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COPA mutations impair ER-Golgi transport and cause hereditary autoimmune-mediated lung disease and arthritis


Unbiased genetic studies have uncovered surprising molecular mechanisms in human cellular immunity and autoimmunity1. We performed whole-exome sequencing and targeted sequencing in five families with an apparent mendelian syndrome of autoimmunity characterized by high-titer autoantibodies, inflammatory arthritis and interstitial lung disease. We identified four unique deleterious variants in the COPA gene (encoding coatomer subunit α) affecting the same functional domain. Hypothesizing that mutant COPA leads to defective intracellular transport via coat protein complex I (COPI)2,3,4, we show that COPA variants impair binding to proteins targeted for retrograde Golgi-to-ER transport. Additionally, expression of mutant COPA results in ER stress and the upregulation of cytokines priming for a T helper type 17 (TH17) response. Patient-derived CD4+ T cells also demonstrate significant skewing toward a TH17 phenotype that is implicated in autoimmunity5,6. Our findings uncover an unexpected molecular link between a vesicular transport protein and a syndrome of autoimmunity manifested by lung and joint disease.

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Figure 1: Genetic segregation of interstitial lung disease and arthritis with COPA mutations.
Figure 2: The binding of mutant COPA to dilysine motifs is impaired.
Figure 3: Mutant COPA leads to an increase in ER stress.
Figure 4: Patients with mutant COPA demonstrate an increase in TH17-priming cytokine levels in BLCLs and an increase in TH17 cell numbers.

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  1. Zenewicz, L.A., Abraham, C., Flavell, R.A. & Cho, J.H. Unraveling the genetics of autoimmunity. Cell 140, 791–797 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  2. Letourneur, F. et al. Coatomer is essential for retrieval of dilysine-tagged proteins to the endoplasmic reticulum. Cell 79, 1199–1207 (1994).

    CAS  PubMed  Google Scholar 

  3. Eugster, A., Frigerio, G., Dale, M. & Duden, R. COP I domains required for coatomer integrity, and novel interactions with ARF and ARF-GAP. EMBO J. 19, 3905–3917 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Popoff, V., Adolf, F., Brügger, B. & Wieland, F. COPI budding within the Golgi stack. Cold Spring Harb. Perspect. Biol. 3, a005231 (2011).

    PubMed  PubMed Central  Google Scholar 

  5. Leipe, J. et al. Role of Th17 cells in human autoimmune arthritis. Arthritis Rheum. 62, 2876–2885 (2010).

    CAS  PubMed  Google Scholar 

  6. Miossec, P., Korn, T. & Kuchroo, V.K. Interleukin-17 and type 17 helper T cells. N. Engl. J. Med. 361, 888–898 (2009).

    CAS  PubMed  Google Scholar 

  7. Cheng, M.H. & Anderson, M.S. Monogenic autoimmunity. Annu. Rev. Immunol. 30, 393–427 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Rieux-Laucat, F. & Casanova, J.L. Autoimmunity by haploinsufficiency. Science 345, 1560–1561 (2014).

    CAS  PubMed  Google Scholar 

  9. Garg, S. et al. Lysosomal trafficking, antigen presentation, and microbial killing are controlled by the Arf-like GTPase Arl8b. Immunity 35, 182–193 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Todd, D.J., Lee, A.-H. & Glimcher, L.H. The endoplasmic reticulum stress response in immunity and autoimmunity. Nat. Rev. Immunol. 8, 663–674 (2008).

    CAS  PubMed  Google Scholar 

  11. Strange, C. & Highland, K.B. Interstitial lung disease in the patient who has connective tissue disease. Clin. Chest Med. 25, 549–559 (2004).

    PubMed  Google Scholar 

  12. Bamshad, M.J. et al. The Centers for Mendelian Genomics: a new large-scale initiative to identify the genes underlying rare Mendelian conditions. Am. J. Med. Genet. A. 158A, 1523–1525 (2012).

    PubMed  Google Scholar 

  13. Fishelson, M. & Geiger, D. Exact genetic linkage computations for general pedigrees. Bioinformatics 18 (suppl. 1), S189–S198 (2002).

    PubMed  Google Scholar 

  14. Brandizzi, F. & Barlowe, C. Organization of the ER-Golgi interface for membrane traffic control. Nat. Rev. Mol. Cell Biol. 14, 382–392 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Schröder-Köhne, S., Letourneur, F. & Riezman, H. α-COP can discriminate between distinct, functional di-lysine signals in vitro and regulates access into retrograde transport. J. Cell Sci. 111, 3459–3470 (1998).

    PubMed  Google Scholar 

  16. Goldberg, J. Decoding of sorting signals by coatomer through a GTPase switch in the COPI coat complex. Cell 100, 671–679 (2000).

    CAS  PubMed  Google Scholar 

  17. Claerhout, S. et al. Abortive autophagy induces endoplasmic reticulum stress and cell death in cancer cells. PLoS ONE 7, e39400 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Hasnain, S.Z., Lourie, R., Das, I., Chen, A.C.-H. & McGuckin, M.A. The interplay between endoplasmic reticulum stress and inflammation. Immunol. Cell Biol. 90, 260–270 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Tanjore, H., Blackwell, T.S. & Lawson, W.E. Emerging evidence for endoplasmic reticulum stress in the pathogenesis of idiopathic pulmonary fibrosis. Am. J. Physiol. Lung Cell. Mol. Physiol. 302, L721–L729 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Samali, A., Fitzgerald, U., Deegan, S. & Gupta, S. Methods for monitoring endoplasmic reticulum stress and the unfolded protein response. Int. J. Cell Biol. 2010, 830307 (2010).

    PubMed  PubMed Central  Google Scholar 

  21. Ogata, M. et al. Autophagy is activated for cell survival after endoplasmic reticulum stress. Mol. Cell. Biol. 26, 9220–9231 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Deretic, V., Saitoh, T. & Akira, S. Autophagy in infection, inflammation and immunity. Nat. Rev. Immunol. 13, 722–737 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Bhattacharya, A. & Eissa, N.T. Autophagy and autoimmunity crosstalks. Front. Immunol. 4, 88 (2013).

    PubMed  PubMed Central  Google Scholar 

  24. Razi, M., Chan, E.Y.W. & Tooze, S.A. Early endosomes and endosomal coatomer are required for autophagy. J. Cell Biol. 185, 305–321 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Adolph, T.E. et al. Paneth cells as a site of origin for intestinal inflammation. Nature 503, 272–276 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Palmer, M.T. & Weaver, C.T. Autoimmunity: increasing suspects in the CD4+ T cell lineup. Nat. Immunol. 11, 36–40 (2010).

    CAS  PubMed  Google Scholar 

  27. Wheeler, M.C. et al. KDEL-retained antigen in B lymphocytes induces a proinflammatory response: a possible role for endoplasmic reticulum stress in adaptive T cell immunity. J. Immunol. 181, 256–264 (2008).

    CAS  PubMed  Google Scholar 

  28. Glatigny, S. et al. Proinflammatory Th17 cells are expanded and induced by dendritic cells in spondylarthritis-prone HLA-B27–transgenic rats. Arthritis Rheum. 64, 110–120 (2012).

    CAS  PubMed  Google Scholar 

  29. DeLay, M.L. et al. HLA-B27 misfolding and the unfolded protein response augment interleukin-23 production and are associated with Th17 activation in transgenic rats. Arthritis Rheum. 60, 2633–2643 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Goodall, J.C. et al. Endoplasmic reticulum stress-induced transcription factor, CHOP, is crucial for dendritic cell IL-23 expression. Proc. Natl. Acad. Sci. USA 107, 17698–17703 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Gaffen, S.L., Jain, R., Garg, A.V. & Cua, D.J. The IL-23–IL-17 immune axis: from mechanisms to therapeutic testing. Nat. Rev. Immunol. 14, 585–600 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Bolze, A. et al. Ribosomal protein SA haploinsufficiency in humans with isolated congenital asplenia. Science 340, 976–978 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Gissen, P. & Maher, E.R. Cargos and genes: insights into vesicular transport from inherited human disease. J. Med. Genet. 44, 545–555 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Russo, R., Esposito, M.R. & Iolascon, A. Inherited hematological disorders due to defects in coat protein (COP)II complex. Am. J. Hematol. 88, 135–140 (2013).

    CAS  PubMed  Google Scholar 

  35. Weber, C.K. et al. Antibodies to the endoplasmic reticulum–resident chaperones calnexin, BiP and Grp94 in patients with rheumatoid arthritis and systemic lupus erythematosus. Rheumatology 49, 2255–2263 (2010).

    CAS  PubMed  Google Scholar 

  36. Olewicz-Gawlik, A. et al. Interleukin-17 and interleukin-23: importance in the pathogenesis of lung impairment in patients with systemic sclerosis. Int. J. Rheum. Dis. 17, 664–670 (2014).

    CAS  PubMed  Google Scholar 

  37. Weaver, C.T., Elson, C.O., Fouser, L.A. & Kolls, J.K. The Th17 pathway and inflammatory diseases of the intestines, lungs, and skin. Annu. Rev. Pathol. 8, 477–512 (2013).

    CAS  PubMed  Google Scholar 

  38. Nistala, K. et al. Interleukin-17–producing T cells are enriched in the joints of children with arthritis, but have a reciprocal relationship to regulatory T cell numbers. Arthritis Rheum. 58, 875–887 (2008).

    PubMed  PubMed Central  Google Scholar 

  39. Benham, H. et al. Th17 and Th22 cells in psoriatic arthritis and psoriasis. Arthritis Res. Ther. 15, R136 (2013).

    PubMed  PubMed Central  Google Scholar 

  40. Reid, J.G. et al. Launching genomics into the cloud: deployment of Mercury, a next generation sequence analysis pipeline. BMC Bioinformatics 15, 30 (2014).

    PubMed  PubMed Central  Google Scholar 

  41. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. DePristo, M.A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491–498 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Teer, J.K., Green, E.D., Mullikin, J.C. & Biesecker, L.G. VarSifter: visualizing and analyzing exome-scale sequence variation data on a desktop computer. Bioinformatics 28, 599–600 (2012).

    CAS  PubMed  Google Scholar 

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We thank the patients and their families for their involvement in these studies. The group at the University of California San Francisco thanks R. Schekman for useful comments, S. McClymont, O. Estrada, R. Wadia and M. Newasker for assistance with subject recruitment and the University of California San Francisco Genomics Core. Funding was provided by US National Institutes of Health (NIH) grant R01AI067946 (J.S.O.), the Jeffrey Modell Foundation (J.S.O.), US NIH grant K08HL095659 (A.K.S.), the Foundation of the American Thoracic Society (A.K.S.), the Pulmonary Fibrosis Foundation (A.K.S.), the Nina Ireland Lung Disease Program (A.K.S.), US NIH (National Human Genome Research Institute/National Heart, Lung, and Blood Institute) grant U54HG006542 and (National Institute of Neurological Disorders and Stroke) grant 2RO1NS058529 (J.R.L.), US NIH (National Human Genome Research Institute) grant U54HG003273 (R.A.G.), US NIH grant K23NS078056 (W.W.) and US NIH grant AI053831 (L.B.W.).

Author information

Authors and Affiliations




L.B.W., B.J. and W.W. designed and performed experiments, analyzed data and wrote the manuscript. T.J.V., L.R.F., D.L.C., S.K.N., S.D.D. and M.R.W. provided clinical care and analyzed clinical data. J.H. and K.D.J. performed pathology services. A.S.-P., K.L., T.G., R.L.P.S.-C., C.-G.J., N.Z. and L.F.T. analyzed data. Y.S., E.M.M., D.L., K.N., M.T., M.J. and C.S.L. performed experiments and analyzed data. G.M., N.T.E., F.R.P. and M.D.R. designed experiments and analyzed data. S.N.J., S.P., D.M.M., E.B., R.A.G., M.S.A. and P.-Y.K. organized studies. S.M.L., R.L.P.S.-C. and M.H.C. analyzed data and assisted with writing the manuscript. J.S.O., J.R.L. and A.K.S. supervised the study and wrote the manuscript.

Corresponding authors

Correspondence to Jordan S Orange or Anthony K Shum.

Ethics declarations

Competing interests

J.R.L. has stock ownership in 23 and Me, is a paid consultant for Regeneron Pharmaceuticals, has stock options in Lasergen, Inc., and is a co-inventor on multiple US and European patents related to molecular diagnostics for inherited neuropathies, eye diseases and bacterial genomic fingerprinting. The Department of Molecular and Human Genetics at Baylor College of Medicine derives revenue from the chromosomal microarray analysis (CMA) and clinical exome sequencing offered in the Baylor Miraca Genetics Laboratory (BMGL). R.A.G. is an advisor to GE Healthcare/Clarient, Inc. and the Allen Institute for Brain Science and is interim CSO of the BMGL. The other authors have no disclosures relevant to the manuscript.

Additional information

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Integrated supplementary information

Supplementary Figure 1 Renal pathology of patients A.III.6 and D.III.5.

(a,b) Renal biopsy H&E staining shows immune complex crescentic glomerulonephritis with fibrocellular crescents (b) and glomeruli with mild mesangial expansion and hypercellularity. (c,d) IgG+ and IgA+ mesangial foci confirm antibody deposits. (e) The electron micrograph shows rare electron-dense deposits. (f) Kidney explant H&E staining shows end-stage renal disease with diffuse global sclerosis and interstitial chronic inflammation.

Supplementary Figure 2 Sanger sequencing chromatograms for COPA in family members.

Sanger sequencing reactions were performed on genomic DNA covering the area identified by whole-exome sequencing with a 20-bp snapshot around the point mutation shown. A black asterisk indicates the position of the mutation. A red asterisk indicates the mutation. Patient identifiers are shown above the chromatograms.

Supplementary Figure 3 COPA expression in patient cells is equivalent to that in controls.

(a,b) COPA protein expression in the B-lymphoblastoid cell lines (BLCLs) of five controls (CO3 is D.III.6, CO4 is C.III.10, CO5 is D.III.4), three patients from family C (PA1 is C.IV.15, PA2 is C.V.1, PA3 is C.IV.2), one patient from family B (PA4 is B.III.3), two patients from family A (PA5 is A.II.5, PA6 is A.III.6) and two patients from family D (PA7 is D.III.5, PA8 is D.I.2) was analyzed. (a) Western blot analysis of COPA and GAPDH is shown. Numbers indicate the expression of COPA relative to GAPDH expression. (b) Unpaired t tests with Welch’s correction were used for statistical evaluation of protein expression in affected patients in comparison to controls. ns, not significant (P > 0.05). (c) COPA mRNA expression in BLCLs analyzed via qPCR is shown. P values are not significant (>0.05) for all comparisons. (d) Immunofluorescent staining of BLCLs. DAPI staining is shown in blue, and COPA staining is shown in red. Colocalization (yellow) of COPA (red) with the ER-Golgi intermediate complex (ERGIC)-53 (green) in single cells is shown. Staining was visualized using a Zeiss Apotome wide-field microscope.

Supplementary Figure 4 Binding of mutant K230N COPA to dilysine motifs is impaired.

(a) Binding of mutant COPA to a dilysine motif was examined by taking either Flag-tagged wild-type or mutant K230N COPA and incubating it with Wbp1p peptide-coupled agarose beads. The protein-bead complexes were analyzed by western blot (WB) using an antibody to Flag. Numbers indicate the relative expression as a percent of wild-type COPA levels. Statistical analysis of three independent experiments is shown. *P < 0.05. (b) Binding of mutant COPA to a dilysine motif was also assessed within T-REx-293 cells stably expressing Flag-tagged wild-type or mutant COPA by transiently transfecting cells with an expression construct for GFP-CD8-KKTN. Cell lysates were precipitated with antibody to CD8, and immunoprecipitates were assayed for Flag-COPA expression and GFP-CD8 enrichment. Numbers indicate relative expression as a percent of wild-type COPA or GFP-CD8 levels in cells expressing wild-type COPA. Statistical analysis of five independent experiments is shown. **P < 0.01.

Supplementary Figure 5 Patient lungs or cells demonstrate an increase in the ER stress markers BiP, ATF4 and CHOP.

(a) Immunohistochemistry staining for the ER stress component BiP in lung biopsy samples from an additional control and an additional E241K patient is shown. Hematoxylin was used for a nuclear counterstain. Scale bars, 40 µm. Enlarged insets emphasize BiP staining in lung epithelial cells. (b) BiP staining in alveolar macrophages is shown (arrows, box). Scale bars, 40 µm. (c) qPCR analysis of BiP expression in untreated (white bars; –) and treated (gray and black bars; +) BLCLs after stimulation with 100 mM thapsigargin (TG). The left graph indicates the results from four controls (CO1 (n = 12), CO2 (n = 3), CO3 (n = 4), CO4 (n = 9); CO3 is a related control from family D, D.III.6, and CO4 is from family C, C.III.10). All results were normalized to the values for untreated control 1. Data shown are from two patients from family D (PA7, D.III.5 (n = 6), PA8, D.I.2 (n = 6)). One-way ANOVA followed by Dunnett’s multiple-comparison test was used to compare thapsigargin-treated experimental groups with thapsigargin-treated control 1 as a reference. Means and s.e.m. of one experiment representative of three independent experiments are shown. *P < 0.05, **P < 0.01. (d) Graphs demonstrating BiP mRNA expression 48 h after transfection as assessed by qPCR. HEK293 cells were transiently transfected with wild-type (WT) COPA or mutant E241K or K230N COPA expression constructs. Cells transfected with mutant COPA showed significantly increased BiP levels when normalized to levels in cells transfected expressing wild-type COPA. Means and s.e.m. are shown for each column. One-way ANOVA followed by Dunnett’s multiple-comparison test was used to compare experimental groups against HEK293 cells transfected with wild type as the control column. Results shown are from one experiment (n = 3) representative of 3 independent experiments. ***P < 0.001. (e,f) HEK293 cells were transiently transfected with either WT or mutant Flag-tagged COPA. Cells were lysed and analyzed by western blot for the expression of Flag-COPA and GAPDH 48 h later. (g) Induction of ER stress measured by ATF4 and CHOP expression 48 h after COPA knockdown. Means and s.e.m. of one experiment (n = 3) representative of 3 independent experiments are shown. Statistical comparisons were made using Welch’s unpaired t test. *P < 0.05, ***P < 0.001. (h) Graphs indicating ATF4 (left) and CHOP (right) expression 48 h after transfection as assessed by qPCR. HEK293 cells were transfected with wild-type (WT) or mutant E241K COPA constructs. Means and s.e.m. of one experiment (n = 4) representative of 3 independent experiments are shown. Statistical comparisons were made using Welch’s unpaired t test. *P < 0.05, **P < 0.01.

Supplementary Figure 6 Mutant COPA increases autophagosomes.

(a,b) BLCLs from patient PA4 (B.III.3) and a control were stained with antibody to CD107a (green) or LC3B (red) and imaged under super-resolution using time-gated STED microscopy. White lines indicate the edges of individual cells. (c,d) The areas of the resulting structures were graphed and compared statistically using the Mann-Whitney U test and were found to be significantly increased in patient-derived cells. ***P < 0.001. (e,f) As an overall measure of cellular autophagosome content, the amount of both LC3 and CD107a was assessed by mean fluorescence intensity (MFI) measurement and was increased in COPA-mutant BLCLs from patients (LC3B MFI 41 ± 3.6 (n = 24) versus 32.9 ± 7.3 (n = 8), ***P < 0.001; CD107a MFI 9.8 ± 0.9 (n = 8) versus 13.5 ± 5.2 (n = 24), **P<0.01).

Supplementary Figure 7 Overexpression of mutant COPA increases autophagosome size and number.

HEK293T cells stably expressing GFP-LC3B as an indicator of autophagosomes and transfected with WT, R233H or D243G COPA construct and GFP puncta were measured for both autophagosome number and volume using confocal imaging as an indication of autophagosome formation. (a,b) Representative pictures are shown for WT and R233H COPA. Blue lines indicate the edges of individual cells. (c) In quantitative analyses across repeated experiments, the expression of D243G and R233H mutant COPA resulted in a statistically significant increase in autophagosome size (WT, 138 ± 38 (n = 17); D243G, 17,411 ± 6,658 (n = 9); R233H, 16,467 ± 6,797 (n = 14)) and (d) autophagosome number (WT, 16.2 ± 3.2; D243G, 936 ± 372; R233H, 582 ± 188). The Mann-Whitney U test was used for statistical analysis. ***P < 0.001.

Supplementary Figure 8 Autophagy catabolism is impaired in COPA-mutant patient-derived cells.

(a) Representative patient or control BLCLs were either untreated (black) or were stimulated with the autophagy-inducing drug Torin (gray) or a combination of Torin and baflomycin A (white bar) to pause autophagy by preventing fusion with the lysosome for 4 h. Cells were lysed and evaluated by western blot analysis for p62 levels (representative example provided). The levels of p62 were quantified using ImageJ software, normalized to GAPDH levels and are graphed above the western blot. (b) Student’s unpaired t test was used for statistical analysis of untreated control (n = 4; black bar) and patient (n = 4; white bar) samples. The graph shows means and s.d. from the pooled data of three independent experiments. *P < 0.05.

Supplementary Figure 9 Immune cell cytokine expression in patient BLCLs.

Cytokine expression was measured in BLCLs from CO1, CO4 (C.III.10), PA2 (C.V.1) and PA3 (C.IV.2) either untreated (white bars; –) or treated (gray and black bars; +) with TG. Samples were analyzed via qPCR for the mRNA levels of IL10, IFNA2 and TGFB. Shown are mRNA levels normalized against the average value for healthy control 1 (CO1) in the absence of stimulation. Error bars indicate the standard error for triplicates in the assay. Results are representative of three independent experiments. Nothing indicated P > 0.05; *P < 0.05, ***P < 0.001.

Supplementary Figure 10 IFN-γ+IL-17+CD4+ T cells in COPA-mutant patients versus controls.

CD4+ T cells from three COPA-mutant patients and three age-matched controls were analyzed for the intracellular cytokines IL-17A and IFN-γ after stimulation with PMA and ionomycin. FACS plots gated on living CD3+CD4+ T cells are shown.

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Watkin, L., Jessen, B., Wiszniewski, W. et al. COPA mutations impair ER-Golgi transport and cause hereditary autoimmune-mediated lung disease and arthritis. Nat Genet 47, 654–660 (2015).

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