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Morphological and bioenergetic demands underlying the mitophagy in post-mitotic neurons: the pink-parkin pathway.

Amadoro G, Corsetti V, Florenzano F, Atlante A, Bobba A, Nicolin V, Nori SL, Calissano P - Front Aging Neurosci (2014)

Bottom Line: Evidence suggests a striking causal relationship between changes in quality control of neuronal mitochondria and numerous devastating human neurodegenerative diseases, including Parkinson's disease, Alzheimer's disease, Huntington's disease, and amyotrophic lateral sclerosis.Contrary to replicating mammalian cells with a metabolism essentially glycolytic, post-mitotic neurons are distinctive owing to (i) their exclusive energetic dependence from mitochondrial metabolism and (ii) their polarized shape, which entails compartmentalized and distinct energetic needs.Here, we review the recent findings on mitochondrial dynamics and mitophagy in differentiated neurons focusing on how the exceptional characteristics of neuronal populations in their morphology and bioenergetics needs make them quite different to other cells in controlling the intracellular turnover of these organelles.

View Article: PubMed Central - PubMed

Affiliation: Institute of Translational Pharmacology - National Research Council Rome, Italy ; European Brain Research Institute Rome, Italy.

ABSTRACT
Evidence suggests a striking causal relationship between changes in quality control of neuronal mitochondria and numerous devastating human neurodegenerative diseases, including Parkinson's disease, Alzheimer's disease, Huntington's disease, and amyotrophic lateral sclerosis. Contrary to replicating mammalian cells with a metabolism essentially glycolytic, post-mitotic neurons are distinctive owing to (i) their exclusive energetic dependence from mitochondrial metabolism and (ii) their polarized shape, which entails compartmentalized and distinct energetic needs. Here, we review the recent findings on mitochondrial dynamics and mitophagy in differentiated neurons focusing on how the exceptional characteristics of neuronal populations in their morphology and bioenergetics needs make them quite different to other cells in controlling the intracellular turnover of these organelles.

No MeSH data available.


Related in: MedlinePlus

Confocal microscopy and image analysis of double immunofluorescence for cyt C (a mitochondrial marker; green channel) and LC3 (for visualization of autophagosomes; red channel), carried out on primary mature hippocampal cultures (15 DIV) at 12 h post-infection (MOI 50) with mock- and myc-NH2 26-230 human tau vectors. Nuclei were stained with DAPI (blue channel). (A–C) Numerous labeled LC3 stained vesicles intensely positive (colocalized) for cyt C were observed in myc-NH2htau neurons. Arrows point to two large mitophagosomal structures. (G–I) LC3 immunofluorescence is very faint in mock-treated cultures (D–F); (J–L) colocalization analysis performed with ImageJ, including the spatial pattern of colocalized points of (D,J), the intensity height of the luminance in the colocalized points (E,K), the spatial profile of the fluorescence intensity for both fluorescence channels for the white line positioned on several mitophagosomes in the second row (F,L). Scale bar 7 μm. Figure referring to data from Amadoro et al. (2014).
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Figure 2: Confocal microscopy and image analysis of double immunofluorescence for cyt C (a mitochondrial marker; green channel) and LC3 (for visualization of autophagosomes; red channel), carried out on primary mature hippocampal cultures (15 DIV) at 12 h post-infection (MOI 50) with mock- and myc-NH2 26-230 human tau vectors. Nuclei were stained with DAPI (blue channel). (A–C) Numerous labeled LC3 stained vesicles intensely positive (colocalized) for cyt C were observed in myc-NH2htau neurons. Arrows point to two large mitophagosomal structures. (G–I) LC3 immunofluorescence is very faint in mock-treated cultures (D–F); (J–L) colocalization analysis performed with ImageJ, including the spatial pattern of colocalized points of (D,J), the intensity height of the luminance in the colocalized points (E,K), the spatial profile of the fluorescence intensity for both fluorescence channels for the white line positioned on several mitophagosomes in the second row (F,L). Scale bar 7 μm. Figure referring to data from Amadoro et al. (2014).

Mentions: The mitochondria quality control regulates in post-mitotic neurons several vital metabolic functions such as their proper distribution to synaptic terminals, maintenance of electron transport chain (ETC) activity and electrical connectivity (Stowers et al., 2002; Verstreken et al., 2005; Chen and Chan, 2006; Liu and Shio, 2008; Bereiter-Hahn and Jendrach, 2010; Ferree and Shirihai, 2012; Misko et al., 2012), protection of mtDNA integrity (Westermann, 2002; Parone et al., 2008), apoptosis (Suen et al., 2008), formation and function of synapses and dendritic spines (Li et al., 2004). As other cell types, neuronal populations also continually modulate size and number of these organelles, according to the variable energy demands and metabolic states throughout the entire lifetime and/or different sub-cellular compartments (Chen and Chan, 2009; Santos et al., 2010; Vives-Bauza and Przedborski, 2011; Van Laar and Berman, 2013). However, a tight control of the interplay between their mitochondrial dynamic and bioenergetic status is of particular relevance for post-mitotic neurons because they have a unique metabolic as well as morphological profile which entails specialized and compartimentalized energetic needs. Indeed, neuronal populations are typically characterized by: (i) high bioenergetic needs as the ATP production classically depends in these cells on OxPhos respiration rather than glycolysis (Rolfe and Brown, 1997; Attwell and Laughlin, 2001; Mironov, 2009; Bolanos et al., 2010); (ii) a very polarized morphology with extensive neuritic projections which are crucial for neuronal survival via a proper maintenance of their mitochondrial biomass. Remarkably, although the human brain consists of only 2% of the volume of the body, it is roughly responsible for 25% of net oxygen consumption in resting conditions (Magistretti and Pellerin, 1999) with neurons generating as much as 95% of their ATP exclusively from mitochondrial OXPhos (Erecińska et al., 1994). However, it is worth noticing that neurons and astrocytes – which are the two major types of brain cells – exhibit a different preference for glucose utilization since its metabolism in neuron is diverted mainly to the pentose phosphate pathway in order to regenerate antioxidants (reduced glutathione) and to promote survival (Bolanos et al., 2010). As they constantly require an active and efficient defense mechanism against oxidative stress (Almeida et al., 2005; Herrero-Mendez et al., 2009), neuronal populations are indeed unable to switch to anaerobic glycolytic metabolism (as an ATP-generating mechanism) during an acute mitochondrial stress, relying on lactate as an alternative substrate for their mitochondria-derived bioenergetic purposes (Pellerin et al., 2007). In addition, it is generally assumed that only 0.2% of the neuronal cellular volume is in the cytoplasmic soma while about 99.8% is constituted by the axonal and dendritic compartments (Devor, 1999; Fjell and Walhovd, 2010; Florenzano, 2012). For instance, the axonal length of projection neurons – such as those of rat dopaminergic neurons that are localized in the substantia nigra which is an area selectively affected in PD – can be as long as 470 μm or more and can provide several axon collaterals each of them making in turn contacts with approximately 400 synapses (Matsuda et al., 2009). Besides, in order to locally provide ATP supply and calcium buffering required for the neuronal activity of high energy-demanding terminal synapses (Schon and Przedborski, 2011), an high number of mitochondria resides far away from soma being localized in distal axon and dendritic processes (Hollenbeck, 2005) such as presynaptic terminals, including the active zones where synaptics vesicles (SVs) are released (Rowland et al., 2000; Perkins et al., 2010), post-synaptic densities, nodes of Ranvier and in growth cones (Fabricius et al., 1993; Morris and Hollenbeck, 1993). Collectively, such peculiar requirements imply that a high number of mitochondria spend the majority of their time in traveling up-and-down between the sites of their biogenesis, which are mainly localized into cell bodies (Davis and Clayton, 1996; Saxton and Hollenbeck, 2012; Figure 2), and those of their functional utilization which instead are close to terminal endings (Li et al., 2004). Interestingly there’s a positive correlation between the frequency and/or the intensity of synapse electrical activity and the number of metabolically active mitochondria at presynaptic compartment (Dubinsky, 2009). Furthermore, provided that the mitochondria size and mass are not the same for all neurons (Dubinsky, 2009; Lu, 2009) and that intrinsic mitophagic capacity has been found to be brain region-specific (Diedrich et al., 2011), any perturbation in controlling the dynamics properties of these organelles (Verstreken et al., 2005; Kann and Kovács, 2007; Nunnari and Suomalainen, 2012) can seriously and selectively compromise their survival (Xue et al., 2001). Different morphologies and ultrastructural profiles of mitochondria have been also correlated with distinct bioenergetic demands of the tissues they occupy and mitochondrial network in neurons is demonstrated to be distinct from those of other tissues in morphology, interconnectivity as well as cytoplasmatic pattern distribution (Dubinsky, 2009; Kuznetsov et al., 2009; Mironov, 2009). Neurons critically depend on autophagy for differentiation and survival (Komatsu et al., 2006) and are particularly prone to autophagic stress (Chu, 2006) so that basal autophagy appears to be more efficient than in other proliferating non-neuronal cells types (Boland et al., 2008) and is also likely to be regulated in alternative and quite different ways (Ashrafi and Schwarz, 2013; Van Laar and Berman, 2013). Being terminally differentiated and producing high levels of ROS against relatively fewer antioxidant molecules (Cui et al., 2004; Fatokun et al., 2008), neurons need to refurbish “old” mitochondrial pool to prevent the deleterious accumulation of oxidative damage, as suggested by the fact that antioxidant treatment supports the survival of cerebellar Purkinje cells (PCs) from knockout mice for dynamin-1-like protein (Drp1) fission protein (Kageyama et al., 2012). In contrast, proliferating cells constantly generate “new” mitochondria during continuous cell replication cycles so that oxidative stress may be diluted and maintained at relatively low levels, even without any mitochondrial division (Kageyama et al., 2012). A proper interplay between the bioenergetic – which is mainly regulated by energy requirement and substrate availability – and the mitochondrial quality control and autophagy – which control the overall health of mitochondrial population and their relative abundance – is specifically critical in neurons as it impinges on their intrinsic resistance to stress and, then, on their survival. Indeed, the relative sensitivity of different neuronal populations to mitochondrial inhibitors is tightly correlated with their “spare respiratory capacity,” which is an index of general mitochondrial health taking into account the ratio of the glucose utilization rate to the expression level of respiratory chain complexes (Fern, 2003). Interestingly, the vulnerability to a complex I inhibitor such as rotenone of cultured striatal neurons, which are selectively affected in HD pathology, is primarily determined by their “spare respiratory capacity” rather than oxidative stress (Yadava and Nicholls, 2007). Likewise, presynaptic mitochondria from hippocampus and cortex show a lower spare respiratory capacity to rotenone when compared to non-synaptic mitochondria from the same regions (Davey et al., 1997), in favor with the finding that the bioenergetic failure of peripheral mitochondria in vivo initiates the loss of synaptic terminals in neurodegenerative diseases.


Morphological and bioenergetic demands underlying the mitophagy in post-mitotic neurons: the pink-parkin pathway.

Amadoro G, Corsetti V, Florenzano F, Atlante A, Bobba A, Nicolin V, Nori SL, Calissano P - Front Aging Neurosci (2014)

Confocal microscopy and image analysis of double immunofluorescence for cyt C (a mitochondrial marker; green channel) and LC3 (for visualization of autophagosomes; red channel), carried out on primary mature hippocampal cultures (15 DIV) at 12 h post-infection (MOI 50) with mock- and myc-NH2 26-230 human tau vectors. Nuclei were stained with DAPI (blue channel). (A–C) Numerous labeled LC3 stained vesicles intensely positive (colocalized) for cyt C were observed in myc-NH2htau neurons. Arrows point to two large mitophagosomal structures. (G–I) LC3 immunofluorescence is very faint in mock-treated cultures (D–F); (J–L) colocalization analysis performed with ImageJ, including the spatial pattern of colocalized points of (D,J), the intensity height of the luminance in the colocalized points (E,K), the spatial profile of the fluorescence intensity for both fluorescence channels for the white line positioned on several mitophagosomes in the second row (F,L). Scale bar 7 μm. Figure referring to data from Amadoro et al. (2014).
© Copyright Policy - open-access
Related In: Results  -  Collection

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Show All Figures
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Figure 2: Confocal microscopy and image analysis of double immunofluorescence for cyt C (a mitochondrial marker; green channel) and LC3 (for visualization of autophagosomes; red channel), carried out on primary mature hippocampal cultures (15 DIV) at 12 h post-infection (MOI 50) with mock- and myc-NH2 26-230 human tau vectors. Nuclei were stained with DAPI (blue channel). (A–C) Numerous labeled LC3 stained vesicles intensely positive (colocalized) for cyt C were observed in myc-NH2htau neurons. Arrows point to two large mitophagosomal structures. (G–I) LC3 immunofluorescence is very faint in mock-treated cultures (D–F); (J–L) colocalization analysis performed with ImageJ, including the spatial pattern of colocalized points of (D,J), the intensity height of the luminance in the colocalized points (E,K), the spatial profile of the fluorescence intensity for both fluorescence channels for the white line positioned on several mitophagosomes in the second row (F,L). Scale bar 7 μm. Figure referring to data from Amadoro et al. (2014).
Mentions: The mitochondria quality control regulates in post-mitotic neurons several vital metabolic functions such as their proper distribution to synaptic terminals, maintenance of electron transport chain (ETC) activity and electrical connectivity (Stowers et al., 2002; Verstreken et al., 2005; Chen and Chan, 2006; Liu and Shio, 2008; Bereiter-Hahn and Jendrach, 2010; Ferree and Shirihai, 2012; Misko et al., 2012), protection of mtDNA integrity (Westermann, 2002; Parone et al., 2008), apoptosis (Suen et al., 2008), formation and function of synapses and dendritic spines (Li et al., 2004). As other cell types, neuronal populations also continually modulate size and number of these organelles, according to the variable energy demands and metabolic states throughout the entire lifetime and/or different sub-cellular compartments (Chen and Chan, 2009; Santos et al., 2010; Vives-Bauza and Przedborski, 2011; Van Laar and Berman, 2013). However, a tight control of the interplay between their mitochondrial dynamic and bioenergetic status is of particular relevance for post-mitotic neurons because they have a unique metabolic as well as morphological profile which entails specialized and compartimentalized energetic needs. Indeed, neuronal populations are typically characterized by: (i) high bioenergetic needs as the ATP production classically depends in these cells on OxPhos respiration rather than glycolysis (Rolfe and Brown, 1997; Attwell and Laughlin, 2001; Mironov, 2009; Bolanos et al., 2010); (ii) a very polarized morphology with extensive neuritic projections which are crucial for neuronal survival via a proper maintenance of their mitochondrial biomass. Remarkably, although the human brain consists of only 2% of the volume of the body, it is roughly responsible for 25% of net oxygen consumption in resting conditions (Magistretti and Pellerin, 1999) with neurons generating as much as 95% of their ATP exclusively from mitochondrial OXPhos (Erecińska et al., 1994). However, it is worth noticing that neurons and astrocytes – which are the two major types of brain cells – exhibit a different preference for glucose utilization since its metabolism in neuron is diverted mainly to the pentose phosphate pathway in order to regenerate antioxidants (reduced glutathione) and to promote survival (Bolanos et al., 2010). As they constantly require an active and efficient defense mechanism against oxidative stress (Almeida et al., 2005; Herrero-Mendez et al., 2009), neuronal populations are indeed unable to switch to anaerobic glycolytic metabolism (as an ATP-generating mechanism) during an acute mitochondrial stress, relying on lactate as an alternative substrate for their mitochondria-derived bioenergetic purposes (Pellerin et al., 2007). In addition, it is generally assumed that only 0.2% of the neuronal cellular volume is in the cytoplasmic soma while about 99.8% is constituted by the axonal and dendritic compartments (Devor, 1999; Fjell and Walhovd, 2010; Florenzano, 2012). For instance, the axonal length of projection neurons – such as those of rat dopaminergic neurons that are localized in the substantia nigra which is an area selectively affected in PD – can be as long as 470 μm or more and can provide several axon collaterals each of them making in turn contacts with approximately 400 synapses (Matsuda et al., 2009). Besides, in order to locally provide ATP supply and calcium buffering required for the neuronal activity of high energy-demanding terminal synapses (Schon and Przedborski, 2011), an high number of mitochondria resides far away from soma being localized in distal axon and dendritic processes (Hollenbeck, 2005) such as presynaptic terminals, including the active zones where synaptics vesicles (SVs) are released (Rowland et al., 2000; Perkins et al., 2010), post-synaptic densities, nodes of Ranvier and in growth cones (Fabricius et al., 1993; Morris and Hollenbeck, 1993). Collectively, such peculiar requirements imply that a high number of mitochondria spend the majority of their time in traveling up-and-down between the sites of their biogenesis, which are mainly localized into cell bodies (Davis and Clayton, 1996; Saxton and Hollenbeck, 2012; Figure 2), and those of their functional utilization which instead are close to terminal endings (Li et al., 2004). Interestingly there’s a positive correlation between the frequency and/or the intensity of synapse electrical activity and the number of metabolically active mitochondria at presynaptic compartment (Dubinsky, 2009). Furthermore, provided that the mitochondria size and mass are not the same for all neurons (Dubinsky, 2009; Lu, 2009) and that intrinsic mitophagic capacity has been found to be brain region-specific (Diedrich et al., 2011), any perturbation in controlling the dynamics properties of these organelles (Verstreken et al., 2005; Kann and Kovács, 2007; Nunnari and Suomalainen, 2012) can seriously and selectively compromise their survival (Xue et al., 2001). Different morphologies and ultrastructural profiles of mitochondria have been also correlated with distinct bioenergetic demands of the tissues they occupy and mitochondrial network in neurons is demonstrated to be distinct from those of other tissues in morphology, interconnectivity as well as cytoplasmatic pattern distribution (Dubinsky, 2009; Kuznetsov et al., 2009; Mironov, 2009). Neurons critically depend on autophagy for differentiation and survival (Komatsu et al., 2006) and are particularly prone to autophagic stress (Chu, 2006) so that basal autophagy appears to be more efficient than in other proliferating non-neuronal cells types (Boland et al., 2008) and is also likely to be regulated in alternative and quite different ways (Ashrafi and Schwarz, 2013; Van Laar and Berman, 2013). Being terminally differentiated and producing high levels of ROS against relatively fewer antioxidant molecules (Cui et al., 2004; Fatokun et al., 2008), neurons need to refurbish “old” mitochondrial pool to prevent the deleterious accumulation of oxidative damage, as suggested by the fact that antioxidant treatment supports the survival of cerebellar Purkinje cells (PCs) from knockout mice for dynamin-1-like protein (Drp1) fission protein (Kageyama et al., 2012). In contrast, proliferating cells constantly generate “new” mitochondria during continuous cell replication cycles so that oxidative stress may be diluted and maintained at relatively low levels, even without any mitochondrial division (Kageyama et al., 2012). A proper interplay between the bioenergetic – which is mainly regulated by energy requirement and substrate availability – and the mitochondrial quality control and autophagy – which control the overall health of mitochondrial population and their relative abundance – is specifically critical in neurons as it impinges on their intrinsic resistance to stress and, then, on their survival. Indeed, the relative sensitivity of different neuronal populations to mitochondrial inhibitors is tightly correlated with their “spare respiratory capacity,” which is an index of general mitochondrial health taking into account the ratio of the glucose utilization rate to the expression level of respiratory chain complexes (Fern, 2003). Interestingly, the vulnerability to a complex I inhibitor such as rotenone of cultured striatal neurons, which are selectively affected in HD pathology, is primarily determined by their “spare respiratory capacity” rather than oxidative stress (Yadava and Nicholls, 2007). Likewise, presynaptic mitochondria from hippocampus and cortex show a lower spare respiratory capacity to rotenone when compared to non-synaptic mitochondria from the same regions (Davey et al., 1997), in favor with the finding that the bioenergetic failure of peripheral mitochondria in vivo initiates the loss of synaptic terminals in neurodegenerative diseases.

Bottom Line: Evidence suggests a striking causal relationship between changes in quality control of neuronal mitochondria and numerous devastating human neurodegenerative diseases, including Parkinson's disease, Alzheimer's disease, Huntington's disease, and amyotrophic lateral sclerosis.Contrary to replicating mammalian cells with a metabolism essentially glycolytic, post-mitotic neurons are distinctive owing to (i) their exclusive energetic dependence from mitochondrial metabolism and (ii) their polarized shape, which entails compartmentalized and distinct energetic needs.Here, we review the recent findings on mitochondrial dynamics and mitophagy in differentiated neurons focusing on how the exceptional characteristics of neuronal populations in their morphology and bioenergetics needs make them quite different to other cells in controlling the intracellular turnover of these organelles.

View Article: PubMed Central - PubMed

Affiliation: Institute of Translational Pharmacology - National Research Council Rome, Italy ; European Brain Research Institute Rome, Italy.

ABSTRACT
Evidence suggests a striking causal relationship between changes in quality control of neuronal mitochondria and numerous devastating human neurodegenerative diseases, including Parkinson's disease, Alzheimer's disease, Huntington's disease, and amyotrophic lateral sclerosis. Contrary to replicating mammalian cells with a metabolism essentially glycolytic, post-mitotic neurons are distinctive owing to (i) their exclusive energetic dependence from mitochondrial metabolism and (ii) their polarized shape, which entails compartmentalized and distinct energetic needs. Here, we review the recent findings on mitochondrial dynamics and mitophagy in differentiated neurons focusing on how the exceptional characteristics of neuronal populations in their morphology and bioenergetics needs make them quite different to other cells in controlling the intracellular turnover of these organelles.

No MeSH data available.


Related in: MedlinePlus