Glycerol 3-phosphate acyltransferase exacerbates α-synuclein-induced toxicity by increasing lipid peroxidation

Domain: biology
Published: 2026-01-19
Editorial outcome: minor_revision

Abstract
Although multiple cellular pathways have been implicated in α-Synuclein (α-syn)-associated Parkinson’s disease (PD), the role of lipid metabolism remains elusive. In this study, we identify Drosophila mino, which encodes the mitochondrial isoform of the lipid synthesis enzyme glycerol 3-phosphate acyltransferase (GPAT), as a potent modifier of α-syn. Silencing the expression of mino significantly suppresses α-syn-induced PD phenotypes in Drosophila, including dopaminergic neuronal loss and locomotion defects as well as circadian rhythm-related activities, whereas mino overexpression yields opposite effects. Mechanistically, we find that mino modulates the levels of mitochondrial reactive oxygen species and lipid peroxidation. Importantly, treatment of α-syn-expressing flies with FSG67, a GPAT inhibitor of glycerol 3-phosphate acyltransferase, reproduces the benefits of mino knockdown. FSG67 also inhibits α-syn aggregation and lipid peroxidation in mouse primary neurons treated with α-syn preformed fibrils. Our study elucidates an important factor contributing to α-syn toxicity and offers a therapeutic direction for PD.

Introduction
Parkinson’s disease (PD) is a prevalent neurodegenerative disease that is characterized clinically by motoric deficits, including bradykinesia, tremors, and rigidity. The principal neuropathology underlying PD is the loss of dopaminergic (DA) neurons in the substantia nigra pars compacta of the midbrain, which results in the disruption of the nigrostriatal pathway leading to movement disorders. Accompanying the DA neurodegeneration is the presence of intraneuronal inclusions known as Lewy bodies (LBs), which are enriched with α-synuclein (α-syn)1,2. Rare mutations and copy number variations in the α-syn-encoding gene SNCA, such as A30P and A53T, are causative for monogenic forms of PD3–5. Genome-wide association studies have established an association between genetic variations in the SNCA gene and the risk for PD6. However, the effects of these genetic variations are modest compared to other PD risk genes, like GBA1 or LRRK27, potentially attributable to the polygenic mode of inheritance and interactions with genetic modifiers of SNCA8–10.

Lipid dyshomeostasis is increasingly recognized as a key player in PD pathogenesis. LBs are not merely aggregates of α-syn but contain abundant lipids from damaged organelles, which implicate lipid dyshomeostasis as a mechanism in LB biogenesis and PD pathogenesis11,12. Several lipid metabolism genes are linked to PD, including PLA2G6, GBA, LRRK2, Parkin, SMPD1, SCARB2, DGKQ, and SYNJ113–15. Lipidomic irregularities in the polyunsaturated fatty acids, glycerophosphatidylcholine, diacylglycerol, and triglycerides have been observed in the serum and brain tissues of PD patients14,16–18.

The N-terminal domain of α-synuclein has affinity for lipid membranes, and studies have shown that mutations A30P, E46K, and G51D in this region can alter the protein’s oligomeric state19–21. α-syn deficiency disturbs brain lipid metabolism, as evidenced by changes in palmitate uptake and neutral lipid content. This disruption is associated with alterations in the esterification of arachidonic acid and docosahexaenoic acid into phospholipids22–24. Excessive α-syn induces the accumulation of lipid droplets in yeast25, and promotes the synthesis of polyunsaturated ether phospholipids in induced pluripotent stem cell-derived human midbrain dopaminergic neurons, leading to lipid peroxidation and increased sensitivity to ferroptosis, a form of cell death marked by iron-dependent accumulation of lipid peroxides26,27.

Lipid-metabolizing enzymes affect α-syn aggregation and associated neurotoxicity. For example, stearoyl-CoA desaturase (SCD) regulates the unsaturation level of fatty acids and affects α-syn oligomeric composition in yeast, cells, and transgenic mice28–32; fatty acid CoA synthetase long-chain family member 4 (ACSL4) regulates fatty acids partitioning into the fatty acyl-CoA pool and influences lipid peroxidation and ferroptosis that are linked to α-syn neurotoxicity26,33,34. Lysophosphatidic acid acyltransferase (LPAAT), which converts lysophospholipids to phospholipids and helps to reconstitute phosphatidylcholine, is upregulated in postmortem PD brains and cultured neurons overexpressing SNCA E35K/E46K/E61K mutants35. The lipase LIPE regulates the equilibrium between α-syn tetramer and monomer, which affects α-syn neurotoxicity36. Several PD models reveal that modulating fatty acid and lipid metabolism genes, including LPCAT, SCD, and LIPE, may reverse α-syn aggregation and associated phenotypes30,35,36. YTX-7739, an SCD inhibitor, has progressed to phase 1 clinical trials29. Uncovering the lipid involvement in PD pathogenesis is therefore critical, as it paves the way for therapeutic strategies.

In this study, we used transgenic Drosophila overexpressing α-syn as a model for genetic screening, and identify mino, which encodes the mitochondrial isoform of the lipid synthesis enzyme glycerol 3-phosphate acyltransferase (GPAT), as a modifier of α-syn. We find that neuronal silencing of mino mitigates α-syn-associated PD-like phenotypes in Drosophila, including dopaminergic neuronal loss and locomotion defects, whereas mino overexpression yields opposite effects. Neuronal silencing of mino in Drosophila PD model is linked to reduced levels of mitochondrial reactive oxygen species, membrane lipid peroxidation, and less α-syn higher-order oligomers in the brain. Knocking down other GPAT-encoding genes Gpat4, or CG15450 reveals a common role of GPAT in modulating α-syn neurotoxicity. Treatment of α-syn-expressing flies with FSG67, a GPAT inhibitor, reproduces the benefits of mino/GPAT knockdown. FSG67 inhibits α-syn fibril aggregation and lipid peroxidation in mouse primary neurons treated with α-syn preformed fibrils. Taken together, our study elucidates an important factor/pathway contributing to α-syn toxicity and offers a novel therapeutic direction for PD.

Results
Drosophila screen identifies mino RNAi as a suppressor of α-syn neurotoxicity

To identify modifiers of α-syn, we performed a genetic screen in a Drosophila model of synucleinopathy, where we overexpressed human wild-type α-syn in the photoreceptor (PR) neurons R1-R6. Overexpression of α-syn in PR neurons induced vacuole formation in the lamina layer, where PR neurons form synapses with downstream lamina monopolar neurons37. To identify candidate genes for screening, we utilized a delta SVM model to predict single-nucleotide polymorphisms (SNPs) with differential transcription factor binding among 83 human PD risk loci from the Parkinson’s disease genome-wide association study locus browser (v1.9)38,39. Based on the location of SNPs, we manually selected 1–3 nearest genes for each locus. Subsequently, we ordered available RNAi or dCas9/gRNA-VPR overexpression lines from the Bloomington Drosophila Stock Center (BDSC). These lines targeted the Drosophila orthologues of the selected human genes, which were identified using the DIOPT OrthologFinder40. Finally, we crossed 107 lines targeting 92 genes with the Drosophila synucleinopathy model to examine whether they can influence α-syn-induced vacuole formation in the lamina41 (Supplementary Data 1).

From 107 RNAi and overexpression fly lines, we identified five RNAi lines (targeting Ggamma1, mino, nonC, RpII215, or Src64B) and nine overexpression lines (targeting Acbp1, Bap170, bnl, CG5214, CG7461, Psn, Pu, SdhC, and wg) that suppressed vacuole formation in α-syn flies by more than 2-fold at an adjusted P value of 0.01 (Fig. 1a). We subsequently selected mino, CG5214, CG7461, SdhC with roles in energy and lipid metabolism, to test if their RNAi or overexpression could mitigate the climbing declines in a pan-neuronal α-syn (GAL4) fly model which expresses α-syn (nSyb-GAL4>SNCA) (Supplementary Fig. 1A). mino RNAi alleviate the climbing phenotype in α-syn flies for up to 8 weeks post-eclosion (Fig. 1b and Supplementary Fig. 1A, B). This was also observed in another pan-neuronal α-syn (QF2) fly model, which expresses higher levels of α-syn by nSyb-QF2>SNCA and shows accelerated decline of climbing abilities (Fig. 1c, d). Overexpressing mino using an upstream activating sequence (UAS) insertion line minoEY00734 exacerbates α-syn-induced locomotor impairments (Fig. 1d). Analysis of brain-extracted mRNA showed a 50% reduction and a fourfold increase of mino transcripts by mino RNAi and overexpression, respectively (Supplementary Figs. 1B and 2K). These results suggest a role for mino in modulating α-syn neurotoxicity.

Pan-neuronal overexpression of α-syn is toxic to DA neurons42. Among the DA neuron clusters in the fly brain, the protocerebral anterior medial (PAM) cluster contains more than 100 tyrosine hydroxylase-positive (TH+) DA neurons and is involved in startle-induced negative geotaxis43,44. We utilized the Labkit pixel classification to quantify the PAM TH+ neurons (Supplementary Fig. 1C)45. α-syn (GAL4) model exhibits a less severe phenotype with a loss of PAM TH+ neurons evident at day 49 but not at day 32, compared to control flies (nSyb>EGFP RNAi) (Fig. 1e, f). In contrast, the α-syn (QF2) model shows an early toxicity with neuronal loss at day 32 compared to control flies (nSyb-QF2, nSyb>EGFP RNAi) (Supplementary Fig. 1D). When housed at a higher temperature of 29 °C, the reduction of PAM TH+ neurons in α-syn (QF2) flies occurs earlier at day 21 (Fig. 1g, h). Although varying α-syn expression levels or temperatures are associated with differences in the timing of neuronal loss, mino RNAi mitigates PAM TH+ neuronal loss in both models (Fig. 1g, h). In contrast, mino overexpression exacerbates the loss of PAM TH+ neurons in α-syn (QF2) flies (Fig. 1g, h). The protocerebral posterior medial 1/2 (PPM1/2), posterior lateral protocerebrum (PPL1), and dorsal medial (DM) clusters did not show DA neuron loss in α-syn (QF2) flies at day 21 (Supplementary Fig. 1E). Although we observed a lower number of TH+ cells in α-syn (QF2) flies upon eclosion, the effect of mino on α-syn-associated neurodegeneration is likely manifested during the post-developmental stage (Supplementary Fig. 1F). α-syn (QF2) model was used for all the subsequent studies.

Several α-syn PD models have been reported with disruptions in a circadian rhythm-associated locomotor behavior46–48. Similarly, we observed that α-syn induces an accelerated decline in daily activities, as shown by the disappearance of the morning peak and reduced amplitude at the evening peak (Fig. 2a–c). This decline is alleviated in the presence of neuronal mino RNAi (Fig. 2a–c). Although mino RNAi restored the evening peak’s average intensity, it did not lead to recovery of the morning peak (Supplementary Fig. 2A, B). In the absence of α-syn, neither mino RNAi nor its overexpression affects the daily activities (Fig. 2a–c).

Neuron–glia metabolic crosstalk is associated with energy homeostasis and neurodegeneration49. We further explored whether the changes of mino in glia also affect the daily locomotor activities of α-syn flies. Glia-specific mino RNAi did not show obvious α-syn-modifying effects, whereas simultaneous mino RNAi expression in neurons and glia mitigates the decline in daily locomotor activities in α-syn flies (Supplementary Fig. 2C–F). From mino insertion mutants, we identified minof04927, which shows a reduction of mino transcripts level to 16% and 50% of control flies in homozygote and heterozygote adult, respectively (Supplementary Fig. 2G, H, J). minof04927 flies exhibit increased transcription of transposons flamenco-2, 1731, and 42AB (Supplementary Fig. 2H), in agreement with its role in regulating primary transposon silencing in germline50, as well as reduced PAM TH+ neurons compared to control flies (Supplementary Fig. 2I, L), suggesting an adverse effect of systematic mino insufficiency. We integrated minof04927 into α-syn model and found that α-syn flies with homozygous minof04927 did not show significant differences of PAM TH+ neurons compared to α-syn flies (Supplementary Fig. 2I, L). However, minof04927/+ mitigates the PAM TH+ neuronal loss and the decline of daily locomotor activities in α-syn flies (Supplementary Fig. 2N, O), suggesting that a limited systematic insufficiency of mino may be protective against α-syn toxicity.

Taken together, our results identified mino as a modifier of α-syn in two Drosophila models of PD.

mino modulates α-syn-induced lipid peroxidation and associated cell death

mino encodes glycerol 3-phosphate acyltransferase which catalyzes the acylation of acyl-CoA to glycerol-3-phosphate contributing to the synthesis of phospholipids and triglycerides51. Previous studies have shown that α-syn oligomerization and toxicity could be enhanced by the interaction with phospholipid membranes, and that α-syn alters the lipid profiles or is associated with lipid peroxidation17,26,27,52,53. Thus, we examined lipid peroxidation in α-syn fly brains and if mino could affect it. To analyze lipid peroxidation levels of neuronal membranes using BODIPY C11, we labeled neuronal membranes with a cell membrane-localized infrared fluorescent protein (mIFP)54. Although we separated the imaging sessions for BODIPY C11 and mIFP to minimize bleed-through, we found that BODIPY C11-stained brains without the mIFP transgene have emission in the infrared channel when excited by 640 nm laser; therefore, the presence of mIFP fluorescence was unable to differentiate between neuronal or glial membranes if co-stained with BODIPY C11 (Supplementary Fig. 3A, B). When flies were cultured at 25 °C for 3 weeks, the membrane lipid peroxidation levels in the brain optic lobe were not affected by α-syn (Supplementary Fig. 3C, D). However, the lipid peroxidation levels of α-syn fly brains were further decreased by mino RNAi and increased by mino overexpression (Supplementary Fig. 3C, D). When flies were raised at 29 °C for 3 weeks, α-syn caused an increase in membrane lipid peroxidation levels, which were reduced by mino RNAi and increased by mino overexpression (Fig. 3a, b). In the absence of α-syn, neither mino RNAi nor its overexpression affects the lipid peroxidation levels (Fig. 3a, b). Thus, the effect of mino on lipid peroxidation levels is dependent on α-syn.

We investigated whether mino’s effects on α-syn-associated lipid peroxidation correlate with changes in cell death in the optic lobe. As a positive control, we treated flies with H2O2, which induces positive TUNEL signals (Fig. 3n). TUNEL-labeled cell death in the optic lobe of α-syn fly brains was reduced by mino RNAi and increased by mino overexpression (Fig. 3c, d). Neither mino RNAi nor its overexpression alone induces TUNEL-labeled cell death in optic lobes (Fig. 3c, d). We did not observe positive staining of cleaved caspase-3 or cleaved Dcp-1 in α-syn fly brains (Fig. 3e and Supplementary Fig. 3E, H), whereas the hs-hid (heat shock promoter-head involution defective) third instar larva brain shows positive staining after heat shock (Supplementary Fig. 3F, G). Similarly, we observed the cleavage of apoptosis reporters Apoliner55 and hPARP1-Venus56 in hs-hid larva brains upon heat shock but not in α-syn fly brains (Supplementary Fig. 3I–L). The cleavage of hPARP1-Venus occurs only in one brain among 50 brains without α-syn examined (Supplementary Fig. 3M). Given the limitations of these approaches, we cannot completely exclude the possibility of apoptosis in α-syn fly brains.

Neuronal α-syn causes LDs accumulation in glia

Lipid droplets (LDs) accumulation is a strategy by which cells manage stress, including protection against lipid peroxidation57. We examined if LDs accumulate in fly brains with pan-neuronal α-syn using BODIPY 493/503. Replacing Triton X-100 by saponin during the fixation of cultured cells reportedly could stabilize the LDs for staining58. In contrast to cultured cells, we observed that 0.1% Triton X-100 in the fixative could resolve the LDs fluorescence from the background signals in fly brains (Supplementary Fig. 4A). In 3-week-old control fly brains without α-syn, we observed massive LDs in central brains but not in optic lobe (Fig. 4a). However, in fly brains with pan-neuronal α-syn, the optic lobe also accumulates massive LDs (Fig. 4a). We quantified the time-dependent accumulation of LDs within the optic lobe cortex from day 1 to week 7 (Fig. 4b, c). In flies with and without α-syn, LDs could be observed at day 1 post-eclosion (Fig. 4b, c), but were reduced after week 1 (Fig. 4b), which is similar to the findings of LD dynamics in fly retina59. In flies without α-syn, no massive LDs were observed up to week 6 examined (Fig. 4b, c). However, in fly brains with α-syn, LDs showed time-dependent accumulation from week 1 to 6 examined (Fig. 4b, c). To determine if LDs were localized in neurons or glia, we expressed EGFP-tagged TAG lipase bmm (UAS-bmm.EGFP) either in glia or neurons of fly brains and co-stained the LDs with LipidTOX. In α-syn fly brains, LDs colocalizes with glial bmm but not with neuronal bmm (Fig. 4d). Genomic-tagged bmm.GFP could be detected surrounding the peri-brain fat bodies and at variable portions of LDs in the optic lobe of the day 1 fly brain (Supplementary Fig. 4B). We expressed GFP either in glia or neurons in fly brains with α-syn and found that LDs localize outside neuronal GFP but are enclosed within glial GFP (Supplementary Fig. 4C).

To determine if the LDs were coated by Drosophila Perilipin (encoded by Lsd-1 and Lsd-2), using genomic-tagged Lsd-1.GFP we found that Lsd-1.GFP was detectable enclosing the peri-brain fat bodies, but not on the LDs of α-syn brains or the central brain (Supplementary Fig. 4D), which confirmed the tissue specificity of Lsd-160. From the public fly brain or head RNA sequencing datasets61–63, we found that fly brain preferentially expressed Lsd-2 and that Lsd-2 is mainly expressed in glia and head sensory neurons but little in brain central nervous system (CNS) neurons (Supplementary Fig. 4E–I). We overexpressed Lsd-2 or triglyceride lipase bmm either in glia or neurons and found that glial bmm expression, but not neuronal expression, suppressed the α-syn-associated LDs accumulation (Fig. 4e, f). On the other hand, glial but not neuronal Lsd-2 overexpression increased the α-syn-associated LDs (Fig. 4g, h). These results confirmed the glial localization of LDs. The presence of LDs in fly photoreceptor neuron expressing α-syn has been reported60. Fly head or brain RNA-sequencing datasets61–63 show that in addition to Lsd-2, mdy, the fly brain-expressing homolog of DGAT catalyzing the last step of triglycerides synthesis, are expressed in glia and head sensory neurons but little in CNS neurons (Supplementary Fig. 4E–I). These data align with the localization of LDs in glia of fly brains and in α-syn-expressing photoreceptor neurons in retina60.

LDs have been associated with an antioxidant role that retards α-syn neuronal toxicity59,64. We examined if modulating glial LDs affect neuronal α-syn-associated neurodegeneration. The α-syn-associated decrease of PAM TH+ neurons was not affected by bmm or Lsd-2 overexpression in glia or neurons (Fig. 4i, j). The TUNEL-labeled cell death in the optic lobe of α-syn fly brains was not affected by Lsd-2 overexpression in glia or neurons, or by bmm overexpression in glia. However, bmm overexpression in neurons mildly increased the cell death in α-syn fly brains (Fig. 4k–m).

Taken together, our results indicate that fly brains with pan-neuronal α-syn accumulate LDs predominantly in glia. Due to differences in the localization between glial LDs and neuronal α-syn, we were unable to address the possibility that LDs with specific compositions, or in different cellular contexts, could potentially modify α-syn aggregation or toxicity in ways not captured by our assays.

TCA cycle metabolites isocitrate and citrate increased in α-syn fly brains

Glia Lsd-2 overexpression causes increased LDs in pan-neuronal α-syn fly brains in contrast to control brains without α-syn (Fig. 4g, h). Given the reported pathway that fatty acids synthesized in neurons are transported to glia and stored as LDs59,65, we reasoned that α-syn fly brains may have increased de novo synthesis of fatty acids, possibly from citrate (Fig. 5a). In the tricarboxylic acid (TCA) cycle, citrate is converted to α-ketoglutarate, which is further converted to succinyl-CoA by α-ketoglutarate dehydrogenase (OGDH) complex, whose dysfunction or deficiency is implicated in PD66–68. A blockage of OGDH may cause the build-up of metabolites in preceding steps (Fig. 5a). To address these possibilities, we conducted a short-chain fatty acids (SCF) metabolomics assay on dissected 3-week-old fly brains (10 brains pooled, n=1, no technical or biological replicates) with or without pan-neuronal α-syn (Fig. 5b and Supplementary Data 2, Supplementary Data 6). Among the TCA cycle metabolites, isocitrate showed a ten-fold increase, and citrate showed a fivefold increase in α-syn fly brains compared to brains without α-syn, whereas the increase is less than 1.5-fold for malate, fumarate, and succinate. Lactate showed a threefold increase, consistent with the increased lactate dehydrogenase level in α-syn-expressing fly brains (Fig. 5a, b). Glycolate, which was reported as TH+ neuron-protective metabolite associated with DJ-169, is reduced to 36% compared to brains without α-syn.

ATP citrate lyase, encoded by ACLY in humans and ATPCL in flies, catalyzes the conversion of citrate to oxaloacetate and acetyl-CoA, which links carbohydrate to lipid metabolism70 (Fig. 5a). A reported proteomics analysis of α-syn-expressing fly head showed a 26-fold decrease of ATPCL isoform E2QCF1 and a 1.5-fold increase of isoform Q7KN8571. E2QCF1 differs from Q7KN85 only by the absence of phosphorylation-regulated peptide ALSPTAAKPIKLPPISA, a region also differs between fly ATPCL and human ACLY (Supplementary Fig. 5A). We detected the expression of isoform Q7KN85 but not E2QCF1 in the mRNA of fly brains (Supplementary Fig. 5B). The mRNA and protein levels of ATPCL in α-syn fly brains are comparable to those without α-syn (Fig. 3e and Supplementary Fig. 5B–D).

Next, we ask if knockdown or overexpression of neuronal mino affect lipid staining in fly brains. Although the massive LDs were not observed from the BODIPY 493/503-stained background signal in fly brains without α-syn, neuronal mino overexpression was associated with an increase in the background signal in the optic lobe cortex, whereas neuronal mino RNAi was associated with a reduction of the background signal (Fig. 5c, d). On the other hand, in fly brains with α-syn and BODIPY 493/503-stained LDs, neuronal mino knockdown caused an increase in LDs levels, whereas neuronal mino overexpression did not affect LDs levels (Fig. 5e, f). These mino-associated changes of lipid staining suggest a possibility that neuronal mino may affect the membrane lipid levels in normal fly brains and LDs levels in α-syn fly brains, likely involves the neuron–glia transport and deposition of fatty acids into lipids which deserves further investigation.

We conducted lipidomic analyses of fly brains to explore the possible lipid differences associated with α-syn and mino (Supplementary Fig. 6 and Supplementary Data 3 and 6). Phospholipids constitute the largest proportion (40.05%) of total fly brain lipids (Supplementary Fig. 6A). The percentage of phospholipids increased with α-syn expression (log2(FC)=0.15). This α-syn effect seems to be mitigated in the presence of mino RNAi (log2(FC)=0.07) and enhanced when mino is overexpressed (log2(FC)=0.17) (Supplementary Fig. 6A). Phosphatidylcholine (PC) and phosphatidylethanolamine (PE), the two most abundant species comprising over 95% of total brain phospholipids, exhibited similar trends in response to α-syn expression and mino RNAi (Supplementary Fig. 6B). PC and PE in α-syn-expressing brains showed increased presence of monounsaturated fatty acids (MUFAs) and decreased presence of polyunsaturated fatty acids (PUFAs) (Supplementary Fig. 6C, D). α-syn fly brains showed increased transcripts of Pcyt1 and Pect, which encode the rate-limiting steps of PC and PE synthesis, and increased Desat2, which encodes stearoyl-CoA desaturase, a homolog of human α-syn toxicity modifier stearoyl-CoA desaturase (SCD)72 (Supplementary Fig. 6E). Three lipid species, including Cer-NS (d16:1/24:0), TG (50:4)-FA18:3, and TG (54:2)-FA18:2, were detected in α-syn fly brains but not in control brains without α-syn (Supplementary Fig. 6F).

Taken together, our data demonstrate the increase of TCA cycle metabolites in α-syn fly brains, and that neuronal mino perturbations affect brain lipid staining in both normal and α-syn fly brains.

A common role of GPAT as modulators of α-syn neurotoxicity

To address if other GPAT members51 have a role in modulating α-syn neurotoxicity, we extended our RNAi targeting to Gpat4, and CG15450, two other Drosophila homologs of GPAT. mino is predicted to reside on the mitochondria, whereas Gpat4, and CG15450 are predicted to reside on the endoplasmic reticulum73 (Fig. 6a). Similar to mino RNAi, neuronal knockdown of Gpat4 and CG15450 suppressed the decline of climbing abilities (Fig. 6b), mitigated the reduction in daily locomotor activities (Fig. 6c, d), attenuated the decline of PAM TH+ neurons in α-syn flies, and showed a similar effect in brain lipid staining as mino RNAi (Figs. 6e, f and 5c–f). Similarly, the Gpat4f0898/+ heterozygote that exhibits a 34% reduction of Gpat4 transcript level compared to w1118 mitigated PAM TH+ neuron loss and locomot declines in α-syn flies (Supplementary Fig. 2M–Q). α-syn flies treated with the commercial GPAT inhibitor FSG6774 showed improvements in daily locomotor activities and PAM TH+ neuron loss (Fig. 6g–i and Supplementary Fig. 7A). In contrast, RNAi of Gnpat, an enzyme predicted to reside on the peroxisome for ether lipid synthesis, did not affect the locomotion activities of α-syn flies (Fig. 6a–d). Despite the observation that Gnpat RNAi mitigated the loss of DA neurons in the PAM cluster (Fig. 6e), these results highlight the broad effects of GPAT activity in modulating α-syn neurotoxicity.

We have previously shown that α-syn expression in fly brains is associated with glycolysis reprogramming and increased levels of Lactate dehydrogenase (Ldh)41. GPAT RNAi did not change the Ldh levels of α-syn flies (Fig. 7a, b) or the total α-syn or pS129 levels. Thus, mino does not seem to function upstream of α-syn.

The phospholipid membrane plays a role in α-syn oligomerization75,76. We investigated whether GPAT affects α-syn oligomerization levels in α-syn fly brains. α-syn expressed in fly brains is mainly detected as monomers42,77. Cross-linkers dimethyl dithio-bispropionimidate (DTBP)78 could stabilize the α-syn oligomers for detection (Supplementary Fig. 8A). With 4 mM DTBP treatment, we found that GPAT RNAi, but not Gnpat RNAi, suppressed the formation of higher-order α-syn oligomers (Fig. 7c, d). GPAT RNAi specifically reduced α-syn tetramers and higher-order oligomers, without impacting α-syn dimers or trimers, either in comparison to their respective monomers or to total α-syn levels (Fig. 7c, d). We did not detect proteinase K-resistant α-syn aggregates in α-syn fly brains (Supplementary Fig. 8B).

α-syn oligomers or aggregates were associated with the accumulation of mitochondrial reactive oxygen species (ROS), including H2O275. We expressed the H2O2 sensor mito-roGFP2-Orp1 in photoreceptor neurons to assess transient mitochondrial H2O2 levels79. mino RNAi or overexpression did not affect the mitochondrial H2O2 index in photoreceptor neurons without α-syn (Fig. 8a, b). In α-syn-expressing photoreceptor neurons, mino RNAi was associated with a reduction, whereas mino overexpression was associated with an increase, of the H2O2 index (Fig. 8a, b). MitoTimer is a mitochondrial ROS-sensitive sensor reflecting the cumulative redox history of mitochondria by shifting the emission fluorescence from green to red80. We verified the mitochondrial localization of pan-neuronally expressed MitoTimer (Supplementary Fig. 8C). α-syn expression in fly brains accelerated MitoTimer aging in the optic lobe, and this effect was mitigated by mino RNAi but enhanced by mino overexpression (Fig. 8c, d). We noted a mild suppression of MitoTimer aging by mino RNAi in the absence of α-syn (Fig. 8c, d). GPAT RNAi showed similar effects as mino in affecting MitoTimer aging (Fig. 8e, f).

α-syn flies fed with 1 mM FSG67 for 3 weeks at 25 °C showed a reduction of tetramers and higher-order oligomers in comparison to monomers (Fig. 7e and Supplementary Fig. 8D). FSG67 also caused a suppression of MitoTimer aging in α-syn flies incubated at 22 °C (Fig. 8g, h). However, this suppression was lost when flies were incubated at 25 °C (Fig. 8g, h).

Taken together, our results demonstrate GPAT as a modulator of α-syn neurotoxicity by affecting the α-syn oligomerization and mitochondrial ROS accumulation.

Pharmacological inhibition of GPAT suppresses α-syn-induced lipid peroxidation in mouse primary neurons treated with α-syn preformed fibrils (PFF)

We investigated the effect of GPAT on α-syn aggregation in primary mouse neurons treated with α-syn preformed fibrils (PFF). PFF treatment induced the formation of fibers and aggregates positive for α-syn phosphorylation at serine 129 (pS129) (Fig. 9a). Co-treatment of neurons with PFF and FSG67 attenuated the levels of pS129 signals (Fig. 9a, b). PFF-induced pS129 fiber and aggregates partially colocalized with the staining of lipid peroxidation product 4-HNE, and that PFF-treated neurons exhibited elevated levels of staining of 4-HNE and MDA (Fig. 9a, c–e). 4-HNE and MDA staining in PFF-treated neurons were ameliorated by FSG67 co-treatment (Fig. 9a, c–e). BODIPY C11 staining showed elevated lipid peroxidation levels in PFF-treated neurons, which were mitigated when co-treated with FSG67 (Fig. 9f, g). Collectively, our results suggest that GPAT is a relevant player in α-syn-induced cytotoxicity in the mammalian context.

Methods
Mouse primary neuron culture and staining

Mice-related studies were approved by and conformed to the guidelines of the Institutional Animal Care Committee (IACUC) of the Nanyang Technological University Lee Kong Chian School of Medicine (IACUC Protocol A20037). C57BL/6 mice were housed in groups of two to five in individual ventilated cages (IVC) under specific pathogen-free conditions in a temperature-controlled environment (23 °C) with 70% humidity and a 12-h light/dark cycle (light on at 7:00 a.m.). Food and water were provided ad libitum, and all procedures adhered to humane care guidelines. Embryonic day 17.5 mouse fetuses without gender identification from pregnant female C57BL/6 were obtained. Sex was not factored into the experimental design due to the technical impracticability of determining fetal sex at the embryonic stage. A total of three pregnant mice were used, one for each of the three repeats of the experiment. The cortices were isolated and dissociated with papain (LS003119, Worthington) for 30 min at 37 °C. Papain was removed, and the cortices were washed with DMEM/FBS and spun down at 200 × g for 5 min. Cells were titrated, spun down, and resuspended in Neurobasal medium supplemented with B27 and GlutaMAX (Gibco). In total, 80,000 cells/well were plated. At day 7, mice primary cortical neurons were treated with 1 μg/ml α-syn monomers (SPR-323, StressMarq) or 1 μg/ml synuclein PFF (SPR-322, StressMarq) with or without 75 μM or 150 μM FSG (HY-112489, MedChemExpress LLC) for 2 weeks. Following treatment, cells were fixed in 4% PFA/4% sucrose/PBS for 30 min at room temperature, then washed three times with PBS. Subsequently, cells were blocked in 0.2 M glycine, 0.1 mg/ml saponin, and 30 mg/ml BSA in PBS for 45 min. Primary antibody staining was carried out in antibody diluent (0.1 mg/ml saponin and 1 mg/ml BSA in PBS) for 1 h at room temperature using anti-Malondialdehyde antibody (Abcam, 11E3, ab243066, 1:500), anti-4-Hydroxynonenal antibody (Abcam, HNEJ-2, ab48506, 1:500), and anti-α-syn phospho S129 (Abcam, ab51253, 1:500). After washing three times with PBS, cells were incubated with secondary antibodies in antibody diluent for 1 h, followed by four washes with PBS. Finally, cells were stained with BODIPY 493/503 (Thermo Fisher Scientific, D-3922, 1:1000) and 1 μg/ml DAPI, mounted, and imaged using an FV3000 confocal microscope (Olympus). The 4-HNE and MDA signals were quantified by thresholding the image and then measuring the intensity sum of the area above the threshold on the image using ImageJ/Fiji. For the lipid peroxidation assay, 5 mM BODIPY C11 stock solution was added to the culture medium of a glass-bottom cultured dish in 1:1000 dilutions and incubated for 0.5 h, then directly imaged in the green and red channels, respectively. The ratio of mean intensity in the cell was analyzed using ImageJ/Fiji.

Drosophila stocks

Flies were grown at 25 °C with a standard yeast-cornmeal-dextrose diet. Only male flies were collected for experiments. Aging experiments were conducted at 25 °C, unless otherwise stated. Adult male flies were gathered in groups of 20–30 per vial for aging. During aging, the food was changed every 2 days for the initial 2 weeks and subsequently replaced daily from the 3rd week onward. All the Drosophila stocks used in this study, except for Rh1-GAL4, could be purchased from BDSC. There are no newly generated fly stocks from this study. The sources of Drosophila stocks are listed in Supplementary Table 1. minof04927 is sourced from Exelixis, Inc. minof04927, minoEY00734 and Gpat4f06898 mutants were outcrossed to w1118. The nSyb-QF2>SNCA stock was deposited to BDSC (RRID:BDSC_600605) by Koh Tong-Wey. The reference to Rh1-GAL4 is provided within the Supplementary Information.

Drosophila brain immunostaining

Larvae or adult fly brains were dissected in PBS, fixed in 3.7% paraformaldehyde in PBS with 0.1% Triton X-100 on ice for 0.5 h, and subsequently fixed at room temperature for an additional 0.5 h. For LDs staining, room temperature fixation was extended to 1 h. Following fixation, brains were rinsed in PBS with 0.4% Triton X-100 (PBST) and subjected to primary antibody staining for 1 day at 4 °C, then washed in PBST and incubated in secondary antibodies for 1 day at 4 °C, followed by washing with PBST. In the TUNEL assay, after removal of the buffer, the TUNEL reaction mixture (Roche, 12156792910) was added, incubated in a 37 °C water bath for 1 h, and briefly washed. Subsequently, brains were stained in PBST with 4’,6-diamidino-2-phenylindole (DAPI) for 3 h, briefly washed, and mounted with Prolong Gold (Thermo Fisher Scientific) on bridged slides, positioned as a line with the anterior side facing upward and both sides padded with double layers of Scotch transparent tape (except for a single layer for TH staining in the PAM cluster). For positive control of apoptosis, third instar larvae of w1118 or hs-hid were heat-shocked in a 37 °C water bath for 2 h and allowed to recover for 5 h before dissection. For Apoliner, the heat shock is 1 h without recovery. Imaging was performed using an FV3000 confocal microscope with consistent image settings for samples within each experiment and analyzed using Bitplane Imaris 8.4 or ImageJ/Fiji. TUNEL analysis was performed using the Imaris Spots module. The primary antibodies used include rabbit anti-Tyrosine Hydroxylase TH (Pel Freeze, P40101-150, Lot ajo391o, 1:500), rabbit anti-Cleaved Caspase-3 (Asp175) (Cell Signaling Technology, 9661, Lot 43, 1:500), rabbit anti-Cleaved Caspase-3 (Asp175) (5A1E) (Cell Signaling Technology, 9664, Lot 22, 1:500), mouse anti-repo (DSHB, 8D12, Lot 3/10/22, 1:500), mouse anti-α-tubulin (DSHB, 12G10, Lot 1/13/22, 1:5000), rabbit anti-Cleaved Drosophila Dcp-1 (Asp216) (Cell Signaling Technology, 9578, Lot 5, 1:500), rabbit anti-cleaved PARP (Abcam, ab2317, Lot 559599, 1:500), mouse anti-GFP (Roche, 11814460001, Lot 14442000-30021090, 1:500), rabbit anti-GFP (Thermo Fisher Scientific, A6455, Lot 2415918, 1:500), mouse anti-ATP5A (Abcam, ab14748, Lot 2101063327, 1:500).

Drosophila brain lipid droplet imaging

Adult fly brains were dissected in PBS, fixed in 3.7% paraformaldehyde in PBS with 0.1% Triton X-100 on ice for 0.5 h, and subsequently fixed at room temperature for an additional 1 h. Following fixation, brains were rinsed in PBS with 0.1% Triton X-100 (PBST) with DAPI for 1 h and then stored at 4 °C. Before imaging, brains were stained in PBS with 0.1% Triton X-100 (PBST) and BODIPY 493/503 (Thermo Fisher Scientific, D-3922, 1:1000) or LipidTOX (Thermo Fisher Scientific, H34476, 1:1000) for 0.5 h in room temperature with continuous rolling, then briefly washed with PBS and mounted using 9:1 mixture of glycerol and 1.5 M Tris-HCl, pH 8.8 between a gap formed by double layers of Scotch transparent tape on glass slide. Z-stacks aimed at the center of the optic lobe are imaged immediately within 1 h using FV3000. BODIPY 493/503 was excited using 488 nm laser with 0.01% laser power and collected at 500–550 nm emission light. To quantify the volume of LDs, representative sample images were concatenated along the T-axis and trained using Labkit (Fiji) to generate a classifier of the LDs. The classifier was used to automatically predict the LDs of all samples in a batch and generate binary masks. The volume of LDs per sample was analyzed using Bitplane Imaris 8.4.

Drosophila PAM TH+ neuron quantification

The TH+ neurons within a single PAM cluster were imaged using FV3000 with 512×512 resolution and 0.34 µm slice interval for both TH and DAPI channels, generating z-stacks. Labkit training and TH+ region prediction were performed on a computer with an NVIDIA Quadro P6000. Twenty representative z-stacks, encompassing a spectrum of TH signals and backgrounds, were vertically merged into a unified stack using Fiji/ImageJ. In Labkit (Fiji), the stack underwent more than 100 cycles of “scribbling-predicting-correcting” to train the TH+ pixel classifier against backgrounds. The resulting classifier file with a size of 379 megabytes was applied consistently for subsequent TH+ neuron analysis. For TH+ region identification, the classifier file was loaded into Labkit to batch process a folder of z-stack TH images. The defects, including noise and vacuoles on the Labkit-predicted mask images, were further refined using a customized Matlab (Mathworks) code “Correct_Labkit_TH.m” (version 1.0). The source code, instructions for installation and use, description of code dependencies, and the test data are available in Supplementary Data and also at https://github.com/rmd13/FlyBrain_PAM_TH_DAPI_Labkit/. The code sequentially processes each slice of a Labkit-generated 0/1 mask image. Its smooths the mask using a Gaussian smoothing filter with a sigma of 1.5 to enhance the image quality. Following smoothing, a threshold of 0.25 is applied to the resulting image; thus, only the pixels above this threshold are labeled as a mask. The mask slice is then dilated using a square-shaped structuring element with a width of 5 pixels to fill in small gaps within the mask. Additionally, the code identifies and fills larger holes that still exist within the mask, provided these holes have an area of less than 200 pixels. Finally, the mask is eroded using the same square-shaped structuring element with a width of 5 pixels. The processed mask images were imported into Bitplane Imaris 8.4.1 as a new channel alongside the raw images. TH+ surfaces and DAPI spots were created using Imaris in the mask and DAPI channel, respectively. The number of TH+ neurons in the PAM cluster was counted as DAPI spots located within the TH+ surface by running the Bitplane Imaris 8.4’s surface distance transformation extension outside the TH+ surfaces.

Drosophila brain lipid peroxidation assay

Fly brains expressing pan-neuronal infrared fluorescent protein (mIFP) were dissected in PBS and transferred into Eppendorf tube 1 containing 100 μl of PBS. In Eppendorf tube 2, 0.5 μl of 5 mM BODIPY C11 DMSO solution (Thermo Fisher Scientific, D3861) and 0.5 μl of 1% saponin (Sigma, S7900) were added into 350 μl PBS (B), mixed, and transferred to tube 1, which was then rolled at room temperature for 30 min. Following the rolling process, brains were briefly washed in PBS and mounted with PBS on a bridged slide using two layers of Scotch transparent tape, creating a 5 mm gap. Thick nail polish was used to secure the four corners of the coverslip, and additional PBS was added to fill any gaps if necessary. BODIPY C11 was immediately imaged in FV3000 using a ×100 objective lens. The brain optic lobe was located and live-imaged using a 640 nm laser to determine the position of labeled neuronal membranes. Subsequently, images were acquired in the green channel (488 nm laser, 0.04% laser power, 515–545 nm emission) and red channel (561 nm laser, 0.02% laser power, 575–605 nm emission), respectively. Four to five images were acquired for each brain. For each group, the brains were imaged within 1 h. The lipid peroxidation index was analyzed as the ratio of the mean intensity of membrane area in the green channel to the mean intensity in the red channel using ImageJ/Fiji. For each brain, the lipid peroxidation index from four to five images was averaged. A pseudo-colored image was generated by creating a ratio channel and masking out the unstained area in Bitplane Imaris 8.4.

Drosophila daily locomotor activity assay

Fly food, extracted from a vial, was trimmed into two semi-circles with a height of 5 mm and then placed on tissue paper for a 0.5-h drying period. To administer FSG67 (HY-112489, MedChemExpress LLC), 10 μl of 0, 1, 2.5, or 5 mM FSG67 dissolved in PBS was evenly spread on the fly food until absorption. One end of a clean glass tube for locomotor activity assay was inserted down vertically into the food and capped. Anesthetized flies were individually transferred into each tube, and then the tube was blocked with a sponge on the other end. For the locomotor activity assay, these loaded glass tubes were then affixed to the DAM2 Drosophila activity monitors (TriKinetics). The locomotor activities were recorded at a frequency of 10 s over a period of one to three weeks, maintaining a 12-h light/dark cycle of LED illumination controlled via an Arduino-controlled relay by the same computer. The food was replaced every three to five days. Actograms captured during this period were analyzed using the ActogramJ plugin104 in ImageJ/Fiji. Daily locomotor activities were further analyzed and plotted using Microsoft Office Excel (2010) and GraphPad Prism 8.3.0. For the other assay of flies using FSG67, the loaded tubes were placed on trays inside the incubator.

Drosophila brain short-chain fatty acids and lipidomic assay

For each genotype for short-chain fatty acids or lipidomic assay, ten fly brains per genotype were dissected in cold PBS and pooled into an Eppendorf tube on ice with 50 μl PBS. Then PBS was carefully removed under a stereomicroscope, and tubes were frozen at −80 °C. The tubes were sent to the Singapore Phenome Center (SPC) on a cryobox pre-chilled at −80 °C overnight. The total number of sample pools (n), i.e., tubes, is 1 for nSyb-QF2 and 1 for nSyb-QF2>SNCA, with nSyb-QF2 as the control. There are no technical replicates and no biological replicates. Short-chain fatty acids and lipidomic assays were performed, and data were returned as Excel files. The detailed methods are provided in Supplementary Methods and Supplementary Table 3. The spectral data are provided in Supplementary Data 6.

Western blot

An equal number of fly brains were dissected and pooled into PBS on ice. PBS was removed, and brains were homogenized with pestles in brain lysis buffer that contains Tris-HCl, pH 8.0 10 mM, NaCl 200 mM, Triton X-100 1%, EDTA 5 mM, Glycerol 5%, PMSF 0.5 mM, DTT 1 mM, Protease Inhibitor Cocktail (Roche, 11873580001). For α-syn pSer129) blotting, Phosphatase Inhibitor Cocktail 2 (Sigma, P5726) and Phosphatase Inhibitor Cocktail 3 (Sigma, P0044) were added to brain lysis buffer (1:300). For proteinase K treatment, equal number of fly heads were homogenized in lysis buffer (50 mM Tris-HCl pH 7.5, 5 mM EDTA, 0.1% NP40, 1 mM DTT, and 1% protease inhibitor cocktail, incubated for 1 h at 25 °C, and centrifuged at 17,949 × g for 1 min. The supernatants were collected and incubated for 30 min at 25 °C with proteinase K (Roche, 03115828001). For sample loading, an equal volume of 2× Laemmli loading buffer (Tris-HCl, pH 6.8, 125 mM, bromophenol blue 0.02%, SDS 4%, glycerol 20%, β-mercaptoethanol 10%) was added to the lysate and heated at 50 °C for 0.5 h. For detection of α-syn oligomers, fly brains were dissected in PBS and cross-linked in the same-day prepared buffer A (HEPES 20 mM pH 8.5, KCl 120 mM, EDTA 2 mM, sucrose 0.25 M, glycerol 1%, Dimethyl dithiobispropionimidate (DTBP) 4 mM, protease inhibitor cocktail (Roche)) on ice for 1 h. Then the reaction was halted by adding 10 mM Tris-HCl pH 8.8 for 10 min on ice. Brains were then homogenized with a pestle, and an equal volume of 2× Laemmli loading buffer was added without β-mercaptoethanol or DTT, followed by heating at 50 °C for 0.5 h. For head lysate but not brain lysate, the samples were further centrifuged at 10,621 × g for 2 min, and the supernatant was collected. The samples were loaded into Mini Protean TGX (stain-free) 4–20% gel (Bio-Rad, 4568094, 4568095, 4568096) to run for 100 V 1.5 h. The gel was UV-activated and transferred onto a PVDF membrane using transfer buffer (Tris 25 mM, Glycine 192 mM, 20% methanol) at 100 V for 1.5 h. The membrane was fixed in PBS with 3.7% PFA and 0.025% glutaraldehyde for 0.5 h, stained-free imaged, and blocked in 5% milk in Tris-buffered saline with 0.1% Tween-20 (TBST). Primary antibodies used include mouse anti-α-syn (BD 610787, Lot 6092600, 1:1000), rabbit anti-Gpi (Merck, HPA024305, Lot B118974, 1:1000), rabbit anti-LDH (Thermo Fisher, PA5-26531, Lot XJ3718422A, 1:1000), rabbit anti-ATPCL (Cell signaling, 4332, Lot 2, 1:1000), rabbit anti-pSer129-α-synuclein D1R1R (Cell signaling, 23706, Lot 2, 1:1000), and secondary antibodies include anti-mouse HRP (CST, 7076S, 1:3000) and anti-rabbit HRP (Amersham, NA934-1ML, 1:3000). The HRP was detected using Western Bright ECL and Sirius (Advansta) in ChemiDoc imaging system (Bio-Rad). The membrane was subsequently re-blotted with mouse anti-α-tubulin (DSHB, 12G10, Lot 1/13/22, 1:5000). The image was analyzed using Image Lab (Bio-Rad, 6.0.0) and ImageJ/Fiji (v1.53q), and the results were plotted in GraphPad Prism (8.3.0).

Mito-roGFP2-Orp1 imaging for H2O2

Retina expressing mito-roGFP2-Orp1 were dissected in PBS and fixed in PBS with 3.7% PFA, 0.1% Triton X-100, and 20 mM N-Ethylmaleimide (Thermo Fisher Scientific, 23030) for 0.5 h on ice, followed by another 0.5 h at room temperature. The fixed retina was washed in PBST with 5% goat serum overnight at 4 °C and then was mounted with Prolong Gold anti-fade mountant (Thermo Fisher Scientific, P10144). Mito-roGFP2-Orp1 was imaged by exciting with a 405 nm or 488 nm laser, respectively, and collecting 500–530 nm emission light. In all, 405 nm laser was used for the H2O2-bound form and 488 nm laser for the H2O2-free form of the sensor. The H2O2 index was determined by the ratio of the mean intensity of the mitochondria in the two channels using ImageJ/Fiji.

MitoTimer imaging

Brains were dissected in PBS and fixed in PBS with 3.7% PFA and 0.1% Triton X-100 for 0.5 h on ice and an additional 0.5 h at room temperature. Following fixation, the brains were washed in PBST with 5% goat serum and DAPI overnight at 4 °C and then mounted with Prolong Gold anti-fade mountant (Thermo Fisher Scientific, P10144). The green channel (488 nm laser, 500–540 nm emission) and the red channel (561 nm laser, 570–620 nm emission) were imaged on the cortex layer of the optic lobe. The ratio of the mean intensity of MitoTimer between the red and the green channel was analyzed using ImageJ/Fiji.

Drosophila climbing assay

The climbing assay was conducted on a customized workstation composed of a background white foam, side LED light, bottom light, 50 ml glass cylinders, an elastic cushion, and a Nikon digital camera securely affixed to a tripod. A sponge pad was positioned in the inner bottom of the cylinder to minimize potential harm to the flies during the climbing assay. In total, 10–20 flies were flipped into a capped cylinder, tapped to the bottom, and allowed to climb for 5 s, following which an image was promptly captured using the camera. The average climbing height for all the images was analyzed using a customized FlySpotter program (Srinivas Gorur-Shandilya, https://github.com/sgs/fly-spotter) and graphically represented using GraphPad Prism.

Real-time PCR

Fly brains were dissected in PBS, with trachea sacs and fat bodies detached, and were subsequently transferred into RNAlater (Thermo Fisher Scientific, R0901). Alternatively, heads or bodies were collected. Following removal of excess fluid, RNA was extracted using TRIzol™ Reagent (Thermo Fisher Scientific, 15596026). The mRNA concentrations were measured using NanoDrop 2000 Spectrophotometers, and the concentration was adjusted by adding RNase-free water (Thermo Fisher Scientific, AM9932) to reach an equal concentration across all samples. The mRNA was then treated with dsDNase (Thermo Fisher Scientific, EN0771). Subsequently, cDNA was prepared using the Invitrogen SuperScript II First-Strand Synthesis System for RT-PCR (Thermo Fisher Scientific, 11904-018). qPCR was performed using iQ™ SYBR Green Supermix (Bio-Rad, 1708882) and the LightCycler 96 Instrument (Roche). The data was analyzed using LightCycler 96 software (Roche). RPL32 served as a single internal control for mRNA quantification of experiments not involving α-syn. RPL32 and ed served as double internal controls for mRNA quantification of experiments involving α-syn.

Public RNA-sequencing dataset illustration

The expression levels for genes of interest, as well as cell identities, were extracted from the Fly Cell Atlas Drosophila head RNA-sequencing dataset (https://flycellatlas.org/) and additional RNA-sequencing datasets GSE223626, GSE21866161–63 using HDF5viewer (3.1.4). Raw read counts from Fly Cell Atlas were normalized per cell when necessary. The combined expression data was imported into Excel and arranged by cell types, and imported to Matlab (MathWorks R2016a) for visualization using the function imagesc.

Synuclein preformed fibril preparation

In total, 15 μl of 2 mg/ml synuclein PFF (StressMarq SPR-324) aliquoted into screw-capped tubes were sonicated in an ultrasonic bath sonicator for 2.5 h at the following conditions: Sweep, 37 Hz frequency, 60% power. Water was changed at 30-min intervals to maintain the water temperature at 15 °C.

Statistics and reproducibility

For mouse experiments, the biological or technical replicates are detailed in the figure legend. For each experiment with fruit flies, the design involves an experiment using multiple biological sample replicates for each group to ensure robustness of our findings. No statistical method was used to predetermine sample size. No data were excluded from the analyses except that for the α-syn modifier screening where data distributions were not normal in over 90% of groups, only the 25% to 75% percentile of data points were utilized for testing to identify candidate genes. The experiments were not randomized. The investigators were not blinded to allocation during experiments and outcome assessment, with the exception of collecting data for α-syn modifier genetic screening, short-chain fatty acids, and lipidomic analysis. For fly experiments, every single fly is a biological replicate that contributes to a single data point of the plot, unless otherwise indicated in the figure legend. For each plot or experiment, the number of flies (n) used for multiple groups of genotypes and chemical treatments are not identical between groups, and these numbers are indicated in the figure legend. All the statistics are two-sided. Statistical analyses were conducted using GraphPad Prism 8.3.0 and Matlab (MathWorks R2016a). For the genetic screening, the Anderson-Darling test was applied to assess the non-normal distribution of all the data, followed by the Mann–Whitney U test. The P values were adjusted by the Benjamini–Hochberg method using the Matlab function padj= PVAL_ADJUST(p, ‘BH’), where p is the input vector of all the P values (fakenmc/pval_adjust, version 1.2.0.2, by Nuno Fachada. https://github.com/nunofachada/pval_adjust). Apart from genetic screening, data distribution was not formally tested to be normal or not. For data analysis of multiple groups, one-way ANOVA or two-way ANOVA was used to determine significant differences among multiple groups of interest, unless otherwise indicated in the figure legend. This is followed by Tukey’s post hoc test for comparisons between two groups, or Dunnett’s post hoc test for comparisons between a selected control group such as α-syn alone with other groups such as α-syn with other treatments or genetic manipulations. Data are presented as mean ± SD or a violin plot. Significance levels are *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Ren et al. report a novel role of the fly GPAT homolog mino as modulator of aSyn mediated toxicity in a fly model of Parkinson’s disease. They found that mino silencing suppress several phenotypes associated with aSyn expression in flies. Silencing of other GPAT produce similar beneficial effects. The pharmacological inhibition of GPAT via FSG67 is also beneficial in both flies and mouse primary neurons expressing aSyn. This is an interesting work with solid quantification methods. My enthusiasm is tempered due to several pitfalls in the study. -First the entire study is only based on a silencing approach, which may be associated with off target effects. The standard in the field is to use loss of function mutations combined with rescue experiments. They should at least confirm their observations with available mutants for the genes tested in the paper. -Another issue also related to the first one is that there is no evidence that silencing of mino (or other silenced genes tested in the study) affects the production of LPA, PA and ultimately TAG. Mino OE has been shown to be sufficient to induce lipid droplet production. Are TAG-lipid droplets detected in the study? -A previous study has shown the effect of modulating lipid droplet content by the lipase bmm on aSyn aggregation (Girard et al. 2021). Could it be that the observed phenotypes are due to lipid droplet modulation by GPAT? If it is the same mechanism, this may not be that novel. If it is a different mechanism, they authors need to discuss it. -In figure 3C, miroRNAi OE in WT background is not shown at 29C. -The asyn aggregation analyses should be expanded. Previous works have shown phosphorylated Syn and aSyn proteinase K resistance in Drosophila. -The analyses on cell death are incomplete. The lack of caspase activation should also be tested with the sensitive cleaved Dcp-1 antibody. In addition, the overexpression of p35 should confirm that effector caspases are not involved in the execution of cell death. -They did not show that the FSG67 drug targets GPAT activity in flies.", "reviewer_2": "The manuscript by Ren et al is focused on the unravelling the effect of Glycerol 3-phosphate acyltransferase (mino) on alpha-synuclein toxicity. The authors shown that silencing mino lead to the abrogation of the pathology in locomotor activity induced by a-synuclein in Drosophila. The manuscript is potentially novel and interesting. However, some of the key conclusions of the authors are not supported by the data. Critics 1. One of the major pathology in cell which is indicated is increased lipid peroxidation in mino RNAi in combination with a-synuclein. However, BODIPY C11 is ratiometric indicator which is constantly oxidised in cell membranes due to basal oxidation. Considering this, the measurements of LP with this indicator can be taken only as the rate of oxidation (rate of BODIPY C11 ration increase in time) but not as a single images and measurements of intensity (ratio). 2. Results on the measurements of the products of lipid peroxidation - 4-HNE and MDA are presented. However there are no information in the Method section or in the figure legends how these measurements were done. 3. Glycerol 3-phosphate acyltransferase (GPAT) is the mitochondrial isoform of the lipid synthesis enzyme. Can be all observed changes be induced by the different level of lipids in mitochondria? The changes in lipid composition should be measured. 4. The effect of the lipid composition on a-synuclein is not novel and published previously. Additionally, if the authors indicate it as a mechanism of the pathology - why it is observed in the Drosophila, there a-synuclein is in predominantly monomeric state? 5. Figure 6. Fibrillar a-synuclein is know not to be redox active and it is not clear how modification of mino could change lipid peroxidation in primary neurons.", "reviewer_3": "The paper by Mengda Ren and colleagues addresses a timely and interesting topic regarding the role of lipid dyshomeostasis in -synuclein induced neuropathology in PD. The authors identity mino as gene capable of modulating the pathological effects of -syn overexpression in drosophila, which they propose occurs via a reduction in lipid peroxidation and ferroptotic pathways that may be induced by alpha-synuclein. Overall suppression of mino appears to improve effects in locomotor activities, and lipid peroxidation production in flies’ optic lobe, an effect that may occur across other GPATs. However, the ability to draw conclusions on how this is related to the alpha-synuclein mechanisms of toxicity int terms of aggregation, lipid peroxidation and ferroptosis are less well supported by the data. The manuscript would improve significantly if the controls were clearly defined, the alpha-synuclein overexpression model deeply phenotyped, and the pathways of alpha-synuclein toxicity and their intersection with Mino more clearly elucidated. The translation to the mammalian model was preliminary and requires more work to demonstrate that this is relevant in mouse models. In the discussion, the authors “favor a model by which -syn elicits neuronal death through ferroptosis”. However, this is not clearly proven by the data and would really require the convergence of iron, lipid peroxidation and cell death to be present, as well as established ferroptosis inducers/inhibitors to prove this. Undoubtedly they have shown interesting observations on alpha-synuclein aggregation, and lipid peroxidation, and a genetic interaction with Mino, but do not provide a unifying mechanism or hypothesis on how they relate to each other. Additional issues throughout the manuscript include figures with missing panels, unclear statistical comparisons, using colour or symbol schemes that change and vary within the figures, making it difficult to follow, and presumptions drawn from the results without supporting literature or data. The statistical analysis section in the methods could clearly outline the definition of N in each figure. Specific comments; Figure 1: - The authors use two models of driving expression of alpha-synuclein, either in a subset of neurons or pan-neuronally. They do not show the expression level of alpha-synuclein in either model, or how this varies between models, and whether the manipulation of genes through knockdown or overexpression alters alpha-synuclein expression levels (as a potential mechanism for modulating toxicity). Why is the pan-neuronal model ‘severe’ compared to the other model? - What was the rationale behind doing the genetic screen in the Drosophila model expressing -syn in the PR neurons instead of the model which has a more severe and disease relevant synucleinopathy phenotype? - Regarding supplementary data 1, mino RNAi alone influences climbing phenotype and therefore the “rescue” effect of mino suppression in the presence of -syn should be compared to the mino RNAi line, not the eGFP RNAi + -syn. If the analysis was done looking at fold change between mino RNAi and mino RNAi + -syn I’m not sure the authors would find a rescue on climbing defects, except at week 1 and week 6. - In supplementary figure 1a, authors include the control eGFP RNAi line, it is not evident whether this control in included in the remaining figures? Furthermore, in some experimental designs both the mino RNAi and OE flies are shown in the results, while in other cases only the mino RNAi flies are shown (and not the OE). Could the authors clarify on this matter? - The neurodegeneration of dopaminergic neurons was assessed by looking at TH+ neurons in the PAM region, did the authors look in other brain regions containing TH neurons? And did they confirm the overexpression of -syn in those TH+ neurons as well as the KD or OE of mino? - Where is the quantification of fig 1E? Where is fig 1F – it is in the legend and text but not in figure panel? (Effect of changing temperature and effect of Mino O/E data) - Mino knockdown only rescues TH neuronal loss in the d42 neuronal loss, not the d30 severe model – why? What makes one model more severe? Why would there be a difference in the rescue? - Figure 2: - Circadian rhythms are disrupted in the synuclein o/e model, with partial restoration in Mino KD and partial worsening in evening peak with Mino O/E. Which neurons are affected here? Why use the pan neuronal model here? What is the link to alpha-synuclein expression and the circuitry involved? - Why does glial Mino RNAI alone lead to significant deficit compared to no alpha-synuclein expression (in supp fig 2)?? What is the glial expression of Mino composed to neurons? - What is synuclein levels in the glia in the model (presumably none??) - so how would the authors expect any effect of Mino knockdown in glia? - Supp fig 2 - difficult to see the comparisons and significance because of the annotation (all in thick black bars) - Authors state that mino overexpression aggravates -syn induced reduction of locomotor activities. Based on the figures, it is unclear if the -syn flies (in red) were statistically compared to syn + mino OE (blue). From looking at the locomotor activity graphs I am not convinced mino OE aggravates -syn induced locomotor defects. - Lines 209-217, the authors determine that mino seems to exert its effects on -syn induced pathology in neurons based on the lack of effect on daily locomotor activities when knocking-down mino in glia, however, -syn expression is driven only in neurons in the pan-neuronal -syn flie model – they cannot conclude this unless -syn overexpression and mino suppression is present simultaneously in the same cell type. Figure 3 - The infrared membrane sensor imaging does not look clearly membranous in the images – how was this assessed? Was the membrane sensor used for any analysis (it is not clear if used for merge with Bodipy, and if it was, then where are the controls for ensuring no cross-excitation/bleed through). Did the total membrane compartment change in alpha-synuclein over expression and/or Mino conditions? - When assessing lipid peroxidation with imaging, it is useful to have a positive control to determine the dynamic range of the dye and be able to detect the oxidised C11-Bodipy (ex:488) signal. From the images on figure 3a, there seems to be no difference in oxidised C11-BODIPY across all four conditions, despite the quantification in figure 3c showing significant differences. Therefore the images do not represent the quantification. - Figure 3f, the measures of cell death in optic lobes assessed by TUNEL seem very low. I am concerned the window of cell death is too small to detect a protection or worsening with mino RNAi/OE. What was the rationale behind assessing cell death in the optic lobes instead of the PAM region where the authors previously confirmed a reduction in TH+ neurons? - A positive control for the 4-HNE staining would be helpful Figure 4: - Figure 4a – Similarly to Sup fig1a, mino RNAi alone increases climbing height in the absence of -syn, therefore the -syn neurotoxicity “rescue” observed in the -syn + mino RNAi fly may not be due to the interaction of mino with -syn, but merely the mino RNAi line performing better in the first place. Figure 4b does not show the effect of mino RNAi alone, which may show an increase the daily locomotor activities based on the increase in startle-induced climbing abilities. - GPATs rescue behavioural phenotype but do they rescue the lipid peroxidation phenotype as well? Were these tested, as they would be important to link the mechanism with Mino? Figure 5 - Line 308 - how can monomeric alpha-synuclein be in the insoluble fraction (by definition is intrinsically disordered in solution) - not sure these references quoted here can define this. Following buffers/denaturation the alpha-synuclein may have been denatured to its monomeric form. - The authors use a biochemical method with cross linking to show alpha-syn exists as oligomers in fractions - supported in supp fig 4. Where is the alpha-synuclein KO to show the specificity of the antibody here - or the authors would need to mass spec the bands to show that the higher bands are indeed alpha-synuclein. Higher bands are often non specificity and controls/further evidence that this method is detecting higher order oligomers is required - all of Fig 5a-c requires these controls. Additional techniques to assess -syn aggregation like ELISAs kits and microscopy imaging (ThT, amytracker for amyloid staining formation or pS129 -syn) may be helpful. - The authors investigate mitochondrial H2O2 - what about whole cell ROS? Why not first see whether generalised lipids can do this phenomenon and then ask the compartmentalised question of the effect in the mitochondria? What causes the MitoTimer appearances in a-syn o/e fly? Are the mitochondria damaged in this model? This phenotype needs to be determined before it is possible to understand the effect of Mino in this model. - Mitochondria is the main source of superoxide production. Could the authors explain on their choice of measuring H2O2? Furthermore, there is no data to support that the H2O2 sensor mito-roGFP2-Orp1 is localised to the mitochondria. A co-stain with a mitochondrial dye such as TMRM or mitoTracker would support this assay. - Throughout the manuscript, the statistical comparisons carried out are confusing (i.e fig 5g, -syn flies should be compared to no -syn flies, and not mino RNAi) Figure 6: - Figure 6a – The pS129 -syn antibody seem to be staining almost the entire neurons which is unexpected for a phospho syn stain where you would expect punta stain in the aggregates. Furthermore, the 488 BODIPY stain doesn’t seem specific to the neurons as the background signal is considerably higher in the PFF treated conditions. Is the 488 BODIPY referring to the oxidised form of the C11 BODIPY or the BODIPY 493/503? C11-C11 Bodipy is a lipophilic dye that specifically locates to cellular membranes, while BODIPY 494/503 stain nonpolar lipids. Either way, I am not sure the BODIPY stain is measuring lipid peroxidation. - Because the PFFs are everywhere there would be chance colocalization with Bodiipy. - How do the authors know that the GPAT inhibitor is not just reducing uptake of the PFFs causing less p-syn staining, rather than affecting seeding/aggregation? - Background staining in the PFF treated may be artefact of autofluorescence of protein added to cells - there is no equivalent control for this - Define replicates in fig 6 - technical from single wells, or across multiple animals? - To strengthen the effect of GPAT suppression in -syn induced lipid peroxidation in neurons, I would suggest adding a genetic supression (si/shRNA) in addition to using the pharmacological inhibition in case the FSG67 has non-specific targets, specially at the concerningly high concentrations used in this paper (75 and 150 mM whilst the IC50 is in the low uM range ).", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "Response to Reviewer’s comments (NCOMMS-24-19397)\nREVIEWER #1\nThe paper by Mengda Ren and colleagues addresses a timely and interesting topic regarding the role of\nlipid dyshomeostasis in α-syn induced neuropathology in PD. The authors identity as gene capable of\nmodulating the pathological effects of α-syn overexpression in drosophila, which they propose occurs\nvia a reduction in lipid peroxidation and ferroptotic pathways that may be induced by α-syn. Overall\nsuppression of appears to improve effects in locomotor activities, and lipid peroxidation production in\nflies’ optic lobe, an effect that may occur across other GPAT. However, the ability to draw conclusions\non how this is related to the α-syn mechanisms of toxicity in terms of aggregation, lipid peroxidation and\nferroptosis are less well supported by the data. The manuscript would improve significantly if the\ncontrols were clearly defined, the α-syn overexpression model deeply phenotyped, and the pathways\nof α-syn toxicity and their intersection with more clearly elucidated. The translation to the mammalian\nmodel was preliminary and requires more work to demonstrate that this is relevant in mouse models.\nOur response: We thank the reviewer for considering our manuscript “timely and interesting” and for\nthe recommendations to improve our report, especially regarding the relationship between mino and\nα-syn toxicity, and the need for clearer controls and phenotyping. We have now addressed these issues\nin our revised manuscript as follows:\nFirstly, we have stated the use of control flies clearly in the manuscript text with the following statement,\ni.e. “Hereafter, α-syn (QF2) model was used for all subsequent studies. Due to the observed high\nlethality of EGFP RNAi in α-syn (QF2) flies and its unexpected knockdown of the fluorescent protein-\nbased reporters, in subsequent studies we used GAL4-only, i.e., like nSyb-QF2, nSyb-GAL4 as controls\ninstead of nSyb-QF2, nSyb>EGFP RNAi where appropriate.”\nSecondly, we have enhanced the characterization of the α-syn expression levels in both the mild α-syn\n(GAL4) and more severe α-syn (QF2) models. We wish to highlight that the α-syn fly model has been\nextensively characterized by Ordonez, D. G et. al1. In this revision, we have furthered the\ncharacterization by conducting a metabolomics assay, which revealed alterations in the pathway\naffected by α-syn, linking glycolysis, the TCA cycle, lipid synthesis, and ultimately by mino, along with\nits downstream lipid-related effects (Fig. 5A).\nRegarding the translation to the mammalian model, we acknowledge the preliminary nature of this work.\nThe extension of our findings to mouse models will be a focus in our subsequent research efforts. This\nwill allow us to demonstrate the relevance of our findings in a more complex, mammalian system.\nNotwithstanding, our demonstration that the GPAT inhibitor FSG67 works similarly in mouse primary\nneurons in reducing α-syn phosphorylation and associated lipid peroxidation supports a conservation\nof the relationship between α-syn and mino and the relevance of our findings in the mammalian context.\n1 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nIn the discussion, the authors “favor a model by which α-syn elicits neuronal death through ferroptosis”.\nHowever, this is not clearly proven by the data and would really require the convergence of iron, lipid\nperoxidation and cell death to be present, as well as established ferroptosis inducers/inhibitors to prove\nthis. Undoubtedly, they have shown interesting observations on α-syn aggregation, and lipid\nperoxidation, and a genetic interaction with Mino, but do not provide a unifying mechanism or\nhypothesis on how they relate to each other.\nOur response: We appreciate the reviewer's insightful comments regarding the proposed role of\nferroptosis in α-syn-induced neuronal death. We agree that the direct proof of ferroptosis as the sole\nmechanism of cell death in our model requires a more comprehensive demonstration of the\nconvergence of iron, lipid peroxidation, and cell death, along with the use of established inducers and\ninhibitors of ferroptosis.\nWe wish to clarify that although our study indeed documented phenomena associated with ferroptosis\n(e.g. lipid peroxidation), our primary focus was not to definitively establish ferroptosis as the unified\nmechanism of cell death in α-syn-associated pathology. Our findings suggest that α-syn may contribute\nto a cellular environment conducive to ferroptosis, but we do not claim a direct causal link without\nfurther evidence.\nRelated, we did not detect widespread apoptosis using multiple apoptosis markers and reporters,\nincluding cleaved caspase-3, Apoliner and CD8::hPARP1-Venus, which is consistent with the idea that\nalternative pathways of cell death may be at play. We reference previous work that has shown α-syn\nflies to be responsive to iron, ferroptosis inducers, and suppressors, which supports the notion that\nferroptosis could be a contributing factor2. Moreover, our previous study shows that the iron chelator\nDFO, which is known to suppress ferroptosis, mitigate DA neuron loss in α-syn flies by hypoxia induction\nand glycolytic pathway maintenance3. However, we are cautious not to overinterpret our results as\ndefinitive proof of ferroptosis as the primary cause of cell death. It is possible that multiple approaches\nof cell death are combined in α-syn-associated pathology.\nIn our revised manuscript, we have stated in our associated result section that “Despite the possibility\nthat various reporters might be detectable only during specific stages of apoptosis, the absence of the\npredominantly apoptotic signals in α-syn flies suggests that apoptosis may not be primarily occurring\nin α-syn-expressing fly brains or otherwise occurs in a transient manner that is difficult to capture by\nthe various assays we have performed”. Further, we have refined our discussion to more accurately\nreflect the complexity of the cell death pathways involved in α-syn pathology. We emphasized that while\nour data point towards a potential role for ferroptosis, additional experiments, including the use of\nspecific ferroptosis modulators, will be necessary to fully elucidate the mechanisms underlying\nneuronal death in this context.\n2 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nAdditional issues throughout the manuscript include Figures with missing panels, unclear statistical\ncomparisons, using colour or symbol schemes that change and vary within the Figures, making it\ndifficult to follow, and presumptions drawn from the results without supporting literature or data. The\nstatistical analysis section in the methods could clearly outline the definition of N in each Figure.\nOur response: We thank the reviewer for the meticulous review and for highlighting areas where the\nclarity of our manuscript can be improved. We apologize for the above shortcomings and have\naddressed them as follows:\n• Missing Panels in Figures: We have carefully reviewed the Figures and provided our response\nbelow (especially in our response to 1.9).\n• Statistical Comparisons: We agree that clear statistical comparisons are essential for the\nreader's understanding. In our response to 5.4, we have revised the Figure labels and legends\nto accurately represent the statistical analyses conducted, thereby enhancing the clarity of our\ndata presentation.\n• Color and Symbol Schemes: We recognize the importance of consistent visual elements in\nFigures for ease of interpretation. To address the reviewer's concern, we have restructured our\ncolor and symbol schemes across all Figures. The revised Figures now feature a simplified and\nconsistent approach, which we believe will significantly improve the readability and reduces\nconfusion.\n• Supporting Literature and Data: We appreciate the reviewer's suggestion to bolster our\nconclusions with additional supporting literature and data. We included the relevant references\nand more data to strengthen our findings and ensure that our interpretations are well-founded.\n• Statistical Analysis and Definition of N: In response to the reviewer's feedback, we have\nenhanced the statistical analysis and N definition at the end of each Figure legend to specify the\nnumber of biological replicates.\nWe hope that these revisions will address the reviewer's concerns, which are thankful as they helped\nenhance the overall quality of the manuscript. We appreciate the opportunity to improve our work and\nthank the reviewer for the valuable input.\nSpecific comments\nFigure 1:\n1.1 The authors use two models of driving expression of α-syn, either in a subset of neurons or pan-\nneuronally. They do not show the expression level of α-syn in either model, or how this varies between\nmodels\nOur response: We agree with the reviewer and have now provided a clearer description of the three\ndistinct fly models employed in our study. The first model, which expresses α-syn in photoreceptor\nneurons, is utilized for genetic screening and is only referenced in the initial results section and for the\nmitochondria H O sensor analysis. The second and third fly models express α-syn pan-neuronally. The\n2 2\nsecond model, using the nSyb-GAL4 driver to express α-syn (nSyb-GAL4>SNCA.J7), is used for initial\nvalidation of mino from the selected genes through climbing assays and TH+ neuron quantification. The\n3 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nthird model, which expresses α-syn more robustly using the nSyb-QF2 driver1 (nSyb-QF2>QUAS-SNCA),\nforms the basis of the majority of our study. As recommended by the reviewer, we have now included a\nwestern blot analysis in Figure 1C that demonstrates the expression level of α-syn in both pan-neuronal\nmodels that is consistent with the findings by Ordonez, D. G., et al.1. Our data revealed that the QF2-\nbased model expresses α-syn at an apparently higher level compared to the GAL4-based model and is\nassociated with more severe phenotypes.\n1.2 Whether the manipulation of genes through knockdown or overexpression alters α-syn expression\nlevels (as a potential mechanism for modulating toxicity).\nOur response: We thank the reviewer for raising the important point regarding the potential impact of\ngene manipulation on α-syn expression levels, which could be a confounding factor in interpreting our\nresults. To address this concern, we have conducted analysis of α-syn protein levels following the\nknockdown of GPAT. As shown in Figure 7A, RNAi-mediated reduction of GPAT does not lead to\nsignificant alteration in the expression levels of α-syn. This result confirms that the observed effects on\ntoxicity are not due to changes in α-syn expression but rather acting downstream of α-syn.\n1.3 Why is the pan-neuronal model ‘severe’ compared to the other model?\nOur response: The enhanced severity observed in the α-syn (QF2) model is attributable to the\ncomparatively higher expression level of α-syn. This phenomenon has been previously documented in\nthe literature1 and corroborated by our own findings in this study. In the revised manuscript, we have\nincluded Figure 1C to show the elevated expression of α-syn in the α-syn (QF2) pan-neuronal model.\n1.4 What was the rationale behind doing the genetic screen in the Drosophila model expressing α-syn\nin the PR neurons instead of the model which has a more severe and disease relevant phenotype?\nOur response: We appreciate the reviewer's inquiry into the rationale for selecting the PR neuron-\nspecific Drosophila model for the genetic screen as opposed to a model with a more severe and\ndisease-relevant phenotype. The decision to conduct the genetic screen in the PR neuron model was\nbased on several strategic considerations:\n1. Established Model: The PR neuron model has a well-established history and has been validated\nby numerous studies3,4, providing a reliable approach for our screen.\n2. Resource Constraints: Conducting a genetic screen by climbing assay using pan-neuronal α-syn\nmodels would require substantial resources, including significant manpower, incubator space,\nand working areas. Given the limitations in these resources, this was deemed impractical for\ninitial screening efforts. Instead, this approach is more suited for the refinement and verification\nof a select number of candidate lines.\n3. Quantification Limitations: At the time of the screen, we lacked an automated method to\nquantify PAM TH+ neurons, which is crucial for batch screening. The development of Labkit5\noccurred subsequent to our initial screening, providing us with a tool to later automate the\nquantification of PAM TH+ neurons.\n4 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nWe believe that the PR neuron model offered an optimal balance between feasibility and the potential\nfor meaningful discovery. The choice of model has allowed us to efficiently identify key genetic\nmodifiers, which we are now further characterizing and validating in the context of more severe\nphenotypes. In addition, skd, a known genetic modifier of α-syn, is also identified from our screen,\nfurther validating the effectiveness of our screen. We hope this explanation clarifies our approach and\njustifies our selection of the PR neuron model for the genetic screen.\n1.5 Regarding supplementary data 1, RNAi alone influences climbing phenotype and therefore the\n“rescue” effect of suppression in the presence of α-syn should be compared to the RNAi line, not the\neGFP RNAi + α-syn. If the analysis was done looking at fold change between RNAi and RNAi + α-syn I’m\nnot sure the authors would find a rescue on climbing defects, except at week 1 and week 6.\nWe appreciate the reviewer's careful analysis and concerns regarding the interpretation of the \"rescue\"\neffect in our study, particularly in the context of the mino RNAi line. We believe the reviewer is referring\nto Supplementary Figure 1A (as there is no climbing data in Supplementary Data 1, which refers to the\ngenetic screen using PR neurons), which is also reflected in Figure 1B. As this comment is related to\nresponse 2.2 and 4.1, we addressed them together here below.\nWe fully understand the reviewer’s concern that when assessing the rescue phenomenon, the\ngenotypes should be compared in terms of mino RNAi and/or α-syn. We wish to highlight the following.\nFirstly, our data shows that mino RNAi or OE does not significantly alter the sum of daily locomotor\nactivity in the absence of α-syn (Fig. 2A and 2B). Secondly, we characterized minof04927/+ heterozygote\nmutation, which reduces mino transcript levels to 50%, a level similar to RNAi-mediated reduction, and\nshowed that minof04927/+ does not affect daily locomotor activity in control flies that does not express α-\nsyn (see Fig. R1.1 below).\nFigure R1.1. Effect of minof04927/+ and Gpat4f06898/+ on daily locomotor activities of flies expressing α-syn or not. N\n= 10, 10, 10, 12, 12, 12 (from left to right).\nIt is noteworthy to highlight that we also characterized the homozygote mutation minof04927, which\nreduces mino transcript to 17% of normal level. This homozygous mino mutant causes a mild reduction\nof locomotor activity and reduced PAM TH+ neurons, suggesting that severe reduction of mino is\n5 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nadverse (Fig. R1.2 a-b). Consistent with this, we also observed that high concentration of GPAT inhibitor\nFSG67 (5 mM) feeding in wild-type flies causes reduction of locomotor activity (Fig. 6G).\nFigure R1.2 (a) Effect of minof04927 homozygote on daily locomotor activities of flies expressing α-syn or not. N =\n10.\nFigure R1.2 (b) Effect of minof04927 homozygote and cell type-\nspecific overexpression conversion on PAM cluster TH+ neurons in\nflies incubated at 29oC for 3 weeks. N = 68, 65, 67, 71, 77, 64, 70, 59\n(from left to right).\nGiven the reduction in locomotor activity and PAM TH+ neurons observed in the homozygous mino\nmutant, we were curious if genetic re-expression of mino may modify the phenotype. To address this,\nwe utilized the cis-oriented UAS element in the minof04927 flies, which allows the homozygous mutant to be\ntransformed from deficient to mino overexpression state when GAL4 is added. We found that adding\nrepo-GAL4 to minof04927 homozygote in α-syn flies, which drives glia-specific mino overexpression (i.e.\nleaving mino expression in neurons deprived), further mitigate the PAM cluster dopaminergic neuron\nloss and TUNEL-labeled cell death in the optic lobe (Fig. R1.2 b-c). On the contrary, adding nSyb-GAL4\nto minof04927 homozygote in α-syn flies, which mimics a brain condition of neuron-specific mino\noverexpression and glia-specific mino deprivation, further exacerbates the PAM cluster dopaminergic\nneuron loss and TUNEL-labeled cell death in the optic lobe (Fig. R1.2 b-c). When α-syn is absent, all\nthese manipulations have no further effect on PAM neuron decrease or cell death (Fig. R1.2 b-c).\n6 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nFigure R1.2 (c) Effect of minof04927 homozygote and cell type-\nspecific overexpression conversion on TUNEL quantification of\nthe optic lobe of flies incubated at 29oC for 3 weeks. Scale bar =\n40 um. N = 40, 39, 39, 39, 55, 62, 72, 61.\nBased on these results and considering that mino RNAi and minof04927/+ both show about 50% decrease\nof mino transcripts, we propose that mild reduction of mino, preferably in the neuron but also feasible\nin the whole brain, is the optimal strategy in mitigating α-syn neurotoxicity, in comparison to drastic\ndeprivation of mino or the glia-specific mino deprivation.\nA key consideration in genetic modifier screening is the rarity of identifying a gene that can completely\nrescue α-syn-induced neurotoxicity. Typically, what we observed are modifying effects that alter the\nextent of α-syn neurotoxicity to various extents. In essence, the expression of α-syn leads to\nneurotoxicity irrespective of whether it is in a wild-type (WT) or candidate gene RNAi background. The\ncritical question, therefore, is whether the RNAi of a candidate gene results in reduced neurotoxicity\ncompared to α-syn expression in a WT background. This is why our focus is on the comparison between\nα-syn alone and α-syn combined with gene RNAi. While it is feasible that, depending on the method of\ncharacterization, a rescue effect may occasionally seem to completely restore WT levels at specific\ntime points, as noted in weeks 1 and 6, this is not the general outcome.\nCollectively, we thoroughly comprehend the reviewer’s concern regarding the unique instance where\nmino RNAi by itself exhibits an atypical effect. We acknowledge this concern and trust that our response\nincluding the additional experimental results provided above addresses the questions raised.\n1.6 In supplementary Figure 1A, authors include the control eGFP RNAi line, it is not evident whether\nthis control is included in the remaining Figures?\nOur response: We apologize for the lack of clarity regarding the above. To clarify, we have utilized the\neGFP RNAi control in our initial experiments with the PR neuronal and nSyb-GAL4 pan-neuronal α-syn\nfly models. However, we encountered significant challenges with this control in the QF2-based models.\nThe eGFP RNAi shows high lethality in the α-syn (QF2) model, which precluded its use in our aging-\nrelated experiments. Moreover, we found that the eGFP RNAi cross-reacts and diminishes the\nexpression and fluorescence of some of the fluorescent protein-based markers and reporters used in\nour study (mito-roGFP2-Orp1, MitoTimer, mIFP, CD8::hPARP1-Venus, and CD8a-RFP-DIAP1-nGFP).\n7 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nDue to the observed high lethality of EGFP RNAi in α-syn (QF2) flies and its unexpected effects on the\nfluorescent protein-based reporters, we therefore decided to use GAL4-only in our subsequent studies,\ni.e., nSyb-QF2, nSyb-GAL4 as controls instead of nSyb-QF2, nSyb>EGFP RNAi for Figure 2 and\nsubsequent Figures. Overall, we found that the mino-related effects are consistently comparable to\nwhen we used eGFP RNAi as controls.\n1.7 Furthermore, in some experimental designs both the RNAi and OE flies are shown in the results,\nwhile in other cases only the RNAi flies are shown (and not the OE). Could the authors clarify this matter?\nOur response: Thank you for highlighting this aspect of our experimental design. The discrepancy in\nthe presentation of mino RNAi and OE stems from genetic cross scheme constraints. The mino OE\nconstruct is located on the third chromosome, while the mino RNAi is on the second chromosome. This\nchromosomal arrangement precluded the direct combination of mino OE with certain reporters, such\nas MitoTimer, which are also located on the third chromosome. Initially, we were unable to generate a\nsuitable experimental design for these reporters without resorting to complex genetic recombination.\nWe undertook a tri-component meiotic recombination strategy between nSyb-QF2, QUAS-SNCA, and\nminof04927 (which also contains an UAS element for mino OE). As a result of this strategy, we were able\nto successfully re-conduct the MitoTimer experiment with the mino OE, and the outcomes are\npresented in Figure 8E and 8F.\n1.8 The neurodegeneration of dopaminergic neurons was assessed by looking at TH+ neurons in the\nPAM region, did the authors look in other brain regions containing TH neurons? And did they confirm the\noverexpression of α-syn in those TH+ neurons as well as the KD or OE of mino?\nOur response: As recommended, we have now extended our analysis to other brain regions containing\nTH-positive neurons, including the PPL1, PPM1/2, and PPM3 clusters. Our results did not reveal a\nsignificant effect of either α-syn or GPAT RNAi on these populations. It is noteworthy to mention that\nthere is a lack of literature on the loss of dopaminergic neurons in these clusters of the α-syn (QF2) fly\nmodel1,3,6-9. Moreover, the findings in other α-syn fly modes over the past two decades have been\ninconsistent, with some studies even reporting contradictory outcomes1,10-31, as summarized in the\ntable below.\n8 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\n1.9 Where is the quantification of fig 1E? Where is fig 1F – it is in the legend and text but not in Figure\npanel? (Effect of changing temperature and effect of O/E data)\nOur response: We thank the reviewer for noticing this. There were apparently unintended spatial\nadjustments in our submitted figure that have obscured the labelling of Figure 1F. We apologize for the\nconfusion and have now corrected it.\n1.10 knockdown only rescues TH neuronal loss in the d42 neuronal loss, not the d30 severe model –\nwhy? What makes one model more severe? Why would there be a difference in the rescue?\nOur response: We thank the reviewer for raising this important point and we acknowledge the need for\na clearer explanation of the outcomes observed in our different fly models. We wish to clarify that there\nis no day 42 and day 30 neuronal loss data in the manuscript. Instead, there is neuronal loss data at day\n49 and day 32 for α-syn (GAL4) model, and day 32 and week 3 for α-syn (QF2) model.\n(1) In the α-syn(GAL4) model, day 32 flies does not show TH+ neuron loss (because this model\nexpresses α-syn more modestly and neuronal loss is not significant at day 32), but day 49 shows TH+\nneuron loss that could be rescued by mino RNAi.\n(2) In the α-syn(QF2) model, which expresses α-syn more robustly, day 32 flies show TH+ neuron loss\n(because this model is severe and shows neuronal loss at earlier timepoint) that could be rescued by\nmino RNAi.\nThe difference in the severity of neurodegeneration between the α-syn (GAL4) and α-syn (QF2) models\nis attributed to the varying levels of α-syn protein expression. The α-syn (GAL4) model exhibits a less\nsevere phenotype, with a notable loss of PAM TH+ neurons evident at day 49 but not at day 32. In\ncontrast, the α-syn (QF2) model demonstrates a more aggressive form of toxicity, with neuronal loss\napparent as early as day 32, thus makes the α-syn (QF2) model more severe. Importantly, although\nvarying α-syn expression levels lead to differences in the timing of neuronal loss, mino RNAi rescues\nTH+ neuron loss in both models. We hope this clarifies the question raised by the reviewer.\nFigure 2:\n2.1 Circadian rhythms are disrupted in the syn o/e model, with partial restoration in KD and partial\nworsening in evening peak with O/E. Which neurons are affected here? Why use the pan neuronal model\nhere? What is the link to α-syn expression and the circuitry involved?\nOur response: We thank the reviewer for highlighting this important aspect of our research. The choice\nof a pan-neuronal model is justified by the fact that α-syn pathology in PD is not restricted to specific\nbrain regions. The pan-neuronal expression pattern in our α-syn fly model reflects the widespread\nexpression of α-syn in the human brain. Given this broad expression, it is challenging to pinpoint the\nexact neurons affected by the manipulation of α-syn and mino.\nCircadian disruptions are indeed non-motor symptoms of PD32-37. Our findings align with previous\nstudies that demonstrated the role of α-syn in circadian rhythm disturbances. For instance, the Ddc-\n9 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nGAL4-driven of α-syn mutants has been associated with both motor symptoms and abnormal sleep-\nlike behavior16. Additionally, the gut-brain axis and the interaction of signaling peptide CCH1a with DA\nneurons regulate arousability from sleep38. Sleep disturbances have been documented in mice Thy1-α-\nsyn model, as well as in mice with selectively induced degeneration of DA neurons via mitochondrial\ndeprivation39,40. Furthermore, studies indicate that sleep deprivation may exacerbate the neurotoxic\neffects of oligomeric α-syn, hastening the loss of DA neurons41. While we speculate that DA neurons\nmay be a key point of intersection for α-syn's impact on circadian rhythms, we acknowledge that other\nfactors, such as lipid metabolism, glial involvement, and circadian-related genes, could also contribute\nto the observed phenomena42-48.\n2.2 Why does glial RNAI alone lead to significant deficit compared to no α-syn expression (in supp fig\n2)??\nOur response: We appreciate the reviewer's attention to this detail. This part has been addressed in\nsection 1.5 of our response.\nWhat is the glial expression of composed to neurons?\nOur response: We believe the reviewer meant \"compared\" instead of “composed”. To clarify, according\nto public single-cell RNA sequencing (scRNA-seq) data, mino is indeed expressed in both glial cells and\nneurons, with a higher expression level observed in glial cells as opposed to neurons49 (Fig. R1.3).\nFigure R1.3. From fly head snRNA-seq dataset\nFlyCellAtlas49.\n2.3 What is syn levels in the glia in the model (presumably none??) - so how would the authors expect\nany effect of knockdown in glia?\nOur response: We confirm the reviewer's notion that in our pan-neuronal α-syn fly model, glial cells do\nnot express α-syn. This has been validated through immunostaining, as depicted in Figure R1.4 below.\nRegarding the impact of mino knockdown specifically in glia, we addressed this in section 1.5 of our\nresponse. We reasoned that mino is required in glia to catalyze LDs formation, because the glycerol-3-\nphosphate backbone in the glia LDs originates from the reaction between glycerol-3-phosphate and\nneuronal-transported fatty acids to form the lysophosphatidic acid, and then converted to\nphosphatidic acid, then diacylglycerol, and finally triglycerides. Among these, the first step is catalyzed\nby mino. On the other hand, neuronal-transported fatty acids may have an alternative fate of being\noxidized by mitochondria. We speculate that glial mino RNAi may affect the balance between the two\n10 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nfates of fatty acids in glia, in a manner that is not identical but is reminiscent of the interesting role of\nmino RNAi in neurons. This may cause lipid profile changes inside glia. Since lipid metabolism has been\nassociated with circadian rhythm of flies, that in turn is associated with locomotor behavior, we\nspeculate that glia mino RNAi may indirectly affect their locomotor behaviors48,50,51.\nFigure R1.4. Immunostaining of repo and α-syn in optic lobe of fly expressing α-syn or not.\n2.4 Supp fig 2 - difficult to see the comparisons and significance because of the annotation (all in thick\nblack bars)\nOur response: We apologize for the poor visual clarity of our data presentation in Supplementary\nFigure 2. To address this, we have revised the figure by reducing the line thickness of all plots, thereby\nmaking the bars and lines less prominent and enhancing the visibility of the comparisons and statistical\nsignificance. We appreciate the feedback and believe this change has significantly improved the\nreadability.\n2.5 Authors state that overexpression aggravates α-syn induced reduction of locomotor activities.\nBased on the Figures, it is unclear if the α-syn flies (in red) were statistically compared to α-syn + OE\n(blue). From looking at the locomotor activity graphs I am not convinced OE aggravates α-syn induced\nlocomotor defects.\nOur response: We agree with the reviewer and apologize for this error of statement in our initial\nsubmission. We have revised our statement. The corrected statement now reads: “This disruption in\nthe circadian rhythm-related locomotor activities in α-syn is alleviated in the presence of mino RNAi”.\nWe thank the reviewer for bringing this to our attention.\n2.6 Lines 209-217, the authors determine that seems to exert its effects on α-syn induced pathology in\nneurons based on the lack of effect on daily locomotor activities when knocking-down in glia, however,\nα-syn expression is driven only in neurons in the pan-neuronal α-syn flie model – they cannot conclude\nthis unless α-syn overexpression and suppression is present simultaneously in the same cell type.\nOur response: We acknowledge the validity of the reviewer's concern. Our initial conclusion may have\noverstated the implications of our findings without direct evidence of co-expression of α-syn and mino\n11 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nsuppression in the glia. In light of this, we have rephrased as follows:\n“Given that metabolic crosstalk between neurons and glia is associated with neuronal energy\nhomeostasis, neuroinflammation, and neurodegeneration, we next investigate whether the changes of\nmino in neurons or glia differentially affect the phenotypes of neuronal α-syn. For this purpose, we\ndownregulated mino expression using RNAi either solely in glia (repo-GAL4) or simultaneously in\nneurons and glia (nSyb-GAL4 and repo-GAL4) and assessed their impact on the fly’s daily locomotor\nactivities. We found that expressing mino RNAi in glia alone has no tangible α-syn-modifying effects,\nwhereas simultaneous mino RNAi expression in neurons and glia mitigates the decline in daily\nlocomotor activities in α-syn flies (Supplementary Fig. 2 C-F). Our results suggest that mino RNAi acts\nmainly in neurons to mitigate α-syn- mediated toxicity”.\nFigure 3\n3.1 The infrared membrane sensor imaging does not look clearly membranous in the images – how was\nthis assessed? Was the membrane sensor used for any analysis (it is not clear if used for merge with\nBodipy, and if it was, then where are the controls for ensuring no cross-excitation/bleed through). Did\nthe total membrane compartment change in α-syn over expression and/or conditions?\nOur response: We thank the reviewer for the careful examination of our imaging data. To address the\nconcerns, we would like to provide the following clarifications:\nImaging Protocol: The infrared channel is excited using a 640 nm laser and images are captured within\nthe 650-750 nm range. We have taken precautions to minimize cross-excitation/bleed-through by\ncapturing the green, red, and infrared channels in separate sessions.\nCross-Excitation/Bleed-Through: Using brains that do not express mIFP, we observed that BODIPY C11\nhas an inherent and unavoidable emission on the infrared channel when excited by the 640 nm laser\n(Supplementary Fig. 3B). This is consistent with the findings by Bailey et al, who also reported a similar\nweak background signal on the infrared channel when using BODIPY C1152. In their report, larval brains\nwere stained with BODIPY C11 and LipidTox Deep Red for LDs visualization. Despite a faint background\nlipid signal being detectable, it is important to note that the LipidTOX-stained LDs exhibit significantly\nhigher brightness compared to the background. In contrast, our imaging settings are adjusted to\nhighlight the background membrane lipids and the relatively dim mIFP fluorescence.\nValidation of mIFP Expression: To confirm the specificity of the infrared signal of the mIFP, we imaged\nmIFP-expressing brains without BODIPY C11 staining and observed membranous signals on the\ninfrared channel (Supplementary Fig. 3B), indicating the presence and membrane localization of mIFP.\nHowever, we noted that the imaging pattern appears dimmer compared to BODIPY C11 staining.\nMembrane Compartment Analysis: Supplementary Fig. 3M demonstrates that brains expressing pan-\nneuronal membrane-tagged Venus reflect overall membrane morphology, which appears similar with\nor without α-syn and mino RNAi. While we cannot ascertain the impact of α-syn on membrane ultra-\nstructure, we seek the reviewer’s understanding that this is beyond the scope of our current study.\n12 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nIn view of the above, we have updated our manuscript to include the following statement: \"Although we\nhave separated the capture sessions for BODIPY C11 and mIFP to minimize bleed-through, there is still\nan inherent emission of BODIPY C11 in the infrared channel, precluding the differentiation of neuronal\nand glial membranes in the images (Supplementary Fig. 3B).\"\nWe appreciate the reviewer's attention to these details and believe that our revised manuscript now\nmore accurately reflects the limitations and considerations of our imaging analysis.\nFig. 6G from Bailey, et al. 201552.\nSupplementary Figure 3B in this study.\n13 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nSupplementary Figure 3M in this study.\n3.2 When assessing lipid peroxidation with imaging, it is useful to have a positive control to determine\nthe dynamic range of the dye and be able to detect the oxidised C11-Bodipy (ex:488) signal.\nOur response: We agree with the reviewer and as recommended, we have now included a positive\ncontrol to establish the dynamic range of the BODIPY C11 dye. We used H O -treated neurons as a\n2 2\npositive control in Supplementary Figure 3B and 3C. The results on these Figures demonstrate the\nresponsiveness of the dye to oxidative stress, with neurons treated with 20 mM H O for 30 minutes\n2 2\nexhibiting a notable increase in the green to red signal ratio, confirming the dye's sensitivity to lipid\nperoxidation.\nFrom the images on Figure 3A, there seems to be no difference in oxidised C11-BODIPY across all four\nconditions, despite the quantification in Figure 3C showing significant differences. Therefore the images\ndo not represent the quantification.\nOur response: We acknowledge the reviewer's observation and understand the potential for confusion.\nThe lack of visually apparent differences in the oxidized C11-BODIPY signal across the conditions may\nindeed seem at odds with the significant differences reported in the quantification. This discrepancy\ncan be attributed to the inherent variability in staining intensity between samples, which is a common\nchallenge in such imaging studies. To address this, our analysis relies on the ratiometric approach,\nwhich is a standard method for assessing lipid peroxidation levels using BODIPY C11. By calculating\nthe ratio of green (oxidized) to red signal, we are able to normalize for variations in staining and provide\na more accurate representation of lipid peroxidation levels. The quantification of mean intensity per fly\nfor both oxidized and reduced forms, as presented in Figure R1.5 below, supports the statistical\ndifferences observed.\n14 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nFigure R1.5. BODIPY C11 oxidized and reduced intensity of fly brains, respectively.\n3.3 Figure 3f, the measures of cell death in optic lobes assessed by TUNEL seems very low. I am\nconcerned the window of cell death is too small to detect a protection or worsening with RNAi/OE.\nOur response: We share the reviewer’s concern regarding the potential narrowness of the window for\ndetecting cell death, which could impact the assessment of protective or exacerbating effects\nassociated with mino RNAi/OE. To address this issue, we have taken several steps to optimize the\nTUNEL staining procedure. We have ordered a new TUNEL assay kit, implemented a pre-wash step\nusing dilution buffer to enhance the effectiveness of the buffer, and increased the incubation volume\nfrom 5 µl to 10 µl per sample group. These modifications have resulted in an improved TUNEL signal,\nallowing for a more robust detection of changes in cell death rates. The enhanced staining protocol is\nreflected in the updated data presented in Figure 3C and 3D, where the effects of mino RNAi/OE on cell\ndeath are now more clearly discernible.\nWhat was the rationale behind assessing cell death in the optic lobes instead of the PAM region where\nthe authors previously confirmed a reduction in TH+ neurons?\nOur response: The decision to evaluate cell death in the optic lobes was based on the need for a region\nwith a sufficient number of cells to yield a statistically meaningful TUNEL signal. The optic lobes, with\ntheir population of approximately 70,000 cells53, allow for the detection of TUNEL-positive spots in the\ndozens within the context of α-syn fly brains. In contrast, the PAM cluster, comprising only about one\nhundred neurons, does not provide a sufficient sample size to yield quantifiable TUNEL-positive cells\nfor analysis, as illustrated in Supplementary Figure 3I. Our approach of assessing cell death in the\noptic lobes, in addition to monitoring TH+ neuron loss in the PAM cluster, represents a more\ncomprehensive way to characterize cell/neuron death in α-syn brains. We believe that this dual\napproach ensures a more thorough understanding of the neurodegenerative process in our model.\n15 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\n3.4 A positive control for the 4-HNE staining would be helpful\nOur response: We appreciate the reviewer's suggestion for the addition of a positive control for the 4-\nHNE staining. We have carefully considered this important point and have made the decision to exclude\nthe fly 4-HNE staining data from the manuscript. This decision was based on the observation of an\naberrant staining pattern that could be attributed to non-specific binding, thereby compromising the\nreliability of the data. To ensure the validity of our staining assays, we have included positive controls\nfor other assays within the study. Specifically, a positive control using hs-hid for the apoptosis reporter\nassay is provided in Supplementary Figure 3G, 3L, 3J, and the use of H O as a positive control for the\n2 2\nTUNEL assay is shown in Supplementary Figure 3O. These controls demonstrate the effectiveness of\nour staining protocols in appropriate experimental contexts.\nFigure 4:\n4.1 Figure 4A – Similarly to Sup fig1a, RNAi alone increases climbing height in the absence of α-syn,\ntherefore the α-syn neurotoxicity “rescue” observed in the α-syn + RNAi fly may not be due to the\ninteraction of with α-syn, but merely the RNAi line performing better in the first place. Figure 4B does not\nshow the effect of RNAi alone, which may show an increase the daily locomotor activities based on the\nincrease in startle-induced climbing abilities.\nOur response: We acknowledge the reviewer's insightful observation regarding the impact of mino\nRNAi on climbing behavior in the absence of α-syn. The reviewer's point is well taken, and we have\naddressed this in section 1.5 of our response above.\nOur findings indicate that the climbing assay and daily locomotor assay do not always correlate, which\nwe attribute to the distinct nature of these assays. The climbing assay provides a momentary snapshot\nof startle-induced behavior, while the daily locomotor assay offers a continuous assessment of activity\nover time. In light of this, we have pivoted our focus to the daily locomotor assay, which we believe\nprovides a more comprehensive view of the flies' behavioral changes. As noted in Figure 2A, mino RNAi\nalone does not alter daily locomotor activities in flies without α-syn. We also wish to highlight that the\nabsence of additional control groups in original Figure 4B is due to the constraints of the DAM2\nlocomotor assay plate, which has a limited capacity. With six groups already included on the assay\nplate, there was insufficient space to accommodate the four additional control groups. Given the\nestablished lack of effect of mino RNAi on locomotor activity without α-syn, we prioritized the\nexperimental groups that were most relevant to our hypotheses.\nWe hope the reviewer will find our above clarifications acceptable.\n4.2 GPAT rescue behavioural phenotype but do they rescue the lipid peroxidation phenotype as well?\nWere these tested, as they would be important to link the mechanism with Mino?\nOur response: We appreciate the reviewer's suggestion to explore the effects of other GPAT on lipid\nperoxidation, which will enhance our understanding of the mechanism of action linked to mino. While\nwe have not yet extended our BODIPY C11 assays to include other GPAT, we recognize the importance\nof this line of inquiry. We plan to address this in future studies, which will further elucidate the role of\nGPAT in lipid homeostasis and its relation to neurodegenerative phenotypes.\n16 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nFigure 5\n5.1 Line 308 - how can monomeric α-syn be in the insoluble fraction (by definition is intrinsically\ndisordered in solution) - not sure these references quoted here can define this. Following\nbuffers/denaturation the α-syn may have been denatured to its monomeric form.\nOur response: To clarify, our lysis method involves squashing dissected brains in lysis buffer, and the\nlysate is directly loaded onto western blot gels without centrifugation to separate fractions. Therefore,\nwe did not physically separate insoluble fractions from the lysate. The references cited in the\nmanuscript used a different approach, involving the separation of soluble and insoluble fractions from\nwhole heads. To address this issue, we have revised the manuscript to remove the words “soluble and\ninsoluble fractions” to prevent misunderstanding. Additionally, we have included new data from\nproteinase K digestion experiments in Supplementary Figure 7B, which demonstrate the absence of\ndetectable proteinase K-resistant α-syn aggregates in the α-syn fly heads. We believe these revisions\nand additional data help clarify the nature of the α-syn species we are detecting in our assays.\n5.2 The authors use a biochemical method with cross linking to show α-syn exists as oligomers in\nfractions - supported in supp fig 4. Where is the α-syn KO to show the specificity of the antibody here -\nor the authors would need to mass spec the bands to show that the higher bands are indeed α-syn.\nHigher bands are often non specificity and controls/further evidence that this method is detecting\nhigher order oligomers is required - all of Fig 5a-c requires these controls. Additional techniques to\nassess α-syn aggregation like ELISAs kits and microscopy imaging (ThT, amytracker for amyloid staining\nformation or pS129 α-syn) may be helpful.\nOur response: To address the concerns raised:\nSpecificity of the Antibody: Drosophila do not ordinarily express α-syn. The non-transgenic control\nnSyb-QF2, which lacks the QUAS-SNCA transgene, is indeed included in the original Figure 5A-5C as\nindicated by the circles below in our figure (see reproduced figure below). The leftmost lane in Figure\n5B clearly shows a very clean background in the nSyb-QF2 control, demonstrating the absence of non-\nspecific binding. We apologize for any confusion caused by the initial presentation of the lanes, which\nmay have inadvertently led to misinterpretation, such as mistaking a lane for the image margin. The\nFigure is more clearly annotated in the revised manuscript to avoid misinterpretation.\nValidation of Higher Molecular Weight Bands: We appreciate the reviewer's recommendation to further\nvalidate the higher molecular weight bands observed. Although mass spectrometry is indeed a\ndefinitive technique for protein identification, it is not commonly employed for the detection of α-syn\noligomers in Western blot analyses and we also face logistical challenges for its detection via MS.\nFurthermore, the α-syn antibody utilized in our study is widely recognized for its high quality and\nreliability, which provides confidence regarding its specificity.\nWe agree with the reviewer that complementary techniques can provide a more comprehensive\nunderstanding of α-syn aggregation. We have added proteinase K digestion experiments\n(Supplementary Fig. 7B) and found no detectable proteinase K-resistant aggregated α-syn in the fly\nbrains, and we have also included Western blot analysis of pS129-α-syn (Fig. 7A) in the updated\n17 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nmanuscript.\nMoving forward, we are keen to study the mechanism underlying mino-mediated effects on α-syn\naggregation as a related but separate study and will use the spectrum of relevant assays that the\nreviewer has suggested, such as ELISA kits, ThT fluorescence assays, and amyloid staining with\nAmytracker, to comprehensively confirm the formation of α-syn oligomers and aggregates.\n5.3 The authors investigate mitochondrial H O - what about whole cell ROS? Why not first see whether\n2 2\ngeneralised lipids can do this phenomenon and then ask the compartmentalised question of the effect\nin the mitochondria?\nOur response: The reviewer raises a valid point regarding the investigation of whole cell reactive oxygen\nspecies (ROS) in comparison to mitochondrial H O . While it is true that ROS generation is not exclusive\n2 2\nto mitochondria and could occur in other cellular compartments, our initial focus on mitochondrial\nH O was driven by the specific localization prediction of mino to the mitochondria and the established\n2 2\nliterature reporting α-syn-induced mitochondrial ROS production. Additionally, our use of MitoTimer\nanalysis has provided valuable insights into the temporal accumulation of ROS within the mitochondria.\nWe nonetheless acknowledge that a broader assessment of whole cell ROS could provide a more\ncomprehensive understanding of the phenomenon. The similarity in effects between GPAT and mino on\nα-syn toxicity suggests that ROS production might indeed be a more generalized cellular response. In\nfuture studies, we will incorporate cellular ROS sensors, such as cytosolic H O sensors, to investigate\n2 2\nthe broader cellular ROS landscape.\nWhat causes the MitoTimer appearances in α-syn o/e fly? Are the mitochondria damaged in this model?\nThis phenotype needs to be determined before it is possible to understand the effect of in this model.\nOur response: Thank you for your insightful query regarding the MitoTimer appearance in the α-syn flies\nmodel and the potential mitochondrial damage. To address this, we reference existing literature that\n18 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nhave documented mitochondrial fragmentation and alterations in size and shape in fly brains with pan-\nneuronal α-syn expression3.\nThe MitoTimer fluorescence we observed reflects the mitochondrial morphology changes, as MitoTimer\nis targeted to the mitochondria. Regarding the MitoTimer's purpose, in contrast to mito-roGFP2-Orp1,\nwhich measures transient H O levels at a specific time point, MitoTimer is designed to assess the\n2 2\ncumulative redox history of ROS. MitoTimer's fluorescence color change over time with a basal rate but\nis accelerated in the presence of ROS-generating chemicals like rotenone, antimycin, and paraquat54.\nWe have refined the description of MitoTimer in our manuscript to clarify this point: \"Alongside the\ntransient H O sensor, we utilized MitoTimer, a probe that captures the cumulative redox history of\n2 2\nmitochondria by shifting in green-to-red fluorescence, to investigate the historical accumulation of\nmitochondrial ROS (MitoTimer aging) in our fly model.\"\nIn our revised manuscript, we have included additional analysis of MitoTimer in the context of GPAT and\nmino overexpression (Fig. 8E and 8F). Our findings suggest a novel metabolic pathway involving GPAT\nand α-syn, where α-syn induces a blockade in the TCA cycle, leading to citrate accumulation and\nsubsequent de novo fatty acid synthesis. We further found that GPAT mediates the partitioning of fatty\nacids to neuronal membrane lipid synthesis and glial LDs, which provides a clearer understanding of\nmino's role in this model.\n5.4 Mitochondria is the main source of superoxide production. Could the authors explain on their choice\nof measuring H O ?\n2 2\nOur response: We appreciate the reviewer's inquiry regarding the choice of measuring H O instead of\n2 2\ndirectly measuring superoxide production in mitochondria. The decision to utilize the H O sensor was\n2 2\nprimarily influenced by the practicality and accessibility of the available resources within the\nDrosophila stock center. The H O sensor stock is not only readily accessible but also widely recognized\n2 2\nfor its ease of use in Drosophila research. Moreover, H O is a downstream product of superoxide anion\n2 2\nradical, and its measurement provides a valuable indirect assessment of mitochondrial superoxide\nproduction. We believe that this approach aligns with current standards in the field and offers a robust\nmeans of evaluating oxidative stress responses in our model system.\nFurthermore, there is no data to support that the H O sensor mito-roGFP2-Orp1 is localised to the\n2 2\nmitochondria. A co-stain with a mitochondrial dye such as TMRM or mitoTracker would support this\nassay.\nOur response: We appreciate the reviewer's concern regarding the localization of the H O sensor mito-\n2 2\nroGFP2-Orp1 to the mitochondria and the suggestion to use mitochondrial dyes such as TMRM or\nmitoTracker to confirm the localization. We wish to clarify that the mitochondrial localization of mito-\nroGFP2-Orp1 has indeed been validated by others as shown below55. In this Figure, they demonstrate\nthe co-staining of mito-roGFP2-Orp1 with TMRM, providing evidence of its mitochondrial localization.\nAdditionally, to further reinforce the specificity of our assay, we have included a co-staining with ATP5A\nin Supplementary Figure 7C, which confirms the mitochondrial localization of MitoTimer and ensures\nthat our observations with the MitoTimer sensor are also specific to the mitochondrial compartment.\n19 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nSupplementary Figure 1 from the reference55\nThroughout the manuscript, the statistical comparisons carried out are confusing (i.e fig 5g, α-syn flies\nshould be compared to no α-syn flies, and not RNAi)\nOur response: We thank the reviewer for pointing out the confusion in the statistical comparisons,\nspecifically in Figure 5G. We apologize for our oversight and appreciate the opportunity to clarify this\nmatter. We have corrected the labeling in Figure 8D (previously Fig. 5G) in the revised manuscript. We\nhave updated the Figure legends to improve clarity. For example, in Figure 1B legend, we added the\nstatement “The asterisks in b indicate the comparisons of α-syn with mino RNAi and α-syn with EGFP\nRNAi”. We believe this approach will aid in the reader's understanding of the data presented. Alongside\nthis, we have also carefully considered and revised the color scheme for our Figures to reduce\nconfusion. For example, in the revised manuscript, we avoided using green and red in the labeling, due\nto color preference concerns. We appreciate the reviewer's attention to this detail and the opportunity\nto improve our data presentation.\nUpdated Figure 8D.\nFigure 6:\n6.1 Figure 6A – The pS129 α-syn antibody seem to be staining almost the entire neurons which is\nunexpected for a phospho syn stain where you would expect punta stain in the aggregates.\nOur response: Thank you for highlighting the staining pattern observed with the pS129 α-syn antibody.\nWe acknowledge that the initial images presented a more diffuse pattern than the anticipated punctate\n20 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nstaining of aggregates. As reported by Volpicelli-Daley, L. A., et al. (2011) )56, the pS129 staining can\nassume diverse forms, including punctate, intermittent, filamentous, and Lewy body-like structures, all\nof which are also represented in our images. Additionally, the staining morphology can vary with\nincubation time. In response, we updated Figure 9A with images that depict the punctate staining better.\nMoreover, we observed the distinctions in pS129 staining morphology between human and mouse\nneurons treated with PFF, with human neurons typically displaying a more distinct punctate\nmorphology (unpublished data).\n6.2 Furthermore, the 488 BODIPY stain doesn’t seem specific to the neurons as the background signal\nis considerably higher in the PFF treated conditions. Is the 488 BODIPY referring to the oxidised form of\nthe C11 BODIPY or the BODIPY 493/503? C11-C11 Bodipy is a lipophilic dye that specifically locates to\ncellular membranes, while BODIPY 494/503 stain nonpolar lipids. Either way, I am not sure the BODIPY\nstain is measuring lipid peroxidation. Because the PFFs are everywhere there would be chance\ncolocalization with Bodiipy.\nOur response: We apologize for the confusion regarding the BODIPY label; the correct dye used is\nBODIPY 493/503. We agree with the reviewer's observation that the BODIPY 493/503 signal does exhibit\nvariable background levels, particularly in the PFF-treated conditions, and it does not exclusively target\nneuronal membranes. To address the specificity of the BODIPY 493/503 stain, we conducted control\nexperiments where we treated coverslips with PFF in the absence of neurons and observed no\nbackground staining. This suggests that the observed background is indeed neuron-dependent.\nConsidering this, we have removed the BODIPY 493/503 staining data from the current manuscript to\navoid any misinterpretation of the results. We are committed to ensuring the accuracy and specificity\nof the data presented and we thank the reviewer for bringing this issue to our attention.\n6.3 How do the authors know that the GPAT inhibitor is not just reducing uptake of the PFFs causing less\np-syn staining, rather than affecting seeding/aggregation?\nOur response: We agree with the reviewer and acknowledge the valid concern. At this stage, we do not\nhave direct evidence to definitively distinguish between the inhibitor's effect on PFF uptake versus its\ninfluence on seeding/aggregation. We acknowledge this limitation and agree that it is a critical question\nthat warrants further investigation. To address this, we are planning future studies that will utilize\nfluorescence-labeled PFFs to directly assess the impact of the GPAT inhibitor on PFF uptake and\nseeding efficiency. These experiments will provide a more detailed understanding of the inhibitor's\nmode of action in the context of p-syn pathology. Notwithstanding, we have now included this\nimportant point that the reviewer has raised in our revised discussion:\n“While our data demonstrate that the GPAT inhibitor reduces pathological α-synuclein (p-syn)\naccumulation, the precise mechanism—whether through diminished PFF uptake or direct interference\nwith seeding/aggregation—remains unresolved. Although we cannot yet definitively rule out an effect\non PFF internalization, the observed reduction in p-syn suggests a potential role for GPAT inhibition in\nmodulating α-synuclein aggregation dynamics. Future studies employing fluorescence-labeled PFFs\nwill be critical to dissect the inhibitor’s impact on uptake versus seeding efficiency, thereby clarifying\nits mechanism of action.\"\n21 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\n6.4 Background staining in the PFF treated may be artifact of autofluorescence of protein added to cells\n- there is no equivalent control for this\nOur response: We thank the reviewer for highlighting this important point. To address this issue, we\nhave conducted control experiments where we treated coverslips with PFF alone, in the absence of\nneurons, and did not observe any BODIPY 493/503 background staining. This suggests that the\nbackground fluorescence observed is likely neuron-dependent and may or may not be related to the\nPFF protein itself. Nonetheless, given the uncertainty surrounding the origin of the background\nfluorescence, we have removed the BODIPY 493/503 staining data from the manuscript in this revision.\nWe believe this decision ensures the integrity of the data presented and avoids any potential\nmisinterpretation.\n6.5 Define replicates in fig 6 - technical from single wells, or across multiple animals?\nOur response: In the initial submission, the replicates referred to were indeed technical replicates\nderived from single animals. To enhance the robustness of our findings, we have since conducted\nadditional experiments that include biological replicates from multiple animals. For the pS129 and\nBODIPY C11 data, we have now included three data points in Figure 9G, each representing the mean of\ntechnical replicates from separate animals. This approach provides a more comprehensive view of the\nvariability across different samples. Regarding the MDA and 4-HNE data, we encountered issues with\nantibody performance between different batches, which limited our ability to include biological\nreplicates from multiple animals. As a result, the current data for MDA and 4-HNE are based on\ntechnical replicates from a single animal. We acknowledge this limitation and are actively working to\naddress the antibody variability to improve the reliability of these measurements. In the revised\nmanuscript, we have clarified the definitions of replicates in the Figure legend to ensure that the readers\nunderstand the nature of the data presented.\n6.6 To strengthen the effect of GPAT suppression in α-syn induced lipid peroxidation in neurons, I would\nsuggest adding a genetic supression (si/shRNA) in addition to using the pharmacological inhibition in\ncase the FSG67 has non-specific targets, specially at the concerningly high concentrations used in this\npaper (75 and 150 mM whilst the IC50 is in the low uM range ).\nOur response: We thank the reviewer for the valuable and agree that the use of genetic suppression,\nsuch as si/shRNA, is indeed a robust approach to complement our pharmacological inhibition with\nFSG67. FSG67 is a fatty acid analogue specifically designed to target GPAT enzymes, and its efficacy in\nreducing triglyceride synthesis has been demonstrated in previous studies57,58. As recommended, we\nare planning to include GPAT siRNA experiments in our future studies to reinforce the specificity of our\nfindings. However, for the current manuscript, we believe that the existing data reasonably supports the\nspecificity of FSG67's action on GPAT. Importantly, we would like to clarify that the concentrations of\nFSG67 employed in our experiments were 75 and 150 µM, not mM, as incorrectly stated in the method\nsection. We apologize for this typographical error and have corrected it in our revised manuscript.\n22 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nREVIEWER #2\nRen et al. report a novel role of the fly GPAT homolog mino as modulator of α-syn mediated toxicity in a\nfly model of Parkinson’s disease. They found that mino silencing suppress several phenotypes\nassociated with α-syn expression in flies. Silencing of other GPAT produce similar beneficial effects. The\npharmacological inhibition of GPAT via FSG67 is also beneficial in both flies and mouse primary neurons\nexpressing α-syn. This is an interesting work with solid quantification methods. My enthusiasm is\ntempered due to several pitfalls in the study.\nOur response: We thank the reviewer for the positive comment that our report represents “interesting\nwork with solid quantification methods” and for the recommendations below to improve our study.\n1. First the entire study is only based on a silencing approach, which may be associated with off target\neffects. The standard in the field is to use loss of function mutations combined with rescue experiments.\nThey should at least confirm their observations with available mutants for the genes tested in the paper.\nOur response: We appreciate the reviewer’s concern regarding the potential off-target effects\nassociated with our silencing approach. We acknowledge the field’s standard practice of utilizing loss\nof function mutations complemented by rescue experiments. At the time of submission, we were in the\nmidst of selecting and validating the mutants and recombining the mutant with α-syn flies. The table\nbelow summarizes the mino mutants that we have tested (see also Fig. R2.1a).\nBDSC# insertion comment\n22297 minoEY18945 The mino RNA expression level is about 90% of w1118.\n18818 minof04927 We have verified that minof04927 is a WH insertion in the annotated\norientation. Although the original line is homozygous lethal, after\noutcrossing to w1118, we established a stock of viable and fertile\nhomozygotes. Head qPCR results show 50% decrease in the mino\ntranscript level in the original stock balanced with TM6B (Fig. R2.1b)\nand decreased to 17% in outcrossed homozygotes (Fig. R2.1c).\n85124 minoe01419 Through PCR verifications, we have shown that this is a wrongly\nannotated line with no insertion of RB in mino, but with a PB\ninsertion elsewhere. Additionally, PCR band crossing the annotated\ninsertion site was obtained from the homozygotes, the same as wild\ntype flies. This line thus has been shelved from the DBSC stock\ncenter. Head qPCR shows a mino transcript level similar to wild-\ntype flies.\n86114 Gpat4f06898 Homozygote lethal mutant. Head qPCR of outcrossed\nGpat4[f06898]/+ shows a 34% decrease of Gpat4 transcript level.\n23 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nminof04927 homozygote mutation shows a reduction of mino transcript in the head to 17% of its normal\nlevel and corresponding upregulation of transposon flamenco-2, 1731 and 42AB in fly body-extracted\nmRNA (Fig. R2.1c) that is in agreement with the role of mino in regulating transposon silencing in the\ngermline. We found that partial loss of mino or Gpat4 heterozygotes using minof04927/+ and Gpat4f06898/+\ncould mitigate the decline of daily locomotor activities and PAM cluster dopaminergic neuron loss in α-\nsyn-expressing flies (Fig. R2.1d and e), which confirm our observations using RNAi lines.\nTo further explore the effect of severe reduction of mino, we integrate the minof04927 homozygote in the\nPD model by recombination of minof04927, nSyb-QF2 and QUAS-SNCA, and then cross to minof04927\nmutants (Fig. R2.1f and g). We found that when α-syn is absent, minof04927 homozygote alone causes a\ndecrease of PAM TH+ neurons (Fig. R2.1i) and mild reduction of daily locomotor activities (Fig. R2.1h),\nsuggesting that although mino is not an essential gene (which may be because of the redundancy\namong other GPAT members), its severe reduction alone has adverse effect. Consistent with this, we\nalso observed that high concentration of GPAT inhibitor FSG67 (5 mM) feeding in wild-type flies causes\nreduction of locomotor activity (Fig. 6G). When α-syn is present, minof04927 homozygote neither mitigate\nthe loss of the PAM TH+ neurons (Fig. R2.1i) nor the extent of TUNEL-labeled cell death in the optic lobe\n(Fig. R2.1j). We also observed that in α-syn fly brains, minof04927 homozygote causes a surge of\nlocomotor activities during the 1st week, but after week 1 the locomotor activities deteriorate to a level\nworse than α-syn flies alone (Fig. R2.1h). These data reveal complex and time-dependent interplay\nbetween mino and α-syn when mino is manipulated to a dramatically lower level.\nTo further analyze the cell-type-specific effect of mino in α-syn flies, we utilize the cis-oriented UAS\nelement in the minof04927, which allows the minof04927 flies to transform from deficient to mino\noverexpression state when GAL4 is added (Fig. R2.1f). We verified the UAS element that nSyb-GAL4/+\ndriving minof04927 homozygote cause a 20-fold increase of head mino transcripts (Fig. R2.1b). We found\nthat adding repo-GAL4 to minof04927 homozygote in α-syn flies, which drives glia-specific mino\noverexpression (i.e. leaving mino expression in neurons deprived), further mitigate the PAM cluster\ndopaminergic neuron loss and TUNEL-labeled cell death in the optic lobe (Fig. R2.1i and j). On the\ncontrary, adding nSyb-GAL4 to minof04927 homozygote in α-syn flies, which mimics a brain condition of\nneuron-specific mino overexpression and glia-specific mino deprivation, further exacerbates the PAM\ncluster dopaminergic neuron loss and TUNEL-labeled cell death in the optic lobe (Fig. R2.1i and j).\nWhen α-syn is absent, all these manipulations have no further effect on PAM neuron decrease or cell\ndeath (Fig. R2.1i and j).\nBased on these results and considering that mino RNAi and minof04927/+ both show about 50% decrease\nof mino transcripts, we propose that mild reduction of mino, preferably in the neuron but also feasible\nin the whole brain, is the optimal strategy in mitigating α-syn neurotoxicity, in comparison to drastic\ndeprivation of mino or the glia-specific mino deprivation.\n24 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nFigure R2.1 (a) Schematic illustration of mino gene transcripts and the position of insertion mutations. The\ndirection of UAS elements in the insertions are indicated on top of arrows. The red blocks indicate coding DNA\nsequences, and the gray boxes indicate the un-translated regions.\nFigure R2.1 (b) qPCR analysis of mino expression from head-extracted mRNAs. Each data point was taken from\ndistinct pooled head samples. N = 3.\nFigure R2.1 (c) qPCR analysis of GPAT, several lipid metabolism-related genes and reported target transposons\nfrom head- and body-extracted mRNAs of w1118 and minof04927. Each column of data points was taken from distinct\npooled samples. All the data are normalized to w1118 head. N = 3.\n25 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nFigure R2.1 (d) Effect of minof04927/+ and Gpat4f06898/+ on PAM cluster TH+ neurons in flies incubated at 29oC for 3\nweeks.\nFigure R2.1 (e) Effect of minof04927/+ and Gpat4f06898/+ on daily locomotor activities of flies expressing α-syn or not.\nN = 10, 10, 10, 12, 12, 12.\nFigure R2.1 (f) Schematic illustration of the design of minof04927 transformed\nfrom mutant status to mino overexpression status.\n26 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nFigure R2.1 (g) Single fly PCR verification of the meiotic recombination between minof04927 (using primers BSF2p-\nGolic: AGCTCGTTACAGTCCGGTGCGTTT; w3UTR-F: TGTGACCTGTTCGGAGTGATTAGC;), nSyb-QF2 (using\nprimers nSybPro-200F: CGAAAGGCTGTCGTGGCAAGTG; QF2+200R: GGGACACTCGTTGACGCTTTGA;) and\nQUAS-SNCA (using primers hsp70-F: CCAGCAACCAAGTAAATCAACTGC; hSNCA-R:\nTTAGGCTTCAGGTTCGTAGTCTTG).\nFigure R2.1 (h) Effect of minof04927 homozygote on daily locomotor activities of flies expressing α-syn or not. N =\n10.\nFigure R2.1 (i) Effect of minof04927 homozygote and cell type-specific overexpression conversion on PAM cluster\nTH+ neurons in flies incubated at 29oC for 3 weeks. N = 68, 65, 67, 71, 77, 64, 70, 59.\n27 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nFigure R2.1 (j) Effect of minof04927 homozygote and cell type-specific overexpression conversion on TUNEL\nquantification of the optic lobe of flies incubated at 29oC for 3 weeks. Scale bar = 40 um. N = 40, 39, 39, 39, 55,\n62, 72, 61.\nNote: Each data point indicates one biological replicate. Data were analyzed with one-way ANOVA followed by\nTukey’s and Dunnett’s multiple comparisons test. Data are presented as mean ± S.D. *p < 0.05, **p < 0.01, ***p <\n0.001, and ****p < 0.0001.\n28 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nTo address concerns about RNAi off-target effects, in addition to the mino RNAi line used (minoHMJ30154),\nwe have tested another RNAi line, minoHMS05787. We found that pan-neuronal Gal4 driving minoHMS05787\nleads to 100% lethality, tested using the available nSyb-Gal4 lines in the table below. Since minof04927 is\nan effective mutant and the homozygote is viable and fertile, we suspect that minoHMS05787 is an off-\ntargeting line that targets some other essential gene(s). Interestingly, when we test this off-targeting line\nin glia using repo-GAL4, the flies could survive to adult stages. These findings suggest that the unknown\noff-target gene(s) of minoHMS05787 are critical in neurons during neuronal development.\nlethality with lethality with\nnSyb-GAL4 lines\nminoHMJ30154 minoHMS05787\ny[1] w[*]; P[w[+m*]=nSyb-GAL4.S]3; viable 100% lethal\ny[1] w1118; P[y[+t7.7] w[+mC]=nSyb-GAL4.P]attP2 viable 100% lethal\nw1118; M[w[+mC]=nSyb-GAL4.P}ZH-86Fb]/TM6B viable 100% lethal\nw[*]; P[y[+t7.7] w[+mC]=GMR57C10-GAL4]attP40 viable 100% lethal\nw1118; P[y[+t7.7] w[+mC]=GMR57C10-GAL4]attP2 viable 100% lethal\nFor Gnpat, we have verified a homozygote viable mutant GnpatCR00030 which decreased to 17% of its\nnormal transcript level. Currently in the process of outcrossing and will subsequently verify the Gnpat\ninsertion mutants. However, our preliminary experiments (data not shown) using the not-yet\noutcrossed GnpatCR00030/+ heterozygotes show that GnpatCR00030/+ alone cause a reduction of locomotor\nactivities in brains regardless of with or without α-syn. Nevertheless, the GnpatCR00030/+ still rescue the\nloss of PAM TH+ neurons in α-syn brains. This corresponds well to our previous unexpected RNAi results\nthat Gnpat RNAi also mitigates PAM TH+ neuron loss but does not improve locomotor activities of α-syn\nflies.\nAs for CG15450, due to the current unavailability of mutants, we may consider generating mutants\nusing CRISPR technology in our future extension studies.\n2. Another issue also related to the first one is that there is no evidence that silencing of mino (or other\nsilenced genes tested in the study) affects the production of LPA, PA and ultimately TAG. mino OE has\nbeen shown to be sufficient to induce lipid droplet production. Are TAG-lipid droplets detected in the\nstudy?\nOur response: We thank the reviewer for the excellent suggestion regarding the need to establish a\ndirect link between the silencing of mino and other genes and the production of LPA, PA, and TAG. At\nthe time of submission, we were in the process of investigating the lipid droplets (LDs) of fly brains and\nthus this unfinished part was not included in the initial submission. The revised manuscript now\nincludes a new section (Neuronal α-syn causes non-toxic LDs accumulation in glia) along with\nFigure 4. In brief, we found that in brains without α-syn, LDs are predominantly found in the central brain\nbut not optic lobe. However, pan-neuronal α-syn leads to a marked accumulation of LDs in the optic\nlobe. We confirmed the glial localization of LDs. Furthermore, manipulation of LDs through the\nexpression of TG lipase bmm and Lsd-2 revealed that changes in LDs levels do not affect the toxic\neffects of α-syn on TH+ neurons or cell death, suggesting that LDs are non-toxic by-products.\nOur data also show that GPAT RNAi increase LDs, whereas mino overexpression does not. Instead, mino\n29 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nOE enhances the BODIPY 493/503-stained background, indicating a role for neuronal mino in\nmembrane lipid synthesis rather than triglycerides. This suggests that neuronal GPAT RNAi may\ninfluence the fate of neuronal fatty acids between membrane lipid synthesis and their transport to glia.\nIn the revised manuscript we also provided supporting evidence from public single-cell RNA\nsequencing datasets showing that DGAT(mdy), which catalyzes the last step of triglyceride synthesis,\nis predominantly expressed in glia but not CNS neurons.\nTo delve deeper into the mechanisms behind increased lipid synthesis, we have performed a short-\nchain fatty acid (SCFs) metabolomics assay, which revealed a specific blockage in the TCA cycle before\nα-ketoglutarate, leading to the accumulation of α-ketoglutarate, isocitrate, and citrate. These\nmetabolites favor de novo fatty acid synthesis, which is consistent with increased glial LDs\naccumulation. The new data are presented in a new result section (TCA cycle metabolites α-\nketoglutarate, isocitrate, and citrate are specifically increased in α-syn fly brains and contribute\nto glial LDs and neuronal phospholipid synthesis) along with Figure 5. With these new insights, we\nalso updated the abstract image (see updated image below).\nRegarding the analysis of LPA and PA, we conducted fly brain lipidomic analysis (Supplementary Fig.\n6) using a pool of n=10 fly brains. Phospholipids constitute the largest proportion (40.05%) of total fly\nbrain lipids. The percentage of phospholipids increased with α-syn expression (log2(FC) = 0.15), an\neffect that was mitigated by mino RNAi (log2(FC) = 0.07) and enhanced by mino overexpression (log2(FC)\n= 0.17) (Supplementary Fig. 6A). Among phospholipids, PC and PE, the two most abundant species\ncomprising over 95% of total phospholipids, exhibited similar trends in response to α-syn expression\nand mino RNAi (Supplementary Fig. 6B). A common phenomenon related to changes in PC and PE in\nα-syn-expressing brains is the increased presence of monounsaturated fatty acids (MUFAs) and the\ndecreased presence of polyunsaturated fatty acids (PUFAs) (Supplementary Fig. 6C and 6D). In\nagreement with this, α-syn-expressing fly brains show increased transcripts of Pcyt1 and Pect, which\nencode enzymes catalyzing the rate-limiting steps of PC and PE synthesis, and increased Desat2, which\nencodes stearoyl-CoA 9-desaturase for MUFA generation, and also a homologue of human α-syn\ntoxicity modifier SCD59,60 (Supplementary Fig. 6E). Additionally, 3 lipid species—Cer-NS (d16:1/24:0),\nTG (50:4)-FA18:3, and TG (54:2)-FA18:2—were detected only in α-syn-expressing fly brains\n(Supplementary Fig. 6F). LPA is not detectable in the sample. PA constitutes 0.1% of total brain lipids\nand the data is shown in the Table below.\n30 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nFigure R2.2 Lipidomic analysis comparing the α-syn’s effect on relative proportion of various lipid species in\ncontrol, mino RNAi and mino OE background.\nmino RNAi mino OE α -syn,mino RNAi α -syn,mino OE\nPA/total lipids Ctrl /Ctrl /Ctrl α-syn /α -syn /α -syn\nPA (34:1)/Total lipids 9.71277E-05 0.00011092 0.00015090.00022862 0.000202581 0.000250224\nPA (34:2)/Total lipids 0.000113191 0.0001364 0.00020860.00031286 0.000260778 0.000370554\nPA (36:0)/Total lipids 0.000270281 0.00029984 0.00034740.00033261 0.000306638 0.000276732\nPA (36:1)/Total lipids 8.60032E-05 0.00010315 0.00010680.00015546 0.000145517 0.000135464\nPA (36:2)/Total lipids 0.000254567 0.00030669 0.00037040.00041612 0.000295389 0.000510475\nPA (36:3)/Total lipids 0.000268236 0.0002975 0.0003702 0.0004686 0.000391054 0.000519388\nTotal PA/Total lipids 0.001089407 0.00125451 0.00155430.00191428 0.001601957 0.002062837\nTable: PA species detected compared to total lipids.\n31 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nUpdated abstract image of working hypothesis.\n3. A previous study has shown the effect of modulating lipid droplet content by the lipase bmm on α-syn\naggregation (Girard et al. 2021). Could it be that the observed phenotypes are due to lipid droplet\nmodulation by GPAT? If it is the same mechanism, this may not be that novel. If it is a different\nmechanism, they authors need to discuss it.\nOur response: We thank the reviewer for highlighting the study by Girard et al. (2021) and its relevance\nto the potential role of LDs content in α-syn aggregation. We acknowledge the importance of\ndistinguishing our findings from existing literature. Our investigation reveals a distinct mechanism by\nwhich GPAT RNAi influences lipid metabolism in the context of α-syn expression. Our data suggests\nthat the silencing of mino leads to the rerouting of neuronal fatty acids to glia, resulting in the\naccumulation of glial LDs. Contrary to the expectation that mino knockdown would reduce LDs61-65, we\nobserved an increase in glial LDs, which is not observed with neuronal mino overexpression. This\nsuggests that glial LDs accumulation is an indirect consequence of the α-syn-related pathway.\nWe have compared our findings with those of Girard et al. (2021) and noted several key differences.\nFirstly, the LDs accumulation in our study occurs in glia within the optic lobe of the brain, which is\ndifferent from the accumulation in photoreceptor neurons in the cited study. We hypothesize that these\ndifferences may arise from the distinct anatomical locations (optic lobe versus photoreceptor).\nPhotoreceptor neurons do not belong to central nervous system (CNS), whereas optic lobe belongs to\nthe CNS. Interestingly, from public single-cell RNA sequencing datasets of fly head we found that DGAT-\nencoding gene mdy, which catalyze the last step of triglycerides synthesis, is predominantly expressed\nin glia and sensory neurons (largely photoreceptor) of the fly head but are much less or void in CNS\n32 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nneurons (Fig. R2.3a, b, c). This may explain why LDs could accumulate in photoreceptors (and also in\nphotoreceptor-associated retina glia in mitochondria mutants in other studies66), in optic lobe glia (as\nshown in our study), but not in optic lobe neurons. Another DGAT-encoding gene, Dgat2 is gut and fat\nbody-enriched and is much less present in the head dataset compared to mdy (Fig. R2.3a, b, c and\nFlybase).\nFigure R2.3 (a) From fly head snRNA-seq dataset FlyCellAtlas49.\nFigure R2.3 (b) From dissected brain (thus no retina and photoreceptor neuron) scRNA-seq dataset\nGSE22362667.\n33 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nFigure R2.3 (c) From head snRNA-seq dataset GSE21866168.\nSecondly, in Girard et al.’s report (2021), LDs are internalized within neurons and coated with α-syn,\nwhereas our study suggests LDs accumulation in glia due to TCA cycle metabolite changes and neuron-\nglia lipid transfer. The varying strengths of the GAL4 drivers used (a much stronger Rh1-GAL4 versus\nnSyb-GAL4, Fig. R2.3d) may also lead to concentration-dependent variations in toxicity.\nFigure R2.3 (d) Image from Ph.D. thesis “IDENTIFICATION OF α-syn DOMINANT MODIFIERS IN A DROSOPHILA\nMODEL OF NEURODEGENERATION”, NATIONAL UNIVERSITY OF SINGAPORE, 2020.\nFurthermore, our experiments with glial expression of bmm or Lsd-2 demonstrate that modulating LDs\nlevels in glia does not alter α-syn-induced TH+ neuron loss and cell death, suggesting that the toxicity\nof LDs is context-dependent and that the implications of LDs changes on neurotoxicity should be\nanalyzed in a case-by-case basis.\nIn conclusion, our study proposes a mechanism of LDs accumulation that is different from the findings\nby Girard et al. (2021). Our results underscore the complexity of LDs dynamics in the context of α-syn\ntoxicity and contribute a new perspective to the field. We have included a discussion of these points in\nthe revised manuscript to clarify the distinctiveness of our findings.\n34 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\n4. In Figure 3C, RNAi OE in WT background is not shown at 29°C.\nOur response: We appreciate the reviewer’s attention to the absence of the mino RNAi/OE in the WT\nbackground at 29°C. They were initially not included for the purpose of comparisons between 25°C and\n29°C. In response to this comment by the reviewer, we have now added the images back. Additionally,\nto maintain clarity and organization, we relocated the images at 25°C to Supplementary Figure 3D.\nThese adjustments ensure that the Figure panels are more logically structured.\n5. The α-syn aggregation analyses should be expanded. Previous works have shown phosphorylated\nSyn and α-syn proteinase K resistance in Drosophila.\nOur response: We thank the reviewer for highlighting the need to expand the analysis of α-syn\naggregation, including the phosphorylated α-syn and proteinase K resistance, which are critical\nmarkers in α-syn pathology. As recommended, we have conducted analysis of α-syn pS129\nphosphorylation using Western blotting. Our results in Figure 7A indicate no significant change in the\nlevels of pS129/α-syn following GPAT RNAi treatment. Furthermore, as suggested, we have also\nperformed proteinase K resistance assay with a titrated series of proteinase K concentrations. Our\nresults in Supplementary Figure 7B show that even at a concentration of Proteinase K as low as 0.005\nμg/ml, which is 100-fold lower than the minimum concentration used by Girard et al. (2021), there is no\ndetectable proteinase K-resistant α-syn in the fly brains of our pan-neuronal α-syn model. This suggests\nthat the proteinase K-resistant α-syn is minimal or undetectable in our fly model.\n6. The analyses on cell death are incomplete. The lack of caspase activation should also be tested with\nthe sensitive cleaved Dcp-1 antibody. In addition, the overexpression of p35 should confirm that effector\ncaspases are not involved in the execution of cell death.\nOur response: We appreciate the reviewer’s concern pertaining to the lack of completeness in our cell\ndeath analyses. As recommended, we have undertaken a more comprehensive examination of\napoptosis in our α-syn fly model. We employed cleaved Dcp-1 antibody for immunostaining and\nWestern blot analyses, as well as the Apoliner (CD8a-RFP-DIAP1-nGFP) reporter and the CD8::hPARP1-\nVenus reporter to assess apoptosis. We have included positive control experiments using hs-hid larvae\nbrains. Despite the use of these multiple apoptosis indicators, we did not detect apoptotic signals in α-\nsyn-expressing fly brains. Studies have shown that elevated α-syn expression increases lipid\nperoxidation and that ferroptosis modulators affect α-syn-induced toxicity2,69. In light of these findings,\nwe have revised the manuscript to reflect a more nuanced interpretation of our data. We state that\n“Despite the possibility that various reporters might be detectable only during specific stages of\napoptosis, the absence of the predominantly apoptotic signals in α-syn flies suggests that apoptosis\nmay not be primarily occurring in α-syn-expressing fly brains or otherwise occurs in a transient manner\nthat is difficult to capture by the various assays we have performed”\nRegarding the overexpression of p35 to assess its impact on cell death pathways, we acknowledge the\nreviewer’s suggestion as a valuable addition to our study. At this time, we have not initiated the p35\noverexpression experiments. However, we are in the process of ordering the related fly stocks and plan\nto include them in our future study.\n35 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\n7. They did not show that the FSG67 drug targets GPAT activity in flies.\nOur response: We appreciate the reviewer’s emphasis on confirming FSG67’s targeting of GPAT in\nDrosophila. Although we have not yet directly measured GPAT activity in flies, FSG67 was rationally\ndesigned and optimized extensively based on the GPAT structural motif, and its efficacy in reducing α-\nsynuclein pathology aligns with GPAT inhibition as the likely mechanism. Moreover, the specificity of\nFSG67 towards GPAT1 and GPAT2 isoforms of liver mitochondrial GPAT has been tested in previous\nstudies57,70.\n36 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nREVIEWER #3\nThe manuscript by Ren et al is focused on the unravelling the effect of Glycerol 3-phosphate\nacyltransferase (mino) on α-syn toxicity. The authors shown that silencing lead to the abrogation of the\npathology in locomotor activity induced by α-syn in Drosophila. The manuscript is potentially novel and\ninteresting. However, some of the key conclusions of the authors are not supported by the data.\nOur response: We thank the reviewer for considering our report as “potentially novel and interesting\nand for the recommendations below to improve our study.\nCritics\n1. One of the major pathology in cell which is indicated is increased lipid peroxidation in RNAi in\ncombination with α-syn. However, BODIPY C11 is ratiometric indicator which is constantly oxidised in\ncell membranes due to basal oxidation. Considering this, the measurements of LP with this indicator\ncan be taken only as the rate of oxidation (rate of BODIPY C11 ration increase in time) but not as a single\nimages and measurements of intensity (ratio).\nOur response: We appreciate the reviewer’s insightful comments regarding the use of BODIPY C11 as\na ratiometric indicator for measuring lipid peroxidation. We acknowledge the concern about the basal\noxidation of BODIPY C11 in membranes and the importance of distinguishing between the rate of\noxidation and static measurements.\nBODIPY C11 is a widely recognized ratiometric probe for assessing lipid peroxidation in various\nbiological samples, including cultured cells, live and frozen tissues, as well as plant systems69,71-79. It is,\nto the best of our knowledge, the sole method available for direct imaging of lipid peroxidation. As\ndemonstrated by Wang et al., the conversion of UV-induced lipid peroxidation to BODIPY C11 occurs\nrapidly, within seconds79. The gradual accumulation of BODIPY C11 peroxidation, as the reviewer noted,\nwas observed as an extremely slow process over an extended period of 140 hours in healthy cells, with\nthe aim to investigate the BODIPY C11’s potential cellular toxicity72. The BODIPY C11 signal intensifies\nonly when ROS generators like AAPH are introduced to healthy cells with BODIPY C11, leading to ROS\ngeneration and a considerable increase in lipid peroxidation within 45 minutes72. This confirms that\nBODIPY C11 is promptly oxidized by lipid peroxidation and provides a real-time indication of lipid\nperoxidation levels, and that the cellular toxicity of BODIPY C11 during the brief 0.5-hour exposure is\nconsidered minimal when contrasted with the BODIPY C11 toxicity process observed over an extended\n140-hour period. The widespread adoption of BODIPY C11 in lipid peroxidation research suggests that\nbasal oxidation is not a significant concern for the research community.\nConsistent with Wang et al.'s findings79,80, the 0.5-hour incubation period is intended to ensure BODIPY\nC11 penetration into the tissue. Therefore, our staining and imaging protocol is not intended to measure\nthe rate of oxidation over 0.5 hours but rather to capture the existing differences in lipid peroxidation\nlevels between genotypes in the brain prior to BODIPY C11 application. We believe that our\nmethodology is appropriate for the intended comparison of lipid peroxidation across different\nexperimental conditions.\n37 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nUtilizing the PALP protocol described by Wang et. al.79, we have validated that BODIPY C11-labeled fly\nbrain tissue can undergo additional oxidation when exposed to a potent 405 nm laser pulse, resulting\nin a rapid increase in BODIPY C11 fluorescence within seconds. This observation suggests that the\noxidation capacity of BODIPY C11 is far from being exhausted. Furthermore, considering our\nobservations that a 488 nm laser can independently trigger lipid peroxidation in just one second at a\npower output of 1%, we maintained the 488 nm laser at a conservative intensity of 0.04% to avoid the\nlaser-induced artifact.\nWe hope the above explanation is acceptable and seek the reviewer’s understanding of our\nexperimental intent.\n2. Results on the measurements of the products of lipid peroxidation - 4-HNE and MDA are presented.\nHowever there are no information in the Method section or in the Figure legends how these\nmeasurements were done.\nOur response: Thank you for bringing this to our attention. We apologize for the lack of details regarding\nthe quantification of 4-HNE and MDA in the initial submission. To address this, we have now included a\ndescription of the measurement process in the Methods section. Specifically, the quantification of 4-\nHNE and MDA signals is performed by applying a threshold to the images using ImageJ/Fiji, followed by\nmeasuring the sum of intensities above the threshold within the defined area.\n3. Glycerol 3-phosphate acyltransferase (GPAT) is the mitochondrial isoform of the lipid synthesis\nenzyme. Can be all observed changes be induced by the different level of lipids in mitochondria?\nThe changes in lipid composition should be measured.\nOur response: We thank the reviewer for highlighting the importance of distinguishing between\nmitochondrial and other subcellular lipid changes in the context of GPAT. To address this point, we\nadded the subcellular localization predictions of different Drosophila GPAT members in Figure 6A.\nAlthough mino is predicted to localize to mitochondria and that Gpat4 and CG15450 are predicted to\nreside in the ER, findings by Vagin et al. (2018) suggesting that mino also exhibit ER localization81. Due\nto resources and materials limitations, we were unable to analyze the suggested mitochondria-specific\nlipidomic changes. However, we have conducted the whole-brain lipidomic analysis to determine the\neffect of mino RNAi and overexpression on lipids. Phospholipids constitute the largest proportion\n(40.05%) of total fly brain lipids. The percentage of phospholipids increased with α-syn expression\n(log2(FC) = 0.15), an effect that was mitigated by mino RNAi (log2(FC) = 0.07) and enhanced by mino\noverexpression (log2(FC) = 0.17) (Supplementary Fig. 6A). Among phospholipids, PC and PE, the two\nmost abundant species comprising over 95% of total phospholipids, exhibited similar trends in\nresponse to α-syn expression and mino RNAi (Supplementary Fig. 6B). A common change of PC and\nPE in α-syn-expressing brains was the increased presence of monounsaturated fatty acids (MUFAs) and\nthe decreased presence of polyunsaturated fatty acids (PUFAs) (Supplementary Fig. 6C and 6D). In\nagreement with this, α-syn-expressing fly brains show increased transcripts of Pcyt1 and Pect, which\nencode enzymes catalyzing the rate-limiting steps of PC and PE synthesis, and increased Desat2, which\nencodes stearoyl-CoA 9-desaturase for MUFA generation, and also a homologue of human α-syn\ntoxicity modifier SCD59,60 (Supplementary Fig. 6E). Additionally, 3 lipid species—Cer-NS (d16:1/24:0),\n38 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nTG (50:4)-FA18:3, and TG (54:2)-FA18:2—were detected only in α-syn-expressing fly brains\n(Supplementary Fig. 6F). We also found that mino RNAi and overexpression affect the strength of brain\nmembrane lipid staining, which reflects the predominant phospholipids levels. This suggests that\nalteration of the broader membrane lipids is more likely regulated by GPAT. In the revised manuscript,\nwe have added this part into a new section “TCA cycle metabolites α-ketoglutarate, isocitrate, and\ncitrate are increased in α-syn fly brains and contribute to glial LDs and neuronal phospholipid\nsynthesis”.\n4. The effect of the lipid composition on α-syn is not novel and published previously. Additionally, if the\nauthors indicate it as a mechanism of the pathology - why it is observed in the Drosophila, there α-syn\nis in predominantly monomeric state?\nOur response: We acknowledge the reviewer’s point regarding the previous work on the effect of lipid\ncomposition on α-syn. It is true that the interaction between α-syn and lipids has been reported in the\nliterature. We wish to clarify that we do not claim novelty in this regard.\nα-syn, known for its inherent structural flexibility and lack of a defined conformation, is prone to forming\npathological aggregates known as Lewy bodies, which are a hallmark of synucleinopathies—a class of\nneurological disorders associated with α-syn. Although the contribution of α-syn to disease progression\nis well-established, the exact details of its assembly within normal cellular contexts remain\nincompletely understood. The question of whether α-syn primarily exists as monomers or as a\nspectrum of oligomeric conformations and the toxicity of various α-syn oligomeric species remains a\nsubject of ongoing debate, with both hypotheses supported by robust scientific findings82. Research\nindicates that the ratio of α-syn to lipids influences the configuration and exposure of the hydrophobic\nNAC domain in the solvent, which affect the intermolecular hydrophobic interactions and is thought to\ncontribute to the initiation of aggregation83,84. Cardiolipin, a mitochondria-specific lipid, is particularly\nhighlighted in this context due to its high curvature, which predisposes it to revealing the NAC domain\nat the membrane surface even at lower α-syn-lipid ratios85-87. Consequently, the monomeric form of α-\nsyn is seen as a key factor reflecting the α-syn-lipid interactions and oligomerization.\nNotwithstanding, we believe that the main findings of our report in this study regarding the ability of\nGPAT to modulate α-syn toxicity, and our new finding on the buildup of citrate in α-syn flies that\npromotes phospholipid synthesis and thereby contributes to α-syn-mediated neurotoxicity, are\nimportant insights that shed more light on the disease mechanism associated with α-syn. Indeed, we\nhave the reviewer to thank for the excellent suggestion for us to examine the changes in lipid\ncomposition, which allowed us to make the interesting finding on citrate buildup.\n5. In Figure 6, fibrillar α-syn is known not to be redox active and it is not clear how modification of could\nchange lipid peroxidation in primary neurons.\nOur response: We appreciate the reviewer’s insightful comments. We agree that fibrillar α-syn is not\nredox active in isolation. However, the presence of α-syn within the cellular environment can indirectly\nmediate mitochondrial dysfunction and lead to a redox imbalance88. The impact of α-syn on cellular\nhomeostasis is not a result of its direct redox properties but is rather due to its complex interactions\n39 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nwith cellular components. In addition, our study elucidates the metabolic effects of neuronal α-syn,\nultimately resulting in the accumulation of lipid droplets (LDs) in glial cells. This complex interplay\nunderscores the multifaceted role of α-syn in cellular pathology. We have discussed this in our revised\nmanuscript.\n40 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nREVIEWER #4\nReviewer #4 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of\nthe Nature Communications initiative to facilitate training in peer review and to provide appropriate\nrecognition for Early Career Researchers who co-review manuscripts.\nOur response: Thank you.\n41 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nReference\nactin cytoskeleton. Neuron 97, 108-124 (2018).\nthe Presence of Iron: Implications for Parkinson’s Disease. Antioxidants 12 (2023).\nReports 41, 111852 (2022).\nexome sequencing. Genome Biol 18, 22 (2017).\nprogram in vivo. Glia 67, 1933-1957 (2019).\nParkinson's disease 6, 40 (2020).\n16, 33 (2021).\n(2002).\nGeldanamycin in Drosophila. J Biol Chem 280, 2873-2878 (2005).\nneurodegenerative phenotypes in a Drosophila model of Parkinson's disease. Disease models & mechanisms 4, 701-\n707 (2011).\ndisease. Genes, Brain and Behavior 13, 812-820 (2014).\nOne 9, e97758 (2014).\nScience 313, 324-328 (2006).\nParkinson's disease-like non-motor symptoms in Drosophila. 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Frontiers in Neuroscience 14 (2020).\n45 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nResearch 56, 2898-2906 (2023).\nrisk in Parkinson's disease. bioRxiv (2023).\n46 | Page\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nNew Reviewer\nThe authors have used mutant alleles, f04927 for mino (reducing 50% expression) and f06898 for\nGpat4 (reducing 34% expression), to replicate the RNAi suppression results on PAM TH+ neurons\n(R2.1d) and daily activity (R2.1e). Suppression by homozygous f04927 are not obvious. I suggest that\nusing loss-of-function alleles to replicate the RNAi results is a common practice in the fly field. The\nconsistent results should be included in the text, which could be included in a supplemental data. The\nresults from homozygous mutants should be also included. The reduction of Gpat4 in the f06898\nallele by qPCR should be shown as in Fig. R2.1b.\nOur response: We thank the reviewer for the helpful suggestions. As recommended, we have now\nincluded the data of the mutant alleles (including qPCR, PAM TH+ neurons and daily activity) into the\nsupplementary figure 1H-J, 1L-Q. We have also expanded the text that describes this result (see below)\nat the end of the Result section: Drosophila screen identifies mino RNAi as a suppressor of α-syn\nneurotoxicity.\n“From mino insertion mutants, we identified minof04927, which shows a reduction of mino transcripts\nlevel to 16% and 50% of control flies in homozygote and heterozygote adult, respectively\n(Supplementary Fig. 2G, 2H and 2J). minof04927 flies exhibit increased transcription of transposons\nflamenco-2, 1731 and 42AB (Supplementary Fig. 2H), in agreement with its role in regulating primary\ntransposon silencing in germline50, as well as reduced PAM TH+ neurons compared to control flies\n(Supplementary Fig. 2I and 2L), suggesting an adverse effect of systematic mino insufficiency. We\nintegrated minof04927 into α-syn model and found that α-syn flies with homozygous minof04927 did not\nshow significant differences of PAM TH+ neurons compared to α-syn flies (Supplementary Fig. 2I\nand2L). However, minof04927/+ mitigates the PAM TH+ neuronal loss and the decline of daily locomotor\nactivities in α-syn flies (Supplementary Fig. 2N and 2O), suggesting that a limited systematic\ninsufficiency of mino may be protective against α-syn toxicity.”\nReviewer #2\nThe authors addressed all my comments.\nOur response: Thank you.\nReviewer #3\nThis was an in-depth and extensive response to the reviewers, and overall many clarifications and\nchanges were made to the manuscript. I believe this has led to significant improvements to the figures\nand attention to all the errors in the previous version.\nSome of the information, for example, the Inclusion of rationale for choice of models, has been\nprovided to the reviewers but remains missing in the manuscript would be helpful (eg: The difference\nin the severity of neurodegeneration between the α-syn (GAL4) and α-syn (QF2) models is attributed to\nthe varying levels of α-syn protein expression. The α-syn (GAL4) model exhibits a less severe\nphenotype, with a notable loss of PAM TH+ neurons evident at day 49 but not at day 32. In contrast, the\nα-syn (QF2) model demonstrates a more aggressive form of toxicity, with neuronal loss apparent as\n1 | Pa ge\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nearly as day 32, thus makes the α-syn (QF2) model more severe. Importantly, although varying α-syn\nexpression levels lead to differences in the timing of neuronal loss, mino RNAi rescues TH+ neuron\nloss in both models. We hope this clarifies the question raised by the reviewer.)\nOur response: We thank the reviewer for the helpful suggestions. As recommended, we have now\nincluded the rationale for our choice of models and described the differences in the severity of\nneurodegeneration between the α-syn (GAL4) and α-syn (QF2) models as below in the result section.\n“mino RNAi alleviates the climbing phenotype in α-syn flies for up to 8 weeks post-eclosion (Fig. 1B,\nSupplementary Fig. 1A and 1B). This was also observed in another pan-neuronal α-syn (QF2) fly model,\nwhich expresses higher levels of α-syn by nSyb-QF2>SNCA and shows accelerated decline of\nclimbing abilities (Fig. 1C and 1D).”\n“α-syn (GAL4) model exhibits a less severe phenotype with a loss of PAM TH+ neurons evident at day\n49 but not at day 32, compared to control flies (nSyb>EGFP RNAi) (Fig. 1E and 1F). In contrast, the\nα-syn (QF2) model shows an early toxicity with neuronal loss at day 32 compared to control flies\n(nSyb-QF2, nSyb>EGFP RNAi) (Supplementary Fig. 1D). When housed at a higher temperature of 29°C,\nthe reduction of PAM TH+ neurons in α-syn (QF2) flies occurs earlier at day 21 (Fig. 1G and 1H).\nAlthough varying α-syn expression levels or temperatures are associated with differences in the timing\nof neuronal loss, mino RNAi mitigates PAM TH+ neuronal loss in both models (Fig. 1G and 1H). In\ncontrast, mino overexpression exacerbates the loss of PAM TH+ neurons in α-syn (QF2) flies (Fig. 1G\nand 1H).”\nIn addition, we also included the data of the mutant alleles including qPCR, PAM TH+ neurons and\ndaily activity into the supplementary figure 1H-J, 1L-Q, as well as a description of the expression\nprofiles of mdy and Lsd-2.\n“The presence of LDs in fly photoreceptor neuron expressing α-syn has been reported60. Fly head or\nbrain RNA-sequencing datasets61-63 shows that in addition to Lsd-2, mdy, the fly brain-expressing\nhomologue of DGAT catalyzing the last step of triglycerides synthesis, are expressed in glia and head\nsensory neurons but little in CNS neurons (Supplementary Fig. 4E-I). These data align with the\nlocalization of LDs in glia of fly brains and in α-syn-expressing photoreceptor neurons in retina60.”\nOccasional over interpretation of the result - for example, on using the TUNEL assay, the assumption\nhas been death by lipid peroxidation (line 776). I liked the new section on LD phenotype in glia - the\nauthors then try increasing or lowering expression of LDs, and not showing cell death is given as proof\nthey are not toxic - although this is an oversimplication of the result and conclusion cannot be made\nthat this is true - maybe a certain type of LD and may alter a-syn aggregation in specific way etc etc ,\nand so this conclusion should be toned down.\nOur response: We thank the reviewer for the thoughtful comment. We agree with the reviewer and\nhave re-worded our statements throughout the manuscript to tone down our above claims. Further, in\nthe Result section, we also stressed the limitation of our methods in determining the cell death from\napoptosis or lipid peroxidation, and of the link between cell death and LDs.\n2 | Pa ge\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nFor a complete track of all the modifications, we have provided a marked word file of our manuscript\nthat compares the last revision with the current version. We have listed some examples below of our\nrevised text mostly related to the reviewer’s concern.\n“We did not observe positive staining of cleaved caspase-3 or cleaved Dcp-1 in α-syn fly brains (Fig.\n3E, Supplementary Fig. 3E and 3H), whereas the hs-hid (heat shock promoter - head involution\ndefective) third instar larva brain shows positive staining after heat shock (Supplementary Fig. 3F and\n3G). Similarly, we observed the cleavage of apoptosis reporters Apoliner55 and hPARP1-Venus56 in\nhs-hid larva brains upon heat shock but not in α-syn fly brains (Supplementary Fig. 3I-L). The cleavage\nof hPARP1-Venus occurs only in one brain among 50 brains without α-syn examined (Supplementary\nFig. 3M). Given the limitation of these approaches, we cannot completely exclude the possibility of\napoptosis in α-syn fly brains.\n“LDs have been associated with antioxidant role that retards α-syn neuronal toxicity59,64. … Taken\ntogether, our results indicate that fly brains with pan-neuronal α-syn accumulate LDs predominantly\nin glia. Due to differences in the localization between glial LDs and neuronal α-syn, we were unable to\naddress the possibility that LDs with specific compositions, or in different cellular contexts, could\npotentially modify α-syn aggregation or toxicity in ways not captured by our assays.\nIn the revision, the authors make some new discoveries: - 'simultaneous upregulation of glycolysis\nand blockage of a step in the TCA cycle catalyzed by OGDH in α-syn fly model contributes to citrate\naccumulation and massive LDs formation in the optic lobe where LDs were seldom observed. Through\nknockdown or overexpression of neuronal mino, we showed that the destination of the neuronal fatty\nacids could be diverted between glial LDs or neuronal membrane lipids.' I think this is still a\nhypothesis albeit a very interesting one - discussion needs to raise the interesting hypothesis and\nexplain how it would be addressed\nOur response: We thank the reviewer for the suggestions. We have rephrased this part in our Result\nsection as follows:\n“Next, we ask if knockdown or overexpression of neuronal mino affect lipid staining in fly brains.\nAlthough the massive LDs were not observed from the BODIPY 493/503-stained background signal in\nfly brains without α-syn, neuronal mino overexpression was associated with an increase of the\nbackground signal in the optic lobe cortex, whereas neuronal mino RNAi was associated with a\nreduction of the background signal (Fig. 5C and 5D). On the other hand, in fly brains with α-syn and\nBODIPY 493/503-stained LDs, neuronal mino knockdown caused an increase of LDs levels, whereas\nneuronal mino overexpression did not affect LDs levels (Fig. 5E and 5F). These mino-associated\nchanges of lipid staining suggest a possibility that neuronal mino may affect the membrane lipid level\nin normal fly brains and LDs levels in α-syn fly brains, likely involves the neuron-glia transport and\ndeposition of fatty acids into lipids which deserves further investigation.”\nIn the discussion part, we add the following sentences:\n“In cultured PD cells, which were bathed in a high volume of culture medium for efficient metabolite\nexchange, OGDH suppression specifically decreased TCA cycle metabolites downstream of OGDH,\n3 | Pa ge\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nwhereas citrate levels remained unchanged67. In contrast, the metabolite changes observed in native\nfly brains, where neurons are intricately wrapped by glia and exchange is more complex, characterize\na PD-like environment in a more physiologically relevant context.”\n“Our results also point to a hypothesis that neuronal mino may influence the fate of fatty acids by\nmodulating their contribution between glial LD storage and membrane lipid synthesis. This\nhypothesis aligns with our findings that neuronal mino knockdown enhances glial LD accumulation in\nα-syn fly brains, whereas mino overexpression alters background lipid staining levels in fly brains\nwithout α-syn, possibly reflecting changes in brain membrane lipids. Future in vitro studies on the\neffect of GPAT on neuronal membrane lipid changes and flux of fatty acids from neurons to culture\nmedium, and studies tracing the flux of fatty acids to glia in neuron-glia co-culture, will be helpful to\ntest this hypothesis.\nStats section: there is still no description of n or N - this is now done in the figure legends but it\nremains confusing - data points are single biological replicates and then N= , without it being clear\nwhat N is - as shown below:\nFigure 1: In c, f, and g, each data point indicates one biological replicate. N = 3 for c. N = 50, 48, 57, 40,\n20, 17, 50, 29 for f. N = 71, 39, 35, 50, 64, 55 for g. Figure 3: Each data point indicates one biological\nreplicate. Each data point in b indicated the lipid peroxidation level of one fly, averaged from 4 images.\nN = 35, 30, 33, 31,30,32 forb.N=29,28,25,28,23,31,35,21,26,22,22,28ford.N=1for.\nOur response: We thank the reviewer for pointing out our mistake here, which we apologize. In this\nrevision, we have changed all the uppercase “N” to “n” and described the definition of “n” in each\nfigure legend. For all the fly experiments, the “n” refers to the biological replicates, either for single vial\nfor climbing analysis, or for singly fly for the immunostaining and locomotor analysis, or for a unique\npool of flies for western blot or metabolites analysis.\nFor example:\nFigure 1:\nIn b and d, each data point indicates the mean climbing height of 1 vial containing 20 to 30 flies,\nmeasured repeatedly across timepoints. In c, each data point and each lane indicates one pool of\ndissected fly brains. In f and h, each data point indicates one fly. Number of vials (n) per group is 13,\n14, 12, 14, 14, 14, 14, 14 for 8 time points in b, respectively, and 12, 20, 16, 19 for 4 time points in d,\nrespectively. Number of pools of dissected fly brains (n) per group 3 for c; Number of flies (n) per\ngroup is 50, 48, 57, 40, 20, 17, 50, 29 for e, f; 71, 39, 35, 50, 64, 55 for g, h.\nFigure 3:\nEach data point in b indicated the lipid peroxidation level of one fly, averaged from 4 images. Each\ndata point in d indicates one fly. Each data point in e indicates one pool of flies. Number of flies (n)\nper group is 35, 30, 33, 31, 30, 32 for b; 29, 28, 25, 28, 23, 31, 35, 21, 26, 22, 22, 28 for d. Number of\npools (n) per group is 1 for e except 3 for ATPCL quantification.\nData availability statement is insufficient , and states that 'all the data is in the manuscript' - except all\nthe imaging datasets and lipidomic datasets are not in the manuscript files, and I did not find a link to\n4 | Pa ge\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nwhere the data would be in this section - so this needs to be detailed and clear - where is it uploaded\nto?\nOur response: Thank you for highlighting this. We noted that in the last revision, we only showed the\npanel of TH+ immunostaining images for Figure 1F. As recommended, in this update, we added all the\nmissing panels of TH+, TUNEL staining, the missing panel of MitoTimer for flies fed with FSG67 at 25oC,\nand TH+ staining for PPL1, PPM1/2 and PPM3 TH+ clusters. We have now inserted all these image\npanels beside the related plot. We also provided the raw excel files for lipidomic and TCA metabolites\nin our Supplementary Data. Further, the Supplementary Data now contains the Matlab code with test\nimages and Labkit classifier file, as well as all the Graphpad Prism pzfx files used to generate the plots\nwith the p-value in the statistics information tabs. Finally, we labeled the exact p-values for all the*, **\nand *** for all the plots.\nBelow is our updated statement:\nData Availability\nThe genetic screening data (Supplementary Data 1), raw short-chain fatty acids excel data\n(Supplementary Data 2), raw lipidomics excel data (Supplementary Data 3), the Matlab code, Labkit\nclassifier file and test images (Supplementary Data 4), the spectral data of lipidomic and short-chain\nfatty acids (Supplementary Data 6) generated in this study are provided as Supplementary Data. The\nnumeric data that were used for plotting the graphs in the figures and supplementary figures, and the\nraw western blot images are provided in Source Data. The Graphpad Prism pzfx files used to generate\nthe plots also with the statistics comparison information tabs are provided in Supplementary Data 5.\nThe sources of RNA sequencing datasets for the gene expression profiles in Supplementary figure 4e-i\nare cited and public available. Source data are provided with this paper as a Source Data file.\nCode Availability\nThe Labkit classifier file for PAM cluster neuron prediction and the code for the correction of\nLabkit-predicted TH+ regions could be downloaded from Github\n(https://github.com/rmd13/FlyBrain_PAM_TH_DAPI_Labkit). We also provided the code, Labkit\nclassifier file and test images generated in this study in Supplementary Data 4. The code is under MIT\nlicense.\nReviewer #3 (Remarks on code availability):\nI did not assess any code\n5 | Pa ge\nResponse to Reviewer’s comments (NCOMMS-24-19397)"}, {"round": 2, "reviewer_comments": {"reviewer_2": "The authors addressed all my comments.", "reviewer_3": "This was an in-depth and extensive response to the reviewers, and overall many clarifications and changes were made to the manuscript. I believe this has led to significant improvements to the figures and attention to all the errors in the previous version. Some of the information, for example, the Inclusion of rationale for choice of models, has been provided to the reviewers but remains missing in the manuscript would be helpful (eg: The difference in the severity of neurodegeneration between the α- syn (GAL4) and α-syn (QF2) models is attributed to the varying levels of α-syn protein expression. The α-syn (GAL4) model exhibits a less severe phenotype, with a notable loss of PAM TH+ neurons evident at day 49 but not at day 32. In contrast, the α-syn (QF2) model demonstrates a more aggressive form of toxicity, with neuronal loss apparent as early as day 32, thus makes the α-syn (QF2) model more severe. Importantly, although varying α-syn expression levels lead to differences in the timing of neuronal loss, mino RNAi rescues TH+ neuron loss in both models. We hope this clarifies the question raised by the reviewer.) Occasional over interpretation of the result - for example, on using the TUNEL assay, the assumption has been death by lipid peroxidation (line 776) I liked the new section on LD phenotype in glia - the authors then try increasing or lowering expression of LDs, and not showing cell death is given as proof they are not toxic - although this is is an oversimplication of the result and conclusion cannot be made that this is true - maybe a certain type of LD and may alter a-syn aggregation in specific way etc etc , and so this conclusion should be toned down. In the revision, the authors make some new discoveries: - 'simultaneous upregulation of glycolysis and blockage of a step in the TCA cycle catalyzed by OGDH in α-syn fly model contributes to citrate accumulation and massive LDs formation in the optic lobe where LDs were seldom observed. Through knockdown or overexpression of neuronal mino, we showed that the destination of the neuronal fatty acids could be diverted between glial LDs or neuronal membrane lipids.' I think this is still a hypothesis albeit a very interesting one - discussion needs to raise the interesting hypothesis and explain how it would be addressed Stats section: there is still no description of n or N - this is now done in the figure legends but it remains confusing - data points are single biological replicates and then N= , without it being clear what N is - as shown below: Figure 1 In c, f, and g, each data point indicates one biological replicate. N = 3 for c. N = 50, 48, 57, 40, 20, 17, 50, 29 for f. N = 71, 39, 35, 50, 64, 55 for g. Figure 2: Each data point indicates one biological replicate. Each data point in b indicated the lipid peroxidation level of one fly, averaged from 4 images. N = 35, 30, 33, 31,30,32 forb.N=29,28,25,28,23,31,35,21,26,22,22,28ford.N=1fore. Data availability statement is insufficient , and states that 'all the data is in the manuscript' - except all the imaging datasets and lipidomic datasets are not in the manuscript files, and I did not find a link to where the data would be in this section - so this needs to be detailed and clear - where is it uploaded to?"}, "author_response": "New Reviewer\nThe authors have used mutant alleles, f04927 for mino (reducing 50% expression) and f06898 for\nGpat4 (reducing 34% expression), to replicate the RNAi suppression results on PAM TH+ neurons\n(R2.1d) and daily activity (R2.1e). Suppression by homozygous f04927 are not obvious. I suggest that\nusing loss-of-function alleles to replicate the RNAi results is a common practice in the fly field. The\nconsistent results should be included in the text, which could be included in a supplemental data. The\nresults from homozygous mutants should be also included. The reduction of Gpat4 in the f06898\nallele by qPCR should be shown as in Fig. R2.1b.\nOur response: We thank the reviewer for the helpful suggestions. As recommended, we have now\nincluded the data of the mutant alleles (including qPCR, PAM TH+ neurons and daily activity) into the\nsupplementary figure 1H-J, 1L-Q. We have also expanded the text that describes this result (see below)\nat the end of the Result section: Drosophila screen identifies mino RNAi as a suppressor of α-syn\nneurotoxicity.\n“From mino insertion mutants, we identified minof04927, which shows a reduction of mino transcripts\nlevel to 16% and 50% of control flies in homozygote and heterozygote adult, respectively\n(Supplementary Fig. 2G, 2H and 2J). minof04927 flies exhibit increased transcription of transposons\nflamenco-2, 1731 and 42AB (Supplementary Fig. 2H), in agreement with its role in regulating primary\ntransposon silencing in germline50, as well as reduced PAM TH+ neurons compared to control flies\n(Supplementary Fig. 2I and 2L), suggesting an adverse effect of systematic mino insufficiency. We\nintegrated minof04927 into α-syn model and found that α-syn flies with homozygous minof04927 did not\nshow significant differences of PAM TH+ neurons compared to α-syn flies (Supplementary Fig. 2I\nand2L). However, minof04927/+ mitigates the PAM TH+ neuronal loss and the decline of daily locomotor\nactivities in α-syn flies (Supplementary Fig. 2N and 2O), suggesting that a limited systematic\ninsufficiency of mino may be protective against α-syn toxicity.”\nReviewer #2\nThe authors addressed all my comments.\nOur response: Thank you.\nReviewer #3\nThis was an in-depth and extensive response to the reviewers, and overall many clarifications and\nchanges were made to the manuscript. I believe this has led to significant improvements to the figures\nand attention to all the errors in the previous version.\nSome of the information, for example, the Inclusion of rationale for choice of models, has been\nprovided to the reviewers but remains missing in the manuscript would be helpful (eg: The difference\nin the severity of neurodegeneration between the α-syn (GAL4) and α-syn (QF2) models is attributed to\nthe varying levels of α-syn protein expression. The α-syn (GAL4) model exhibits a less severe\nphenotype, with a notable loss of PAM TH+ neurons evident at day 49 but not at day 32. In contrast, the\nα-syn (QF2) model demonstrates a more aggressive form of toxicity, with neuronal loss apparent as\n1 | Pa ge\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nearly as day 32, thus makes the α-syn (QF2) model more severe. Importantly, although varying α-syn\nexpression levels lead to differences in the timing of neuronal loss, mino RNAi rescues TH+ neuron\nloss in both models. We hope this clarifies the question raised by the reviewer.)\nOur response: We thank the reviewer for the helpful suggestions. As recommended, we have now\nincluded the rationale for our choice of models and described the differences in the severity of\nneurodegeneration between the α-syn (GAL4) and α-syn (QF2) models as below in the result section.\n“mino RNAi alleviates the climbing phenotype in α-syn flies for up to 8 weeks post-eclosion (Fig. 1B,\nSupplementary Fig. 1A and 1B). This was also observed in another pan-neuronal α-syn (QF2) fly model,\nwhich expresses higher levels of α-syn by nSyb-QF2>SNCA and shows accelerated decline of\nclimbing abilities (Fig. 1C and 1D).”\n“α-syn (GAL4) model exhibits a less severe phenotype with a loss of PAM TH+ neurons evident at day\n49 but not at day 32, compared to control flies (nSyb>EGFP RNAi) (Fig. 1E and 1F). In contrast, the\nα-syn (QF2) model shows an early toxicity with neuronal loss at day 32 compared to control flies\n(nSyb-QF2, nSyb>EGFP RNAi) (Supplementary Fig. 1D). When housed at a higher temperature of 29°C,\nthe reduction of PAM TH+ neurons in α-syn (QF2) flies occurs earlier at day 21 (Fig. 1G and 1H).\nAlthough varying α-syn expression levels or temperatures are associated with differences in the timing\nof neuronal loss, mino RNAi mitigates PAM TH+ neuronal loss in both models (Fig. 1G and 1H). In\ncontrast, mino overexpression exacerbates the loss of PAM TH+ neurons in α-syn (QF2) flies (Fig. 1G\nand 1H).”\nIn addition, we also included the data of the mutant alleles including qPCR, PAM TH+ neurons and\ndaily activity into the supplementary figure 1H-J, 1L-Q, as well as a description of the expression\nprofiles of mdy and Lsd-2.\n“The presence of LDs in fly photoreceptor neuron expressing α-syn has been reported60. Fly head or\nbrain RNA-sequencing datasets61-63 shows that in addition to Lsd-2, mdy, the fly brain-expressing\nhomologue of DGAT catalyzing the last step of triglycerides synthesis, are expressed in glia and head\nsensory neurons but little in CNS neurons (Supplementary Fig. 4E-I). These data align with the\nlocalization of LDs in glia of fly brains and in α-syn-expressing photoreceptor neurons in retina60.”\nOccasional over interpretation of the result - for example, on using the TUNEL assay, the assumption\nhas been death by lipid peroxidation (line 776). I liked the new section on LD phenotype in glia - the\nauthors then try increasing or lowering expression of LDs, and not showing cell death is given as proof\nthey are not toxic - although this is an oversimplication of the result and conclusion cannot be made\nthat this is true - maybe a certain type of LD and may alter a-syn aggregation in specific way etc etc ,\nand so this conclusion should be toned down.\nOur response: We thank the reviewer for the thoughtful comment. We agree with the reviewer and\nhave re-worded our statements throughout the manuscript to tone down our above claims. Further, in\nthe Result section, we also stressed the limitation of our methods in determining the cell death from\napoptosis or lipid peroxidation, and of the link between cell death and LDs.\n2 | Pa ge\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nFor a complete track of all the modifications, we have provided a marked word file of our manuscript\nthat compares the last revision with the current version. We have listed some examples below of our\nrevised text mostly related to the reviewer’s concern.\n“We did not observe positive staining of cleaved caspase-3 or cleaved Dcp-1 in α-syn fly brains (Fig.\n3E, Supplementary Fig. 3E and 3H), whereas the hs-hid (heat shock promoter - head involution\ndefective) third instar larva brain shows positive staining after heat shock (Supplementary Fig. 3F and\n3G). Similarly, we observed the cleavage of apoptosis reporters Apoliner55 and hPARP1-Venus56 in\nhs-hid larva brains upon heat shock but not in α-syn fly brains (Supplementary Fig. 3I-L). The cleavage\nof hPARP1-Venus occurs only in one brain among 50 brains without α-syn examined (Supplementary\nFig. 3M). Given the limitation of these approaches, we cannot completely exclude the possibility of\napoptosis in α-syn fly brains.\n“LDs have been associated with antioxidant role that retards α-syn neuronal toxicity59,64. … Taken\ntogether, our results indicate that fly brains with pan-neuronal α-syn accumulate LDs predominantly\nin glia. Due to differences in the localization between glial LDs and neuronal α-syn, we were unable to\naddress the possibility that LDs with specific compositions, or in different cellular contexts, could\npotentially modify α-syn aggregation or toxicity in ways not captured by our assays.\nIn the revision, the authors make some new discoveries: - 'simultaneous upregulation of glycolysis\nand blockage of a step in the TCA cycle catalyzed by OGDH in α-syn fly model contributes to citrate\naccumulation and massive LDs formation in the optic lobe where LDs were seldom observed. Through\nknockdown or overexpression of neuronal mino, we showed that the destination of the neuronal fatty\nacids could be diverted between glial LDs or neuronal membrane lipids.' I think this is still a\nhypothesis albeit a very interesting one - discussion needs to raise the interesting hypothesis and\nexplain how it would be addressed\nOur response: We thank the reviewer for the suggestions. We have rephrased this part in our Result\nsection as follows:\n“Next, we ask if knockdown or overexpression of neuronal mino affect lipid staining in fly brains.\nAlthough the massive LDs were not observed from the BODIPY 493/503-stained background signal in\nfly brains without α-syn, neuronal mino overexpression was associated with an increase of the\nbackground signal in the optic lobe cortex, whereas neuronal mino RNAi was associated with a\nreduction of the background signal (Fig. 5C and 5D). On the other hand, in fly brains with α-syn and\nBODIPY 493/503-stained LDs, neuronal mino knockdown caused an increase of LDs levels, whereas\nneuronal mino overexpression did not affect LDs levels (Fig. 5E and 5F). These mino-associated\nchanges of lipid staining suggest a possibility that neuronal mino may affect the membrane lipid level\nin normal fly brains and LDs levels in α-syn fly brains, likely involves the neuron-glia transport and\ndeposition of fatty acids into lipids which deserves further investigation.”\nIn the discussion part, we add the following sentences:\n“In cultured PD cells, which were bathed in a high volume of culture medium for efficient metabolite\nexchange, OGDH suppression specifically decreased TCA cycle metabolites downstream of OGDH,\n3 | Pa ge\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nwhereas citrate levels remained unchanged67. In contrast, the metabolite changes observed in native\nfly brains, where neurons are intricately wrapped by glia and exchange is more complex, characterize\na PD-like environment in a more physiologically relevant context.”\n“Our results also point to a hypothesis that neuronal mino may influence the fate of fatty acids by\nmodulating their contribution between glial LD storage and membrane lipid synthesis. This\nhypothesis aligns with our findings that neuronal mino knockdown enhances glial LD accumulation in\nα-syn fly brains, whereas mino overexpression alters background lipid staining levels in fly brains\nwithout α-syn, possibly reflecting changes in brain membrane lipids. Future in vitro studies on the\neffect of GPAT on neuronal membrane lipid changes and flux of fatty acids from neurons to culture\nmedium, and studies tracing the flux of fatty acids to glia in neuron-glia co-culture, will be helpful to\ntest this hypothesis.\nStats section: there is still no description of n or N - this is now done in the figure legends but it\nremains confusing - data points are single biological replicates and then N= , without it being clear\nwhat N is - as shown below:\nFigure 1: In c, f, and g, each data point indicates one biological replicate. N = 3 for c. N = 50, 48, 57, 40,\n20, 17, 50, 29 for f. N = 71, 39, 35, 50, 64, 55 for g. Figure 3: Each data point indicates one biological\nreplicate. Each data point in b indicated the lipid peroxidation level of one fly, averaged from 4 images.\nN = 35, 30, 33, 31,30,32 forb.N=29,28,25,28,23,31,35,21,26,22,22,28ford.N=1for.\nOur response: We thank the reviewer for pointing out our mistake here, which we apologize. In this\nrevision, we have changed all the uppercase “N” to “n” and described the definition of “n” in each\nfigure legend. For all the fly experiments, the “n” refers to the biological replicates, either for single vial\nfor climbing analysis, or for singly fly for the immunostaining and locomotor analysis, or for a unique\npool of flies for western blot or metabolites analysis.\nFor example:\nFigure 1:\nIn b and d, each data point indicates the mean climbing height of 1 vial containing 20 to 30 flies,\nmeasured repeatedly across timepoints. In c, each data point and each lane indicates one pool of\ndissected fly brains. In f and h, each data point indicates one fly. Number of vials (n) per group is 13,\n14, 12, 14, 14, 14, 14, 14 for 8 time points in b, respectively, and 12, 20, 16, 19 for 4 time points in d,\nrespectively. Number of pools of dissected fly brains (n) per group 3 for c; Number of flies (n) per\ngroup is 50, 48, 57, 40, 20, 17, 50, 29 for e, f; 71, 39, 35, 50, 64, 55 for g, h.\nFigure 3:\nEach data point in b indicated the lipid peroxidation level of one fly, averaged from 4 images. Each\ndata point in d indicates one fly. Each data point in e indicates one pool of flies. Number of flies (n)\nper group is 35, 30, 33, 31, 30, 32 for b; 29, 28, 25, 28, 23, 31, 35, 21, 26, 22, 22, 28 for d. Number of\npools (n) per group is 1 for e except 3 for ATPCL quantification.\nData availability statement is insufficient , and states that 'all the data is in the manuscript' - except all\nthe imaging datasets and lipidomic datasets are not in the manuscript files, and I did not find a link to\n4 | Pa ge\nResponse to Reviewer’s comments (NCOMMS-24-19397)\nwhere the data would be in this section - so this needs to be detailed and clear - where is it uploaded\nto?\nOur response: Thank you for highlighting this. We noted that in the last revision, we only showed the\npanel of TH+ immunostaining images for Figure 1F. As recommended, in this update, we added all the\nmissing panels of TH+, TUNEL staining, the missing panel of MitoTimer for flies fed with FSG67 at 25oC,\nand TH+ staining for PPL1, PPM1/2 and PPM3 TH+ clusters. We have now inserted all these image\npanels beside the related plot. We also provided the raw excel files for lipidomic and TCA metabolites\nin our Supplementary Data. Further, the Supplementary Data now contains the Matlab code with test\nimages and Labkit classifier file, as well as all the Graphpad Prism pzfx files used to generate the plots\nwith the p-value in the statistics information tabs. Finally, we labeled the exact p-values for all the*, **\nand *** for all the plots.\nBelow is our updated statement:\nData Availability\nThe genetic screening data (Supplementary Data 1), raw short-chain fatty acids excel data\n(Supplementary Data 2), raw lipidomics excel data (Supplementary Data 3), the Matlab code, Labkit\nclassifier file and test images (Supplementary Data 4), the spectral data of lipidomic and short-chain\nfatty acids (Supplementary Data 6) generated in this study are provided as Supplementary Data. The\nnumeric data that were used for plotting the graphs in the figures and supplementary figures, and the\nraw western blot images are provided in Source Data. The Graphpad Prism pzfx files used to generate\nthe plots also with the statistics comparison information tabs are provided in Supplementary Data 5.\nThe sources of RNA sequencing datasets for the gene expression profiles in Supplementary figure 4e-i\nare cited and public available. Source data are provided with this paper as a Source Data file.\nCode Availability\nThe Labkit classifier file for PAM cluster neuron prediction and the code for the correction of\nLabkit-predicted TH+ regions could be downloaded from Github\n(https://github.com/rmd13/FlyBrain_PAM_TH_DAPI_Labkit). We also provided the code, Labkit\nclassifier file and test images generated in this study in Supplementary Data 4. The code is under MIT\nlicense.\nReviewer #3 (Remarks on code availability):\nI did not assess any code\n5 | Pa ge\nResponse to Reviewer’s comments (NCOMMS-24-19397)"}]

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