Proteomics analysis of autophagy cargos reveals distinct adaptations in PINK1 and LRRK2 models of Parkinson disease

Autophagy is essential for neuronal homeostasis, while defects in autophagy are implicated in Parkinson disease (PD), a prevalent and progressive neurodegenerative disorder. We used unbiased proteomics to compare cargos degraded by basal autophagy in the brain from two mouse models of PD, PINK1-/- and LRRK2G2019S mice. We find evidence for the upregulation of adaptive pathways to support homeostasis in both PD models. In PINK1-/- mice, we observed increased expression of the selective receptor BNIP3 along with evidence of engagement of other alternative pathways for mitophagy. Despite these changes, we find the rate of autophagic flux in PINK1-/- neurons is decreased. In LRRK2G2019S mice, hyperactive kinase activity known to impair autophagosomal and lysosomal function results in increased secretion of extracellular vesicles and autophagy cargo. In support of this observation, we find reduced levels of PIKFYVE, a negative regulator of extracellular vesicle secretion, in both brain and cortical neurons from LRRK2G2019S mice. Thus, distinct adaptive pathways are activated to compensate for perturbations induced by either loss of PINK1 or hyperactivation of LRRK2. Our findings highlight the engagement of compensatory pathways to maintain homeostasis in the brain, and provide insights into the vulnerabilities these compensatory changes may introduce that may further contribute to PD progression.


INTRODUCTION
Autophagy is an evolutionarily conserved process for the clearance and recycling of proteins and organelles. Neurons have a unique dependence on autophagy, as impairment of this pathway leads to either neurodevelopmental or neurodegenerative phenotypes 1-3 . Cellular, genetic, and pathological data point to two major types of autophagy in neurons. Acute stress induces the targeting of dysfunctional organelles or aggregated proteins for turnover, in regulated pathways for mitophagy, lysophagy and aggrephagy, among other mechanisms 4 . These pathways generally involve damage-sensing, leading to induction of a downstream response. For example, mitochondrial damage leads to the stabilization of PINK1 kinase on the 1 0 outer mitochondrial membrane (OMM), which in turn triggers a feedforward activation of the E3 ubiquitin ligase Parkin, leading to widespread ubiquitination of mitochondrial proteins and recruitment of ubiquitin-binding receptors such as OPTN that serve as a platform leading to the engulfment of the damaged organelle by a double-membrane autophagosome [5][6][7][8] . Similarly, in lysophagy, lysosomal membrane permeabilization that cannot be repaired via the ESCRT pathway leads to ubiquitination of proteins within the lysosomal membrane, followed by the recruitment of receptors including TAX1BP1 and p62/SQSTM1, and again the engulfment via a locally formed autophagosome 9,10 .
In addition to these stress-induced mechanisms, there is robust cellular and in vivo evidence for 2 0 a requirement of basal autophagy in neurons [11][12][13] . Autophagosomes form constitutively at synaptic sites and the axon terminus, engulfing diverse cargos into double-membrane autophagosomes. Newly formed autophagosomes then undergo a stereotypical pattern of highly regulated transport toward the soma, driven by the molecular motor cytoplasmic dynein. Defects in this transport impede the degradation of engulfed cargos. A notable example occurs in neurons expressing the most common familial mutation in Parkinson's disease (PD), the G2019S mutation in LRRK2. Pathological mutations in LRRK2 kinase induce hyperactivity, leading to hyper-phosphorylation of RAB proteins that are known LRRK2 kinase targets 14 , and key regulators of vesicle trafficking pathways 15 . Elevated LRRK2 activity is sufficient to disrupt both the transport and the maturation of autophagic vesicles in the axon, leading to a block in 3 0 autophagic degradation 16 .
To better understand how autophagy supports normal neuron function, we used proteomics to identify the major cargos engulfed by autophagic vesicles in the brain under basal conditions, and found that mitochondrial fragments and synapse-related proteins were the prominent cargos of this homeostatic pathway. Western blotting and live imaging studies of induced human neurons and primary rodent neurons confirmed that these cargos were highly enriched in autophagic vesicles in neurons 17 .
Next, we sought to understand how autophagic cargo might be altered in the context of PD, 4 0 which is tightly linked to disrupted autophagy. PD is a progressive neurodegenerative disease primarily affecting dopaminergic neurons in the substantia nigra pars compacta. It presents as a movement disorder in patients with an average age of onset at 60. 15% of PD cases are familial, but in both familial and sporadic PD the most common risk factor is age, with disease severity correlating with age 18 . There have been many links of disrupted autophagy to PD. Abnormal autophagosome are accumulated in post-mortem patient brain tissue independent of etiology 19 ; familial mutations in the genes encoding PINK1 and Parkin impair the selective autophagic degradation of damaged mitochondria, and mutations in LRRK2 impair autophagosome trafficking and maturation. Functional autophagy is responsible for clearing αsynuclein aggregates that can form the characteristic pathological Lewy bodies found in PD 20,21 .

0
Therefore, it is reasonable to hypothesize that impairments to the autophagy pathway may be 1 causative for disease, although the late age of onset in PD patients suggests that there are likely to be additional disease drivers or modifiers that involves the slow accumulation of damage over time.
Here, we report the changes in autophagy cargo observed using unbiased proteomics to analyze two distinct mouse models of PD, PINK1 knock-out mice and LRRK2 G2019S knock-in mice. In both models, we find evidence for the upregulation of compensatory pathways for protein clearance and organelle quality control. PINK1 loss in mice leads to compensatory changes in autophagy machinery, so that mitochondria are still engulfed within autophagic 6 0 vesicles (AVs). In LRRK2 G2019S mice, we find evidence of increased secretion, which may help to maintain neuronal homeostasis by removal of damaged organelles or aggregated proteins from the affected neurons. Further, we analyze how the AV cargo changes with age, finding that ageassociated changes to lysophagy are distinct from the changes seen in genetic PD models, but may further exacerbate disease progression. Overall, we report many changes to autophagy in PD-associated models and highlight a common theme of compensation in response to PDassociated mutations to maintain the clearance of neuronal proteins.

0
Autophagic vesicles from PINK -/mice contain mitochondria PINK1 is a kinase that stabilizes and amplifies ubiquitination on damaged mitochondria to promote autophagosome formation and clearance 5 . However, previous studies in Drosophila and mouse indicate that under basal conditions, PINK1 and/or Parkin contribute minimally to mitochondrial turnover 12,17,22 . Therefore, we were curious to define the broader impacts of PINK1 loss on overall mitochondrial turnover by autophagy.
We investigated the autophagic cargo in brains collected from 7-month-old PINK1 -/mice compared to aged matched wild type mice. We previously confirmed that AV enrichment yields 8 0 preparations in which ≥85% of vesicles were bona fide AVs. To assess the likelihood that a given protein in our AV fraction is a true cargo destined for degradation, we calculated a parameter termed the "cargo score" by determining its enrichment in a proteinase K-protected fraction relative to the total AV fraction 17 .
Over 600 proteins exhibit significantly different cargo scores in AVs derived from PINK1 -/brains as compared to scores determined for AVs isolated from the brain of age-matched wild-type mice, indicative of widespread alterations in protein and organelle turnover (Figure 1a, Supplementary Table 1). Gene ontology (GO) analysis on the proteins that exhibited significantly decreased cargo scores from PINK1 -/brain as compared to WT suggests that 9 0 certain mitochondrial proteins have decreased engulfment under basal conditions (Figure 1b).
To further understand how the observed changes in cargo are reflective of the state of the brain, we immunoblotted for proteins of interest from total brain and AV fractions. Increased enrichment of the protein within the AV could reflect higher levels of total protein in the brain, or alternatively indicate higher rates of turnover via autophagy. Therefore, we first compared levels in brain lysates between WT and PINK1 -/-, and then compared the levels of the proteins in the AV and AV+PK fraction between WT and PINK1 -/-. 34/82 of the mitochondrial proteins that are lower in PINK1 -/-AVs are mitochondrial transcription and translation associated (Supplementary Table 2), suggesting there is a loss of autophagic engulfment of this specific subset of 1 0 0 mitochondrial proteins in PINK1 -/mice. We confirmed these observations by focusing on GFM2, a mitochondrial elongation factor responsible for ribosome release during translation that had 2 one of the highest fold changes between WT and PINK1 -/cargo scores. While GFM2 levels are not altered in brain lysates of PINK1 -/mice relative to wild type mice, we noted that this protein is significantly decreased within PINK1 -/derived AVs (Figure 1c). EM analysis of enriched autophagosomes from wild type and PINK1 -/mouse brains shows that there is a slight, but significant decrease in the fraction of AVs that contain mitochondrial fragments, although there is no difference in acidified vesicles, or vesicles that contain synaptic vesicle like structures (Figure 1g, h, Supplementary Figure 1a,b). However, still 30% of the AVs derived from the PINK1 -/mice contain mitochondrial fragments.

0
Our previous work highlighted a surprising enrichment of mitochondrial nucleoids within brain AVs, and showed that TFAM-positive nucleoids are engulfed constitutively within the axon in primary neurons 17 . TFAM is also enriched within autophagosomes isolated from the brain of PINK1 -/knockout mice. However, total TFAM levels in PINK1 -/brain lysates were significantly lower than levels seen in wild type brain lysates (Figure 1i-l). Therefore, comparing the amount of TFAM within AVs relative to the total amount in the brain, AVs are engulfing proportionally more TFAM in PINK1 -/mice ( Figure 1m). qPCR analysis did not detect changes in the amount of mtDNA present in whole brain samples from WT compared to PINK1 -/mice (Supplementary Figure 1c), thus further investigation on the impact of decreased TFAM levels following the loss 1 2 0 of PINK1 in total brain is required.

PINK1 -/mice increase selective autophagic pathways to remove mitochondria
The continued clearance of mitochondrial fragments and TFAM-positive nucleoids in PINK1 -/derived AVs led us to ask whether we might find evidence for compensatory changes in autophagy in this PD model. Such compensatory changes might explain the limited phenotypic consequences observed in knock-out mice despite the loss of an important quality control pathway. Indeed, proteins associated with selective mitophagy had increased likelihood to be AV cargo in the absence of PINK1 (Figure 2a As FIS1 is associated with the fission of damaged mitochondrial components, and MFF is associated with mitochondrial maintenance and biogenesis 23 , this suggests that damaged mitochondria are still effectively cleared in PINK1 -/mice. Thus, we examined alternate pathways for the selective removal of damaged mitochondria. We observed increased BNIP3 24,25 and BCL2L13 26,27 , two previously reported mitophagy receptors, in AVs from PINK1 -/brains by mass spectrometry (Figure 2a). We compared these two adaptors in whole brain and AV fractions by immunoblot (Figure 2g-n) and found higher levels of BCL2L13 in PINK1 -/total brain lysate relative to wildtype (Figure 2l). Both BNIP3 and BCL2L13 1 4 0 were enriched in AVs from PINK1 -/mice, suggesting that these mitophagy receptors may be preferentially engaged to compensate for the loss of PINK1 (Figure 2j, n). HUWE1, an E3 ligase that regulates PINK1 -/independent mitophagy by ubiquitylating MFN2 and recruiting AMBRA1 to initiate autophagosome formation 28 , was identified as significantly increased in PINK1 -/brain derived AVs by proteomics ( Figure 2a). Although immunoblot analysis did not show changes to HUWE1 (Supplementary Figure 2f-i), we did note increased engulfment of MFN2 in AVs ( Figure  2o-r), suggesting this pathway may be activated to recruit mitochondria to autophagosomes. Together, the changes suggest evidence of upregulation of compensatory pathways to remove damaged mitochondria in the absence of PINK1.

5 0
We also noted changes to synaptic proteins, another major cargo of basal autophagy, within the PINK1 -/brain AVs (Supplementary Figure 3a). Proteomics suggests that the autophagic engulfment of both pre-and post-synaptic density proteins were significantly changed in PINK1 -/brain-derived AVs as compared to wild type (Supplementary Figure 3a,b). The multiple statistically significant changes observed by MS are consistent with the observed broad changes in synapse formation and dendritic morphology induced by the loss of PINK1 29-31 . Close inspection of the proteomic dataset also identified significant differences in proteins in the nitric oxide (NO) and spermidine synthesis pathway in the PINK1 -/brain-derived AVs (Supplementary Figure 3c). We immunoblotted for NOS1, SRM, and MAT2A, proteins required for NO and spermidine synthesis, in WT and PINK1 -/total brain and brain-derived AVs Figure 3d-o), and found that there are higher levels of these proteins in brains of PINK1 -/mice, suggesting possible increased production of NO and spermidine in PINK1 -/mouse brain. Supplemental spermidine rescues growth phenotypes in mitophagy deficient yeast 32 , and increases WIPI2 levels, a protein that promotes autophagosome biogenesis in neurons 33 , and autophagic flux in aged hippocampal neurons 34 . Consistent with these findings and the idea that spermidine production may be increased, immunoblotting indicated that total brain levels of WIPI2 were also increased (Supplementary Figure 3p-s).
LRRK2 G2019S alters the autophagy of proteins regulating extracellular vesicle production 1 7 0 Mutations in the LRRK2 gene are the most common familial cause of PD, resulting in hyperactive LRRK2 kinase activity. Evidence of elevated LRRK2 kinase activity has also been shown in idiopathic PD cases 35 . Hyperactive LRRK2 increases the phosphorylation of RAB proteins that regulate vesicular trafficking 14,36 . Previously, we have shown that the G2019S mutation in LRRK2 leads to significant impairment in the trafficking and acidification of AVs 16 . Thus, we were curious how autophagic cargos might be altered in the brains of LRRK2 G2019S mice, and how these alterations might compare to the changes observed in PINK1 -/mice.
Overall, 71 proteins exhibited significantly different cargo scores when comparing results from analysis of brain-derived AVs from LRRK2 G2019S and wild type mice ( Figure 3a, Supplementary 1 8 0 Table 3), an order of magnitude less than the observed 652 proteins with significantly different cargo scores found in comparisons of PINK1 -/and wild type derived AVs. Yet 73% of the significant LRRK2 G2019S changes were common to the changes observed in the PINK1 -/model, identifying some similar response (Supplementary Figure 4 a,b). Autophagy cargo decreased in both PINK1 -/and LRRK2 G2019S brain as compared to wild type include synapse-related proteins (Supplementary Table 4), suggesting that some remodeling of synapses is common to different forms of PD. While we observed a mild reduction in the fraction of PINK1 -/derived AVs containing mitochondrial fragments, expression of LRRK2 G2019S did not affect the number of AVs with mitochondrial cargo (Supplementary Figure 4 c,d).

9 0
Most strikingly, GO analysis of the significantly changed AV cargo proteins from LRRK2 G2019S brains found that terms for extracellular organelles were enriched, including a lower cargo score for TSG101 and a higher cargo score for PIKFYVE (Figure 3a, b). Immunoblotting confirmed that TSG101, involved in the formation of extracellular vesicles (EVs) and commonly used as a marker of EVs 37 , was decreased in LRRK2 G2019S AVs (Figure 3c-f). PIKFYVE is a kinase that phosphorylates PI3P to PI(3,5)P2, thereby regulating vesicular dynamics, lysosome fission and the fusion of multivesicular bodies to the lysosome 38-40 . When PIKFYVE is inhibited, it results in increased EV release 41,42 . Immunoblotting identified lower, although non-significant, levels of PIKFYVE in LRRK2 G2019S brain (Figure 3g, h). While AV levels of PIKFYVE were lower, the amount protected from proteinase K was sustained (Figure 3i-k). This suggests that the lower 2 0 0 levels of PIKFYVE in the brain may result from autophagic degradation.
Based on these results, we wondered if the secretion of EVs was increased in the LRRK2 model. Consistent with this possibility, we found increased levels of TSG101 in conditioned media from LRRK2 G2019S primary cortical neurons, which could be reduced by kinase inhibition of LRRK2 with MLi2 (Figure 3l, m, Supplementary Figure 4e, f). Additionally, proteomics identified increased levels of hnRNPK within AVs in LRRK2 G2019S (Figure 3a), which has been previously shown to be secreted in EVs in an autophagy-dependent manner 43 . Although changes in hnRNPK levels within AVs from LRRK2 G2019S did not reach statistical significance by immunoblotting ( Supplementary Figure 4i-l), levels of hnRNPK in conditioned media were 2 1 0 elevated in a kinase-dependent manner, as inhibition of LRRK2 kinase activity by MLi2 reduced the amount of hnRNPK secreted (Figure 3n, o, Supplementary Figure 4g, h). Together, these data suggest that while uptake into autophagosomes is not profoundly affected in the LRRK2 model, there are changes consistent with an induction of secretory autophagy to maintain proteostasis upon inhibition of lysosomal degradation, as discussed by Solvik et al. 44 .

Aging leads to decreased lysosomal cargo in AVs
Aging is the most significant risk factor for PD, common to both familial and sporadic cases. Thus, we next asked whether aging can affect the nature of cargo turned over by autophagy in 2 2 0 the brain, and if this might also contribute to PD progression. We proteomically profiled AVs derived from the brains of young (1-month-old) and old (18-month-old) mice for comparison of age-dependent changes 45 .
Overall, 94 proteins were observed to significantly change with aging in AVs isolated from young and old mouse brains ( We hypothesize that decreased lysophagy, as opposed to decreased autophagosome acidification, was responsible for the lower levels of lysosomal proteins in AVs derived from aged mice for three reasons. The lysosomal membrane proteins LAMP1 and RagA are found within the proteinase K protected fraction in AVs from young mice, whereas if autophagosomelysosome fusion was impaired, membrane proteins should remain on the surface of the autophagolysosome (APL) and thus be degraded by the addition of protease (Supplementary 2 4 0 Figure 5g, k). Additionally, EM analysis between AVs derived from young and old mouse brain does not indicate a change in the number of APLs, identified by dense, unilamellar structures (Supplementary Figure 5m, n). Lastly, there is no delay in the rate of autophagosome acidification with age in dorsal root ganglion neurons (DRGs) 46 . To confirm whether lysophagy could be affected with age, we investigated whether LGALS8, a crucial component of lysophagy 47 ,or the lysophagy receptors p62/SQSTM1 and TAX1BP1 9,10 changed in total brain and in AVs with age. We found that the amount of LGALS8 and p62/SQSTM1 in the total brain lysate decreased, while total brain levels of TAX1BP1 were strongly increased, suggesting there may be an impairment in lysophagy in aging brain (Figure 4k-v).

5 0
Increased autophagic engulfment of α-synuclein with age GO analysis of the cargos significantly enriched in AVs isolated from old mice compared to young mice include terms related to mitochondria and synapses (Figure 5a, b), similar to our findings from AVs isolated from 7-month-old mice 17 . EM of enriched autophagosomes did not show any obvious changes to the mitochondrial cargo, as mitochondrial fragments were identified in about half of the AVs examined (Supplementary Figure 5m, o).
We noted the higher levels of αand βsynuclein in AVs isolated from the brains of older mice ( Figure 5a). α-synuclein is known to be degraded by autophagy 20,48 and is a key component of

6 0
Lewy bodies that correlate with PD progression 49 . We confirmed that α-synuclein levels increased within AVs with age by immunoblotting (Figure 5c-f). We did not find changes in the amount of fibrillar proteins by Thioflavin T staining in total brain or within AVs with age, nor changes to phosphorylated α-synuclein (Supplementary Figure 6a-d). We further validated an increased colocalization of endogenous α-synuclein with endogenous LC3 puncta by immunocytochemistry in the cell body of dorsal root ganglion neurons from 18-month-old compared to 1-month-old mice (Figure 5g-i). Immunostaining indicated that colocalization of the lysosomal protein LAMP1 with LC3 is maintained (Figure 5j, k). We did not observe changes to the colocalization of α-synuclein with LAMP1 with age (Figure 5l, m).

7 0
Secretion of α-synuclein is increased in LRRK2 mice α-synuclein pathology spreads in PD patient brains in a stereotypical pattern that correlates with the staging of clinical symptoms. Previous research has demonstrated that exogenous αsynuclein fibrils can induce Lewy body formation in neurons both in vitro and in mouse brain via a prion-like activity 50-56 . We investigated whether the LRRK2 G2019S mutation affected AV levels and the extracellular release of α-synuclein. Levels of α-synuclein within AVs were not increased in the adult LRRK2 G2019S brain-derived AVs (Figure 6a-c). However, the hyperactive kinase activity of LRRK2 G2019S in primary cortical neurons resulted in increased secretion of αsynuclein into the conditioned media, as these elevated levels can be rescued by treatment with We next investigated whether the increased secretion of α-synuclein from LRRK2 G2019S neurons correlated with changes to the circulating plasma levels in mice, and whether increasing age might also increase secretion. We confirmed that the levels of α-synuclein within AVs increased with age in wildtype mice, but were unchanged by the LRRK2 G2019S mutation (Figure 6g-i, Supplementary Figure 7a). We observed an increase in plasma levels of α-synuclein in the LRRK2 G20191S mutant mice consistent with the increased levels in conditioned media from primary neurons, but we did not observe any further change in the plasma levels of α-synuclein with age ( Figure 6j).

9 0
We investigated whether TSG101 levels were changing within AVs or in plasma with age and the LRRK2 mutation. As observed previously, TSG101 levels associated with AVs were decreased with the LRRK2 mutation, but we did not observe further changes to the levels in AVs with age ( Figure 6k-m, Supplementary Figure 7a). TSG101 levels in plasma increased with the LRRK2 G2019S mutation, but was not further increased with age ( Figure 6n), which tracks with the same pattern of secreted α-synuclein.
We compared the AV levels, extracellular secreted and plasma levels of TFAM from adult and aged wild type and LRRK2 G2019S mice and embryonic primary cortical neurons (Figure 6o . However, we detected higher plasma levels of TFAM in LRRK2 G2019S mice that further increased with age ( Figure 6r). These data suggest there are multiple pathways of secretion that are upregulated in LRRK2 G2019S mice, one for TSG101-positive EVs that is LRRK2 kinase dependent, and another for mitochondrial fragments or mtDNA.

1 0
We identify distinct degradative signatures in mouse models of PD, characterized by changes to cargos turned over by basal autophagy in the brain. These changes in autophagosome cargo are reflective of overall changes to neuronal biology, including alterations in synaptic protein turnover in PD 57 and changes to the lysosome in aged brain 58 . We find evidence for activation of compensatory mechanisms to maintain protein and organelle clearance, including increased autophagosome biogenesis and mitophagy adaptors in the absence of PINK1, and increased secretion in LRRK2 G2019S brain. We propose that these compensatory pathways maintain neuron health in the short term. However with age and further age-related stresses, there may be repercussions to the engagement of compensatory mechanisms that may ultimately contribute to PD onset, such as increased secretion leading to cell-to-cell transfer of α-synuclein 3 2 0 or the inflammatory molecule mtDNA.
We find increased expression and use of alternative mitophagy adaptors in PINK1 -/mice ( Figure 2). We have not directly tested whether the compensatory mitophagy pathways are as efficient as PINK1/Parkin at clearing damaged mitochondria, but because we observed fewer AVs containing mitochondrial fragments (Figure 1h), and PINK -/mouse models are reported to have increased mitochondrial dysfunction with age or with mitochondrial damage 59,60 , we suspect that the adaptive mechanisms are less resistant to additional stresses. We hypothesize that a there may also be an increase in autophagosome biogenesis in PINK1 -/mice because of the increase in WIPI2 levels ( although further in vitro flux assays are required to confirm. We believe that the higher levels of alternate mitophagy adaptors, potentially in combination with increased autophagic flux, may be responsible for the lower levels of TFAM observed in the PINK1 -/brain. We do not yet know how this impacts mitochondrial function or resilience, considering that mtDNA levels appear unaffected in total brain lysates. Additionally, we propose that the adaptations implemented may contribute to the abnormal development of synapses observed in PINK1 deficient animals and primary neurons 29-31,61 . Previously, abnormal synapses following PINK1 loss were attributed to reduced bioenergetic capacity, based on the relocalization of mitochondria to active postsynapses 62 . We propose that abnormal NO production predicted based on the higher levels of NOS1 in PINK1 -/mouse brain tissue ( AVs derived from LRRK2 G2019S mouse brain displayed fewer significant changes to the AV cargo, but our analysis indicated that secretion was upregulated ( Figure 3a). Impaired autophagosome-lysosome fusion increases the secretion of autophagosome cargo 41,44 . Therefore, we hypothesize that the defect in trafficking and acidification caused by LRRK2 G2019S 3 5 0 16 results in an increase in secretion of some of the AV cargo through EVs as a compensatory mechanism to remove undegraded cargo. Autophagosomes can fuse with MVBs to form amphisomes, which can then release EVs extracellularly 64-66 , or autophagy cargo can be directly loaded into MVBs in an LC3-dependent mechanism 43 , but we cannot yet determine if one of these pathways drives the observed compensation more than the other. Interestingly, we identified several biomarkers of neurodegenerative disease as changed within the AVs from LRRK2 G2019S mouse brains (Supplementary Table 3). Other autophagy cargo may provide candidates for novel biomarkers to detect changes to autophagy before later stages of disease progression.

6 0
We find that with advanced age, we see fewer lysosomal proteins and more α-synuclein as AV cargo ( Figure 4, Figure 5). Cell biology and GWAS studies strongly implicate lysosomal failure as causative for PD pathology 67 , therefore impaired clearance of damaged lysosomes with age may be a contributing factor, and further exacerbate disease progression. We predict that lower levels of LGALS8 and p62/SQSTM1 contribute to the decrease in lysosomal proteins present in AVs derived from older mice, and the accumulation of TAX1BP1 is reflective of the impairments of lysosome degradation by autophagy. α-synuclein pre-formed fibrils are rapidly endocytosed and delivered to the lysosome and can induce lysosomal rupture 68 , which may contribute to the seeding progression of α-synuclein aggregates 69 . We suspect that increased delivery of αsynuclein to the lysosome with age may result in more damaged lysosomes that require 3 7 0 lysophagy. If the observed decreases in LGALS8 decrease the rate of lysophagy with age, the increase in α-synuclein in AVs may further aggravate the accumulation of defective lysosomes.
Increased secretion of α-synuclein in the LRRK2 G2019S primary cortical neurons and mice is consistent with previous findings linking both impaired autophagy and the LRRK2 G2019S mutation to increased secretion of α-synuclein 70-72 . We believe that in addition to increased phosphorylation of Rab35, the impaired acidification of autophagosomes in the LRRK2 G2019S model 16 results in the unconventional secretion of α-synuclein, similar to the secretion of αsynuclein and autophagosome cargo via Rab27a mediated pathways 44,70 . Both Rab27a and Rab35 have been linked to exosome secretion, consistent with our findings of higher TSG101 3 8 0 secretion in the LRRK2 G2019S mice in the same pattern as α-synuclein secretion ( Figure 3m, Figure 6e, j, n).
In a surprising finding, although the levels of α-synuclein increase within AVs with age, this does not correlate with the plasma levels of α-synuclein in aged LRRK2 G2019S mice (Figure 6j), which we would expect from a model where AVs fuse directly with MVBs, and the inner AV membrane becomes the EV itself.
We cannot yet rule out that the amount of α-synuclein secreted by aged neurons is unchanged, as clearance by surrounding glia may affect the amount of α-synuclein that ends up in the plasma. However, assuming that the plasma levels are indeed reflective of the amount secreted from neurons, there are a few alternative models that fit the data. Recent

9 0
research has demonstrated that α-synuclein aggregates can be released extracellularly from the lysosome or acidified MVBs 73,74 . If α-synuclein pre-formed fibril transfer occurs primarily on the surface of exosomes following the fusion of lysosomes to multivesicular bodies as proposed in Bayati et al., 2022, the number of EVs secreted may be the limiting factor for the amount of secreted α-synuclein in aged LRRK2 G2019S mice. As acidification of the AVs does not decrease with age 46 , we would not expect increases to EV secretion with age as found in the LRRK2 G2019S mice, which is supported by our measurements of the plasma levels of TSG101 in aged mice (Figure 6n).
The distinct pattern of secretion of TFAM that is increased in both LRRK2 G2019S and aged mice 4 0 0 ( Figure 6r) suggests an alternative pathway of secretion compared to α-synuclein. Recently, damaged mitochondria were shown to be secreted in an autophagy dependent manner distinct from the secretion of small EVs when normal autophagy is inhibited in ATG7 -/cells 75 . Our findings are consistent with these results, but we cannot yet determine what is driving the increased extracellular levels of TFAM. We posit that alternative secretion of TFAM in aging and the LRRK2 mutation may contribute to inflammation that drives PD progression, as TFAM is associated with mtDNA, which is potently pro-inflammatory when released from the mitochondria 76,77 .
Is compensatory secretion in the context of impaired autophagy good or bad for neuron health?

1 0
Most likely it is both, depending on context. We found that the α-synuclein in AVs from WT brain did not seem to be aggregated or fibrillar (Supplementary Figure 6). If LRRK2 mutations cause monomeric α-synuclein secretion as we suggest, it may prevent intra-neuronal buildup that can promote pathogenic aggregation, and the secreted α-synuclein may be cleared extracellularly by microglia 78 . Indeed, decreased α-synuclein in the CSF is correlated with PD-diagnosis and further reduced with older age, suggesting that secretion is protective to remove α-synuclein from the neuron where it may aggregate 18 . However if the α-synuclein is aggregated prior to secretion, as is the case with pre-formed fibrils, secretion in response to impaired autophagy could propagate PD pathology and accelerate disease progression as previously found 79,80 . If aging results in increased α-synuclein delivery to the lysosome and MVB that outpaces its 4 2 0 secretion on the surface of EVs, could this further contribute to aggregation and Lewy body formation?
Although both genetic PD models upregulate pathways to compensate for impaired autophagy, each response is specific to the type of autophagy impairment. It would not be beneficial to increase autophagosome formation in the LRRK2 G2019S model via the same process as in the PINK1 -/model if the extra autophagosomes will only then get stuck in a traffic jam. How the different impairments to autophagy are sensed and subsequently compensated for is a question that requires further study, as it may identify targetable avenues for novel PD therapies. In all, our proteomic analysis identifies changes to the autophagy pathway that may contribute to PD 4 3 0 progression in multiple ways, including regulating Lewy body propagation, neuroinflammation and mitochondrial and synapse dysfunction, further cementing the crucial role of autophagy in maintaining neuron health and demonstrating the importance of this pathway in neurodegenerative disease progression.   Representative immunoblot (c) and quantifications (mean ± SEM, unpaired t test) of the levels of GFM2 in total brain (d), AV fraction (e), and AV+PK fraction (f), normalized to total protein and WT total brain lysate levels. WT n=4, PINK1 -/-n=5. g. Representative electron micrographs of AVs derived from WT and PINK1 -/mouse brains. Insert highlights an identified AV containing a mitochondrial fragment and synaptic vesicle like structures. h. Quantification of AVs containing mitochondria from EM images (WT n=3; PINK1 -/-n=3, >400 events counted per 4 8 0 biological replicate). i-m. Representative immunoblot (i) and quantifications (mean ± SEM, unpaired t test) of the levels of TFAM in total brain (j), AV fraction (k), and AV+PK fraction (l), normalized to total protein and WT total brain lysate levels, or (m) AV+PK fraction normalized to total protein and internally normalized to total brain levels. WT n=5, PINK1 -/-n=6.  Figure 1a, with alternate mitophagy receptors highlighted in orange. b. Schematic of alternative mitophagy adaptors. c-f. Representative immunoblot (c) and quantifications (mean ± SEM, unpaired t test) of the levels of FIS1 in total brain (d), AV fraction (e), and AV+PK fraction (f), normalized to total protein and WT total brain lysate levels. WT n=5, PINK1 -/-n=6. g-j. Representative immunoblot (g) and quantifications (mean ± SEM, unpaired t test) of the levels of BNIP3 in total brain (h), AV fraction (i), and AV+PK fraction (j), normalized to total protein and WT total brain lysate levels. WT n=4, PINK1 -/-n=4. k-n. Representative immunoblot (k) and quantifications (mean ± SEM, unpaired t test) of the levels of BCL2L13 in total brain (l), AV fraction (m), and AV+PK fraction (n), normalized to total protein and WT total brain lysate levels. WT n=4, PINK1 -/-n=6. o-r. Representative immunoblot (o) and quantifications (mean ± SEM, unpaired t test) of the levels of MFN2 in total brain (p), AV fraction (q), and AV+PK fraction (r), normalized to total protein and WT total brain lysate levels. WT n=4, PINK1 -/-n=5. 5 0 0

Figure 3: LRRK2 G2019S mice increase secretion of EVs
Volcano plot analysis of the ratio of AV+PK to AV derived from brain of LRRK2 G2019S relative to WT mice. Significantly increased or decreased proteins are depicted as larger circles, except ALIX which is highlighted but did not meet the defined statistical cut-off. WT n=6; LRRK2 G2019S n=5. Proteins reported to be EV cargo are highlighted in aqua. Proteins involved in EV formation and a validated EV cargo hnRNPK are highlighted in teal. b. Graph of p-values of the top gene ontology terms using the Enrichr database of all proteins significantly changed within AVs (the dotted box in panel a.) c-f. Representative immunoblot (c) and quantifications (mean ± SEM, unpaired t test) of the levels of TSG101 in total brain (d), AV fraction (e), and AV+PK fraction (f), 5 1 0 normalized to total protein and WT total brain lysate levels. WT n=4, LRRK2 G2019S n=4. g-k.
Representative immunoblot (g) and quantifications (mean ± SEM, unpaired t test) of the levels of PIKFYVE in in total brain (h), AV fraction (i), and AV+PK fraction (j), normalized to total protein and WT total brain lysate levels, or (k) levels of AV+PK normalized to total protein and AV levels. WT n=4, LRRK2 G2019S n=4. l-m. Immunoblot (l) and (m) quantification (mean ± SEM, ANOVA with Šídák's) of levels of TSG101 in conditioned media from WT or LRRK2 G2019S primary cortical neurons, treated with DMSO or the LRRK2 kinase inhibitor MLi2 (100nM for 72h), normalized to total protein levels and WT, DMSO control. n=3 per condition. n-o.

1
Representative immunoblot (n) and (o) quantification (mean ± SEM, ANOVA with Šídák's) of levels of hnRNPK in conditioned media from WT or LRRK2 G2019S primary cortical neurons, 5 2 0 treated with DMSO or MLi2 (100nM for 72h), normalized to total protein levels and WT, DMSO control. n=3 per condition. Figure 4: Evidence of decreased lysophagy in the brain with age a. Volcano plot analysis of the ratio of AV+PK to AV derived from brain of 18-month-old relative to 1-month-old WT mice. Significantly increased or decreased proteins are depicted as larger circles. 1-month n=10; 18-month n=11. Proteins annotated as lysosomal are denoted in purple. b. Graph of p-values of the top gene ontology terms using the Enrichr database from proteins significantly lower in old compared to young brain-derived AVs (the dotted box in panel a.) c-f. Representative immunoblot (c) and quantifications (mean ± SEM, unpaired t test) of the levels of GLA in total brain (d), AV fraction (e), and AV+PK fraction (f), normalized to total protein and WT total brain lysate levels. 1-month n=4, 18-month n=4. g-j. Representative immunoblot (g) and quantifications (mean ± SEM, unpaired t test) of the levels of SCARB2 in total brain (h), AV fraction (i), and AV+PK fraction (j), normalized to total protein and WT total brain lysate levels. 1-month n=3, 18-month n=3. k-n. Representative immunoblot (k) and quantifications (mean ± SEM, unpaired t test) of the levels of LGALS8 in total brain (l), AV fraction (m), and AV+PK fraction (n), normalized to total protein and 1-month total brain lysate levels. 1-month n=4, 18month n=4. o-r. Representative immunoblot (o) and quantifications (mean ± SEM, unpaired t test) of the levels of p62/SQSTM1 in total brain (p), AV fraction (q), and AV+PK fraction (r), normalized to total protein and 1-month total brain lysate levels. 1-month n=4, 18-month n=4. s- Representative immunoblot (s) and quantifications (mean ± SEM, unpaired t test) of the levels of TAX1BP1 in total brain (t), AV fraction (u), and AV+PK fraction (v), normalized to total protein and 1-month total brain lysate levels. 1-month n=4, 18-month n=4. levels of α-synuclein in total brain (d), AV fraction (e), and AV+PK fraction (f), normalized to total protein and 7-month old total brain lysate levels. 1-month n≥5, 18-month n≥5. g. Representative immunocytochemistry of DRGs derived from 1-month-old or 18-month-old mice, and co-stained for the lysosomal marker LAMP1, α-synuclein, and the autophagosome marker LC3. 1-month n=3, 18-month n=4. h-m. Quantification of ICC images (mean ± SEM, unpaired t test), separated by cell body and axon, using automated Mander's coefficient to quantify colocalization, as indicated in the y-axis labels. LRRK2 G2019S relative to WT derived (a) total brain, (b) AV fraction, and (c) AV+PK fraction, normalized to total protein and WT total brain lysate levels. WT n=5, LRRK2 G2019S n=6. d-e.
Representative immunoblot (d) and (e) quantification (mean ± SEM, ANOVA with Šídák's) of levels of α-synuclein in conditioned media from WT or LRRK2 G2019S primary cortical neurons, treated with DMSO or the LRRK2 kinase inhibitor MLi2 (100nM for 72h), normalized to total protein levels and WT, DMSO control. n=3 per condition. f. Quantification of levels of αsynuclein in WT or LRRK2 G2019S primary cortical neurons, treated with DMSO or the LRRK2 kinase inhibitor MLi2 (100nM for 72h), normalized to total protein levels and WT, DMSO control.
1 2 n=3 per condition. g-i. Quantifications of immunoblots (mean ± SEM, ANOVA with Šídák's) for the levels of α-synculein in total brain (g), AV fraction (h), and AV+PK fraction (i) from 7-month 5 7 0 old and 18-month-old WT and LRRK2 G2019S mice, normalized to total protein and 7-month old WT total brain lysate levels. n=4 per condition. j. Quantification of immunoblots (mean ± SEM, ANOVA with Šídák's) for the level of α-synuclein from plasma from 7-month old and 18-monthold WT and LRRK2 G2019S mice, normalized to total protein and 7-month old WT plasma levels. n≥5 per condition. k-m. Quantifications of immunoblots (mean ± SEM, ANOVA with Šídák's) for the levels of TSG101 in total brain (k), AV fraction (l), and AV+PK fraction (m) from 7-month old and 18-month-old WT and LRRK2 G2019S mice, normalized to total protein and 7-month old WT total brain lysate levels. n≥3 per condition. n. Quantification of immunoblots (mean ± SEM, ANOVA with Šídák's) for the level of TSG101 from plasma from 7-month old and 18-month-old WT and LRRK2 G2019S mice, normalized to total protein and 7-month old WT plasma levels. n≥9 per condition. o-q. Quantifications of immunoblots (mean ± SEM, ANOVA with Šídák's) for the levels of TFAM in total brain (o), AV fraction (p), and AV+PK fraction (q) from 7-month old and 18-month-old WT and LRRK2 G2019S mice, normalized to total protein and 7-month old WT total brain lysate levels. n≥3 per condition. n. Quantification of immunoblots (mean ± SEM, ANOVA with Šídák's) for the level of TFAM from plasma from 7-month old and 18-month-old WT and LRRK2 G2019S mice, normalized to total protein and 7-month old WT plasma levels. n≥6 per condition.

Lead contact
Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Erika Holzbaur (holzbaur@pennmedicine.upenn.edu).

Data and code availability
The MS proteomics data have been deposited to the MassIVE repository with the dataset identifier MSV000090264. were euthanized according to University of Pennsylvania Institutional Animal Care and Use Committee approved procedures and the brain above the brainstem was removed and homogenized in a sucrose buffer (see method details).

Isolation of autophagic vesicles by differential centrifugation
Enriched autophagosome fractions were isolated following a protocol modified from Strømhaug et al., 1998 andMaday et al., 2014. Briefly, one mouse brain or ~15 million neurons were collected in a 250mM sucrose solution buffered with 10μM HEPES and 1mM EDTA at pH 7.3, homogenized using a tissue grinder, incubated with Gly-Phe-β-naphthylamide (GPN) for 7 min at 37°C to destroy lysosomes and subsequently subjected to three differential centrifugations through 9.5% Nycodenz and 33% Percoll and 30% Optiprep discontinuous gradients to isolate vesicles of the appropriate size and density. Following collection, the autophagic vesicle enriched fraction (AV) was divided into three, one third was treated with 10μg Proteinase K for 45min at 37°C, similar to Le Guerroué et al., 2017 andZellner et al., 2021, to degrade nonmembrane protected proteins and enrich for internal autophagosome cargo (AV+PK), one third 8 4 0 was membrane permeabilized by the addition of 0.2% Triton X-100 prior to the same proteinase K treatment as a negative control (AP+Tx+PK), and the other third was left untreated for identification of all internal and externally-associated proteins on autophagosomes. AV-enriched fractions were subsequently used for mass spectrometry, electron microscopy, immunoblotting and confocal microscopy.

Proteomics -sample preparation and digestion
The AV and AV+PK fractions from independent mouse brain preparations were lysed with RIPA buffer (50 mM HEPES (pH 7.4), 150 mM NaCl, 1% sodium deoxycholate, 1% NP-40, 0.1% SDS, 2.5 mM MgCl2, 10 mM sodium glycerophosphate, 10 mM sodium biphosphate) containing 8 5 0 1 µg/ml aprotinin, 1 µg/ml leupeptin, 1 mM benzamidine, 1 mM AEBSF and 1% final SDS. Lysates were sonicated on ice three times, followed by centrifugation (13000 rpm, 5 min). Protein concentration was measured by Bradford assay. Protein extracts (50 ug) were subjected to disulfide bond reduction with 5 mM TCEP (room temperature, 10 min) and alkylation with 25 mM chloroacetamide (room temperature, 20 min) and followed by TCA precipitation, prior to protease digestion. Samples were resuspended in 100 mM EPPS, pH 8.5 containing 0.1% RapiGest and digested at 37°C for 8 h with Trypsin at a 100:1 protein-to-protease ratio. Trypsin was then added at a 100:1 protein-to-protease ratio and the reaction was incubated for 6 h at 37°C. Following incubation, digestion efficiency of a small aliquot was tested. The sample was vacuum centrifuged to near dryness, resuspended in 5% formic acid for 15 min, centrifuged at 8 6 0 10000×g for 5 minutes at room temperature and subjected to subjected to C18 StageTip desalting.

Proteomics -Liquid chromatography and tandem mass spectrometry
Mass spectrometry data were collected using an Orbitrap Eclipse Tribrid Mass Spectrometer (Thermo Fisher Scientific), combined with a high-field asymmetric waveform ion mobility spectrometry (FAIMS) Pro interface, coupled to a Proxeon EASY-nLC1000 liquid chromatography (LC) pump (Thermo Fisher Scientific). Peptides were separated on a 100 μ m inner diameter microcapillary column packed in house with ~35 cm of Accucore150 resin (2.6 μ m, 150 Å, Thermo Fisher Scientific, San Jose, CA) with a gradient (ACN, 0.1% FA) over a total 8 7 0 60 min run at ~550 nL/min. For analysis, we loaded 1/4 of each fraction onto the column. The scan sequence began with an MS 1 spectrum (Orbitrap analysis resolution 120,000 at 200 Th; mass range 375−1500 m/z; automatic gain control (AGC) target 4×10 5 ; maximum injection time 50 ms) and peak-picking algorithm Advanced Peak Determination was used. Precursors for MS 2 analysis were selected using a cycle type of 1 sec/CV method (FAIMS CV=-40/-60/-80 (Schweppe et al., 2019)). MS 2 analysis consisted of collision-induced dissociation (quadrupole ion trap analysis; Rapid scan rate; AGC 2.0×10 4 ; isolation window 0.7 Th; normalized collision energy (NCE) 35; maximum injection time 35 ms). Monoisotopic peak assignment was used, determined charge states between 2 and 6 were required for sequencing, previously 1 9 interrogated precursors were excluded using a dynamic window (60 s ± 10 ppm) and dependent 8 8 0 scan was performed on a single charge state per precursor.

Proteomics -Data analysis
Mass spectra were processed using Protein Discoverer using the Minora algorithm (set to default parameters). Database searching included all canonical entries from the mouse Reference Proteome UniProt database (SwissProt -2019-12), as well as an in-house curated list of contaminants. The identification of proteins was performed using the SEQUEST-HT engine against the database using the following parameters: a tolerance level of 10 ppm for MS 1 and 0.6 Da for MS 2 post-recalibration and the false discovery rate of the Percolator decoy database search was set to 1%. Trypsin was used as the digestion enzyme, two missed 8 9 0 cleavages were allowed, and the minimal peptide length was set to 7 amino acids. Carbamidomethylation of cysteine residues (+57.021 Da) were set as static modifications, while oxidation of methionine residues (+15.995 Da) was set as a variable modification. Final proteinlevel FDR was set to 1%. Precursor abundance quantification was determined based on intensity and the minimum replicate feature parameter was set at 50%. Proteins were quantified based on unique and razor peptides.
Protein quantification values were exported for further analysis in Microsoft Excel and Perseus (Tyanova et al., 2016)and statistical test and parameters used are indicated in the corresponding Supplementary Data Tables datasets. Briefly, Welch's t-test analysis was 9 0 0 performed to compare two datasets, using s0 parameter (in essence a minimal fold change cutoff) and correction for multiple comparison was achieved by the permutation-based FDR method, both functions that are built-in in Perseus software.    Cell body 10 -7 10 -6 10 -5 10 -4 10 -3 10 -2 10 -1 10 0 10 1 p-value  b r a i n l y s a t e A V A V + P K A V + T x + P K b r a i n l y s a t e A V A V + P K A V + T x + P K b r a i n l y s a t e A V A V + P K A V + T x + P K kDa b r a i n l y s a t e A V A V + P K A V + T x + P K b r a i n l y s a t e A V A V + P K A V + T x + P K b r a i n l y s a t e A V A V + P K A V + T x + P K  Vacuolar membrane Vacuolar lumen 10 -7 10 -6 10 -5 10 -4 10 -3 10 -2 10 -1 10 0 10 1 p-value 18-month-old : 1-month-old cargo score      b r a i n l y s a t e A V A V + P K A V + T x + P K b r a i n l y s a t e A V A V + P K A V + T x + P K kDa b r a i n l y s a t e A V A V + P K A V + T x + P K b r a i n l y s a t e A V A V + P K Figure 2: MFF and HUWE1 not changed in PINK1 -/brain or AVs (related to Figure 2) a-d. Representative immunoblot (a) and quantifications (mean ± SEM, unpaired t test) of the levels of MFF in total brain (b), AV f raction (b), and AV +PK fraction (d), normalized to total protein and WT total brain lysate levels. WT n=6, PINK1 -/-n=6. f-i. Representative immunoblot (f) and quantifications (mean ± SEM, unpaired t test) of the levels of HUWE1 in total brain (g), AV fraction (h), and AV +PK fraction (i), normalized to total protein and WT total brain lysate levels. WT n=6, PINK1 -/-n=6.

PINK1 -/-
Supplementary  b r a i n l y s a t e A V A V + P K A V + T x + P K b r a i n l y s a t e A V A V + P K A V + T x + P K kDa b r a i n l y s a t e A V A V + P K A V + T x + P K b r a i n l y s a t e A V A V + P K A V + T x + P K kDa b r a i n l y s a t e A V A V + P K A V + T x + P K b r a i n l y s a t e A V A V + P K  Endosome membrane Cell-cell contact zone Glutamatergic synapse 10 -8 10 -7 10 -6 10 -5 10 -4 10 -3 10 -2 10 -1 10 0 10 1 p-value  Figure 1a, with presynaptic proteins highlighted in pink, post-synaptic proteins highlighted in violet, and proteins associated in both the pre and post synapse highlighted in maroon. b. Graph of p-values of the top gene ontology terms using the Enrichr database from proteins significantly higher in PINK1 -/compared to WT brain-derived AVs (the dotted box in panel a.) c. Diagram of nitric oxide and spermidine synthesis pathways, with proteins significantly changed as cargo in PINK1 -/mice highlighted in gold. d-g.
Representative immunoblot (d) and quantifications (mean ± SEM, unpaired t test) of the levels of NOS1 in total brain (e), AV f raction (f), and AV +PK fraction (g), normalized to total protein and WT total brain lysate levels. WT n=6, PINK1 -/-n=6. h-k. Representative immunoblot (h) and quantifications (mean ± SEM, unpaired t test) of the levels of SRM in total brain (i), AV f raction (j), and AV +PK fraction (k), normalized to total protein and WT total brain lysate levels. WT n=4, PINK1 -/-n=5. l-o. Representative immunoblot (l) and quantifications (mean ± SEM, unpaired t test) of the levels of MAT2A in total brain (m), AV f raction (n), and AV +PK fraction (o), normalized to total protein and WT total brain lysate levels. WT n=4, PINK1 -/-n=5. p-s. Representative immunoblot (p) and quantifications (mean ± SEM, unpaired t test) of the levels of WIPI2 in total brain (q), AV f raction (r), and AV +PK fraction (s), normalized to total protein and WT total brain lysate levels. WT n=3, PINK1 -/-n=6.   Figure 4: LRRK2 G2019S AVs have some common changes to AV ca rgo as PINK1 -/but does no effect on mitochondrial fragment engulfment, and increased secretion of EVs (related to Figure 3) a. Euler diagram of overlap of significant changes between PINK1 -/and WT AV cargo, and LRRK2 G2019S and WT AV cargo. b. Scatter plot showing the overlapping changes to AV cargo between PINK1 -/and LRRK2 G2019S derived AV s. Size of circle denotes the LRRK2 G2019S p value, and color of circle denotes the PINK1 -/p value. c. Representative electron micrographs of AVs derived from WT or LRRK2 G2019S mouse brains d. Quantification of AVs containing mitochondria from EM images. e,f. (e) Immunoblot of total levels of TSG101 in WT and LRRK2 G2019S primary cortical neurons, treated with DMSO or MLi2 (100nM for 72h) and (f) quantification (mean ± SEM, ANOVA with Šídák's) of TSG101 levels normalized to total protein and DMSO, WT control. n=3 per condition. g,h. (g) Representative immunoblot of total levels of hnRNPK in WT and LRRK2 G2019S primary cortical neurons, treated with DMSO or MLi2 (100nM for 72h) and (h) quantification (mean ± SEM, ANOVA with Šídák's) of hnRNPK levels normalized to total protein and DMSO, WT control. n=3 per condition. i-l. Representative immunoblot (i) and quantifications (mean ± SEM, unpaired t test) of the levels of hnRNPK in total brain (l), AV fraction (k), and AV +PK fraction (l), normalized to total protein and WT total brain lysate levels. WT n=5, LRRK2 G2019S n=7. b r a i n l y s a t e A V A V + P K A V + T x + P K b r a i n l y s a t e A V A V + P K A V + T x + P K b r a i n l y s a t e A V A V + P K A V + T x + P K kDa b r a i n l y s a t e A V A V + P K A V + T x + P K b r a i n l y s a t e A V A V + P K A V + T x + P K b r a i n l y s a t e A V A V + P K A V + T x + P K  Scatter plot showing the overlapping changes to AV cargo between aging and LRRK2 G2019S derived AV s. Size of circle denotes the aging p value, and color of circle denotes the LRRK2 G2019S p value. b. Euler diagram of overlap of significant changes between PINK1 -/and WT AV cargo, and aging AV cargo. c. Scatter plot showing the overlapping changes to AV cargo between aging and PINK1 -/derived AV s. Size of circle denotes the aging p value, and color of circle denotes the PINK1 -/p value. d-g. Representative immunoblot (d) and quantifications (mean ± SEM, unpaired t test) of the levels of LAMP1 in total brain (e), AV fraction (f), and AV +PK fraction (g), normalized to total protein and WT total brain lysate levels. 1-month n=4, 18-month n=4. h-k. Representative immunoblot (h) and quantifications (mean ± SEM, unpaired t test) of the levels of RagA in total brain (i), AV f raction (j), and AV +PK fraction (k), normalized to total protein and WT total brain lysate levels. 1-month n=4, 18-month n=4. m.
Representative electron micrographs of AVs derived from 1-month and 18-month old mouse brains. n,o. Quantification of (n) autophagolysosomes or (o) AVs containing mitochondria from EM images (1-month n = 3 and 18-month n = 2, >1400 events counted per condition). α-synuclein p-S129 α-synuclein ThT intensity per g protein ThT intensity per g protein ThT intensity per g protein Total brain AV+PK fraction Positive control 1 month 18 months BSA control BSA 37°C 1 month 18 months b r a i n l y s a t e A V A V + P K A V + T x + P K b r a i n l y s a t e A V A V + P K A V + T x + P K b r a i n l y s a t e A V A V + P K A V + T x + P K  Figure 5) a-c. Quantification (mean ± SEM, unpaired t test) of Thioflavin T AU, normalized to µg protein, from (a) total brain fraction and (b) AV+PK fraction from 1-month (n=6) and 18-month (n=6) mice, and (c) positive control of denatured BSA (n=5). d. Representative immunoblot of asynuclein and phosphorylated S129-a-synuclein from 1-month, 7-month and 18-month old mice and AV fractions, as indicated.
b r a i n l y s a t e A V A V + P K A V + T x + P K b r a i n l y s a t e A V A V + P K A V + T x + P K b r a i n l y s a t e A V A V + P K A V + T x + P K b r a i n l y s a t e A V A V + P K A V + T x + P K   Figure 6) a. Representative immunoblot of total brain and AV fractio ns for a -synuclein, TFAM and TSG101 from wildtype and LRRK2 G2019S 7-month-old and 18-month-old mice. b,c. Quantification (mean ± SEM, ANOVA with Šídák's) of TFAM levels, normalized to total protein and DMSO, WT control, from (b) conditioned media or (c) cell lysate from WT or LRRK2 G2019S primary cortical neurons, treated with DMSO or the LRRK2 kinase inhibitor MLi2 (100nM for 72h).