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Pharmacological rescue of impaired mitophagy in Parkinson’s disease-related LRRK2 G2019S knock-in mice

  1. Francois Singh
  2. Alan R Prescott
  3. Philippa Rosewell
  4. Graeme Ball
  5. Alastair D Reith
  6. Ian G Ganley  Is a corresponding author
  1. MRC Protein Phosphorylation and Ubiquitylation Unit, University of Dundee, United Kingdom
  2. Dundee Imaging Facility, School of Life Sciences, University of Dundee, United Kingdom
  3. Novel Human Genetics Research Unit, GlaxoSmithKline Pharmaceuticals R&D, United Kingdom
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Cite this article as: eLife 2021;10:e67604 doi: 10.7554/eLife.67604

Abstract

Parkinson’s disease (PD) is a major and progressive neurodegenerative disorder, yet the biological mechanisms involved in its aetiology are poorly understood. Evidence links this disorder with mitochondrial dysfunction and/or impaired lysosomal degradation – key features of the autophagy of mitochondria, known as mitophagy. Here, we investigated the role of LRRK2, a protein kinase frequently mutated in PD, in this process in vivo. Using mitophagy and autophagy reporter mice, bearing either knockout of LRRK2 or expressing the pathogenic kinase-activating G2019S LRRK2 mutation, we found that basal mitophagy was specifically altered in clinically relevant cells and tissues. Our data show that basal mitophagy inversely correlates with LRRK2 kinase activity in vivo. In support of this, use of distinct LRRK2 kinase inhibitors in cells increased basal mitophagy, and a CNS penetrant LRRK2 kinase inhibitor, GSK3357679A, rescued the mitophagy defects observed in LRRK2 G2019S mice. This study provides the first in vivo evidence that pathogenic LRRK2 directly impairs basal mitophagy, a process with strong links to idiopathic Parkinson’s disease, and demonstrates that pharmacological inhibition of LRRK2 is a rational mitophagy-rescue approach and potential PD therapy.

Introduction

Parkinson’s disease (PD) is the second most common neurodegenerative disorder, affecting 1–2% of the population over 60 years old, and 4% above 85 years of age (Coppedè, 2012). The main symptoms of PD are muscle rigidity, bradykinesia, resting tremor, and postural instability and may be accompanied by sleep disorders, anosmia, depression, and dementia (Sironi et al., 2020). It is characterised by a progressive and selective degeneration of dopaminergic (DA) neurons of the substantia nigra pars compacta (SNpc). Currently, there are no treatments available that modify the course of neurodegenerative decline. Although this disease is mostly sporadic, about 15% of cases appear to be inherited and in support of this, 20 genes implicated in PD have been identified from familial genetic studies while ~90 loci have been identified from PD-GWAS (Deng et al., 2018). The exact causes of PD are currently unknown but some evidence strongly links impaired mitochondrial and lysosomal function to disease pathology (Sironi et al., 2020).

Mutations in PARK8, encoding for LRRK2 (Leucine-Rich Repeat Kinase 2), are the most frequently reported cause of PD (Bouhouche et al., 2017). The most common mutation associated with PD is the substitution of glycine at position 2019 of LRRK2 to serine (G2019S), representing 4% of familial and 1% of sporadic cases (Lill, 2016). LRRK2 is a large multidomain protein with two catalytic domains: a Ras of complex (ROC) GTPase domain that is able to bind GTP and hydrolyse it, and a kinase domain that utilises a subset of Rab GTPases as substrates (Steger et al., 2016). Importantly, all the segregating mutations associated with PD are located in the catalytic core. A mutation in the ROC/COR domain, such as the R1441C/G/H or the Y1699C mutation, leads to decreased GTPase activity and elevated kinase activity (Rudenko and Cookson, 2014). Mutations in the kinase domain, such as the G2019S or the I2020T, also lead to an elevated kinase activity. Hence, enhanced kinase activity appears to be a common factor in pathogenic LRRK2 mutations. Although the function of LRRK2 within cells is currently unknown, mounting evidence implicates a role in membrane trafficking (Steger et al., 2016; Pfeffer, 2018; Hur et al., 2019).

Macroautophagy is a membrane trafficking pathway that delivers intracellular components to the lysosome for degradation (Yu et al., 2018). These components can include whole organelles such as mitochondria. The autophagic turnover of mitochondria is termed mitophagy, which acts as a mitochondrial quality control mechanism that allows the selective degradation of damaged or unnecessary mitochondria (Rodger et al., 2018; Montava-Garriga and Ganley, 2020). Mitophagy itself has strong links to PD following the landmark discoveries that PINK1 and Parkin, two other genes mutated in familial PD, sequentially operate to initiate mitophagy in response to mitochondrial depolarisation in cell lines (Narendra et al., 2008; Koyano et al., 2014; Pickrell and Youle, 2015; Yamano et al., 2018). However, when this pathway becomes relevant in vivo, and under what physiological conditions, is unclear especially given that PINK1 and Parkin are not required for regulation of mitophagy under normal, or basal, conditions (McWilliams et al., 2018a; McWilliams et al., 2018b; Lee et al., 2018). Indeed, our understanding of the detailed mechanisms regulating basal mitophagy remains elusive.

In this study, we sought to define the physiological link between mitochondrial turnover and LRRK2 in relation to PD. We utilised our previously published mouse reporter models to study mitophagy (mito-QC) and autophagy (auto-QC; Fig. 1A, D and McWilliams et al., 2018a; McWilliams et al., 2016; McWilliams et al., 2019) in either LRRK2 knockout mice, or knock-in mice harbouring the pathogenic LRRK2 G2019S mutation. Whilst we found minimal impact of LRRK2 on general autophagy (macroautophagy), we observed that the LRRK2 G2019S activation-mutation was associated with reduced mitophagy in specific tissues, including dopaminergic neurons and microglia within the brain. In contrast, knockout of LRRK2 resulted in increased mitophagy. Taken together, these data imply that LRRK2 kinase activity inversely correlates with basal mitophagy levels. In support of this, we found that that treatment of cells or animals with the potent and selective CNS penetrant LRRK2 kinase inhibitor, GSK3357679A (Tasegian et al., 2021; Ding, 2021, in preparation), rescued these LRRK2 G2019S-associated mitophagy defects and enhanced mitophagy in dopamine neurons and microglia in the brains of genotypically normal mice. Our results identify a physiological role for LRRK2 in the regulation of basal mitophagy in vivo and underline the potential value of pharmacological inhibition of LRRK2 as a potential therapeutic strategy to ameliorate aspects of Parkinson’s disease driven by mitochondrial dysfunction.

Results

The pathogenic G2019S LRRK2 mutation impairs basal mitophagy but not autophagy in vitro

To investigate the physiological role of LRRK2 in regulating autophagy we utilised two previously validated and highly similar mouse reporter models (McWilliams et al., 2018a; McWilliams et al., 2016; McWilliams et al., 2019). These transgenic reporter models rely on constitutive expression of a tandem mCherry-GFP tag from the Rosa26 locus. In the mito-QC model, which monitors mitophagy, the tandem tag is localised to mitochondria (by an outer mitochondrial targeting sequence derived from residues 101–152 of the protein FIS1). In the auto-QC model, which monitors general (macro)autophagy, the tandem tag is localised to autophagosomes (by conjugation to the N-terminus of MAP1LC3b). For both models, when a mitochondrion or autophagosome is delivered to lysosomes, the low lysosomal luminal pH is sufficient to quench the GFP signal, but not that from mCherry. Hence, the degree of mitophagy or general autophagy can be determined by the appearance of mCherry-only puncta, which represent mito/autolysosomes (Figure 1A and D). Given that mitophagy is a form of autophagy, the use of both models allows us to monitor the specificity of autophagy in vivo. A large disruption of autophagy in general will also influence mitophagy, whereas a block in mitophagy, which likely represents a small fraction of the total autophagy occurring at any one time, will tend to have little influence on the total autophagic levels.

Figure 1 with 1 supplement see all
LRRK2 kinase activity impairs basal mitophagy in vitro.

(A) Schematics of the mito-QC reporter in mouse model. (B) Representative images of mito-QC primary MEF cultures established from LRRK2 WT, LRRK2 G2019S, and LRRK2 KO embryos. Boxed area is magnified on the right and arrowheads indicate examples of mitophagy (mCherry-only mitolysosomes). (C) Mitophagy quantitation of data shown in B from six to nine independent experiments, as described in Materials and methods. Below is representative immunoblot showing LRRK2 protein expression. (D) Schematics of the auto-QC reporter in mouse model. (E) Representative images of auto-QC primary MEF cultures established from LRRK2 WT, LRRK2 G2019S, and LRRK2 KO embryos. Boxed area is magnified on the right and arrowheads indicate examples of autolysosomes and arrows highlight autophagosomes. (F) Quantitation of data shown in E from four to six independent experiments. (G) Representative images of mito-QC primary MEFs treated with control (DMSO) or 10 nM GSK3357679A. Boxed area is magnified on bottom left and arrowheads indicate examples of mitolysosomes. (H) Quantitation of mitophagy shown in G from three to seven independent experiments. Corresponding immunoblot of indicated proteins is shown below. Scale bars, 10 μm. Overall data is represented as mean +/- SEM. Statistical significance is displayed as *p<0.05, and ***p<0.001.

To investigate the effect of LRRK2 kinase activity on mitophagy, we first isolated and cultured primary mouse embryonic fibroblasts (MEFs) derived from wild-type mice (WT), mice homozygous for the Parkinson’s disease-associated LRRK2 G2019S mutant, or mice homozygous for a LRRK2 knockout (KO) variant; all of which were on a homozygous mito-QC reporter background (Figure 1B and C). A small degree of basal mitophagy was evident in all cell lines. However, we observed that LRRK2 G2019S KI mutant cells displayed significantly lower basal mitophagy levels, whereas the absence of LRRK2 (KO) led to an increase of this process. Interestingly, our data suggests that LRRK2 predominantly influences basal mitophagy as deferiprone (DFP) and long-term amino acid starvation in Earls Balanced Salt Solution (EBSS), both strong mitophagy inducers (Allen et al., 2013), increased mitophagy to a similar level across all genotypes (Figure 1—figure supplement 1A and B).

We next investigated general autophagy using the LRRK2 mouse lines mentioned above on the homozygous auto-QC background. In contrast to mitophagy, in isolated primary MEFs we noticed no significant difference in the number of mCherry-only autolysosomes across all the Lrrk2 genotypes under basal conditions (Figure 1E and F). We also analysed amino acid starvation-induced autophagy, by EBSS incubation. A robust autophagy response was observed in all cells and as with basal autophagy, the Lrrk2 genotype failed to significantly alter this large increase in autolysosomes (Figure 1—figure supplement 1C).

LRRK2 kinase inhibitors correct the G2019S mitophagy defects in vitro

Using genetics, our observations show that LRRK2 kinase activity inversely correlates with mitophagy in vitro. If this is the case, then pharmacological inhibition of LRRK2 kinase activity should also increase mitophagy. Therefore, we aimed to investigate if the mitophagy deficit observed in the G2019S cells could be rescued with LRRK2-selective kinase inhibitors. To that end, we turned to GSK3357679A, a novel pyrrolopyrimidine LRRK2 kinase inhibitor that exhibits excellent cellular potency, selectivity, oral bioavailability and pharmacokinetics/pharmacodynamics correlation in animal studies (Tasegian et al., 2021; Ding, 2021, in preparation). We tested GSK3357679A in primary mito-QC MEFs and observed a dose-dependent effect on mitophagy with a maximal stimulation achieved at a concentration of 10 nM in WT cells (Figure 1G and H). The level of stimulation was equivalent to the level of mitophagy observed in LRRK2 KO cells. Importantly, GSK3357679A failed to alter mitophagy in the absence of LRRK2, demonstrating that its mitophagy-enhancing properties are dependent on LRRK2. In the G2019S cells, we observed a reduced response, with a maximal effect on mitophagy reached at 100 nM and this may reflect the increased kinase activity of this mutant (Nichols et al., 2009). Western blotting analysis confirmed that GSK3357679A potently inhibited LRRK2 kinase activity in a dose-dependent manner, as indicated by decreased phosphorylation of its substrate Rab10 at threonine 73 (Steger et al., 2016), as well as reduced LRRK2 S935 phosphorylation (an indirect measure of LRRK2 activity (Ito et al., 2016), Figure 1H).

To further support a role for LRRK2 kinase activity in negatively regulating basal mitophagy, we utilised two additional and structurally distinct tool LRRK2 kinase inhibitors, GSK2578215A (Reith et al., 2012) and MLi-2 (Fell et al., 2015), in primary mito-QC MEFs. As with GSK3357679A, both these compounds were able to inhibit LRRK2 in cells and increase mitophagy (Figure 1—figure supplement 1D and E). We do note that at high concentrations, MLi2 failed to stimulate mitophagy and this may be due to off-target effects, as at 20 nM it also inhibited mitophagy in the LRRK2 KO cells (Figure 1—figure supplement 1D). Thus, genetically and chemically, the data show that LRRK2 inhibition enhances basal mitophagy in cells and in these assays, GSK3357679A displayed a superior performance compared to other available LRRK2 kinase inhibitors.

LRRK2 inhibition activates conventional mitophagy independently of the PINK1 pathway

Although mito-QC monitors the delivery of mitochondria to lysosomes, it does not give any mechanistic insight as to how this occurs. Given that multiple mitophagy-like pathways exist, which can be dependent or independent of the canonical macroautophagy machinery (Montava-Garriga and Ganley, 2020), we decided to investigate this further. LC3 is the classical autophagosome marker and if mitophagy is occurring via canonical autophagy then LRRK2 inhibition should result in increased co-localisation between mitochondria and LC3. To test this, we took advantage of our primary auto-QC MEFs and co-stained these for the mitochondrially localised ATP synthase subunit beta (ATPB, Figure 2A). Treatment of cells with GSK3357679A significantly increased co-localisation of mCherry-GFP-LC3 with ATPB, both at the autophagosome stage (GFP and mCherry-positive, Figure 2B) and autolysosome stage (mCherry-only positive, Figure 2C). This implies LRRK2 inhibition uses a canonical autophagy pathway to drive mitophagy. To confirm the requirement for the LC3 conjugation machinery in this form of mitophagy, we expressed the mito-QC reporter in the previously reported macroautophagy-deficient ATG5 KO MEFs (Kuma et al., 2004). In the matched WT MEFs, GSK3357679A was able to induce mitophagy in a similar manner to the primary mito-QC MEFs; however, mitophagy induction was blocked in the ATG5 KO MEFs (Figure 2D). As a final, reporter-independent method to confirm mitophagy, we carried out transmission electron microscopy (TEM, Figure 2E and F). To aid in this process, we first immortalised the primary mito-QC MEFs, to remove their time limitation, and confirmed that LRRK2 inhibition could still induce mitophagy (Figure 2—figure supplement 1A–C). Partially degraded mitochondrial structures could clearly be identified within autolysosomes (representative images shown in Figure 2E) and when quantified, a significant 1.3-fold increase was detected in the GSK3357679A-treated samples. Taken together, the data show that LRRK2 inhibition stimulates mitophagy through canonical ATG5-dependent autophagy and confirms that the mito-QC reporter is measuring a conventional mitophagy pathway in this instance.

Figure 2 with 1 supplement see all
LRRK2-dependent mitophagy relies on the general autophagy machinery but is independent of the PINK1 pathway.

(A) Representative images of auto-QC primary MEF cultures treated with 10 nM GSK3357679A for 24 hr and immunolabelled with ATPB. Arrows show examples of autophagosomes containing mitochondria, and arrowheads show examples of autolysosomes containing mitochondria. Scale bars, 10 μm. (B) Quantitation of autophagosomes containing mitochondria shown in (B) or autolysosomes containing mitochondria shown in (C) from three independent experiments. (D) Representative images of WT and ATG5 KO mito-QC immortalised MEF cultures treated with 10 nM GSK3357679A for 24 hr. Corresponding quantitation from three independent experiments is shown below. Scale bars, 10 μm. (E) Representative transmission electron microscopy images from immortalised MEFs treated with 10 nM GSK3357679A for 24 hr. MLy: Mitolysosome; M: Mitochondria; A: autophagosome. Scale bars, 500 nm. (F) Quantitation of data in E from three independent experiments. (G) Representative images of PINK1 KO mito-QC primary MEF cultures treated with/without with 10 nM GSK3357679A for 24 hr. Scale bars, 10 μm. (H) Quantitation of the of mitophagic cells from data shown in G from 3 (4 for KO) independent experiments. (I) Immunoblots of the indicated proteins from WT and PINK1 KO primary MEFs (KO-1 and KO-3 are derived from different embryos) treated with/without 10 nM GSK3357679A or 10 μM CCCP for 24 hr. Overall data is represented as mean +/- SEM. Statistical significance is displayed as *p<0.05 and **p<0.01.

The most widely studied mitophagy pathway involves the activation of PINK1 and Parkin that occurs following mitochondrial depolarisation (Montava-Garriga and Ganley, 2020). Given that mutations in PINK1, Parkin and LRRK2 can all lead to PD, it was important to determine if LRRK2 inhibition resulted in PINK1-dependent mitophagy. To test this, we used previously generated primary MEFs derived from mito-QC x PINK1 KO mice (McWilliams et al., 2018a). Treatment of litter-matched WT and PINK1 KO mito-QC MEFs with GSK3357679A resulted in a comparable increase in mitophagy regardless of the presence or absence of PINK1 (Figure 2G and H). To support the PINK1-independent nature of this pathway we immunoblotted for PINK1-dependent phospho-ubiquitin. We observed no detectible increase in phospho-ubiquitin levels following LRRK2 inhibition, which contrasted with that observed following mitochondrial depolarisation with CCCP treatment (Figure 2I). To further examine the relationship between PINK1/Parkin-dependent mitophagy and LRRK2 inhibition, we sought to directly monitor Parkin-dependent mitophagy. As high levels of Parkin are needed to observe PINK1/Parkin-dependent mitophagy, we next overexpressed HA-tagged Parkin and induced mitophagy with CCCP treatment (Figure 2—figure supplement 1D–F). mito-QC clearly detected a large and significant increase in mitophagy following mitochondrial depolarisation, but this was unaffected by GSK3357679A, as were phospho-ubiquitin levels.

The lack of involvement of PINK1 and Parkin in the observed mitophagy could imply that mitochondrial depolarisation is not a major trigger for this pathway. We thus explored mitochondrial function in general in response to LRRK2 inhibition and GSK3357679A treatment. Firstly, we noticed no obvious changes to mitochondrial morphology and ultrastructure, as observed using TEM (Figure 2—figure supplement 1G). Secondly, using high-resolution respirometry, we measured mitochondrial oxygen consumption. We first investigated if GSK3357679A treatment directly affected the mitochondrial respiratory chain. Thus, we activated the NADH- and succinate-linked pathway and injected sequentially incremental doses of GSK3357679A. This had no direct effect on the mitochondrial respiratory chain (Figure 2—figure supplement 1H). Secondly, we evaluated the chronic effects of LRRK2 inhibition by incubating immortalised MEFs for 24 hr with 10 nM GSK3357679A (Figure 2—figure supplement 1I). Despite an increase in mitophagy (Figure 2—figure supplement 1C), we did not observe any difference in mitochondrial respiration. Furthermore, we did not observe any change in substrate preference. Thus, LRRK2 inhibition does not globally impact mitochondrial form or function at this timepoint. However, given that the fraction of mitochondria targeted for mitophagy is likely small compared to the total pool, we cannot rule out that this population is functionally impaired.

Mutation of LRRK2 in vivo alters mitophagy in specific cell populations within the brain

Given the effects of LRRK2 kinase activity on mitophagy in vitro, we next sought to use our mouse lines to investigate this in vivo. PD is primarily a neurodegenerative disorder, so we first explored mitophagy in the brain. We focussed on four cell populations: two neuronal populations linked to movement – dopaminergic (DA) neurons of the substantia nigra pars compacta (SNpc) and Purkinje neurons of the cerebellum; as well as in two glial cell populations – cortical microglia and cortical astrocytes. In midbrain, we identified SNpc DA neurons using tyrosine hydroxylase (TH) staining and found no difference in the number of DA neurons per field across the Lrrk2 genotypes (Figure 3A and B). These cells are the mouse equivalent of the human population of DA neurons that degenerate in PD and we have previously found that they undergo substantial mitophagy (McWilliams et al., 2018a). Basal mitophagy was significantly enhanced in the LRRK2 KO neurons compared to WT, and although not statistically significant, mitophagy appeared reduced in DA neurons of LRRK2 G2019S KI mice compared to WT (Figure 3A and C). While we cannot say that mitophagy is significantly impaired in the G2019S DA neurons from this set of experiments using nine individual mice, we did however find a significant mitophagy reduction in G2019S DA neurons in a later set of experiments, with 10 mice per condition (Figure 6A and B). Taken together, these observations are similar to our earlier results in MEFs and showed that the presence of LRRK2 can impact mitophagy in this clinically relevant population of neurons within the midbrain. To determine if this effect is typical of neurons in general, we investigated mitophagy in another neuronal population involved in motor control, the Purkinje neurons. These cells were identified in cerebellar sections using immunostaining against the calcium sensor Calbindin-D28k. These cells are rich in mitochondria and as shown previously (McWilliams et al., 2016), they also undergo significant mitophagy (Figure 3D). Contrary to what we observed in SNpc DA neurons, no statistical difference in mitophagy in Purkinje cells was found between any group (Figure 3E).

Figure 3 with 1 supplement see all
Mutation of LRRK2 in vivo alters brain mitophagy.

(A) Representative image of tyrosine hydroxylase (TH) immunolabelled dopaminergic neurons within the substantia nigra pars compacta (SNpc) undergoing basal mitophagy in LRRK2 WT, LRRK2 G2019S, and LRRK2 KO mito-QC mice. Arrowheads show examples of mitolysosomes and arrows indicate mitochondria. (B) Quantitation of the number of TH positive cells per field of view using a 63x objective. (C) Quantitation of basal mitophagy per μm (Sironi et al., 2020) of TH staining, data points represent means from individual mice. (D) Representative maximal intensity projection and isosurface render of calbindin immunolabelled Purkinje neurons in mito-QC cerebellum sections, undergoing basal mitophagy. (E) Quantitation of basal mitophagy per μm (Sironi et al., 2020) of calbindin staining, data points represent means from individual mice. (F) Representative image and isosurface renders of Iba1 immunolabelled microglia undergoing basal mitophagy in cortical sections from LRRK2 WT, LRRK2 G2019S, and LRRK2 KO mito-QC mice. Arrowheads highlight mitolysosomes. (G) Quantitation of the number of Iba1-positive cells in the brain cortex per field of view using a 63x objective. (H) Quantitation of basal mitophagy per Iba1-positive cell body, data points represent means from individual mice. (I) Representative maximal intensity projection and isosurface render of GFAP immunolabelled astrocytes undergoing basal mitophagy in mito-QC cortical sections. (J) Quantitation of basal mitophagy per μm (Sironi et al., 2020) of GFAP staining, data points represent means from individual mice. Scale bars, 10 μm. Overall data is represented as mean +/- SEM. Statistical significance is displayed as *p<0.05, **p<0.01, and ***p<0.001.

As we observed neuron-specific alterations of mitophagy, we next examined the effect of Lrrk2 genotype in two distinct populations glial cells within the cortex. Immune-related microglia were identified by Iba1 (ionised calcium-binding adapter molecule 1, Figure 3F). Notably, we observed an enhanced presence of microglial cells in the cortex of G2019S animals when compared to WT or KO mice (Figure 3G). We do not yet understand the nature of this increase and further work will be needed to determine if there are simply more microglia in the G2019S mice, or an increased movement of cells to this area of the brain. Regardless, when mitophagy quantitation was normalised for cell number (mitolysosomes per Iba1-positive cell body per field), we found a significant decrease in basal mitophagy in G2019S microglia compared to WT, as well as an increase in mitophagy levels in KO cells (Figure 3H). Thus, as with DA neurons, LRRK2 can impacts basal mitophagy in microglia. In contrast, cortical astrocytes, stained with glial fibrillary acidic protein (GFAP, Figure 3I), did not show any observable difference in mitophagy across Lrrk2 genotypes (Figure 3J).

In contrast to the Lrrk2 genotype effects on mitophagy in DA neurons and microglia, analysis of auto-QC mouse brains indicated no change in general macroautophagy in these cell types (Figure 3—figure supplement 1). Thus, the LRRK2 G2019S mutation is not causing a major disruption in neuronal autophagy but does influence basal mitophagy levels.

Mutation of LRRK2 in vivo also alters mitophagy in peripheral organs with high LRRK2 expression

We next assessed mitophagy levels in the lungs, a tissue in which the levels of LRRK2 are known to be elevated (Uhlén et al., 2005; Uhlen et al., 2010). Basal mitophagy across the whole lung was evident in all genotypes and in a similar fashion to MEFs, DA neurons and microglia, mitophagy was reduced in G2019S mice and enhanced (over 2-fold relative to WT) in KO mice (Figure 4A and B), Consistent with this, mitochondrial content was decreased when comparing KO to G2019S (although no significant increase of this parameter was detected compared to WT, see Figure 4—figure supplement 1A). As previously reported (Baptista et al., 2018; Plowey et al., 2008), we observed enlarged type II pneumocytes with considerable vesicular-like structures in all the animals of the LRRK2 KO group that is attributable to the accumulation of large lamellar bodies, which are secretory lysosomes responsible for surfactant release. We confirmed the nature of these structures as enlarged lamellar bodies by filipin staining lung sections for cholesterol, a component found in surfactant (Figure 4—figure supplement 1B).

Figure 4 with 1 supplement see all
Effects of Lrrk2 genotype on basal mitophagy and macroautophagy in selected peripheral tissues.

(A) Representative tile scan and images of mito-QC lungs from LRRK2 WT, LRRK2 G2019S, and LRRK2 KO mice. Arrows on the tile scan highlight Type II pneumocytes (II.), alv. show alveoli. Arrowheads in the higher magnification images indicate examples of mitolysosomes and circled cells correspond to Type II pneumocytes (II.) and I. indicates Type I pneumocytes. (B) Quantitation of lung basal mitophagy from data shown in D, data points represent means from individual mice. (C) Representative images of mito-QC kidney cortex from LRRK2 WT, LRRK2 G2019S, and LRRK2 KO mice. glm. indicates glomeruli and pt. indicates proximal tubule examples. (D) Quantitation of kidney basal mitophagy from data shown in F, data points represent means from individual mice. (E) Representative images of auto-QC lungs from LRRK2 WT, LRRK2 G2019S, and LRRK2 KO mice. Arrowheads highlight autolysosomes, arrows indicate autophagosomes, and II. indicates Type II pneumocytes. (F) Quantitation of lung autophagy from data shown in C, data points represent means from individual mice. (G) Representative images of auto-QC kidney cortex from LRRK2 WT, LRRK2 G2019S, and LRRK2 KO mice. Arrowheads and, arrows as in C, glm. indicates glomeruli, and pt. indicates proximal tubules. (H) Quantitation of kidney autophagy from data shown in E, data points represent means from individual mice. Scale bars, Tile scan in A: 100 μm, Other pictures:10 μm. Overall data is represented as mean +/- SEM. Statistical significance is displayed as **p<0.01, and ***p<0.001.

The tissue reported to have the highest LRRK2 expression is the kidney (Uhlén et al., 2005; Uhlen et al., 2010). We first investigated mitophagy in the kidney cortex, where we had previously shown the proximal tubules to be a major site of mammalian mitophagy (McWilliams et al., 2016). LRRK2-dependent mitophagy changes in the kidney were much lower in magnitude compared to the lung, yet there was a small decrease in G2019S-expressing tissue (Figure 4C and D). However, we do note that mitophagy is 10-fold higher in this region compared to lung, which may mask relatively small changes conferred by Lrrk2 genotypes.

We next studied in vivo genotype effects on autophagy, using the same conditions and organs as for the mito-QC reporter. Consistent with brain and MEF data, no significant difference in the number of autolysosomes was observed in the lungs of auto-QC reporter mice (Figure 4E and F). Again, enlarged type II pneumocytes were observed in LRRK2 KO animals (Figure 4E). Likewise, in the kidney cortex, we did not detect an effect of Lrrk2 genotype on autolysosomes (Figure 4G and H). We also note that no major difference was seen in the number of autophagosomes across both lung and kidney (Figure 4—figure supplement 1C and D). Taken together, these data suggest that the Lrrk2 genotype does not majorly affect all autophagy pathways but predominantly impacts basal mitophagy, both in vitro and in vivo.

GSK3357679A corrects the G2019S mitophagy defect in vivo

We next sought to determine if we could pharmacologically rescue the observed mitophagy defects in vivo. For this purpose, we utilised GSK3357679A – the pharmacodynamic characteristics of which have been shown to be suitable for extended oral dosing studies in rodents (Tasegian et al., 2021; Ding, 2021, in preparation). We administered mito-QC WT, G2019S, and LRRK2 KO mice with GSK3357679A via oral gavage every 12 hr for a total of four doses. During this period, we observed no effect of GSK3357679A on body weight in any genotype (Figure 5—figure supplement 1A). Tissues were then harvested 2 hr post the final dose. We focused our analyses on tissues where our previous analyses of Lrrk2 genotypic variants suggested a LRRK2-dependent role in mitophagy, namely the brain and lung as well as the kidney.

Initially focussing on the brain, LRRK2 inhibition was confirmed in tissue lysates of GSK3357679A dosed mice by phosphosite immunoblotting of LRRK2 and its substrate Rab12 (Figure 5A). GSK3357679A decreased the phosphorylation of LRRK2 on S935 and the phosphorylation of Rab12 on S106, in both WT and G2019S mice (Figure 5A and B). Interestingly, the level of Rab12 phosphorylation was higher in G2019S brains, which could reflect the higher kinase activity that is associated with this mutation.

Figure 5 with 1 supplement see all
GSK3357679A treatment inhibits LRRK2 in the brain.

(A) Immunoblots of the indicated LRRK2-related, mitochondrial and autophagy proteins from brain lysates of LRRK2 WT, LRRK2 G2019S, and LRRK2 KO mito-QC mice treated with vehicle or GSK3357679A. (B) Quantitation of phosphorylation data from the LRRK2-related proteins displayed in A. (C) Quantitation of mitochondria- and mitochondrial biogenesis-related proteins displayed in A. (D) Quantitation of autophagy-related proteins displayed in A. Overall data is represented as mean +/- SEM. Statistical significance is displayed as *p<0.05, **p<0.01, ***p<0.001, and ****p<0.0001.

In the same tissue lysates, we also immunoblotted for mitochondrial markers (Figure 5A and C). We did not find any significant difference in the levels of the matrix-localised HSP60 or the outer membrane-localised TOMM20, in either WT or G2019S mice. We think the failure to see any increase in these markers in the G2019S brain likely reflects the low degree of basal mitophagy in general and that we are analysing whole brain tissue that will contain cells that are unresponsive to changes in LRRK2 activity (see Figure 3D and I). However, in the lysates analysed from two LRRK2 KO mice, both these proteins were reduced. This observation is consistent with increased mitophagy in LRRK2 KO cells, and given the data in G2019S brains, implies that the total loss of LRRK2 kinase activity has a relatively larger mitophagy effect than that the smaller activity change caused by the pathogenic mutation. Of potential relevance, we found that the mitochondrial biogenesis marker PGC-1α was increased in the brains of G2019S mice. Likewise, we saw a similar increase in the basal level of the related protein, PGC-1β. Additionally, in both WT and G2019S brains, LRRK2 inhibition caused a further increase in PGC-1β, suggesting a potential activation of mitochondrial biogenesis. In confirmation, we observed an increase of the master regulator of mitochondrial biogenesis, TFAm (Ljubicic et al., 2010), which coordinates the simultaneous expression of both mitochondrial and nuclear genomes, and controls the mtDNA copy number (Figure 5A and C). While the timecourse of GSK3357679A treatment is likely too short to see significant mitochondrial biogenesis (Singh et al., 2015; Daussin et al., 2012), it possible that this is a cellular response to changing mitophagy. While further work will be needed to validate this, a careful balance between mitochondrial turnover and biogenesis has been shown to occur previously (Palikaras et al., 2015). In addition to brain, we also confirmed LRRK2 kinase inhibition in the lungs and kidneys of the same animals, with GSK3357679A-treated mice showing significant loss of both LRRK2 S935 phosphorylation and Rab 10 T73 phosphorylation (Figure 5—figure supplement 1B and C).

As LRRK2 kinase activity was successfully inhibited in GSK3357679A-treated animals, we next analysed mitophagy. In DA neurons of the SNpc, we found that treatment with GSK3357679A increased mitophagy in both WT and G2019S KI mice. In-line with earlier results, the vehicle dosed G2019S group displayed significantly lower mitophagy compared to the vehicle- dosed WTs (Figure 6A and B). Importantly, treatment with GSK3357679A restored G2019S mitophagy to base-line WT levels (Figure 6A and B). No difference was observable in the KO groups in presence of GSK3357679A, showing mitophagy effects are through on-target LRRK2 inhibition.

Figure 6 with 1 supplement see all
Pharmacological rescue of LRRK2-mediated mitophagy defects in vivo.

(A) Representative image of tyrosine hydroxylase (TH) immunolabelled dopaminergic neurons of the substantia nigra pars compacta in LRRK2 WT, LRRK2 G2019S, and LRRK2 KO mito-QC mice treated or not (vehicle) with GSK3357679A. Arrowheads indicate mitolysosome examples. (B) Quantitation of mitophagy from data shown in A, with the addition of LRRK2 KO. Each data point represents mean value from an individual mouse. (C) Representative images of Iba1 positive cortical microglia from LRRK2 WT, and LRRK2 G2019S mice treated or not (vehicle) with GSK3357679A. Arrowheads indicate mitolysosomes. (D) Quantitation of mitophagy from data shown in E, with the addition of LRRK2 KO. (E) Representative images of mito-QC lungs from LRRK2 WT, and LRRK2 G2019S mice treated or not (vehicle) with GSK3357679A. Arrowheads highlight mitolysosomes. (F) Quantitation of mitophagy from data shown in E, with the addition of LRRK2 KO. For (B), (D), and (F), V = vehicle dosed animals, GSK = GSK3357679A dosed animals. Each data point represents mean value from an individual mouse. Scale bars, 10 μm. Overall data is represented as mean +/- SEM. Statistical significance is displayed as *p<0.05, **p<0.01, ***p<0.001, and ****p<0.0001.

As we had found differences in cortical microglial mitophagy between genotypes, we next investigated the effect of GSK3357679A treatment on this cell population. GSK3357679A increased mitophagy in the cortical microglia in both WT and G2019S groups (Figure 4E and F). Consistently, GSK3357679A restored G2019S mitophagy levels to a value similar to that detected in the control group (WT-V). Mitophagy was unaffected by GSK3357679A in the KO groups, confirming GSK3357679A specificity on LRRK2 kinase activity. As seen earlier (Figure 3G), microglial cell numbers were increased in the cortex of vehicle-treated G2019S mice compared with vehicle-treated WT mice (Figure 6—figure supplement 1A). Intriguingly, GSK3357679A treatment recovered the increase in number of cortical microglia observed in LRRK2 G2019S KI mice (Figure 4—figure supplement 1B), suggesting that LRRK2 kinase activity is a key contributor to regulation of microglial numbers in this mouse line.

In the lungs, we found that GSK3357679A increased mitophagy levels in both WT and G2019S KI animals (Figure 6E and F). GSK3357679A had no effect on mitophagy levels in the lungs of LRRK2 KO mice (Figure 6F). Importantly, in the G2019S group, GSK3357679A elevated mitophagy levels to a value similar to the WT Vehicle group, suggesting LRRK2-inhibition can also rescue the G2019S-mediated defect in mitophagy in lung. As observed for other LRRK2 inhibitors we observed enlarged lamellar bodies in Type-II pneumocytes in the lungs of mice treated with GSK3357679A, similar to that observed in LRRK2 KO mice (Figure 4A) and to what has been previously reported in the presence of other LRRK2 kinase inhibitors (Fell et al., 2015; Baptista et al., 2018; Fuji et al., 2015). Consistent with KO mice, in the kidney we found that GSK3357679A had a minimal effect on mitophagy despite this organ exhibiting robust LRRK2 inhibition (compare Figure 4C and D with Figure 6—figure supplement 1B and C). Although as previously mentioned, the very high levels of mitophagy in this tissue could be masking any subtle mitophagy increases.

In summary, these results show that a pathogenic mutation of LRRK2 impairs basal mitophagy not just in isolated cells, but also in distinct cell types within tissues. Importantly, this phenotype can be rescued by the use of LRRK2 kinase inhibitors.

Discussion

Our work reveals that LRRK2 kinase activity inversely correlates with basal mitophagy levels, both in vitro and in vivo in specific cells and tissues. Strikingly, the mitophagy defects seemed to be specific to certain cell types. Indeed, we observed different effects in two different neuronal subpopulations and in two microglial subpopulations. More work is needed to understand why mitophagy is more sensitive to LRRK2 kinase activity in these cells, but it may help explain why DA neurons degenerate in PD. Interestingly, we found a higher mitochondrial content in the soma of Purkinje neurons compared to DA neurons, indicative of a higher oxidative metabolism in the former. In addition, mitophagy levels were much lower in the Purkinje cells, implying an inverse correlation between oxidative metabolism and mitophagy, similar to previous observations in different muscle subtypes (Montava-Garriga et al., 2020). Speculatively, the higher basal level of mitophagy in these DA neurons could be required to maintain oxidative metabolism in light of their lower mitochondrial numbers, thus rendering them susceptible to defects affecting mitophagy. Also of potential relevance, we observed a higher difference in mitophagy levels between genotypes in the cortical microglia than in the DA neurons. Brain resident microglia have been shown to have much higher LRRK2 levels and activity than neuronal populations, which could have implications for disease aetiology (Schapansky et al., 2015).

The work presented here shows for the first time that pathogenic LRRK2 mutations can alter basal mitophagy in clinically relevant cell populations in vivo. However, the extent to which impaired mitophagy drives an individual’s Parkinson’s disease remains to be determined. PINK1 and Parkin-mediated mitophagy is a significant pathway with respect to PD and so it was important to confirm if this was also occurring here. However, we found that loss of PINK1 (and hence a block in Parkin activation) did not impact mitophagy induced upon LRRK2 inhibition and nor did it alter the magnitude of Parkin-dependent mitophagy that occurs following mitochondrial depolarisation. This fits well with previous data generated by us and others, which demonstrates that loss of PINK1 or Parkin activity does not significantly alter basal mitophagy rates in vivo (McWilliams et al., 2018a; McWilliams et al., 2018b; Lee et al., 2018; Wrighton et al., 2021). We take this to mean that the PINK1/Parkin pathway drives mitophagy under distinct types of extreme mitochondrial stress, such as that caused during repeated exhaustive exercise (Sliter et al., 2018), in contrast to the basally regulated LRRK2 pathway described here. Regardless, if loss of stress-induced PINK1/Parkin-dependent mitophagy can lead to PD, then it is reasonable to assume that loss of LRRK2-regulated basal mitophagy could also contribute. These data now imply that impaired mitophagy may be a common theme in PD pathology.

Recent reports in other models support our conclusion of a role for LRRK2 in regulating mitophagy. In vitro assays in patient derived fibroblasts bearing G2019S or R1441C LRRK2 variants are consistent with our in vitro cell assays and observations in vivo (Wauters et al., 2020; Bonello et al., 2019; Korecka et al., 2019; Hsieh et al., 2016).

The mechanism by which LRRK2 kinase activity regulates basal mitophagy is currently unclear and various potential pathways exists, as discussed in our recent review (Singh and Ganley, 2021). LRRK2 has been shown to phosphorylate a subset of Rab GTPases (Steger et al., 2016) and, given the roles of Rabs in membrane trafficking, it is tempting to suggest that they may be key in regulating this mitophagy pathway (Pfeffer, 2018; Pfeffer, 2017). It has been recently shown that lysosomal overload stress induces translocation of Rab7L1 and LRRK2 to lysosomes (Eguchi et al., 2018). This leads to the activation of LRRK2 and the stabilisation of Rab8 and Rab10 through phosphorylation. Another recent study showed that LRRK2 mutations inhibit the mitochondrial localisation of Rab10 (Wauters et al., 2020). LRRK2 also plays a role in trafficking and may influence mitophagosome travel to lysosomes. Previous work has shown that LRRK2 activity can influence phagosome trafficking to lysosomes (Härtlova et al., 2018) and recently it was shown that LRRK2 can influence axonal autophagosome trafficking via the motor adaptor protein JIP4 (Boecker et al., 2021). Relatedly and also of relevance, LRRK2 regulation of JIP4 has been implicated in lysosome tubulation (Bonet-Ponce et al., 2020).

It is also possible that LRRK2 kinase activity alters mitochondrial function and indirectly affects mitophagy. Although we failed to detect an effect of LRRK2 inhibition of global cellular mitochondrial respiration, it is possible a small pool of mitochondria has altered oxygen consumption that impacts mitophagy. Indeed, deleterious mitochondrial phenotypes have been observed in LRRK2 G2019S patient-derived cells (Delcambre et al., 2020; Mortiboys et al., 2010; Sanders et al., 2014), although further work is needed to clarify if this is a cause or consequence of impaired mitophagy. It is important to note that GSK3357679A led to activation of mitochondrial biogenesis via PGC-1β and not PGC-1α. Although PGC-1α has been widely studied and described in the literature, the specific role of PGC-1β remains debated (Gali Ramamoorthy et al., 2015; Singh et al., 2019). Our current findings suggest that in the brain, PGC-1β-dependent mitochondrial biogenesis, triggered by LRRK2-dependent mitophagy, could act to prevent excessive loss of mitochondrial content and maintain mitochondrial homeostasis.

We used two highly similar reporter models in primary MEFs and in mice to study general autophagy and mitophagy. The use of both the mito-QC and the auto-QC reporters, in combination with selective LRRK2 kinase inhibitors, provided evidence that LRRK2 kinase activity affects mitophagy, rather than autophagy in general. The role of LRRK2 kinase activity on autophagy has been previously investigated in several studies with inconclusive or contradictory effects (Plowey et al., 2008; Härtlova et al., 2018; Schapansky et al., 2014; Gómez-Suaga et al., 2012; Bravo-San Pedro et al., 2013; Manzoni et al., 2013; Orenstein et al., 2013). However, with our reporter systems, we cannot entirely exclude that other selective autophagy pathways are affected. Additionally, total flux through the autophagy pathway is likely to be much higher than the relative flux attributable to mitophagy, and combined with the observed higher inter-individual variability with our autophagy reporter, this makes it potentially more difficult to pick up small changes. For these reasons, it would be unreasonable to entirely exclude the involvement of LRRK2 in general autophagy, although our results lack support for this.

Our results show that three structurally distinct selective LRRK2 kinase inhibitors are active on mitophagy in MEF cells, and that in vivo the tool compound GSK3357679A demonstrates similar cell-specific effects in DA neurons and microglia within the brain. Importantly, use of this inhibitor in vitro and in vivo supported our genetic data in suggesting that LRRK2 kinase activity inversely correlates with the level of basal mitophagy. The fact that we could rescue G2019S-impared mitophagy in PD-relevant cell types, within the brain, provides an exciting prospect that LRRK2 inhibitor-mediated correction of mitophagic defects in Parkinson’s patients could have therapeutic utility in the clinic. In addition, LRRK2 kinase activity inhibitors could also provide a way to increase mitophagy in general, which could be beneficial in idiopathic PD, or indeed, in other non-related conditions where increased clearance of mitochondria could be beneficial, such as mitochondrial diseases. As with other LRRK2 inhibitors, GSK3357679A also induced enlarged lamellar bodies in the lung and it is possible that this effect could limit the therapeutic approach of targeting LRRK2. However, it is important to note that extensive preclinical studies in vivo failed to detect any effects of LRRK2 inhibition on lung function (Baptista et al., 2020) and likewise, no deleterious effects have been reported for LRRK2 kinase inhibitors in clinical studies for Parkinson’s disease thus far (Biogen Denali Therapeutics Inc, 2021a; Biogen Denali Therapeutics Inc, 2021b).

Here we demonstrate, through both genetic manipulation and pharmacology, that the most common mutation in PD impairs basal mitophagy in tissues and cells of clinical relevance. The fact that we can rescue this genetic defect in mitophagy using LRRK2 inhibitors, holds promise for future PD therapeutics.

Materials and methods

Animals

Experiments were performed on mice genetically altered for Leucine-rich repeat kinase 2 (LRRK2), using either wild-type, LRRK2 G2019S (Steger et al., 2016) mutation knock-in mice, or mice in which LRRK2 has been ablated (Parisiadou et al., 2009; Lin et al., 2009) (KO).The mitophagy (mito-QC) and the autophagy (auto-QC) reporter mouse models used in this study were generated as previously described (McWilliams et al., 2018a; McWilliams et al., 2016).

Primary mouse embryonic fibroblasts culture

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Cells used in this study were Mouse Embryonic Fibroblasts (MEFs) derived in-house and were tested mycoplasma negative (MycoAlert, Lonza, LT07-318). Primary mouse embryonic fibroblasts were derived, from time-mated pregnant females at E12.5 for the LRRK2-related lines and E17.5 for the PINK1 KO and Parkin overexpressing MEFs. Primary MEFs were maintained in DMEM (Gibco, 11960–044) supplemented with 10% FBS, 2 mM L-Glutamine (Gibco, 2503–081), 1% Na-Pyruvate (Gibco, 11360–070), 1% Non-essential amino acids (Gibco, 11140–035), 1% Antibiotics (Penicillin/Streptomycin 100 U/ml penicillin and 100 μg/ml streptomycin; Gibco), and 150 μM β-Mercaptoethanol (Gibco, 21985–023) at 37°C under a humidified 5% CO2 atmosphere.

Immortalised mouse embryonic fibroblasts

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Immortalised MEFs (McWilliams et al., 2018a) were maintained in DMEM (Gibco, 11960–044) supplemented with 10% FBS (20% for Parkin over-expressing MEFs), 2 mM L-Glutamine (Gibco, 2503–081), 1% Na-Pyruvate (Gibco, 11360–070), 1% Non-essential amino acids (Gibco, 11140–035), 1% Antibiotics (Penicillin/Streptomycin 100 U/ml penicillin and 100 μg/ml streptomycin; Gibco), at 37°C under a humidified 5% CO2 atmosphere. ATG5 knock-out immortalised MEFs and their corresponding wild-type were a kind gift from the Mizushima lab (Kuma et al., 2004). Cells were transduced to express the mito-QC reporter, and selected as previously described (Allen et al., 2013).

Primary and immortalised mouse embryonic fibroblasts treatments

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To assess mitophagy and autophagy upon stimulation, cells were treated for 24 hr with either 1 mM 3-Hydroxy-1,2-dimethyl-4(1H)-pyridone (Deferiprone/DFP, Sigma-Aldrich, 379409), or incubated in Earl’s balanced salt solution (EBSS, Gibco, 24010–043). mito-QC MEFs were also treated for 24 hr with LRRK2 kinase activity inhibitors GSK2578215A (Reith et al., 2012) (250, 500, 1000 nM), MLi-2 (Fell et al., 2015) (5, 10, and 20 nM), or GSK3357679A (compound 39 (Tasegian et al., 2021; Ding, 2021, in preparation), 0.1, 1, 10, 100, 1000 nM). All treatments (apart from EBSS) were in DMEM (Gibco, 11960–044) supplemented with 10% FBS (20% for Parkin over-expressing MEFs), 2 mM L-Glutamine (Gibco, 2503–081), 1% Non-essential amino acids (Gibco, 11140–035), 1% Antibiotics (Penicillin/Streptomycin 100 U/ml penicillin and 100 μg/ml streptomycin; Gibco), and 150 μM β-Mercaptoethanol (Gibco, 21985–023) at 37°C under a humidified 5% CO2 atmosphere. MLi-2 and GSK2578215A were synthesised by Natalia Shpiro (University of Dundee) as described previously (Reith et al., 2012; Fell et al., 2015).

Light microscopy

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MEFs were plated on glass coverslips and treated as described in the previous paragraph. At the end of the treatment, cells were washed twice in DPBS (Gibco, 14190–094), and fixed in 3.7% Paraformaldehyde (Sigma, P6148), 200 mM HEPES, pH=7.00 for 20 min. Cells were washed twice with, and then incubated for 10 min with DMEM, 10 mM HEPES. After a wash with DPBS, nuclei were stained or not with Hoechst 33342 (1 µg/mL, Thermo Scientific, 62249) for 5 min. Cells were washed in DPBS and mounted on a slide (VWR, Superfrost, 631–0909) with Prolong Diamond (Thermo Fisher Scientific, P36961). Images were acquired using a Nikon Eclipse Ti-S fluorescence microscope with a 63x objective.

Quantitation of mitophagy and autophagy in vitro

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Quantification of red-only dots was semi-automatised using the mito-QC counter plugin on FIJI as previously described (Montava-Garriga et al., 2020; Schindelin et al., 2012). Note, in primary MEFs we observed heterogeneity between cells and observed changes in mitophagy over increasing passages, which were uniform across Lrrk2 genotypes. To keep quantitation consistent, we ran our experiments in sets of the same passage (simultaneously with the different genotypes) and set a threshold above which the cells were considered as mitophagic. We analysed the distribution of mitolysosomes per cell of untreated WT cells and set the threshold based on a truncated mean to remove outliers (note, outliers were only removed to set the threshold and all data were included in the quantitation). Therefore, due to the heterogeneity of the primary MEFs and passage, representing the data in percentage of mitophagic cells allowed us to better compare data sets.

Autophagosomes and autolysosomes were quantified using the Autophagy counter plugin on FIJI developed in house, following the same principle as the mito-QC counter (Singh et al., 2020). The macro ‘auto-QC_counter.ijm’ (‘version 1.0 release’, DOI: 10.5281/zenodo.4158361) is available from the following github repository: https://github.com/graemeball/autoQC_counter copy archived at swh:1:rev:789f01e896eb25607809239a894010e5e25c25c6 Ball, 2020.

ATPB immunostaining in auto-QC primary MEFs and quantitation

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Primary auto-QC MEFs were fixed as described in the previous paragraph. Cells were then permeabilised with 0.3% Triton X-100 in PBS for 5 min and washed twice in PBS/BSA 1%, followed by a 15-min incubation in PBS/BSA 1% on a shaker. Cells were incubated with the primary antibody directed against ATPB (1/200, Abcam, ab14730) prepared in PBS/BSA 1% for 1 hr at 37°C. Coverslips were washed three times in PBS/BSA 1% on shaker for 10 min, and cells were incubated with a Goat anti-Mouse IgG (H+L) Cross-Adsorbed Secondary Antibody, Pacific Blue (1/500, ThermoFisher Scientific, P31582) prepared in PBS/BSA 1% for 30 min at room temperature. Coverslips were then washed three times in PBS on shaker for 10 min and mounted as described above. Images were acquired using a Zeiss LSM880 with Airyscan laser scanning confocal microscope (Plan-Apochromat 63x/1.4 Oil DIC M27) using the optimal parameters for acquisition (Nyquist). 10–15 images were acquired per sample. Images were analysed with the Volocity Software (version 6.3, Perkin-Elmer). Images were first filtered using a fine filter to suppress noise. Subcellular structures of interest were detected by thresholding each channel. Colocalisation of autophagosomes with mitochondria was evaluated by intersecting the thresholded yellow (both red and green) signal with the thresholded signal from the blue channel. Colocalisation of autolysosomes with mitochondria was evaluated by intersecting thresholded red-only signal (identified by identified by detecting the high-intensity objects in the red channel and applying a red/green ratio threshold) with thresholded signal from the blue channel. Experiments were realized in triplicate using two passages of two MEF lines derived from independent matings. The percentage of ATPB positive autophagosomes or autolysosomes relative to their corresponding total number of autophagosomes/autolysosomes was determined by dividing the number of ATPB-colocalising autophagosomes/autolysosomes detected per field by the number of total autophagosomes/autolysosomes detected per field, multiplied by 100.

Transmission electron microscopy (TEM) sample preparation

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Cells were fixed on the dish in 4% paraformaldehyde and 2.5% glutaraldehyde in 0.1 M sodium cacodylate buffer (pH 7.2) for 30 min then scraped and transferred to a tube and fixed for a further 30 min prior to pelleting. The pellets were given three washes in cacodylate buffer, cut into small pieces and they were then post-fixed in 1% OsO4 with 1.5% Na ferricyanide in cacodylate buffer for 60 min. After another three washes they were contrasted with 1% tannic acid and 1% uranyl acetate. The cell pellets were then dehydrated through alcohol series into 100% ethanol, changed to propylene oxide left overnight in 50% propylene oxide 50% resin and finally embedded in 100% Durcupan resin (Sigma). The resin was polymerised at 60°C for 48 hr and sectioned on a Leica UCT ultramicrotome. Sections were contrasted with 3% aqueous uranyl acetate and Reynolds lead citrate before imaging on a JEOL 1200EX TEM using an SIS III camera.

TEM quantitation

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Cells for quantitative imaging were selected by uniform random sampling, ie. a random start point on the section was selected and cells chosen at uniform distances across the section. Cells were viewed initially at low magnification (×2500) and regions with electron-lucid cytoplasm were chosen and imaged at high magnification (×40,000). The images were then anonymised and scored blinded for autolysosomes with or without mitochondria. Three independent experiments were quantified with a total of 181 and 256 images per Control and GSK3357679A treated group, respectively. For each image, up to 10 autolysosomes were scored (with an average of 1.93 autolysosomes per picture). For each image, the percentage of autolysosomes containing mitochondria was calculated by dividing the number of autolysosomes containing mitochondria by the total number of autolysosome and multiplying this value by 100. The relative increase in mitolysosomes was calculated by setting the control value of each independent experiment at one to highlight the consistent increase with GSK3357679A.

High-resolution respirometry in immortalised MEFs

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Mitochondrial respiration was studied in digitonin-permeabilised cells (10 μg / 106 cells) to keep mitochondria in their architectural environment. The analysis was performed in a thermostated oxygraphic chamber at 37°C with continuous stirring (Oxygraph-2 k, Oroboros instruments, Innsbruck, Austria). Cells were collected with trypsin and placed in MiR05 respiration medium (110 mM sucrose, 60 mM lactobionic acid, 0.5 mM EGTA, 3 mM MgCl2, 20 mM taurine, 10 mM KH2PO4, 20 mM HEPES adjusted to pH 7.1 with KOH at 30°C, and 1 g/l BSA essentially fatty acid free). Acute effects of GSK3357679A on the mitochondrial respiratory chain (n=4) were determined by successively injecting incremental doses of the compound (0.1 nM, 1 nM, 10 nM, 100 nM, and 100 nM) into the oxygraph chamber after activating the NS pathways (Glutamate (G) 10 mM, Malate (M) 2 mM, ADP (P) 2.5 mM, and Succinate (S) 10 mM). Chronic effects of GSK3357679A on mitochondrial respiration (n=4) were determined after 24 hr incubation with 10 nM GSK3357679A using the Substrate-Uncoupler-Inhibitor titration protocol number 2 (SUIT-002) (Doerrier et al., 2018). Briefly, after residual oxygen consumption in absence of endogenous fuel substrates (ROX, in presence of 2.5 mM ADP) was measured, fatty acid oxidation pathway state (F) was evaluated by adding malate (0.1 mM) and octanoyl carnitine (0.2 mM) (OctMP). Membrane integrity was tested by adding cytochrome c (10 μM) (OctMcP). Subsequently, the NADH electron transfer-pathway state (FN) was studied by adding a high concentration of malate (2 mM, OctMP), pyruvate (5 mM, OctPMP), and glutamate (10 mM, OctPGMP). Then succinate (10 mM, OctPGMSP) was added to stimulate the S pathway (FNS), followed by glycerophosphate (10 mM, OctPGMSGpP) to reach convergent electron flow in the FNSGp-pathway to the Q-junction. Uncoupled respiration was next measured by performing a titration with CCCP (OctPGMSGpE), followed by inhibition of complex I (SGp) with rotenone (0.5 μM, SGpE). Finally, residual oxygen consumption (ROX) was measured by adding Antimycin A (2.5 μM). ROX was then subtracted from all respiratory states, to obtain mitochondrial respiration. Results are expressed in pmol · s−1 · 106 cells.

Animal studies

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Initial power calculations were undertaken using a two-sample, two-sided equality calculation with power set at 0.8 and type I error at 5%. Based on pilot data in the heart (mean of 60.6 mitolysosomes per section with a standard deviation of 19.8), to be able to detect a 40% change (i.e. a mean of ~24 mitolysosomes) we would require a sample size ~10. Experiments were performed on 81 adult mice (9–23 weeks old) of both genders (n=8–12 per group for the mito-QC reporter, and n=9–15 per group for the auto-QC reporter), all homozygous for the corresponding reporter (mitophagy or autophagy).

The effect of the CNS penetrant LRRK2 kinase inhibitor GSK3357679A in vivo was assessed using 50 adult mice (9–17 weeks old at the end of the study), all homozygous for the mito-QC reporter. Mice of both genders were randomly assigned to the vehicle or to the GSK3357679A-treated group (WT-Vehicle: n=10, WT-GSK3357679A: n=10, G2019S-Vehicle: n=10, G2019S-GSK3357679A: n=10, KO-Vehicle: n=5, and KO-GSK3357679A: n=5). Vehicle-treated animals were dosed (10 mL/kg) with aqueous methylcellulose (1% w/v, Sigma, M0512) prepared in sterile water (Baxter, UKF7114), or with GSK3357679A (15 mg/kg/dose) prepared in aqueous methylcellulose. Treatment was administered by oral gavage every 12 hr for a total of four times per mouse. Mice were culled 2 hr (+/- 9 min) after the last dosing.

Animals were housed in sex-matched littermate groups of between two and five animals per cage in neutral temperature environment (21° ± 1°C), with a relative humidity of 55–65%, on a 12:12 hr photoperiod, and were provided food and water ad libitum. All animal studies were ethically reviewed and carried out in accordance with the Animals (Scientific Procedures) Act 1986 as well as the GSK Policy on the Care, Welfare and Treatment of Animals, and were performed in agreement with the guidelines from Directive 2010/63/EU of the European Parliament on the protection of animals used for scientific purposes. All animal studies and breeding were approved by the University of Dundee ethical review committee, and further subjected to approved study plans by the Named Veterinary Surgeon and Compliance Officer and performed under a UK Home Office project license in agreement with the Animal Scientific Procedures Act (ASPA, 1986).

Sample collection

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Mice were terminally anesthetised with an intraperitoneal injection of pentobarbital sodium (Euthatal, Merial) then trans-cardially perfused with DPBS (Gibco, 14190–094) to remove blood. Tissues were collected and either snap frozen in liquid nitrogen and stored at −80°C for later biochemical analyses or processed by overnight immersion in freshly prepared fixative: 3.7% Paraformaldehyde (Sigma, P6148), 200 mM HEPES, pH=7.00. The next day, fixed tissues were washed three times in DPBS, and immersed in a sucrose 30% (w/v) solution containing 0.04% sodium azide until they sank at the bottom of the tube. Samples were stored at 4°C in that sucrose solution until further processing.

Immunolabeling of brain free-floating sections

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The brain was frozen-sectioned axially using a sledge microtome (Leica, SM2010R), and 50-µm-thick sections were stored in PBS at 4°C until further treatment. Free-floating sections were permeabilised using DPBS (Gibco, 14190–094) containing 0.3% Triton X-100 (Sigma Aldrich, T8787) three times for 5 min. Sections were then blocked for 1 hr in blocking solution (DPBS containing 10% goat serum (Sigma Aldrich, G9023), and 0.3% Triton X-100). Primary antibody incubation was performed overnight in blocking solution containing one of the following antibodies: Anti-Tyrosine Hydroxylase (1/1000, Millipore, AB152), Anti-Iba-1 (1/1000, Wako, 019–19741), Anti Calbindin-D28k (1/1000, Swant, CB38), Anti-Glial Fibrillary Acidic Protein (1/1000, Millipore, MAB360). The next day, sections were washed two times for 8 min in DPBS containing 0.3% Triton X100 and then incubated for 1 hr in blocking solution containing the secondary antibody (1/200, Invitrogen P10994 Goat anti-Rabbit IgG (H+L) Cross-Adsorbed Secondary Antibody, Pacific Blue, or Invitrogen P31582 Goat anti-Mouse IgG (H+L) Cross-Adsorbed Secondary Antibody, Pacific Blue). Sections were then washed two times for 8 min in DPBS containing 0.3% Triton X100 and mounted on slides (Leica Surgipath X-tra Adhesive, 3800202) using Vectashield Antifade Mounting Medium (Vector Laboratories, H-1000) and sealed with nail polish.

Tissue section and immunostaining

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Tissues were embedded in an O.C.T. compound matrix (Scigen, 4586), frozen and sectioned with a cryostat (Leica CM1860UV). Twelve microns sections were placed on slides (Leica Surgipath X-tra Adhesive, 3800202), and then air dried and kept at −80°C until further processing. Sections were thawed at room temperature and washed three times for 5 min in DPBS (Gibco, 14190–094). Sections were then counterstained for 5 min with Hoechst 33342 (1μg/mL, Thermo Scientific, 62249). Slides were mounted using Vectashield Antifade Mounting Medium (Vector Laboratories, H-1000) and high-precision cover glasses (No. 1.5H, Marienfeld, 0107222) and sealed with transparent nail polish.

Tissue confocal microscopy

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Confocal micrographs were obtained by uniform random sampling using either a Zeiss LSM880 with Airyscan, or a Zeiss 710 laser scanning confocal microscope (Plan-Apochromat 63x/1.4 Oil DIC M27) using the optimal parameters for acquisition (Nyquist). 10–15 images were acquired per sample, depending on the tissue, by an experimenter blind to all conditions. High-resolution, representative images were obtained using the Super Resolution mode of the Zeiss LSM880 with Airyscan.

Quantitation of mitophagy and autophagy in vivo

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Quantification of mitophagy and autophagy was carried out on at least 10 pictures per sample. Images were processed with Volocity Software (version 6.3, Perkin-Elmer). Images were first filtered using a fine filter to suppress noise. Tissue was detected by thresholding the Green channel. For the immunolabelings in the brain (TH, Iba1, Calbindin D-28k, and GFAP), each cell population of interest was detected by thresholding the Pacific Blue labelled channel. A ratio image of the Red/Green channels was then created for each image.

For the mito-QC reporter, mitolysosomes were then detected by thresholding the ratio channel as objects with a high Red/Green ratio value within the tissue/cell population of interest. The same ratio channel threshold was used per organ/set of experiments. To avoid the detection of unspecific high ratio pixels in the areas of low reporter expression, a second red threshold was applied to these high ratio pixels. This double thresholding method provides a reliable detection of mitolysosomes as structures with a high Red/Green ratio value and a high Red intensity value.

For the general autophagy reporter, high-intensity red pixels were detected by thresholding the red channel within the tissue/cell population of interest. The same red channel threshold was used per organ/set of experiments. Autophagosomes and autolysosomes were then differentiated by thresholding the high-intensity red pixels depending on their Red/Green ratio channel value. Pixels with a low Red/Green ratio were considered as autophagosomes, whereas pixels with a high Red/Green ratio were considered as autolysosomes. The same ratio channel threshold was used per organ/set of experiments. Representative 3D Isosurface Rendering were generated using the Imaris software (Bitplane, version 8.1.2).

Filipin staining

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Frozen fixed tissue sections were washed in PBS to remove any excess O.C.T compound (Scigen, 4586) excess. Sections were then incubated for 2 hr at room temperature with filipin (200 μg/mL; Sigma-Aldrich, F9765) and then washed twice in PBS. Tissue sections were mounted using Vectashield Antifade Mounting Medium (Vector Laboratories, H-1000) and sealed with nail polish. High-resolution, representative images were obtained using the Super Resolution mode of the Zeiss LSM880 with Airyscan (Plan-Apochromat 63x/1.4 Oil DIC M27).

Western blotting

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Frozen tissue was homogenised with a Cellcrusher (Cellcrusher, Cork, Ireland) tissue pulveriser. Approximately 20–30 mg of pulverised tissue were then lysed on ice for 30 min with (10 µL/mg tissue) of RIPA buffer [50 mM Tris–HCl pH 8, 150 mM NaCl, 1 mM EDTA, 1% NP-40, 1% Na-deoxycholate, 0.1% SDS, and cOmplete protease inhibitor cocktail (Roche, Basel, Switzerland)], phosphatase inhibitor cocktail (1.15 mM sodium molybdate, 4 mM sodium tartrate dihydrate, 10 mM β-glycerophosphoric acid disodium salt pentahydrate, 1 mM sodium fluoride, and 1 mM activated sodium orthovanadate), and 10 mM DTT.

For culture cells, cells were washed twice with DPBS before being lysed on ice for 10 min (60 uL per 2 ml of cell culture) with either RIPA or IP lysis buffer (50 mM HEPES pH 7.4, 150 mM NaCl, 1 mM EDTA, 10% glycerol, 0.5% NP40), cOmplete protease inhibitor cocktail (Roche, Basel, Switzerland), phosphatase inhibitor cocktail (1.15 mM sodium molybdate, 4 mM sodium tartrate dihydrate, 10 mM β-glycerophosphoric acid disodium salt pentahydrate, 1 mM sodium fluoride, and 1 mM activated sodium orthovanadate), and 10 mM DTT.

After lysis, the mixture was vortexed and centrifuged for 10 min at 4°C at 20,817xg. The supernatant was collected, and the protein concentration determined using the Pierce BCA protein assay kit (ThermoFisher Scientific, Waltham, MA, USA). For each sample, 20–25 µg of protein was separated on a NuPAGE 4–12% Bis-Tris gel (Life technologies, Carlsbad, CA, USA). Proteins were electroblotted to 0.45 µm PVDF membranes (Imobilon-P, Merck Millipore, IPVH00010; or Amersham Hybond, GE Healthcare Life Science, 10600023), and immunodetected using primary antibodies directed against phospho-Ser935 LRRK2 rabbit monoclonal (1/1000, MRC PPU Reagents and Services, UDD2), LRRK2 rabbit monoclonal (1/1000, MRC PPU Reagents and Services, UDD3), phospho-Rab10 (Thr73) rabbit monoclonal (1/1000, Abcam, ab230261), Rab10 mouse monoclonal (1/1000, nanoTools 0680–100/Rab10-605B11), recombinant Anti-Rab12 (phospho S106) rabbit antibody [MJF-R25-9] (1/1000, Abcam ab256487), Total Rab12 sheep antibody (1 μg/mL, MRC PPU Reagents and Services, SA227), PGC-1α mouse monoclonal (4C1.3) (1/1000, Millipore, ST1202), PGC-1β mouse monoclonal (E-9) (1/500, Santa Cruz Biotechnology, sc-373771), TFAm mouse monoclonal [18G102B2E11] (1/1000, abcam, ab119684), HSP60 rabbit polyclonal (D307) (1/1000, Cell Signalling Technology, #4870S), TOMM20 rabbit polyclonal (FL-145) (1/1000, Santa Cruz Biotechnology, sc-11415), p62/SQSTM1 mouse monoclonal (2C11) (1/1000, Abnova, H00008878-M01), LC3A/B rabbit polyclonal (1/1000, Cell Signalling Technology, #4108S), phospho-ubiquitin (Ser65) rabbit monoclonal (E2J6T) (1/1000, Cell Signalling Technology, #62802S), Ubiquitin (P4D1) mouse monoclonal (1/1000, BioLegend, 646302), Parkin mouse monoclonal (1/2000, Santa-Cruz Biotechnology, sc-32282), α-Tubulin (11H10) Rabbit monoclonal antibody (1/10000, CST, 2125S), and β-Actin mouse monoclonal antibody (1/1000, Proteintech, 60008–1-Ig). All antibodies to LRRK2 were generated by MRC PPU Reagents and Services, University of Dundee (http://mrcppureagents.dundee.ac.uk).

Statistics

Data are represented as means ± SEM. Number of subjects are indicated in the respective figure legends. Statistical analyses were performed using a one-way analysis of variance (ANOVA) or two-way ANOVA followed by a Tukey HSD using RStudio version 1.1.1335 (R Studio Team, 2015). Statistical significance is displayed as * p< 0.05: ** p < 0.01, *** p<0.001, and **** p<0.0001.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files.

References

    1. Pfeffer SR
    (2018) LRRK2 and Rab GTPases
    Biochemical Society Transactions 46:1707–1712.
    https://doi.org/10.1042/BST20180470
  1. Software
    1. R Studio Team
    (2015)
    RStudio: Integrated Development for R
    RStudio: Integrated Development for R.
  2. Data
    1. Singh F
    2. Ball G
    3. Ganley IG
    (authors) (2020)
    Semi-automated quantitation of macroautophagy with the auto-QC counter v1
    protocols.io.

Decision letter

  1. Suzanne R Pfeffer
    Senior and Reviewing Editor; Stanford University School of Medicine, United States

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

[Editors' note: this paper was reviewed by Review Commons.]

Acceptance summary:

The autophagic turnover of mitochondria is termed mitophagy. This study provides the first in vivo evidence that pathogenic, Parkinson's disease-associated LRRK2 kinase directly impairs basal mitophagy, and demonstrates that pharmacological inhibition of LRRK2 is a rational mitophagy-rescue approach and potential Parkinson's disease therapy.

https://doi.org/10.7554/eLife.67604.sa1

Author response

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

In this manuscript, Singh et al., have directed their scientific inquiry towards understanding the role of LRRK2 (Leucine Rich Repeat Kinase 2) in mediating mitophagy, a process of clearing damaged mitochondria by autophagosomes. The discovery of PINK1 and PARK2 as Parkinson's Disease (PD) – relevant genes, has led to a significant amount of interest in delineating the role of PINK1/Parkin in mitophagy, especially induced by toxins including CCCP. However, the role of PINK1/Parkin in basal mitophagy, not induced by toxins, has been unclear. Recently, LRRK2 has emerged as a potential modulator of mitophagy. In the manuscript, the authors study the impact of LRRK2 on basal mitophagy using three mouse genotypes: WT, KO, and the pathogenic G2019S LRRK2 variant with increased kinase activity. While similar studies have been conducted on fibroblasts, PD patient-derived tissues, etc, this is the first study to recapitulate the role of G2019S LRRK2 in suppressing mitophagy in vivo. Each genotype is also engineered with a mito-QC or an auto-QC reporter at a specific nuclear locus in order to differentiate between mitochondria or autophagosomes trafficked to lysosomes for degradation, vs cytoplasmic organelles, respectively. These mouse models have been already well established by this group. Using these models, the authors have shown that the number of mitolysosomes is lower in the overactive G2019S variant and higher in the LRRK2 KO, suggesting that mitophagy is inversely correlated with LRRK2 kinase activity. After establishing these results in MEFs, the authors proceed to confirm this phenotype in different mice tissues, including four brain regions (only dopaminergic neurons and microglia show significant changes in mitophagy based on genotype), lungs, and kidneys. They proceed to test a LRRK2-specific kinase inhibitor that is CNS penetrant, GSK3357679A (GSK), and report the rescue of mitolysosomal number in brain and lung tissue, but not kidney cells of the G2019S variant. They also employ immunoblotting for the detection of LRRK2 self-phosphorylation, and Rab10 substrate phosphorylation as means of indirectly confirming the phenotypes of the mouse models and the inhibition of LRRK2 kinase activity by GSK.

While the results presented are interesting, the study is largely descriptive and does not provide mechanistic insight into mitophagic vs autophagic phenotypes, nor tissue selective data. This is a real limitation to enthusiasm. What is provided is generally rigorously performed. In addition, an examination of LRRK2 expression across tissue types and cell types, as well as markers other than Rab10 would have been informative. It is promising to note that LRRK2 kinase activity inhibition could be a potential therapeutic target. However, further analysis would be required to confirm the lack of off-target or long-term effects of GSK administration – which compound has off-target effects MLi2 or the GSK, for example. How does one explain the effects of MLi2 on mitophagy in LRRK2 KO cells? There are additional concerns that need to be addressed. The various suggestions for improving the manuscript are listed below.

We thank the reviewer for their careful and considered review. They have raised important points and the suggestions below, which have tried to address, give an important mechanistic insight that was lacking from the original version of the manuscript.

Major comments:

• In Figures 1C, 1H, and S1, why has the percentage of mitophagic cells been calculated as opposed to the number of mitolysosomes per cell, while in Figure 1F the number of autolosysomes per cell is presented? It is also unclear how mitophagic cells are selected – what is the specific cutoff for the number of mitolysosomes in each cell to qualify as "mitophagic cell"? Please report the mitolysosomes per cell, as that provides crucial information regarding increased mitophagy within each cell and not just within a population of cells. It will also maintain consistency of representation in other figures (number of mitolysosomes quantified by area and number of mitolysosomes per cell body). If it is not possible to report it, please include an explanation.

We apologise for the lack of consistency here between the reporters in terms of quantitation and have now displayed data for both as a percentage of mitophagic and autophagic cells. The reason for this is that in the primary mito-QC MEFs (but not auto-QC) we saw small increases in mitophagy after each passage, which were unform across all genotypes/treatments. However, as the rates of basal mitophagy are relatively low, when means were compared between individual experiments this reduced the significance. We have added the following to the description in the Methods section:

Line 488: “Note, in primary MEFs we observed heterogeneity between cells and observed changes in mitophagy over increasing passages, which were uniform across Lrrk2 genotypes. […] Therefore, due to the heterogeneity of the primary MEFs and passage, representing the data in percentage of mitophagic cells allowed us to better compare data sets.”

• Line 430: "GSK had no effect on mitophagy levels in the lungs of LRRK2 KO mice (Figure 4G)". The statement is not consistent with the reported data as Figure 4G only shows WT and G2019S LRRK2 lungs, and not LRRK2 KO. Data not shown?

The quantitation for KO mitophagy and GSK is shown in the new Figure 6F and we will ensure this is clearly stated in the text to avoid confusion:

Line 355: “GSK3357679A had no effect on mitophagy levels in the lungs of LRRK2 KO mice (Figure 6F).”

• The authors report that MLi-2, a more potent LRRK2 inhibitor than GSK, results in decreased mitophagy at higher concentrations and note that the LRRK2-independent effects of MLi-2 on mitophagy. It raises the question whether GSK has similar side-effects as well? Are there much higher concentrations of GSK which are detrimental to the effect of mitophagy due to over-inhibition of LRRK2 kinase activity? Also, are there adverse effects of GSK administration beyond 36 hours? How will this translate to the potential use of GSK as a therapeutic tool? More experimentation comparing the two is warranted. Also, if conclusions are to be drawn/mentioned from MLi2, then the data should be present in the body of the manuscript and not relegated to supplemental data.

We would like to clarify that there are two ‘GSK’ compounds here – GS2578215 (a selective cellular tool LRRK2 benzamide compound – Reith et al., 2012) and the novel structurally distinct GSK3357679A that is more potent and selective (Ding et al., in prep). We apologise if were not clear in the text, as the potency of the novel GSK3357679A is similar to that of MLi-2, and using a 50-fold higher concentration (compared to MLi-2) no side-effects were observed in the LRRK2 KO cells (Figure 1). Some confusion may have arisen due the use of the previously published and less potent GSK2578215A in the same figure as MLi-2 (S1). We have clarified and simplified the message in the text (as shown below). Our aim in this work was not to provide a direct comparison between MLi-2 and GSK3357679A, but rather show that other LRRK2 inhibitors also cause increased mitophagy – and that the specific compound used for the in vivo studies gave results similar to other LRRK2 inhibitors in the cell-based assay. In terms of in vivo tolerability profile of GSK3357679A in rodents, we have bid orally dosed GSK3357679A for up to 14 days with no adverse effects (Ding et al., in prep). We currently have no data beyond 14 days bid oral dosing in mice, but have no reason to anticipate any adverse effects. The 36 hour dosing duration used for the mitophagy work reported here was selected solely in consideration of animal use ethics – as we observed the effect of compound on mitophagy within this relatively short dosing window.

Line 136: “To further support a role for LRRK2 kinase activity in negatively regulating basal mitophagy we utilised two additional and structurally distinct tool LRRK2 kinase inhibitors, GSK2578215A 26 and MLi-2 27, in primary mito-QC MEFs. […] Thus, genetically and chemically, the data show that LRRK2 inhibition enhances basal mitophagy in cells and in these assays, GSK3357679A displayed a superior performance compared to other available LRRK2 kinase inhibitors.”

• What is the mechanism of GSK in inducing mitophagy? The authors have previously reported that basal mitophagy does not require PINK1/Parkin (McWilliams et al., 2018). Is the increased mitophagy by GSK dependent on PINK1/Parkin? Recently Bonello et al., 2019 have reported that LRRK2 impairs basal mitophagy in a Parkin-dependent manner, that can be rescued by the LRRK2 kinase inhibitor LRRK2-IN-1. The comparison of the effect of GSK on mitolysosomes between WT, Pink1 KO, Parkin KO, and PINK1 KO + LRRK2 G2019S variant would be insightful in dissecting the mode of action of GSK and contribute towards the understanding of the players involved in basal (non-toxin induced) mitophagy.

We thank the reviewer for raising this point on mechanism, which is something we are committed to working out. While it will be beyond the scope of the current manuscript to work out the complete mechanism of LRRK2-mediated mitophagy, we have addressed the important point raised by the Reviewer. Using previously generated primary PINK1 KO mito-QC MEFs (McWilliams et al., 2018) we have shown that the GSK3357679A-induced mitophagy is independent of PINK1 and we detected no changes in phosphoubiquitin levels due to LRRK2 inhibition. These data are shown in a new Figure 2G-I. Additionally, we carried out the classical Parkin-dependent assays and found that LRRK2 inhibition had no effect on this (new Figure S2D-F). The Bonello et al., paper is an interesting manuscript and we reference it in our work here – however, the mechanistic aspect of this work involves Parkin overexpression and thus we feel that they are examining a different pathway. In summary, we feel that the work here is monitoring a PINK1 (and hence Parkin)-independent pathway.

• Additionally, the fact that PINK1/Parkin was not found essential for basal mitophagy in mice (McWilliams et al., 2018) and Drosophila (Lee et al., 2018), but is essential in human cells (Bonello et al., 2019) and is not trivial when it comes to the clinical relevance of GSK as a pharmacological inhibitor of LRRK2 to induce mitophagy and should be addressed in the Discussion section. In addition, this section will greatly benefit from discussing the opposing data and its ramifications in the area of LRRK2-induced basal mitophagy.

We would like to point out that PINK1/Parkin mitophagy is not essential for all pathways in human cells – indeed we have previous published that mitophagy can be induced independently of Parkin in primary human PD patient fibroblasts (and other human-derived cell lines, Allen et al. 2013, PMID: 24176932). There has also been an additional manuscript published showing that basal mitophagy occurs independently of PINK1 in Zebrafish (Wrighton et al., 2021, PMID: 33536245). Also, from the work by Sliter et al. looking at mitophagy induced in vivo following exhaustive exercise, though the mitophagy that was induced was dependent on PINK1, the basal level of mitophagy was not – hence similar to our reported results. We do not feel our results conflict with the vast majority of work, nor do we feel it controversial to show that there are mitophagy pathways that are independent of PINK1/Parkin. Regardless of any PINK1/Parkin involvement, we do not think this takes away from the potential that LRRK2-mediated modulation of mitophagy may contribute to disease risk and potential treatment. We have added to the Discussion section, as noted here.

Line 369: “PINK1 and Parkin-mediated mitophagy is a significant pathway with respect to PD and so it was important to confirm if this was also occurring here. […] Regardless, if loss of stress-induced PINK1/Parkin-dependent mitophagy can lead to PD, then it is reasonable to assume that loss of LRRK2-regulated basal mitophagy could also contribute”.

• Brain Rab 10?

We and other independent groups at our institution have been unable to detect high levels of phosphorylated Rab10 in brain extracts. We cannot fully explain this, but it may be possible that a Rab10 phosphatase is highly active in this region. However, we have now found that another LRRK2 substrate, Rab12, is readily phosphorylated in brain and provides an additional marker for LRRK2 activity. These new data is included in a new Figure 5.

• While this manuscript focuses on mitophagy, it fails to address any potential effects of LRRK2 on mitochondrial biogenesis. How is the total mitochondrial number and mitochondrial biogenesis affected by the LRRK2 genotypes and GSK application? For example, is an increase or decrease in mitophagy compensated by a concomitant decrease or increase in mitochondrial biogenesis, or does it remain the same? Tools such as MitoTimer used in conjunction with mitoQC and autoQC would yield significant information regarding the biological mechanisms underlying LRRK2's effect on mitochondrial homeostasis. Not required, just a mechanistic suggestion.

The Reviewer raises a very important point here and we thank them for this suggestion. We believe the overall level of mitophagy under basal conditions is relatively low compared to the total mitochondrial pool, however over time this could lead to significant differences in mitochondrial number if biogenesis is not compensated for. To look at mitochondrial content and biogenesis markers, we probed brain tissue lysates in the different Lrrk2 genotypes treated with/without GSK3357679A. Surprisingly, we found that LRRK2 inhibition did indeed trigger upregulation of mitochondrial biogenesis markers (PGC1B and TFAM). The new data is shown in Figure 5.

The text has been changed to discuss this.

Line 301: “Of potential relevance, we found that the mitochondrial biogenesis marker PGC-1α was increased in the brains of G2019S mice. […] While further work will be needed to validate this, a careful balance between mitochondrial turnover and biogenesis has been shown to occur previously 43.”

To further look at mitochondrial function, we examined their ultrastructure by TEM and also performed high-resolution respirometry in isolated MEFs, via the Oroboros Oxygraph-2k. LRRK2 inhibition did not globally alter mitochondrial function. This new data is shown in Figure S2I and H and discussed in the text.

Line 190: “…we noticed no obvious changes to mitochondrial morphology and ultrastructure, as observed using TEM (Figure S2G). Secondly, using high resolution respirometry, we measured mitochondrial oxygen consumption. […] However, given that the fraction of mitochondria targeted for mitophagy is likely small compared to the total pool, we cannot rule out that this population is functionally impaired.”

Minor comments:

• In Figure S1, what is the effect of DFP on autolysosomal number? Similarly, what is the effect of serum starvation on mitophagy?

We have these data and apologise for their omission – LRRK2 genotypes do not alter mitophagy/autophagy levels under these stimuli. These data are now included in the revised Figure S1.

• Line 305: please expand PK/PD.

Expanded to Pharmacokinetics/pharmacodynamics.

• Line 424: Figures 4C and 4D show dopaminergic neurons and not lungs as mentioned in the text. Figure legends mention that lungs are shown in 4G and 4H.

• In-text citation of Figure 4H is missing.

• Figure S1D, p-value indications are missing in the figure, although mentioned in the figure legend.

Apologies – we have corrected these mistakes/omissions in the text.

• Line 430: "Consistent with the genetics, in the kidney we found that GSK had a minimal effect on mitophagy despite this organ exhibiting robust LRRK2 inhibition". It is not clear how the lack of increase in mitolysosome number in kidneys is consistent with genetics. Please explain or rephrase.

We have rephrased the text as we agree it is confusing – we were referring to the genetics as in the LRRK2 KO animals.

Line 617: “Consistent with KO mice, in the kidney we found that GSK3357679A had a minimal effect on mitophagy despite this organ exhibiting robust LRRK2 inhibition (compare Figure 4C and D with S6B and C).”

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

In this paper, authors provide evidences for a potential role of LRRK2 in the regulation of basal mitophagy in different tissues. LRRK2 is a protein kinase often mutated in PD. One of the most common is the G2019S kinase- gain of function mutation. Using mitophagy (mito-QC) and autophagy (auto-QC) reporter mice, authors demonstrate that basal mitophagy is regulated by LRRK2 kinase activity in vitro and ex vivo. In particular, mitophagy is downregulated in MEFs deriving from G2019S transgenic mice, and this has been confirmed ex vivo in specific neuronal cells population, and in the lungs. They also demonstrate that genetic ablation of LRRK2 or chemical inhibition of its enzymatic activity (with a highly specific kinase inhibitor named GSK3357679A-unpublished) can rescue the mitophagy defects observed in LRRK2 G2019S mice. Autophagy levels measured in cells and tissues are unaffected between the different genotypes. This finding led the authors to conclude that LRRK2 kinase activity acts specifically on basal mitophagy, rather than autophagy in general.

We thank the Reviewer for their comprehensive analysis of this manuscript and support for our findings. As described below, we have tried to address all the comments to add important mechanistic data.

Major comments:

Overall, the results of the paper are convincing and clearly demonstrate a role of LRRK2 kinase activity in the regulation of basal mitophagy. Data and methods are very well described and the number of replicates and statistical analysis is adequate.

It is however unexplored how LRRK2 regulates mitophagy. As such, this is a descriptive work that shows for the first time a role for LRRK2 in mitochondrial quality control, but does not propose a molecular mechanism for this very intriguing finding.

The use of the mito-QC probe is an extremely valuable tool to measure basal mitophagy in vivo and in vitro, but should be ideally paralleled by other approaches. Decreased number of red mitochondria in mito-QC expressing cells/tissue can be the result of delayed acidification, which does not necessarily correlates to altered mitochondrial quality control. For this reason, we strongly advice measuring the overall effect on mitochondrial mass/content (see suggested additional experiments) and/or direct interaction between autophagic components and mitochondria.

We have carried out additional mito-QC independent experiments, as described below.

The effect on basal mitophagy upon GSK3357679A treatment is very interesting, and might hold therapeutic opportunities: are these mitochondria that are targeted to mitophagy dysfunctional? In other words, is this the result of mitochondrial quality control, or does it affect overall mitochondria turnover (i.e. functional mitochondria as well)? This is very important to clarify. Enhanced mitochondrial degradation can be counterproductive, unless specifically targeted to dysfunctional mitochondria and/or paralleled by increased mitochondrial biogenesis.

We thank the reviewer for this important comment and have performed additional work to look at mitochondrial function and biogenesis. Consistent with the small levels of mitophagy occurring (relative to levels that we observe following stimulation with DFP, CCCP etc.), we were unable to detect global changes in mitochondrial morphology (EM) or respiration (Oxygraph) following LRRK2 inhibition. These data are shown in a new Figure S2G-I and described in the text.

Line 190: “…we noticed no obvious changes to mitochondrial morphology and ultrastructure, as observed using TEM (Figure S2G). Secondly, using high resolution respirometry, we measured mitochondrial oxygen consumption. […] However, given that the fraction of mitochondria targeted for mitophagy is likely small compared to the total pool, we cannot rule out that this population is functionally impaired.”

We also blotted for mitochondrial content in brain tissue and again, consistent with small changes in mitophagy, we did not detect a large change in following LRRK2 inhibition at this timepoint, though the level of mitochondrial markers was less in KO animals, which is consistent with the increased mitophagy in this tissue. These data are in a new Figure 5A and C. We also followed up on the mitochondrial biogenesis aspect, and we thank the Reviewer for suggesting these experiments as they yielded relevant results that showed upregulation of signalling following LRRK2 inhibition in the brain. The new data is shown in Figure 5A and C.

Additional text has been added to discuss this:

Line 301 “Of potential relevance, we found that the mitochondrial biogenesis marker PGC-1α was increased in the brains of G2019S mice. […] While further work will be needed to validate this, a careful balance between mitochondrial turnover and biogenesis has been shown to occur previously 43.”

Details on the characterization of LRRK2 kinase inhibitor GSK3357679A are not available. Data are unpublished, and the manuscript is in preparation (ref: Ding., et al.). It is therefore difficult to evaluate whether GSK3357679A is doing what the authors claim, in terms of LRRK2 kinase activity-inhibition. Is this work currently under revision? Authors are proposing a back to back? Would it be possible to see the results on the characterization of this novel inhibitor?

We also appreciate the comments regarding the Ding et al., manuscript describing the characterisations of the novel GSK LRRK2 inhibitor GSK3357679A. This is a separate GSK manuscript, outside of our lab, and we had assumed this manuscript would be available at the time of review. However, detailed characterisation of the properties of GSK3357679A are now in the public domain (https://www.biorxiv.org/content/10.1101/2021.05.21.445132v2), as referenced in the manuscript. The molecular structure of GSK3357679A will be reported in the Ding et al. medicinal chemistry paper that is in the final stages of approval at GSK. It is our hope that this data will shortly be available (in time for publication of this work). Following public disclosure of the structure of GSK3357679A it is intended to make this compound openly available to the research community via a third-party chemical supply company.

Suggested additional experiments and specific comments:

• Only one approach (mito-QC) has been used to measure mitophagy. It would be valuable to integrate the obtained results with additional approaches. For example by evaluating steady state levels of mitochondrial resident proteins as read out of mitochondrial content. Interaction between autophagy marker LC3 II and mitochondria via IF is also a desirable approach to investigate autophagy of mitochondria. This is doable at least for the in vitro part of the paper using MEFs cells.

The mito-QC assay is the most sensitive one we have in terms of monitoring mitophagy and can easily detect low levels of mitophagy, such as basal mitophagy, that could be missed using measurements of the total mitochondrial pool. However, the Reviewer makes an important and valid point to use alternate methods. We have now measured the co-localisation of mitochondrially localised ATPB and LC3 (our tandem reporter version) and did indeed find a small degree of co-localisation between mitochondria and autophagosomes as well as autolysosomes, which is consistent with the mito-QC data. We also employed EM and found that LRRK2 inhibition resulted in a significant fold-increase in mitolysosomes. These data confirm mitophagy and help rule out alternate pathways such as MDVs. These data have been incorporated into a new Figure 2A-C and E-F.

• Autophagy levels measured in cells and tissues are unaffected between the different genotypes. This finding led the authors to conclude that LRRK2 kinase activity acts specifically on basal mitophagy, rather than autophagy in general. It is important to confirm these results by Western Blot analysis of LC3 II protein. As suggested by the authors, it is possible that a block in mitophagy will have little influence on the total autophagic levels. However, it is also possible, that LRRK2 regulates mitochondrial quality control via autophagy-independent mechanisms such as those that are directly regulated by endosome-lysosome interaction (MDV or Rab5-dependent). This possibility could explain why LRRK2 regulates mitophagy without apparently impacting general autophagy.

This is an intriguing possibility that LRRK2 maybe regulating mitochondrial turnover via an autophagy-independent mechanism. In addition to the EM data mentioned above that shows partially degraded mitochondria in lysosomes, we also measured the effects of LRRK2 inhibition on mitophagy in ATG5 KO MEFs (From the Mizushima Lab). Loss of ATG5 blocked the increase in mitophagy, implying LRRK2-dependent mitophagy requires the conventional autophagy machinery. The new data are shown in Figure 2D:

• Mitophagy does not seem to be negatively affected in TH neurons of G2019S mice (Figure 2C): although a trend toward reduced mitophagy is observed, this is not significant. We suggest to rephrase "….., mitophagy appeared reduced in DA neurons of LRRK2 G2019S KI mice compared to WT (Figure 2A and C). This was similar to our earlier observations in MEFs and showed that the presence of LRRK2 can impact mitophagy in this clinically relevant population of neurons within the midbrain." The sentence is inaccurate; TH neurons from G2019S mice do not show decreased mitophagy. It is actually worrisome that LRRK2 gain-of-function mutant impairs mitophagy in MEFs cells but does not seem to have an effect on disease-relevant neurons (i.e. TH positive cells). We suggest consolidating this trend with additional biological replicates (strongly advisable), or rephrasing the paragraph accordingly.

The Reviewer is of course correct here and we apologise for the confusion, we simply wanted to state that there is a downward trend, which is clearly shown – but this is not significant. We have not increased biological replicates, given that a similar experiment was already performed with 10 mice per condition (as opposed to 9 for this one, new Figure 3 A and C). The data in the previous Figure 4D, with 10 mice per condition does show a significant genotype effect using a 2-way ANOVA – the genotype significance was unfortunately omitted from the original Figure 4D and will be shown and discussed in the revised manuscript:

Line 213 “Basal mitophagy was significantly enhanced in the LRRK2 KO neurons compared to WT, and although not statistically significant, mitophagy appeared reduced in DA neurons of LRRK2 G2019S KI mice compared to WT (Figure 3A and C). While we cannot say that mitophagy is significantly impaired in the G2019S DA neurons from this set of experiments using nine individual mice, we do however find a significant mitophagy reduction in G2019S DA neurons in a later set of experiments, with ten mice per condition (Figure 6A and B)”.

• In the analyzed mutant cells (KO and G2019S), stress (DFP)-induced mitophagy is comparable across all genotypes, which led the authors to conclude that LRRK2 predominantly influences basal mitophagy. This sounds a bit of an overstatement considering the peculiar way by which DFP induces mitophagy. DFP does not affect ΔΨm, and it appears to trigger mitophagy via PINK1/Parkin-independent mechanism. To clarify this point it would be helpful to repeat the experiment in MEFs cells using CCCP or valinomycin.

This a very good point and we analysed the classical Parkin dependent mitophagy pathway in MEFs using CCCP. LRRK2 inhibition did not alter mitophagy under any of these conditions and additionally the LRRK2-depednent mitophagy was independent of PINK1. These new data are shown in Figure S2D-F and Figure 2G-I respectively.

• In the description of figure 4C-D the authors claim that "In DA neurons of the SNpc, we found that treatment with GSK3357679A increased mitophagy in both WT and G2019S KI mice" however the figure shows that the increase of mitophagy in G2019S mice treated with GSK335779A is not significant compared to the vehicle-treated, and that should be clarified in the text. Overall, it seems that in TH neurons of G2019S mice, mitophagy is not clearly affected.

Again, apologies for the confusion and the text will be rephrased here as mentioned above. There is indeed a significant difference, via a 2-way ANOVA, in WT vs G2019S mitophagy in this experiment (but unfortunately we only showed the GSK3357679A significance in the original figure). This is displayed in the new Figure 6A and B.

Minor comments:

• Quantification of mitophagy is differently expressed throughout the paper. For example:

– In MEFs, it is expressed as Mitophagic cells %. Considering that the mito-QC Counter should report an increase in the total number of mitolysosomes, what are the parameters that define a mitophagic cell? Cells with at least 1 red (or more?)-only dots? This should be clarified.

– In microglia, it is expressed as Mitolysosomes per cell body

– In all the remaining tissues, it is presented as Mitolysosomes per area

It is advisable to present these data in a consistent way, if possible.

We apologise for the lack of clarity/consistency here – we have unified quantitation values in MEFs as percentage of mitophagic/autophagic cells and state in the Methods as to our reasoning behind this:

Line 487: “Note, in primary MEFs we observed heterogeneity between cells and observed changes in mitophagy over increasing passages, which were uniform across Lrrk2 genotypes. […] Therefore, due to the heterogeneity of the primary MEFs and passage, representing the data in percentage of mitophagic cells allowed us to better compare data sets.”

For microglia, we found that their numbers were increased in G2019S cortex, hence for this case we normalised to cell number. We have better explained this in the text.

Line 234: “when mitophagy quantitation was normalised for cell number (mitolysosomes per Iba1 positive cell body per field), we found a significant decrease in basal mitophagy in G2019S microglia compared to WT, as well as an increase in mitophagy levels in KO cells (Figure 3H)”.

• In Figure 4D the description in the text states that "the vehicle dosed G2019S group displayed significantly lower mitophagy compared to the vehicle- dosed WTs" The statement seems inaccurate.

As above, we have included the omitted 2-way ANOVA significance on genotype.

• typos: lane 66 Figure 1D instead of 1C.

This has been corrected.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

The authors investigated the role of LRRK2, a protein kinase frequently mutated in Parkinson's disease (PD), on mitophagy in vivo. Using mitophagy and autophagy reporter mice, bearing either knockout of LRRK2 or expressing the pathogenic kinase-activating G2019S LRRK2 mutation, the authors found that basal mitophagy was specifically altered in clinically relevant cells and tissues. Basal mitophagy inversely correlates with LRRK2 kinase activity in vivo, and use of distinct LRRK2 kinase inhibitors in cells increased basal mitophagy. Indeed, CNS penetrant LRRK2 kinase inhibitor, GSK3357679A, rescued the mitophagy defects observed in LRRK2 G2019S mice. This study provides in vivo evidence that pathogenic LRRK2 directly impairs basal mitophagy, a process with strong links to idiopathic Parkinson's disease, and demonstrates that pharmacological inhibition of LRRK2 is a rational mitophagy-rescue approach and potential PD therapy.

We thank the Reviewer for all their work in constructively assessing our manuscript. As described below, we hope to have addressed all the comments in a satisfactory manner and in doing so have added clarifying mechanistic insights.

Major comments:

I suggest that the authors discuss following points more.

(1) The authors surmised that the failure of higher doses of MLi-2 to stimulate mitophagy is due to an off-target effect. Indeed, at 20 nM, MLi-2 inhibited mitophagy even in the LRRK2 KO cells (Figure S1D). Is it possible that TBK1 is inhibited by higher doses of MLi-2 and consequently mitophagy is decreased?

The Reviewer raises an interesting point and we have examined a previous in-house kinase screen on the specificity of MLi-2 (found here: http://www.kinase-screen.mrc.ac.uk/screening-compounds/672622 ). However, there was no identified inhibition of TBK1, even at high doses of MLi-2. Our main intention was to show that additional structurally distinct LRRK2 inhibitors also enhance mitophagy (which they do) – it is just that we found at high concentrations of MLi-2, there appeared to be an off-target effect. We have toned down the text as follows:

Line 136 “To further support a role for LRRK2 kinase activity in negatively regulating basal mitophagy we utilised two additional and structurally distinct tool LRRK2 kinase inhibitors, GSK2578215A 26 and MLi-2 27, in primary mito-QC MEFs. As with GSK3357679A, both these compounds were able to inhibit LRRK2 in cells and increase mitophagy (Figure S1D and E). We do note that at high concentrations, MLi2 failed to stimulate mitophagy and this may be due to an off-target effect, as at 20 nM it also inhibited mitophagy in the LRRK2 KO cells (Figure S1D). Thus, genetically and chemically, the data show that LRRK2 inhibition enhances basal mitophagy in cells and in these assays, GSK3357679A displayed a superior performance compared to other available LRRK2 kinase inhibitors.”

(2) To use LRRK2 kinase inhibitor as a therapeutic drug against PD, it is important to suppress the cytotoxic effect derived from LRRK2 dysfunction. For example, if LRRK2 inhibition causes an abnormal phenotype in lung, it is important to avoid such abnormalities. In this work, enlarged lamellar bodies were observed in the G2019S mice when GSK3357679A elevated mitophagy levels to a value similar to the WT control (Figure 4G and 4H). Namely, when the mitophagy value is equivalent to WT mice, the lung phenotype looks similar to LRRK2 KO mice. If the authors fine-tuned the concentration of GSK3357679A, both the basal mitophagy and the pulmonary phenotype become similar to WT? Or else, the toxic phenotype in lung does not appear in patients with lrrk2 G2019K mutation? The authors need to discuss this topic to make their statement about LRRK2 inhibitor more convincing.

This is an important point and has been much discussed in the field following previous observations of the pulmonary phenotype. We included the mouse lung histopathology data to illustrate that GSK3357679A acts in a similar manner to other reported LRRK2 kinase inhibitors, in that it induces an increase in lamellar body density in type II pneumocytes in the lung in mice. Recent work though has found that extensive in vivo and ex vivo preclinical studies, funded by Michael J Fox Foundation (Baptista et al., 2020), failed to detect any effects of LRRK2 kinase inhibitors on lung function. Additionally, no deleterious effects on lung function have been reported for LRRK2 kinase inhibitors in clinical studies for Parkinson’s disease thus far. We have added this information to the discussion as follows:

Line 431: “As with other LRRK2 inhibitors, GSK3357679A also induced enlarged lamellar bodies in the lung and it is possible that this effect could limit the therapeutic approach of targeting LRRK2. However, it is important to note that extensive preclinical studies in vivo failed to detect any effects of LRRK2 inhibition on lung function 69 and likewise, no deleterious effects have been reported for LRRK2 kinase inhibitors in clinical studies for Parkinson’s disease thus far 70,71.”.

(3) page 21, line 424, "Figure 4C and 4D" should be "Figure 4G and 4E".

We apologise for these mistakes and they have been corrected in the revision.

(4) From great body of works in vitro, I agree that the LRRK2 pathogenic mutation (especially G2019S) is a kinase-activated mutation. On the other hand, no clear increase in either LRRK2 autophosphorylation or Rab10 phosphorylation was observed in lrrk2 G2019S KI mice (Figure 4A). Only Rab10 phosphorylation in kidney seems increase in lrrk2 G2019S KI mice. Is there any legitimate reason to explain these data?

Yes, this result does not follow published data showing increased kinase activity for the G2019S mutant and we cannot fully explain it. We speculate that a Rab10 phosphatase may be more active in some tissues, hence the increase in phosphorylation is not readily observed. However, we have now analysed an additional LRRK2 substrate, Rab12, and find its phosphorylation is increased in brain G2019S tissues vs WT – It is possible that specific Rab substrates are more sensitive to the G2019S mutation. We have included the new data in a revised Figure 5.

(5) The authors states that the loss of PINK1 or Parkin activity does not significantly alter basal mitophagy rates in vivo, and three papers are cited in the manuscript [Cell Metab (2018) and Open Biol (2018) by McWilliams et al., and JCB (2018) by Lee et al]. Indeed, from their own data using mito-QU mice, the authors have legitimate concerns about a current model.

However, contribution of PINK1 and Parkin to mitophagy in vivo is still controversial as rather conflicting results have been reported by other three papers [Cornelissen et al., (2018) Deficiency of parkin and PINK1 impairs age-dependent mitophagy in Drosophila. eLife 7; Sliter et al., (2018) Parkin and PINK1 mitigate STING-induced inflammation. Nature 561; Kim et al., (2019) Assessment of mitophagy in mt-Keima Drosophila revealed an essential role of the PINK1-Parkin pathway in mitophagy induction in vivo. FASEB J 33]. Even if these papers focused on aging- or mitochondrial stress-dependent mitophagy, and there were methodological differences (not mito-QC but mito-Keima) to monitor mitophagy, these papers are worth citing in the Discussion section.

This is an important point raised by the Reviewer and touched on by the other Reviewers. Firstly, we have confirmed that the LRRK2-dependent pathway observed here is independent of PINK1. Using previously generated primary PINK1 KO mito-QC MEFs (McWilliams et al., 2018) we have shown that the GSK3357679A-induced mitophagy is independent of PINK1 and we detected no changes in phosphoubiquitin levels due to LRRK2 inhibition. Additionally, we carried out the classical Parkin-dependent assays and found that LRRK2 inhibition had no effect on this. These data are shown in the new Figure 2G-I and S2D-F.

We do hope that we are not being controversial here (or previously). Our past work has shown that not all mitophagy pathways go through PINK1/Parkin – and here we propose that both dependent and independent pathways could contribute to mitochondrial dysfunction and PD. We do note that recently published work using mtKeima and a tandem mCherry-GFP reporter also found that basal mitophagy is independent of PINK1 in Zebrafish (Wrighton et al., 2021, PMID: 33536245). Also, the article by Lee et al., compared both mito-QC and mtKeima and did not find any role for PINK1 and Parkin under basal conditions. We think that the main point is that we and others have looked under basal conditions, whilst the “conflicting” papers mentioned have looked under stress conditions. We do not think we are being controversial to suggest multiple mitophagy pathways exists. Indeed, from the work by Sliter et al. looking at mitophagy following repeated exhaustive exercise, though the mitophagy that was induced was dependent on PINK1, the basal level of mitophagy was not – hence similar to our reported results! Regardless of any PINK1/Parkin involvement, we do not think this takes away from the potential that LRRK2-mediated modulation of mitophagy may contribute to disease risk and potential treatment. To note this, we have added to the Discussion section:

Line 369: “PINK1 and Parkin-mediated mitophagy is a significant pathway with respect to PD and so it was important to confirm if this was also occurring here. However, we found that loss of PINK1 (and hence a block in Parkin activation) did not impact mitophagy induced upon LRRK2 inhibition and nor did it alter the magnitude of Parkin-dependent mitophagy that occurs following mitochondrial depolarisation. This fits well with previous data generated by us and others, which demonstrates that loss of PINK1 or Parkin activity does not significantly alter basal mitophagy rates in vivo 17,18,46,47. We take this to mean that the PINK1/Parkin pathway drives mitophagy under distinct types of extreme mitochondrial stress, such as that caused during repeated exhaustive exercise 48, in contrast to the basally regulated LRRK2 pathway described here. Regardless, if loss of stress-induced PINK1/Parkin-dependent mitophagy can lead to PD, then it is reasonable to assume that loss of LRRK2-regulated basal mitophagy could also contribute.”

(6) Paper by Lee et al. (basal mitophagy is widespread in Drosophila but minimally affected by loss of pink1 or parkin. J. Cell Biol 2018) is duplicated as citation # 19 and 39.

Apologies, the duplication has been removed.

https://doi.org/10.7554/eLife.67604.sa2

Article and author information

Author details

  1. Francois Singh

    MRC Protein Phosphorylation and Ubiquitylation Unit, University of Dundee, Dundee, United Kingdom
    Contribution
    Conceptualization, Formal analysis, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1696-9815
  2. Alan R Prescott

    Dundee Imaging Facility, School of Life Sciences, University of Dundee, Dundee, United Kingdom
    Contribution
    Investigation, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0747-7317
  3. Philippa Rosewell

    MRC Protein Phosphorylation and Ubiquitylation Unit, University of Dundee, Dundee, United Kingdom
    Contribution
    Formal analysis, Investigation, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1399-8602
  4. Graeme Ball

    Dundee Imaging Facility, School of Life Sciences, University of Dundee, Dundee, United Kingdom
    Contribution
    Software, Methodology, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6526-2306
  5. Alastair D Reith

    Novel Human Genetics Research Unit, GlaxoSmithKline Pharmaceuticals R&D, Stevenage, United Kingdom
    Contribution
    Conceptualization, Formal analysis, Funding acquisition, Writing - review and editing
    Competing interests
    No competing interests declared
  6. Ian G Ganley

    MRC Protein Phosphorylation and Ubiquitylation Unit, University of Dundee, Dundee, United Kingdom
    Contribution
    Conceptualization, Resources, Formal analysis, Supervision, Funding acquisition, Investigation, Methodology, Writing - original draft, Project administration, Writing - review and editing
    For correspondence
    i.ganley@dundee.ac.uk
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1481-9407

Funding

Medical Research Council (MC_UU_00018/2)

  • Ian G Ganley

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We acknowledge Paul Appleton at the Dundee Imaging Facility, Dundee. The Zeiss LSM880 with Airyscan was supported by the ‘Wellcome Trust Multi-User Equipment Grant’ [208401/Z/17/Z]. We would also like to acknowledge Dr Jin-Feng Zhao and Dr Thomas McWilliams for their expert technical assistance. This work was funded by a grant from the Medical Research Council, UK (IGG; MC_UU_00018/2) and GlaxoSmithKline. Requests for provision of GSK3357679A should be directed to Alastair Reith (alastair.d.reith@gsk.com).

Ethics

Animal experimentation: All animal studies were ethically reviewed and carried out in accordance with Animals (Scientific Procedures) Act 1986 as well as the GSK Policy on the Care, Welfare and Treatment of Animals, and were performed in agreement with the guidelines from Directive 2010/63/EU of the European Parliament on the protection of animals used for scientific purposes. All animal studies and breeding were approved by the University of Dundee ethical review committee, and further subjected to approved study plans by the Named Veterinary Surgeon and Compliance Officer and performed under a UK Home Office project license in agreement with the Animal Scientific Procedures Act (ASPA, 1986).

Senior and Reviewing Editor

  1. Suzanne R Pfeffer, Stanford University School of Medicine, United States

Publication history

  1. Preprint posted: December 7, 2020 (view preprint)
  2. Received: February 17, 2021
  3. Accepted: June 30, 2021
  4. Version of Record published: August 3, 2021 (version 1)

Copyright

© 2021, Singh et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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