Abstract
Autophagy is a conserved pathway where cytoplasmic contents are engulfed by autophagosomes, which then fuse with lysosomes enabling their degradation. Mutations in core autophagy genes cause neurological conditions, and autophagy defects are seen in neurodegenerative diseases such as Parkinson’s disease and Huntington’s disease. Thus, we have sought to understand the cellular pathway perturbations that autophagy-perturbed cells are vulnerable to by seeking negative genetic interactions such as synthetic lethality in autophagy-null human cells using available data from yeast screens. These revealed that loss of proteasome and nuclear pore complex components cause synergistic viability changes akin to synthetic fitness loss in autophagy-null cells. This can be attributed to the cytoplasm-to-nuclear transport of proteins during autophagy deficiency and subsequent degradation of these erstwhile cytoplasmic proteins by nuclear proteasomes. As both autophagy and cytoplasm-to-nuclear transport are defective in Huntington’s disease, such cells are more vulnerable to perturbations of proteostasis due to these synthetic interactions.
Subject terms: Macroautophagy, Diseases
Park et al. show that cells with impaired autophagy shuttle cytoplasmic proteins to the nucleus for degradation by nuclear proteasomes, revealing synergistic vulnerabilities in diseases where autophagy and nucleocytoplasmic transport are compromised.
Main
Autophagy is a pathway conserved from yeast to humans enabling the degradation of cytoplasmic proteins and organelles. After such substrates are captured by autophagosomes, these are trafficked to lysosomes where their contents are degraded. Mutations in different core autophagy genes cause neurological syndromes, and autophagy compromise is a feature of neurodegenerative diseases such as Parkinson’s disease (PD) and Huntington’s disease (HD)1,2. Indeed, induction of autophagosome biogenesis lowers the levels of disease-causing proteins and ameliorates phenotypes in murine and other animal models of HD and related neurodegenerative diseases3,4. Given the importance of autophagy in health and disease, it is crucial to understand the processes that are buffered by normal autophagy and the cellular pathway perturbations that autophagy-perturbed cells are vulnerable to. We started to address this challenge by seeking to identify genetic interactions, when an allele of gene A combines with an allele of gene B resulting in a double-mutant with an unexpected phenotype5–7. This may be an exacerbation of the expected combined phenotype of the single-mutants; for example, two single-mutants have normal growth, but the double-mutant has slow growth, a negative interaction. The most severe negative interaction causing synthetic fitness loss is synthetic lethality, where two non-lethal single alleles combine to cause lethality, representing cellular pathways that buffer each other. This approach is suitable for identifying interactions with loss-of-function alleles of core autophagy genes, as these are well tolerated in mammalian cells8,9.
Results
Identifying genes that protect autophagy-defective cells
As synthetic lethal interactions between yeast genes increase the likelihood of such interactions between their human orthologues 3–19-fold10–12, we analysed human orthologues of yeast genes with at least five negative genetic or synthetic lethal interactions with core autophagy genes, identified using two databases (from genetic interactions available in YeastMine and from their orthologues available in HGCN) (Supplementary Table 1 and Extended Data Fig. 1a). We used this cutoff to maximize the chance that the interactions were via autophagy and not through autophagy-independent functions of autophagy genes. We used CRISPR/Cas9 to knock out each of the 30 human orthologues and compared the survival of these knockouts in ATG16L1 or ATG9 wild-type (WT) (ATG16+ or ATG9+) versus isogenic ATG16L1 knockout (ATG16−) or ATG9 knockout (ATG9−) HeLa cells, which lack key genes required for autophagosome biogenesis (Fig. 1a and Extended Data Fig. 1b)9,13. Note that the ATG16L1-null and ATG9-null cells, which have normal viability, each have their own control lines. Our fluorescence-activated cell sorting (FACS)-based cell number assay with CRISPR/Cas9 knockouts of human orthologues of yeast genes showing synthetic lethality with autophagy gene knockouts identified potential synthetic lethal interactions with both ATG16L1-null and ATG9-null cells. These were selected on the basis of at least one out of two guides tested showing a more rapid decline in cell numbers in both autophagy-null lines versus their matched WT, autophagy-competent control lines: PSMD7 (proteasome 26S subunit, non-ATPase 7), NUP98 (nucleoporin 98 and 96 precursor) and NUP133 (nucleoporin 133) (Fig. 1b,c, Extended Data Fig. 2 and Supplementary Tables 2 and 3). We validated these candidates implicating the proteasome and nuclear pore complex (NPC) as synthetic lethal interactors with autophagy by assessing cell death in ATG16L1-null (ATG16−) versus WT (ATG16+) cells using siRNAs as distinct reagents (Fig. 1d–g and Extended Data Fig. 3a). To follow-up PSMD7, we further confirmed that different proteasome inhibitors (MG132 and bortezomib) enhanced cell death in ATG16L1-null versus WT cells (Extended Data Fig. 3b–f). Similarly, we observed a dramatic increase in cell death when we combined ivermectin14, an importin α/β inhibitor, with SBI-0206965 (SBI), a highly selective autophagy kinase ULK1 inhibitor, versus either compound alone (Extended Data Fig. 3g–k)15. In time-course studies, we also found that autophagy inhibition alone (SBI) was less toxic than autophagy inhibition plus proteasome inhibition by bortezomib and/or nuclear import inhibition by importazole, which is an importin β inhibitor16 (Fig. 1h). Similar trends were seen in time-course studies with distinct proteasome and nuclear import inhibitors (MG132 and ivermectin14, respectively) at different concentrations and combinations (Extended Data Fig. 3l–o). Moreover, consistent with these candidates, other proteasome subunits and nucleoporins were identified in yeast as negative genetic and synthetic lethal interactors with four or fewer distinct autophagy core gene knockouts (Supplementary Table 4). Taken together, these data suggest that nucleoporins and proteasome activity buffer cell survival in autophagy-null cells and that these genetic interactions are conserved from yeast to mammalian cells.
Nuclear relocation of substrates in autophagy compromise
The A53T α-synuclein (A53T α-Syn) mutant, which causes autosomal dominant PD, is cleared by both autophagy and the proteasome17, the two major intracellular clearance pathways. Thus, we have used this protein as a model substrate. We observed that short-term (6 h) proteasome inhibition by MG132 or bortezomib caused an accumulation of A53T α-Syn in the nucleus of autophagy-null versus WT cells (Fig. 2a,b and Extended Data Fig. 4a,b). Fluorescence recovery after photobleaching (FRAP) experiments confirmed that the green fluorescent protein (GFP)-A53T α-Syn (a good autophagy substrate) signal in the nucleus recovered more rapidly in ATG16L1-null versus WT cells and no such effect was seen with GFP alone (a poor autophagy substrate predominantly cleared by proteasome) (Fig. 2c–e shows just the nuclear FRAP recovery and Extended Data Fig. 4c,d shows the nuclear FRAP recovery divided by the fluorescence of an unbleached cytoplasmic region in the same cell exposed to nuclear photobleaching). These data further support the steady-state data suggesting that autophagy compromise leads to nuclear transport of A53T α-Syn (Fig. 2c–e and Extended Data Fig. 4c,d). MG132 treatment of A53T α-Syn-expressing cells also increased nucleus-localized aggregated proteins (aggresomes) detected with Proteostat dye in ATG16L1-null versus WT cells (Fig. 2f and Extended Data Fig. 4e). Furthermore, prolonged proteasome inhibition caused a greater proportion of autophagy-null cells (without A53T α-Syn) to exhibit nuclear accumulation of endogenous aggresomes, compared with proteasome-inhibited WT cells (Fig. 2g and Extended Data Fig. 4f). Thus, we hypothesized that autophagy inhibition, which impacts cytoplasmic protein degradation, causes relocation of substrates to the nucleus for degradation by nuclear proteasomes. Indeed, knockdown of either of the NPC constituents NUP98 (refs. 18,19) or NUP133 (ref. 20), two other hits from our synthetic lethal screen, as well as treatment with ivermectin, an importin α/β inhibitor16, decreased A53T α-Syn nuclear/cytoplasmic ratios specifically in autophagy-null cells by immunoblotting of fractionated cells (Extended Data Fig. 4g–j) and by microscopy (Fig. 2h). Notably, these data are consistent with published work showing that nuclear import of α-Syn is importin α-dependent, and associated with the interaction of importin α with α-Syn21, which we confirmed (Extended Data Fig. 4k). Importin α can directly bind to certain proteins and enable their nuclear import without the requirement of importin β, highlighting the versatility and complexity of nucleocytoplasmic transport mechanisms22–24. This non-canonical form of importin α-dependent, importin β-independent nuclear import is likely driven by the ability of importin α itself to enter the nucleus, independently of importin β22. However, α-Syn did not bind importin β, and this may explain why the importin β inhibitor importazole did not affect A53T α-Syn shuttling (Extended Data Fig. 4l). These data suggest that proteasome inhibition and impairment of NPC function may act via a common pathway to cause synergistic viability changes akin to synthetic fitness loss in autophagy-null cells.
Autophagy inhibition relocates ‘bulk’ proteins into nucleus
Based on our findings, we hypothesized that ‘bulk autophagy substrates’, the general pool of cytoplasmic proteins degraded by autophagy, will move to the nucleus in autophagy-inhibited cells. To assess if the transport of newly synthesized proteins into the nucleus was increased in autophagy-null cells, we used two approaches. First, we assessed the localization of newly synthesized misfolded peptides/proteins by treating cells for 2 h with puromycin, an antibiotic that resembles the 3′ end of aminoacylated tRNA (aa-tRNA), which causes premature translational termination (a cytoplasmic event)25. ATG16L1-null cells had more puromycin-induced misfolded protein inclusions in the nucleus compared with their WT counterparts (Extended Data Fig. 5). Second, we labelled newly synthesized proteins with AHA (l-azidohomoalanine) using ‘click’ chemistry26,27 and showed that autophagy inhibition by SBI-0206965 (SBI) increased the intensity of nuclear-localized AHA-labelled proteins (Fig. 2i and Extended Data Fig. 6a). Note that a 10% change in bulk protein in the nucleus versus the cytoplasm is very meaningful from a biological perspective, as many proteins in the cytoplasm (for example, those associated with membranes and organelles) cannot enter the nucleus. More AHA-labelled proteins were localized in the nucleus upon MG132 treatment in ATG16L1-null cells compared with WT cells (Fig. 2j and Extended Data Fig. 6b–f). Significantly, we show both by immunoblotting of fractionated cells (Fig. 2k and Extended Data Fig. 6g) and by microscopy (Extended Data Fig. 6h) that reinstatement of autophagy by complementation of ATG16L1-null cells with GFP-ATG16L1 rescued the nuclear/cytoplasmic accumulation of AHA-labelled proteins to normal ratios in the absence or presence of MG132. These data indicate that autophagy inhibition causes excessive translocation of numerous newly synthesized and misfolded proteins into the nucleus (Fig. 2l).
Moreover, to confirm that nuclear proteasomes were involved in the degradation of the proteins translocated to this compartment after autophagy inhibition, we knocked down AKIRIN2, a key mediator of proteasome import into the nucleus28 (which we replicated in Fig. 3a,b). Loss of AKIRIN2 increased A53T α-Syn levels in the nucleus more in ATG16L1-null cells than in WT cells (Fig. 3c,d) and resulted in more cell death in the autophagy-null versus WT cells (Fig. 3e,f). These data suggest that autophagy loss causes proteins to shuttle into the nucleus for degradation by nuclear proteasomes (Fig. 3g).
As ATG16L1 functions in the conjugation of LC3 to phosphatidylethanolamine (PE), resulting in lipidated LC3 (LC3-II)9, we assessed whether the non-lipidated form of LC3/ATG8, which would accumulate in autophagy-deficient cells, impacted the cytoplasm-to-nuclear shuttling autophagy substrates in autophagy-null conditions. The non-lipidated LC3 mutant, LC3 G120A, where glycine 120 is replaced with alanine (LC3 G120A)9 did not affect the localization of α-Syn A53T, compared with wild-type (WT) LC3 in HeLa cells (Extended Data Fig. 7a).
Furthermore, the cytoplasm-to-nuclear shuttling of proteins in autophagy-null cells is unlikely to be due to aberrant NPCs, as NPC morphology and RAN (Ras-related nuclear protein) localization in autophagy-depleted cells (ATG16L1 KO) were similar to WT cells (Extended Data Fig. 7b).
We next examined whether autophagy inhibition induces the association of autophagy substrates, like α-Syn A53T, with importins21. α-Syn A53T binding with importin α was not significantly affected in autophagy-deficient cells (ATG16L1 KO) compared with WT (Extended Data Fig. 4k). However, as we compute the strength of binding by dividing the amount of immunoprecipitated material by the amount of immunoprecipitated α-Syn, the system may be oversaturated with α-Syn that accumulates and is immunoprecipitated more abundantly in the autophagy-null cells. To bypass this uncertainty, we acutely inhibited autophagy with the autophagy kinase ULK1/2 inhibitor (SBI) and observed that it caused more α-Syn A53T to interact with importin α (Extended Data Fig. 7c), indicating that some autophagy substrates may have increased binding to importins when autophagy is impaired.
To directly investigate the status of cytoplasm-to-nuclear transport, ATG16L1 WT and knockout cells were transfected with NLS–tdTomato–NES (Lentiviral-S-tdTomato), which is a shuttling reporter containing both an NLS and an NES fused to tdTomato29,30. Autophagy compromise induced either by ATG16L1 depletion or autophagy kinase ULK1/2 inhibition (SBI) resulted in a greater nuclear occupancy of the reporter, suggesting increased cytoplasm-to-nucleus trafficking (Extended Data Fig. 7d,e). Together these data suggest that autophagy compromise causes an ‘overflow’ of bulk cytoplasmic proteins (likely autophagy substrates) into the nucleus (Extended Data Fig. 7f).
Nucleocytoplasmic shuttling defect in Huntington’s disease
HD is an autosomal dominant neurodegenerative disorder which is associated with mild autophagy inhibition and disruption of the NPC and nucleocytoplasmic transport1,31. Consistent with previous data in various systems in cell culture and in vivo3,26,32, induced pluripotent stem (iPS) cell-derived neurons from a juvenile patient with HD originally carrying 125 CAG trinucleotide repeats (HTT125Q) (Extended Data Fig. 8a)33 had lower levels of LC3-II/autophagosomes than controls (Fig. 4a)32. In line with recent studies suggesting that HD is associated with defective nucleus-cytoplasmic transport31, HTT125Q-derived neurons had compromised nuclear membrane integrity, and mislocalization of the NPC and RAN (which enables translocation of proteins and RNA through the NPC) to the cytosol, compared with control (Fig. 4b,c).
As modest autophagy compromise is likely quite well tolerated in humans34, we considered whether cells with the HD mutation would manifest the biochemical alterations that would be predicted from a combined deficiency in autophagy and cytoplasm-to-nuclear transport. Accordingly, we tested whether the normal ability of cells to cope with autophagy compromise by shuttling cytoplasmic substrates to the nucleus for proteasomal degradation was compromised in cells carrying the HD mutation. A lower abundance of newly synthesized bulk proteins was present in the nucleus, in HTT125Q iPS cell-derived neurons compared with controls (Fig. 4d), in mouse striatal cells with homozygous (Q111/111) and heterozygous (Q7/Q111) knock-ins of the HD mutation compared with WT cells (Q7/Q7) (Extended Data Fig. 8b,c) and in HD patient fibroblasts compared with controls (Extended Data Fig. 8d,e), suggesting impaired cytoplasm-nuclear transport. These experiments were conducted in cells treated with proteasome inhibitors to limit degradation of the nuclear pool to enable complete ascertainment of the nuclear transport of newly synthesized proteins in the cytoplasm.
Autophagy inhibition with ATG16L1 knockdown in WT iPS cell-derived neurons (Fig. 4a) or with SBI-0206965 in WT striatal cells (Extended Data Fig. 9a) and WT fibroblasts (Extended Data Fig. 9b) increased nuclear levels of newly synthesized proteins (with or without proteasome inhibition), consistent with our model that cells cope with the accumulation of cytoplasmic autophagy substrates by trafficking these to the nucleus for proteasomal degradation (Extended Data Fig. 9c–f). However, in HD iPS cell-derived neurons (Fig. 4e and Extended Data Fig. 9c,d), HD mutant striatal cells (Extended Data Fig. 9e) and HD fibroblasts (Extended Data Fig. 9f–h), the levels of newly synthesized proteins in the nucleus were reduced after autophagy inhibition, suggesting that HD cells do not have efficient means of relocating the accumulating autophagy substrates proteins from the cytoplasm to the nucleus (Fig. 4f).
Notably, in HD neurons with and without autophagy or proteasome inhibition, aggregates are predominantly cytoplasmic and can be seen in both the cell body and neurites. It was difficult to determine whether nuclei had aggregates or more intense huntingtin staining. Autophagy inhibition increased the cytoplasmic area occupied by aggregates; in contrast, proteasome inhibition increased the percentage of cells with aggregates in the cytoplasm, in the cell body and their area/volume (Extended Data Fig. 10a–c). There may be ceiling effects with these observations as there will likely be a maximum volume of the cells occupied by aggregates that can be tolerated before cell death occurs.
As the HD cells already have a degree of autophagy compromise, this suggests that they are prone to synergistic viability changes akin to synthetic fitness loss due to impaired autophagy and compromised cytoplasm-to-nuclear transport reducing the ability of the cells to manage to ‘overflow’ of cytoplasmic autophagic substrates by nuclear proteasomal degradation. Indeed, MG132 caused more cell death in both iPS cell-derived neurons (Fig. 5a) and striatal cells with the HD mutation compared with controls (Fig. 5b and Extended Data Fig. 10d), consistent with their autophagy defect. Furthermore, HD disease cells were also more sensitive to autophagy inhibition and joint autophagy and proteasome inhibition (Fig. 5a,b and Extended Data Fig. 10e–g). This is consistent with our model that the defective cytoplasm-to-nuclear transport in HD mutation-carrying cells also makes them more vulnerable to autophagy inhibition – two synergistic effects compromising fitness that are inherently present in these cells to a mild extent (Figs. 4f and 5c).
Discussion
In conclusion, our data reveal that the synthetic lethality of autophagy gene mutants with those encoding the nuclear core complex or proteasome components that is seen in yeast is conserved as synergistic loss of viability in human cells. These negative interactions can be attributed to cells responding to the accumulation of cytoplasmic autophagic substrates in autophagy deficiency by trafficking them into the nucleus via the nuclear pores to enable degradation by nuclear proteasomes. The need for nuclear proteasomes in this scenario may reflect the saturation of cytoplasmic proteasomal machinery or the possibility that the nucleolus may enable better protein quality control35. Both autophagy and NPC activities are compromised in HD, and we propose that the negative genetic interaction resulting from the loss of these processes may be a much more potent driver of pathology than the multiplicative effects of both modest defects. The negative genetic interaction between defective autophagy and compromised nuclear pore function is not confined to HD, as both defects have been reported in other diseases, like motor neuron disease caused by C9orf72 mutations and tauopathy36–38. Thus, we propose that such interactions between different pathways may be critical drivers of many monogenic and complex diseases.
Methods
These experiments did not require specific ethics approval, except for patient-derived cell lines, which were obtained with appropriate approvals.
Cell culture
HeLa (human cervical epithelium) (ATCC; CCL-2; CVCL_0030), HEK293FT (human embryonic kidney cell line; Invitrogen, R70007), striatal neuronal cell lines derived from WT HTT Q7/Q7, heterozygous HTT Q7/Q111 and homozygous HTT Q111/Q111 knock-in mice (Coriell Institute CH00097, CH00096 and CH00095, respectively), which are neuronal progenitor cell lines from E14 striatal primordia of HdhQ111 knock-in and WT littermate embryos generated using tsA58 SV40 large T antigen39, were maintained in Dulbecco’s modified Eagle’s medium (DMEM) (4.5 mg l−1 glucose; Sigma) supplemented with 10% FBS (Sigma-Aldrich, F7524), 2 mM l-glutamine (Sigma-Aldrich, G7513) and 100 U ml−1 penicillin-streptomycin (Sigma-Aldrich, P0781). Primary fibroblasts from three unaffected controls (Ctrl, Coriell Institute, GM04711 (Cont1); GM04729 (Cont2), GM04865 (Cont3)), five patients with HD (Coriell Institute GM21757 (HD1), GM0485 (HD3), GM04287 (HD4), GM21756 (HD5); polyQ17/80 HD30501 (HD2) was from F. Squitieri, were cultured in GlutaMAX medium (Gibco) supplemented with 20% FBS (Sigma-Aldrich, F7524), 100 U ml−1 penicillin-streptomycin (Sigma-Aldrich, P0781), MEM non-essential amino acid solution (Sigma-Aldrich, M7145) and 2 mM l-glutamine (Sigma-Aldrich, G7513). Ub-G76V-GFP-expressing stable HeLa cell line, which was described previously26. Autophagy-deficient ATG16L1 CRISPR KO (ATG16L1 KO) HeLa cells and ATG9 CRISPR KO (ATG9 KO) HeLa cells, together with corresponding autophagy-competent control lines (WT HeLa), were generated by our group following previously published protocols9.
All cell lines were incubated at 37 °C (except for striatal neuronal cells maintained at 33 °C) and 5% CO2, in a humidified atmosphere and were regularly tested for Mycoplasma contamination every 2 weeks. All cell lines were authenticated by the provider company and/or by western blot analysis of specific proteins.
Human iPS cell culture and iNeuron differentiation
The G3 line of iPS cells previously derived from WTC11 (Cont iPS cells) were kindly provided by M. E. Ward (National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland)40. For HTT125Q iPS cells, iPS cells were generated from peripheral blood mononuclear cells donated by a juvenile patient with HD originally carrying 125 CAGs (HTT125Q). Stem cells were cultured in E8 Flex medium (Gibco, A2858501) on Vitronectin (Thermo Scientific, A14700)-coated plates at 37 °C, 5% CO2. iPS cells were dissociated with 0.5 mM EDTA when reaching 70% confluency for the maintenance. Neuronal differentiation was performed as described previously33,41. In brief, iPS cells were dissociated into single cells using accutase and then split to 250,000 cells per well in a Geltrex (Thermo Fisher Scientific, A1413302)-coated six-well plate. On the following day, the medium was changed with the induction medium (DMEM/F12 (Gibco, 21331-020), N2 supplement (100×; Gibco, 17502-048), GlutaMAX (100×; Gibco, 35050-061), non-essential amino acids (100×; Gibco, 11140-035), 2-mercaptoethanol (1,000×; Gibco, 31350-010), penicillin-streptomycin (100×; Gibco, 15140-122 (10,000 U ml−1) with doxycycline (1 µg ml−1)). For differentiation, cells were switched to Neurobasal medium (NB growth medium) consisting of Neurobasal (Gibco, 21103-049), B27 supplement (50×; Gibco, 17504-044), GlutaMAX (100×; Gibco, 35050-061), 2-mercaptoethanol (1,000×; Gibco, 31350-010), penicillin-streptomycin (100×; Gibco, 15140-122), NT3 (10 ng ml−1; Peprotech, 45003), BDNF (10 ng ml−1; Peprotech, 45002) with doxycycline (1 µg ml−1; Sigma-Aldrich, D9891). On day 4 after induction, cells were plated onto PDL (Gibco, A38904-01)/Geltrex double-coated dishes depending on the experimental purpose. NB growth medium was changed on the following day. After day 7, the cultures were maintained in NB growth medium without doxycycline and changed every other day.
Cas9 stable cell line
For Cas9 stable cell lines, ATG16L1 WT and KO and ATG9 WT and KO were transduced virus carrying LentiCas9 blast (pKLV-Cas9 blast) in medium supplemented with 6 μg ml−1 Polybrene (Sigma-Aldrich, H9268). Infected cells were selected with 10 μg ml−1 blasticidin (Sigma-Aldrich, 15205). Cas9 stable cell lines (the pool) were assessed for Cas9 cutting efficiency with a lentiviral vector encoding BFP, GFP and an sgRNA against GFP. The percentage of BFP+/GFP− (edited) to BFP+/GFP+ (total transduced) cells was analysed by FACS to identify Cas9-positive and Cas9-negative cells, respectively, using the LSRFortessa flow cytometer (BD). Data were analysed using FlowJo v.10.7.1 Software (BD Life Sciences)42,43.
Antibodies and reagents
The following primary antibodies were used for western blot and immunofluorescence (IF): rabbit monoclonal anti-LC3B (ab192890), mouse monoclonal anti-GAPDH (ab8245), rabbit polyclonal anti-GFP (ab6556), rabbit polyclonal anti-Lamin B1 (ab16048), rabbit monoclonal anti-Nup98 (ab124980), rabbit monoclonal anti-Nup133 (ab155990), rabbit monoclonal anti-PSMD7 (ab181072), mouse monoclonal anti-NPC proteins antibody (ab24609), mouse monoclonal anti-KPNB1 (3E9) (ab2811); rabbit polyclonal anti-KPNA2 (ab70160) from Abcam; Rabbit polyclonal anti-RAN (10469-1-AP), rabbit polyclonal anti-Lamin B1 (12987-1-AP), rabbit polyclonal anti-H2B (15857-1-AP), mouse monoclonal anti-GFP (66002-1Ig), rabbit polyclonal anti-GFP (50430-2-AP), rabbit polyclonal anti-LC3 (14600-1-AP) from Proteintech; rabbit anti-K48-linkage polyubiquitin (8081), rabbit polyclonal anti-PSMA5 (2457), rabbit monoclonal anti-ATG16L1 (8089) from Cell Signaling; rabbit polyclonal anti-ATG16L1 (MBL, PM040); mouse anti-puromycin (MABE343), mouse anti-polyglutamine-expansion (MAB1574) anti-ubiquitinylated proteins (FK2) (04-263) from Millipore; rabbit polyclonal anti-AKIRIN2 (Atlas Antibodies, HPA064239); mouse monoclonal anti-C6ORF166 (3D9) (AKIRIN2) (Abnova, H00055122-M01); mouse monoclonal anti-PSMB4 (H-3) (Santacruz, sc390878); and mouse monoclonal anti-HA.11 clone 16B12 (Covance, MMS-101P). All primary antibodies were used for overnight incubation at 4 °C and secondary antibodies were used at a dilution of 1:4,000 with incubation for 1 h at room temperature. The secondary antibodies used for IF were conjugated to Alexa Fluor 488 or 594 (Invitrogen). The secondary antibodies used for western blot were the horseradish peroxidase (HRP)-conjugated secondary antibodies, anti-mouse (NA931V, GE Healthcare) and anti-rabbit (NA934V, GE Healthcare) from GE Healthcare and the LI-COR secondary antibodies, anti-mouse 680 and anti-rabbit 800.
The reagents used included MG132 (C2211), SBI-0206965 (SML1540), ivermectin (I8898) and importazole (SML0341) from Sigma-Aldrich; bortezomib (PS-341) (Selleck Chem, S1013), InstantBlue Coomassie Protein Stain (ISB1L) (Abcam, ab119211) and O-propargyl-puromycin (Jena Bioscience, NU-931-05). Reagents were dissolved with DMSO (Sigma-Aldrich). Other reagents were 500 µg ml−1 Geneticin Selective Antibiotic (G418, Gibco, 11811-031), MEM amino acids solution (11130-051) and non-essential amino acids solution (11140-050) from Thermo Scientific.
Plasmids and siRNAs
The pre-designed siRNAs (On-Target Plus SMART pool and/or sets of deconvoluted oligonucleotides) and pre-designed pLKO.1 shRNAs vectors were acquired from the RNAi Consortium are described in Supplementary Table 5.
The following constructs were used: the enhanced GFP (EGFP)-tagged mutant α-synuclein (pEGFP-A53T α-syn) and pHM-mutant α-synuclein (pHM-A53T α-syn) was produced by our group44. EGFP-tagged ATG16L1 (pEGFP-ATG16L1)45 and EGFP-empty (EGFP-C1) was purchased from Clontech. EGFP-tagged LC3 (LC3 WT) and EGFP-LC3-G120A (LC3 G120A) constructs were kind gifts from T. Yoshimori (Osaka University, Japan)9. The LentiCas9 blast vector and the Lenti-PB (pKLV-PB-U6 gRNA(BbsI)-PGKpuro2ABFP) gRNA cloning vector for the CRISPR/Cas9 screen were kindly gifted from E. Metzakopian, UK DRI42.
Transfection
For siRNA transfection, HeLa cells were plated in 6 well plates and transfected with 100 nM siRNA using Lipofectamine RNAi max (Invitrogen, 13778150) for 4–6 h, according to the manufacturer’s instructions. On the following day, cells were split if required and then target genes were knocked down with a second siRNA transfection. To measure cytotoxicity in 96-well plates, HeLa cells were cultured in 96-well plates and then transfected with siRNAs using Lipofectamine 2000 (Invitrogen, 11668) in growth medium without antibiotics for 4–6 h, following the manufacturer’s instructions. Transfected cells were re-seeded in 96-well plates, and followed by another siRNA post-transfection after 48 h. siRNAs were used at 30 nM. After transfections, cells were incubated with full growth medium.
For DNA transfection, cells were seeded in 6 well plates and cells were transfected with 1 µg of DNA with TransIT-2020 reagent (Mirus, MIR5400), following the manufacturer’s instructions. The following day, cells were re-seeded for the relevant experimental requirements.
Lentivirus production and infection
shRNA lentiviral particles were produced and transduced following the RNAi Consortium protocols as described previously46. In brief, HEK293FT packaging cells in 100 mm dishes were co-transfected at 60–70% confluence with a mix of 2.5 μg psPAX2 vector (packaging vector), 270 ng pMD2.G vector (envelope vector) and 2.7 µg hairpin-pLKO.1 vector using TransIT-LT1 (Mirus) transfection reagent according to the manufacturer’s instructions. Transfected cells were cultured in high-serum medium (20% FBS). After 40 h, cell culture medium containing the virus was collected and replaced by high-serum medium at three times repeatedly every 24 h. Viral preps were then concentrated by centrifugation at 160, 100g for 90 min. For infection in iPS cell-derived neurons, viruses were added to the iPS cell-derived neurons and incubated overnight. On the following day, medium was replaced by full growth medium and cells were further incubated for an additional 4 days before testing the knockdown effects.
For synthetic lethality (SL) CRISPR/Cas9 arrayed screening, gRNA virus production for 96-well plates was performed as previously described42,43. In brief, individual lentiviral plasmids containing an sgRNA were transfected into HEK293FT packaging cells in a 96-well plate format (sgRNA sequences in Supplementary Table 6). HEK293FT packaging cells in 96-well plates were co-transfected at 70% confluence with a mix of 19.5 ng psPAX2 vector (packaging vector), 12.5 ng pMD2.G vector (envelope vector) and 25 ng lentiviral plasmid containing sgRNA using Lipofectamine LTX with PLUS transfection reagent (Invitrogen, 15338100), according to the manufacturer’s instructions. After 24 h, the medium was replaced by full growth medium (DMEM). The viral preparations were collected at 48 h and 72 h post-transfection and then aliquoted and stored at −80 °C. For infection in Cas9 stable HeLa cell lines (ATG16L1 WT, KO and ATG9 WT, KO), viral titres were added to the cells in the presence of 6 µg ml−1 Polybrene (Sigma-Aldrich) and incubated overnight. On the following day, the medium was replaced by full growth medium and cells were incubated further before screening started.
Western blot analysis
Cells were cultured in 6- or 12-well plates depending on experimental requirements. Cells were washed in ice-cold PBS twice, then lysed in 1× Laemmli buffer (62.5 mM Tris, pH 6.8, 2% SDS, 10% glycerol, 50 mM dithiothreitol (DTT) and 0.01% bromophenol blue) and boiled at 100 °C for 10 min or lysed in RIPA buffer (150 nM NaCl, 1% NP-40, 0.5% NaDoc, 0.1% SDS and 50 mM Tris-HCl, pH 7.4; Sigma-Aldrich) supplemented with protease and phosphatase inhibitor cocktail (Roche Diagnostics). Cells were incubated on ice for 10 min and then centrifuged at 16,000g for 10 min at 4 °C. Protein concentrations of supernatants were quantified using a Bradford assay kit (Bio-Rad). Then, lysates were denatured with 2× Laemmli buffer and boiled at 100 °C for 10 min. For western blot analysis, samples were subjected to SDS–PAGE separation and transferred onto PVDF membranes (Millipore, IPFL00005 or IPVH00005). PVDF membranes were blocked with 4% skim-milk in PBS containing 0.1% Tween for 1 h and incubated with primary antibody at 4 °C overnight. After washing the membrane with 0.1% Tween-PBS, the secondary antibodies were used at a dilution of 1:4,000 and incubated for 1 h at room temperature. Proteins on the membrane were visualized with direct infra-red fluorescence detection on a LI-COR Odyssey scanner or with an ECL enhanced chemiluminescence detection kit (GE Healthcare). The protein levels on the immunoblots were quantified using ImageJ program or IMAGE STUDIO Lite software.
Immunoprecipitation
For immunoprecipitation of GFP-α-Syn A53T proteins using GFP-Trap, according to the manufacturer’s instructions (gtma-100, ChromoTek), cells were lysed with lysis buffer (10 mM Tris-HCl, pH 7.5, 150 mM NaCl, 0.5 mM EDTA and 0.5% NP-40) containing protease and phosphatase inhibitors from Roche Diagnostics for 30 min at 4 °C. The lysed cells were centrifuged at 13,000g for 10 min and the supernatant was transferred to a new E-tube and mixed with dilution buffer (10 mM Tris-HCl, pH 7.5, 150 mM NaCl and 0.5 mM EDTA). For input loading control, 50 µl of supernatant from each sample was mixed with 2× Laemmli buffer and then boiled at 100 °C for 10 min. The samples were further incubated with 25 µl pre-washed GFP-Trap beads for 1 h at 4 °C on a rotating surface. GFP-beads were washed five times with dilution buffer, resuspended with 2× Laemmli buffer and boiled at 100 °C for 10 min.
Immunofluorescence
For immunofluorescence, cells on coverslips were fixed with 4% paraformaldehyde (PFA; Sigma-Aldrich) for 5 min. After washing, cells were permeabilized with 0.1% Triton X-100 for 10 min or ice-cold methanol for 15 min (for anti-PSMB4, anti-PSMA5 or anti-GFP) and blocked with 3% BSA (Thermo Scientific, BP1605-100) for 1 h. Cells were incubated with primary antibodies in blocking buffer overnight at 4 °C. After rinsing three times with PBS, cells were incubated with secondary antibodies tagged with Alexa Fluor (Molecular Probes) for 90 min at room temperature. After incubation, cells on coverslips were washed with PBS and then mounted in ProLong Gold Antifade reagent with DAPI (Invitrogen, P36931).
For aggresome detection, aggregates in cells were detected using PROTEOSTAT Aggresome detection kit (Enzo Life Sciences, ENZ-51035) following the manufacturer’s protocol. In brief, cells were fixed in 4% PFA for 30 min at room temperature and then incubated with permeabilizing solution (0.5% Triton X-100, 3 mM EDTA) on ice for 30 min with gently shaking. Cells were stained with PROTEOSTAT Aggresome Detection Reagent for 30 min at room temperature, protected from light, followed by 15 min wash in PBS. Coverslips were mounted with ProLong Gold Antifade Reagent.
Imaging was performed with LSM710 or LSM880 Zeiss confocal (×40, ×63 NA 1.4 Plan Apochromat oil-immersion lens, Carl Zeiss).
Imaging for monitoring nucleocytoplasmic shuttling
Nucleocytoplasmic shuttling using the NLS–tdTomato–NES construct was assessed as described previously31. Cells were transfected with the NLS–tdTomato–NES construct (provided by J. Rothstein; Addgene cat. no. 112579). For fixed cell imaging, transfected cells were plated on glass coverslips. After drug treatments as per experimental requirements, cells were fixed with 4% PFA for 3 min. Cells on coverslips were washed with PBS and mounted in ProLong Gold Antifade reagent. For live-cell imaging, transfected cells were plated onto MatTek Petri dishes (MatTek). After adding Hoechst 33342 dye (1:5,000, Cell Signaling Technology, cat. no. 4082S) for 10 min, they were imaged at 37 °C, utilizing an LSM780 Zeiss confocal equipped with a ×63 oil-immersion lens.
Imaging for FRAP analysis
FRAP assay was used to measure the real-time kinetics of nuclear fluorescence recovery after photobleaching in cells expressing either GFP-empty or GFP-A53T α-Syn in WT or ATG16L1-null cells. FRAP assay and analysis was performed with the approach described previously21.
For FRAP assay imaging, transfected cells were plated onto MatTek Petri dishes (MatTek) and then they were imaged at 37 °C, utilizing an LSM780 Zeiss confocal equipped with a ×63 oil-immersion lens. Each cell was scanned at low laser power to minimize fluorescence loss during bleaching and the region of interest (ROI) within the nucleus was then photobleached at 70% laser power with 488 nm wavelength for approximately 3 s.
For FRAP data analysis, we used two methods. The first simply assessed fluorescence recovery in the previously photobleached nuclear region. The second assessed the fluorescence of a nuclear ROI that had been previously photobleached compared with a cytoplasmic ROI (a control region) in the same cell that had not been previously photobleached; here, the fluorescence data before and after bleaching was expressed as a ratio of nuclear/cytoplasmic fluorescence.
For each analytical approach, the pre-bleach ratios were set to 100% to normalize between samples. Finally, the first post-bleach image was set to time 0, with successive time points converging toward 100% fluorescence recovery. We used this approach to normalize across different experiments, as differences in initial post-bleach mean values may be exaggerated due to the large difference in early transport rates in different experiments and a slight delay between fluorescence bleach and image capture. The recovery curves are shown each based on an average of 12–15 cells and representative of at least three independent experiments. Details are previously described47. To compare initial nuclear transport rates, linear regression analysis (curve-fitting) of the values from the first 32 s and the average recovery curves were performed in Excel and GraphPad Prism10.
Synthetic lethality CRISPR/Cas9 Screen with gRNAs
To clone the gRNAs into the pKLV-PB-U6 gRNA(BbsI)-PGKpuro2ABFP (Lenti-PB) vector, pre-designed single-strand oligonucleotides with compatible overhangs for BbsI (sequences kindly provided by E. Metzakopian, UK DRI) were purchased from Merck, annealed and cloned into the BbsI site of Lenti-PB using standard restriction enzyme cloning.
Cas9 stable cells were infected with Lenti-PB vector carrying the gRNAs and BFP with about 50% infection efficiency in 96-well plates. After lentiviral gRNA infection for 3 days (starting point), the number of infected cells was monitored by BFP fluorescence using FACS (LSRFortessa instrument, BD) in the indicated intervals between starting (day 3) and finishing time point (day 12)48. Cells were first gated on forward (FSC-A) and side scatter (SSC-A) and then for singlets (FSC-A/FSC-H), before gating the BFP+ cells.
Cell viability was assessed as the percentage of BFP+ cells relative to the starting point (day 3 after infection). Non-targeting gRNA-transfected cells were used as a negative control. FACS-based cell number analysis was performed using FlowJo v.10.7.1 software for macOS (BD Life Sciences).
Lactate dehydrogenase cytotoxicity assay
Lactate dehydrogenase (LDH) activity was determined with CyQUANT LDH Cytotoxicity Assay kit (Invitrogen, C20301), following the manufacturer’s instructions. To prepare controls, cells were incubated with 10 µl sterile water for the spontaneous LDH release sample or with 10 µl of 10× Lysis buffer for the maximum LDH release sample in cell culture medium for 45 min in an incubator. Then, 50 µl of each sample medium was collected and transferred to a new 96-well plate and then mixed with 50 µl reaction mixture. The plates were incubated at room temperature with light protection for 30 min. Then, 50 µl stop solution was added to each sample well to stop the reaction. LDH activity was measured by absorbance using a TECAN Spark microplate reader at 490 nm and 680 nm (as a reference wavelength).
Incucyte live-cell imaging
For live-cell imaging of cytotoxicity, cells were incubated with CellTox Green Dye (Promega, G8741, 1:1,000 dilution) to measure cytotoxicity caused by changes of membrane integrity, according to the manufacturer’s protocol. The cell plate was placed in the Incucyte machine (Essen Bioscience, Incucyte S3 with ×10 magnification) with cell culture conditions. Images were acquired with green fluorescence (Ex, 450–490 nm; Em, 500–530 nm) and phase. The level of cell death was calculated based on dead cells with green fluorescent area (green) divided by total cells area (phase) using Incucyte, indicating that these results reflect overall cells measured with total cell area (phase). All five fields in a well were calculated per condition for each experiment.
Detection of newly synthesized proteins
Newly synthetized proteins were detected using BONCAT (bioorthogonal non-canonical amino acid tagging) or SUnSET (surface sensing of translation) methods as previously described26.
For BONCAT27, cells were cultured in DMEM with no methionine and no cysteine (Gibco, 21013024) for 1 h and then treated with the methionine analogue AHA (Thermo Scientific, C10102) in DMEM without methionine for 4 h. To measure the levels of newly synthesized proteins in subcellular fractions by immunoblotting, nuclear/cytoplasmic fractionations were performed as described in section below with mild detergent49. In nuclear/cytosolic fractionations, AHA-labelled proteins were generated using the Click-iT Protein Reaction Buffer kit (Thermo Scientific, C10276) according to the manufacturer’s protocol. AHA-labelled proteins clicked with biotin alkyne (Thermo Scientific, B10185) were examined by western blotting, followed by incubation with streptavidin–Alexa Fluor 488 (Thermo Scientific, S11223). To visualize newly synthesized proteins by IF, AHA-labelled cells on glass coverslips were fixed with 4% PFA and permeabilized with 0.25% TrionX100 for 15 min. After washing with 2% BSA in PBS, AHA-labelled proteins were detected using the Click-iT Cell Reaction Buffer kit (Thermo Scientific, C10269) according to the manufacturer’s protocol. AHA-labelled proteins were clicked with either Alexa Fluor 488 Alkyne (Thermo Scientific, A10267) or Alexa Fluor 594 Alkyne (Thermo Scientific, A10275), followed by mounting with ProLong Gold Antifade with DAPI (Thermo Scientific, P36935).
For analysis of puromycin-induced foci using SUnSET methods25, cells were incubated with O-propargyl-puromycin (Jena Bioscience, NU-931-05) for 2 h before fixation. For analysis of ubiquitin-positive puromycin-induced foci formation, cells were incubated with 5 μg ml−1 puromycin for 3–4 h in full growth medium, followed by fixation in 4% PFA and staining with FK2 antibody (Millipore, 04-263). Imaging for puromycin-labelled proteins was performed as previously described50. In brief, O-propargyl-puromycin-labelled (Jena Bioscience, NU-931-05) cells were fixed in ice-cold methanol for 2 min at −20 °C, washed with PBS and permeabilized with 0.2% Triton X-100. Cells were stained by incubating for 30 min in 100 mM Tris, pH 8.5, 0.5 mM CuSO4, 20 μM Alexa Fluor 594-azide (Thermo Scientific, A10270) and 50 mM ascorbic acid, followed by washing. Coverslips were mounted with ProLong Gold Antifade Reagent.
Nuclear and cytoplasmic fractionation
For general cell fractionation in steady-state, nuclear and cytoplasmic fractions were isolated using the NE-PER Nuclear and Cytoplasmic Extraction kit (Thermo Scientific, 78833), as described previously13.
To detect newly synthesized proteins in cellular fractions, subcellular fractionation was performed as described previously49. After incubation with AHA, cells were washed with ice-cold PBS and collected after centrifugation at 500g for 10 min at 4 °C. Pellets were suspended with 200 µl ice-cold lysis buffer A (NaCl 150 mM, HEPES (pH 7.4) 50 mM, digitonin (Sigma-Aldrich, D141) 25 mg ml−1 and hexylene glycol (Sigma-Aldrich, 112100, 1 M) containing a protease inhibitor cocktail (Roche Diagnostics, 11873580001). Samples were incubated on a rotator for 10 min at 4 °C and then centrifuged at 2,000g for 10 min at 4 °C. The supernatant was considered as the cytosolic fraction. Then, 200 µl ice-cold lysis buffer B (NaCl 150 mM, HEPES (pH 7.4) 50 mM, IGEPAL (Sigma-Aldrich, I7771) 1% and hexylene glycol 1 M) containing a protease inhibitor cocktail was added to the pellets and mixed by vortexing. The tubes were placed on ice for 30 min and then centrifuged at 7,000g for 10 min at 4 °C. The supernatant contains membrane bound organelles. The remaining pellets were resuspended with 200 µl ice-cold lysis buffer C (NaCl 150 mM, HEPES (pH 7.4) 50 mM, sodium deoxycholate 0.5%, sodium dodecyl sulfate 0.1% and hexylene glycol 1 M) containing Benzonase (Sigma-Aldrich, E1014) and protease inhibitors. For collecting nuclear fractions, samples were lysed on rotator for 30 min at 4 °C to enable complete solubilization. After centrifugation at 7,800g for 10 min 4 °C, supernatants containing nuclear extracts were transferred into pre-chilled new tubes. Histone H2B or Lamin B1 was used as a nuclear control and GAPDH was used as a cytosolic control.
FACS analysis of Ub-G76V-GFP
HeLa cells stably expressing Ub-G76V-GFP, a ubiquitin fusion degradation reporter degraded by the proteasome, were previously described26. HeLa/Ub-G76V-GFP were treated with proteasome inhibitors for 6 h or 24 h at different concentrations. Cells were then trypsinized and GFP fluorescence was analysed using an Attune NxT Flow Cytometer (Thermo Scientific) using the BL1 (488 530/30) detector. Cells were first gated on forward (FSC-A) and side scatter (SSC-A) for P1 and then for singlets (FSC-A/FSC-H) for P2. Then, 20,000 single cells were recorded for each replicate. GFP+ gates were set using normal HeLa cells. The data were analysed using FlowJo software v.10.7.1.
Bioinformatic analysis
The genetic interactions of the core autophagy genes of Saccharomyces cerevisiae (ATG1, ATG2, ATG3, ATG4, ATG5, VPS30, ATG7, ATG8, ATG9, ATG10, ATG12, ATG13, ATG14, ATG16, ATG17, ATG18, ATG29 and ATG31) were downloaded from the Saccharomyces Genome Database (www.yeastgenome.org) using YeastMine51 and filtered for SL and negative genetic interactions using R software (https://www.Rproject.org/). Genes showing genetic interactions with at least five core autophagy genes were selected for further analysis. To obtain the human orthologues, the yeast genes selected were either uploaded to HumanMine52,53 or compared with the orthologue list downloaded from the HUGO Gene Nomenclature Committee (HGNC Database, https://www.genenames.org/)54.
Image analysis
Fluorescence intensity of confocal images was measured by ImageJ. A minimum of 30 cells were examined for each condition. All experiments were repeated in at least three biological experiments (n = 3). To confirm previously published results, experiments were performed once with three different siRNA oligonucleotides and two different proteasome subunits or different time points and different concentrations of drugs with different inhibitors for the same mechanisms (about 30 cells in each condition). The background was fixed for all within-experiment analyses.
Statistics and reproducibility
Significance levels for comparisons between groups were determined with an unpaired or paired two-tailed Student’s t-test or a one-way ANOVA, or a two-way ANOVA followed by an appropriate post hoc test for multiple comparisons using GraphPad Prism 7 and 10 (GraphPad Software) or Excel (Microsoft Office). For the two-way ANOVA, we sought to avoid situations where all values for a control condition were 1, which would result in no variance, violating assumptions for ANOVAs. Thus, we took the normalized fold changes from each experiment individually (where control data in ATG16+ and ATG16− were originally both set to 1) and divided all data points from the normalized data by the number of conditions. The resulting numbers were used as the control values for each experiment, which were then multiplied by the fold change in each perturbation condition to derive the perturbation values. These data were used for the ANOVAs (see source data). For the graphs, we illustrate effects by setting control data in ATG16+ and ATG16− cells to 1, so that different responses to perturbations between the different cell lines can be readily appreciated. For the one-way ANOVA, we restricted the analysis to each condition separately.
Western blots protein levels were normalized to total forms or a housekeeping protein, such as GAPDH. All data were expressed as mean ± s.e.m., as stated in figure legends and source data. P values <0.05 were considered statistically significant.
Sample sizes were chosen on the basis of extensive experience with the assays we have performed. No randomization was performed for cell culture experiments, as it was not necessary. But all perturbations were performed in parallel. No data were excluded from the analyses. Staining and analysis were performed in a blinded fashion. Investigators were not blinded to allocation during experiments and outcome assessment. Data distribution for parametric test was assumed to be normal but this was not formally tested.
Reporting summary
Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.
Online content
Any methods, additional references, Nature Portfolio reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at 10.1038/s41556-024-01488-7.
Supplementary information
Source data
Acknowledgements
This research was supported by the Cambridge Institute for Medical Research (CIMR) Flow Cytometry Core Facility and CIMR Microscopy Core Facility, who we thank for their advice and support in flow cytometry. This work is supported by the UK Dementia Research Institute through UK DRI, principally funded by the Medical Research Council (to D.C.R. and G.B.) and the National Institute for Health and Care Research (NIHR) Cambridge Biomedical Research Centre (BRC-1215-20014). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.
Extended data
Author contributions
S.J.P. and D.C.R. developed the study rationale. S.J.P. and D.C.R. wrote the manuscript, which was commented on by all authors. S.J.P. designed and performed most of the experiments. S.M.S. and L.W. performed experiments and assisted with data analysis. A.D.B. analysed yeast genetic interactions. E.S. helped the experimental design of CRISPR/Cas9 screen. F.S. provided HD fibroblasts. G.B. provided HTT125Q iPS cells. D.C.R. supervised the study.
Peer review
Peer review information
Nature Cell Biology thanks Andrew Yoo and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Data availability
All data supporting the findings of this study are available from the corresponding author upon reasonable request. Source data are provided with this paper.
Code availability
The custom R script used in the analysis of yeast genetic interactions with core autophagy genes is available at https://github.com/adc67/YeastGeneticAnalysis.
Competing interests
D.C.R. is a consultant for Aladdin Healthcare Technologies, Mindrank AI, Nido Biosciences, Drishti Discoveries, Retro Biosciences, PAQ Therapeutics and Alexion Pharma Intl Ops Limited. G.B. is a founder and Director of Function Rx. The other authors declare no competing interests.
Footnotes
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data
is available for this paper at 10.1038/s41556-024-01488-7.
Supplementary information
The online version contains supplementary material available at 10.1038/s41556-024-01488-7.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
All data supporting the findings of this study are available from the corresponding author upon reasonable request. Source data are provided with this paper.
The custom R script used in the analysis of yeast genetic interactions with core autophagy genes is available at https://github.com/adc67/YeastGeneticAnalysis.