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Atypical chemokine receptor 1 on nucleated erythroid cells regulates hematopoiesis

Nature Immunology volume 18, pages 753–761 (2017)Cite this article

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Abstract

Healthy individuals of African ancestry have neutropenia that has been linked with the variant rs2814778(G) of the gene encoding atypical chemokine receptor 1 (ACKR1). This polymorphism selectively abolishes the expression of ACKR1 in erythroid cells, causing a Duffy-negative phenotype. Here we describe an unexpected fundamental role for ACKR1 in hematopoiesis and provide the mechanism that links its absence with neutropenia. Nucleated erythroid cells had high expression of ACKR1, which facilitated their direct contact with hematopoietic stem cells. The absence of erythroid ACKR1 altered mouse hematopoiesis including stem and progenitor cells, which ultimately gave rise to phenotypically distinct neutrophils that readily left the circulation, causing neutropenia. Individuals with a Duffy-negative phenotype developed a distinct profile of neutrophil effector molecules that closely reflected the one observed in the ACKR1-deficient mice. Thus, alternative physiological patterns of hematopoiesis and bone marrow cell outputs depend on the expression of ACKR1 in the erythroid lineage, findings with major implications for the selection advantages that have resulted in the paramount fixation of the ACKR1 rs2814778(G) polymorphism in Africa.

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Figure 1: ACKR1 is expressed in the bone marrow by ECs and NECs.
Figure 2: ACKR1 deficiency alters HSPC populations.
Figure 3: ACKR1 deficiency changes HSPC transcriptomes.
Figure 4: ACKR1 on erythroid cells but not on ECs regulates HSPCs.
Figure 5: ACKR1 on BM erythroid cells regulates HSPCs.
Figure 6: ACKR1 on NECs promotes direct cell interactions with HSCs.
Figure 7: Lack of ACKR1 affects neutrophil phenotype.
Figure 8: Lack of ACKR1 on NECs together with its expression in ECs causes neutropenia.

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Acknowledgements

J.D. and I.N.-B. are joint first authors, and A.T., M.C.-A., M.B., S.L.E., E.H. and K.N. contributed equally to this work. We thank M. Ulvmar, E. Ross, G. Volpe, P. Cauchy and A. Cunningham for their advice, R. Bird and S. Kissane for their assistance with cell sorting and microarray experiments, respectively, H. Vyas and P. Kelay for help with laboratory work and D. Santovito for help with statistical analysis. We thank M. Mack (University of Regensburg) and M. Uchikawa (Japanese Red Cross) for their generous gifts of antibodies specific for mouse CCR2 and human ACKR1 antibody, respectively, and J. Allen (University of Manchester) and M. Bader (Max Delbruck Center) for critical reading of the manuscript and their suggestions. A.R. is grateful to M. Tsaloumas, A. Denniston and N. Glover for the vision. Supported by Medical Research Council grant G0802838 (A.R.), a Senior Visiting Fellowship of the Center for Advanced Studies LMU, Munich (A.R.), Wellcome Trust grant WT090962MA (I.N.-B., A.R. and P.M.), Deutsche Zentrum Für Herz-Kreislauf-Forschung 86X2600229 (J.D. and C.W.), a Marie Curie Actions Intra-European Fellowship ATHEROCHEMOKINE (J.D.), Deutsche Forschungsgemeinschaft grants SFB1123/A1 (C.W.), SFB1123/Z1 (M.B. and R.T.A.M.) and INST 409/150-1 FUG (C.W. and R.T.A.M.), European Research Council grant ERC AdG °692511 (C.W.), Swiss National Science Foundation Sinergia grant CRSII3_160719 (E.H. and A.R.), a TransCard PhD fellowship in Translational Cardiovascular and Metabolic Medicine of the Helmholtz International Research School (K.N.), an ERA-EDTA short-term fellowship (K.A.) and Ministry of Economy, Industry and Competitiveness (MINECO) grant AF2015-65607-R (A.H.). The CNIC is supported by MINECO and the Pro-CNIC Foundation and is a Severo Ochoa Center of Excellence (MINECO award).

Author information

Author notes

  1. Antal Rot

    Present address: William Harvey Research Institute, Queen Mary University of London, London, UK

  2. Johan Duchene and Igor Novitzky-Basso: These authors contributed equally to this work.

Authors and Affiliations

  1. Institute for Cardiovascular Prevention, Ludwig-Maximilians University (LMU), Munich, Germany

    Johan Duchene, Mariaelvy Bianchini, Katrin Nitz, Remco T A Megens, Andres Hidalgo, Christian Weber & Antal Rot

  2. Blood and Marrow Transplant Unit, Queen Elizabeth University Hospital, Glasgow, UK

    Igor Novitzky-Basso

  3. Department of Microbiology and Immunobiology and Center for Immune Imaging, Harvard Medical School, Boston, Massachusetts, USA

    Aude Thiriot & Ulrich H von Andrian

  4. Ragon Institute, Cambridge, Massachusetts, USA

    Aude Thiriot & Ulrich H von Andrian

  5. Fundación Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain

    Maria Casanova-Acebes & Andres Hidalgo

  6. Department of Biology, Centre for Immunology and Infection, University of York, Heslington, UK

    S Leah Etheridge, Elin Hub, Katharina Artinger & Antal Rot

  7. Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany

    Katrin Nitz

  8. Clinical Division of Nephrology, Department of Internal Medicine, Medical University of Graz, Graz, Austria

    Katharina Artinger & Kathrin Eller

  9. Institute of Immunology and Immunotherapy, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK

    Jorge Caamaño & Paul Moss

  10. Institute of Laboratory Animal Science, University of Veterinary Medicine Vienna, Vienna, Austria

    Thomas Rülicke

  11. Cardiovascular Research Institute Maastricht, University of Maastricht, Maastricht, The Netherlands

    Remco T A Megens & Christian Weber

  12. Center for Advanced Studies, Ludwig-Maximilians University, Munich, Germany

    Antal Rot

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  1. Johan Duchene
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Contributions

A.R. conceived the study; J.D., I.N.-B., R.T.A.M., U.H.v.A., A.H., C.W. and A.R. designed the experiments; J.D., I.N.-B., A.T., M.C.-A., M.B., S.L.E., E.H., K.N., K.A. and T.R. performed the experiments and evaluated the data; J.D., I.N.-B., K.E., J.C., P.M., R.T.A.M., U.H.v.A., A.H., C.W. and A.R. interpreted the data; and A.R., J.D. and C.W. wrote the manuscript.

Corresponding authors

Correspondence to Christian Weber or Antal Rot.

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Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Validation of the monoclonal antibody to mouse ACKR1 and expression of ACKR1 by BM hematopoietic cells.

(a to d) Comparison of immunostaining of BM cells by anti-mouse ACKR1 antibodies: new validated monoclonal (a and c, Thiriot A et al Ref. 29) and non-validated polyclonal (b and d, FAB6695P from R&D Systems used by Hur et al., Ref. 43, to report ACKR1 expression in BM macrophages). (a and b) ACKR1 immunoreactivity in nucleated erythroid cells (NECs; CD71+Ter119+), neutrophils (Neutro; CD11b+CD115–F4/80–Ly6G+), monocytes (Mono; CD11b+ CD115+F4/80–Ly6G–) and macrophages (Macro; CD11b+CD115–F4/80+Ly6G–) in BM of wild-type (WT) mice. Left, representative flow cytometry histogram plots; right, quantitative analysis. n=3. (c and d) ACKR1 immunoreactivity and negative control staining (NC) in NECs and macrophages (Macro) in BM of WT (blue) and ACKR1-deficient (KO, red) mice. Left, representative flow cytometry histogram plots; right, quantitative analysis. n=3. BM immunostaining using validated monoclonal antibody (a and c) show that ACKR1 is expressed in the BM by erythroid cells only but not by macrophages. Polyclonal non-validated antibody failed to immunoreact with NECs but at high concentration stained BM macrophages, (b) however non-specifically as (d) to the same extent in WT and KO mice. All data are Mean±SEM. One-Way ANOVA (a and b). Two-Way ANOVA (c and d). *P<0.001. (e) Relative expression of ACKR1 in hematopoietic and stromal populations as determined by microarray analysis based on the data in the BM cells transcriptome database (https://gexc.riken.jp/models). Microarray dataset of adult definitive murine erythroblasts were retrieved from ArrayExpress (https://www.ebi.ac.uk/arrayexpress; E-MTAB-1035) and implemented in Gene Expression Commons database (link to this model https://gexc.riken.jp/models/1649). Proerythroblasts (ProE), early normoblasts (BasoE), late normoblasts (PolyE), reticulocytes (Ret) and Endothelial cells (BM EC) in BM express ACKR1 whereas BM macrophages (BM Macro) do not.

Supplementary Figure 2 ACKR1 is expressed by endothelial cells and nucleated erythroid cells in the BM but not by other hematopoietic cells.

(a) Immunofluorescence micrographs of wild-type (WT) and ACKR1-deficient (KO) BM stained with anti-ACKR1 (red), anti-CD31 (endothelial cells, blue), anti-Ter119 (erythroid cells, yellow) antibodies and DAPI (nuclei, turquoise). (b) ACKR1 expression (MFI) on HSPCs, megakaryocyte progenitors (MkP) and leukocytes (Leu) as compared to the subpopulations of erythroid cells at different stages of development (I-VI) in WT (red) and KO (blue) BM (Mean±SEM; n=3). Scale bar, 30 μm (c) Human ACKR1 mRNA BM expression data retrieved from DMAP (http://portals.broadinstitute.org/dmap/home). Subpopulations of erythroid cells (ERY1-4) were defined as follows: CD71hi GlyA–(Ery1), CD71hi GlyA+(Ery2), CD71lo GlyA+(Ery3) and CD71–GlyA+(Ery4). Mean±SEM, One-Way ANOVA; *P < 0.001.

Supplementary Figure 3 ACKR1 deficiency does not affect erythroid parameters in BM and blood.

(a) BM cellularity in in WT (blue) and ACKR1-deficient (KO; red) mice (Mean±SEM; n=9). (b) Percentage of proerythroblasts (I), early normoblasts (II), intermediate normoblasts (III), late normoblasts (IV), reticulocytes (V) and mature red cells (VI) in BM of WT and KO mice (Mean±SEM; n=3). (c) Erythrocyte parameters in blood. RBC: Red blood cell counts; HCT: Haematocrit; Hb: haemoglobin. (Mean±SEM; n=9).

Supplementary Figure 4 Flow cytometry analysis of HSPCs, CD48+ subpopulations of LSK cells and CLP cells.

(a) Gating strategy to identify HSPC populations. LSK, defined as Lin–Sca-1+c-Kit+ were subdivided into LSK CD48+ and LSK CD48+. Myeloid progenitor cells (MPC) were defined as Lin–Sca-1–c-Kit+. (b) Frequency of LSK CD48+ cells in in WT (blue) and ACKR1-deficient (KO, red) BM. (c) Relative distribution of their MPP2, and lineage-restricted progenitor (LRP) 1 and LRP2 sub-populations. Representative dot plots, left; quantitative analysis, right. (d) Frequency of MPP2, LRP1 and LRP2 in the BM of WT and KO mice. (e) Frequency of common lymphoid progenitors (CLP) defined as Lin–Sca-1loc-Kitlo (G1 gate in a) and IL7Rɑ+Ftl3+. Representative dot plots, left; quantitative analysis, right. (b-d) n=12 in four independent experiments. (f) n=5 in two independent experiments. All data show Mean±SEM. Two-tailed Student’s t-test; ***p < 0.001.

Supplementary Figure 5 Gene expression in LSKs and GMPs from WT and ACKR1-deficient mice.

(a) Microarray heatmap of genes expressed in LSKs and GMPs from wild-type (WT) and ACKR1-deficient (KO) BMs. Each row represents a gene and columns show individual cell populations, in duplicates. Two clusters defined by hierarchical clustering analysis reflect specific gene expression in LSK and GMP. The levels of expression of specific LSK and GMP enriched genes were similar in WT and KO BM. (b) Left, blue: Comparative gene expression in neutrophils (PMNs) and GMPs from Immgen dataset (www.immgen.org). The expression of the 444 genes was higher in PMNs vs. GMPs on average >10 times. Three genes with the highest increase, Ltf, Ly6G and Mmp8, were expressed ca. 100 times more in PMN, than in GMP. Right, red: comparative gene expression in GMPs from WT vs. KO BM expressed as fold change. The level of expression of the overwhelming majority of genes was the same in GMPs from WT and KO BMs (mean fold change 1) but some were expressed orders of magnitude higher in KO GMPs. The transcripts for three most overexpressed genes Rentlg, Camp and Ngp, were in excess of 1000 times higher in KO vs. WT GMPs. These genes were not highly upregulated during the differentiation of GMPs towards PMNs (left panel, blue). This excluded a potential contamination of the GMP with PMNs and was consistent with the induction of a specific transcriptional program of a subset of neutrophil specific genes (also see Fig. 3c) in GMPs rather than only their conventional differentiation to PMNs. (c) Microarray heatmap from Fig. 3a with the list of genes. (d) Microarray heatmap from Fig. 3b with the list of genes.

Supplementary Figure 6 BM and blood cell parameters in reciprocal irradiation BM chimeric and parabiotic wild-type and ACKR1-deficient mice.

(a) Schematic representation of experimental groups of irradiation BM chimeric mice. (b,c) Confirmation of successful BM chimerism by flow cytometric measurement of ACKR1 expression on erythroid cells in BM and in blood. (b) Quantitative analysis of ACKR1 expression on subpopulations of erythroid cells (I-VI) in BM. (c) Percentages of ACKR1+and ACKR1– RBC in peripheral blood. (d) Relative distribution of MPP2, LRP1 and LRP2 subpopulation of LSK CD48+ in irradiation BM chimeric mice: wild-type (WT) BM cells reconstituted into WT mice (blue), WT BM cells reconstituted into ACKR1-deficient (KO) mice (light blue), KO BM cells reconstituted into KO mice (red) and KO BM cells reconstituted into WT mice (pink); right, representative dot plots; left, quantitative analysis. (e) Schematic representation of experimental groups in parabiosis experiments. (f) Confirmation of shared circulation in parabiosis by measurement of plasma CCL2 levels in individual naïve and parabiotic mice. WT with WT parabionts (blue), KO with KO parabionts (red), WT parabiont in WT with KO pair (purple) and KO parabiont in WT with KO pair (orange) (g) Relative distribution of MPP2, LRP1 and LRP2 subpopulation of LSK CD48+, right, representative dot plots; left, quantitative analysis. All data are n=4 from two independent experiments, Mean±SEM. One-way ANOVA; *P < 0.05, **P < 0.01 and ***P < 0.001.

Supplementary Figure 7 Interactions of HSCs and nucleated erythroid cells in the BM.

(a) Representative flow cytometry histograms showing staining by antibodies against CD48, Lineage (Lin; B220, CD3, CD11b, Gr1), CD150 and CD71 used for identification of HSCs and nucleated erythroid cells (NECs). The HSCs (LSK CD150+ CD48–) are distinguished as Lin– CD150+CD48–CD71–; the NECs (CD71+ Ter119+) are CD71+Lin–CD150–CD48–; the MPCs and CD48+LSK subset are Lin–CD48+ CD150–CD71– and the lineage cells are Lin+CD48+. (b) Application of the above combination of antibodies to the two-photon microscopy of the whole-mounted femur. HSCs (Lin–CD150+CD71–; green) and NECs (Lin–CD150– CD71+; red) appear clearly distinct. HSCs (in the upper rows of magnification insets, green; in lower rows of insets, only outlined in white) did not stain for lineage or CD71. Scale bars, 50 μm and 40 μm (c) Representative two photon microscopy images of the whole-mounted femurs from ACKR1-deficient mice used for the measurements of the distance between NECs and HSCs. (d) Quantitative analysis of HSC, MMP1, MPP2 and LRP populations interacting with NECs assessed by flow cytometry. Wild-type (WT, blue) and ACKR1-deficient (KO, red). Two-tailed Student’s t-test, (n=3). All numeric data are Mean±SEM. ***P < 0.001.

Supplementary Figure 8 Effect of ACKR1 on the expression of cell surface markers and cell numbers in BM and blood.

(a) CD62L, CD11a, CD16/32, CD45 and CD11b expression in BM neutrophils (CD11b+Ly6G+) from wild-type (WT, blue) and ACKR1-deficient (KO, red) mice; NC (white), negative control staining. Top, representative flow cytometry histograms; bottom, quantitative analysis. (b) Representative flow cytometry histograms of staining blood neutrophils (CD11b+Ly6G+) from WT and KO mice with antibodies against CD62L and CD11a and (c) antibodies against CXCR2, CCR1, CCR2, CCR3 and CCR5. (d) Representative flow cytometry histograms of CXCR1, CXCR2 and CCR2 antibodies staining of blood neutrophils from Duffy-positive and Duffy-negative individuals, grey and black histograms, respectively, negative control staining, NC (white). (e) PMN (CD11b+Ly6G+CD115–), monocyte (CD11b+Ly6G–CD115+) and B lineage cell (B220+CD19+) counts in BM of WT and ACKR1-deficient mice (n=6). (f) Monocyte (CD45+CD11b+Ly6G– CD115+) and lymphoid cell (CD45+ and B220+ or CD3+) counts in blood of WT and ACKR1-deficient mice (n=6). (g) Platelet counts in blood of WT and ACKR1-deficient mice (n=16). (h) Expression of CD16/32 on blood neutrophils (CD11b+Ly6G+CD115–) in reciprocal BM chimeric mice; WT BM cells reconstituted into WT mice (blue), WT BM cells reconstituted into KO mice (light blue), KO BM cells reconstituted into KO mice (red) and KO BM cells reconstituted into WT mice (pink); n=4 from two independent experiments. (i) Representative immunofluorescence micrograph of human spleen stained with monoclonal anti-ACKR1 (Fy6, red) antibody. All data show Mean±SEM. (a and e-g) two-tailed Student’s t-test; *P < 0.05, **P < 0.01. (h) one-way ANOVA; **P < 0.01.

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Duchene, J., Novitzky-Basso, I., Thiriot, A. et al. Atypical chemokine receptor 1 on nucleated erythroid cells regulates hematopoiesis. Nat Immunol 18, 753–761 (2017). https://doi.org/10.1038/ni.3763

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