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University of Washington
Using Drosophila to Study the PINK1-Parkin Mitochondrial Quality Control Pathway Leo Pallanck University of Washington
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The PINK1-Parkin Pathway
Mitofusins Parkin Drp1 Mitofusins PINK1
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The PINK1-Parkin Pathway
Mitofusins Parkin PINK1 Drp1 Mitofusins Lysosome
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The PINK1-Parkin Pathway
Mitofusins Parkin PINK1 Drp1 Mitofusins Contributions of fly genetics to this model: =>PINK1 & Parkin mutants accumulate enlarged defective mitochondria =>PINK1 & Parkin act in a common pathway =>Parkin ubiquitinates mitofusin to promote mt fragmentation Lysosome
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The PINK1-Parkin Pathway
Mitofusins Some important remaining questions: =>Do PINK1 & Parkin promote mitochondrial turnover in vivo? Parkin PINK1 Drp1 Mitofusins =>Do PINK1 and Parkin influence mitochondrial quality control in Dopaminergic neurons? Lysosome =>What other factors act in the PINK1-Parkin pathway?
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Do PINK1 & Parkin promote mitochondrial turnover in vivo?
Our approach: stable isotope labeling and mass spectrometry (collaboration with the laboratory of Mike MacCoss) CD3 D3-leucine (mass: +3) D3-leucine Per Wikipedia, Leu is most common AA in human proteins (makes up 9.1% of all protein). MW 131. Per MM, 75% of dietary Leu is incorp’d into protein Thank Geoff here In vivo labeling and mass spectrometry Tracking mitochondrial turnover through long-lived mitochondrial proteins Raise flies normally, collect on day of eclosion Advantages: Look at specific proteins without fractionation Look at inner membrane/matrix proteins Multiple kinds of proteins at once from same sample Large N possible No chance of picking up free precursor as with radioactivity % of leucine in peptides D3 trypsin digest total proteins unlabeled leucine D3 D3 D3 D3 5 & 10 days time 6
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Technical challenges with this approach:
1. Quantifying the amount of D3-leucine incorporation into protein 2. Estimating the D3-leucine “precursor pool” to allow an accurate measurement of turnover Solution: TOPOGRAPH; an algorithm that we helped developed in collaboration with the MacCoss laboratory
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1. Quantifying the amount of D3-leucine incorporation into protein
Topograph finds the “best fit” (natural isotope distribution + n D3-leucines) actual amount of isotope Fractional Abundance predicted Compare to theoretical distributions Solve linear equations to get best match to distribution, contribution of each labeled form (1, 2, 3 Leu) % 0 D3-leucines % 1 D3-leucine isotope (additional mass units)
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Technical challenges with this approach:
1. Quantifying the amount of D3-leucine incorporation into protein 2. Estimating the D3-leucine “precursor pool” to allow an accurate measurement of turnover Solution: TOPOGRAPH; an algorithm that we developed in collaboration with the MacCoss laboratory
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2. Estimating the D3-leucine “precursor pool” to allow an accurate measurement of turnover
e.g., AIGLPEDLIQK (2 leucines) Requires multiple Leu containing peptides precursor pool 100% D3-leucine 25% turnover “Old” “New” precursor pool 50% D3-leucine 50% turnover “Old” “New” D3-leucine content after X hours of labeling: 25%
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TOPOGRAPH determines this distribution
2. Estimating the D3-leucine “precursor pool” to allow an accurate measurement of turnover enables an estimate of turnover “New”: “Old”: TOPOGRAPH determines this distribution = 50% turnover and uses probability-based calculations to estimate the D3-leucine content of the precursor pool
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Predictions of the PINK1-Parkin mitochondrial QC model:
control time % D3-leucine Non-mitochondrial proteins PINK1 or parkin mutants PINK1 or Parkin overexpression Mitochondrial proteins PINK1 or Parkin overexpression control % D3-leucine PINK1 or parkin mutants Presumes a steady state I’m measuring replacement (synthesis) in order to measure degradation time 12
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mitochondrial protein turnover is decreased in parkin mutants
mean increase in half-life: 29.9% mean decrease in half-life: ~31%
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nonmitochondrial protein turnover is similarly decreased in parkin mutants
not different w/just long-lived cyto—not even when I kicked out gly phos mean increase in half-life: 30.4%
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Why are nonmitochondrial proteins affected?
Parkin regulates protein turnover more broadly than anticipated? The accumulation of defective mitochondria has a general effect on mitochondrial turnover? GO QUICKLY ON THIS SLIDE Also maybe some mitochondrial proteins not normally turned over by UPS are now diverted to that system and are overloading it.
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PINK1 overexpression increases mitochondrial protein turnover
repeated measures t-test error bars are 95% confidence intervals mean decrease in half-life: ~10%
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Importantly, mitochondrial proteins are selectively affected by PINK1 overexpression
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The PINK1-Parkin Pathway
Mitofusins Important remaining questions: =>Do PINK1 & Parkin promote mitochondrial turnover in vivo? Parkin PINK1 Drp1 Mitofusins =>Do PINK1 and Parkin influence mitochondrial quality control in Dopaminergic neurons? Lysosome =>What other factors act in the PINK1-Parkin pathway?
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Do PINK1 & Parkin influence mitochondrial QC in dopamine neurons?
(Brand and Perrimon, 1993) First needed to develop a simple method to purify specific dopaminergic neurons from the fly brain: -Uses the UAS/GAL4 system to mark the neurons of interest Examples Dopaminergic neurons Cholinergic neurons Etc. GFP -Uses FACS to collect the marked neurons following mechanical and enzymatic brain dissociation
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FACS purification of dopaminergic neurons from the adult Drosophila brain:
TH-GAL4; UAS-GFP Non-transgenic flies 2% of events 0.02% of events DAPI DAPI Show most recent data FITC (GFP) FITC (GFP) FACS-purified dopaminergic neurons also express appropriate markers (e.g., TH, VMAT, etc.)
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Predictions: park+/- park-/-
-mt membrane potential should correlate with PINK1-Parkin activity -accumulation of enlarged mt in parkin mutants. DA neurons DA neurons P < 0.05 park+/- -CCCP 1.2 P < 0.01 45% 55% 0.8 Relative MMP 22% 78% 0.4 # of cells WT Park-/- PINK1OE park-/- +CCCP Show PINK1-Parkin pathway model and test predictions: Parkin mutations should result in accumulation of enlarged & depolarized mitochondria in dopaminergic neurons. Genetic perturbations that promote mitochondrial fragmentation and autophagy should suppress these phenotypes Show CCCP data on this slide Next slide, show MMP in parkin mutants and controls and rescue of this phenotype, along witt effects of PINK1 overexpression; also show that these can rescue the neurodegenerative phenotype of parkin mutants Next slide show that the effects of Parkin mutations on mitochondrial integrity are greater in DA neurons, than in other neuronal populations analyzed. P < 0.01 62% 38% 100 80 100% 0% 60 % fused mt # of cells 40 20 WT Park-/- Mitotracker fluorescence Mitotracker fluorescence
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Do manipulations that promote mt fragmentation and turnover influence the parkin neuronal phenotypes? Lysosome Mitofusins Drp1 PINK1 1.2 P < 0.01 0.8 Relative MMP 0.4 WT park-/- park-/- TgDRP1 park-/- Mfn Rnai park-/- TgAtg8a 1.2 P < 0.001 PPL1 neurons Relative # 0.8 0.4 WT park-/- park-/- TgDRP1 park-/- Mfn Rnai park-/- TgAtg8a
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What explains the selective sensitivity of dopaminergic neurons to mutations in PINK1 and parkin?
-An enhanced sensitivity of mitochondria? -An increased sensitivity of cell survival in response to a general mitochondrial defect? P < 0.05 P < 0.01 1.2 100 P < 0.01 80 0.8 Relative MMP 60 % fused mt 40 0.4 20 WT DA neurons Park-/- WT Park-/- Cholinergic neurons Park-/- =>Mitochondria in dopaminergic neurons are more sensitive to perturbations of the PINK1-Parkin pathway
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The PINK1-Parkin Pathway
Mitofusins Important remaining questions: =>Do PINK1 & Parkin promote mitochondrial turnover in vivo? Parkin PINK1 Drp1 Mitofusins =>Do PINK1 and Parkin influence mitochondrial quality control in Dopaminergic neurons? Lysosome =>What other factors act in the PINK1-Parkin pathway?
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suppression or enhancement?
A screen for PINK1 overexpression modifiers: Can this phenotype be used to screen for novel components of the PINK1-Parkin pathway? -mutations of activators (like parkin) should suppress -mutations of inhibitors (like mitofusin) should enhance WT A deletion bearing chromosome UAS-PINK1 ey-GAL4 Cy Del Sb + ; X suppression or enhancement? PINK1 PINK1 park-/- Will this work???
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A screen for PINK1 overexpression modifiers:
Can this phenotype be used to screen for novel components of the PINK1-Parkin pathway? -mutations of activators (like parkin) should suppress -mutations of inhibitors (like mitofusin) should enhance WT 6 PINK1 Eye severity score 4 PINK1 park-/- 2 WT PINK1OE PINK1OE Park-/- PINK1OE Park+/- PINK1OE Mfn+/- Will this work???
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A screen for PINK1 overexpression modifiers:
Can this phenotype be used to screen for novel components of the PINK1-Parkin pathway? -mutations of activators (like parkin) should suppress -mutations of inhibitors (like mitofusin) should enhance WT Enhancer 6 PINK1 Eye severity score 4 PINK1 park-/- 2 Suppressor WT PINK1OE PINK1OE Park-/- PINK1OE Park+/- PINK1OE Mfn+/- Will this work???
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A screen for PINK1 overexpression modifiers:
-We have thus far screened deletions covering >95% of the genes residing on two of the three major chromosomes in Drosophila 31 suppressors 53 enhancers Some suppressors: Parkin, p62 Some enhancers: mitofusin, Afg3L2 Some are stronger modifiers than Parkin and Mitofusin Ongoing efforts: -Testing the specificity of modifiers -mapping the modifier gene
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Summary -The PINK1-Parkin pathway promotes selective mitochondrial turnover in vivo -PINK1 & Parkin influence mitochondrial QC in dopaminergic neurons -Mitochondria in dopaminergic neurons are selectively sensitive to the loss of the PINK1-Parkin pathway (a toxic effect of dopamine?) -We’ve identified a large collection of candidate PINK1-Parkin pathway components
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Acknowledgements Evvie Vincow Jonathon Burman Ruth Thomas
Michael MacCoss Nick Shulman Department of Genome Sciences University of Washington Former Contributors: Angela Poole Cornell University Alex Whitworth University of Sheffield Jessica Greene Fred Hutchinson Cancer Research Center National Institutes of Health UMDF
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How accurately does Topograph estimate the precursor pool?
-A validation experiment using yeast Uniformly label yeast proteins for many generations in media containing a defined D3-leucine content Subject the yeast proteins to mass spectrometry and use Topograph to measure the precursor pool Presumes a steady state I’m measuring replacement (synthesis) in order to measure degradation Amount of D3-Leucine in media 33% 67% Topograph’s estimate of D3-Leucine precursor pool 33% 68% Pretty Accurately!!! 31
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