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Autophagic stress activates distinct compensatory secretory pathways in neurons
Sierra D. Palumbos1,2, Jacob Popolow1, Juliet Goldsmith1,2, Erika L.F. Holzbaur1,2*
1Department of Physiology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, PA 19104, USA; 2Aligning Science Across Parkinson’s (ASAP) Collaborative
Research Network, Chevy Chase, MD 20815, USA
*Correspondence: holzbaur@pennmedicine.upenn.edu (E.L.F.H.)
ORCID IDs: S.D.P 0000-0002-3595-984X; J.G. 0000-0002-6935-1744; E.L.F.H. 0000-0001-
5389-4114
Keywords: Autophagy, Parkinson’s disease, Secretion, Mitochondria, Neurodegeneration
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SIGNIFICANCE
A hallmark feature of many neurodegenerative diseases is autophagy dysfunction, resulting in the
accumulation of damaged proteins and organelles that is detrimental to neuronal health. The late
onset of neurodegenerative diseases, however, suggests alternative quality control mechanisms
may delay neuronal degeneration. Here, we demonstrate that neurons expressing a Parkinson’s
Disease-causing mutation upregulate the release of two extracellular vesicle populations. First, we
observe the increased expulsion of secreted autophagosomes to mediate cellular waste disposal.
Second, we observe the increased release of exosomes, likely to facilitate transcellular
communication. Thus, we propose that increases in secretory autophagy and exosome release are
a homeostatic response in neurons undergoing chronic stress.
ABSTRACT
Autophagic dysfunction is a hallmark of neurodegenerative disease, leaving neurons vulnerable to
the accumulation of damaged organelles and proteins. However, the late onset of diseases suggests
that compensatory quality control mechanisms may be engaged to delay the deleterious effects
induced by compromised autophagy. Neurons expressing common familial Parkinson’s disease
(PD)-associated mutations in LRRK2 kinase exhibit defective autophagy. Here, we demonstrate
that both primary murine neurons and human iPSC-derived neurons harboring pathogenic LRRK2
upregulate the secretion of extracellular vesicles. We used unbiased proteomics to characterize the
secretome of LRRK2G2019S neurons and found that autophagic cargos including mitochondrial
proteins were enriched. Based on these observations, we hypothesized that autophagosomes are
rerouted toward secretion when cell-autonomous degradation is compromised, likely to mediate
clearance of undegraded cellular waste. Immunoblotting confirmed the release of autophagic
cargos and immunocytochemistry demonstrated that secretory autophagy was upregulated in
LRRK2G2019S neurons. We als o found that LRRK2G2019S neurons upregulate the release of
exosomes containing miRNAs. Live-cell imaging confirmed that this upregulation of exosomal
release was dependent on hyperactive LRRK2 activity, while pharmacological experiments
indicate that this release staves off apoptosis. Finally, we show that markers of both vesicle
populations are upregulated in plasma from mice expressing pathogenic LRRK2. In sum, we find
that neurons expressing pathogenic LRRK2 upregulate the compensatory release of secreted
autophagosomes and exosomes, to mediate waste disposal and transcellular communication,
respectively. We propose that this increased secretion contributes to the maintenance of cellular
homeostasis, delaying neurodegenerative disease progression over the short term while potentially
contributing to increased neuroinflammation over the longer term.
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INTRODUCTION
Macroautophagy, hereafter referred to as autophagy, is a fundamental cellular process by
which aggregated proteins and dysfunctional organelles are degraded (1). Neurons utilize
autophagy as a homeostatic mechanism, exhibiting robust basal autophagy in the absence of
cellular stressors. Knockout of critical components of the autophagy machinery, including Atg5
and Atg7 is sufficient to induce neurodegeneration (2, 3). In neurons under basal conditions, cargos
to be cleared by autophagy are captured within double membrane autophagosomes that forms
preferentially at axonal termini as well as presynaptic sites and are then trafficked back toward the
cell soma (4, 5). Autophagosomes fuse with lysosomes en route to the soma in order to degrade
internalized cargos (6). Disruption of either autophagosome trafficking or lysosomal fusion inhibit
compartment maturation and the subsequent degradation of cargos internalized within axonal
autophagosomes (6, 7).
In many neurodegenerative diseases, autophagic dysfunction results in the accumulation
of protein aggregates and dysfunctional organelles, threatening neuronal homeostasis (1, 8, 9).
Parkinson’s Disease (PD), for example, is a progressive neurodegenerative disease characterized
by autophagic dysfunction, accumulation of 𝛼-synuclein aggregates, and neuroinflammation (9–
11). Mutations that induce hyperactivity of the kinase LRRK2, including LRRK2G2019S and
LRRK2R1441H, represent some of the most common causes of familial PD. LRRK2 hyperactivity
leads to aberrant phosphorylation of Rab GTPases, key regulators of trafficking pathways in the
cell (12, 13), including the trafficking and maturation of neuronal autophagosomes (Figure 1A)
(7, 14–16).
We hypothesized that the resulting strain on autophagy-dependent degradation in neurons
might induce activation of alternative quality control mechanisms to prevent or delay
proteotoxicity. One possibility is that neurons expressing hyperactive LRRK2 may upregulate
secretion, ejecting undegraded cellular waste to the extracellular space via autophagy-dependent
secretion. Secretory autophagy is a broad term encompassing multiple pathways that rely on
autophagic proteins to mediate the release of diverse contents (17, 18). In canonical secretory
autophagy, autophagic proteins mediate the fusion of the outer membrane of an autophagosome
with the plasma membrane to release soluble proteins trapped between the vesicular membranes
and the inner autophagic vesicle (19, 20). Non-canonical secretory autophagy pathways have also
been identified that mediate the release of different vesicle populations or organelles, including
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exosomes (21), exophers (22), and mitochondria (23). Given that inhibition of autophagosome-
lysosome fusion has been shown to trigger the upregulation of autophagy-dependent secretion (24–
27), we reasoned that neurons expressing pathogenic LRRK2 mutations may similarly engage
secretion as a compensatory mechanism in response to autophagic dysfunction.
Here, we demonstrate that neurons expressing hyperactive LRRK2 activate the
compensatory release of both secreted autophagosomes and exosomes. We performed unbiased
proteomic and transcriptomic characterization of vesicles released from LRRK2G2019S neurons,
demonstrating that secretory autophagy exports known cargos of autophagy, including
mitochondria and synaptic proteins, while we find that the secreted exosomes contain microRNAs
(miRNAs) known to regulate autophagy and inflammation. As further confirmation of our model,
we used both fixed and live-cell imaging to demonstrate that the two vesicle populations exhibit
distinct spatial and temporal dynamics of release. Further, we find that the release of exosomes is
neuroprotective. Finally, we show that release of both vesicle populations is upregulated in plasma
of a mouse line expressing pathogenic LRRK2G2019S. Based on these findings, we propose that
activation of these two secretion pathways mediate distinct roles, the release of cellular waste via
secreted autophagosomes and transcellular communication via exosomes. Together, we propose
that upregulation of these secretory pathways acts as a compensatory mechanism to sustain cellular
homeostasis when autophagy-mediated degradation is impaired. Importantly, however, the
elevated secretion of proinflammatory contents such as mitochondrial DNA (28, 29) and miRNAs
(30, 31) is likely to negatively affect neuronal health over the longer term, contributing to
neurodegenerative disease progression in patients with PD.
RESULTS
LRRK2 mutant neurons upregulate secretion
Pathogenic mutations in LRRK2 induce kinase hyperactivity, leading to inappropriate
phosphorylation of kinase substrates, predominantly organelle-associated Rab GTPases (15), and
a resulting disruption in intracellular trafficking pathways (12), specifically disrupting
autophagosome maturation in neurons (7, 16). To test our hypothesis that this disruption might
lead to a compensatory increase in secretion, we began by focusing on the most common PD-
linked mutation in LRRK2, a G2019S missense mutation. We isolated embryonic cortical neurons
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from wild type and LRRK2G2019S mice. Conditioned media were collected from cultured neurons
over 10 days and EVs were enriched from the harvested media. For each replicate, the same
number of neurons were plated, and the resulting EV measurements were normalized total protein
levels in cell lysates. We tracked the size and concentration of particles secreted using Nanoparticle
Tracking Analysis (NTA) and observed a 15% increase in particles in EV samples isolated from
LRRK2G2019S neurons as compared to EV samples isolated from control neurons (Figure 1B, C).
No significant changes in size distribution were detected, with the most commonly detected
particle size being 135nm in wild type and 145nm in LRRK2G2019S samples (Figure 1F). Several
shoulder peaks were also detected in our analysis of both wild type and LRRK2 particles,
suggesting the release of multiple vesicle populations over a range of sizes (Figure 1C).
To extend this observation, we examined EV secretion from human iPSC-derived neurons
(KOLF2.1J (32)) harboring a distinct Parkinson’s Disease-causing mutation, LRRK2R1441H. This
mutation results in a more profound hyperactivation of the LRRK2 kinase as compared to G2019S,
leading to more profound deficits in autophagosome trafficking (15, 16). Again, we observed
significantly more particles released from LRRK2R1441H neurons as compared to isogenic control
neurons (a 42% increase) (Figure 1D), with no change in size distribution detected between the
genotypes (Figure 1F). While this is a cross-species comparison, the effect size on secretion
appears to be correlated with the extent of kinase hyperactivation.
To confirm these findings, we used CalceinAM to assay intact vesicles collected from WT
and LRRK2G2019S neurons following EV isolation via ultracentrifugation (33). CalceinAM
fluoresces after passively entering an EV that is unpermeabilized and thus the fluorescent signal
corresponds to intact, membrane-enclosed structures. Consistent with our NTA results, we
observed significantly more CalceinAM puncta in samples collected from LRRK2G2019S mutant
neurons (Figure 1G, H), indicating increased secretion of extracellular vesicles. Thus, in both
mouse and human neurons, hyperactive LRRK2 induces increased secretion of extracellular
vesicles.
Proteomic profiling of offloaded vesicles
Extracellular vesicles serve a variety of purposes (34, 35), including waste disposal (22,
36) and transcellular signaling (37), and therefore may contain a wide range of internalized cargos
and transmembrane proteins that can vary by vesicle class and cell type. To characterize the
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released vesicles, we first performed quantitative proteomic analysis of isolated vesicles from 5
independent cultures of control and of LRRK2G2019S primary cortical neurons. Extracellular
vesicles were enriched via ultracentrifugation to broadly capture released EVs. The protein
concentration of isolated EVs was normalized across samples prior to quantitative mass
spectrometry analysis (Supplemental Figure 1A-B). Detected proteins were assigned an
expression value based on the number of detected reads within a given sample (median expression
value = 0). Vesicle enrichment for both genotypes was confirmed by comparison to previous EV
proteomic analysis that characterized proteins found in either small or large vesicle fractions (38)
(Figure 2A, Supplemental Figure 1C). We noted the presence of 89/100 of the most common
EV-associated proteins, which were readily detected above the median detection threshold in both
control and LRRK2 samples (expression value > 0) (39) (Figure 2E, Supplemental Figure 1D).
Next, we compared the expression of detected proteins associated with either small EVs (Figure
2B) or large EVs (Figure 2C) across genotypes. While we detected no change in the average
expression value of small-EV associated proteins, we did detect significantly higher expression
values for large-EV associated proteins in LRRK2G2019S samples, suggesting that large EVs were
likely enriched in these samples.
Ontology analysis of the secretomes of LRRK2 G2019S and wild type confirmed that proteins
associated with secretion, including those associated with exosome formation, e.g., multivesicular
body (MVB) proteins, were readily released (Figure 2D and Supplemental Figure 1E).
Interestingly, we noted that proteins associated with synaptic function, mitochondria and
autophagy were also enriched in the secretomes from both LRRK2 G2019S and wild type neurons
(Figure 2D and Supplemental Figure 1E). Recently, we used proteomic analysis to define the
basal cargos of neuronal autophagosomes and detected both synaptic proteins and mitochondria as
enriched autophagosome cargo (40). Given this commonality, we reasoned that these neurons
could be releasing a population of autophagic vesicles via secretory autophagy. To test this
possibility, we compared all detected proteins in EVs isolated from LRRK2G2019S or control
neurons to the previously characterized proteome of autophagosomal cargos from brain (40). In
both cases, over 70% of known autophagic cargos from brain were detected within our EV
proteomic datasets (Figure 2E).
If wild type and LRRK2G2019S neurons are releasing secreted autophagosomes, members of
the ATG8 family, well-established markers of autophagosomes, should be detected among the
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secreted proteins. Consistent with this, nearly all secretory autophagy pathways have reported the
release of the autophagic protein LC3B (17, 21, 22, 24, 25), a member of the ATG8 family. In line
with previous work, we detected 5 of 6 ATG8s in both the LRRK2G2019S and control samples, with
the highest detected being LC3B (Figure 2E, Supplemental Figure 1D). Thus, unbiased
proteomic profiling of the secretomes from either control or LRRK2G2019S primary cortical neurons
detected markers associated with multiple classes of extracellular vesicles, including exosomes
and secreted autophagosomes.
To determine how the secretory proteome was altered in LRRK2G2019S mutants, we
performed differential expression analysis and observed 250 upregulated proteins and 80
downregulated proteins in samples from LRRK2G2019S neurons as compared to control neurons
(Figure 2F). Ontology analysis of the differentially expressed proteins suggests that mitochondrial
proteins are the most prominent cargo upregulated in LRRK2G2019S EVs (Supplemental Figure
1F). Indeed, 92/250 upregulated secreted proteins are classified as mitochondrial by MitoCarta3.0
(41). This observation could indicate that secreted autophagosomes are more readily released by
LRRK2G2019S as 20% of all neuronal autophagosome cargo is mitochondrially-derived (40). The
contents of LRRK2G2019S autophagosomes are largely unchanged from wild type, with
mitochondria being readily targeted for autophagosome engulfment (42). Further, while
autophagosome maturation is impaired in LRRK2G2019S neurons, overall numbers of
autophagosomes are not significantly impacted. Thus, our findings suggest that LRRK2G2019S
neurons, which exhibit autophagosome maturation defects, may be redirecting unacidified
autophagosomes toward extracellular release.
Transcriptomic profiling of released vesicles
In addition to proteins, many extracellular vesicles contain RNAs, including miRNAs, to
mediate transcellular communication. We therefore performed unbiased small RNA (smRNA)
sequencing of isolated vesicles from both LRRK2G2019S and wild type neurons. Secreted
extracellular vesicles were isolated via ultracentrifugation followed by RNA extraction, smRNA
library preparation, and subsequent sequencing of the normalized libraries. In EVs isolated from
both wild type and LRRK2G2019S, miRNAs were detected, with 391 and 499 miRNAs reaching our
detection threshold (average of at least 2 reads across 5 samples), respectively. KEGG analysis of
the downstream targets of the top 25 miRNAs detected in EVs isolated from both wild type and
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LRRK2G2019S neurons confirmed that the secreted vesicles were likely mediating transcellular
communication (Figure 2G). Many signaling pathways, including ones that impact inflammatory
responses, e.g., MAPK, were enriched in both the wild type and LRRK2G2019S secretome (43). In
both genotypes, 4 of the top 5 detected miRNAs were of the let-7 miRNA family (Figure 2H),
which play a role in many processes, including autophagy and inflammation (44, 45). Thus, both
wild type and LRRK2G2019S neurons are offloading miRNAs which could be relevant to neuronal
homeostasis. We next asked whether any miRNAs were differentially expressed, and detected no
miRNAs significantly upregulated in either genotype (Supplemental Figure 2A). While no
individual miRNA was significantly upregulated in LRRK2 EVs, the average levels of the top 50
detected miRNAs were all elevated in LRRK2 compared to wild type (Figure 2I, Supplemental
Figure 2B). Together, our immunoblots and transcriptomics results argue that it is the overall
quantity, and not the contents, of released exosomes that are altered in LRRK2G2019S neurons.
Hyperactive LRRK2 enhances the secretion of distinct classes of extracellular vesicles
To identify the class(es) of extracellular vesicles being offloaded from LRRK2G2019S
neurons, we performed differential ultracentrifugation of conditioned media to separate EV
populations based on density. Large extracellular vesicles, including microvesicles and secreted
autophagosomes, were enriched via a 20,000xg spin (large EVs/P20), followed by sequential
enrichment of small EVs, including exosomes, via a 100,000xg spin (small EVs/P100) (Figure
3A)(46). Large (P20) and small (P100) EV pellets were isolated and analyzed by immunoblot
using antibodies against known EV-associated transmembrane proteins and cargos (Figure 3B).
Given that our proteomics results closely mirrored previous proteomic profiling of brain
autophagosomes, we first probed for LC3/ATG8 which is offloaded in many secretory autophagy
pathways. LC3-I is conjugated to phosphatidylethanolamine to form LC3-II, which marks the
forming autophagosome and stays associated throughout autophagosome maturation (47, 48).
Across both genotypes, the majority of both LC3-I and LC3-II was detected in the large EV/P20
fraction. Of note, we observed significantly more LC3-II in EVs isolated from LRRK2G2019S
neurons as compared to control neurons in the P20 fraction (2.1- fold increase, p=0.0089) (Figure
3C, D).
Most extracellular vesicles are enriched for a family of transmembrane proteins, the
tetraspanins, which form microdomains on vesicles important for functions including biogenesis
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and cargo sorting. We compared the expression of CD81 and CD63, the two most highly enriched
tetraspanins on exosomes (49), on EVs isolated from control vs. LRRK2G2019S neurons and
observed no change in CD81 or CD63 expression in the large EV/P20 fraction. Thus, the large
LC3-II+ vesicles being secreted from LRRK2 mutant neurons lack tetraspanins, an observation
consistent with their identification as secreted autophagosomes. Strikingly, in the P100 fraction
enriched for small EVs, we observed significantly more CD81 (8.4 fold increase) and CD63 (2.6
fold increase) in EVs released from LRRK2 mutant neurons as compared to wild type neurons
(Figure 3E, F). Changes in the relative enrichment of these proteins were not due to changes in
protein expression as no significant changes were observed by immunoblot analysis of neuronal
lysates (Supplemental Figure 3).
Together, these observations suggest that two populations of EVs are upregulated in
LRRK2 mutants: 1) larger EVs that are positive for LC3-II but lack canonical tetraspanins and 2)
small EVs enriched for CD63 and CD81. Given our proteomic observations suggesting that
autophagic cargo are expelled from LRRK2 neurons and previous literature that has found CD63
expression largely restricted to exosomes, we propose that these two EV populations (large EVs
and small EVs) represent secreted autophagosomes and exosomes, respectively.
Large and small EVs contain distinct cargos
To provide additional insight into the nature and function of the two populations of secreted
vesicles detected, we used immunoblotting to compare cargos associated with either secreted
autophagosomes or exosomes. Given the size and density of autophagosomes (50), we first asked
if known autophagosome cargos were enriched in our P20 fraction. Previously, our lab defined the
contents of neuronal autophagosomes under basal conditions and found that both synaptic proteins,
including Synapsin-1, and mitochondria enriched in the nucleoid marker TFAM are targeted to
autophagosomes under basal conditions (40). More recently, we found that several cargos are
increased in autophagosomes isolated from the brains of mice expressing mutant LRRK2,
including the RNA-binding protein, hnRNPK (42). hnRNPK has been shown to interact with LC3
and is secreted within EVs released via LC-3 Dependent Extracellular vesicle Loading and
Secretion (LDELS)(25). Consistent with our model that hyperactive LRRK2 activity induces the
release of secreted autophagosomes, we saw significant increases in the release of Syn-1 (1.8-fold
increase), TFAM (3.2-fold increase), and hnRNPK (5.9-fold increase) in the LRRK2 P20 pellet as
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compared to controls when measured by immunoblotting (Figure 3 G-I). In contrast, these
proteins were minimally detected in the P100 fractions from either LRRK2G2019S or wild type
neurons.
Exosomes originate in the multivesicular body, or MVB, where different contents, e.g.,
ESCRT proteins and RNAs, are loaded into small vesicles before being released into the
extracellular space (51). We tracked the expression of the ESCRT protein and canonical EV cargo,
TSG-101 and observed a 3.5-fold increase in the small EV/P100 fraction in LRRK2G2019S mutants
(Figure 3H). In contrast, we observed no significant change in enrichment of TSG-101 in the P20
fraction corresponding to large EVs. Exosomes are very small and thus contain limited cargo, often
enriched for miRNA and mRNA (51, 52). Our smRNA transcriptomic analysis confirmed that
miRNAs were released by both wild type and LRRK2G2019S neurons. To determine if RNAs were
contained within secreted exosomes, we asked whether P100 fractions isolated from wild type or
LRRK2G2019S neurons contained RNA. We used the RNA specific dye, SYTO RNASelect
(Thermo), to measure relative levels in fluorescence across our different conditions and observed
that RNA could be readily detected in both wild type and LRRK2G2019S P100 fractions
(Supplemental Figure 2C), suggesting that RNAs are likely cargos within released exosomes.
LRRK2 mutant neurons release secreted autophagosomes
ATG 8 family members (LC3/GABARAP) are stably associated with both the inner and
outer membrane of mature autophagosomes. In canonical secretory autophagy, the outer
LC3/GABARAP membrane fuses with the plasma membrane to release both lumen contents and
the inner autophagosome vesicle (53). If autophagosome content is secreted in this manner from
the cortical neurons examined here, LC3 should be detected at the cell surface. We transfected
wildtype and LRRK2G2019S neurons with fluorescently labeled LC3 and tracked expression at the
cell surface using live TIRF microscopy. Consistent with secretory autophagy events, we observed
frequent LC3 bursts at the cell surface in both control and LRRK2G2019S neurons (Figure 4A-B).
To quantitate this effect, we measured external LC3/GABARAP by immunocytochemistry using
an antibody against GABARAPL1/L2/L3 in unpermeabilized control (Figure 4C) and
LRRK2G2019S neurons (Figure 4E). We detected significantly more GABARAPL1/L2/L3 at the
cell surface of LRRK2G2019S neurons, consistent with a higher level of secretory autophagy (Figure
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4G). We confirmed that this signal could be detected in TIRF (Figure 4D, F) and was distinct from
LC3/GABARAP localization in permeabilized cells (Supplemental Figure 3B).
Interestingly, we noted that in both our live and fixed imaging approaches, surface
GABARAPL1/L2/L3was spatially enriched in a somal compartment which often extended into a
single tapered process, consistent with the primary dendrite (Figure 4C-E). Morphological
characterization confirmed that in ~70% of neurons imaged, an accumulation of external
GABARAPL1/L2/L3 could be observed at the presumed primary dendrite. We transfected neurons
with the AIS marker, Ankyrin G (AnkG) and confirmed that the accumulation of
GABARAPL1/L2/L3 was dendritic, rather than axonal (Figure 4F). Thus, LC3 secretion events
are restricted to the somatodendritic compartment. This observation mirrors previous observations
from live cell imaging indicating that once axonal autophagosomes enter the soma, they are
constrained to the somal and dendritic regions(5).
LRRK2 mutant neurons upregulate release of exosomes
Our immunoblotting results suggest that small EVs containing both CD81 and CD63 are
also secreted from LRRK2G2019S neurons. As immunoblotting relies on the pooling of EVs to look
for global changes, we next used ExoView (Spectradyne) to track tetraspanin expression at the
level of individual EVs. We captured EVs from both wild type and LRRK2G2019S neurons using an
anti-CD81 antibody followed by subsequent antibody detection against CD81, CD9 and CD63
(Figure 5A). Consistent with our earlier observations, more CD81+ EVs were released from
LRRK2G2019S neurons compared to wild type neurons (Figure 5B). Additionally, we detected more
CD81+/CD63+, and CD81+/CD9+ dual-labeled vesicles captured from LRRK2G2019S EVs (Figure
5B). These observations corroborated our immunoblotting results, where we observed substantial
CD81 and CD63 release from LRRK2G2019S neurons, consistent with the release of exosomes.
CD63 is a commonly used marker of exosomes (51, 54). Given our immunoblot results
that CD63 is significantly enriched in the small EV/P100 fraction from LRRK2G2019S neurons, we
sought to better characterize the secretion of CD63 positive EVs using live cell imaging. We
expressed the pH sensitive fluorophore, pHluorin, tagged to CD63 (CD63-pHluorin) in primary
cortical neurons isolated from wild type or LRRK2G2019S mice. The modified GFP signal of
CD63pHluorin is quenched in acidic environments such as the MVB, and is only observed upon
fusion with the extracellular membrane for EV release (Figure 5C). We measured CD63-pHluorin
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signal in control and LRRK2G2019S neurons using TIRF microscopy. New fusion events could be
readily identified when the first frame of the video was subtracted from all subsequent frames
(Figure 5D-G), or via kymographs (Figure 5H). We observed a 4-fold increase in fusion events
in LRRK2G2019S neurons compared to wild type neurons suggesting that exosomal secretion is
upregulated in LRRK2G2019S neurons (Figure 5I). Additionally, this upregulation of CD63
secretion events is dependent on LRRK2 hyperactivity as pre-treatment of neurons with MLI-2, a
selective LRRK2 kinase inhibitor(55), blocked the observed increase of CD63 fusion events
(Figure 5I). In contrast to the LC3 secretion events described above, CD63-postitive release events
were primarily observed on the cell soma with no clear spatial clustering near or at the primary
dendrite, although occasionally fusion events could be observed on neurites. Individual fusion
events could be observed to persist beyond the length of the movie, suggesting that CD63 could
be docked upon MVB fusion as well as released.
To determine whether human neurons expressing the LRRK2R1441H mutation similarly
released CD63+ EVs, we also performed live cell imaging of LRRK2R1441H and isogenic control
iPSC-derived neurons expressing CD63-pHluorin. Again, we observed significantly more fusion
events in LRRK2R1441H neurons compared to wild type neurons (Figure 5J). Thus, hyperactive
LRRK2 promotes the secretion of CD63+ EVs in both mouse and human neurons.
LRRK2 hyperactivity prompts the release of exosomes via secretory autophagy
While the majority of secreted LC3 was detected in our P20 fraction, we also could detect
a significant increase in secreted LC3-II in the LRRK2G2019S P100 fraction in a direct comparison
(p=0.0286). Several groups have demonstrated that LC3/ATG8 lipidation and the LC3-conjugation
machinery are critical for several secretory autophagy pathways, including LDELS(25), secretory
autophagy during lysosomal inhibition (SALI) (24), and apilimod-mediated secretion of exosomes
(21). To determine if the LRRK2-mediated secretion of exosomes was similarly dependent on LC3
conjugation, we knocked down ATG7 using siRNA (Supplemental Figure 4A-B) and tracked
CD63-pHluorin fusion events in LRRK2G2019S neurons. We determined that ATG7 activity was
required for LRRK2 mediated exosome release as we observed a nearly 50% reduction in the
number of CD63 secretion events in neurons expressing the ATG7 siRNA (Supplementary Figure
4C). To confirm that ATG7 was not responsible for the release of exosomes under basal conditions,
we also expressed ATG7 siRNA in wild type primary cortical neurons and tracked CD63-pHluorin
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events. When compared to the non-coding siRNA control, ATG7 knockdown had no effect on
exosome secretion from wild type neurons (Supplemental Figure 4D), suggesting that LC3
conjugation was required for the increased exosomal release induced by hyperactive LRRK2.
Chronic and acute strain on autophagy maturation differentially influence secretion
In LRRK2G2019S neurons, autophagic degradation is chronically strained (7, 16) with
ongoing disruptions to autophagosome maturation throughout the lifetime of the neuron. Previous
reports suggest that an acute prevention of autophagosome degradation via Bafilomycin A 1
(BafA1) (56, 57) can also initiate the upregulation of secretion in several different cell types (58,
59) (Supplemental Figure 5A). To determine if hyperactive LRRK2 was promoting secretion of
EVs via a similar mechanism as BafA1, we tracked secretion in neurons treated for 2 hours with
increasing concentrations of BafA1 (0nM, 50nM, 500nM). Consistent with previous reports, we
observed significantly more particles secreted by BafA1 treated neurons as measured via NTA
(Supplemental Figure 5B-C). We next isolated Large EVs/P20 and Small EVs/P100 released
from DMSO and BafA1 treated neurons for immunoblot analysis (Supplemental Figure 5D). We
observed that BafA1 treatment significantly increased the release of CD81 in small EVs
(Supplementary Figure 5G), but, in contrast to LRRK2G2019S neurons, CD63 was not detected in
small EVs in either condition (Supplemental Figure 5J). BafA1 treated neurons did release more
TSG101 and LC3 selectively within large EVs (Supplementary Figure 5E-F, I-J). These results
reveal distinct differences between BafA1-mediated secretion and the enhanced secretion induced
by mutant LRRK2 expression in neurons.
To confirm that these secretion pathways were distinct, we tracked fusion events of CD63-
pHluorin in BafA1-treated neurons. We observed no change in the number of CD63-pHluorin
events in neurons treated with DMSO or BafA1 (Supplementary Figure 6G). As we observed no
change in CD63-pHluorin events and only moderately increased CD81 signal, we next asked
whether BafA1treatment promoted the secretion of the tetraspanin, CD9. We tracked CD9-
pHluorin fusion events in primary cortical neurons and observed significantly more fusion events
in neurons following BafA1 incubation (Supplementary Figure 6A-F). In contrast, LRRK2G2019S
neurons exhibited no change in CD9-pHluroin events compared to wild type (Supplementary
Figure 6H-I). Thus, while we observe that hyperactive LRRK2 activity initiates the release of two
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EV populations, exosomes and secreted autophagosomes, BafA1 mediates the release of a third
population of EVs which are CD81+/ CD9+, consistent with the release of microvesicles.
Upregulation of secretion in hyperactive LRRK2 mutant animals
Our studies on neurons in vitro identified two secretory pathways that are upregulated in
both primary mouse cortical neurons and human iPSC-derived glutamatergic neurons expressing
PD-associated mutations that induce hyperactive LRRK2 activity. To determine if each of these
pathways were also upregulated in vivo, we compared levels of relevant vesicle markers in plasma
isolated from one year old LRRK2G2019S and wild type mice.
First, we asked if overall secretion from neurons was elevated by measuring circulating
levels of neuronal protein, BIII-tubulin (Figure 6A). We detected significantly more BIII-tubulin
in LRRK2G2019S plasma compared to wild type plasma (Figure 6E), demonstrating increased
neuronal secretion in LRRK2G2019S neurons in vivo. Consistent with a prior report, we also
observed more TSG101 in plasma from LRRK2G2019S mice, in agreement with overall secretion
levels being elevated (Figure 6B, F). In primary cultured neurons, both CD81 and CD63 were
secreted by LRRK2G2019S neurons. In isolated plasma, we observed a significant increase in CD81
in LRRK2G2019S plasma (Figure 6C, G), but failed to detect any change in CD63 (Supplemental
Figure 6A-B). Together, these observations are consistent with neuronal upregulation of secretion
and an upregulation of exosomal release in LRRK2G2019S animals. We next asked if upregulation
of secreted autophagosomes could be detected in LRRK2G2019S animals. We tracked circulating
levels of the neuronal autophagy cargo Synapsin-1 and significantly more circulating Synapsin-1
in LRRK2G2019S plasma (Figure 6D, H). Thus, it is likely that both the described exosomal
pathway and secretory autophagy pathway are upregulated in LRRK2G2019S animals.
Exosomal release is beneficial to LRRK2 mutant neurons
Our live cell imaging and immunoblotting results suggest that hyperactive LRRK2 activity
promotes the release of both neuronal exosomes and secreted autophagosomes. Does the release
of either of these vesicles impact neuronal survival? Recently, it has been observed that
augmenting exosomal secretion can extend lifespan in several ALS models. To determine if the
observed exosomal release was beneficial to LRRK2G2019S expressing neurons, we treated DIV7
primary neurons with increasing doses of GW4869. GW4869 blocks the release of exosomes via
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inhibition of Neutral Sphingomyelinase (N-SMase), a critical component for the budding of
intraluminal vesicles into the lumen of the MVB. Following two hours of GW4869 exposure, we
tracked levels of activated Caspase 3/7. In wild type neurons, short-term, low doses of GW4869
failed to increase the percent of cells with activated Caspase 3/7, suggesting these cells were
largely insensitive to the inhibition of exosomal secretion (Figure 6I, K). In contrast, LRRK2G2019S
neurons exposed to 5µM GW4869 exhibited a dramatic increase in Caspase 3/7 activation (13%
at baseline vs. 53% at 5µM) (Figure 6J-K). This observation suggests that LRRK2G2019S neurons
rely on exosomal secretion for survival and are thus more sensitive to exosomal inhibition. In
contrast, blocking the release of microvesicles using the drug Y27632, had no impact on cell
survival in control or LRRK2G2019S neurons (Figure 6L). Thus, we find that LRRK2 hyperactive
activity promotes the compensatory release of exosomes in neurons, which is critical for their
survival.
DISCUSSION
Here, we identify two compensatory secretion pathways, the release of secreted
autophagosomes and exosomes, that work in tandem to mediate export of cellular waste and
intercellular communication, respectively, in PD-neurons facing autophagic stress (Figure 7). We
used both unbiased proteomic and transcriptomic analyses to characterize the cargos of these two
vesicle classes, e.g., mitochondria in secreted autophagosomes and miRNAs in secreted exosomes.
We further corroborated this model using live imaging, demonstrating that the two vesicle classes
are both molecularly and spatially distinct. Using a specific LRRK2 inhibitor, we demonstrated
that exosomal release is dependent on LRRK2 activity. Finally, we found that neuronal secretion
is augmented in animals harboring the LRRK2G2019S mutation and that the secretion of exosomes
is critical for LRRK2G2019S neuronal survival in vitro. Together, we define two secretory pathways
that are upregulated in neurons expressing mutant LRRK2 and thus undergoing prolonged strain
to autophagy-mediated degradation.
We find that autophagosome contents are dumped from neurons harboring hyperactive
LRRK2, raising the question of what happens to the released cellular waste, e.g., mitochondria, in
vivo? Mitochondrial exchange between neighboring cells, including neurons and adjacent glia, has
been described by multiple groups (22, 23, 36, 60, 61) Tunneling nanotubes can serve as one
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mechanism to donate mitochondria transcellularly to rescue neurons facing oxidative stress (62).
Neuronal mitochondria can also be transferred to nearby glia for transcellular degradation, though
the mechanism is unknown (61). Our findings suggest an additional mode of transfer of
mitochondrial fragments from neurons to glia via secreted autophagosomes. This model is
supported by recent findings that neurons can release autophagosomes, presumably via secretion,
to be internalized by neighboring astrocytes (63). Given that LRRK2G2019S neurons exhibit
impaired autophagy (7, 16), neighboring cells may take up and ultimately degrade neuronal
cellular waste, including mitochondria, via the pathway described here. A parallel process has been
observed for cardiomyocytes, which release mitochondria in large vesicular structures termed
exophers for transcellular degradation by nearby macrophages (22). Effective internalization of
neuronally secreted mitochondrial fragments enriched in mtDNA by surrounding glia could
preclude the activation of harmful neuroinflammatory responses (28).
In parallel to the expulsion of secreted autophagosomes, we observed a significant increase
in exosome secretion. These released exosomes contain RNA, and specifically miRNAs,
suggesting that they could be mediating intercellular communication (64). We found this exosomal
release to be neuroprotective in monoculture, thus, exosomes could be impacting neighboring
neurons. Of interest, we noted that released exosomes are enriched for members of the let-7
miRNA family. Let-7 miRNAs are implicated in many processes that impact neuronal homeostasis,
including the induction of neuronal autophagy (45). Release of let-7 can be mediated by
inflammation (65) and circulating levels of certain let-7 miRNAs have been found to be elevated
in PD patient cerebral spinal fluid (66, 67) and serum (68), suggesting secretion of this family of
miRNAs could play a role in disease progression (69). Further work is needed to define the
downstream fate and role of both the secreted autophagosomes and exosomes in vivo in disease
models.
Both genetic (26) and pharmacologic (27, 58, 59, 70, 71) inhibition of autophagosome
maturation can trigger the release of vesicles via various secretory autophagy pathways across
diverse cell types, thus highlighting the tight interplay between autophagy-dependent degradation
and autophagy-dependent secretion. Our findings suggest that the coordination between
degradation and secretion is both stress-dependent and cell-type specific. While chronic strain on
autophagy via LRRK2 hyperactivity resulted in the release of exosomes and presumed secreted
autophagosomes, acute inhibition of autophagy maturation via BafA1 prompted the release of
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microvesicles. These contrasting pathways indicate that current pharmacologic strategies used to
augment secretion likely fail to recapitulate disease states. Additionally, we observed that BafA1
treatment of primary cortical mouse neurons resulted in the secretion of microvesicles, contrasting
previous reports in other cell lines (58, 59). Thus, we observe cell-type specific responses to
autophagy strain as well as differential responses to types of strain within a given cell type.
Our work has interesting implications regarding the role of secretion pathways in the
context of neurodegenerative disease, suggesting that, at least in the short term, secretion can serve
as an unburdening mechanism for neurons facing autophagic stress. Our findings complement
recent work which found that increasing exosomal secretion via PIKFYVE inhibition was
neuroprotective in several models of ALS (21). However, enhanced secretion of cellular debris,
e.g., mitochondrial DNA, has the potential to induce a pro-inflammatory environment. Indeed,
overall secretion is upregulated in models of neurodegenerative diseases including age-related
macular degeneration (53) and Christianson Syndrome (72), and PD patients have higher levels of
circulating mitochondria (73). Finally, upregulation of secretion could contribute to the spread of
protein aggregates, as both alpha-synuclein (74) and amyloid-beta (75) can be released via
secretory autophagy pathways. Thus, while enhanced secretion may have short-term benefits in
staving off neuronal cell death, the described compensatory pathways may promote chronic
neuroinflammation over longer timescales, contributing to age-dependent neurodegeneration.
Together, we posit that upregulated secretion is a compensatory mechanism that has
immediate beneficial effects for neurons, but that over time, detrimental downstream impacts may
contribute to disease progression.
MATERIALS AND METHODS
Experimental Lines
Primary cortical neurons
All experiments used in this paper follow an approved protocol by the Institutional Animal Care
and Use Committee at the University of Pennsylvania. Primary cortical neurons were isolated
from either Lrrk2-p.G2019S KI mice (model #1390) or B6NTac mice (model #B6), originally
obtained from Taconic. For BafA1 experiments, C57BL/6J (model #000664) obtained from
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Jackson Laboratories were used. The isolation and culturing protocol followed is as previously
published on protocols.io (https://doi.org/10.17504/protocols.io.81wgby723vpk/v1). Briefly,
mouse cortices of both sexes were isolated from embryos at DIV 15.5, meninges were removed,
and then cortices were digested with .35% Trypsin. Following digestion, cortices were triturated
to single cells, counted, and then plated on imaging dishes (P35G- 1.5-20-C; MatTeK) that had
been coated overnight with PLL (Sigma, # P1274). For initial plating, neurons were resuspended
in attachment media containing MEM (ThermoFisher, # 11095-072) with 10% heat inactivated
horse serum (ThermoFisher, # 16050-122), 33mM D-glucose (SigmaAldrich # G8769) and 1mM
sodium pyruvate (Corning, # 36017004). Following 6 hours of incubation at 37°C, attachment
media was replaced with maintenance media consisting of Neurobasal (ThermoFisher, # 21103-
049), supplemented with 2% B-27 (Gibco, #17504-044), 33mM D-glucose, 2mM GlutaMAX
(Gibco, #35050061), 100 U/mL penicillin and 100 mg/mL streptomycin (Gibco, #35050061.
For EV isolation, neurons were cultured until DIV11. To allow for the maximum number of
collect EVs, no media was replaced, but, additional media was added at DIV7 to prevent
dehydration and nutrient deprivation. For imaging experiments, neurons were imaged on DIV 7
following a 48-hour transfection using Lipofectamine 2000 (ThermoFisher, #11668019) and 1.5
µg total plasmid DNA. For knock down experiments, siRNA (ATG7 or ctrl) was transfected in
48 hours prior to imaging.
Human iPSC derived neurons
iPSCs (KOLF2.1J background WT and LRRK2-R1441H KI) were gifted to the Holzbaur lab
from B. Skarnes as (Jackson Laboratories) through the iPSC Neurodegenerative Disease
Initiative (iNDI). Both lines have a stably integrated doxycycline-inducible hNGN2 for neuronal
differentiation and have been described previously(32) and characterized in further detail by our
lab(16). iPSCs were cultured as previously described. Briefly, iPSCs were thawed in Essential 8
medium (ThermoFisher, #A151700) and plated onto Matrigel coated dishes and passaged twice
before neuronal differentiation. Neurons were differentiated following an established protocol for
i3Neurons and Piggybac-delivered NGN2 neurons (https://www.protocols.io/view/ineuron-
differentiation-from-human-ipscs-261ge348yl47/v1). After differentiation, neurons were
cryopreserved in i3Neuron media (BrainPhys Neuronal Medium (with 2% B-27 (Gibco, #17504-
044), 10ng/mL BDNF (PeproTech 450-02), 10ng/mL NT-3 (PeproTech 450-03), and 1µg/mL
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Laminin (Corning, # 354232), with 10% DMSO, and 20% FBS). Cryopreserved differentiated
KOLF2.1J neurons were thawed onto either 35-mm glass bottom dishes (300,000 neurons plated
for live imaging experiments) or 10-cm tissue culture treated dishes (3 million neurons plated for
EV isolation) coated with poly-L-ornithine overnight. Neurons were cultured for 21 days. ½ of
i3Neuron media was replaced every 3-4 weeks to prevent nutrient deprivation. For live imaging
experiments, neurons were transfected using 3µg of DNA and Lipofectamine Stem
(ThermoFisher) 2 days prior to imaging.
Nanoparticle Tracking Analysis
ZetaVIEW S/N 18-390 from Particle Metrix was calibrated using 100µM polycistronic beads.
Extracellular vesicle samples isolated via the Qiagen ExoEasy (Qiagen, #76064) and were then
diluted (1:1000 – 1:2000) in ddH2O directly before measurement to ensure accurate particle
count. Samples were loaded onto ZetaVIEW from Particle Metrix and mode was set to size
distribution with particle range set to 50nM- 1000nM. Minimum brightness was set to 20,
sensitivity was set to 75 and shutter was set to 75. Prior to measurement, drift was confirmed to
be minimal cell quality was confirmed to be “very good”. For each sample, the average particle
count over 11 channels was taken. All experiments were performed at room temperature.
Particles were counted using ZetaView (version 8.05.12 SP2) software, captured with a .712
mum/px camera. Original concentration was calculated based on starting dilution factor and
normalized to starting protein concentration. Particles count distribution for example plots were
based on diluted counts taken directly from ZetaView software.
CalceinAM – TIRF analysis
Extracellular vesicles were pelleted via a 100X G spin for 90 minutes and resuspended in .2µM
filtered 1X PBS. Diluted samples (1:1000) were then incubated with 10 µM Calcein AM
(Invitrogen, C3099) at 37C for 30 minutes. 10 µL of solution was then applied to an individual
PTFE Printed Slide well (Electron Microscopy Sciences, 63430-04) and incubated at room
temperature for 10 minutes. Individual wells contain a bioadhesive surface which facilitates
direct binding to slide. Wells were washed 3X with 10 µL of .2µM filtered 1X PBS before being
mounted with for TIRF microscopy. For each sample, 6 individual planes were captured using
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Perkin-Elmer Ultra VIEW Vox fitted with an Orbital Ring-TIRF arm. Images were segmented
using trainable 2D Weka Segmentation followed by object count in FIJI.
EV isolation via ultracentrifugation
For mass spectrometry analysis, 40mL of conditioned media was isolated from 10 million DIV11
primary cortical neurons (Lrrk2-p.G2019S KI or B6NTac genotype). Conditioned media was
spun at 500g to remove dead cell and large debris. Supernatant was moved to thick-walled tubes
fit for the Ti45 fixed angle rotor. All extracellular vesicles were pooled with a single 100,000g
(RCF average) 90-minute spin at 4C, followed by a 1mL wash and subsequent 100,000g (RCF
average) 90-minute spin in an Optima MAX XP ultracentrifuge fitted with a swinging bucket
TLS 55 rotor. Pellet was resuspended in 100 µL of 1X PBS and 10% of each sample was set
aside for protein quality analysis and concentration. Concentration was initially determined using
a Qiagen Qubit kit and confirmed via Coomassie. 30µg of protein was collected for each sample
and vacuum dried and stored at -80 prior to mass spectrometry analysis.
For immunoblotting, two populations of extracellular vesicles (LEVs and SEVs) were enriched
via ultracentrifugation. 10-40 mL of cultured media isolated from 2-10 million primary cortical
neurons was collected on DIV10. Media was spun at 500G for 10 minutes to remove cell debris.
Supernatant was collected and then subjected to a 20,000g spin for 30 minutes using an
Eppendorf 5417C centrifuge at 4°C. Pellets were washed with 1mL filtered 1X PBS before being
subjected to an additional 20,000g spin for 30 minutes at 4C. Washed pellet was resuspended in
75 µL of 1X PBS before being denatured for immunoblotting (Large EVs/P20). Supernatant was
collected and then spun at 100,000g (RCF average) for 90-minutes at 4°C using an Optima XPN
80 ultracentrifuge fitted with a swinging bucket SW41 TI rotor. Following initial spin,
supernatant was removed and pellet was resuspended in 1X PBS and then subjected to an
additional 100,000X G spin using an Optima MAX XP ultracentrifuge fitted with a swinging
bucket TLS 55 rotor for 90 minutes at 4°C. Small EVs/P100 pellet was collected following
second spin and resuspended in 75 µL of 1X PBS before being denatured for immunoblotting.
Protein extraction and digestion for proteomics
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EV pellets isolated via 100,000 x g spin were solubilized in extraction buffer (5% sodium
dodecyl sulfate (Affymetrix), 50mM TEAB (pH 8.5, Sigma), and protease inhibitor cocktail
(Roche cOmplete, EDTA free)). Samples were sonicated and then centrifuged at 3000g for 10
minutes before protein concentration was measured by intrinsic tryptophan fluorescence. 10ug of
each sample was digested per the S-Trap Micro (Protifi) manufacturer’s protocol(76). After
digestion, peptides were eluted and organic solvent was dried off via vacuum centrifugation and
reconstituted in 0.1% TFA containing iRT peptides (Biognosys, Schlieren, Switzerland). Peptide
concentration was measured at OD280 and samples were adjusted to 400 ng/ul.
Mass Spectrometry data acquisition
Following sample preparation, samples were randomized and analyzed on an Exploris 480 mass
spectrometer (Thermofisher Scientific San Jose, CA) coupled with an Ultimate 3000 nano UPLC
system and an EasySpray source. 5ul of sample was loaded onto an Acclaim PepMap 100 75um
x 2cm trap column (Thermo) at 5uL/min, and separated by reverse phase (RP)-HPLC on a
nanocapillary column (75 μm id × 50cm 2um PepMap RSLC C18 column (Thermo)). Mobile
phase A consisted of 0.1% formic acid and mobile phase B of 0.1% formic acid/acetonitrile.
Peptides were eluted into the mass spectrometer at 300 nL/min with each RP-LC run comprising
a 105-minute gradient from 3% B to 45% B.
The following mass spectrometer settings for data independent acquisition (DIA) were used:
First, a full MS scan at 120,000 resolution, with a scan range of 350-1200 m/z and normalized
automatic gain control (AGC) target of 300%, and maximum inject time. This was followed by
variable (DIA) isolation windows, MS2 scans at 30,000 resolution, a normalized AGC target of
1000%, and automatic injection time. The default charge state was 3, the first mass was fixed at
250 m/z, and the normalized collision energy for each window was set at 27.
Proteomic bioinformatics analysis
Raw data were searched using Spectronaut(77, 78) and proteomics data processing and statistical
analysis were conducted in R. The MS2 intensity values generated by Spectronaut were utilized
for analyzing the entire proteome dataset. Following log2 transformation and normalization the
median value for each sample was subtracted to produce an expression value. Only proteins with
complete values in at least one cohort were included. A Limma t-test was used to identify
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proteins with differential abundance. Lists of differentially abundant proteins were generated
based on criteria of adjusted P.Value <0.05.
For ontology analysis, PANTHER was used and terms were compared to available MitoCarta
3.0(41), SynGo(79), and EV datasets(39).
Small RNA Isolation and Sequencing
To isolate small RNAs, the miRNeasy kit (Qiagen) was used. Following isolation, RNA sample
quality was assessed by High Sensitivity RNA Tapestation (Agilent Technologies Inc.) and
quantity was determined via Qubit 2.0 RNA HS assay (ThermoFisher). Library construction is
performed based on manufacturer’s recommendation for the SMARTer smRNA library
preparation kit (Takara Bio USA Inc). Final library quantity was measured by KAPA SYBR®
FAST qPCR and library quality evaluated by TapeStation D1000 ScreenTape (Agilent
Technologies). Equimolar pooling of libraries was performed based on QC values and sequenced
on an Illumina NovaSeq S4 (Illumina, California, USA) with a read length configuration of 150
PE for 20M PE reads per sample (20M in each direction).
miRNA Differential Expression Analysis
Raw data reads were filtered to remove low quality reads or redundant reads. Reads were further
filtered to ensure N content was greater than 10% reads, match greater than or equal to 15bp and
mismatch number less than or equal to 3bp. Fastp was used for data quality filtering to remove
adapter sequences from read.
For miRNA identification and quantification, we used COMPSRA, a comprehensive platform for
small RNA-Seq data analysis. To align the clean reads to the reference genome, COMPSRA uses
STAR as its default RNA sequence aligner with default parameters. The aligned reads are
quantified and annotated. DESeq2 software was used to analyze the DEG for samples with
biological replicates and edgeR was used for the samples without replicates. During the analysis,
samples should be firstly grouped so that comparison between every two groups as a control-
treatment pairwise can be done later. During the process, Fold Change≥2.00 and padj≤0.05 are
set as screening criteria. Fold Change (FC) indicates the ratio of expression levels between two
samples (groups).
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Immunoblotting
For whole cell lysate samples, DIV11 cultured neurons were lysed in RIPA buffer (50 mM Tris-
HCl supplemented with150 mM NaCl, 0.1% Triton X-100, 0.5% sodium deoxycholate and 0.1%
SDS, pH=7.4, 1X Halt Protease and phosphatase inhibitor) at 4C for 30 minutes before being
centrifuged at 13,000 RPM for 10 minutes. Concentration of all samples was confirmed via
Pierce BCA Protein Assay Kit (ThermoFisher #23225) and then denatured in 1X denaturing
buffer containing SDS and boiled at 95C for 10 minutes. For all EV samples, EVs were enriched
via ultracentrifugation, and equal volume was taken from each replicate before being denatured
in 1X denaturing buffer and boiled at 95C for 10 minutes. All EV protein samples were loaded
onto gradient SDS-PAGE gels (BioRad #4568084) while lysates and plasma were loaded onto to
fixed percent SDS-PAGE gel to be resolved. Following protein separation, resolved proteins
were transferred to PVDF membranes (#), and dried overnight. Total protein was determined
using Revert™ 700 Total Protein Stain (Licor #926-11021) following the manufacturer’s
protocol. Membranes were destained and then blocked using EverBlot Blocking Buffer (Bio-Rad
#) before being incubated with primary antibodies over night at 4C (Antibodies listed in primary
resource table). Following 3X washes with 1X TBST, membranes were incubated with
appropriate secondary antibodies and band intensities were quantified using Image Studio™
Software (Li-COR).
ExoView R100
Tetraspanin CD9, CD63 and CD81 distribution were analyzed using the ExoViewR100 platform
using the Leprechaun mouse tetraspanin ExoView kits (Unchained Labs # 251-1046) following
the kit assay protocol. Isolated EVs (P100) were diluted 1:100 in the proprietary incubation
solution II. 50 μL of each sample was placed inside a Falcon 24-well cell culture plate, flat
bottom (Fisher Scientific Catalogue number 08-772-1) for the capture of EV hamster anti mouse
CD81antigen (Clone Eat-2) as well as controls Armenian hamster isotype IgG (Clone HTK888)
and rat isotype IgG2ak (Clone RTK2758). Samples were incubated for 16 h at RT and then
washed 3X with Solution A on an ELISA microplate orbital shaker at 500 rpm (FisherbrandTM
Fisher Scientific # 88-861-023). Chips were then incubated with an antibody cocktail made of
0.6 μL Amrmenia hamster anti mouse CD81+(Clone Eat-2) conjugated with Alexfluor 555, 0.6 μL
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rat anti mouse CD63(Clone NVG-2) conjugated with Alexfluor 647, and 0.6 μL of rat anti mouse
CD9 (Clone MZ3) conjugated with Alexfluor 488 in 300 μL of blocking solution for 1h at RT in
on orbital shaker at 500 rpm. Chips were washed with 1X Solution A, followed by 3X washes
with 1X Solution B and at 500 rpm. Image acquisition from each chip was carried out using the
ExoView® R100 platform, and the data were analyzed by the ExoView Analyzer software
version 3.2 (NanoView Biosciences). The images of the acquisition were visually inspected and
all the artifacts onto the spots were manually removed from the analysis. Non-specific binding
was checked on the mouse isotype control IgG spots. The cut off was manually established for
all the chip to exclude the majority of the signal (> 90%) captured on the isotype control.
Immunocytochemistry
For all samples, DIV7 primary cortical neurons were fixed 4% PFA for 7 minutes at 37C. For
permeabilized samples, plates were incubated 95% MeOH for 8 minutes at -20C following PFA
fixation- unpermeabilized samples skipped this step. Samples were then washed 3x times with
1X PBS before being blocked (5% goat serum, 1% BSA in 1X PBS) for 1 hour at RT. Plates
were incubated overnight at 4C with primary antibody diluted in blocking buffer. The following
day, plates were washed 3X with 1X PBS and then incubated with appropriate secondary
antibodies for 1 hour at RT in blocking buffer. All samples were incubated Hoechst nuclear
counter stain for 10 minutes prior to imaging.
Neurons were imaged using a Perkin-Elmer Ultra VIEW Vox spinning disk with an ORCA
FUSION Gen-III cMOS camera. Images were captured using a 100X 1.49NA oil-immersion
objective with VisiView (Visitron). Z-stacks were captured with a .2µM step. For analysis, max
projections of 19 z-steps were created in FIJI. Cells were selected if they were fully in frame and
not overlapping significantly with a neighboring cell. Cell outline was traced manually and the
average fluorescence intensity for the soma was determined. Experimenter was blinded at the
time of analysis.
TIRF microscopy
To assay fusion events of CD63phluorin, CD9phluorin, or LC3, primary cortical neurons were
transfected 48 hours prior to imaging. If neurons were treated with MLI-2, drug was applied in
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maintenance media 1 hour prior to imaging. Immediately before imaging, neuronal maintenance
media was replaced with Hibernate E supplemented with 2% B-27 and 22mM D glucose. All live
experiments were captured with a Perkin-Elmer Ultra VIEW Vox microscope fitted with a
Visitron Orbital Ring-TIRF arm. A CFI Apo TIRF 100X (1.49 NA) oil immersion objective was
used for all experiments and videos were captured using VisiView (Visitron). For CD63phluorin
experiments and CD9phluorin experiments, cells were imaged over a 20-minute time frame
(1frame/5seconds) with perfect focus. For LC3 experiments, cells were imaged over a 5-minute
time frame (1frame/500ms).
All analysis was done blinded by two independent experimenters. Videos were aligned in FIJI
using the Fast4DReg plugin. The first frame was then subtracted from all subsequent frames
using the Image Calculator in FIJI. Fusion events were defined as a rapid increase in GFP signal
that persisted for 5 or more frames. Cells were analyzed if they remained in focus for 20 minutes
and at least a single fusion event could be identified.
Plasma isolation
Following IACUC approved euthanasia and decapitation, 500µL of trunk blood from 1yo Lrrk2-
p.G2019S KI mice (model #1390) or B6NTac mice (model #B6) was collected into EDTA
collection tubes (Sarstedt Inc #NC9990563). Blood was then spun at 2,000g for 10 minutes.
100µL of supernatant (plasma) was carefully collected into a new Eppendorf tube, diluted with
200µL of 1XPBS, and then denatured (final concentration 1X denaturing buffer with SDS, 20
minutes at 95°C) for immunoblotting.
Cell Death Assay
Primary cortical DIV7 neurons were treated with varying concentrations of either GW4869
(Tocris #6741) or Y27632 (Tocris #1254) for two hours. A single drop of CellEvent Caspase-3/7
Green Detection Reagent (ThermoFisher R37111) was added to individual dishes and incubated
at at 37 °C, 5% CO2 for 30 min. Neurons were treated with Hoechst nuclear stain 10 minutes
prior to imaging. Cells were imaged using Leica DMI6000B inverted epifluorescence
microscope (20X) equipped a climate-controlled chamber. Analysis was performed using
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CellPose to quantify the total number of cell bodies in Hoechst and the number of Caspase3/7
positive cells.
Statistics
Statistical tests of all NTA, immunoblotting, fixed, and live imaging experiments were performed
in Graphpad Prism V10. For NTA analysis, the concentration of detected particles was used to
determine total number of secreted particles. Total number of secreted particles were compared
using a two-tailed t-test. For immunoblot analyses in which the comparison was between two
groups, a Kruskal-Wallis test was used. For immunoblot analyses comparing three or more
groups, a two-way ANOVA with Šídák's multiple comparisons test was used. For live-cell and
fixed imaging, an unpaired t-test was performed on the mean of the biological replicates to
determine significance. Biological replicates (n) are displayed as larger data points in superplot
graphs with technical replicates as smaller, transparent points. In all cases, significance was
defined as a p-value <0.05 and the detected p-value was displayed in each figure. Statistics used
for proteomic and transcriptomic results are specified in their respective methods sections.
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DATA AVAILABILITY
The data, protocols, and key lab materials that were used and generated in this study are listed in
a Key Resource Table, including all pertaining identifiers, which will be deposited at Zenodo
upon acceptance for publication. The proteomics dataset has been deposited to MassIVE
(MSV000095428), and the transcriptomics dataset has been deposited to Sequence Read Archive
(SUB14821825. No code was generated for this study. Data cleaning, processing, analysis and
visualization was performed using GraphPad Prism and R. An earlier version of this manuscript
was posted to bioRxiv (TBD).
AWKNOWLEDGEMENTS
We thank Mariko Tokito and Karen Jahn for their technical assistance and advice. We also thank
Dr. Bishal Basak, Dr. Elizabeth Gallagher, Dr. Kaya Matson, and all other members of the
Holzbaur lab for their valuable feedback on the manuscript and thoughtful discussion. We also
want to thank Dr. Dorotea Fracchiolla for her guidance and management.
We thank the cores at the University of Pennsylvania and companies that aided in the completion
of this work. Specifically, we thank the Extracellular Vesicle core facility (RRID:SCR_022444)
and Dr. Luca Musante for his technical assistance and expert advice. We thank the CHOP-Penn
Proteomics core facility (RRID:SCR_023099), Lynn Spruce, and Dr. Hossein Fazelinia for their
technical assistance and advice. We also thank CD Genomics for their technical expertise and
assistance.
This work was supported by the Michael J. Fox Foundation (MJFF) (MJFF-021130, MJFF-
15100, and MJFF-019411 to E.L.F. Holzbaur. The E.L.F. Holzbaur laboratory is funded by the
joint efforts of The MJFF and the Aligning Science Across Parkinson’s initiative. MJFF
administers the grant ASAP-000350 on behalf of ASAP and itself.
This work is supported by the National Institute of Neurological Disorders and Stroke (R01-
NS060698 awarded to E.L.F. Holzbaur and F32-NS129586 awarded to S.D. Palumbos)
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28
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Figure 1: Neurons expressing hyperactive LRRK2 upregulate secretion
A) Schematic representing degradative-autophagy in control (left) and LRRK2 mutant (right)
neurons. Neurons expressing hyperactive LRRK2 exhibit delayed autophagosome
trafficking down the axon, stalled autophagosome maturation and reduced acidification.
B) Quantification of Nanoparticle Tracking Analysis (NTA) of secreted particles isolated from
DIV11 wild type and LRRK2G2019S primary cortical neurons. Particle count normalized to
cell number. N=3, two-tailed t-test, error bars represent mean and SEM.
C) Representative size distribution of measured particles released from wild type and
LRRK2G2019S primary cortical neurons in individual experiment.
D) Quantification of NTA of secreted particles isolated from DIV21 wild type and
LRRK2R1441H human iPSC derived KOLF2.1J neurons. Particle count normalized to cell
number. N=3, two-tailed t-test, error bars represent mean and SEM.
E) Representative size distribution of measured particles released from control and
LRRK2R1441H human iPSC derived KOLF2.1J neurons in an individual experiment.
F) Measured particle diameter of the most common particle size (mode) from control and
LRRK2 neurons in both mouse primary cortical neurons and human iPSC derived
KOLF2.1J neurons. N=3, 2-way ANOVA with uncorrected Fisher’s least significant
difference (LSD), error bars represent mean and SEM.
G) Representative TIRF images of vesicles treated with Calcein AM isolated from wild type
(left) and LRRK2G2019S (right) primary cortical neurons. Images have been pseudo-colored.
H) Superplot representing measured CalceinAM fluorescing puncta per field of view of
vesicles isolated from control and LRRK2G2019S primary cortical neurons. N=4, two-tailed
t-test comparing biological replicates, error bars represent SEM.
Figure 2: Proteomic profiling reveals autophagic cargo secreted from LRRK2G2019S primary
cortical neurons
A) Percent of proteins (pie chart inserts) characterized as “Small EV enriched” or “Large EV
enriched” by Lischnig et al.(38), detected in LRRK2 secretome. Proteins detected in
extracellular vesicles isolated from 5 replicate samples of LRRK2G2019S neurons ranked by
abundance. Median protein abundance = 0. Large EV proteins colored blue, Small EV
proteins colored orange.
B) Average expression value of all detected Small EV(38)proteins between control and
LRRK2 G2019S secretome across replicates. N=5, two-tailed t-test, error bars represent SEM.
C) Average expression values of all detected Large EV(38)proteins between control and
LRRK2 G2019S secretome across replicates. N=5, two-tailed t-test, error bars represent SEM.
D) Bubble plot representation of ontology terms of top 50% of detected proteins in
LRRK2G2019S secretome. Ontology analysis of GO cellular component by PANTHER. Each
bubble depicts unique GO term and size of bubble represents number of proteins within
term that was detected. Bubbles are pseudo coated by terms indicated in box inset.
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35
E) Proteins detected in LRRK2G2019S secretome ranked by abundance. Black dots indicate
proteins defined as top 100 EV-associated cargo. Red dots indicate members of ATG 8
family. Percent of proteins characterized as autophagic cargo(40) (pie chart insert) detected
in LRRK2G2019S EVs.
F) Volcano plot representing differentially secreted proteins from control and LRRK2G2019S
neurons. Green circles indicate mitochondrial associated proteins as defined by MitoCarta
3.0. Size of dot correlates to normalized expression value.
G) Bubble plot representation of ontology terms from proteins differentially expressed
between control and LRRK2G2019S EVs. Significance threshold determined by p-value of
differential abundance analysis. Each bubble depicts unique GO term. Bubbles are pseudo
colored based on broader terms indicated below. Size of bubble represents number of
proteins representing that term.
Figure 3: Two secretory pathways are upregulated in LRRK2G2019S neurons
A) Schematic representing differential ultracentrifugation approach to enrich for secreted
autophagosomes and exosomes. P20 indicates pellet isolated following 20,000g spin and
P200 indicates pellet isolated following 100,000g spin. Additional vesicle populations are
captured with this approach.
B) Representative western blots of isolated P20 and P100 fractions from primary cortical
control and LRRK2G2019S neurons. Dashed lines indicate corresponding lanes are from the
same gel. Detected protein and corresponding molecular weight indicated. Equal volume
was loaded for each well and samples were normalized to amount of detected media
protein, albumin.
C-J) Quantifications of relative levels of detected band intensities for C) LC3-I, D) LC3-
II, E) CD81, F) CD63, G) TSG101, H) hNRNPK, I) Synapsin-1, and J) TFAM from P20
and P100 vesicular fractions isolated from control (blue) and LRRK2G2019S (red) neurons.
All quantifications of band intensities are normalized to the control P20 band to clearly
indicate relative abundance of detected proteins. Individual replicates represented by black
dots. 2way ANOVA with Šídák's multiple comparison test. Error bars indicate SEM.
K) KEGG analysis of targets of the top miRNAs detected in both wild type and
LRRK2G2019S neuronal secretome. The top 25 miRNAs was consistent between both
genotypes.
L) Average number of reads of top 25 miRNAs detected in control and LRRK2G2019S
secreted transcriptome. For each miRNA, read average is elevated in LRRK2G2019S. In both
genotypes, 4 of the top 5 miRNAs are members of the let-7 family.
M) Schematic representing two vesicle populations that are upregulated in LRRK2G2019S
neurons. Presumed secreted autophagosomes (left) contain LC3-II, mitochondria, synaptic
proteins and RNA-binding proteins. Presumed exosomes express CD81, CD63 and
TSG101.
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Figure 4: Secreted autophagosomes are upregulated in LRRK2G2019S neurons
A-B) Representative frame sequence of A) control and B) LRRK2G2019S neurons
transfected with LC3 mScarlet captured with TIRF microscopy over 5-minute period.
Temporal color code represents frames from 1-601 (2 frames/sec). Increases in
fluorescence intensity at cell surface are consistent with secretory autophagy events.
Dashed boxes indicate example LC3 fluorescent event on soma and individual process.
C-D) Representative TIRF imagee of external GABARAP signal in C) wild type and D)
LRRK2G2019S neurons.
E) Quantification of external GABARAP signal. Superplot of biological and technical
replicates. N=3, two-tailed t-test comparing biological replicates, error bars represent SEM.
F) Representative image LRRK2G2019S neuron transfected with AnkyrinG and
immunstained for external GABARAP. Axon Initiation Segment (AIS) indicated by bar.
Insets of AIS and dendrite.
G) Representative linescans of GABARAP (magenta) and AnkG (grey) of axon and
dendrite of images from F.
Figure 5: Secretion of exosomes is augmented in LRRK2G2019S neurons
A) Representative image of ExoView anti-CD81 captured vesicles from control and
LRRK2G2019S neurons. Zoomed in views indicated by dashed rectangles.
B) Quantification of detected particles positive for individual or combination of tetraspanins,
CD81, CD63, and CD9. Total particle count noted.
C) Schematic indicating imaging pipeline to detect CD63pHluorin secretion events.
CD63pHluorin signal is quenched in acidic environments. When the multivesicular body
(MVB) fuses with the plasma membrane, CD63pHluorin will fluoresce. Neurons
expressing CD63pHluorin were imaged in TIRF microscopy to capture secretion events at
the cell surface.
D) Representative image of CD63pHluorin expressing control neuron. Dashed box indicates
panels depicted in panel E. Yellow line indicates kymograph depicted in panel H (left).
E) Time series of CD63pHluorin expression in control neuron. The first frame was subtracted
from all subsequent frames. Time stamp indicated in each frame. Dashed circles indicate
fusion events.
F) Representative image of CD63pHluorin expressing LRRK2G2019S neuron. Dashed box
indicates panels depicted in panel G. Yellow line indicates kymograph depicted in panel H
(right).
G) Time series of CD63pHluorin expression in LRRK2G2019S neuron. The first frame was
subtracted from all subsequent frames. Time stamp indicated in each frame. Dashed circles
indicate fusion events.
H) Representative kymographs and schematic indicating CD63pHluorin fusion events over
time.
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I) Quantification of CD63pHluorin events in control, LRRK2G2019S, and LRRK2G2019S + MLI-
2 primary cortical neurons. Superplot indicating biological and technical replicates. N=4,
ordinary one-way ANOVA with Tukey’s multiple comparison test of biological replicates,
error bars represent SEM.
J) Quantification of CD63pHluorin events in control, LRRK2R1441H KOLF2.1J neurons.
Superplot indicating biological and technical replicates. N=3, two-tailed t-test comparing
biological replicates, error bars represent SEM.
Figure 6: Compensatory release of exosomes and secreted autophagosomes
A-D) Representative western blots of isolated plasma from one year old control and
LRRK2G2019S mice against A) Class III β-tubulin, B) TSG101, C) CD81, and D) Synapsin-
1.
E-H) Quantification of relative band intensity of isolated plasma from one year old control
and LRRK2G2019S mice for E) Class III β-tubulin, F) TSG101, G) CD81, and H) Synapsin-
1. N=11, two-tailed t-test, error bars represent SEM.
I) Example images of control and LRRK2G2019S neurons treated with 5 µM of the exosome
inhibitor, GW4869. DIC images with overlay of activated CellEvent Caspase3/7 ready
probe which is an early indicator of apoptosis.
J) Example images of control and LRRK2G2019S neurons treated with 40 µM of the
microvesicle inhibitor, Y27632. DIC images with overlay of activated CellEvent
Caspase3/7 ready probe which is an early indicator of apoptosis. Scale bar = 20µM
K) Quantification of percent of neurons with activated Caspase 3/7 following two hours of
treatment with varying levels of GW4869. N=3, 2way ANOVA with Šídák's multiple
comparison test. Error bars indicate SEM.
L) Quantification of percent of neurons with activated Caspase 3/7 following two hours of
treatment with varying levels of Y27632. N=3, 2way ANOVA with Šídák's multiple
comparison test. Error bars indicate SEM.
Figure 7: Complementary secretion pathways mediate cellular homeostasis in LRRK2
neurons
Schematic of proposed model. Neurons expressing pathogenic LRRK2 exhibit delays in
axonal autophagosome trafficking and maturation. Two compensatory secretion pathways
are upregulated in response to this chronic autophagic stress. Secreted autophagosomes are
preferentially released from a somatodendritic compartment to mediate release of
autophagosome cargo. Exosomes are released from the cell soma to likely mediate
transcellular signaling.
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Mouse
Cortical Human
IPSC Derived
0
50
100
150
200
Particle Diameter (nm)
ns ns
Wild type Hyperactive LRRK2
Delayed Maturation
Failure to Acidify
CTRL LRRK2 R1441H
0
2×109
6×109
8×109
1×1010
Secreted Particles / mL
0.0034
0 100 200 300 400
0
1×106
2×106
3×106
4×106
Particle Diameter (nm)
Measured Particles
CTRL
LRRK2 R1441H
0 100 200 300 400
0.0
5.0×105
1.0×106
1.5×106
2.0×106
2.5×106
Particle Diameter (nm)
Measured Particles
CTRL
LRRK2 G2019S
CTRL LRRK2 G2019S
0
2×1010
6×1010
8×1010
1×1011
Secreted Particles/ mL
0.0173
A
2µm LRRK2 G2019S
G H
B C D E
CTRL LRRK2
0
500
1000
1500
CalceinAM
Puncta/Field of View
0
500
1000
1500 0.0323
CTRL
CalceinAM
F
Figure 1
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P20
Control
LRRK2
Control
LRRK2
P100
CD63 50
CD81 22
TSG101
Syn-1
hNRNPK
TFAM
45
25
75
55
Albumin
Albumin
Albumin
LC3 16
14
P20 P100
0
1
2
3
LC3I
Relative Protein Levels
P20 P100
0
5
10
15
20
Relative Protein Levels
0.9588 <0.0001
P20 P100
P20 P100
0
1
2
3
4
5
TSG101
Relative Protein Levels
0.9329 0.0029
0.0
0.5
1.0
1.5
2.0
2.5
Synapsin1
Relative Protein Levels
0.0019 0.2624
0
1
2
3
4
5
Relative Protein Levels
P20 P100
P20 P100
0
2
4
6
Relative Protein Levels
0.9205 0.0005
P20 P100
P20 P100
0
5
10
15
hNRNPK
Relative Protein Levels
0.0120 0.9992
0
2
4
6
80.0486 0.9501
LC3II
0.1347 0.7427 0.0089 0.8859
CD81 CD63
TFAM
Relative Protein Levels
CTRL LRRK2
CD81+
CD63+
miRNAs
Small EVs
LRRK2 induced Secretion
LC3+
Mito+
TFAM+
Secreted
Autophagosomes
500 x g
20,000 x g
100,000 x g
Dead Cells
and
Debris
P20
Secreted
Autophagosome
Enriched
P100
Exosome
Enriched
A
C D
E F
G H
IJ
B
K
Figure 3
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CTRL
GABARAP TIRF
0
1
2
3
4
CTRL LRRK2
0
1
2
3
4
Relative Fluorescence
External GABARAP
0.0346
CTRL
LC3
LRRK2
A B
C
F G
D E
5µm
5µm
LRRK2
AnkG
AIS
Dendrite Dendrite
Dendrite
AIS
GABARAP
AIS
AIS
0.4
0.6
0.8
1.0
RelativeFluorescence
Axon
0 2000 4000 6000 8000
0.25
0.50
0.75
1.00
Distance(micron)
RelativeFluorescence
Dendrite
10 µm
Figure 4
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72
423
215
46
2
13
4
775
92
861
236
115
19
44
27
1394
CTRL LRRK2
CD63
CD81
CD9
CD63/CD81
CD63/CD9
CD81/CD9
CD63/CD81/
CD9
Total
500
Particle Count
1000
CTRL LRRK2 G2019S
10µm
CD63
CD81
CD9
Control
Control LRRK2 G2019S
LRRK2 G2019S
D
HJI
30:00
30:00
15:00
10µm 5µm
15:000:00
0:00
E
FG
5µm
5 min
CD63Phluorin
CD63Phluorin
A
C
B
TIRF
CTRL LRRK2
R1441H
0.0
0.5
1.0
CD63 phluorin events/min
0.0013
-
-
+
-
+
+
LRRK2
(G2019S)
MLI-2
0.0
0.5
1.0
1.5
CD63 phluorin events/min
0.0039
0.8816
0.0070
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CD81 Syn-1
TSG101βIIITub
Total
Protein
Total
Protein
Total
Protein
Total
Protein
CTRL LRRK2 CTRL LRRK2
4550
75
22
0 2.5 5
0
20
40
60
80
100
GW4869 Concentration (µM)
% cells with activated caspase
CTRL
LRRK2
*
Exosome Inhibitor
0 20 40
0
20
40
60
80
100
Microvesicle Inhibitor
Y27632 concentration (µM)
% cells with activated caspase
Control
LRRK2
CTRL +5µM GW4869 LRRK2 +5µM GW4869
A B
C
E
I
J
K L
F G H
D
CTRL LRRK2
0.0
0.5
1.0
1.5
2.0
Relative Protein Levels
0.0411
CTRL LRRK2
0
1
2
3
4
Relative Protein Levels
0.0338
CTRL LRRK2
0
1
2
3
4
Relative Protein Levels
0.0279
CTRL LRRK2
0
1
2
3
Relative Protein Levels
0.0104
TSG101 Plasma
βIIITub Plasma Syn1 Plasma
CD81 Plasma
Caspase 3/7
CTRL +40µM Y27632 LRRK2 +40µM Y27632
20µM
Figure 6
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Overwhelmed Autophagy
Waste Disposal Signaling
LRRK2 Mutant Neurons
Delayed
Maturation
Failure to
Acidify
Secreted
Exosomes
Secreted
Autophagosomes
Soma
Somatodendritic
Axon
CD63+
CD81+
LC3+,TFAM+
Figure 7
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