1. Neuroscience

Parkinson’s disease-associated PINK1 loss disrupts ensheathing glia and causes dopaminergic neuron synapse loss

  1. Lorenzo Ghezzi
  2. Sabine Kuenen
  3. Ulrike Pech
  4. Nils Schoovaerts
  5. Ayse Kilic
  6. Suresh Poovathingal
  7. Kristofer Davie
  8. Jochen Lamote
  9. Roman Praschberger  Is a corresponding author
  10. Patrik Verstreken  Is a corresponding author
  1. VIB-KU Leuven Center for Neuroscience, Belgium
  2. KU Leuven, Department of Neurosciences, Leuven Brain Institute, Belgium
  3. VIB-KU Leuven Center for Neuroscience, Single Cell and Microfluidics Expertise Unit, Belgium
  4. VIB-KU Leuven Center for Neuroscience, Single Cell Bioinformatics Unit, Belgium
  5. VIB Flow Core Leuven, VIB Technologies, Belgium
  6. Medical University of Innsbruck, Institute of Human Genetics, Austria
https://doi.org/10.7554/eLife.105386.3
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Cite this article
  1. Lorenzo Ghezzi
  2. Sabine Kuenen
  3. Ulrike Pech
  4. Nils Schoovaerts
  5. Ayse Kilic
  6. Suresh Poovathingal
  7. Kristofer Davie
  8. Jochen Lamote
  9. Roman Praschberger
  10. Patrik Verstreken
(2026)
Parkinson’s disease-associated PINK1 loss disrupts ensheathing glia and causes dopaminergic neuron synapse loss
eLife 14:RP105386.
https://doi.org/10.7554/eLife.105386.3
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eLife Assessment

This valuable study explores the role of Pink1 in regulating mitochondria-organelle contacts and glial function, advancing our understanding of the mechanisms underlying neurodegenerative diseases. The findings highlight key genes and cellular processes that are critical in maintaining neuronal health, with implications for glial biology and Parkinson's disease research. The methodology and data are solid. This work will be of significant interest to researchers in neuroscience, cell biology, and neurodegenerative diseases.

https://doi.org/10.7554/eLife.105386.3.sa0

Abstract

Parkinson’s disease (PD) is commonly associated with the loss of dopaminergic neurons in the substantia nigra, but many other cell types are affected even before neuron loss occurs. Recent studies have linked oligodendrocytes to early stages of PD, though their precise role is still unclear. PINK1 is mutated in familial PD, and through unbiased single-cell sequencing of the entire brain of Drosophila Pink1 models, we observed significant gene deregulation in ensheathing glia (EG), cells that share functional similarities with oligodendrocytes. We found that the loss of Pink1 leads to abnormalities in EG, similar to the reactive response of EG seen upon nerve injury. Using cell-type-specific transcriptomics, we identified deregulated genes in EG as potential functional modifiers. Specifically downregulating two trafficking factors in EG, Vps35 and Vps13, also mutated in PD, was sufficient to rescue neuronal function and protect against dopaminergic synapse loss. Our findings demonstrate that Pink1 loss in neurons triggers an injury-like response in EG, and that Pink1 loss in EG, in turn, disrupts neuronal function. Vesicle trafficking components, which may regulate membrane interactions between organelles in EG, seem to play a role in maintaining neuronal health and ultimately preventing dopaminergic synapse loss. Our work highlights the essential role of glial support cells in the pathogenesis of PD and identifies vesicle trafficking within these cells in disease progression.

Introduction

Parkinson’s disease (PD) is characterized by motor symptoms such as bradykinesia, rigidity, and tremor that are caused by the progressive loss of dopaminergic neurons in the substantia nigra (Lang and Lozano, 1998). However, most of the patients report non-motor symptoms, such as constipation, hyposmia, and sleep defects, even before the onset of motor symptoms (Munhoz et al., 2015). This suggests that PD is a progressive neurodegenerative disease that initiates many years before the diagnosis and involves different neuronal systems, multiple anatomical areas, and different cell types. While therapies symptomatically improve motor functioning temporarily by restoring dopaminergic tone, they do not effectively prevent neurodegeneration and disease progression. This highlights the necessity to identify cell-types and biological mechanisms that act at the earliest stages of disease.

With the advent of single-cell sequencing applied to PD and control brains in combination with evidence from genome-wide association studies (GWAS), it is now possible to identify which cells and mechanisms are at play in PD models that recapitulate early stages of PD (Kaempf et al., 2026; Pech et al., 2025). Among these, one study reported that genes related to GWAS loci are enriched for oligodendrocyte-specific gene expression (Bryois et al., 2020). Interestingly, differential gene expression (DGE) between post-mortem brains with Braak scores of 1–2, 3–4, and 5–6 and controls suggested a role for oligodendrocytes at an early stage of PD prior to the overt loss of dopaminergic neurons (Bryois et al., 2020). Additionally, two independent single-cell sequencing studies, one of the human substantia nigra and one of the midbrain, both associated PD genetic risk with oligodendrocyte-specific expression patterns (Agarwal et al., 2020; Smajić et al., 2022). While these studies started to link dysfunction of oligodendrocytes to the early stages of PD, they did not address their role in the pathophysiology of the disease.

Here, we describe a Drosophila model to start assessing how neuron-glia cross-talk contributes to PD. Drosophila has been successfully used to investigate cellular and molecular dysfunction preceding the onset of age-related symptoms, including dopaminergic neuron-dependent motor symptoms (Kaempf et al., 2026; Pech et al., 2025; Valadas et al., 2018). Furthermore, Drosophila glial cells display several anatomical and functional features that show remarkable similarity to their mammalian counterparts (Freeman and Doherty, 2006; Kremer et al., 2017). While the small size of the Drosophila brain does not necessitate elaborate myelination, ensheathing glia (EG) in this species share not only anatomical features with oligodendrocytes, such as the ability to wrap around nerve tracts in the central nervous system (Kremer et al., 2017; Yildirim et al., 2019), but also important molecular and functional features, such as providing metabolic support and regulating neuronal activity (Delgado et al., 2018; Otto et al., 2018).

In a brain-wide single-cell sequencing experiment, we identified EG as the most deregulated cell type in a young (pre-motor) Pink1 loss-of-function Drosophila model. Using cell-specific labeling, immunohistochemistry, and electrophysiological recordings, we correlated the transcriptional deregulation in EG with changes that appear similar to those seen upon nerve injury. Additionally, we find that healthy EG are fundamental to support dopaminergic synapse integrity in Pink1 mutants. Finally, using cell-type-specific transcriptomic, high-throughput screening, and immunohistochemistry, we identified vesicle trafficking as a genetic modifier and showed that Vps13 and Vps35 are EG-expressed regulators that maintain dopaminergic synapse integrity. Our study shows that neuron-EG cross-talk is already disrupted at a young age by the loss of Pink1 in neurons, but also in EG, and that EG are fundamental to support dopaminergic synapse integrity, suggesting a role for oligodendrocytes in the progression of PD.

Results

EG in Pink1 loss-of-function flies show cell non-autonomous response

We previously created a whole-brain single-cell RNAseq dataset from different Drosophila PD knock-in models (Pech et al., 2025). This dataset was generated from young 5-day-old flies to capture ‘early’ changes related to PD pathophysiology. We re-analyzed the data from Pink1P399L knock-in loss-of-function mutant flies and isogenic controls and performed differentially expressed gene (DEG) analysis for each cell type using DESeq2 (Figure 1A). Glial cell subtypes show the highest degree of transcriptional deregulation; particularly, EG are strongly affected (Figure 1A). While flies do not myelinate neurons, EG serve similar supporting functions as oligodendrocytes (Otto et al., 2018; Yildirim et al., 2019). These results suggest that EG are deregulated in young Pink1P399L mutants (and also Pink1KO-WS/y, see below) at an age prior to dopaminergic neuron-dependent motor defects (Kaempf et al., 2026; Pech et al., 2025).

Figure 1 with 1 supplement see all
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Ensheathing glia (EG) are affected non-cell autonomously by Pink1 loss-of-function (with Figure 1—figure supplement 1).

(A) tSNE of the cells of Pink1P399L knock-in mutants (5-day-old). Cell types are labeled with colors, indicating the number of deregulated genes compared to control. EG are encircled and labeled. (B–B”) Maximum intensity projections of confocal images of fly brains (5±1-day-old) stained with anti-GFP (green) and anti-Brp (magenta), where anti-GFP marks EG and anti-Brp marks presynaptic sites of the antennal lobes in flies where CD8GFP is expressed via the EG driver MZ709-Gal4. Scale bar: 20 µm. (B’) Maximum intensity projection of confocal images of controls vs. controls 24 hr after olfactory receptor neuron (ORN)-severing (injury). (B”) Maximum intensity projection of confocal images of Pink1KO-WS/y vs. Pink1KO-WS/y 24 hr after ORNs severing (injury). (C) Quantification of GFP intensity within the glomeruli of the antennal lobe area, region of interest (ROI), in 5±1-day-old flies (as in B) relative to controls. ANOVA with Dunnett’s multiple comparison test, * is p<0.05, *** is p<0.001. Effect size: η2=0.23. Bars: mean ± SD; points are individual animals, N≥13 per genotype, 4 replicates. (D–D”) Maximum intensity projection of confocal images of fly brains (5±1-day-old) stained with anti-GFP (green) and anti-Brp (magenta), where anti-GFP marks EG and anti-Brp marks presynaptic sites of the antennal lobes in flies where CD8GFP is expressed via the EG driver MZ709-Gal4. Scale bar: 20 µm. (D’) Maximum intensity projection of confocal images of control (w1118) and Pink1KO-WS/y animals. (D”) Maximum intensity projection of confocal images of animals with Pink1 downregulation in EG and Pink1KO-WS/y with Pink1 rescued in EG. (E) Quantification of GFP intensity within the glomeruli of the antennal lobe area in 5-day-old flies (as in D) relative to controls. ANOVA with Tukey’s multiple comparison test, ** is p<0.01, *** is p<0.001. **** is p<0.0001. Effect size: η2=0.36. Bars: mean ± SD; points are individual animals, N≥10 per genotype, 4 replicates.

When neurons are damaged, activated EG invade the neuropil (Doherty et al., 2009; MacDonald et al., 2006). For example, when fly antennal lobes are removed, severing the olfactory receptor neurons (ORNs), EG invade the antennal lobe neuropil (MacDonald et al., 2006), potentially as a protective response (Figure 1B’–C). To test if EG invaded the neuropil in Pink1 mutant flies, we expressed a transmembrane fluorescent protein (UAS-CD8GFP) under the control of a promoter specific to EG (MZ709-Gal4) (Doherty et al., 2009, Figure 1—figure supplement 1) in control and Pink1KO-WS/y flies. Samples were labeled with anti-GFP and the pre-synaptic protein Bruchpilot (NC82). Similar to ORN-severed controls, GFP signal, lining the membrane of EG, is visible inside the antennal neuropil in Pink1KO-WS/y, and severing the ORN in Pink1KO-WS/y does not further exacerbate this phenotype (Figure 1B”–C). Even though we cannot exclude that in Pink1 mutants the GFP signal is merely upregulated, Pink1 loss and neuron-severing that triggers EG activation appear to display a similar neuropil-invasion phenotype.

In order to determine whether this phenotype is cell-autonomous, we generated cell-type-specific Pink1 perturbations. We either downregulated Pink1 using a previously well-validated RNAi line specifically in EG (EG-specific Pink1 loss-of-function – Figure 1D’’), or we re-expressed wild-type Pink1 specifically in EG in Pink1KO-WS/y flies (all cells, but the EG, loss-of-function – Figure 1D”). When Pink1 is knocked down in EG (but present in other cells, including neurons), no additional GFP signal is detected in the neuropil (Figure 1D’’–E). However, when Pink1 is not present in neurons and expressed in EG, the GFP is present inside the antennal neuropil (Figure 1D”–E). This suggests that Pink1-defective neurons activate the EG in a cell non-autonomous fashion to invade, and potentially protect, the neuropil.

EG function supports synaptic integrity

Our finding that Pink1KO-WS/y in neurons elicits a cell non-autonomous response in EG suggested that EG might, in turn, also functionally modulate neuronal integrity in mutant flies. To test this, we made use of a readily accessible model circuit in the fly visual system with an easy electrophysiological readout, electroretinograms (ERGs). Notably, whereas our functional readout here interrogates neuronal activity in the visual system, our analysis of EG morphology was performed in the antennal lobe, a distinct brain region. We therefore make the explicit assumption that EG perform comparable functions across fly brain regions. This assumption is supported by our single-cell sequencing dataset, in which we did not detect region-specific segregation of EG into distinct clusters that could be attributed to different brain areas. The ERG waveforms are susceptible to changes in intracellular signaling, neuronal function, and synaptic transmission, and have been well characterized and amply used to assess neuronal and cellular function (Hardie and Raghu, 2001; Praschberger et al., 2023; Soukup et al., 2016; Wu and Wong, 1977). We exploited this method to understand the role of Pink1 in EG on neuronal function and synaptic transmission in young flies.

Comparing control with young Pink1KO-WS/y flies does not show a difference in the ‘depolarization response’, indicating that – as expected – there is no neurodegeneration occurring in the photoreceptors at this stage (Figure 2A). However, when comparing the ON peak – which represents synaptic transmission from the photoreceptors and within the underlying neuronal circuit, and is a more robust readout of this than the OFF peak (Vilinsky and Johnson, 2012) – we detect a significant reduction in mutant compared to control animals, suggesting that in Pink1KO-WS/y flies, synaptic communication in this circuit is partially impaired, already in 5-day-old animals (Figure 2A and B).

Figure 2 with 1 supplement see all
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Pink1 in ensheathing glia (EG) is necessary to support synaptic integrity (with Figure 2—figure supplement 1).

(A) Representative electroretinogram (ERG) traces of indicated genotypes: ON peak is highlighted by the arrow. (B) Normalized ON peak amplitude of flies (5±1-day-old). ANOVA with Tukey’s multiple comparison test, ns is p>0.05, ** is p<0.01, **** is p<0.0001. Effect size: η2=0.55. Bars: mean ± SD; points are individual animals, N≥11 per genotype, 3 replicates. (C–C”) (C) Maximum intensity projection of confocal images of control and Pink1KO-WS/y in mushroom bodies (MBs) of aged flies (22±2-day-old), stained with anti-TH (cyan) and anti-DLG (magenta) antibodies – DLG is used to mark post-synaptic sites of MBs. The black-and-white image is the middle Z-plane within the region of interest of the MB (region of interest [ROI], yellow), which is used to represent the thresholded TH area (white). Scale bar: 20 µm. (C’) Maximum intensity projection of confocal images of w1118 with Pink1 downregulation in EG. (C”) Maximum intensity projection of confocal images of Pink1KO-WS/y with Pink1 rescued in EG. (D) Quantification of the dopaminergic synaptic area at MB neuropil in aged flies (22±2-day-old). ANOVA with Tukey’s multiple comparison test, ns is p>0.05, *** is p<0.001. Effect size: η2=0.38. Bars: mean ± SD; points are individual animals, N≥12 per genotype, 3 replicates.

In order to discern the role of EG in this defective ERG response, we (1) downregulated Pink1 specifically in EG and (2) we expressed Pink1 specifically in the EG of Pink1KO-WS/y. When Pink1 is knocked down specifically in EG, we observe the same reduction in ON peak response as in the Pink1KO-WS/y flies. This indicates that EG integrity is necessary for efficient neurotransmission in this circuit. Conversely, the ON peak defect of Pink1KO-WS/y mutants is rescued when Pink1 is reintroduced in EG only. This suggests that activated EG are able to, at least partially, buffer the detrimental effects of Pink1 deficiency in neurons (Figure 2A and B).

To also test EG function in relation to PD-relevant dopaminergic (DA) synapses, we evaluated the loss of dopaminergic neuron afferents. In a previous paper from our laboratory, we have shown that the loss of Pink1 function causes a progressive loss of protocerebral anterior medial dopaminergic neuron (PAM DAN) afferents in the mushroom body (MB) neuropil in 25-day-old animals, but not when they are 5-day-old (Kaempf et al., 2026). Indeed, we confirm that 25-day-old animals show a decrease in the dopaminergic synaptic area in MB lobes (Figure 2C and D). Hence, while EG are already activated at a young age in Pink1KO-WS/y, DA synapses are structurally still intact (at 5 days of age) and only deteriorate in older flies. We then knocked down Pink1 specifically in EG and found a similar strong decrease in DA synaptic area as compared to global Pink1KO (Figure 2C’–D). Conversely, when Pink1 is reintroduced specifically in EG of Pink1KO-WS/y animals, DA synapse loss is significantly rescued (Figure 2C”–D, Figure 2—figure supplement 1). Together, these results indicate that Pink1 in EG is necessary to protect dopaminergic neurons from synapse loss.

EG cell-type-specific transcriptomics reveals modifiers of neuronal dysfunction

To identify pathways in EG that are deregulated by Pink1 loss-of-function, we optimized a method to isolate EGs from the rest of the brain, enabling us to perform much higher-sensitivity transcriptomics than what we achieved with our 10× droplet-based single-cell sequencing (Pech et al., 2025). We fluorescently labeled EG nuclei (GMR-56-Gal4) with histone-fused GFP (UAS-His2Av::eGFP) and used fluorescence-activated cell sorting (FACS) to isolate EG. We sorted 300 cells per technical replicate and performed bulk RNAseq using the highly sensitive SMART-seq2 protocol to robustly generate RNAseq libraries from this low number of input material (Figure 3A). The sequencing results of EG-sorted cells vs. neuron-sorted cells (nSyb-Gal4 instead of GMR-56-Gal4) show strong enrichment of EG cell markers in the former and strong enrichment of neuronal markers in the latter (Figure 3B), thus indicating that we can reliably obtain brain-cell-type-specific transcriptomes with this approach. We then compared the transcriptomic profile of EG in Pink1KO-WS/y to that of control using differential expression analysis and found 617 deregulated genes in EG (Supplementary file 1, padj<0.05) (Figure 3C). To understand whether the deregulated genes were enriched for a specific pathway or associated with a cellular component compared to non-significantly deregulated genes, we performed Gene Ontology analysis of the deregulated genes in Pink1KO-WS/y flies. Our analysis resulted in generic terms and very diverse pathways that did not allow us to draw further conclusions.

Figure 3
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Cell-type-specific transcriptomics reveals modifiers of neuronal dysfunction.

(A) Scheme of cell-type-specific transcriptomics (Created in BioRender. Verstreken, P. (2025) https://biorender.com/p56u250). (B) Scaled gene expression of representative genes for ensheathing glia (EG) and neurons after sorting EG or neurons using the protocol described in (A). N=2, 2 replicates. (C) Differentially expressed genes (DEGs) in EG in Pink1KO-WS/y compared to control flies, plotted according to their log2foldchange and the –log10 of the adjusted p-value. Intercept in red (–log10 adjusted p-value = 4.31); light green dots are all detected genes, dark green are the 50 most deregulated genes, and the pink dot is from a gene positive in the genetic screen in (D). *Two data points are outside the boundaries of the plot. To determine the transcriptomic profile of each genotype, N=3 independent repeat experiments were used, with 3 replicates each time. (D) Electroretinogram (ERG) ON peak value differences of control (red) and of Pink1KO-WS/y flies (5±1-day-old) with DEGs downregulated or upregulated, specifically in EG relative to Pink1KO-WS/y. ANOVA with Dunnett’s test, * is p<0.05, ** is p<0.01, **** is p<0.0001. Effect size: η2=0.44. Bars: mean ± SD; points are individual animals, N≥3 per genotype. *One data point is outside the boundaries of the plot.

To test if the genes deregulated in EG are modifiers of the neuronal Pink1KO-WS/y phenotypes, we downregulated and upregulated (when possible) the 50 most deregulated genes (Figure 3C), for which RNAi lines were available, specifically in the EG of Pink1KO-WS/y flies and recorded ERGs in 5-day-old animals. Knockdown of one of these genes (CG17660) resulted in a statistically significant rescue of the ON transient defects in Pink1KO-WS/y, and a few exacerbated the defect (Figure 3D). Interestingly, the human orthologs of CG17660, TMEM87A/B, have an established role in endosomal sorting (Gaudet et al., 2011; Hirata et al., 2015). Hence, our genetic screening suggests that Pink1KO-WS/y phenotypes might be suppressed by downregulating genes involved in vesicle trafficking in EG.

PD causative vesicle trafficking gene downregulation in EG rescues synaptic dopaminergic neurons afferent loss

Because our ERG-based modifier screen for the Pink1KO-WS/y phenotype identified a gene with a known role in vesicle trafficking, we next asked whether Pink1 in EG also genetically interacts with other PD-causative genes that function in vesicle trafficking, specifically vesicle trafficking components affecting membrane interactions between mitochondria and the endoplasmic reticulum (ER), like Vps35 and Vps13 (Brickner and Fuller, 1997; Lesage et al., 2016; Vilariño-Güell et al., 2011; Zimprich et al., 2011). We find that the knockdown of each of these genes in EG also rescues the ON transient defect of Pink1KO-WS/y mutants (Figure 4A and B).

Figure 4 with 1 supplement see all
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Vps35 and Vps13 downregulation in ensheathing glia (EG) rescues synaptic deficits in Pink1KO-WS-y flies (with Figure 4—figure supplement 1).

(A) Representative electroretinogram (ERG) traces of control, Pink1KO-WS/y flies, and Pink1KO-WS/y flies with Vps35 or Vps13 downregulated in EG. (B) Quantification of the normalized ON peak response of flies with the genotypes in (A) (5±1-day-old). ANOVA with Dunnett’s multiple comparison test, ns is p>0.05, ** is p<0.01. Effect size: η2=0.48. Bars: mean ± SD; points are individual animals, N≥10 per genotype, 3 replicates. (C) Maximum intensity projection of confocal images of mushroom bodies (MBs) of aged flies (22±2-day-old) of control, Pink1KO-WS/y, and Pink1KO-WS/y with Vps13 downregulated in EG , labeled with anti-TH (cyan) and anti-DLG (magenta); DLG is used to mark the MB neuropil. The black-and-white image is the middle Z-plane within the region of interest of the MB (regions of interest [ROI], yellow), which is used to represent the thresholded TH area (white). Scale bar: 20 µm. (D) Quantification of the dopaminergic synaptic area within MB of aged flies (22±2-day-old). ANOVA with Dunnett’s multiple comparison test, ns is p>0.05, *** is p<0.001. Effect size: η2=0.23. Bars: mean ± SD; points are individual animals, n≥22 per genotype, 5 replicates.

To determine if manipulation of this pathway in EG can also rescue the synaptic innervation defect of PAM DAN onto the MBs in old (20- to 25-day-old) Pink1KO-WS/y mutants, we expressed Vps13 RNAi in EG using MZ709-Gal4. Anti-TH labeling (marking DAN synapses) in the MB area (marked by anti-DLG) is significantly reduced in aged Pink1KO-WS/y, but is rescued to levels comparable to that observed in controls when Vps13 is knocked down in EG (Figure 4C, D, Figure 4—figure supplement 1). These results suggest that manipulation of vesicle trafficking components affecting membrane interactions between mitochondria and the ER in EG regulates glia-neuron cross-talk to maintain synaptic integrity of dopaminergic neuron synapses in the fly brain of Pink1 mutants. Note that the DA synaptic rescue was tested for Vps13 but not for Vps35, and whether EG-specific Vps35 knockdown similarly protects dopaminergic synapses remains to be determined.

Discussion

In this work, we provide evidence for early, non-cell-autonomous activation of EG in a PD-relevant Drosophila Pink1 model. This occurs already in young Pink1-mutant flies when neuronal defects in dopaminergic neurons are not yet measurable. The EG activation and invasion phenotype elicited by Pink1-deficient neurons appears as a protective response as it seems to mimic the response to nerve injury (Doherty et al., 2009; MacDonald et al., 2006). We show that there is a non-autonomous role of EG to support Pink1-deficient neurons. When we manipulate the expression of membrane-lipid trafficking genes, the homologs of the established PD genes VPS13C and VPS35 (Lesage et al., 2016; Vilariño-Güell et al., 2011; Zimprich et al., 2011), specifically in EG, we rescue the dysfunction of Pink1 mutant neuron defects as measured by ERGs and age-dependent PAM DAN synapse loss. Our work shows the importance of neuron-glia cross-talk in the context of Pink1-deficiency. We suggest (1) there is early EG activation secondary to Pink1-loss-induced neuronal impairments; (2) there are specific lipid- and membrane trafficking problems caused by Pink1 loss in EG that center on mitochondria/ER contacts; and (3) there is a convergence of Parkinson-relevant genetic factors that act in EG to maintain neuronal function. CG17660, the single ERG screen hit that initially pointed toward vesicle trafficking as a relevant pathway, has not been further validated in this study; full characterization and testing of DA synaptic rescue in Pink1 mutants remain an important direction for future work.

The loss of Pink1 function in the context of PD has been amply linked to the regulation of mitochondrial health. Pink1 maintains the integrity of the electron transport chain by phosphorylating NDUFA10 (Morais et al., 2009; Morais et al., 2014; Pogson et al., 2014), and when mitochondria are damaged, it phosphorylates Parkin and ubiquitin to facilitate mitophagy (Kane et al., 2014; Narendra et al., 2010; Narendra and Youle, 2024). The regulation of mitophagy is complex and requires mitochondrial rearrangements controlled by mitochondria-organelle contacts (ER and lysosomes) (Wong et al., 2018; Wong et al., 2019; Yamano et al., 2018). Such contacts mediate inter-organellar lipid exchange, as well as facilitate organellar fusion (Kumar et al., 2018; Valadas et al., 2018). In Pink1 mutants, these contacts appear to be increased in number, and this causes cellular defects (Grossmann et al., 2023; Valadas et al., 2018).

We found that in EG, Vps35 functionally interacts with Pink1-induced neuronal dysfunction: its genetic manipulation in EG rescues cell non-autonomous neuronal dysfunction. Loss of Vps35 itself only in EG is sufficient to rescue neuronal Pink1 phenotypes. Pink1 loss-of-function models show increased numbers of mitochondria-ER contact sites (Valadas et al., 2018), affecting mitochondrial calcium levels (Barazzuol et al., 2020; de Brito and Scorrano, 2008; Ham et al., 2023) and dysregulating lipidic ER composition (Valadas et al., 2018; Figure 5A). Indeed, Pink1 is necessary for ubiquitination and degradation of Mitofusin (Poole et al., 2010), which is fundamental for the mitochondria-ER tethering (de Brito and Scorrano, 2008). Interestingly, Vps35 deficiency promotes untethering of mitochondria-ER contact sites by increasing the mitochondrial levels of MUL1, which is necessary for the ubiquitination and degradation of Mitofusin (Puri et al., 2019; Tang et al., 2015; Yun et al., 2014). Hence, conditions that affect mitochondria-ER contact site regulation in EG, by modifying an endosomal trafficking regulator such as Vps35, are expected to rescue Pink1 neuronal dysfunction, possibly by restoring mitochondrial calcium levels and the lipid composition of the ER (Figure 5B), but further work is needed to sort these mechanistic elements in a cell-type-specific manner. We note that while EG-specific Vps35 downregulation rescues the ERG on-transient defect in the visual system, whether it similarly protects dopaminergic synapses, as shown for Vps13 (Figure 4C and D), has not been tested, and this rescue may be cell-type- or phenotype-specific.

Figure 5
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Modulation of endoplasmic reticulum (ER)-mitochondria contact sites and lipid transfer in ensheathing glia (EG) rescues Pink1-dependent neuronal dysfunction.

Schematic representation of the suggested model (Created with BioRender.com). (A) Loss of Pink1 leads to an abnormal increase in endoplasmic reticulum (ER)-mitochondria contact sites (represented by blue thick lines), resulting in enhanced ER-to-mitochondria lipid transfer and dysregulation of ER lipid composition (represented by yellow lipids). Increased organelle membrane contacts and lipid flux in EG contribute to neuronal dysfunction in a non-cell-autonomous manner. (B) Genetic downregulation of ER-mitochondria contact and lipid transfer regulators in EG rescues Pink1-induced neuronal phenotypes through two convergent mechanisms. Reduction of Vps35 may decrease the number of ER-mitochondria contact sites, possibly via MUL1-mediated Mitofusin (Mfn) turnover, potentially normalizing calcium and lipid homeostasis. In parallel, downregulation of Vps13, a lipid transfer facilitator at organelle contact sites, limits ER-to-mitochondria lipid transfer capacity, counteracting the excessive lipid flux induced by Pink1 loss. Both interventions restore organelle homeostasis in EG and result in rescue of neuronal dysfunction through a non-cell-autonomous mechanism. Rescue of neuronal dysfunction by EG-specific Vps35RNAi was demonstrated in the visual system (electroretinogram [ERG] on-transient; Figure 4A and B). Whether this extends to dopaminergic synaptic loss, as demonstrated for Vps13 (Figure 4C and D), has not yet been examined and may be cell-type- and/or phenotype-specific.

Our observation that downregulation of Vps13 in EG also rescues Pink1 is in further support of a role for ER-mitochondria contact site regulation. Vps13 has two mammalian homologs, VPS13A and VPS13C (Velayos-Baeza et al., 2004; Vonk et al., 2017; Vrijsen et al., 2022), which are also mutated in familial Parkinsonism/neurodegenerative disease (Lesage et al., 2016). VPS13A tethers ER to mitochondria and lipid droplets, and VPS13C tethers ER to late endosomes, lysosomes, and lipid droplets (Kumar et al., 2018; Muñoz-Braceras et al., 2019; Vrijsen et al., 2022). The function of these proteins is to facilitate lipid transfer between organelles, a function we previously showed to be increased in Pink1 mutants (Valadas et al., 2018). Hence, the downregulation of Vps13 would counteract the effects of excessive organelle membrane contact formation and dysregulated lipid homeostasis in Pink1 mutants (Figure 5B). We note, however, that while we propose modulation of ER-mitochondria contacts as the mechanism underlying both the Vps13 and Vps35 rescue, direct molecular evidence for this in EG is currently lacking and represents an important question for future investigation.

Lipid homeostasis in glial cells is crucial for supporting neuronal function by providing energy, protecting against oxidative stress, and regulating synaptic health. In oligodendrocytes, maintaining myelin sheaths is critical (Ettle et al., 2016; Lappe-Siefke et al., 2003). While fly EG do not generate such structures, they do wrap processes around neuropil regions, also requiring lipid membrane production (Kremer et al., 2017; Pogodalla et al., 2021). Through lipid metabolism, glia also supply neurons with essential metabolites, cholesterol, and signaling molecules that aid in membrane integrity, synaptic remodeling, and neuroprotection (Delgado et al., 2018; Otto et al., 2018; Saab et al., 2016; Suárez-Pozos et al., 2020). Further work is now required to define which functions, supported by organelle contact sites in glial cells, drive cell-non-autonomous protective mechanisms in neurons. Our work in flies indicates these glial changes precede dopaminergic synapse loss, and, importantly, that rescuing glial defects helps to prevent dopaminergic problems later in life.

Methods

Resource availability

Lead contact

Further information and requests for resources and reagents should be directed to the lead contact, Patrik Verstreken (patrik.verstreken@kuleuven.be).

Materials availability

Data, code, Drosophila models, and reagents are available upon request.

Fly stocks

The fruit flies were maintained in an incubator at 25°C under a 12 hr:12 hr light-dark cycle and provided with a standard diet consisting of corn meal and molasses. For experiments, only male flies were used. Flies were raised in parallel on the same batch of food, which was exchanged every 3–4 days and kept in only male populations of similar density. Flies were aged to 5±1-day-old and 22±2-day-old, as indicated for immunohistochemistry and ERGs, respectively.

To create a set of Drosophila models for PD, CRISPR/Cas9-based gene editing was utilized, as outlined in Kaempf et al., 2026; Pech et al., 2025. In brief, each knockout line contained an attP-flanked w+ reporter cassette that replaced the first shared exon across different isoforms of the targeted gene. For this study, we used knockout flies for Pink1 from this collection (Kaempf et al., 2026). The ‘control’ strain denotes a semi-isogenized w1118 strain that underwent backcrossing to Canton-S for 10 successive generations, resulting in a strain termed Canton-S-w1118. To generate the fly line yw; UAS-His2Av::eGFP.VK27/TM3Sb, we created the pUASTattB_His2Av::eGFP plasmid, linearizing the pUASTattB (Bischof et al., 2007) with EcoRI-BamHI. A gBlock containing the His2Av, a GS linker, and eGFP sequence was cloned into this linearized plasmid with Gibson Assembly. The plasmid was inserted into the VK27 landing site by BestGene. The sequence His2Av::GS::eGFP gBlock is:

TGAATAGGGAATTGGGcAAacATGGCTGGCGGTAAAGCAGGCAAGGATTCGGGCAAGGCCAAGGCGAAGGCGGTATCGCGTTCCGCGCGCGCGGGTCTTCAGTTCCCCGTGGGTCGCATCCATCGTCATCTCAAGAGCCGCACTACGTCACATGGACGCGTCGGAGCCACTGCAGCCGTGTACTCCGCTGCCATATTGGAATACCTGACCGCCGAGGTCCTGGAGTTGGCAGGCAACGCATCGAAGGACTTGAAAGTGAAACGTATCACTCCTCGCCACTTACAGCTCGCCATTCGCGGAGACGAGGAGCTGGACAGCCTGATCAAGGCAACCATCGCTGGTGGCGGTGTCATTCCGCACATACACAAGTCGCTGATCGGCAAAAAGGAGGAAACGGTGCAGGAcCCGCAGCGGAAGGGCAACGTCATTCTGTCGCAGGCCTACGGTTCAGGCGGAGGTGGCAGCGGCGGTGGCGGATCCATGGTGAGCAAGGGCGAGGAGCTGTTCACCGGGGTGGTGCCCATCCTGGTCGAGCTGGACGGCGACGTAAACGGCCACAAGTTCAGCGTGTCCGGCGAGGGCGAGGGCGATGCCACCTACGGCAAGCTGACCCTGAAGTTCATCTGCACCACCGGCAAGCTGCCCGTGCCCTGGCCCACCCTCGTGACCACCCTGACCTACGGCGTGCAGTGCTTCAGCCGCTACCCCGACCACATGAAGCAGCACGACTTCTTCAAGTCCGCCATGCCCGAAGGCTACGTCCAGGAGCGCACCATCTTCTTCAAGGACGACGGCAACTACAAGACCCGCGCCGAGGTGAAGTTCGAGGGCGACACCCTGGTGAACCGCATCGAGCTGAAGGGCATCGACTTCAAGGAGGACGGCAACATCCTGGGGCACAAGCTGGAGTACAACTACAACAGCCACAACGTCTATATCATGGCCGACAAGCAGAAGAACGGCATCAAGGTGAACTTCAAGATCCGCCACAACATCGAGGACGGCAGCGTGCAGCTCGCCGACCACTACCAGCAGAACACCCCCATCGGCGACGGCCCCGTGCTGCTGCCCGACAACCACTACCTGAGCACCCAGTCCGCCCTGAGCAAAGACCCCAACGAGAAGCGCGATCACATGGTCCTGCTGGAGTTCGTGACCGCCGCCGGGATCACTCTCGGCATGGACGAGCTGTACAAATAAGGGTACCTCTAGAGGATCTT

Flies were backcrossed for five generations into our Canton-S-w1118 reference background. The genotypes used in this study are listed in the Key resources table and Supplementary file 2.

ORN axotomy

ORN bilateral axotomy was performed on 4±1-day-old flies by surgical ablation of the third antennal segment. Briefly, flies were anesthetized with CO2, and then both antennae were removed with Dumont #5 forceps and returned to the vial (Purice, 2020; Purice et al., 2017). Flies were allowed to recover for 24 hr on food at 25°C before dissection to perform imaging.

Immunohistochemistry and confocal imaging – invasion phenotype

Immunohistochemistry was performed on adult fly brains of 5±1-day-old, with at least two independent experiments. The brains were dissected in ice-cold PBS and fixed for 20 min in freshly prepared 3.7% paraformaldehyde (in 1× PBS, 0.3% Triton X-100 [PBX] [Sigma]) at room temperature (RT), followed by three 15 min washes in PBX at RT on a shaker. Then, the brains were incubated for 1 hr in blocking solution (PBX, 10% normal goat serum [NGS]) at RT. Following blocking, the brains were incubated with primary antibodies (rabbit anti-GFP [Thermo Fisher Scientific], 1:1000, mouse anti-Brp [DSHB, nc82], 1:100) in blocking solution at 4°C overnight, followed by three 15 min washes in PBX at RT. Secondary antibodies (goat anti-rabbit Alexa488, goat anti-mouse Alexa555, both at 1:1000 [Thermo Fisher Scientific]) in PBX with 10% NGS were subsequently applied overnight at 4°C. Afterward, the brains were washed three times for 15 min in PBT at RT on a shaker and mounted with the anterior facing up in RapiClear 1.47 (SUNJin Lab). Imaging was performed using a Nikon A1R confocal microscope with a 40× (NA 1.15) water immersion lens; Z-stacks (with 0,5 μm step intervals) of the entire antennal lobes were acquired, and the same imaging settings were applied across all genotypes and sessions. The acquisition was carried out using a Galvano scanner, with a zoom factor of 1, scan speed of 0.5, and line averaging set to 2. All images were captured with a pinhole of 0.9 Airy units and a resolution of 1024×1024 pixels. Image analysis was performed using Fiji (Schindelin et al., 2012). Each antennal lobe is composed of multiple glomeruli, and EG separate them and invade them when activated (Doherty et al., 2009; Pogodalla et al., 2021). To quantify EG invasion into the antennal lobe, we calculated the invasion in every single glomerulus. To do so and be consistent with the section of the antennal lobe analyzed, anti-Brp was used to identify the three Z-planes, where DM6 and DM1 glomeruli were present (Wu et al., 2017a). Then, to automatically detect and segment each glomerulus of the antennal lobe section, regions of interest (ROIs) were defined in the SUM projection of the three Z-planes by using the Fiji plugin Stardist (Weigert et al., 2019). The GFP intensity was detected in each ROI, and it was normalized to the area of each ROI (GFP intensity/glomeruli area) to calculate the EG invasion in each glomerulus. Then, the normalized GFP intensity of each glomerulus of an antennal lobe was summed and normalized for the number of glomeruli detected in the antennal lobe. For each experiment, the EG antennal lobe invasion of each fly was normalized to the mean of the control. Representative images show the maximum intensity projections of the three Z-planes.

Immunohistochemistry and confocal imaging – TH staining

Immunohistochemistry was performed on adult fly brains of 22±2-day-old, with at least two independent experiments. The brains were dissected in ice-cold PBS and fixed for 20 min in freshly prepared 3.7% paraformaldehyde (in 1× PBS, 0.2% Triton X-100 [PBX]) at RT, followed by three 15 min washes in PBX at RT on a shaker. Then, the brains were incubated for 1 hr in blocking solution (PBX, 10% NGS) at RT. Following blocking, the brains were incubated with primary antibodies (rabbit anti-TH [Sigma], 1:200, mouse anti-DLG [DSHB], 1:100) in blocking solution at 4°C for 1.5–2 days, followed by three 15 min washes in PBX at RT. Secondary antibodies (goat anti-rabbit Alexa488, goat anti-mouse Alexa555, both at 1:500 [Thermo Fisher Scientific]) in PBX with 10% NGS were applied overnight at 4°C. Afterward, the brains were washed three times for 15 min in PBT at RT on a shaker and mounted with the anterior facing up in RapiClear 1.47 (SUNJin Lab). Imaging was performed using a Nikon A1R confocal microscope with a 20× (NA 0.95) water immersion lens; Z-stacks (with 3 μm step intervals) of the entire brain were acquired, and the same imaging settings were applied across all genotypes and sessions. The acquisition was carried out using a Galvano scanner, with a zoom factor of 1, scan speed of 0.5, and line averaging set to 2. All images were captured with a pinhole of 2.3 Airy units and a resolution of 1024×1024 pixels. Image analysis was performed using Fiji (Schindelin et al., 2012). To quantify dopaminergic neuron innervation of the MB, anti-DLG was used to identify the five Z-planes containing the synaptic region of the MB lobes. The ROI for the MB was defined in the sum projection of the five Z-planes. To exclude background signal comparable to control, the area of anti-TH fluorescence was thresholded (using the default threshold for all Z-planes) within the selected Z-stacks. Quantification of the thresholded area within the ROI was performed in each Z-plane, then summed and normalized to the MB ROI area for each brain individually (TH+area/MB area). For each experiment, the individual TH+area/MB area values were normalized to the mean of the control. Representative images show the maximum projection of five Z-planes and the thresholded middle Z-plane.

Electroretinograms

ERGs were recorded from flies 5±1-day-old as previously described (Heisenberg, 1971; Slabbaert et al., 2016). Flies were immobilized on glass microscope slides using double-sided tape. For recordings, glass electrodes (borosilicate, 1.5 mm outer diameter) filled with 3 M NaCl were placed in the thorax as a reference and on the fly eye for recordings. Each fly was exposed to 5 cycles of 3 s of darkness, followed by 1 s of light stimuli with LED illumination. Response to the stimuli was recorded using Axoscope 10.7 and analyzed using Clampfit 10.7 software (Molecular Devices). ERG traces were analyzed with Igor Pro 6.37 (Wave Metrics) using a custom-made macro.

Single-cell dissociation for cell-type-specific transcriptomics

To test that EG could be isolated from the rest of the brain, we labeled EG and neurons separately in two cohorts of flies with GMR-56-Gal4>UAS-His2Av::eGFP and nSyb-Gal4>UAS-His2Av::eGFP. To identify DEGs in EG, two cohorts were used: the control w1118 expressing GMR-56-Gal4>UAS-His2Av::eGFP and Pink1KO-WS/y expressing GMR-56-Gal4>UAS-His2Av::eGFP. For each genotype, 10 brains of flies 5±1-day-old were collected, with most of the laminae removed, from each experimental repeat. The dissections were performed in ice-cold PBS containing 5 μM Actinomycin D (Sigma) to inhibit changes in gene expression during tissue processing (Wu et al., 2017b). To prevent any bias caused by different experimental batches, all the genotypes were processed in parallel. To minimize variability across batches, the same reagents and procedures were used throughout the experiment. Dissections were completed within 1 hr. The dissection order and the assignment of genotypes to dissectors were alternated to reduce any experimenter-related variation.

For the dissociation of brain tissue, a mix of Dispase I (0.6 mg/ml) (Sigma), Collagenase I (30 mg/ml) (Thermo Fisher), Trypsin (0.5×) (Thermo Fisher), and 5 μM Actinomycin D was used. The brains were incubated for 20 min at 25°C with 1000 rpm shaking, performing four triturations at 5 min intervals. After dissociation, the cell suspensions were washed with PBS containing 5 μM Actinomycin D and then filtered through a 10 μm strainer (Pluriselect), using 300 μl of PBS EDTA (Sigma) 1 μM. DAPI (Sigma) (1:300,000) was added after filtration.

FACS for cell-type-specific transcriptomics

Immediately after the dissociation, cells were sorted using a FACSAria Fusion (BD Biosciences) flow cytometer equipped with four lasers (405 nm, 488 nm, 561 nm, and 640 nm) and a 100 µm nozzle at 20 psi. Live (DAPI-negative), GFP-positive cells were sorted into 96-well PCR plates at 300 cells per well (three wells per genotype) using a four-way purity mask with the FACSDiva software v9.0.1 (BD Biosciences).

Bulk transcriptomics of EG cells

Library preparations and sequencing for the bulk RNAseq of the EG cells were performed using a modified Smart-seq2 protocol (Picelli et al., 2013). Briefly, 3 μl of cell lysis buffer (0.1% Triton X-100, Sigma-Aldrich; 1 U/µl of RNase Inhibitor, RNase OUT [Thermo Fisher]; 2.5 μM Oligo dT[25], (IDT); and 2.5 mM dNTP [Promega]) was aliquoted in triplicate to 96-well plates (4titude, Cat. No. 4TI-0960/C). Roughly 300 cells were sorted into the wells with lysis buffer and the plate was spun down at 2000×g for 1 min prior to storage at –80°C. For the first-strand synthesis, the Smart-Seq2 plates were thawed to RT for a minute and subsequently spun down at 2000×g for a minute. The RNA denaturation was carried out at 72°C for 10 min and then flash-cooled on ice for 5 min. First-strand synthesis mix (1× SuperScript II first strand synthesis buffer [Thermo Fisher]; 5 mM DTT [Thermo Fisher]; 100 U SuperScript II reverse transcriptase enzyme [Thermo Fisher]; 10 U RNAse OUT [Thermo Fisher]; 1 M Betaine [Sigma-Aldrich]; 6 mM MgCl2 [Thermo Fisher]; and 1 µM TSO [IDT Technologies]) was added to the cell lysis mix to a total volume of 10 μl. The first-strand synthesis reaction was carried out with the following program: 42°C for 90 min; 10 cycles of {50°C for 2 min; 42°C for 2 min}; 72°C for 15 min; 4°C indefinite hold. PCR amplification of the first-strand product was performed by adding 15 μl of the PCR mix to the first-strand product (1× KAPA HiFi HotStart Ready Mix [Roche]; and 0.1 μM of IS PCR primer [IDT Technologies]). 22 cycles of the following PCR program were used to amplify the first-strand product: 98°C for 3 min; 22 cycles of {98°C for 20 s; 67°C for 15 s; 72°C for 6 min}; 72°C for 5 min; 4°C indefinite hold. 20 μl of Ampure XP was added to each well and mixed. Standard Ampure XP purification was carried out as per the manufacturer’s recommendation, and the cDNA library was eluted in 17.5 μl of Elution buffer. 17 μl of the eluted library was transferred to a fresh 96-well plate (4titude, Cat. No. 4TI-0960/C). 5 μl of Tn5 tagmentation mix (1× Tagment DNA buffer, Illumina; ATM mix [Illumina], and cDNA library 1 ng) was prepared for cDNA fragmentation. Tn5 tagmentation was performed with the following program: 55°C for 10 min; 4°C indefinite hold. Tagmentation reaction was stopped by quenching the reaction with 1.25 μl of NT buffer for 5 min (Illumina). 1.25 μl of the i5 and i7 Illumina indexes were added to the plates. Finally, 3.75 μl of NPM master mix was added to the plate and mixed well and put for the index PCR amplification: 72°C for 3 min; 95°C for 30 s; 12 cycles of {95°C for 10 s; 55°C for 30 s; 72°C for 30 s}; 72°C for 5 min, and 4°C indefinite hold.

The indexed PCR products were pooled in a single tube, and 0.8× Ampure XP purification (Beckman Coulter) was carried out as per the manufacturer’s recommendation, and finally, the sequencing library was eluted in 35.5 μl of Elution buffer (QIAGEN).

Smart-seq2 libraries were sequenced on the NextSeq 500 (Illumina) sequencing platform. Sequencing was done as per the protocol recommendations: paired-end read of 76 bps (read 1), 76 bps (read 2), 8 bps (index 1), and 8 bps (index 2), targeting a sequencing depth of ~30 million reads per sample.

Analysis of RNAseq data – neuron vs. EG

Raw reads from neuron- vs. glia-specific FACS-sorting experiments were processed using the nf-core/rnaseq pipeline (Patel et al., 2020) with default parameters and the BDGP6 reference genome. The STAR-aligned and salmon-quantified expression matrix was then subset to genes known to be enriched in neurons or glia and displayed as a per-gene scaled heatmap.

Analysis of RNAseq data – EG-specific DEGs

After FACS sorting of PinkKO-WS vs. control EG, FASTQ files resulting from library preparation and sequencing were cleaned with fastp (Chen et al., 2018) with default settings. Aligning and counting were carried out with STAR (Dobin et al., 2013) and the 4th 2020 FlyBase Drosophila melanogaster release (r6.35) with the –quantMode flag set as GeneCounts. For DGE testing, we used DESeq2 (Love et al., 2014), where we fit a negative binomial model and carried out the Wald test. We removed the experimental batch as a covariate according to the design formula~date+genotype. All genes below a Benjamini-Hochberg-corrected p-value of 0.05 were considered deregulated.

scRNAseq data loading, filtering, clustering, and differential expression analysis

Raw count data from Pech et al., 2025, alongside cell annotations provided by the authors, was loaded into Scanpy (v1.9.1) (Wolf et al., 2018) and subset to only include cells in the young control (≤6-day-old) or Pink1P399L samples. After subsetting the data, filtering was performed to remove any cell with less than 250 genes expressed or a percentage of counts coming from mitochondrial genes greater than 15%, the data was then normalized to a total of 10,000 counts and log-transformed. Highly variable genes were detected, total counts and percent of mitochondrial reads were regressed out, and finally the data was scaled to unit variance with a zero mean, clipped to a max of 10.

After data pre-processing, a PCA was performed, Harmony (Korsunsky et al., 2019) was used to correct batches using ‘sample_id’ as a batch key, and 122 components were used for dimensionality reduction and clustering analyses. Leiden clustering was performed with a resolution of 8.0 and using the annotations from Pech et al., 2025, all cells within each cluster were labeled by taking the most common, original annotation per cluster.

Per cluster, a DGE analysis was performed. First, pseudobulk counts were generated by summing the counts per cell type from all cells per sample. These counts were then used in DESeq2 (v1.44.0) (Love et al., 2014) comparing control vs. Pink1P399L samples. The total number of genes significantly up- or downregulated per cluster (padj≤0.05 and an abs (log2foldchange) ≥ 1.5) was counted and plotted.

Statistical analysis

GraphPad Prism was used for visualization and to determine statistical significance. Datasets were tested for normal distribution using the D’Agostino-Pearson Omnibus and the Shapiro-Wilk normality test. For a normally distributed dataset, ordinary one-way ANOVA was used, followed to correct for multiple comparisons by a post hoc Tukey’s test when comparing all the datasets with each other or Dunnett’s test when comparing all the datasets to a general control. For non-normally distributed datasets, the Kruskal-Wallis test is used, followed by a post hoc Dunn’s test to correct for multiple comparisons. Significance levels are defined as * is p<0.05, ** is p<0.01, *** is p<0.001, **** is p<0.0001, and ns, not significant, p>0.05. Effect size is calculated with eta-squared when one-way ANOVA is used, indicated in the figure legend as η2. ‘N’ in the legends is used to indicate how many animals were analyzed. Data are plotted as mean ± SD. Specifics on the statistical test used for each analysis are reported in the figure legends.

Inclusion and diversity

We support inclusive, diverse, and equitable conduct of research.

Appendix 1

Appendix 1—key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
AntibodyRabbit polyclonal anti-GFPThermo Fisher ScientificCat#A-11122; RRID:AB_221569(1:1000)
AntibodyMouse monoclonal anti-BrpDSHBCat#nc82; RRID:AB_2314866(1:100)
AntibodyMouse monoclonal anti-DLGDSHBCat#4F3; RRID:AB_528203(1:100)
AntibodyRabbit polyclonal anti-THSigma-AldrichCat#AB 152(1:200)
AntibodyAlexa Fluor 488 goat anti-rabbitInvitrogenCat#A11034(1:1000) in invasion phenotype, (1:500) in TH staining
AntibodyAlexa Fluor 555 goat anti-mouse IgG2aInvitrogenCat#A21137(1:1000) in invasion phenotype, (1:500) in TH staining
Commercial assay, kitAgencourt AMPure XPBeckman CoulterCat#A63880
Commercial assay, kitKAPA HiFi HotStart ReadyMixRocheCat#07958927001
Commercial assay, kitNextera XT DNA Library Preparation KitIlluminaCat#FC-131-1096
Peptide, recombinant proteinDispase ISigma-AldrichCat#D4818
Peptide, recombinant proteinCollagenase IThermo Fisher ScientificCat#17100017
Peptide, recombinant proteinSuperScript II Reverse TranscriptaseThermo Fisher ScientificCat#18064022
Chemical compound, drugTrypsin-EDTA (0.5%)Thermo Fisher ScientificCat#15400054
Chemical compound, drugTriton X-100 SolutionSigma-AldrichCat#93443-100Ml
Chemical compound, drugParaformaldehydeSigma-AldrichCat#252549
Chemical compound, drugActinomycin DSigma-AldrichCat#A1410
Chemical compound, drugEDTASigma-AldrichCat#E6511
Chemical compound, drugDAPISigma-AldrichCat#D9542
Chemical compound, drugMgCl2 (1 M)Thermo Fisher ScientificCat#AM9530G
Chemical compound, drugRNaseOUTThermo Fisher ScientificCat#10777019
Chemical compound, drugBetaineSigma-AldrichCat#B0300
Chemical compound, drugDTT (100 mM Solution)Thermo Fisher ScientificCat#707265ML
Chemical compound, drugBuffer EBQIAGENCat#19086
Chemical compound, drugRapiClear 1.47Sunjin LabCat#RC147001
Sequence-based reagentdNTP MixPromegaCat#U1511
Sequence-based reagentPrimers, gRNAs, oligos, gBlocksIntegrated DNA Technologies (IDT)
Strain background (D. melanogaster)w[1118] (w1118)Kaempf et al., 2026NA
Strain background (D. melanogaster)w[1118] M{w+} (w1118 w+)Kaempf et al., 2026NA
Genetic reagent (D. melanogaster)w[1118] TI{w[+]=white-STAR}Pink1[KO-WS]/FM7a (Pink1KO-WS/y)Kaempf et al., 2026NA
Genetic reagent (D. melanogaster)Yw;; UAS-His2Av::eGFP.VK27/TM3Sb (UAS- His2Av::eGFP)This studyNA
Genetic reagent (D. melanogaster);;MZ0709-Gal4Ito et al., 1995NA
Genetic reagent (D. melanogaster)y[1] w[*]; P{w[+mC]=UAS-mCD8::GFP.L}LL5, P{UAS-mCD8::GFP.L}2 (UAS-mCD8-GFP)Lee and Luo, 1999BDSC_5137
Genetic reagent (D. melanogaster)w[*]; P{y[+t7.7] w[+mC]=GMR-56-GAL4}attP24/CyO (GMR-56-Gal4)Jenett et al., 2012BDSC_77469
Genetic reagent (D. melanogaster)y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF01672}attP2 (Pink1RNAi)Perkins et al., 2015BDSC_31170
Genetic reagent (D. melanogaster)w[*]; P{w[+mC]=UAS-Pink1.C}A (UAS-Pink1)Bloomington Drosophila Stock CenterBDSC_51648
Genetic reagent (D. melanogaster)w[1118]; P{y[+t7.7] w[+mC]=GMR57C10-GAL4}attP2 (nSyb-Gal4)Jenett et al., 2012BDSC_39171
Genetic reagent (D. melanogaster)y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01715}attP40 (Vps13RNAi)Perkins et al., 2015BDSC_38270
Genetic reagent (D. melanogaster)y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01858}attP40 (Vps35RNAi)Perkins et al., 2015BDSC 38944
Genetic reagent (D. melanogaster)y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS05488}attP40 (CG17660RNAi)Perkins et al., 2015BDSC_67022
Genetic reagent (D. melanogaster)y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF03249}attP2 (ProcRNAi)Perkins et al., 2015BDSC_29570
Genetic reagent (D. melanogaster)y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC05229}attP40 (fizRNAi)Perkins et al., 2015BDSC_62222
Genetic reagent (D. melanogaster)y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF01165}attP2 (CG15011RNAi)Perkins et al., 2015BDSC_31589
Genetic reagent (D. melanogaster)y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC04857}attP40 (CG17612RNAi)Perkins et al., 2015BDSC_57540
Genetic reagent (D. melanogaster)y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC05717}attP40 (PrpkRNAi)Perkins et al., 2015BDSC_64844
Genetic reagent (D. melanogaster)y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.HMJ22434}attP40 (LnpkRNAi)Perkins et al., 2015BDSC_64036
Genetic reagent (D. melanogaster)y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01827}attP2 (PIG-BRNAi)Perkins et al., 2015BDSC_38359
Genetic reagent (D. melanogaster)y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01840}attP2/TM3, Sb[1] (spagRNAi)Perkins et al., 2015BDSC_38371
Genetic reagent (D. melanogaster)y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00070}attP2 (RelRNAi)Perkins et al., 2015BDSC_33661
Genetic reagent (D. melanogaster)y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC04640}attP40 (Atac1RNAi)Perkins et al., 2015BDSC_57250
Genetic reagent (D. melanogaster)y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.GLV21056}attP2 (l(3)07882RNAi)Perkins et al., 2015BDSC_35691
Genetic reagent (D. melanogaster)y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00529}attP2 (PldRNAi)Perkins et al., 2015BDSC_32839
Genetic reagent (D. melanogaster)y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS02243}attP2 (Rpp25RNAi)Perkins et al., 2015BDSC_41679
Genetic reagent (D. melanogaster)y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.HMC03184}attP40 (GMFRNAi)Perkins et al., 2015BDSC_51452
Genetic reagent (D. melanogaster)y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01358}attP2/TM3, Sb[1] (Atg7RNAi)Perkins et al., 2015BDSC_34369
Genetic reagent (D. melanogaster)y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.HMJ03126}attP40 (Ada2aRNAi)Perkins et al., 2015BDSC_50905
Genetic reagent (D. melanogaster)y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC06224}attP2 (CG12773RNAi)Perkins et al., 2015BDSC_65949
Genetic reagent (D. melanogaster)y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00328}attP2 (CG7627RNAi)Perkins et al., 2015BDSC_32337
Genetic reagent (D. melanogaster)y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00870}attP2 (DarkRNAi)Perkins et al., 2015BDSC_33924
Genetic reagent (D. melanogaster)y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF03275}attP2 (CG3703RNAi)Perkins et al., 2015BDSC_29596
Genetic reagent (D. melanogaster)y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01175}attP2/TM3, Sb[1] (NiPp1RNAi)Perkins et al., 2015BDSC_34696
Genetic reagent (D. melanogaster)y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.HMJ22813}attP40 (CG31370RNAi)Perkins et al., 2015BDSC_60456
Genetic reagent (D. melanogaster)y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.HMJ23526}attP40 (IrbpRNAi)Perkins et al., 2015BDSC_61942
Genetic reagent (D. melanogaster)y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02313}attP2 (CG32532RNAi)Perkins et al., 2015BDSC_26750
Genetic reagent (D. melanogaster)y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.HMJ30013}attP40/CyO (RhauRNAi)Perkins et al., 2015BDSC 62936
Genetic reagent (D. melanogaster)y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.HM05047}attP2 (hfwRNAi)Perkins et al., 2015BDSC_28561
Genetic reagent (D. melanogaster)y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF02192}attP2 (achiRNAi)Perkins et al., 2015BDSC_31903
Genetic reagent (D. melanogaster)y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.HMJ23972}attP40/CyO (TTLL6ARNAi)Perkins et al., 2015BDSC_62488
Genetic reagent (D. melanogaster)y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMC03076}attP2 (NosRNAi)Perkins et al., 2015BDSC_50675
Genetic reagent (D. melanogaster)w[1118]; P{w[+mC]=UAS-Nos.L}2 (UAS-Nos)Bloomington Drosophila Stock CenterBDSC_56823
Recombinant DNA reagentpUASTattBBischof et al., 2007https://www.flyc31.org
Software, algorithmFijiSchindelin et al., 2012RRID:SCR_002285https://imagej.net/Fiji
Software, algorithmGraphPad PrismGraphPad SoftwareRRID:SCR_002798https://www.graphpad.com/scientific-software/prism/
Software, algorithmPython (v3.7.3)PythonRRID:SCR_008394http://www.python.org/
Software, algorithmscanpyWolf et al., 2018RRID:SCR_018139https://github.com/theislab/scanpy
Software, algorithmDESeq2Love et al., 2014RRID:SCR_015687https://bioconductor.org/packages/release/bioc/html/DESeq2.html
Software, algorithmClampfitMolecular Deviceshttps://www.moleculardevices.com
Software, algorithmAxoscopeMolecular Deviceshttps://www.moleculardevices.com
Software, algorithmIgor ProWaveMetricsRRID:CR_000325https://www.wavemetrics.com/products/ igorpro/igorpro.htm
Software, algorithmFACSDiva software v9.0.1BD BiosciencesRRID:SCR_001456https://www.bdbiosciences.com/en-be/products/software/instrument-software/bd-facsdiva-software
Software, algorithmnf-core/rnaseqPatel et al., 2020https://nf-co.re/rnaseq/3.14.0/
Software, algorithmfastpChen et al., 2018RRID:SCR_016962https://github.com/OpenGene/fastp
Software, algorithmRStudioRStudio, PBC/Posit
Software, algorithmBioRenderBioRenderhttps://BioRender.com
Software, algorithmSTARDobin et al., 2013RRID:SCR_004463https://github.com/alexdobin/STAR
Software, algorithmHarmonyKorsunsky et al., 2019RRID:SCR_022206https://github.com/immunogenomics/harmony

Data availability

RNA sequence data were deposited in GEO (accession number GSE322929). All data generated or analyzed during this study are included in the manuscript and supporting files; source data file has been provided for all figures in Source data 1.

The following data sets were generated
    1. Ghezzi L
    2. Kuenen S
    3. Pech U
    4. Schoovaerts N
    5. Kilic A
    6. Poovathingal S
    7. Davie K
    8. Lamote J
    9. Praschberger R
    10. Verstreken P
    (2026) NCBI Gene Expression Omnibus
    ID GSE322929. Parkinson's Disease-Associated Pink1 Loss Disrupts Ensheathing Glia And Causes Dopaminergic Neuron Synapse Loss.
    https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE322929
The following previously published data sets were used
    1. Janssens J
    2. Pech U
    3. Aerts S
    4. Verstreken P
    (2025) NCBI Gene Expression Omnibus
    ID GSE228843. Rescuing early Parkinson-induced hyposmia prevents dopaminergic system failure [fruit fly].
    https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE228843

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Article and author information

Author details

  1. Lorenzo Ghezzi

    1. VIB-KU Leuven Center for Neuroscience, Leuven, Belgium
    2. KU Leuven, Department of Neurosciences, Leuven Brain Institute, Leuven, Belgium
    Contribution
    Conceptualization, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6940-886X

  2. Sabine Kuenen

    1. VIB-KU Leuven Center for Neuroscience, Leuven, Belgium
    2. KU Leuven, Department of Neurosciences, Leuven Brain Institute, Leuven, Belgium
    Contribution
    Investigation, Visualization, Methodology, Writing – review and editing
    Competing interests
    No competing interests declared

  3. Ulrike Pech

    1. VIB-KU Leuven Center for Neuroscience, Leuven, Belgium
    2. KU Leuven, Department of Neurosciences, Leuven Brain Institute, Leuven, Belgium
    Contribution
    Funding acquisition, Investigation, Methodology
    Competing interests
    No competing interests declared

  4. Nils Schoovaerts

    1. VIB-KU Leuven Center for Neuroscience, Leuven, Belgium
    2. KU Leuven, Department of Neurosciences, Leuven Brain Institute, Leuven, Belgium
    Contribution
    Investigation, Methodology
    Competing interests
    No competing interests declared

  5. Ayse Kilic

    1. VIB-KU Leuven Center for Neuroscience, Leuven, Belgium
    2. KU Leuven, Department of Neurosciences, Leuven Brain Institute, Leuven, Belgium
    Contribution
    Investigation, Methodology
    Competing interests
    No competing interests declared

  6. Suresh Poovathingal

    1. VIB-KU Leuven Center for Neuroscience, Leuven, Belgium
    2. VIB-KU Leuven Center for Neuroscience, Single Cell and Microfluidics Expertise Unit, Leuven, Belgium
    Contribution
    Investigation, Methodology
    Competing interests
    No competing interests declared

  7. Kristofer Davie

    1. VIB-KU Leuven Center for Neuroscience, Leuven, Belgium
    2. VIB-KU Leuven Center for Neuroscience, Single Cell Bioinformatics Unit, Leuven, Belgium
    Contribution
    Writing – original draft
    Competing interests
    No competing interests declared

  8. Jochen Lamote

    1. VIB-KU Leuven Center for Neuroscience, Leuven, Belgium
    2. VIB Flow Core Leuven, VIB Technologies, Leuven, Belgium
    Contribution
    Data curation, Software, Investigation, Visualization, Methodology, Writing – original draft
    Competing interests
    No competing interests declared

  9. Roman Praschberger

    1. VIB-KU Leuven Center for Neuroscience, Leuven, Belgium
    2. KU Leuven, Department of Neurosciences, Leuven Brain Institute, Leuven, Belgium
    3. Medical University of Innsbruck, Institute of Human Genetics, Innsbruck, Austria
    Contribution
    Conceptualization, Software, Formal analysis, Supervision, Funding acquisition, Investigation, Visualization, Writing – original draft, Writing – review and editing
    For correspondence
    roman.praschberger@i-med.ac.at
    Competing interests
    No competing interests declared

  10. Patrik Verstreken

    1. VIB-KU Leuven Center for Neuroscience, Leuven, Belgium
    2. KU Leuven, Department of Neurosciences, Leuven Brain Institute, Leuven, Belgium
    Contribution
    Conceptualization, Supervision, Funding acquisition, Writing – original draft, Writing – review and editing
    For correspondence
    patrik.verstreken@kuleuven.be
    Competing interests
    P.V. is the scientific founder of Jay Therapeutics
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5073-5393

Funding

KU Leuven (https://ror.org/05f950310)

  • Patrik Verstreken

European Research Council

  • Patrik Verstreken

Chan Zuckerberg Initiative

  • Patrik Verstreken

Vlaamse Overheid

  • Patrik Verstreken

Koning Boudewijnstichting

  • Patrik Verstreken

Fonds Wetenschappelijk Onderzoek

  • Ayse Kilic
  • Patrik Verstreken

European Molecular Biology Organization

  • Roman Praschberger

Deutsche Forschungsgemeinschaft

  • Ulrike Pech

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

Acknowledgements

We thank the Vlaams Supercomputer Centrum, the VIB Nucleomics and Bioimaging Cores, and the Bloomington Drosophila Stock Center (NIH P40OD018537). We are grateful to the members of the Verstreken lab for valuable discussions. Research support was provided by Leuven University Fund and Opening the Future, ERC, the Chan Zuckerberg Initiative, a Methusalem grant from the Flemish government, KU Leuven BOF, Fund Jacqueline Cigrang administered by the KBS, the KBS, Fund Generet, and FWO Vlaanderen to PV; an EMBO long-term fellowship to RP; a DFG fellowship to UP; and an FWO PhD mandate to AK. Cartoons/models/illustrations were created in https://BioRender.com. PV is an alumnus of the FENS-Kavli Network of Excellence.

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© 2025, Ghezzi et al.

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  1. Lorenzo Ghezzi
  2. Sabine Kuenen
  3. Ulrike Pech
  4. Nils Schoovaerts
  5. Ayse Kilic
  6. Suresh Poovathingal
  7. Kristofer Davie
  8. Jochen Lamote
  9. Roman Praschberger
  10. Patrik Verstreken
(2026)
Parkinson’s disease-associated PINK1 loss disrupts ensheathing glia and causes dopaminergic neuron synapse loss
eLife 14:RP105386.
https://doi.org/10.7554/eLife.105386.3

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