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Expression profiling of constitutive mast cells reveals a unique identity within the immune system

Nature Immunology volume 17, pages 878–887 (2016)Cite this article

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Abstract

Mast cells are evolutionarily ancient sentinel cells. Like basophils, mast cells express the high-affinity receptor for immunoglobulin E (IgE) and have been linked to host defense and diverse immune-system-mediated diseases. To better characterize the function of these cells, we assessed the transcriptional profiles of mast cells isolated from peripheral connective tissues and basophils isolated from spleen and blood. We found that mast cells were transcriptionally distinct, clustering independently from all other profiled cells, and that mast cells demonstrated considerably greater heterogeneity across tissues than previously appreciated. We observed minimal homology between mast cells and basophils, which shared more overlap with other circulating granulocytes than with mast cells. The derivation of mast-cell and basophil transcriptional signatures underscores their differential capacities to detect environmental signals and influence the inflammatory milieu.

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Figure 1: Identification of mast cells as distinct from other assayed cell populations.
Figure 2: Characterization of mast cells as transcriptionally distinct from basophils.
Figure 3: Derivation of the mast-cell transcriptional signature.
Figure 4: Distinct and shared transcriptional expression patterns of basophils and mast cells.
Figure 5: Enrichment for expression of the mouse mast-cell signature in human mast cells.
Figure 6: Tissue-specific mast-cell gene expression.
Figure 7: Transcriptional analysis indicates peritoneal-mast-cell turnover.

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Acknowledgements

We thank the other members of the ImmGen Consortium, especially C. Benoist and T. Shay, for discussions; the core ImmGen team, especially A. Rhodes and K. Rothamel, for technical assistance; and A. Chicoine for assistance with the isolation of cells. Supported by the US National Institutes of Health (R24AI072073 to the ImmGen Consortium; R01 HL120952 and U19AI095219 to N.A.B.; AI095219 to N.A.B.; and T32 AI007306 to D.F.D.) and the Steven and Judy Kaye Young Innovators Award (N.A.B.).

Author information

Author notes

  1. Daniel F Dwyer, Nora A Barrett, K Frank Austen, Edy Y Kim, Michael B Brenner, Laura Shaw, Bingfei Yu, Ananda Goldrath, Sara Mostafavi, Aviv Regev, Andrew Rhoades, Devapregasan Moodley, Hideyuki Yoshida, Diane Mathis, Christophe Benoist, Tsukasa Nabekura, Viola Lam, Lewis L Lanier, Brian Brown, Miriam Merad, Viviana Cremasco, Shannon Turley, Paul Monach, Michael L Dustin, Yuesheng Li, Susan A Shinton, Richard R Hardy, Tal Shay, Yilin Qi, Katelyn Sylvia, Joonsoo Kang, Keke Fairfax, Gwendalyn J Randolph, Michelle L Robinette, Anja Fuchs and Marco Colonna Keke Fairfax, Gwendalyn J Randolph, Michelle L Robinette, Marco Colonna,: Full list of members and affiliations appears at the end of the paper.

  2. Nora A Barrett, K Frank Austen and Anja Fuchs: These authors jointly supervised this work.

Authors and Affiliations

  1. Division of Rheumatology, Immunology and Allergy, Brigham and Women's Hospital, Boston, Massachusetts, USA

    Daniel F Dwyer, Nora A Barrett, K Frank Austen, Daniel F Dwyer, Nora A Barrett, K Frank Austen, Edy Y Kim & Michael B Brenner

  2. Harvard Medical School, Boston, Massachusetts, USA

    Daniel F Dwyer, Nora A Barrett, K Frank Austen, Daniel F Dwyer, Nora A Barrett, K Frank Austen, Edy Y Kim & Michael B Brenner

  3. Division of Biological Sciences, University of California San Diego, La Jolla, California, USA

    Laura Shaw, Bingfei Yu & Ananda Goldrath

  4. Computer Science Department, Stanford University, Stanford, California, USA

    Sara Mostafavi

  5. Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA

    Aviv Regev

  6. Division of Immunology, Department of Microbiology & Immunobiology, Harvard Medical School, Boston, Massachusetts, USA

    Andrew Rhoades, Devapregasan Moodley, Hideyuki Yoshida, Diane Mathis & Christophe Benoist

  7. Department of Microbiology & Immunology, University of California San Francisco, San Francisco, California, USA

    Tsukasa Nabekura, Viola Lam & Lewis L Lanier

  8. Icahn Medical Institute, Mount Sinai Hospital, New York, New York, USA

    Brian Brown & Miriam Merad

  9. USA and Department of Cancer Immunology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, Genentech, San Francisco, California, USA.,

    Viviana Cremasco & Shannon Turley

  10. Department of Medicine, Boston University, Boston, Massachusetts, USA

    Paul Monach

  11. Skirball Institute of Biomolecular Medicine, New York University School of Medicine, New York, New York, USA

    Michael L Dustin

  12. Fox Chase Cancer Center, Philadelphia, Pennsylvania, USA

    Yuesheng Li, Susan A Shinton & Richard R Hardy

  13. Department of Life Sciences, Ben-Gurion University of the Negev, Be'er Sheva, Israel

    Tal Shay

  14. Department of Pathology, University of Massachusetts Medical School, Worcester, Massachusetts, USA

    Yilin Qi, Katelyn Sylvia & Joonsoo Kang

  15. Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri, USA

    Keke Fairfax, Gwendalyn J Randolph, Michelle L Robinette & Marco Colonna

  16. Department of Surgery, Washington University School of Medicine, St. Louis, Missouri, USA

    Anja Fuchs

Authors
  1. Daniel F Dwyer
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  2. Nora A Barrett
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  3. K Frank Austen
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Consortia

The Immunological Genome Project Consortium

  • Daniel F Dwyer
  • , Nora A Barrett
  • , K Frank Austen
  • , Edy Y Kim
  • , Michael B Brenner
  • , Laura Shaw
  • , Bingfei Yu
  • , Ananda Goldrath
  • , Sara Mostafavi
  • , Aviv Regev
  • , Andrew Rhoades
  • , Devapregasan Moodley
  • , Hideyuki Yoshida
  • , Diane Mathis
  • , Christophe Benoist
  • , Tsukasa Nabekura
  • , Viola Lam
  • , Lewis L Lanier
  • , Brian Brown
  • , Miriam Merad
  • , Viviana Cremasco
  • , Shannon Turley
  • , Paul Monach
  • , Michael L Dustin
  • , Yuesheng Li
  • , Susan A Shinton
  • , Richard R Hardy
  • , Tal Shay
  • , Yilin Qi
  • , Katelyn Sylvia
  • , Joonsoo Kang
  • , Keke Fairfax
  • , Gwendalyn J Randolph
  • , Michelle L Robinette
  • , Anja Fuchs
  •  & Marco Colonna

Contributions

D.F.D. wrote the manuscript, conceived of and conducted experiments, and analyzed the data; N.A.B. and K.F.A. wrote the manuscript and supervised the experimental design; and The ImmGen Project Consortium contributed to data collection and assisted in experimental design.

Corresponding authors

Correspondence to Nora A Barrett or K Frank Austen.

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Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Tissue localization of constitutive mast cells.

Chloroacetate esterase reactivity in (clockwise from top left) skin, tongue, trachea and esophagus showing localization of constitutive mast cells in each tissue compartment. Scale bars, 100 μm.

Supplementary Figure 2 Gating strategies for the isolation of mast cells and basophils from peripheral tissue.

(a) Flow cytometric gating used to identify mast cells. Representative plots show skin mast cells. After excluding doublets, dead cells were excluded using propridium iodide and mast cells were identified as CD45+CD11c‒CD11b‒CD4‒CD8‒ CD19 ‒ FcεR1α+CD117+. Arrows indicate sequential gates used. (b) Flow cytometric gating used to identify basophils. Representative plots show blood basophils. After excluding doublets, dead cells were excluded using propridium iodide and basophils were identified as CD4‒CD8‒CD19‒NK1.1‒CD117‒CD49b+FcεR1α+. Arrows indicate sequential gates used.

Supplementary Figure 3 Assessment of mast-cell purity following multiple rounds of sorting.

After gating on intact cells and excluding doublets, mast cell purity was determined as a percentage of all intact cells after each round of sorting. mast cells were identified as CD45+CD11c‒CD11b‒CD4‒CD8‒ CD19 ‒ FcεR1α+CD117+. Arrows indicate sequential gates used. Numbers in each panel indicate the percentage of gated cells from the parental gate.

Supplementary Figure 4 Influence of treatment with collagenase and dispase on peritoneal-mast-cell transcription.

Peritoneal mast cells were subjected to collagenase and dispase treatment for 30 min at 37°C, and microarray results were compared to untreated peritoneal mast cells. (a) Transcripts upregulated by two-fold or more in peritoneal mast cells relative to untreated mast cells following treatment with digestion enzymes. Colored gene symbols indicate fivefold (blue) or tenfold (red) higher expression. (b) Transcripts downregulated by twofold or more in peritoneal mast cells relative to untreated mast cells following treatment with digestion enzymes. Colored gene symbols indicate five-fold (blue) decreased expression. n = 6 untreated replicates and n = 3 enzymatically-treated replicates.

Supplementary Figure 5 Influence of treatment with collagenase and dispase on peritoneal-mast-cell hierarchical clustering.

Peritoneal mast cells were subjected to collagenase and dispase treatment for 30 min at 37°C, and microarray results were compared to all other analyzed immunocyte populations by hierarchical clustering using the top 15% most variable genes. Cell populations denoted using standard ImmGen abbreviations as indicated in Fig.1c. Bar height is inversely correlated to homology between linked populations. Data are from n = 3 independent experiments (skin, tongue, trachea, and enzymatically treated mast cells, spleen and blood basophils), n = 6 independent experiments from peritoneal mast cells, and n = 2 independent experiments from esophagus mast cells.

Supplementary Figure 6 Influence of digestion with collagenase on mast-cell surface-marker staining.

Representative histograms indicating CD34 and ItgB2 surface staining on peritoneal mast cells either untreated (red) or incubated with collagenase IV and dispase I for 30 min at 37°C (blue). Grey solid histogram indicates isotype staining for untreated mast cells, black line indicates isotype staining on enzymatically treated mast cells. Results indicative of n = 3 individual experiments.

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Dwyer, D., Barrett, N., Austen, K. et al. Expression profiling of constitutive mast cells reveals a unique identity within the immune system. Nat Immunol 17, 878–887 (2016). https://doi.org/10.1038/ni.3445

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