-MA resulted in a decrease in the number of cells positive for the RGC-specific transcription factor Brn3a at E15.5 (Fig 3A and C). Moreover, blockade of autophagy and mitophagy resulted in alterations in axonal morphology as determined by β-III-tubulin labelling in retinal flatmounts (Fig 3B and D), in line with the view that inhibition of autophagy and mitophagy attenuates RGC differentiation. Next, we investigated whether experimental induction of autophagy stimulates RGC differentiation. In the developing retina, neurogenesis follows a central-to-peripheral gradient, meaning that the first RGCs are generated close to the optic nerve at E13.5 (Appendix Fig S1A and B). Pharmacological induction of autophagy with rapamycin at E13.5 increased the num