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The E3 ubiquitin ligase SPOP controls resolution of systemic inflammation by triggering MYD88 degradation

Nature Immunology volume 20, pages 1196–1207 (2019)Cite this article

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Abstract

The response to systemic infection and injury requires the rapid adaptation of hematopoietic stem cells (HSCs), which proliferate and divert their differentiation toward the myeloid lineage. Significant interest has emerged in understanding the signals that trigger the emergency hematopoietic program. However, the mechanisms that halt this response of HSCs, which is critical to restore homeostasis, remain unknown. Here we reveal that the E3 ubiquitin ligase Speckle-type BTB–POZ protein (SPOP) restrains the inflammatory activation of HSCs. In the absence of Spop, systemic inflammation proceeded in an unresolved manner, and the sustained response in the HSCs resulted in a lethal phenotype reminiscent of hyper-inflammatory syndrome or sepsis. Our proteomic studies decipher that SPOP restricted inflammation by ubiquitinating the innate signal transducer myeloid differentiation primary response protein 88 (MYD88). These findings unearth an HSC-intrinsic post-translational mechanism that is essential for reestablishing homeostasis after emergency hematopoiesis.

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Fig. 1: Hematopoietic-specific loss of Spop promotes acute and lethal neutrophilia.
Fig. 2: Inflammation triggers dysregulated host response and fatal neutrophilia in Spop-deficient animals.
Fig. 3: Loss of Spop leads to an emergency hematopoietic transcriptional program in HSPCs.
Fig. 4: SPOP directly interacts, ubiquitylates and degrades MYD88.
Fig. 5: Loss of MyD88 protein rescues Spop-induced lethal neutrophilia.
Fig. 6: IL-1-Myd88 signaling promotes neutrophilia in Spop-deficient animals.

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Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request. In addition, raw data generated in this study (bulk RNA-seq, scRNA-seq, ATAC-seq) are available at the GEO database under the accession number GSE112542. Raw data for the proteomics Ms/Ms analysis are available at https://www.ebi.ac.uk/pride/archive/projects/PXD009469.

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Acknowledgements

We would like to thank all members of the Aifantis laboratory for discussions throughout the duration of this project, specifically E. Wang and B. Aranda for expert advice in CRISPR/Cas9 technology and K. Hockemeyer for expert advice in preparing the manuscript; A. Heguy and the NYU Genome Technology Center (supported in part by National Institutes of Health, National Cancer Institute grant P30CA016087-30) for expertise with sequencing experiments; the NYU Histology Core (5P30CA16087-31) for assistance; C. Loomis and L. Chiriboga for immunohistochemistry experiments; and S. Naik for her intellectual input. This work used computing resources at the High-Performance Computing Facility at the NYU Medical Center. I.A. is supported by the National Institutes of Health (grant nos. R01CA133379, 5R01CA173636, RO1CA216421, RO1CA133379), the Leukemia and Lymphoma Society (TRP Program) and the NYSTEM program of the New York State Health Department (NYSTEM-N11G-255). L.B. is supported in part by grants (nos. R00-CA166181-04 and R01-CA207513-01) from the National Cancer Institute and Gilead Sciences Research Scholars Program in Hematology/Oncology. I.A. dedicates this work to the memory of his mentor H. von Boehmer.

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Author notes

  1. These authors contributed equally: Maria Guillamot, Dahmane Ouazia.

  2. These authors jointly supervised this work: Luca Busino and Iannis Aifantis.

Authors and Affiliations

  1. Department of Pathology, NYU School of Medicine, New York, NY, USA

    Maria Guillamot, Igor Dolgalev, Nikos Kourtis, Yuling Dai, Kate Corrigan, Luna Zea-Redondo, Anastasia N. Tikhonova, Marina Malumbres, Yixiao Gong, Aristotelis Tsirigos, Christopher Park & Iannis Aifantis

  2. Laura and Isaac Perlmutter Cancer Center, NYU School of Medicine, New York, NY, USA

    Maria Guillamot, Igor Dolgalev, Nikos Kourtis, Yuling Dai, Kate Corrigan, Luna Zea-Redondo, Anastasia N. Tikhonova, Marina Malumbres, Yixiao Gong, Aristotelis Tsirigos, Christopher Park & Iannis Aifantis

  3. Department of Cancer Biology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA

    Dahmane Ouazia & Luca Busino

  4. Applied Bioinformatics Laboratories, Office of Science & Research, NYU School of Medicine, New York, NY, USA

    Igor Dolgalev & Aristotelis Tsirigos

  5. Department of Microbiology, NYU School of Medicine, New York, NY, USA

    Stephen T. Yeung & Kamal M. Khanna

  6. The Stowers Institute of Medical Research, Kansas City, MO, USA

    Anita Saraf, Laurence Florens & Michael P. Washburn

  7. Department of Pathology and Laboratory Medicine, The University of Kansas Medical Center, Kansas City, KS, USA

    Michael P. Washburn

  8. Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA

    Christopher Barbieri

  9. Department of Urology, Weill Cornell Medicine, New York, NY, USA

    Christopher Barbieri

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  1. Maria Guillamot
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Contributions

M.G., I.A. and L.B. conceptualized and designed the study. M.G., I.A. and L.B. prepared the manuscript. M.G. performed, analyzed and interpreted the majority of the experiments describing the mouse modeling. D.O. and L.B. designed, performed and interpreted the majority of the proteomics experiments. I.D., Y.G., L.Z.-R. and A.T. performed all of the computational analysis. N.K. generated mouse strains. Y.D., K.C. and M.M. provided technical assistance with animal models. A.S., L.F. and M.P.W. performed the mass spectrometry. S.T.Y. and K.M.K. performed and interpreted the tissue immunofluorescence and the influenza experiment. C.P. analyzed the mouse pathology. C.B. provided the Spop antibody and shared experimental protocols. A.N.T., K.M.K., C.P. and C.B. provided intellectual input.

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Correspondence to Maria Guillamot, Luca Busino or Iannis Aifantis.

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Supplementary Figure 1 Spop is highly expressed in LT-HSC.

a, Top 15 highest expressed ubiquitin ligase genes in LT-HSC. Heatmap represents the normalized counts relative to 10M reads per gene in the indicated populations. The data was collected from Lara-Astiaso., 2016 29 b, Spop expression profile on different hematopoietic cells from the same dataset. c, Immunoblot showing Spop protein levels in the indicated sorted cells. Data are representative from two independent experiments d, Schematic diagram of Spop conditional allele. e, Immunoblot analysis of Spop protein levels of total bone marrow cells from wild-type (Spop+/+MxCre) and KO (SpopΔ/ΔMxCre) mice following a single Poly(I:C) injection. Data are representative of three independent experiments. f, Percentage of mouse weight-change on d15 after Poly (I:C) injection (Spop+/+MxCre: n=9; SpopΔ/ΔMxCre: n=10). Data represent minimum, first quartile, mean, third quartile and maximum. Statistical analysis: unpaired t-test, two-tailed). g, Kaplan-Meier analysis of survival of Spop+/+MxCre and SpopΔ/ΔMxCre hematopoietic chimeras after donor hematopoietic reconstitution and one injection of Poly(I:C) (n=5 wild-type, n=6 Spop KO. Statistical analysis: Mantel-Cox test). h, Hematoxylin & Eosin stained sections of spleen, lung and liver of wild-type (Spop+/+MxCre) and KO (SpopΔ/ΔMxCre) hematopoietic chimeric mice on d21 post Poly (I:C) injection. Scale bars indicate 100 um (Spleen and liver), 1000 um (lung) and 10 um magnifications. Data are representative from 3 independent experiments(pI:C: Poly (I:C). LT-HSC: Lin-c-Kit+Sca-1+Flk2-CD34-. ST-HSC: Lin-c-Kit+Sca-1+Flk2-CD34+. MPP: Lin-c-Kit+Sca-1+Flk2+CD34+. CMP: Lin- c-Kit+ Sca-1+ FcgRIIlowCD34+. GMP: Lin-c-Kit+Sca-1+FcgRIIhighCD34+. MEP: Lin-c-Kit+Sca-1+FcgRII-CD34-. CLPs: Lin-Flk2+Il7R+).

Source data

Supplementary Figure 2 Gating strategy.

Representative image of the Flow Cytometry gating strategy to identify B-, T- and myeloid cells in peripheral blood and bone marrow of the mice and HSC and progenitors in the bone marrow of the mice.

Supplementary Figure 3 SpopΔMxCre neutrophils display upregulation of inflammatory response gene programs.

a, GSEA enrichment plots of differentially expressed genes in Spop KO SpopΔ/ΔMxCre neutrophils (n=3 mice) compare to control Spop+/+MxCre (n=2 mice). Statistical significance determined by GSEA Nominal p-value b, Heatmap showing the relative expression of selected Toll-like and NF-kB signaling genes identified to be upregulated in Spop KO compare to controls. c, Heatmap showing the relative expression of selected interferon response genes identified to be upregulated in Spop KO compare to controls. d, Ingenuity upstream analysis of differentially expressed genes in SpopΔMxCre neutrophils compare to control. e, ENRICHR transcription factor analysis of the identified differential upregulated genes in Spop KO neutrophils compare to control. (NES: normalized enrichment score).

Supplementary Figure 4 Granulocytic specific Spop deletion does not promote neutrophilia.

a, Immunoblot analysis of Spop protein levels of bone marrow cKit+ cells of wild type, SpopΔ/ΔMxCre and SpopΔ/ΔCreERT2 mice after Poly(I:C) or Tamoxifen treatment. b, Percentage of myeloid (CD11b+Ly6G+) cells in the peripheral blood of (CD11b+Ly6G+) cells in the peripheral blood of Spop KO and control hematopoietic chimeras on the indicated times after Tamoxifen treatment. Data represent mean±s.d. and dots represent different mice. Statistical analysis: unpaired t-test (two-tailed) c, Representative flow cytometry analysis plots of the proportion of myeloid (CD11b+Ly6G+) cells in the peripheral blood of Spop KO and control hematopoietic chimeras on d15 after a sub-lethal LPS injection. d, Representative flow cytometry analysis plots of the proportion of myeloid (CD11b+Ly6G+) cells in the peripheral blood of Spop KO (and control hematopoietic chimeric mice on the indicated days after intranasal influenza inoculation. e, Spop mRNA relative expression levels in the indicated sorted bone marrow cells. Data represent mean±s.d. (n=3 mice per genotype). The results were first standardized for Gapdh expression levels and then each SpopΔ/Δ sample was expressed as a fraction of the expression detected in the correlated control population from the control littermate. g, Percentage of myeloid (CD11b+Ly6G+) cells in the peripheral blood of the indicated mice on d10 following pIpC-challenge (n=5 per genotype). Data represent mean±s.d. and dots represent different mice. Statistical analysis: unpaired t-test (two-tailed). a-f, Data representative of 3 independent experiments.

Source data

Supplementary Figure 5 Conditional deletion of Spop leads to HSPC expansion and myeloid skewing.

a, Representative flow cytometry analysis plot of Lineage negative bone marrow cells at the indicated days after Poly (I:C) injection. b, Representative flow cytometry analysis plots of the proportion of HSPC populations, including LSK (Lineage-Sca-1+Kit+), LK (Lineage-Sca-1-Kit+), HSC (LSK CD135-, CD48- CD150+), MPP2 (LSK CD135- CD48+ CD150+), MPP3 (LSK CD135- CD48+ CD150-), CMP (LK FcyRlow CD34+), GMP (LK FcyRhigh CD34+), MEP (LK FcyRlo CD34+). c, Percentage of LSK and LK populations in the total bone marrow, percentage of HSC, MPP2, MPP3 and MPP4 in LSKs and percentage of CMP, GMP and MEP in LKs (n=4 mice per genotype. Data represent mean±s.d and dots represent different mice. Statistical analysis: unpaired t-Student, two-tailed). a-d Data are representative from 3 independent experiment. d, Heatmap showing the relative expression of the selected GSEA-analyzed leading edge genes in SpopΔ/ΔMxCre and control sorted LSKs (n=2 mice per genotype) together with control HSC, MPP, CMP, GMP and GN (Granulocyte) wild-type populations from Lara-Astiaso et al., 2016. e, GSEA enrichment plots for HSC, MPP3, MPP4 and granulocytic and macrophage precursor signatures47 in SpopΔ/ΔMxCre and control sorted LSKs (n=2 per genotype). Statistical analysis: Normalized Enrichment Score (NES) and GSEA Nominal p-value. f, Cytokine levels in the serum of the indicated hematopoietic chimeras following one pI:C injection (n=4 per genotype and condition). g, Cytokine levels in the bone marrow fluids of the indicated hematopoietic chimeras following one pI:C injection. f,g Data represent mean±s.d and dots represent different mice. Data are representative of two independent experiments.(h=hours, d=days).

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Supplementary Figure 6 Defined gene signature per HSPC clusters.

a,Heatmap showing the expression levels of the 50 most significant markers per cluster, displaying 100 randomly-selected cells of wild-type (Spop+/+MxCre) and Spop KO (SpopΔ/ΔMxCre) LSK. * indicate the upregulation of the C5 specific signature in the cells of other clusters. b, Normalized expression levels of selected population-specific-markers across clusters (C1=4714, C2=2461, C3=1649, C4=1689, C5=1328, C6=1030, C7=196 cells) Data represent mean±s.d. c, Spectral tSNE plot of Spop wild-type (8184) and KO (4920) LSK cells showing the Enrichment Score for Emergency Megakaryocyte gene signature. d, Percentage of Megakarycyte progenitors (Lineage-, Sca-1-, Kit-, CD150+, CD41+) from total progenitor (Lineage-cKit+Sca-1-) cells from the indicated mice (n=4 per genotype and time-point). e, Spectral tSNE plot of Spop wild-type (8184) and KO (4920) LSK cells showing the Enrichment Score for Emergency Granulopoietic gene signature. f, Cell differentiation trajectory using PHATE visualization of wild-type and Spop KO cells, color code for HSC (n=1099), MPP2 (Megakrycyte/Erythroid biased, n=5111), MPP3 (myeloid biased, n=2414) or MPP4 (lymphoid biased, n=3737) gene signatures. g, Spectral tSNE plot of cell cycling color-coded cells. h, Frequency of cells expressing cell cycle genes in SpopΔ/ΔMxCre and control LSKs. i, Percentage of SpopΔ/ΔMxCre and control cell cycling (EdU+) LSKs on d10 post a Poly (I:C) injection. Data represent mean±s.d. n=3. Statistical analysis: unpaired t-student, two-tailed. d,i, Data are representative from 2 independent experiments.

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Supplementary Figure 7 SPOP interacts with MYD88 in a phosphorylation independent manner to inhibit IRAK4 signalling.

a, Left, overall view of the SPOP-BTB dimer (pdb access code = 3HTM (Zhuang et al., 2009)) with protomers in green and cyan. Right, overall view of dimer interface rotated 90° in x. The L193 residue on each protomer is shown in red. The structural images were obtained using UCSF chimera software. b, Immunoblot analysis of whole cell lysates from K562 cells stably expressing HA-tagged SPOP(WT) and SPOP(L193P). Cells were treated with cycloheximide (CHX) for the indicated times. EV, empty vector. c, Top, immunoblot analysis of immunoprecipitated WT and truncated forms of FLAG-tagged MYD88 transiently expressed in HEK 293T cells. EV, empty vector. Bottom, diagram showing MYD88 truncations as well as the differential binding to SPOP. d, Immunoblot analysis of immunoprecipitated FLAG-tagged MYD88 and of FLAG-tagged CDC25A, both transiently expressed in HEK293T cells. Equal volumes of the immunopurified protein were both treated with the λ-phosphatase reaction buffer with or without the enzyme. EV, empty vector. e, Immunoblot analysis of immunoprecipitated FLAG-tagged MYD88(WT) and phosphomimetic mutants (S136D, S137D, S136D/S137D) transiently expressed in HEK 293T cells. EV, empty vector. f, In vivo ubiquitylation of immunoprecipitated FLAG-tagged MYD88 upon co-expresison with HA-tagged SPOP and increasing amounts of HA-tagged IRAK4 in HEK293T cells. A low (l.e.) and high exposure (h.e.) are shown. Protein purification was performed in denaturing conditions. g, Immunoblot analysis of immunoprecipitated FLAG-tagged MYD88 co-expressed with HA-tagged SPOP and either HA-tagged IRAK4(WT) or kinase dead (KD) mutant in HEK293T cells. Protein purification was performed in denaturing conditions. h, Immunoblot analysis of whole cell lysates of HPC-7 cells Spop-WT and Spop-KO. Cells were treated with 10 µg/ml lipopolysaccharides (LPS) for the indicated times. A low (l.e.) and high exposure (h.e.) are shown. a-h Data are representative from 3 independent experiments.

Supplementary Figure 8 Spop loss of function reshapes the open chromatin landscape of the HSPCs.

a, Venn-diagram showing the ATAC-seq signals common and unique for wild-type (Spop+/+MxCre n=2 mice) and SpopΔ/ΔMxCre (n=2 mice) LSKs (Lineage-cKit+Sca-1+ bone marrow cells), sorted on d10 following a Poly (I:C) injection (FDR<0.05). b, GREAT Gene Ontology Biological Function analysis of the 25570 SpopΔMxCre differential open chromatin elements. Statistical analysis: GREAT enrichment binomial test from GREAT c, Genome Browser plots showing the normalized ATAC-seq profiles at the promoter and distal elements of the indicated genes for wild-type (blue) and SpopΔMxCre (green) samples. Data are representative from two mice per genotype. d, Ranking of the most enriched transcription factor (TF) motif within SpopΔMxCre vs wild-type differential open chromatin elements (cumulative binomial distribution P<10-10 .Green=TF motif enriched in the Spop(Δ/Δ)MxCre differential open chromatin elements. Blue=TF motif enriched in the Spop+/+MxCre differential open chromatin elements. Black= TF motif enriched in the SpopΔ/ΔMxCre Spop+/+MxCre differential open chromatin elements).Statistical analysis: HOMER enrichment binomial test e, ATAC-seq Footprint visualization for the indicated TF. Aggregated plot of the Tn5 (transposase) insertions counts per nucleotide.

Supplementary Figure 9 Myd88 deficiency restores the steady-state transcriptional program in Spop KO LSKs.

a, Representative flow cytometry analysis plots of the proportion of HSPC in the lineage- bone marrow from hematopoietic chimeric mice following Poly(I:C) injection including: control (Spop+/+MxCre MyD88+/+), Spop KO (SpopΔ/ΔMxCre MyD88+/+), Myd88 KO (Spop+/+MxCre MyD88-/-) and dKO (SpopΔ/ΔMxCre MyD88-/-. Data are representative from 2 independent experiments. b, Spop mRNA expression levels of LSKs on d10 post Poly (I:C) injection (n=2). c, Immunoblot analysis of HSPC cKit+ bone marrow cells of wild-type (Spop+/+MxCre MyD88+/+), Spop KO (SpopΔ/ΔMxCre MyD88+/+) and dKO (Spop+/+MxCre MyD88-/-) mice. Data are representative from 3 independent experiments. d, Heatmap showing the expression levels of the 50 most significant markers per cluster, displaying 100 randomly-selected cells. e, Percentage of Cycling cells per genotype. f, Percentage of myeloid Cd11b+Ly6G+ cells in peripheral blood of SpopΔ/ΔMxCre mice on day 20 following pIpC challenge and antibody treatment. Bar plots represent mean+-s.d, n=4 mice per condition. g, Representative Flow Cytometry Analysis Plots of the proportion of Myeloid (Cd11b+, Ly6G+) cells in the peripheral blood of the pIpC-stimulated mice.

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Supplementary information

Supplementary Information

Supplementary Figures 1–9 and unmodified blots

Reporting Summary

Supplementary Table 1

Ubiquitinome transcriptional profile in HSPCs.

Supplementary Table 2

Differentially expressed genes in Spop KO LSKs compared with controls.

Supplementary Table 3

Population-specific gene expression: mean expression gene per cluster.

Supplementary Table 4

Cluster-specific differentially expressed genes.

Supplementary Table 5

Spop pull-down mass spectrometry.

Supplementary Table 6

Differential open chromatin sites in Spop KO and control LSK 10 days after Poly(I:C).

Supplementary Table 7

Mean gene expression per cluster and genotype.

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Guillamot, M., Ouazia, D., Dolgalev, I. et al. The E3 ubiquitin ligase SPOP controls resolution of systemic inflammation by triggering MYD88 degradation. Nat Immunol 20, 1196–1207 (2019). https://doi.org/10.1038/s41590-019-0454-6

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