- Journal List
- bioRxiv
- PMC10827206
As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health.
Learn more: PMC Disclaimer | PMC Copyright Notice
Version 1. bioRxiv. Preprint. 2024 Jan 20.
PMCID: PMC10827206
PMID: 38293064
This is a preprint.
It has not yet been peer reviewed by a journal.
The National Library of Medicine is running a pilot to include preprints that result from research funded by NIH in PMC and PubMed.
Kanako Shinno,1 Yuri Miura,2 Koichi M. Iijima,3,4 Emiko Suzuki,1,5 and Kanae Ando1,6,*
Author information Copyright and License information PMC Disclaimer
The complete version history of this preprint is available at bioRxiv.
Associated Data
- Supplementary Materials
- Data Availability Statement
Summary
Neuronal aging and neurodegenerative diseases are accompanied by proteostasis collapse, while cellular factors that trigger it are not identified. Impaired mitochondrial transport in the axon is another feature of aging and neurodegenerative diseases. Using Drosophila, we found that genetic depletion of axonal mitochondria causes dysregulation of translation and protein degradation. Axons with mitochondrial depletion showed abnormal protein accumulation, and autophagic defects. Lowering neuronal ATP levels by blocking glycolysis did not reduce autophagy, suggesting that autophagic defects are associated with mitochondrial distribution. We found eIF2β was upregulated by depletion of axonal mitochondria via proteome analysis. Phosphorylation of eIF2α, another subunit of eIF2, was lowered, and global translation was suppressed. Neuronal overexpression of eIF2β phenocopied the autophagic defects and neuronal dysfunctions, and lowering eIF2β expression rescued those perturbations caused by depletion of axonal mitochondria. These results indicate the mitochondria-eIF2β axis maintains proteostasis in the axon, of which disruption may underly the onset and progression of age-related neurodegenerative diseases.
Keywords: Mitochondria, axonal transport, aging, neuronal proteostasis, protein aggregation, autophagy, Eukaryotic Initiation Factor 2β (eIF2β), Drosophila, neurodegeneration, proteome
Introduction
Neurons have a morphologically complex architecture composed of microcompartments and require tight regulation of the abundance of proteins and organelles spatially and temporally1. Such control of protein amounts, or proteostasis, is essential for neuronal functions2 and is achieved through the orchestration of protein expression, folding, trafficking, and degradation controlled by intrinsic and environmental signals3. Translation is initiated by the eukaryotic initiation factor 2 (eIF2) complex4. eIF2, a heterotrimer of α, β, and γ subunits, transports Met-tRNA to the ribosome in a GTP-dependent manner5. Under stressed conditions, phosphorylation of eIF2α attenuates global translation and initiates translation of mRNAs related to the integrated stress response (ISR)6. As for protein degradation, the autophagosome and proteasome are major systems that maintain proteostasis7. The proteasome degrade unnecessary proteins followed by regulated ubiquitination processes8, and autophagy removes damaged or harmful components, including large protein aggregates and organelles, through catabolism (selective autophagy)9. In addition to autophagy induced by acute stressors, a basal level of selective autophagy mediates the global turnover of damaged proteins10.
Such constitutive autophagy decreases during aging, which may underlie declines in the structural and functional integrity of neurons11. Decreased protein degradation and accumulation of abnormal proteins also contribute to increased risks of neurodegenerative diseases. Age-related neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s disease are often associated with the accumulation of misfolded proteins such as amyloid-β, tau, and α-synuclein12. Enhancement of autophagy mitigates age-related dysfunctions and neurodegeneration caused by proteotoxic stress13. However, it is not fully understood how aging disrupts the regulation of this constitutive autophagy.
Neurons are also highly energy-demanding. At nerve terminals, action potentials trigger the release of neurotransmitters via exocytosis of synaptic vesicles, which requires a constant supply of ATP and calcium buffering14. Such neuronal activity relies on mitochondrial functions15, and mitochondria are actively transported from their major sites of biogenesis in soma to axons16. However, the axonal transport of mitochondria declines during aging171819. Reduced axonal transport of mitochondria is thought to contribute to age-related declines in neuronal functions17192021. The number of functional mitochondria in synapses is reduced in the brains of patients suffering from age-related neurodegenerative diseases such as Alzheimer’s disease22, and mutations in genes involved in mitochondrial dynamics are linked to neurodegenerative diseases23. Mislocalization of mitochondria is sufficient to cause age-dependent neurodegeneration in Drosophila and mice24,25, indicating that the proper distribution of mitochondria is essential to maintain neuronal functions. Thus, depletion of functional mitochondria from axons and proteostasis collapse are common features of aging and neurodegenerative diseases.
Mitochondrial transport is regulated by a series of molecular adaptors that mediate the attachment of mitochondria to molecular motors16. In Drosophila, mitochondrial transport is mediated by milton and Miro, which attaches mitochondria to microtubules via kinesin heavy chain26,27. In the absence of milton or Miro, synaptic terminals and axons lack mitochondria, although mitochondria are numerous in the neuronal cell body28 . We previously reported that RNAi-mediated knock-down of milton or Miro in neurons causes reduction in axonal mitochondria, age-dependent locomotor defects29, and age-dependent neurodegeneration in neuropile area starting around 30 days after eclosion (day-old)24, and enhances axon degeneration caused by human tau proteins24. These results suggest that flies with neuronal knockdown of milton can be used as a model to analyze the effect of depletion of axonal mitochondria during aging. In this study, we investigated a causal relationship between mitochondrial distribution and neuronal proteostasis by using neuronal knockdown of milton. We found that depletion of axonal mitochondria reduced autophagy and increased accumulation of aggregated proteins in the axon prior to neurodegeneration. Proteome analysis and follow-up biochemical analyses revealed that neuronal knockdown of milton increased eIF2β levels. In addition, phosphorylation of eIF2α was lowered in the axon, and global translation was suppressed. Overexpression of eIF2β was sufficient to decrease autophagy and induce neuronal dysfunction, and genetic suppression of eIF2β restored autophagy and improved neuronal function in the milton knockdown background. These findings suggest that loss of axonal mitochondria and elevated levels of eIF2β mediate proteostasis collapse and neuronal dysfunction during aging.
Results
Depletion of axonal mitochondria by knockdown of milton or Miro causes protein accumulation in the axon
In Drosophila, mitochondrial transport is mediated by milton and Miro, which attaches mitochondria to microtubules via kinesin heavy chain26,27 (Figure 1A). It has been reported that expression of milton RNAi in neurons via pan-neuronal elav-GAL4 driver reduced milton protein levels in Drosophila head lysate to 40% and mito-GFP signals in axons to 50%29.
Knockdown of milton or Miro causes protein accumulationin the axon
(A) Schematic representation of the mitochondrial transport machinery. (B, C) Ubiquitinated proteins in brains with neuronal knockdown of milton or Miro. Brains dissected at 14 day-old (B) or 30 day-old (C) were immunostained with an antibody against ubiquitinated proteins. Firefly luciferase RNAi was used as a control. Representative images (left) and quantitation of the number of ubiquitin-positive puncta (right) are shown. Scale bars of hemibrains, 100 μm, Scale bars of magnifications, 10 μm. Means ± SE, n = 8. N.S., p > 0.05; ***p < 0.005 (one-way analysis of variance (ANOVA) followed by Tukey’s honestly significant difference (HSD) post hoc test). (D) Cross sections in the lamina and in the retina were used to analyze the ultrastructure of synapses and cell bodies, respectively. milton RNAi was expressed in the retina and neurons via a combination of GAL4 drivers, a pan-retinal gmr-GAL4 and pan-neuronal elav-GAL4. (E, F) Transmission electron micrographs of presynaptic terminals of photoreceptor neurons of control and milton knockdown flies. Photoreceptor axons are highlighted in blue. Swollen axons (asterisks in (E)) are observed in milton knockdown neurons. Scale bars, 2 μm. Representative images and quantitation are shown. In total, 918–1118 cells from cross-sections of the lamina from each half of the head were analyzed. Mean ± SE, n = 3. **p < 0.001 (Student’s t-test). (F) Dense materials (arrowheads) in synaptic terminals of milton knockdown neurons. Scale bars, 2 μm. (G) Cell bodies of photoreceptor neurons of control and milton knockdown flies. Scale bars, 2 μm. Flies were 27 day-old.
To test how loss of axonal mitochondria affects proteostasis in neurons, we first examined the accumulation of ubiquitinated proteins. At 14 day-old, more ubiquitinated proteins were deposited in the brains of milton knockdown flies than in those of age-matched control flies (Figure 1B, p < 0.005 between control RNAi and milton RNAi). Knockdown of Miro, a partner of milton, also resulted in more ubiquitin-positive puncta, but the difference was not significant (Figure 1B, p = 0.452 between control RNAi and Miro RNAi). These data suggest that the depletion of axonal mitochondria leads to accumulation of ubiquitinated proteins before neurodegeneration occurs.
It has been reported that ubiquitinated proteins accumulate with aging30; thus, we analyzed the accumulation of ubiquitinated proteins in aged brains (30 day-old) with milton knockdown. The number of puncta of ubiquitinated proteins did not significantly differ between control and milton knockdown flies or between control and Miro knockdown flies (Figure 1C, p > 0.05). Together with the effect of milton knockdown in 14-day old flies, this result suggests that depletion of axonal mitochondria accelerates the onset of age-related accumulation of ubiquitinated proteins.”
We examined the ultrastructure of synaptic terminals and cell bodies in photoreceptor neurons with milton knockdown by transmission electron microscopy in 27 day-old flies (Figure 1D). As previously reported24, axonal swelling was observed in these neurons (Figure 1E, asterisks). Some swollen axons in milton knockdown neurons contained dense materials, indicating abnormal protein accumulation in the axon (Figure 1F, arrowheads). In contrast, dense materials were not observed in cell bodies in the milton knockdown retina (Figure 1G). These results indicate that the depletion of axonal mitochondria induces protein accumulation in the axon.
Depletion of axonal mitochondria impairs protein degradation pathways
Since abnormal proteins were accumulated in milton knockdown brains, we next examined if protein degradation pathways were suppressed. We analyzed autophagy via western blotting of the autophagy markers LC3 and p6231. During autophagy progression, LC3 is conjugated with phosphatidylethanolamine to form LC3-II, which localizes to isolation membranes and autophagosomes. The LC3-II/LC3-I ratio was lower in the head lysate of milton knockdown flies than in that of control flies (Figure 2A). We also analyzed an autophagy substrate p62. Brain lysates were sequentially extracted using detergents with different stringencies (1% Triton X-100 and 2% SDS), and p62 was detected by western blotting32. The p62 level was increased in brains of 14 day-old milton knockdown flies (Figure 2B), indicating that autophagy is decreased in these brains. The increase in the p62 level was more prominent in the Triton X-100-soluble fraction than in the SDS-soluble fraction (Figure 2B), suggesting that depletion of axonal mitochondria impairs the degradation of less-aggregated proteins. We also analyzed proteasome activity. At 14 day-old, 20S proteasome activity was significantly decreased in brains with neuronal knockdown of milton (Figure 2C, p < 0.005). Autophagy was also reduced in the brains of milton knockdown flies at 30 day-old (Figure 2D). At this age, milton knockdown increased p62 in both fractions significantly (Figure 2E). Proteasome activities were also decreased in milton knockdown flies at 30 day-old (Figure 2F). These results indicate that depletion of axonal mitochondria impairs protein degradation pathways.
milton knockdown impairs protein degradation pathways
(A, B) Western blotting of head extracts of control and milton knockdown flies with antibodies against LC3 (A) and Ref2P, the fly homolog of mammalian p62 (B). For assessment of p62 levels, heads were extracted with 1% Triton X-100 or 2% SDS (B). Flies were 14 day-old. Representative blots (left) and quantitation (right) are shown. Actin was used as a loading control. Means ± SE, n = 6 (LC3), n = 3 (p62). (C) Proteasome activity in head extracts of control and milton knockdown flies was measured by hydrolysis of Suc-LLVY-AMC (chymotrypsin-like activity) at 14 day-old. Means ± SE, n =3. (D, E) Western blotting of head extracts of 30 day-old control and milton knockdown flies. Blotting was performed with anti-LC3 (D) and anti-p62 (E) antibodies. Representative blots (left) and quantitation (right) are shown. Actin was used as a loading control. Means ± SE, n = 6 (LC3), n = 3 (p62). (F) Proteasome activity in head extracts of 30-day-old control and milton knockdown flies was measured by hydrolysis of Suc-LLVY-AMC (chymotrypsin-like activity). Means ± SE, n = 3. N.S., p > 0.05; *p < 0.05; **p < 0.001; ***p < 0.005 (Student’s t-test).
ATP deprivation does not impair autophagy
milton knockdown downregulates ATP in the axon33. To examine whether the disruption of protein degradation pathways by milton knockdown is due to ATP deprivation, we investigated the effects of knocking down phosphofructokinase (Pfk), a rate-limiting enzyme in glycolysis, on protein degradation pathways. Neuronal knockdown of Pfk was reported to lower ATP levels in brain neurons33. Pfk knockdown and milton knockdown decreased ATP to similar levels (Figure 3A–C). However, in contrast with milton knockdown, Pfk knockdown did not affect the LC3-II/LC3-I ratio (Figure 3D) and decreased p62 level (Figure 3E), suggesting that autophagy is promoted. On the other hand, proteasome activity was decreased by Pfk knockdown (Figure 3F). These results suggest that the downregulation of axonal ATP upon depletion of axonal mitochondria decreases proteasome activity, but not autophagy.
ATP deprivation does not impair autophagy
(A-C) ATP levels in brain extracts of control and milton knockdown flies (A) and control and Pfk knockdown flies (B), and comparison of the effects of milton knockdown and Pfk knockdown on ATP levels (C). Flies were 14 day-old. Means ± SE, n = 3. (D, E) Western blotting of head extracts of flies with neuronal expression of control or Pfk RNAi. Blotting was performed with anti-LC3 (D) and anti-p62 (E) antibodies. For assessment of p62 levels, heads were extracted with 1% Triton X-100 or 2% SDS. Representative blots (left) and quantitation (right) are shown. Actin was used as a loading control. Means ± SE, n = 6 (LC3), n = 3 (p62). (F) Proteasome activity in head lysates of flies with neuronal expression of control or Pfk RNAi was measured by hydrolysis of Suc-LLVY-AMC (chymotrypsin-like activity). Means ± SE, n = 3. N.S., p > 0.05; *p < 0.05; **p < 0.001; ***p < 0.005 (Student’s t-test). Flies were at 14 day-old.
Proteome analysis suggests that depletion of axonal mitochondria causes disruption of autophagy and premature aging
To identify the pathways that mediate the decrease in autophagy in milton knockdown brains, we performed proteome analysis to systematically detect differentially expressed proteins upon neuronal knockdown of milton. We analyzed flies at 7 and 21 day-old, the age before autophagic defects are detected and the age just before the onset of neurodegeneration, respectively. (Figure 4A). 1039 proteins were detected by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Expression of 36 proteins was significantly increased (22 proteins) or decreased (14 proteins) by milton knockdown at 7 day-old (Tables 1 and S1). At 21 day-old, the expression of 41 proteins (31 upregulated and ten downregulated proteins) was significantly altered in milton knockdown flies compared with control flies (Tables 2 and S1). The “Interaction search” algorithm using KeyMolnet showed that proteins whose expression was significantly altered in the brains of milton knockdown flies at both 7 and 21 day-old were closely associated with the autophagic pathway (Tables 3 and 4, respectively). Proteins involved in pathways characteristic of aging, such as the immune response (Transcriptional regulation by STAT), cancer (Transcriptional regulation by SMAD, Transcriptional regulation by myc), longevity (Transcriptional regulation by FOXO, Sirtuin signaling pathway), and stress responses (HSP90 signaling pathway, MAPK signaling pathway)34,35, were enriched in the proteome profiles of milton knockdown flies compared with those of control flies (Tables 3 and 4), suggesting that depletion of axonal mitochondria accelerates aging in the brain.
milton knockdown upregulates eIF2β and decreases phosphorylation of eIF2α and translation
(A) Age of proteome analysis and phenotypes of milton knockdown flies. (B) A scatter plot of the log2 abundance ratio (x-axis) against the −log10 p-value (y-axis) of proteins at 7 day-old. (C) Western blotting of head extracts of flies expressing control or milton RNAi in neurons with an anti-eIF2β antibody. Flies were 14 day-old. Representative blots (left) and quantitation (right) are shown. Tubulin was used as a loading control. Means ± SE, n = 6. (D) eIF2β mRNA levels quantified by qRT-PCR. Means ± SE, n = 4. (E) A schematic representation of the axon (Lobe tips), the cell body region (Kenyon cells), and dendritic region (Calyxes) in the fly brain. Scale bars, 100μm. (F, G) Immunostaining with anti-eIF2α and anti-p-eIF2α antibodies. The mushroom body was identified by expression of mito-GFP. Scale bars, 20μm. The signal intensities of eIF2α and p-eIF2α in axons, dendrites, and cell bodies were quantified and are shown as ratios relative to the control. Means ± SE, n =12. (H) Representative polysome traces of head lysates of control and milton knockdown flies. (I) Western blotting of head lysates of control and milton knockdown flies fed puromycin alone or puromycin and cycloheximide (CHX) with an anti-puromycin antibody. Flies were 14 day-old. Actin was used as a loading control. Representative blots (left) and quantitation (right) are shown. Means ± SE, n = 3. N.S., p > 0.05; *p < 0.05; ***p < 0.005 (Student’s t-test).
Table 1 :
Differentially expressed proteins in milton RNAi fly brains compared to control at 7 day-old detected by proteome analysis
7 day-old | |||
---|---|---|---|
Accessiona | Name | Abundance Ratio | Abundance Ratio P-Value |
Q9V751 | Attacin-B | 100 | 1E-17 |
Q04448 | Bifunctional methylenetetrahydrofolate dehydrogenase/cyclohydrolase, mitochondrial | 100 | 1E-17 |
P22700 | Calcium-transporting ATPase sarcoplasmic/endoplasmic reticulum type | 100 | 1E-17 |
Q9V558 | Cytochrome P450 4p1 | 100 | 1E-17 |
P10552 | FMRFamide-related peptides | 100 | 1E-17 |
P05661-19 | Isoform F of Myosin heavy chain, muscle | 100 | 1E-17 |
Q9VE01 | Probable cytochrome P450 12a5, mitochondrial | 100 | 1E-17 |
Q7KIN0 | Toll-like receptor 7 | 100 | 1E-17 |
Q8MKN0 | Ubiquinone biosynthesis protein COQ9, mitochondrial | 100 | 1E-17 |
Q9VJG0 | Xaa-Pro aminopeptidase ApepP | 100 | 1E-17 |
Q9V8F5 | Bomanin Bicipital 1 | 4.908 | 1E-17 |
P07701 | Salivary glue protein Sgs-5 | 2.843 | 1.9925E-09 |
O76902 | Pleckstrin homology domain-containing family F member 1 homolog | 2.836 | 2.2204E-16 |
P81641 | Alpha-amylase B | 2.684 | 7.4485E-09 |
P19351-4 | Isoform 4 of Troponin T, skeletal muscle | 2.66 | 6.6556E-11 |
Q9VTJ8 | Mitochondrial import inner membrane translocase subunit TIM14 | 2.61 | 3.5421E-07 |
P41375 | Eukaryotic translation initiation factor 2 subunit 2 | 2.465 | 3.3849E-09 |
Q9VYB0 | Selenoprotein BthD | 2.462 | 2.2558E-08 |
B7Z0W9 | Proton channel OtopLc | 2.382 | 1.7174E-06 |
Q9VLR5 | RNA polymerase II transcriptional coactivator | 2.245 | 6.7024E-09 |
Q8IN44 | Protein Turandot A | 2.127 | 8.3866E-13 |
P27779 | Pupal cuticle protein Edg-78E | 2.113 | 1.0021E-08 |
Q9W1X8 | Probable GDP-L-fucose synthase | 0.496 | 2.126E-08 |
P55035 | 26S proteasome non-ATPase regulatory subunit 4 | 0.487 | 5.5016E-11 |
Q9VHN6 | 39S ribosomal protein L19, mitochondrial | 0.487 | 0.00055134 |
Q9VPD2 | Cytosolic Fe-S cluster assembly factor NUBP2 homolog | 0.46 | 6.3451E-05 |
Q9VHD3 | Probable maleylacetoacetate isomerase 1 | 0.432 | 4.5096E-06 |
Q94529 | Probable pseudouridine-5’-phosphatase | 0.416 | 1.088E-14 |
Q27606 | Cytochrome P450 4e2 | 0.398 | 4.1313E-10 |
Q24388 | Larval serum protein 2 | 0.378 | 1.3323E-14 |
Q9VKH6 | Lysosomal thioesterase PPT2 homolog | 0.369 | 2.0523E-06 |
Q24114 | Division abnormally delayed protein | 0.307 | 2.2441E-09 |
Q95NH6 | Attacin-C | 0.01 | 1E-17 |
P29993 | Inositol 1,4,5-trisphosphate receptor | 0.01 | 1E-17 |
Q94526 | Open rectifier potassium channel protein 1 | 0.01 | 1E-17 |
Q9Y115 | UNC93-like protein | 0.01 | 1E-17 |
21 day-old | |||
Accessiona | Name | Abundance Ratio | Abundance Ratio P-Value |
Q10714 | Angiotensin-converting enzyme | 100 | 1E-17 |
C0HKQ8 | Cecropin-A2 | 100 | 1E-17 |
Q9V558 | Cytochrome P450 4p1 | 100 | 1E-17 |
P51592 | E3 ubiquitin-protein ligase hyd | 100 | 1E-17 |
Q9VMJ7 | Lysine-specific demethylase lid | 100 | 1E-17 |
Q9VXP4 | Platelet-activating factor acetylhydrolase IB subunit beta homolog | 100 | 1E-17 |
Q9VY28 | Probable 28S ribosomal protein S25, mitochondrial | 100 | 1E-17 |
Q9W391 | Probable phosphorylase b kinase regulatory subunit alpha | 100 | 1E-17 |
Q9VUQ5 | Protein argonaute-2 | 100 | 1E-17 |
P54359 | Septin-2 | 100 | 1E-17 |
P24492 | Diptericin A | 15.716 | 1E-17 |
Q9VVY3 | Glycogen-binding subunit 76A | 8.986 | 1E-17 |
Q70PY2 | Peptidoglycan-recognition protein SB1 | 6.669 | 1E-17 |
Q9W0M1 | Centrosomal protein cep290 | 6.526 | 1E-17 |
P81641 | Alpha-amylase B | 5.722 | 1E-17 |
P45884 | Attacin-A | 4.997 | 1E-17 |
C0HL66 | Histone H3.3A | 4.778 | 1E-17 |
P26675 | Protein son of sevenless | 4.696 | 1E-17 |
P02515 | Heat shock protein 22 | 4.69 | 1E-17 |
Q95NH6 | Attacin-C | 4.35 | 1E-17 |
P17971-1 | Isoform A of Potassium voltage-gated channel protein Shal | 4.195 | 1E-17 |
Q7K1U0 | Activity-regulated cytoskeleton associated protein 1 | 3.271 | 1E-17 |
P14199 | Protein ref(2)P | 3.014 | 1E-17 |
Q9VU02 | Probable small nuclear ribonucleoprotein Sm D1 | 2.43 | 4.91607E-13 |
Q9VD44 | Poly(A) RNA polymerase gld-2 homolog A | 2.268 | 2.6084E-11 |
Q9V8F5 | Bomanin Bicipital 1 | 2.24 | 5.16671E-11 |
P22979 | Heat shock protein 67B3 | 2.223 | 7.90048E-11 |
P27779 | Pupal cuticle protein Edg-78E | 2.192 | 1.65944E-10 |
Q9NBK5 | Serine/threonine-protein kinase tricornered | 2.059 | 4.15071E-09 |
Q8MLZ7 | Chitinase-like protein Idgf3 | 2.055 | 4.61182E-09 |
Q9V751 | Attacin-B | 2.038 | 6.79416E-09 |
Q9V8M5 | Probable 3-hydroxyisobutyrate dehydrogenase, mitochondrial | 0.492 | 7.42952E-09 |
P84345 | ATP synthase protein 8 | 0.421 | 1.809E-12 |
P33438 | Glutactin | 0.414 | 6.13731E-13 |
Q8IN44 | Protein Turandot A | 0.218 | 1E-17 |
Q8IN43 | Protein Turandot C | 0.195 | 1E-17 |
Q9VFI9 | cGMP-specific 3’,5’-cyclic phosphodiesterase | 0.01 | 1E-17 |
Q94526 | Open rectifier potassium channel protein 1 | 0.01 | 1E-17 |
Q9VHD3 | Probable maleylacetoacetate isomerase 1 | 0.01 | 1E-17 |
Q9W0A0 | Protein draper | 0.01 | 1E-17 |
A1Z7T0 | Serine/threonine-protein kinase N | 0.01 | 1E-17 |
aUniProt accession number
Table 2 :
Molecule networks based on “Interaction search” of KeyMolnet
7 day-old | |||||
---|---|---|---|---|---|
Rank | Name | Score | Score (p) a | Score (v) b | Score (c) c |
1 | Autophagy-related protein signaling pathway | 50.394 | 6.76E-16 | 0.159 | 0.11 |
2 | Calcium signaling pathway | 47.583 | 4.75E-15 | 0.146 | 0.117 |
3 | Transcriptional regulation by SMAD | 44.012 | 5.64E-14 | 0.146 | 0.095 |
4 | GABA signaling pathway | 40.706 | 5.58E-13 | 0.122 | 0.123 |
5 | estrogen signaling pathway | 37.507 | 5.12E-12 | 0.11 | 0.13 |
6 | Sirtuin signaling pathway | 36.87 | 7.96E-12 | 0.122 | 0.095 |
7 | Transcriptional regulation by AP-1 | 34.874 | 3.18E-11 | 0.11 | 0.107 |
8 | Arrestin signaling pathway | 32.84 | 1.30E-10 | 0.11 | 0.092 |
9 | G protein (Gq/11) signaling pathway | 30.889 | 5.03E-10 | 0.085 | 0.149 |
10 | Kainate receptor signaling pathway | 30.049 | 9.00E-10 | 0.073 | 0.214 |
11 | Transcriptional regulation by C/EBP | 29.5 | 1.32E-09 | 0.098 | 0.093 |
12 | Calpain signaling pathway | 28.597 | 2.46E-09 | 0.11 | 0.066 |
13 | Phospholipase D signaling pathway | 28.344 | 2.94E-09 | 0.098 | 0.084 |
14 | HSP90 signaling pathway | 27.188 | 6.54E-09 | 0.085 | 0.104 |
14 | CYP family | 27.188 | 6.54E-09 | 0.085 | 0.104 |
16 | Kir3 channel signaling pathwa | 26.495 | 1.06E-08 | 0.061 | 0.25 |
17 | Estrogen biosynthesis | 26.107 | 1.38E-08 | 0.061 | 0.238 |
18 | CaSR signaling pathway | 25.39 | 2.27E-08 | 0.061 | 0.217 |
19 | PI3K signaling pathway | 24.927 | 3.14E-08 | 0.073 | 0.122 |
20 | PAF receptor signaling pathway | 24.555 | 4.06E-08 | 0.049 | 0.4 |
21 | Transcriptional regulation by PPARa | 24.398 | 4.52E-08 | 0.073 | 0.115 |
21 | BTK signaling pathway | 24.398 | 4.52E-08 | 0.073 | 0.115 |
23 | Transcriptional regulation by STAT | 24.076 | 5.66E-08 | 0.085 | 0.077 |
24 | G protein (Gi/o) signaling pathway | 24.063 | 5.71E-08 | 0.073 | 0.111 |
25 | PARP signaling pathway | 23.742 | 7.13E-08 | 0.073 | 0.107 |
25 | mGluR signaling pathway | 23.742 | 7.13E-08 | 0.073 | 0.107 |
27 | Free fatty acid signaling pathway | 23.433 | 8.83E-08 | 0.073 | 0.103 |
28 | Kir channel signaling pathway | 23.338 | 9.43E-08 | 0.061 | 0.167 |
29 | Oxytocin signaling pathway | 23.327 | 9.51E-08 | 0.049 | 0.333 |
30 | Transcriptional regulation by MEF2 | 22.99 | 1.20E-07 | 0.073 | 0.098 |
31 | S100 family signaling pathway | 22.434 | 1.77E-07 | 0.073 | 0.092 |
32 | Transcriptional regulation by FOXO | 22.301 | 1.94E-07 | 0.073 | 0.091 |
33 | P2Y signaling pathway | 22.172 | 2.12E-07 | 0.061 | 0.143 |
34 | Transcriptional regulation by SRF | 21.174 | 4.23E-07 | 0.061 | 0.125 |
34 | ATF4/ATF6/IRE1 signaling pathway | 21.174 | 4.23E-07 | 0.061 | 0.125 |
36 | Chemerin signaling pathway | 21.082 | 4.50E-07 | 0.049 | 0.235 |
36 | Vasopressin signaling pathway | 21.082 | 4.50E-07 | 0.049 | 0.235 |
38 | Serotonin signaling pathway | 20.854 | 5.28E-07 | 0.073 | 0.077 |
39 | Transcriptional regulation by HIF | 20.834 | 5.35E-07 | 0.098 | 0.043 |
40 | Leukotriene receptorsignaling pathway | 20.724 | 5.78E-07 | 0.049 | 0.222 |
40 | CART signaling pathway | 20.724 | 5.78E-07 | 0.049 | 0.222 |
42 | MAPK signaling pathway | 20.693 | 5.90E-07 | 0.085 | 0.055 |
43 | Transcriptional regulation by RB/E2F | 20.543 | 6.55E-07 | 0.098 | 0.042 |
44 | NAD metabolism | 20.468 | 6.89E-07 | 0.061 | 0.114 |
45 | ERK signaling pathway | 20.425 | 7.11E-07 | 0.073 | 0.073 |
46 | Adenylyl Cyclase signaling pathway | 20.303 | 7.73E-07 | 0.061 | 0.111 |
47 | Bile acid signaling pathway | 20.141 | 8.65E-07 | 0.061 | 0.109 |
21 day-old | |||||
Rank | Name | Score | Score (p) a | Score (v) b | Score (c) c |
1 | Histone demethylation | 84.198 | 4.51E-26 | 0.102 | 0.425 |
2 | CDK inhibitor signaling pathway | 56.497 | 9.83E-18 | 0.078 | 0.295 |
3 | Transcriptional regulation by RB/E2F | 46.598 | 9.39E-15 | 0.108 | 0.095 |
4 | Mst(Hippo) signaling pathway) | 46.343 | 1.12E-14 | 0.09 | 0.133 |
5 | Transcriptional regulation by androgen receptor | 46.078 | 1.35E-14 | 0.078 | 0.178 |
6 | p160 SRC signaling pathway | 45.809 | 1.62E-14 | 0.078 | 0.176 |
7 | Transcriptional regulation by SMAD | 43.961 | 5.84E-14 | 0.09 | 0.119 |
8 | Autophagy-related protein signaling pathway | 41.063 | 4.35E-13 | 0.084 | 0.119 |
9 | Transcriptional regulation by HIF | 39.527 | 1.26E-12 | 0.096 | 0.086 |
10 | Nucleophosmin signaling pathway | 38.417 | 2.72E-12 | 0.054 | 0.273 |
11 | HSP90 signaling pathway | 37.887 | 3.93E-12 | 0.066 | 0.164 |
12 | PAF metabolism | 37.562 | 4.93E-12 | 0.042 | 0.5 |
13 | Transcriptional regulation by STAT | 37.276 | 6.01E-12 | 0.072 | 0.132 |
14 | BcI-2 family signaling pathway | 36.157 | 1.31E-11 | 0.072 | 0.124 |
15 | Sirtuin signaling pathway | 34.782 | 3.39E-11 | 0.072 | 0.114 |
16 | Transcriptional regulation by C/EBP | 33.819 | 6.60E-11 | 0.066 | 0.128 |
17 | PIN1 signaling pathway | 33.172 | 1.03E-10 | 0.06 | 0.149 |
18 | RSK signaling pathway | 30.566 | 6.29E-10 | 0.06 | 0.125 |
19 | Transcriptional regulation by High mobility group protein | 29.873 | 1.02E-09 | 0.054 | 0.148 |
20 | BET family signaling pathway | 29.656 | 1.18E-09 | 0.054 | 0.145 |
21 | Transcriptional regulation by Myc | 28.838 | 2.08E-09 | 0.066 | 0.093 |
22 | Transcriptional regulation by FOXO | 28.827 | 2.10E-09 | 0.054 | 0.136 |
23 | PSD-95 family signaling pathway | 26.154 | 1.34E-08 | 0.048 | 0.14 |
24 | AKT signaling pathway | 25.169 | 2.65E-08 | 0.048 | 0.129 |
25 | Arginine methylation | 24.799 | 3.43E-08 | 0.048 | 0.125 |
26 | gp130 signaling pathway | 24.25 | 5.01E-08 | 0.054 | 0.096 |
27 | Transcriptional regulation by CREB | 23.858 | 6.58E-08 | 0.066 | 0.067 |
28 | Gene regulation by microRNAs (metastasis) | 23.852 | 6.60E-08 | 0.054 | 0.093 |
29 | HDAC signaling pathway | 23.536 | 8.22E-08 | 0.036 | 0.207 |
30 | Calpain signaling pathway | 23.092 | 1.12E-07 | 0.06 | 0.074 |
31 | Transcriptional regulation by IRF | 22.738 | 1.43E-07 | 0.054 | 0.085 |
32 | 2-Oxoglutarate signaling pathway | 22.673 | 1.50E-07 | 0.048 | 0.104 |
32 | 14-3-3 signaling pathway | 22.673 | 1.50E-07 | 0.048 | 0.104 |
34 | Transcriptional regulation by POU domain factor | 22.601 | 1.57E-07 | 0.06 | 0.071 |
35 | Transcriptional regulation by BLIMP-1 | 22.474 | 1.72E-07 | 0.042 | 0.132 |
36 | Gene regulation by microRNAs (metabolism) | 22.39 | 1.82E-07 | 0.054 | 0.083 |
37 | Fatty acid beta oxidation | 22.096 | 2.23E-07 | 0.042 | 0.127 |
38 | Transcriptional regulation by RXR | 22.08 | 2.26E-07 | 0.036 | 0.176 |
39 | ERK signaling pathway | 21.96 | 2.45E-07 | 0.048 | 0.098 |
40 | PARP signaling pathway | 21.913 | 2.53E-07 | 0.042 | 0.125 |
41 | Transcriptional regulation by VDR | 21.618 | 3.11E-07 | 0.054 | 0.078 |
42 | Transcriptional regulation by p53 | 21.168 | 4.24E-07 | 0.072 | 0.05 |
43 | Acetylcholine metabolism | 21.152 | 4.29E-07 | 0.024 | 0.444 |
44 | Gene regulation by microRNAs (embryonic stem cells) | 21.08 | 4.51E-07 | 0.036 | 0.158 |
45 | mTOR signaling pathway | 21.048 | 4.61E-07 | 0.042 | 0.115 |
46 | Gene regulation by microRNAs (cancer) | 21.04 | 4.64E-07 | 0.048 | 0.09 |
47 | Transcriptional regulation by Ets-1/2 | 20.724 | 5.77E-07 | 0.042 | 0.111 |
48 | MAPK signaling pathway | 20.411 | 7.18E-07 | 0.054 | 0.07 |
49 | Gene regulation by microRNAs (cell cycle) | 20.404 | 7.21E-07 | 0.036 | 0.146 |
50 | Transcriptional regulation by p73 | 20.259 | 7.97E-07 | 0.042 | 0.106 |
aScore(p) indicates p-value of the pathway.
bScore(v) indicates the ratio of “Count” to total molecules associated with the loaded list.
cScore(c) indicates the ratio of “Count” to total molecules contained in the pathway.
Depletion of axonal mitochondria upregulates eIF2β and decreases phosphorylation of eIF2α and translation
Differentially expressed proteins in 7 day-old flies may reflect alterations that are causal for autophagic defects. We noticed that the expression level of eIF2β was 2.465-fold higher in the brains of milton knockdown flies than in those of control flies (Figure 4B). Upregulation of eIF2β in the brains of milton knockdown flies was confirmed by western blotting. milton knockdown upregulated eIF2β protein levels more than twice (Figure 4C), but did not change the level of eIF2β mRNA (Figure 4D). eIF2β is a subunit of the eukaryotic initiation factor 2 (eIF2) complex, which is critical for translation initiation and the integrated stress response (ISR)4. eIF2 is a heterotrimer of α, β, and γ subunits, and during the ISR, eIF2α is phosphorylated6. To characterize the effect of milton knockdown on the eIF2α, we analyzed the levels of eIF2α and p-eIF2α in the brain. Western blotting of brain lysates showed that milton knockdown reduced eIF2α levels, but p-eIF2α levels were not significantly affected (Figure S1). To analyze local changes of eIF2α and p-eIF2α, we carried out immunostaining. We focused on the mushroom body, where axons, dendrites, and cell bodies can be easily identified (Figure 4E). Both eIF2α and p-eIF2α were downregulated in the cell body (Kenyon cells) and dendritic (Calyxes) regions of the brains of milton knockdown flies (Figure 4F). In axons (lobe tips), milton knockdown did not downregulate eIF2α (Figure 4G, p = 0.271) but significantly downregulated p-eIF2α (Figure 4G). The ratio of p-eIF2α to eIF2α was lower in the axon but not in the soma or dendritic region.
Downregulation of p-eIF2α alters global translation36. We performed polysome gradient centrifugation to examine the level of ribosome binding to mRNA. In the brains of milton knockdown flies, the level of mRNAs associated with polysomes was reduced (Figure 5H), as expected upon downregulation of p-eIF2α. We also compared the level of translation between the brains of control and milton knockdown flies by assessing the incorporation of puromycin (Figure 4I). Puromycin incorporation was lower in the brains of milton knockdown flies than in those of control flies (Figure 4I, indicated by a bracket). These data indicate that depletion of axonal mitochondria disrupts eIF2 functions in axons and suppresses global translation.
eIF2β upregulation impairs autophagy and decreases locomotor function
(A) eIF2β mRNA levels in head extracts of flies with UAS-eIF2β driven by elav-Gal4 (eIF2β OE) or UAS-GFP driven by elav-Gal4 (control) were quantified by qRT-PCR. Flies were 2–3 day-old. Means ± SE, n=4. (B-C) Western blotting of head extracts with anti-LC3 (B) and anti-p62 (C) antibodies. Flies were 14 day-old. Representative blots (left) and quantitation (right) are shown. Tubulin and actin were used as loading controls. Means ± SE, n = 3 (p62), n = 5 (LC3). (D) Climbing assay revealed early-onset age-dependent locomotor defects in eIF2β-overexpressing flies. Means ± SE, n = 5. N.S., p > 0.05; ***p < 0.005 (Student’s t-test).
eIF2β upregulation reduces the level of p-eIF2α, impairs autophagy, and decreases locomotor function
We were motivated to ask if eIF2β upregulation mediates autophagic defects caused by milton knockdown. If so, neuronal overexpression of eIF2β would also induce autophagy impairment. Neuronal overexpression of eIF2β did not affect the LC3-II/LC3-I ratio (Figure 5A and andB).B). However, overexpression of eIF2β significantly increased the p62 level in the Triton X-100-soluble fraction (Figure 5C, 4-fold vs. control, p < 0.005 (1% PBST)). The p62 level in the SDS-soluble fraction was not significantly affected (Figure 5C, 2-fold vs. control, p = 0.062 (2% SDS)), as observed in brains of milton knockdown flies (Figure 2B). Neuronal overexpression of eIF2β did not affect the eIF2α level but significantly decreased the p-eIF2α level (Figure S2).
Depletion of axonal mitochondria causes an age-dependent decline in locomotor function24, which we also observed in flies with neuronal overexpression of eIF2β (Figure 5D). Locomotor functions were significantly impaired in those flies at 20 day-old and worsened further during aging (Figure 5D, compare 4, 20, and 30 day-old).
These data indicate that upregulation of eIF2β in neurons phenocopies depletion of axonal mitochondria, including suppression of autophagy, and age-dependent locomotor dysfunction, suggesting that upregulation of eIF2β mediates these phenotypes downstream of loss of axonal mitochondria.
Lowering eIF2β rescues autophagic impairment and locomotor dysfunction induced by milton knockdown
Finally, we investigated whether suppression of eIF2β rescues autophagy impairment and locomotor dysfunction caused by neuronal knockdown of milton. Null mutants and flies with RNAi-mediated knockdown of eIF2β in neurons did not survive. Flies lacking one copy of the eIF2β gene survived without any gross abnormality, and the level of eIF2β mRNA in these flies was about 80% of that in control flies (Figure 6A). eIF2β heterozygosity did not affect the eIF2α and p-eIF2α levels (Figure S3 A and B). However, the LC3-II/LC3-I ratio was significantly lower in milton knockdown flies with eIF2β heterozygosity than in flies with milton knockdown alone (Figure 6B). Reduction of eIF2β expression decreased the p62 level in the Triton X-100-soluble fraction, but not the SDS-soluble fraction, in the brains of milton knockdown flies (Figure 6C). Given that milton knockdown increased the p62 level in the Triton X-100-soluble fraction but not in the SDS-soluble fraction (Figure 2B), these results indicate that suppression of eIF2β ameliorates the impairment of autophagy caused by milton knockdown.
Lowering eIF2β rescues autophagic impairment and locomotor dysfunction induced by milton knockdown
(A) eIF2β mRNA levels with one disrupted copy of the eIF2β gene (eIF2βSAstopDsRed/+ (eIF2β −/+)). Head extracts of flies 2–3 day-old were analyzed by qRT-PCR. Means ± SE, n = 3. (B, C) Western blotting of head extracts of flies with neuronal expression of milton RNAi with or without eIF2β heterozygosity with anti-LC3 (B) and anti-p62 (C) antibodies. Flies were 14 day-old. Representative blots (left) and quantitation (right) are shown. Actin was used as a loading control. Means ± SE, n = 5 (LC3), n = 3 (p62). (D) The climbing ability of 20 day-old flies expressing milton RNAi with or without eIF2β heterozygosity. Means ± SE, n = 15. N.S., p > 0.05; *p < 0.05; ***p < 0.005 (Student’s t-test).
eIF2β heterozygosity also rescued locomotor dysfunction induced by milton knockdown. milton knockdown flies with eIF2β heterozygosity exhibited better locomotor function than milton knockdown alone (Figure 6D). The milton mRNA level was not increased in these flies, indicating that the rescue effect in the eIF2β heterozygous background was not mediated by an increased milton mRNA level (Figure S3D). These data suggest that eIF2β upregulation mediates autophagy impairment and locomotor dysfunction caused by depletion of axonal mitochondria.
Discussion
Proteostasis perturbations trigger the formation of pathological aggregates and increase the risks of neurodegenerative diseases during aging. By using neuronal knockdown as a tool to deplete mitochondria from the axon, we provide evidence that loss of axonal mitochondria drives age-related proteostasis collapse via eIF2β (Figure 7). We observed declines in autophagy-mediated degradation of less-aggregated proteins and proteasome activity in milton knockdown flies (Figure 2). Accumulation of ubiquitinated proteins and changes in age-related pathways started prematurely in milton knockdown flies (Figure 1 and and5).5). milton knockdown upregulated eIF2β and downregulated eIF2α phosphorylation (Figure 4). Overexpression of eIF2β phenocopied the effects of milton knockdown, including reduced autophagy and accelerated age-related locomotor defects (Figure 5). Furthermore, lowering eIF2β levels suppressed the impairment of autophagy and locomotor dysfunction induced by milton knockdown (Figure 6). Our results suggest that mitochondrial distribution and eIF2β are part of the mechanisms constituting proteostasis. milton knockdown causes loss of mitochondria in the axon and accumulation of mitochondria in the soma. Thus, accumulation of mitochondria may also have detrimental effects. However, degeneration induced by milton knockdown is prominent in the axon and not detected in the cell body24. Furthermore, abnormal protein accumulation was observed in the axon (Figure 1F) and p-eIF2α/eIF2α was decreased in the neurites but not in the soma (Figure 4F and andG).G). These results suggest that proteostasis defects observed in these flies are caused by depletion of mitochondria in the axon rather than accumulation of mitochondria in the soma.
A schematic representation of the mitochondria-eIF2β axis in the axon to maintain neuronal proteostasis during aging
Our results revealed that eIF2β regulates proteostasis via autophagy and neuronal function during aging. eIF2β is a component of eIF2, which meditates translational regulation and ISR initiation. When ISR is activated, eIF2α phosphorylation suppresses global translation and induces translation of ATF4, which mediates transcription of autophagy-related genes37,38. In milton knockdown neurons, however, both eIF2α and global translation were reduced. Increased levels of eIF2β may disrupt eIF2 complex and its functions. We found that eIF2β upregulation reduced the levels of p-eIF2α (Figure S2), indicating that eIF2β negatively regulates eIF2α. Thus, impairment of autophagy caused by depletion of axonal mitochondria may be due to impairment of ISR. It is also possible that eIF2β mediates autophagy defects via mechanisms independent of ISR, since eIF2β has functions independent of eIF239,40. For example, suppression of eIF2β has been reported to slow down cancer cell growth39. In developing neurons, eIF2β can directly interact with the translational repressor Kra to regulate midline axon guidance40. However, to our knowledge, the roles of eIF2β in aging have not been reported. Our results revealed a novel function of eIF2β to maintain proteostasis during aging.
How depletion of axonal mitochondria upregulates eIF2β is currently under investigation. A major mitochondrial function is ATP production, and depletion of axonal mitochondria downregulates ATP in axons33. However, we found that ATP deprivation does not always suppress autophagy (Figure 3), suggesting it is unlikely to be involved in the mechanisms that induce eIF2β upregulation. Mitochondria also serve as signaling hubs for translation and protein degradation. Mitochondrial proteins are regulated by co-translational protein quality control, and mitochondrial damage induces translational stalling of mitochondrial outer membrane-associated complex-I 30 kD subunit (C-I30) mRNA41. Additionally, the mitochondrial outer membrane ubiquitin ligase MITOL (also known as MARCHF5) ubiquitinates and regulates not only mitochondrial proteins such as Mfn242 but also microtubule-associated43 and endoplasmic reticulum44 proteins. These findings indicate that mitochondria serve as local signaling centers for proteostasis maintenance and eIF2β levels may also be regulated by mechanisms related to mitochondria.
In conclusion, our results suggest that axonal mitochondria and eIF2β form an axis to maintain constitutive autophagy. Suppression of eIF2β rescued autophagic defects and neuronal dysfunction upon loss of axonal mitochondria. Since eIF2β is conserved across many species, including Drosophila and humans, our results suggest that eIF2β may be a possible therapeutic target for aging and diseases associated with mitochondrial mislocalization.
Materials and methods
Fly stocks and husbandry
Flies were maintained in standard cornmeal medium (10% glucose, 0.7% agar, 9% cornmeal, 4% yeast extract, 0.3% propionic acid and 0.1% n-butyl p-hydroxybenzoate) at 25°C under light–dark cycles of 12:12 h. The flies were transferred to fresh food vials for every 2–3 days. UAS-milton RNAi (v41508) was from VDRC and outcrossed to [w1118] for five generations in our laboratory. Transgenic fly lines carrying UAS-luciferase RNAi control for milton RNAi) was reported previously24. GMR-gal4, Elav-gal4, UAS-Pfk RNAi (Bloomington stock center #36782), UAS-luciferase RNAi (Bloomington stock center #31603) (control for Pfk RNAi), UAS-GFP (used for control for UAS-eIF2β) and UAS-eIF2β (eIF2βEY08063, Bloomington stock center #17425) were from the Bloomington stock center. eIF2β heterozygous strain (PBac{SAstopDsRed} LL07719, DGRC#142114) was from KYOTO Drosophila Stock Center. UAS-mitoGFP was a kind gift from Drs. W. M. Saxton (University of California, Santa Cruz).
Immunohistochemistry and image acquisition
Fly brains were dissected in PBS and fixed for 45 minutes in formaldehyde (4% v/v in PBS) at room temperature. After incubation in PBST containing 0.1% Triton X-100 for 10 min for three times, samples were incubated for 1h at room temperature in PBST containing 1% normal goat serum (Wako, Cat# 143-06561) and then incubated overnight with the primary antibody (anti-ubiquitin antibody Ubi-1 (1:50), anti-eIF2α (1:50) and anti-p-eIF2α (1:50)) diluted in 1% NGS/PBST at 4 °C. Samples were then washed for 10 min with PBST including 0.1% Triton X-100 three times and incubated with the secondary antibody for overnight at 4° C. Brains were mounted in Vectashield (Vectorlab Cat#H-1100) and analyzed under a confocal microscope (Nikon).
Electron microscopy
Proboscis was removed from decapitated heads, which were then incubated in primary fixative solution (2.5% glutaraldehyde and 2% paraformaldehyde in 0.1 M sodium cacodylate buffer) at R.T. for 2 hours. After washing heads with 3% sucrose in 0.1 M sodium cacodylate buffer, fly heads were post-fixed for 1 hour in secondary fixation (1% osmium tetroxide in 0.1 M sodium cacodylate buffer) on ice. After washing with H2O, heads were dehydrated with ethanol and infiltrated with propylene oxide and Epon mixture (TAAB and Nissin EM) for 3 hours. After infiltration, specimens were embedded with Epon mixture at 70°C for 2~3 days. Thin-sections (70 nm) of laminas were collected on copper grids. The sections were stained with 5% uranyl acetate in 50% ethanol and Reynolds’ lead citrate solution. Electron micrographs were obtained with a CCD Camera mounted) on a JEM-1400 plus electron microscope (Jeol Ltd.).
SDS–PAGE and immunoblotting
Western blotting was performed as reported previously24. Briefly, heads of 10-20 Drosophila were homogenized with SDS-Tris-Glycine sample buffer (0.312M Tris, 5% SDS, 8% glycerol, 0.0625% BPB, 10% β-mercaptoethanol, 10μ/mL leupeptin, 0.4 μM Pefabloc, 10mM β-glycerphosphate, 10mM NaF) and after boiling at 95°C for 2 minutes, it was centrifuged at 13,200 rpm, and the supernatant was used as a sample. To analyze p62 levels, fly heads were homogenized with 1% PBST and after centrifugation at 13,200 rpm, the supernatant was mixed 1:1 SDS-Tris-Glycine sample buffer, and boiled at 95°C for 2 minutes. The pellet was dissolved with 2% SDS in PBS, then centrifuged again at 13,200 rpm. The supernatant was mixed 1:1 SDS-Tris-Glycine sample buffer and then boiled at 95°C for 2 minutes. SDS–PAGE for western blotting was performed using 15%(w/v) (LC3), 7.5%(w/v) (p62), 10% (w/v) (eIF2α, β, and p-eIF2α) polyacrylamide gels. After electrophoresis, they were transferred to PVDF membrane (Merck Millipore) using a transfer device (BIO-RAD). After transfer, the membrane was blocked with 5% skim milk/TBST (50 mM Tris (pH 7.5), 0.15 M NaCl, 0.05% Tween20) for 1 hour and incubated with primary antibody listed below overnight at 4° C. Membranes were rinsed twice with TBST containing 0.65M NaCl and once with TBST containing 0.15M NaCl. After incubation with the secondary antibody at room temperature for 1 hour, membranes were rinsed twice with TBST containing 0.65M NaCl and once with TBST containing 0.15M NaCl. After incubation with Immobilon Western Chemiluminescent HRP Substrate (Merck Millipore), chemiluminescent signals were detected with Fusion FX (Vilber). Experiments were repeated at least 3 times with independent cohorts of flies. Primary antibodies: anti-LC3 antibody Atg8 (Merck Millipore #ABC975) (1:1000), anti-p62 antibody Ref2P (abcam #ab178440) (1:750), anti-eIF2β antibody (1:1500), anti-eIF2α antibody (abcam #ab26197) (1:1000), anti-p-eIF2α antibody (Cell signaling #3398S) (1:2000), anti-actin antibody (SIGMA A2066) (1:3000) and anti-β tubulin antibody (Sigma #T9026) (1:800,000). Polyclonal anti-eIF2β antibody was raised against a synthetic peptide (CGLEDDTKKEDPQDEA) corresponding to the C-terminal residues 29–43 of Drosophila eIF2β (1:1500).
Secondary antibodies: Peroxidase-conjugated goat anti-mouse IgG antibody (Dako #P0447) (1:2000), peroxidase-conjugated pig anti-rabbit IgG antibody (Dako #P0399) (1:2000)
Proteasome assay
Heads from the 10 flies were homogenized in 150 μl of buffer B (25 mM Tris-HCl [pH 7.5], 2 mM ATP, 5 mM MgCl2, and 1 mM dithiothreitol). Proteasome peptidase activity in the lysates was measured with a synthetic peptide substrate, succinyl-Leu-Leu-Val-Tyr-7-amino-4-methyl-coumarin (Suc-LLVY-AMC) (Cayman). Luminescence was measured on an multimode plate reader 2300 Enspire (PerkinElmer). Experiments were repeated at least 3 times with independent cohorts of flies.
ATP assay
Heads from the 10 flies were homogenized in 50 μl of 6 M guanidine-HCl in extraction buffer (100 mM Tris and 4 mM EDTA, pH 7.8) to inhibit ATPases. Samples were boiled for 5 min and centrifuged. Supernatant was diluted 4% with extraction buffer and mixed with a reaction solution (ATP Determination kit, Invitrogen). Luminescence was measured on a multimode plate reader 2300 Enspire (PerkinElmer). The relative ATP levels were calculated by dividing the luminescence by the total protein concentration, which was determined by the Bradford method. Experiments were repeated at least 3 times with independent cohorts of flies.
Proteomic assay and pathway analysis
Sample preparation
Heads from the 35 flies were homogenized in 110 μl of extraction buffer (0.25% RapiGest SF, 50mM ammonium bicarbonate, 10mM dithiothreitol, 10μ/mL leupeptin, 0.4 μM Pefabloc, 10mM β-glycerphosphate, 10mM NaF). Homogenized samples were centrifugation and boiled for 5 min. After quantification of the protein concentration using a Pierce® 660 nm Protein Assay (Thermo Fisher Scientific), 10 μg proteins from each sample were reduced using 5 mM tris (2-carboxyethyl) phosphine hydrochloride (TCEP-HCl; Thermo Fisher Scientific) at 60°C for 1 h, alkylated using 15 mM iodoacetamide (Fujifilm Wako Pure Chemical, Osaka, Japan) at room temperature for 30 min, and then digested using 1.5 μg Trypsin Gold (Mass Spectrometry Grade; Promega, Madison, WI, USA) at 37°C for 17 h. The digests were acidified by the addition of trifluoroacetic acid (TFA), incubated at 37°C for 30 min, and then centrifuged at 17,000 ×g for 10 min to remove the RapiGest SF. The supernatants were collected and desalted using MonoSpin™ C18 (GL Sciences, Tokyo, Japan). The resulting eluates were concentrated in vacuo, dissolved in 2% MeCN containing 0.1% formic acid (FA), and subjected to LC-MS/MS analysis.
LC-MS/MS analysis and database search
LC-MS/MS analyses were performed on an Ultimate 3000 RSLCnano system (Thermo Fisher Scientific) coupled to a Q Exactive hybrid quadrupole-Orbitrap mass spectrometer (Thermo Fisher Scientific) equipped with a nano electron spray ionization (ESI) source. The LC system was equipped with a trap column (C18 PepMap 100, 0.3 × 5 mm, 5 μm, Thermo Fisher Scientific) and an analytical column (NTCC-360/75-3-125, Nikkyo Technos, Tokyo, Japan). Peptide separation was performed using a 90-min gradient of water/0.1% FA (mobile phase A) and MeCN/0.1% FA (mobile phase B) at a flow rate of 300 nL/min. Elution was performed as follows: 0–3 min, 2% B; 3–93 min, 2%–40% B; 93–95 min, 40%–95% B; 95–105 min, 95% B; 105–107 min, 95%–2% B; and 107–120 min, 2% B. The mass spectrometer was operated in data-dependent acquisition mode. The MS parameters were as follows: spray voltage, 2.0 kV; capillary temperature, 275°C; S-lens RF level, 50; scan type, full MS; scan range, m/z 350–1500; resolution, 70,000; polarity, positive; automatic gain control target, 3 × 106; and maximum injection time, 100 msec. The MS/MS parameters were as follows: resolution, 17,500; automatic gain control target, 1 × 105; maximum injection time, 60 msec; normalized collision energy (NCE), 27; dynamic exclusion, 15 sec; loop count, 10; isolation window, 1.6 m/z; charge exclusion: unassigned, 1 and ≥8; and injection volume, 1 μL (containing 0.5 μg protein). Measurements were made in duplicate for each sample.
The identification of proteins and label-free quantification (LFQ) of the detected peptides were performed using Proteome Discoverer software ver. 2.4 (Thermo Fisher Scientific). The analytical parameters used for the database search were as follows: parent mass error tolerance, 10.0 ppm; fragment mass error tolerance, 0.02 Da; search engine, sequest HT; protein database, Drosophila melanogaster (Fruit fly: SwissProt Tax ID=7227); enzyme name, trypsin (full); maximum number of missed cleavages, 2; dynamic modification, oxidation (methionine), phosphorylation (serine, threonine, tyrosine), acetyl (lysine), GG (lysine); N-terminal modification, Met-loss (methionine), and Met-loss+acetyl (methionine); static modification, carbamidomethylation (cysteine) and FDR confidence, High < 0.01, 0.01 ≤ Medium < 0.05, 0.05 ≤ Low. The parameters for LFQ were as follows: precursor abundance, based on area; and normalization mode, total peptide amount. The abundance ratio of milton RNAi to control RNAi at 7 or 21 day-old was calculated. We considered proteins with the abundance ratio of ≥2.0 or ≤ 0.5 and an ANOVA P-value of < 0.05 based on volcano plots to be differentially expressed of milton RNAi. To extract molecular networks biologically relevant to the proteins differentially expressed due to milton RNAi, pathway analysis was performed using KeyMolnet (KM Data Inc., Tokyo, Japan).
RNA extraction and quantitative real-time PCR analysis
Heads from more than 25 flies were mechanically isolated, and total RNA was extracted using ISOGEN (NipponGene) followed by reverse-transcription using PrimeScript RT reagent kit (Takara). The resulting cDNA was used as a template for PCR with THUNDERBIRD SYBR qPCR mix (TOYOBO) on a Thermal Cycler Dice real-time system TP800 (Takara). Expression of genes of interest was standardized relative to rp49. Relative expression values were determined by the ΔΔCT method (Livak and Schmittgen, 2001). Experiments were repeated three times, and a representative result was shown. Primers were designed using DRSC FlyPrimerBank (Harvard Medical School). Primer sequences are shown below;
eIF2β for 5′-GGACGACGACAAGAGCGAAG -3′
eIF2β rev 5′-CGGTCGCATCACGAACTTTG -3′
milton for 5′-GGCTTCAGGGCCAGGTATCT-3′
milton rev 5′-GCCGAACTTGGCTGACTTTG-3′
Polysome gradient centrifugation
30 heads were homogenized in 150 μl of lysis buffer (25 mM Tris pH 7.5, 50 mM MgCl2, 250 mM NaCl, 1mM DTT, 0.5 mg/ml cycloheximide, 0.1 mg/ml heparin). The lysates were centrifuged at 13,200 rpm at 4 °C for 5 minutes and the supernatant was collected. The samples containing 38μ of RNA was layered gently on top of a 10–25% w/w sucrose gradient (50 mM Tris pH 7.5, 50 mM MgCl2, 250 mM NaCl, 0.1 mg/ml heparin, 0.5 mg/ml cycloheximide in 5 ml polyallomer tube) and centrifuged at 37,000 rpm at 4°C for 150 minutes in a himac CP-NX ultracentrifuge using a P50AT rotor. Samples were fractionated from top to bottom, and absorbance at OD260 nm was analyzed by a Plate reader (EnSpire). Experiments were repeated at least 3 times with independent cohorts of flies.
Puromycin analysis
13 day-old flies were starved for 6 hr and fed 600 μM puromycin (Sigma) or 600 μM puromycin/35 mM cycloheximide (Sigma) in 5% sucrose solution for 20 hr. Incorporated puromycin was quantified by western blot with anti-puromycin antibody and normalized with actin. Experiments were repeated at least 3 times with independent cohorts of flies.
Climbing assay
The climbing assay was performed as previously described24. Flies were placed in an empty plastic vial (2.5 cm in diameter × 10 cm in length). The vial was gently tapped to knock the flies to the bottom, and the number of flies reached to the top, middle and bottom areas of the vials in 10 s was counted. Experiments were repeated 10 times, and the mean percentage of flies in each area and standard deviations was calculated. Experiments were repeated with independent cohorts more than three times, and a representative result was shown.
Statistics
The number of replicates, what n represents, precision measurements, and the meaning of error bars are indicated in Figure Legends. Data are shown as means ± SEM. For pairwise comparisons, Student’s t-test was performed with Microsoft Excel (Microsoft). For multiple comparisons, data were analyzed using one-way ANOVA with Tukey’s HSD multiple-comparisons test in the GraphPad Prism 6.0 software (GraphPad Software, Inc., La Jolla, CA). Results with a p-value of less than 0.05 were considered to be statistically significant.
Highlights
Loss of axonal mitochondria impairs autophagy and accumulates proteins in the axon
Loss of axonal mitochondria upregulates eIF2β and downregulates p-eIF2α
Neuronal upregulation of eIF2β induces autophagic defects and locomotor dysfunction
Lowering eIF2β rescues autophagic defects caused by loss of axonal mitochondria
Supplementary Material
1
Click here to view.(426K, pdf)
Acknowledgments
The authors thank the Bloomington stock center; TRiP at Harvard Medical School (NIH/NIGMS R01-GM084947); the Kyoto Drosophila Stock Center and the Vienna Drosophila RNAi Center for fly stocks. The authors thank Dr. Masayuki Miura from Department of Pharmaceutical Science, University of Tokyo, for proteasome activity assay protocol; Drs. Shin-ichi Hisanaga and Adam Weitemier from the Department of Biological Sciences, Tokyo Metropolitan University, for critical comments; Dr. Taro Saito, Dr. Akiko Asada from the Department of Biological Sciences, Tokyo Metropolitan University, and Dr. Michiko Sekiya from Department of Alzheimer’s Disease Research, National Center for Geriatrics and Gerontology, for technical supports.
Funding
This work was supported by the Sasakawa Scientific Research Grant (2021-4087) (to K.S.), the Takeda Science Foundation (to KA), Hoansha foundation grant (to KA), a research award from the Japan Foundation for Aging and Health (to KA), the Novartis Foundation (Japan) for the promotion of Science (to KA), a Grant-in-Aid for Scientific Research on Challenging Research (Exploratory) [JSPS KAKENHI Grant number 19K21593] (to KA), NIG-JOINT (National Institute of Genetics, 71A2018, 25A2019) (to K.A.) and TMU strategic research fund for social engagement (to KA).
Footnotes
Declaration of interests
The authors declare no competing interests.
Data Availability
The datasets used and/or analyzed during the current study are available from the corresponding author upon request.
References
1. Yerbury J.J., Ooi L., Dillin A., Saunders D.N., Hatters D.M., Beart P.M., Cashman N.R., Wilson M.R., and Ecroyd H. (2016). Walking the tightrope: proteostasis and neurodegenerative disease. J. Neurochem.137, 489–505. 10.1111/jnc.13575. [PubMed] [CrossRef] [Google Scholar]
2. Hetz C. (2021). Adapting the proteostasis capacity to sustain brain healthspan. Cell184, 1545–1560. 10.1016/j.cell.2021.02.007. [PubMed] [CrossRef] [Google Scholar]
3. Balch W.E., Morimoto R.I., Dillin A., and Kelly J.W. (2008). Adapting proteostasis for disease intervention. Science319, 916–919. 10.1126/science.1141448. [PubMed] [CrossRef] [Google Scholar]
4. Kimball S.R. (1999). Eukaryotic initiation factor eIF2. Int J Biochem Cell Biol31, 25–29. 10.1016/s1357-2725(98)00128-9. [PubMed] [CrossRef] [Google Scholar]
5. Jackson R.J., Hellen C.U., and Pestova T.V. (2010). The mechanism of eukaryotic translation initiation and principles of its regulation. Nat. Rev. Mol. Cell Biol.11, 113–127. 10.1038/nrm2838. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
6. Pakos-Zebrucka K., Koryga I., Mnich K., Ljujic M., Samali A., and Gorman A.M. (2016). The integrated stress response. EMBO Rep17, 1374–1395. 10.15252/embr.201642195. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
7. Kroemer G., Marino G., and Levine B. (2010). Autophagy and the integrated stress response. Mol. Cell40, 280–293. 10.1016/j.molcel.2010.09.023. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
8. Nandi D., Tahiliani P., Kumar A., and Chandu D. (2006). The ubiquitin-proteasome system. J Biosci31, 137–155. 10.1007/BF02705243. [PubMed] [CrossRef] [Google Scholar]
9. Glick D., Barth S., and Macleod K.F. (2010). Autophagy: cellular and molecular mechanisms. J. Pathol.221, 3–12. 10.1002/path.2697. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
10. Vargas J.N.S., Hamasaki M., Kawabata T., Youle R.J., and Yoshimori T. (2023). The mechanisms and roles of selective autophagy in mammals. Nat. Rev. Mol. Cell Biol.24, 167–185. 10.1038/s41580-022-00542-2. [PubMed] [CrossRef] [Google Scholar]
11. Aman Y., Schmauck-Medina T., Hansen M., Morimoto R.I., Simon A.K., Bjedov I., Palikaras K., Simonsen A., Johansen T., Tavernarakis N., et al. (2021). Autophagy in healthy aging and disease. Nat Aging1, 634–650. 10.1038/s43587-021-00098-4. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
12. Ross C.A., and Poirier M.A. (2004). Protein aggregation and neurodegenerative disease. Nat. Med.10Suppl, S10–17. 10.1038/nm1066. [PubMed] [CrossRef] [Google Scholar]
13. Rubinsztein D.C., Marino G., and Kroemer G. (2011). Autophagy and aging. Cell146, 682–695. 10.1016/j.cell.2011.07.030. [PubMed] [CrossRef] [Google Scholar]
14. Vos M., Lauwers E., and Verstreken P. (2010). Synaptic mitochondria in synaptic transmission and organization of vesicle pools in health and disease. Front Synaptic Neurosci2, 139. 10.3389/fnsyn.2010.00139. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
15. Cheng A., Hou Y., and Mattson M.P. (2010). Mitochondria and neuroplasticity. ASN Neuro2, e00045. 10.1042/AN20100019. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
16. Hollenbeck P.J., and Saxton W.M. (2005). The axonal transport of mitochondria. J. Cell Sci.118, 5411–5419. 10.1242/jcs.02745. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
17. Takihara Y., Inatani M., Eto K., Inoue T., Kreymerman A., Miyake S., Ueno S., Nagaya M., Nakanishi A., Iwao K., et al. (2015). In vivo imaging of axonal transport of mitochondria in the diseased and aged mammalian CNS. Proc Natl Acad Sci U S A112, 10515–10520. 10.1073/pnas.1509879112. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
18. Milde S., Adalbert R., Elaman M.H., and Coleman M.P. (2015). Axonal transport declines with age in two distinct phases separated by a period of relative stability. Neurobiol. Aging36, 971–981. 10.1016/j.neurobiolaging.2014.09.018. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
19. Vagnoni A., Hoffmann P.C., and Bullock S.L. (2016). Reducing Lissencephaly-1 levels augments mitochondrial transport and has a protective effect in adult Drosophila neurons. J. Cell Sci.129, 178–190. 10.1242/jcs.179184. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
20. Morsci N.S., Hall D.H., Driscoll M., and Sheng Z.H. (2016). Age-Related Phasic Patterns of Mitochondrial Maintenance in Adult Caenorhabditis elegans Neurons. J. Neurosci.36, 1373–1385. 10.1523/JNEUROSCI.2799-15.2016. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
21. Adalbert R., and Coleman M.P. (2013). Review: Axon pathology in age-related neurodegenerative disorders. Neuropathol. Appl. Neurobiol.39, 90–108. 10.1111/j.1365-2990.2012.01308.x. [PubMed] [CrossRef] [Google Scholar]
22. Duncan J.E., and Goldstein L.S. (2006). The genetics of axonal transport and axonal transport disorders. PLoS Genet. 2, e124. 10.1371/journal.pgen.0020124. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
23. Chen H., and Chan D.C. (2009). Mitochondrial dynamics--fusion, fission, movement, and mitophagy--in neurodegenerative diseases. Hum. Mol. Genet.18, R169–176. 10.1093/hmg/ddp326. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
24. Iijima-Ando K., Sekiya M., Maruko-Otake A., Ohtake Y., Suzuki E., Lu B., and Iijima K.M. (2012). Loss of axonal mitochondria promotes tau-mediated neurodegeneration and Alzheimer’s disease-related tau phosphorylation via PAR-1. PLoS Genet. 8, e1002918. 10.1371/journal.pgen.1002918. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
25. Lopez-Domenech G., Higgs N.F., Vaccaro V., Ros H., Arancibia-Carcamo I.L., MacAskill A.F., and Kittler J.T. (2016). Loss of Dendritic Complexity Precedes Neurodegeneration in a Mouse Model with Disrupted Mitochondrial Distribution in Mature Dendrites. Cell Rep17, 317–327. 10.1016/j.celrep.2016.09.004. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
26. Guo X., Macleod G.T., Wellington A., Hu F., Panchumarthi S., Schoenfield M., Marin L., Charlton M.P., Atwood H.L., and Zinsmaier K.E. (2005). The GTPase dMiro is required for axonal transport of mitochondria to Drosophila synapses. Neuron47, 379–393. 10.1016/j.neuron.2005.06.027. [PubMed] [CrossRef] [Google Scholar]
27. Glater E.E., Megeath L.J., Stowers R.S., and Schwarz T.L. (2006). Axonal transport of mitochondria requires milton to recruit kinesin heavy chain and is light chain independent. J. Cell Biol.173, 545–557. 10.1083/jcb.200601067. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
28. Stowers R.S., Megeath L.J., Gorska-Andrzejak J., Meinertzhagen I.A., and Schwarz T.L. (2002). Axonal transport of mitochondria to synapses depends on milton, a novel Drosophila protein. Neuron36, 1063–1077. 10.1016/s0896-6273(02)01094-2. [PubMed] [CrossRef] [Google Scholar]
29. Iijima-Ando K., Hearn S.A., Shenton C., Gatt A., Zhao L., and Iijima K. (2009). Mitochondrial mislocalization underlies Abeta42-induced neuronal dysfunction in a Drosophila model of Alzheimer’s disease. PLoS One4, e8310. 10.1371/journal.pone.0008310. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
30. Tonoki A., Kuranaga E., Tomioka T., Hamazaki J., Murata S., Tanaka K., and Miura M. (2009). Genetic evidence linking age-dependent attenuation of the 26S proteasome with the aging process. Mol. Cell. Biol.29, 1095–1106. 10.1128/MCB.01227-08. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
31. Klionsky D.J., Abdel-Aziz A.K., Abdelfatah S., Abdellatif M., Abdoli A., Abel S., Abeliovich H., Abildgaard M.H., Abudu Y.P., Acevedo-Arozena A., et al. (2021). Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)(1). Autophagy17, 1–382. 10.1080/15548627.2020.1797280. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
32. Bartlett B.J., Isakson P., Lewerenz J., Sanchez H., Kotzebue R.W., Cumming R.C., Harris G.L., Nezis I.P., Schubert D.R., Simonsen A., and Finley K.D. (2011). p62, Ref(2)P and ubiquitinated proteins are conserved markers of neuronal aging, aggregate formation and progressive autophagic defects. Autophagy7, 572–583. 10.4161/auto.7.6.14943. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
33. Oka M., Suzuki E., Asada A., Saito T., Iijima K.M., and Ando K. (2021). Increasing neuronal glucose uptake attenuates brain aging and promotes life span under dietary restriction in Drosophila. iScience24, 101979. 10.1016/j.isci.2020.101979. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
34. Zia A., Pourbagher-Shahri A.M., Farkhondeh T., and Samarghandian S. (2021). Molecular and cellular pathways contributing to brain aging. Behav Brain Funct17, 6. 10.1186/s12993-021-00179-9. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
35. Haigis M.C., and Yankner B.A. (2010). The aging stress response. Mol. Cell40, 333–344. 10.1016/j.molcel.2010.10.002. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
36. Wek R.C. (2018). Role of eIF2alpha Kinases in Translational Control and Adaptation to Cellular Stress. Cold Spring Harb Perspect Biol10. 10.1101/cshperspect.a032870. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
37. Bond S., Lopez-Lloreda C., Gannon P.J., Akay-Espinoza C., and Jordan-Sciutto K.L. (2020). The Integrated Stress Response and Phosphorylated Eukaryotic Initiation Factor 2alpha in Neurodegeneration. J. Neuropathol. Exp. Neurol.79, 123–143. 10.1093/jnen/nlz129. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
38. B’Chir W., Maurin A.C., Carraro V., Averous J., Jousse C., Muranishi Y., Parry L., Stepien G., Fafournoux P., and Bruhat A. (2013). The eIF2alpha/ATF4 pathway is essential for stress-induced autophagy gene expression. Nucleic Acids Res. 41, 7683–7699. 10.1093/nar/gkt563. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
39. Salton G.D., Laurino C., Mega N.O., Delgado-Canedo A., Setterblad N., Carmagnat M., Xavier R.M., Cirne-Lima E., Lenz G., Henriques J.A.P., and Laurino J.P. (2017). Deletion of eIF2beta lysine stretches creates a dominant negative that affects the translation and proliferation in human cell line: A tool for arresting the cell growth. Cancer Biol Ther18, 560–570. 10.1080/15384047.2017.1345383. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
40. Lee S., Nahm M., Lee M., Kwon M., Kim E., Zadeh A.D., Cao H., Kim H.J., Lee Z.H., Oh S.B., et al. (2007). The F-actin-microtubule crosslinker Shot is a platform for Krasavietz-mediated translational regulation of midline axon repulsion. Development134, 1767–1777. 10.1242/dev.02842. [PubMed] [CrossRef] [Google Scholar]
41. Wu Z., Tantray I., Lim J., Chen S., Li Y., Davis Z., Sitron C., Dong J., Gispert S., Auburger G., et al. (2019). MISTERMINATE Mechanistically Links Mitochondrial Dysfunction with Proteostasis Failure. Mol. Cell75, 835–848 e838. 10.1016/j.molcel.2019.06.031. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
42. Sugiura A., Nagashima S., Tokuyama T., Amo T., Matsuki Y., Ishido S., Kudo Y., McBride H.M., Fukuda T., Matsushita N., et al. (2013). MITOL regulates endoplasmic reticulum-mitochondria contacts via Mitofusin2. Mol. Cell51, 20–34. 10.1016/j.molcel.2013.04.023. [PubMed] [CrossRef] [Google Scholar]
43. Yonashiro R., Kimijima Y., Shimura T., Kawaguchi K., Fukuda T., Inatome R., and Yanagi S. (2012). Mitochondrial ubiquitin ligase MITOL blocks S-nitrosylated MAP1B-light chain 1-mediated mitochondrial dysfunction and neuronal cell death. Proc Natl Acad Sci U S A109, 2382–2387. 10.1073/pnas.1114985109. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
44. Takeda K., Nagashima S., Shiiba I., Uda A., Tokuyama T., Ito N., Fukuda T., Matsushita N., Ishido S., Iwawaki T., et al. (2019). MITOL prevents ER stress-induced apoptosis by IRE1alpha ubiquitylation at ER-mitochondria contact sites. EMBO J. 38, e100999. 10.15252/embj.2018100999. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Articles from bioRxiv are provided here courtesy of Cold Spring Harbor Laboratory Preprints