Human Mast Cell Proteome Reveals Unique Lineage, Putative Functions, and Structural Basis for Cell Ablation

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Human Mast Cell Proteome Reveals Unique Lineage, Putative Functions, and Structural Basis for Cell Ablation Graphical Abstract

Authors Thomas Plum, Xi Wang, Mandy Rettel, Jeroen Krijgsveld, Thorsten B. Feyerabend, Hans-Reimer Rodewald

Correspondence [email protected]

In Brief Mast cell functions beyond allergic diseases remain enigmatic. To provide structural information, Plum et al. performed comprehensive proteome analyses on primary human and mouse mast cells, revealing the cells’ unique lineage within the immune system, putative roles in neuroimmune interactions, and targets for antibodymediated mast cell ablation.

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Mast cell proteome is unique among immune lineages and conserved from mice to men

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Mast cells express proteins potentially involved in neuroimmune interactions

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Mast cells lack expression of key innate immune sensors

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MRGRPX2 is a mast cell surface protein suitable for ablation of skin mast cells

Plum et al., 2020, Immunity 52, 1–13 February 18, 2020 ª 2020 Elsevier Inc. https://doi.org/10.1016/j.immuni.2020.01.012

Please cite this article in press as: Plum et al., Human Mast Cell Proteome Reveals Unique Lineage, Putative Functions, and Structural Basis for Cell Ablation, Immunity (2020), https://doi.org/10.1016/j.immuni.2020.01.012

Immunity

Resource Human Mast Cell Proteome Reveals Unique Lineage, Putative Functions, and Structural Basis for Cell Ablation Thomas Plum,1,2 Xi Wang,1,3 Mandy Rettel,4 Jeroen Krijgsveld,5 Thorsten B. Feyerabend,1 and Hans-Reimer Rodewald1,6,* 1Division

for Cellular Immunology, German Cancer Research Center, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany of Biosciences, Heidelberg University, Im Neuenheimer Feld 234, 69120 Heidelberg, Germany 3Division of Theoretical Systems Biology, German Cancer Research Center, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany 4Proteomics Core Facility, European Molecular Biology Laboratory, Meyerhofstraße 1, 69117 Heidelberg, Germany 5Division of Proteomics of Stem Cells and Cancer, German Cancer Research Center, Im Neuenheimer Feld 581, 69120 Heidelberg, Germany 6Lead Contact *Correspondence: [email protected] https://doi.org/10.1016/j.immuni.2020.01.012 2Faculty

SUMMARY

Mast cells are rare tissue-resident cells of importance to human allergies. To understand the structural basis of principle mast cell functions, we analyzed the proteome of primary human and mouse mast cells by quantitative mass spectrometry. We identified a mast-cell-specific proteome signature, indicative of a unique lineage, only distantly related to other immune cell types, including innate immune cells. Proteome comparison between human and mouse suggested evolutionary conservation of core mast cell functions. In addition to specific proteases and proteins associated with degranulation and proteoglycan biosynthesis, mast cells expressed proteins potentially involved in interactions with neurons and neurotransmitter metabolism, including cell adhesion molecules, ion channels, and G protein coupled receptors. Toward targeted cell ablation in severe allergic diseases, we used MRGPRX2 for mast cell depletion in human skin biopsies. These proteome analyses suggest a unique role of mast cells in the immune system, probably intertwined with the nervous system.

INTRODUCTION Mast cells are hematopoietic cells derived from embryonic origins (Gentek et al., 2018; Rodewald et al., 1996) and adult bone marrow (Arinobu et al., 2005) that reside mostly in tissues exposed to internal and external environments. Mastcell-like cells have been described for invertebrate chordates, thus the development of mast cells pre-dated the emergence of immunoglobulin (Ig) genes by 200 million years (Cavalcante et al., 2002; de Barros et al., 2007; Voehringer, 2013). Mammalian mast cells can recognize immunological, inflammatory, and environmental cues by various classes of receptors, including the high-affinity IgE receptor (FcεRI),

G-protein coupled receptors (e.g., C3a receptor), or ion channels (e.g., P2X7R). On the basis of their tissue location, proteoglycan and protease expression patterns, and responsiveness to IgE-independent stimuli, mast cells are often categorized as connective tissue type or mucosal type (En€ck, 1987; Rothenberg and Austen, 1989; Shanahan erba et al., 1984). Upon stimulation, mast cells can rapidly release preformed cytoplasmic granules containing, among other substances, histamine, proteoglycans (notably heparin), and granule-associated proteases. Mast cells can produce leukotrienes, prostaglandins, and cytokines (Mukai et al., 2018). Mast cell products possess a wide range of biological activities, including promotion of local inflammation, enhancement of vessel permeability (Boesiger et al., 1998), and stimulation of peripheral nerves, leading to symptoms such as itching, sneezing, and coughing (Undem and Taylor-Clark, 2014). However, many of the mast cells’ physiological or pathological functions, in particular those beyond allergic diseases, remain enigmatic (Galli, 2016; Rodewald and Feyerabend, 2012). To aid future studies into mast cell functions, comprehensive proteome data are a valuable resource. Proteome analyses of mast cells have been previously reported for proteins released from mouse mast cells (Shubin et al., 2017), for human short-term cultured skin mast cells (Gschwandtner et al., 2017), for phosphoproteins (Cao et al., 2007), and for lipid rafts (Freitas Filho et al., 2019) in cultured rodent mast cells. Here, we isolated primary human connective tissue mast cells from skin and fat from healthy individuals and analyzed the mast cell proteome by quantitative mass spectrometry. In parallel, we analyzed primary mouse connective tissue mast cells, and human-mouse comparison revealed a core protein signature. By comparison with blood leukocytes, the mast cells presented as a unique lineage within the immune system. In addition to proteins associated with degranulation, mast cells expressed proteins potentially involved in neuroimmune communication. The proteome also provides a basis for the identification of cell surface targets for therapeutic mast cell depletion. Finally, as a proof of principle, we demonstrated mast cell ablation by photoimmunotherapy in human skin explants. Immunity 52, 1–13, February 18, 2020 ª 2020 Elsevier Inc. 1

Please cite this article in press as: Plum et al., Human Mast Cell Proteome Reveals Unique Lineage, Putative Functions, and Structural Basis for Cell Ablation, Immunity (2020), https://doi.org/10.1016/j.immuni.2020.01.012

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RESULTS Protein Expression Signature Defines Human Connective Tissue Mast Cells Mast cells were enriched from an abundance of less than 1% in digested tissues to greater than 96% purity after cell sorting (Figure 1A). Histochemical analysis of sorted cells with toluidine blue revealed metachromatic staining of granules, confirming their mast cell identity (Figure 1B). For comparison, we also analyzed peripheral blood mononuclear cells (PBMCs). Proteins were extracted from skin mast cells, fat mast cells, and PBMCs; labeled with stable dimethyl isotopes; and analyzed by high-resolution mass spectrometry (schematically depicted in Figure S1A). Across all nine human proteome samples (skin mast cells, fat mast cells, and PBMCs from 3 donors each), we identified 34,483 peptides, which were mapped to proteins in the UniProt database and to their corresponding genes via alignment to the Ensembl database. A total number of 4,455 unique proteins was identified at a false discovery rate of 1%, of which 3,253 could be quantified by isotopic labeling (Table S1). We correlated quantified proteins (skin mast cells versus PBMCs, or fat mast cells versus PBMCs) between experimental repeats, which indicated good reproducibility (r R 0.85) (Figures S1B and S1C). To identify proteins that were, on the basis of high fold change and significance, expressed in mast cells but not in PBMCs, we plotted the fold changes of quantified proteins against their p values (Figures 1C and 1D). Relative to proteins of PBMCs, 471 proteins in skin mast cells (Figure 1C) and 517 proteins in fat mast cells (Figure 1D) were strongly expressed (p % 0.01; proteins depicted in red; Table S1). We first concentrated our 2 Immunity 52, 1–13, February 18, 2020

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(A) Skin (upper row) and fat tissue (lower row) from patients undergoing cosmetic surgery were digested (left column), magnetic bead enriched for CD117+ cells (middle column) and reanalyzed after cell sorting (right column). Cells were stained with the indicated antibodies. Numbers indicate percentages of cells in the gates. Data are representative of at least ten independent experiments. (B) Cytospins of cell-sorter-purified mast cells were stained with toluidine blue (scale bar, 20 mm). Images are representative of two independent experiments. (C and D) Volcano plots presenting differential protein expression of sorted skin mast cells (C) and sorted fat mast cells (D) compared with PBMCs (log2 fold changes on x axis) and its significances (y axis). Proteins marked in blue (high in PBMCs) or red (high in mast cells) have p values < 0.01. (E) Volcano plots presenting differential protein expression of skin compared with fat mast cells. In (C), (D), and (E), a summary of three independent experiments is shown; in each of the experiments, we compared one sample of skin mast cells, fat mast cells, and PBMCs, yielding fold changes. The x axis shows the mean fold changes for three experiments. Please also see Figure S1.

analysis on mast cell markers known from gene expression (Motakis et al., 2014). Mast cells expressed specific proteases (Pejler et al., 2007), and tryptase (TPSAB1), carboxypeptidase A3 (CPA3), carboxypeptidase M (CPM), chymase 1 (CMA1), and cathepsin G (CTSG) were among the proteins with the highest fold change (Figures 1C and 1D). Moreover, the mastcell-specific enzyme hematopoietic prostaglandin D synthase (HPGDS), as well as the receptor tyrosine kinase CD117 (KIT), and CD203c (also known as ENPP3) were specifically expressed in skin and fat mast cells (Figures 1C and 1D). It has been suggested that mast cells are heterogeneous in different tissues and that their phenotypes are dependent on the microenvironment (Moon et al., 2010). Comparing skin and fat mast cells, we found only 11 proteins with a log2 fold change greater than 2 (Figure 1E). Among these, expression of fattyacid-binding protein 4 (FABP4) was significantly higher in fat than in skin mast cells (Figure 1E). Albeit not significant (p > 0.02), alpha-1 type I collagen (COL1A1), myosin heavy chain 2 (MYH2), and CD36 also displayed stronger expression in fat mast cells than in skin mast cells. Hence, the mast cell protein signatures in these two tissues are almost identical, suggesting a limited effect of the tissue environment on protein expression in connective tissue mast cells, at least for skin and fat. Human Mast Cell Proteome Contains Receptors for Multifaceted Interactions with Tissue Environments Cell surface proteins are of special interest because they define cell-type-specific functions and interactions with the environment, and they might be potential targets for therapeutic antibodies. We filtered the global mast cell proteome (Table S1) for cell surface molecules and ranked them by significance (Table

Please cite this article in press as: Plum et al., Human Mast Cell Proteome Reveals Unique Lineage, Putative Functions, and Structural Basis for Cell Ablation, Immunity (2020), https://doi.org/10.1016/j.immuni.2020.01.012

S2) (the nervous-system-associated proteins will be discussed in a separate section below). Among the strongly expressed cell surface proteins in mast cells were the cell adhesion molecules CD312, sialic-acid-binding Ig-like lectin 6 (SIGLEC6), SIGLEC8, and CD44, which might act in concert to direct migration of bone marrow precursors to peripheral tissues and contribute to the maintenance and tissue residency of mature mast cells (Gurish and Austen, 2012). CD312 is a receptor for dermatan sulfate, and it was recently shown that its cleavage by mast-cell-derived tryptase renders mast cells susceptible to vibration-triggered degranulation (Le et al., 2019). Channel proteins, (e.g., solute carrier family 2 member 13 [SLC2A13], CD92 [also known as SLC44A1], SLC9A1, SLC8A3, and SLC2A6), which transport ions and small metabolites across the plasma membrane (Lin et al., 2015), were also highly expressed in mast cells. These channels might play roles in nutrient, drug, and xenobiotic metabolism (Hediger et al., 2013; Zhang et al., 2019) in human mast cells. Other intercellular signaling components, such as the tetraspanins CD82 and CD63, were also most differentially expressed. CD82 function has recently been linked to the recognition and rejection of xenogeneic porcine aortic endothelial cells by human monocytes and neutrophils (Saleh et al., 2013). Mast cells expressed high amounts of CD82 (Table S2), and thus might exert similar functions in recognition and rejection of xenogeneic cells. The tetraspanin CD63 is needed for efficient mast cell degranulation (Kraft et al., 2013). Identification of Human-Mast-Cell-Specific Cell Surface Proteins with Potential Involvement in Neuroimmune Interactions Among the proteins with the highest fold changes and significance levels in human mast cells (Tables S1 and S2), we found several proteins that are normally expressed by cells of the nervous system. Among these were the adhesion molecules CD171 and neurotrimin (NTM), which both have been shown to promote homophilic cell adhesion and outgrowth of neurons (Gil et al., 1998; Haspel and Grumet, 2003). Mast cells can reside in close proximity to sensory nerves (Undem and Taylor-Clark, 2014) and therefore might interact with nerves via CD171 and NTM. Proteins involved in the regulation of neuronal excitation such as mas-related G-protein coupled receptor member X2 (MRGPRX2), transient receptor potential cation channel subfamily V member 2 (TRPV2), P2X purinoceptor 1 (P2RX1), and CD203c were also strongly expressed in human mast cells. MRGPRX2 is a G-protein coupled receptor that mediates mast cell degranulation by neuropeptides such as substance P (McNeil et al., 2015; Subramanian et al., 2016). TRP ion channels are commonly expressed by sensory nerves and regulate their excitation (Clapham et al., 2001). In human mast cells, the TRPV2 ion channel might be activated by heat or osmotic stress (Zhang et al., 2012). Purinoreceptors such as P2RX1 are ligand-gated ion channels and important signaling molecules in the nervous system (Collo et al., 1996). CD203c is involved in the hydrolysis of extracellular nucleosid-phosphates and thus contributes to dampening of purinergic signaling (Gorelik et al., 2018). Initiation and termination of purinergic signaling by P2RX1 and CD203c might thus be a means of how mast cells control neuronal activation.

The Human Mast Cell Proteome Contains Proteins with Unknown Functions Among the most differentially expressed mast-cell-specific proteins, we found several with no known mast cell annotations in PubMed (phrase search: ‘‘mast cell’’ AND protein name) (included in Table S2). In vitro studies suggest that von Willebrand factor A domain-containing protein 5A (VWA5A) might act as a tumor suppressor by regulating the transcription factor microphthalmia-associated transcription factor (MITF) (Anghel et al., 2012). MITF is an important regulator of mouse mast cell maturation, and thus VWA5A might also influence human mast cell maturation by regulating MITF (Kitamura et al., 2002). Family with sequence similarity 129, member B (FAM129B) has been described as an adherence junction-associated protein and suppressor of apoptosis (Chen et al., 2011). Mast cells are long-lived tissue resident cells, and FAM129B might regulate cell cycle and survival of mast cells. Fermitin family homolog 2 (FERMT2) is a scaffolding protein required for the assembly of focal adhesions and modulation of cell shape and thus might play a role in previously reported polarized degranulation of mast cells (Joulia et al., 2015). The Human Mast Cell Proteome Is Distinct from the Proteome of Other Hematopoietic Cells Unlike other hematopoietic cells, mature mast cells are absent from peripheral blood and thus have not been included in systematic efforts to characterize immune cell proteomes. To better define the relationship of human mast cells with other lineages of the hematopoietic system, we subjected our proteome dataset to the MaxLFQ algorithm of label-free protein quantitation and compared it with a recently published proteome dataset of blood-derived immune cells (Rieckmann et al., 2017). Hierarchical clustering of the 15% most variable proteins of the combined blood cell proteomes and mast cell proteomes separated the two mast cell types from lymphoid and myeloid immune cells (Figure 2A). The distinction of the mast cell lineage was based on high expression of a group of mast-cell-restricted proteins (e.g., CD82, TRPV2, and SLC44A2) and low expression of proteins attributed to circulating lymphoid and myeloid immune cell lineages (e.g., cathepsin S [CTSS], signal regulatory protein alpha-1 [SIRPA], and ecotropic viral integration site 2B protein homolog [EVI2B]) (Figure 2A; Table S3). We next used principal component analysis (PCA) to derive components that reveal large variances between the different immune cell proteome datasets (Figure 2B). The first three principal components (PCs 1–3) cumulatively explained > 60% of variance within the datasets. PC1 and PC2 both markedly separated the two mast cell subsets from all other immune cells (Figure 2B). No other analyzed immune cell type displayed such a distant position. Calculation of Euclidian distances (arbitrary units [AU]) confirmed that mast cells have no close neighbor in the human hematopoietic network (Figure S2). The two mast cell subsets were closest to each other (AU = 1.4). Among myeloid cells, mast cells were closest to basophils (AU = 87); however, overall mast cells had a very distant relationship to all granulocytes (neutrophils, eosinophils, and basophils) (Figure S2). This lack of similarity might be surprising given that granulocytic lineages and mast cells share functional properties such as degranulation and protease release. Immunity 52, 1–13, February 18, 2020 3

Please cite this article in press as: Plum et al., Human Mast Cell Proteome Reveals Unique Lineage, Putative Functions, and Structural Basis for Cell Ablation, Immunity (2020), https://doi.org/10.1016/j.immuni.2020.01.012

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Protein Expression Signature Defines Mouse Connective Tissue Mast Cells For analysis of the mouse mast cell proteome, we purified connective-tissue-type mast cells from peritoneal exudate cells (PECs) (Figure 3A). As control populations, we used PECs from mast-cell-proficient wild type (Cpa3+/+) or from mast-cell-deficient (Cpa3cre/+) mice. Histochemical analysis demonstrated metachromatic staining of sorted mast cells and mast cells in the Cpa3+/+ PEC sample (Figure 3B). Across all nine murine proteome samples (purified peritoneal mast cells, Cpa3+/+ PECs, and Cpa3cre/+ PECs from 3 independent preparations each), we identified 45,396 peptides that could be mapped to 5,459 unique proteins, of which 3,611 could be quantified by isotopic labeling (Table S4). Correlation of quantified proteins between experimental repeats indicated good reproducibility (r R 0.61) (Figure S3A). We excluded major effects of tissue digestion on protein recovery in control experiments (STAR Methods; Figure S3B). The comparison of wild type PECs with mast-cell-deficient PECs revealed 13 proteins with a log2 fold change R 2 (Table S4). We plotted fold changes of quantified proteins against their p values (Figures 3C). Given that the abundance of proteins derived from mast cells in unpurified PECs was too low to reach statistical significance in this comparison, we next compared sorted mast cells with PECs from mast-cell-deficient Cpa3cre/+ 4 Immunity 52, 1–13, February 18, 2020

Figure 2. Mast Cells Are Distinct Within the Hematopoietic System (A) Heatmap of 232 highly variable proteins (variance > 5) among all the compared immune cell types. Abbreviations are as follows: eosinophils, Eos; basophils, Bas; neutrophils, Neu; monocytes, MO; myeloid dendritic cells, mDCs; plasmacytoid dendritic cells, pDCs; plasma cells, Plasma; B cells, B cell; natural killer cells, NK; regulatory T cells, Treg; T helper cells, Th1, Th2, and Th17; peripheral blood mononuclear cells, PBMC; CD4 T cells, CD4; CD8 T cells, CD8; mast cells, MC. Inter-experiment normalized protein expression values were Z-transformed across cell types for individual proteins. Proteins (in rows) were clustered using Ward’s method with correlation distance (dendrogram not shown), and cell types with replicates (in columns) were clustered using Ward’s method with Euclidean distance. The dendrogram above the heatmap shows the hierarchical clustering of cell types, and the length of vertical lines depicts the degree of difference between cell types and clusters on the basis of Euclidean distance. Examples of proteins strongly differentially expressed in mast cells are indicated on the right. (B) PCA of normalized protein abundances for different immune cell types. Different cell types are indicated by colors and cell type labels. In (A) and (B), data from three independent samples of skin mast cells, and three independent samples from fat mast cells are shown. Please also see Figure S2.

mice (Figures 3C). Here, we detected 90 proteins with a significantly stronger (p % 0.01) expression in mast cells compared with PECs (Figure 3D, depicted in red; Table S4). Expression of carboxypeptidase A3 (CPA3), mast cell protease 4 (MCPT4), and chymase 1 (CMA1) are hallmarks of connective tissue mast cells in mice (Pejler et al., 2010), and indeed, as in the human data, CPA3, MCPT4, and CMA1 were among the proteins with the highest fold change (Figures 3C and 3D). In this group, we also detected tryptase beta 2 (TPSB2), cathepsin G (CTSG), mast cell protease 11 (MCPT11), histidine decarboxylase (HDC), KIT (CD117), and interleukin 1 receptor-like 1 (also known as ST-2 or IL-33R) (Figure 3D; Table S4), all of which are typical mast cell markers. The Mouse Mast Cell Surface Proteome Includes Adhesion Molecules, Nutrient Transporters, and Signaling Components Adhesion molecules (CD34, CD43, and CD31 [also known as PECAM1]) were among the most differentially expressed cell surface proteins in mouse mast cells (Table S5). CD34 and CD43 play a role during mast cell development from bone marrow progenitors (Drew et al., 2005). CD31 can inhibit mast cell responses (Wong et al., 2002). The solute carrier proteins SLC16A1 and SLC7A8 were also among the most differentially expressed proteins. SLC16A1 associates with CD147 to form a lactate transporter. Lactate suppresses IL-33-mediated cytokine

Please cite this article in press as: Plum et al., Human Mast Cell Proteome Reveals Unique Lineage, Putative Functions, and Structural Basis for Cell Ablation, Immunity (2020), https://doi.org/10.1016/j.immuni.2020.01.012

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Figure 3. Quantitative Whole-Proteome Analysis of Primary Mouse Mast Cells (A) Flow cytometry of peritoneal cells from wild type Cpa3+/+ (C57BL/6) mice isolated by peritoneal lavage (peritoneal exudate) (left), after magnetic bead enrichment for CD117+ cells (middle), and after cell sorting for CD117+FcεRI+ cells (right). Cells were stained with the indicated antibodies. Numbers indicate percentages of cells in the gates. Data are representative of three independent experiments. (B) Cytospins of Cpa3+/+ PECs, Cpa3cre/+ PECs, and sort-purified mast cells from Cpa3+/+ PECs were stained with toluidine blue (scale bar, 20 mm). Images are representative of two independent experiments. (C and D) Volcano plots presenting differential protein expression of Cpa3+/+ PECs compared with Cpa3cre/+ PECs (C) or sorted peritoneal mast cells from Cpa3+/+ mice compared with Cpa3cre/+ PECs (D) (x axis) and significances (y axis). Proteins marked in blue (high in Cpa3cre/+ PECs) or red (high in mast cells) have p values < 0.01. In (C) and (D), a summary of three independent experiments is shown; in each of the experiments, we compared one sample of Cpa3+/+ PECs, Cpa3cre/+ PECs, and sort-purified mast cells from Cpa3+/+ PECs, yielding fold changes. The x axis shows the mean fold changes for three experiments. Please also see Figure S3.

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blood vessels (Cheng et al., 2013) and to form site-directed degranulation ‘‘synapses’’ (Joulia et al., 2015), processes which might depend on BASP1. Another protein strongly expressed by mouse mast cells is the neuronal cell adhesion molecule 1 (NCAM1 [also known as CD56]). NCAM1 mediates homophilic binding between −5 0 5 3 2 1 0 1 2 3 neurons (Maness and Schachner, 2007; Van Acker et al., 2017) and thus might facilCpa3+/+ PEC / Cpa3cre/+ PEC (log2) Mast cells / Cpa3cre/+ PEC (log2) itate mast cell-nerve cell communication. SLC6A4 and SLC6A1 are transporters for release from mast cells, which could be a mechanism to prevent serotonin (also known as 5-hydroxytryptamine [5-HT]) and g-amiexaggerated mast cell activation after epithelial injury (Abe- nobutyric acid (GABA), respectively. In the nervous system, bayehu et al., 2016). SLC7A8 functions in amino acid uptake, SLC6A4 and SLC6A1 limit nerve activity by neurotransmitter repossibly serving metabolic purposes (Lin et al., 2015). Although uptake across synaptic membranes (Deken et al., 2000). Rodent the mast cells’ metabolic requirements are largely unknown, mast cells produce and secrete 5-HT (Moon et al., 2014), which these proteomic data might shed some light on this area. Mouse might stimulate sensory neurons in the skin that express 5-HT remast cells expressed the tetraspanins CD63, CD81, and CD82. ceptors (Loyd et al., 2013). Therefore, SLC6A4 could be involved in CD81 has been described as an inhibitory receptor for FcεRI- limiting excessive neuronal activation. Mast cells cannot respond to GABA directly (Gentilini et al., 1995); however, they might be mediated mast cell degranulation (Fleming et al., 1997). involved in reducing GABA availability to associated neurons. In agreement with the human mast cell proteome, we found purinorIdentification of Mouse Mast Cell Proteins with Potential eceptors P2RX1, P2RX4, and P2RX7 and the membrane bound Involvement in Neuroimmune Interactions We found several proteins in mouse mast cells that are normally adenosine deaminase (ADA) strongly expressed in mouse mast expressed by cells of the nervous system. Among these, brain cells. Purinergic signaling might be an important pathway how acid soluble protein 1 (BASP1) displayed the highest expression mast cells control neuronal activation. fold change of all proteins (Tables S4 and S5). BASP1 is involved in nerve sprouting and normally expressed in the brain, in dorsal Mast Cells Lack Key Innate Sensor Receptors root neurons, and during nerve regeneration (Frey et al., 2000). In our proteome data, we did not find Toll-like receptor (TLR) Mast cells have been described to extend cellular processes into expression in the analyzed human or mouse mast cells (Tables Immunity 52, 1–13, February 18, 2020 5

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Please cite this article in press as: Plum et al., Human Mast Cell Proteome Reveals Unique Lineage, Putative Functions, and Structural Basis for Cell Ablation, Immunity (2020), https://doi.org/10.1016/j.immuni.2020.01.012

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Figure 4. Analysis of Innate Sensor Receptors in Mast Cells and Macrophages (A) The total numbers of proteins identified in independent samples of mast cells (n = 4) and macrophages (n = 2) are plotted as a Venn diagram. (B) Volcano plot presenting differential protein expression of mast cells compared with macrophages (log2 fold changes on x axis), and its significances (y axis). Proteins marked in blue are preferentially expressed in macrophages (p < 0.01), and proteins marked in red are preferentially expressed in mast cells (p < 0.01). Cell-type-specific marker proteins are indicated. Fold changes on the x axis are based on mean protein expression data from independent samples of mast cells (n = 4) and macrophages (n = 2). (C) Shown is a bar graph depicting the LFQ expression intensities of a set of pattern recognition receptors in mast cells (right) versus macrophages (left). Each bar represents the mean ± SD (n = 2). Abbreviations are as follows: Toll-like receptor components, TLR; RIG-I-like receptor components, RLR; C-type lectin receptor components, CLR; inflammasome components (INF). Please also see Figure S4.

S1 and S4). Because macrophages are known to express TLRs, we next compared purified mast cells and macrophages from the peritoneal cavity and analyzed their proteomes side by side. In this experiment, using the same input cell number, we detected 4,620 proteins in mast cells and 6,669 proteins in macrophages (Table S6). 3,914 proteins were shared between both cell types (Figure 4A). Correlation of quantified proteins between experimental repeats indicated good reproducibility (r R 0.96) (Figures S4A and S4B). Next, we compared macrophages to mast cells by plotting the fold changes of quantified proteins against their p values (Figure 4B), which revealed 1,005 proteins with log2 fold change R 2 in macrophages versus mast cells and 53 proteins with log2 fold change R 2 in mast cells versus macrophages (Figure 4B; Table S6). Both macrophages (C3, integrin alpha M [ITGAM], CD14, and arginase 1 [ARG1]) (Okabe and Medzhitov, 2014) and mast cells (KIT, heparan sulfate Ndeacetylase and N-sulfotransferase 2 [NDST2], CPA3, and CMA1) strongly expressed known lineage-associated proteins (Figure 4B). We searched the proteomes of macrophages and mast cells for expression of a set of key pattern recognition receptors and their signaling pathway components associated with innate immune cell function (Loo and Gale, 2011; Newton and Dixit, 2012; Takeuchi and Akira, 2010). Peritoneal macrophages expressed TLR-2, TLR-3, TLR-4, TLR-7, TLR-8, and TLR-13 as well as the TLR signaling components MYD88, TRIF-related adaptor molecule (TRAM), and interferon regulatory factor 3 (IRF-3) (Figure 4C). In contrast, mast cells expressed MYD88 and IRF-3, but none of the TLRs (Figure 4C). In macrophages, we found the RIG-I-like receptor (RLR) pathway components RIG-I, DEAD box protein 41 (DDX41), DNA-dependent activator of interferon-regulatory factors (DAI), and melanoma differentiation-associated protein 5 (MDA5), whereas in mast cells we only found RIG-I and DDX41 (Figure 4C). Of note, RIG-I and DDX41 are ubiquitously expressed in immune cells (ImmGen RNA sequencing database). The C-type lectin receptors (CLRs) DECTIN-1 and MINCLE, as well as compo6 Immunity 52, 1–13, February 18, 2020

nents of the inflammasome (INF) pathway NLRP3, NLRC4, and AIM2 were only expressed in macrophages and not in mast cells (Figure 4C; Table S6). Tumor necrosis factor-a (TNF-a) was undetectable in macrophages and mast cells, suggesting that TNF-a is not abundantly pre-stored and its expression might require cell activation, likely in an MYD88- and nuclear factor kB (NF-kB)-dependent manner. In summary, several different classes of pattern recognition receptors were detectable in macrophages but not in mast cells, which suggests that peritoneal mast cells, at least at steady state, do not possess broad innate pattern recognition capabilities. Mast Cell Protein Signatures Are Evolutionarily Conserved To search for similarities between human and mouse mast cells, we compared 5,575 mouse peritoneal mast cell proteins (purified peritoneal mast cells versus Cpa3cre/+ PECs) to 4,458 human fat mast cell proteins (purified fat mast cells versus PBMCs) (Figure 5A). On the basis of Ensembl annotations, 406 proteins in both datasets were identified as orthologs (Table S7). Of these, 36 proteins were significantly overexpressed (p % 0.01) in both mouse and human mast cells compared with non-mast cells (Figure 5A, red dots; Table S7). Proteins with the highest fold change in both mouse and human mast cells included CPA3, CMA1, TPSAB1, KIT, monoamine oxidase type B (MAOB), and synaptic vesicular amine transporter (SLC18A2) (Figure 5A) suggesting evolutionary pressure to maintain strong expression of these proteins. The protein signature based on the 36 cross-species-conserved proteins could be grouped into 6 categories: proteases and protease inhibitors (CPA3, CTSG, and latexin [LXN]); bioactive amine metabolism (SLC18A2 and MAOB); proteoglycan metabolism (Nacetyl-alpha-glucosaminidase [NAGLU], N-sulfoglucosamine sulfohydrolase [SGSH], glucosamine-6-sulfatase [GNS], and beta-hexosaminidase subunit beta [HEXB]); granule machinery proteins (synaptic vesicle membrane protein VAT-1

Please cite this article in press as: Plum et al., Human Mast Cell Proteome Reveals Unique Lineage, Putative Functions, and Structural Basis for Cell Ablation, Immunity (2020), https://doi.org/10.1016/j.immuni.2020.01.012

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Figure 5. Evolutionary Conservation Mast Cell Protein Signature

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(A) Mean fold changes for human fat mast cells versus PMBCs (Figure 1D) (x axis; shown in log2 scale) plotted against mean fold changes for mouse peritoneal mast cells versus Cpa3cre/+ PECs (Figure 3D) (y axis; shown in log2 scale). Proteins shared by both human and mouse mast cells (p < 0.01) shown in red. Typical mast cell signature proteins are marked by arrows and names. (B) Scatterplot comparing the odds ratio of mastcell-specific proteins enriched GO terms between human and mouse. The blue line indicates a fitted linear model and its 95% confidence interval is shaded in gray. The Pearson’s correlation coefficient r is also indicated in the plot. Analysis was based on samples shown in (A).

homolog [VAT1], syntaxin-binding protein 2 [STXBP2], unc-13 homolog D [UNC13D], synaptotagmin-like 3 [SYTL3], syntaxin3 [STX3], and RAB27B); receptors for binding and responding to environmental signals (FAM129B, CD117, P2RX1, CD63, and CD82); and others (BASP1, VWA5A, unconventional myosin-ID [MYO1D], RAB44, serine dehydratase-like [SDSL], mammalian ependymin-related protein 1 [EPDR], oxysterolbinding protein-related protein 8 [OSBPL8], echinoderm microtubule-associated protein-like 2 [EML2], arylsulfatase A [ARSA], alpha-N-acetylgalactosaminidase [NAGA], tensin-1 [TNS1], heat shock 70 kDa protein 2 [HSPA2], and gamma-glutamyl hydrolase [GGH]) To further characterize similarities between human (from fat) and mouse (from PECs) mast cells, we performed Gene Ontology (GO) analysis (category Biological Process). We selected GO terms that were enriched (odds ratio R 1 and p value % 0.05) in human and mouse mast cells and plotted the odds ratio of shared GO terms against each other (Figure 5B). The shared GO terms displayed very similar odds ratios across species, and calculation of the Pearson correlation revealed near perfect correlation (r = 0.94). Among others, carbohydrate (e.g., carbohydrate derivative catabolic process) and lipid (e.g., lipid metabolic process) metabolic pathways (Figure 5B) were enriched, suggesting roles for these metabolic pathways in mast cells. Of note, mast cells require lipids and carbohydrates for the generation and maintenance of proteoglycan-carrying granules (Ro¨nnberg et al., 2012; Wernersson and Pejler, 2014). Cell Surface Staining Corroborates Specificity of Protein Expression on Human Mast Cells Having identified a variety of human-mast-cell-enriched cell surface proteins (Table S2), we next sought to confirm the surface expression by specific antibody staining. We tested 16 markers for cell surface expression by flow cytometry on human mast cells from fat, skin, lung, and colon tissue. Skin and fat exclusively contain connective-tissue-type mast cells, whereas lung and colon tissues harbor both connective-tissue-type and mucosaltype mast cells (Albert-Bayo et al., 2019; Bradding, 2009). We stained in parallel peripheral blood basophils, neutrophils, eosinophils, monocytes, T cells, B cells and plasmacytoid dendritic cells (gating strategy for the different populations see Figure S5). As examples, staining of CD171, MRGPRX2, and SIGLEC6 is

shown (Figure 6A). For all antibodies, we calculated the staining indices (Maecker et al., 2004) (Figures 6B; Figure S6). CD171, MRGPRX2, SIGLEC6, CD117, CD203c, and CD51 showed the strongest positive staining (mean fluorescence intensity [MFI] R 1,000) on mast cells and low to undetectable staining (MFI % 100) on PBMC subsets (Figures 6B). CD82, CD63, CD312, CD107a, CD92, CD44, FcεRI, CD26, SIGLEC8, CD59, and CD54 were preferentially (MFI mast cells > MFI blood leukocytes) but not exclusively expressed in mast cells (Figure S6). Although connective tissue mast cells from skin and fat tissue stained uniformly positive for MRGPRX2, only 11.4% of lung and 17% of colon mast cells stained positive (Figure S7), which confirms previous observations that this receptor is predominantly expressed by connective-tissue-type mast cells but not by mucosal-type mast cells (Subramanian et al., 2016). CD171 might be also preferentially expressed on connective-tissue-type mast cells given that only very few lung (4.6%) and colon cells (1.3%) were positive. Skin and fat mast cells stained uniformly positive for SIGLEC6 (Figure 6A), and nearly all colon (99.7%) and > 90% of lung mast cells expressed SIGLEC6 (Figure S7), suggesting that SIGLEC6 is a generic mast cell marker in humans. Photoimmunotherapy Using MRGPRX2-Specific Antibodies Leads to Depletion of Mast Cells from Human Skin Mast cells are involved in many pathologies including allergic asthma, atopic dermatitis, and urticaria (Balzar et al., 2011; Church et al., 2018; Kawakami et al., 2009). Targeting mast cells with specific cell-depleting antibodies might offer a much needed therapeutic option, especially for treatment-resistant asthmatic and allergic patients. However, approaches toward therapeutic mast cell depletion have only recently been initiated, and to our knowledge there is only a single antibody for this purpose in clinical development (NCT03436797). We decided to use one of the newly identified human-mastcell-specific receptors to investigate their use as potential targets for cell-depleting antibodies. Recently, near-infrared photoimmunotherapy has gained attention for the specific depletion of tumor cells. This technology is based on the delivery of photosensitizer (e.g., IR700DX)-coupled monoclonal antibodies to the tumor, followed by activation of cytotoxicity by Immunity 52, 1–13, February 18, 2020 7

Please cite this article in press as: Plum et al., Human Mast Cell Proteome Reveals Unique Lineage, Putative Functions, and Structural Basis for Cell Ablation, Immunity (2020), https://doi.org/10.1016/j.immuni.2020.01.012

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Figure 6. Analysis of Protein Cell Surface Expression by Flow Cytometry (A) The indicated cell populations were stained with antibodies against CD171, MRGPRX2, or SIGLEC6, and histograms show fluorescence intensities. For gating strategies of the indicated populations, please see Figure S5. For isotype control staining, please see Figure S7. Data are representative of at least three independent experiments per tissue (n R 3). For numbers of experiments per tissue, see STAR Methods. (B) Mast cell populations from fat, skin, colon, lung, and the indicated peripheral blood cells were stained with a panel of antibodies for cell identification (see STAR Methods), together with CD171 or MRGPRX2, SIGLEC6, CD117, CD203c, or CD51, and analyzed by flow cytometry. For further antigens, please see Figure S6. Shown is the mean staining index ± SD (log). For numbers of experiments per tissue, see STAR Methods.

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DISCUSSION Mast cells differ from most, if not all, immune cell lineages by their strict tissue localization, and with the exception of pathological mastocytosis, absence from peripheral blood. Yet, they arise from hematopoietic stem cells and thus belong to the immune system (Kitamura et al., 1977). We determined and analyzed the proteome of primary human mast cells. Hierarchical clustering and PCA with Euclidian distance measurement revealed the mast cells’ distinct position within the immune system. In 8 Immunity 52, 1–13, February 18, 2020

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both measurements mast cells were only distantly related to all other immune cells, and hence lacked a close neighbor. Of note, the mast cell proteomes were unrelated even to other granulocytic lineages (neutrophils, eosinophils, and basophils). Regarding pathogen recognition, mast cells have been proposed to be important innate effector cells, detecting pathogens by cell surface and intracellular pattern recognition receptors and responding to microbial cues by degranulation and production of pro-inflammatory cytokines to fight infection (Marshall et al., 2019; St John and Abraham, 2013). Direct proteome comparison of mast cells and macrophages showed that pattern recognition receptor expression was present in macrophages but undetectable in mast cells, suggesting that mast cells differ from innate immune cells, at least in regard to pathogen recognition capabilities. In line with these findings, mast-cell-deficient mice show no obvious signs of immunodeficiency (Feyerabend et al., 2016; 2011; Schubert et al., 2018). The human mast cell proteome signature included proteins previously associated with functions in the nervous system (such as CD171, NTM, and MRGPRX2). The proposition that mast cells interact with neurons is primarily based on close proximity of mast cells to nerves in many tissues (Forsythe, 2019). The adhesion molecules CD171 and NTM found in our proteome analysis might establish direct cell contact between mast cells and neurons. In addition, it has been recognized that mastcell-derived products (e.g., histamine and eicosanoids) can induce activation of neurons, and nerve-cell-derived neuropeptides (e.g., substance P) can induce mast cell degranulation (McNeil et al., 2015; Undem and Taylor-Clark, 2014). Arachidonate 5-Lipoxygenase (ALOX5) and HPGDS, which are required for the generation of arachidonic acid metabolites, were strongly expressed in human mast cells (Table S1), suggesting that mast-cell-derived eicosanoids participate in neuronal crosstalk. Although MRGPRX2-mediated mast cell activation has been linked to neurogenic inflammation (Green et al., 2019; Meixiong et al., 2019), regulation of neuroinflammation by

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illumination with near infrared light (Mitsunaga et al., 2011). With the aim to explore whether we can specifically deplete mast cells from human tissue in vitro, we prepared human skin punch biopsies. After 6 h in culture, skin explants were injected intradermally with photosensitizer-coupled (anti-MRGPRX2-IR700DX) or control (anti-MRGPRX2) antibodies. On the following day, the cultures were exposed to 660 nm light to activate the photosensitizer (IR700DX (Figure 7A). Twenty-four hours after illumination, tissues were digested, and cell suspensions were stained for CD45, CD117, and FcεRI to detect mast cells and CD14 to detect macrophages. In suspensions from control antibody injected skin samples, mast cells represented between 12.4 and 32.4 percent of the cells, which corresponded in median absolute cell numbers to 1,600 human skin mast cell per 12 mm punch biopsy (Figures 7B and 7C). Photo-activation of IR700DX-labeled antibody depleted between 70 and 90 percent of human mast cells, corresponding on average to an approximate reduction from 1,600 to 200 human mast cells per skin punch biopsy (Figures 7B and 7C). The depletion of mast cells was specific as numbers of macrophages (8,500 versus 11,800) were not reduced (Figure 7C). These promising results demonstrate the feasibility of specific mast cell depletion from human tissues.

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Please cite this article in press as: Plum et al., Human Mast Cell Proteome Reveals Unique Lineage, Putative Functions, and Structural Basis for Cell Ablation, Immunity (2020), https://doi.org/10.1016/j.immuni.2020.01.012

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Figure 7. Depletion of Human Skin Mast Cells by Near Infrared Photoimmunotherapy (A) Experimental design. Human skin punch biopsies were prepared and injected with MRGPRX2-IR700DX or MRGPRX2 antibodies followed by illumination with 660 nm light. (B) Skin samples after treatment with anti-MRGPRX2 (top row; n = 4), or anti-MRGPRX2-IR700DX (bottom row, n = 4). Twenty-four h after illumination, mast cell numbers in the explant samples were quantified by flow cytometry on digested skin cells by using antibodies against CD117 and FcεRI. Mast cells are shown in the gates and percentages of cells in the gates are given. Percentages of skin macrophages were determined by staining for CD45 and CD14 (not shown). (C) Absolute numbers of CD45+CD117+FcεRI+ mast cells and CD45+CD14+ macrophages in the treated punch biopsies measured by flow cytometry and total cell counting. Symbols represent the biopsies shown in (B); small horizontal lines indicate the median.

P2RX1 and CD203c has not yet been investigated. In addition to these proteins, the dataset might provide further structural hints on functional interactions of mast cells and nerves. More work will be required to understand how immune and nervous systems coordinate sensory input. It has been suggested that mast cell subsets from different tissues have different phenotypes, controlled by the microenvironment (Moon et al., 2010). However, we found that the proteomes of human mast cells residing in distinct tissues (skin and fat) were highly similar, suggesting little influence of the microenvironment on protein expression. Yet, the fat mast cell

proteome selectively contained the fatty-acid-binding protein FABP4, which might be a direct or indirect effect of the tissue localization. Mast cell functions in fat tissues are to our knowledge unknown, and mast cells play no roles in models of obesity and metabolic syndrome (Gutierrez et al., 2015) or juvenile diabetes (Gutierrez et al., 2014). Of note, CD171 and MRGPRX2 expression was present on connective tissue mast cells in skin and fat but largely absent from mucosal mast cells in gut and lung tissue. These differences might be due to the distinct organ environments and their local functional requirements or to connective tissue versus mucosal mast cell lineages. Immunity 52, 1–13, February 18, 2020 9

Please cite this article in press as: Plum et al., Human Mast Cell Proteome Reveals Unique Lineage, Putative Functions, and Structural Basis for Cell Ablation, Immunity (2020), https://doi.org/10.1016/j.immuni.2020.01.012

Comparing human and mouse, we found a common mast cell protein signature of 33 orthologs. The conserved proteins were functionally associated with mast cell degranulation and release of histamine, heparin, proteases, and other bioactive substances. Mast cells are found in all mammals, non-mammalian vertebrates, and in several invertebrate species (e.g., the urochordate Styela plicata) (Baccari et al., 2011; Cavalcante et al., 2002; Crivellato et al., 2015; de Barros et al., 2007). The presence of mast cells in urochordates suggests that these cells express core functions independently of adaptive immunity and IgE. With the advent of adaptive immunity, much of the function of IgE antibodies is mediated by mast cells or basophils. Storage and IgE-independent or IgE-dependent release of these highly active substances by mast cells points at roles for mast cells in the induction of rapid local and systemic pathophysiological responses (Profet, 1991). These mast cell functions might play important beneficial roles (Galli, 2016). Indeed, experimental evidence demonstrated protective roles for mast cells in defense against animal toxins (Akahoshi et al., 2011; Metz et al., 2006; Schneider et al., 2007) and bee venom (Marichal et al., 2013; Palm et al., 2013) (reviewed in Galli, 2016). Regarding allergic diseases, current drugs target mast-cellmediated pathology mostly by general anti-inflammatory activity (often glucocorticoids), by neutralizing secreted products (antihistamines), or most recently by blocking IgE (Omalizumab). However, some patients cannot sufficiently control disease even under treatment (Holgate and Polosa, 2008; Pakhale et al., 2011; Serra-Batlles et al., 1998). Although mast cells contribute to protection to animal venoms, and might have other beneficial functions, patients severely affected by allergic diseases might gain from mast cell depletion. Mast-cell-depleting monoclonal antibodies might eliminate the need for continuous treatment with anti-inflammatory drugs and might benefit treatment-resistant patients. To this end, the identification of selective antigens on target cells suitable for cell ablation is key (Hansel et al., 2010). By making use of our proteome analysis, we identified 16 surface receptors that were strongly expressed by human mast cells. All of these antigens were stained on the surface of human fat and skin mast cells with varying degrees of selectivity. Within the tested immune cell lineages, CD171, MRGPRX2, SIGLEC6, CD117, CD203c, and CD51 displayed selective expression on mast cells. Injection of MRGPRX2-IR700DX antibodies into human skin explants and activation of the photosensitizer by light in the near-infrared spectrum induced strong depletion of skin-resident human mast cells without noticeable damage to bystander macrophages. This technology might be applicable for mast cell depletion using antibodies directed against the herein identified mast-cell-specific antigens. In summary, this comprehensive proteome resource might be useful toward a full structural understanding of these evolutionary ancient cells and aid in the development of target identification for cell ablation. STAR+METHODS Detailed methods are provided in the online version of this paper and include the following: 10 Immunity 52, 1–13, February 18, 2020

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KEY RESOURCES TABLE LEAD CONTACT AND MATERIALS AVAILABILITY METHOD DETAILS B Human tissue samples B Mice B Human tissue digestion and mast cell isolation B Flow cytometry B Mouse cell isolation and sorting B Cytospins and microscopy B Sample preparation and mass spectrometry B Relative quantification of proteins with stable dimethyl labels B Side-by-side proteomic analysis of mouse mast cells and macrophages B Gene set enrichment analysis B Comparison of human mast cell proteomes with human immune cells proteomes B Conjugation of MRGPX2 antibody with IR700DX and depletion of human mast cells in skin punch biopsies DATA AND CODE AVAILABILITY

SUPPLEMENTAL INFORMATION Supplemental Information can be found online at https://doi.org/10.1016/j. immuni.2020.01.012. ACKNOWLEDGMENTS The authors are grateful to the tissue donors and A. Altinay, R. Uebing, A. €kel, and S. Meuer for kindly making human tissues available. Dalpke, K. Scha We thank B. Fischer and S. Fo¨hr for expert contributions to initial bioinformatic €fer for technical assistance. We thank the Flow Cytometry analysis and S. Scha Facility team at the German Cancer Research Centre (DKFZ) for their support with sorting of human cells. This work was supported by the Helmholtz Graduate School of Cancer Research to T.P., CRC156/TRR156 project A7 to T.B.F. and H.-R.R., and HGF Project Immunology & Inflammation (ZT-0027) and the Leibniz program of the Deutsche Forschungsgemeinschaft to H.-R.R. AUTHOR CONTRIBUTIONS T.P., T.B.F., J.K., and H.-R.R. designed the study; T.P. performed most experiments; M.R. isolated proteins and performed mass spectrometry; X.W. performed bioinformatics analysis; T.P., T.B.F., J.K. and H.-R.R. analyzed and interpreted the data; T.P. and H.-R.R. wrote the manuscript with input from T.B.F.; all authors critically reviewed the manuscript. DECLARATION OF INTEREST The authors declare no competing interests. Received: September 18, 2019 Revised: December 13, 2019 Accepted: January 22, 2020 Published: February 11, 2020 REFERENCES Abebayehu, D., Spence, A.J., Qayum, A.A., Taruselli, M.T., McLeod, J.J.A., Caslin, H.L., Chumanevich, A.P., Kolawole, E.M., Paranjape, A., Baker, B., et al. (2016). Lactic acid suppresses IL-33-mediated mast cell inflammatory responses via hypoxia-inducible factor-1a-dependent miR-155 suppression. J. Immunol. 197, 2909–2917. Akahoshi, M., Song, C.H., Piliponsky, A.M., Metz, M., Guzzetta, A., A˚brink, M., Schlenner, S.M., Feyerabend, T.B., Rodewald, H.-R., Pejler, G., et al. (2011). Mast cell chymase reduces the toxicity of Gila monster venom, scorpion

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STAR+METHODS KEY RESOURCES TABLE

REAGENT or RESOURCE

SOURCE

IDENTIFIER

Antibodies Anti-human CD3 BV421

Biolegend

Cat#317343; RRID: AB_2565848

Anti-human CD4 PE-Cy7

eBioscience

Cat#25-0047-42; RRID: AB_10547059

Anti-human CD14 BV605

Biolegend

Cat#301833; RRID: AB_11126983

Anti-human CD16 FITC

eBioscience

Cat#11-0168-42; RRID: AB_10805747

Anti-human CD19 Alexa Fluor 700

Biolegend

Cat#302225; RRID: AB_493750

Anti-human CD26 PE

Biolegend

Cat#302705; RRID: AB_314289

Anti-human CD36 PE

Biolegend

Cat#336205; RRID: AB_1575032

Anti-human CD44 PE

Biolegend

Cat#338807; RRID: AB_2260222

Anti-human CD45 BV785

Biolegend

Cat#304047; RRID: AB_2563128

Anti-human CD51 PE

Biolegend

Cat#327909; RRID: AB_940561

Anti-human CD54 PE

Biolegend

Cat#353105; RRID: AB_10899575

Anti-human CD59 PE

Biolegend

Cat#304707; RRID: AB_2275871

Anti-human CD63 PE

Biolegend

Cat#353003; RRID: AB_10896786

Anti-human CD82 PE

Biolegend

Cat#342103; RRID: AB_1595551

Anti-human CD92 APC

Biolegend

Cat#371405; RRID: AB_2616928

Anti-human CD107a PE

Biolegend

Cat#328607; RRID: AB_1186062

Anti-human CD117 APC

eBioscience

Cat#17-1179-42; RRID: AB_10596820

Anti-human CD117 PE

eBioscience

Cat#12-1179-42; RRID: AB_1659666

Anti-human CD123 PerCP Cy5.5

eBioscience

Cat#45-1239-42; RRID: AB_10718981

Anti-human CD171 PE

eBioscience

Cat#12-1719-42; RRID: AB_11041119

Anti-human CD193 APC-Cy7

Biolegend

Cat#310711; RRID: AB_10899737

Anti-human CD203c PE

eBioscience

Cat#12-2039-42; RRID: AB_11219482

Anti-human CD312 PE

Miltenyi Biotec

Cat#130-104-655; RRID: AB_2657345

Anti-human FcεRIa APC

eBioscience

Cat#17-5899-42; RRID: AB_10671394

Anti-human FcεRIa PE

eBioscience

Cat#12-5899-42; RRID: AB_10804885

Anti-human IgE FITC

eBioscience

Cat#11-6986-42; RRID: AB_10717244

Anti-human SIGLEC6 PE

R and D Systems

Cat#FAB2859P; RRID: AB_2714157

Anti-human SIGLEC8 APC

Biolegend

Cat#347105; RRID: AB_2561401

Anti-human MRGPRX2 PE

Biolegend

Cat#359003; RRID: AB_2562300

Anti-human MRGPRX2

Biolegend

Cat#359002; RRID: AB_2562299

Anti-mouse CD45 BV785

Biolegend

Cat#103149; RRID: AB_2564590

Anti-mouse CD117 APC

BD Biosciences

Cat#553356; RRID: AB_398536

Anti-mouse F4/80 PE-Cy7

eBioscience

Cat#25-4801-82; RRID: AB_469653

Anti-mouse FcεRIa PE

eBioscience

Cat#12-5898-82; RRID: AB_466028

Isotype APC (MsIgG1, k)

eBioscience

Cat#17-4714-42; RRID: AB_1603315

Isotype PE (MsIgG2a, k)

Biolegend

Cat#400213; RRID: AB_2800438

Isotype PE (MsIgG1, k)

BD Biosciences

Cat#550617; RRID: AB_10050483

Isotype PE (MsIgG2b, k)

eBioscience

Cat#12-4732-42; RRID: AB_1518771

Isotype PE (huIgG1)

Miltenyi Biotec

Cat#130-104-612; RRID: AB_2661690

ChromPure whole mouse IgG

Jackson ImmunResearch

Cat#015-000-003; RRID: AB_2337188

Biological Samples Healthy patient skin and fat samples

Proaesthetics GmbH

https://www.proaesthetic.de/

Patient lung samples

University Hospital Heidelberg

https://www.thoraxklinik-heidelberg.de/

Patient colon samples

University Hospital Heidelberg

https://www.klinikum.uni-heidelberg.de/ (Continued on next page)

e1 Immunity 52, 1–13.e1–e5, February 18, 2020

Please cite this article in press as: Plum et al., Human Mast Cell Proteome Reveals Unique Lineage, Putative Functions, and Structural Basis for Cell Ablation, Immunity (2020), https://doi.org/10.1016/j.immuni.2020.01.012

Continued REAGENT or RESOURCE

SOURCE

IDENTIFIER

Healthy patient buffy coat

Red Cross

https://www.blutspende.de/

Chemicals, Peptides, and Recombinant Proteins Ficoll-Plaque Plus

GE Healthcare

Cat#17-1440-02

Collagenase 8

Sigma

Cat#C2139

DNase 1

Sigma

Cat#D5025

Hyaluronidase

Sigma

Cat#H3506

Toluidine Blue

Sigma

Cat#T3260

Eukitt

Kindler

N/A

Fetal Bovine Serum

Millipore

Cat#TMS-016-B

EDTA

Sigma

Cat#E6758

SYTOX Blue Dead Cell Stain

Thermo fisher

Cat#S34857

Rapigest SF

Waters

Cat#186002123

Sequencing grade Trypsin

Promega

Cat#V5111

Ammonia solution (25% (vol/vol)

Sigma

Cat#1.05432

Formaldehyde (CH2O) (37% (vol/vol)

Sigma

Cat#252549

Formaldehyde (CD2O) (20%, 98% D)

Isotec

Cat#492620

Formaldehyde (13CD2O) (20%, 99% 13C, 98% D)

Isotec

Cat#596388

Sodium cyanoborohydride (NaBH3CN)

Fluka

Cat#71435

Sodium cyanoborodeuteride (NaBD3CN) 96%D

Isotec

Cat#190020

Sodium dihydrogen phosphate (NaH2PO4)

Sigma

Cat#1.06346

Di-sodium hydrogen phosphate (Na2HPO4)

Sigma

Cat#1.06580

TEAB

Sigma

Cat#T7408

Rat tail collagen

Corning

Cat#354236

IRDye 700DX NHS Ester

Li-Cor

Cat#929-70010

CD117 MicroBead Kit, human

Miltenyi Biotec

Cat#130-091-332

CD117 MicroBead Kit, human

Miltenyi Biotec

Cat#130-091-224

Human raw and analyzed data

This paper

PXD014978

Mouse raw and analyzed data

This paper

PXD015040

This lab

N/A

Critical Commercial Assays

Deposited Data

Experimental Models: Organisms/Strains Mouse: Cpa3cre/+ C57BL/6J; cre-recombinase knockin into Cpa3 locus Software and Algorithms MaxQuant (version 1.6.3.4)

Cox and Mann, 2008

N/A

FloJo X

Treestar

https://www.flowjo.com/

ImageJ

Schneider et al., 2012

https://imagej.nih.gov/ij/

Biobase; Biocgenerics; Parallel

Huber et al., 2015

N/A

sva (ComBat algorithm)

Jeffrey T. Leek

10.18129/B9.bioc.sva

LEAD CONTACT AND MATERIALS AVAILABILITY Further information and requests for resources and reagents should be directed to the Lead Contact, Hans-Reimer Rodewald (hr. [email protected]). METHOD DETAILS Human tissue samples Experiments involving human samples were approved by the ethics committee of the University Heidelberg (S-381/2014; S-377/ 2015), and specimen were obtained with written consent of the patients. Fat, skin, lung, and colon tissues were obtained from the Immunity 52, 1–13.e1–e5, February 18, 2020 e2

Please cite this article in press as: Plum et al., Human Mast Cell Proteome Reveals Unique Lineage, Putative Functions, and Structural Basis for Cell Ablation, Immunity (2020), https://doi.org/10.1016/j.immuni.2020.01.012

University Hospital Heidelberg or from Proaesthetics GmbH. Skin and fat tissues were obtained from healthy patients undergoing cosmetic surgery. Lung tissue was obtained from patients undergoing lung cancer surgery (mostly non-small-cell lung carcinoma). Colon tissue was obtained from patients undergoing partial bowel resection due to bowel cancer. Male and female patients at the age of 21–70 years were included and none received chemotherapeutic treatment before surgery. Only tissues without signs of malignancy or cancer that were not used for pathological diagnosis were used for mast cell purification. Buffy coat preparations were obtained from the German Red Cross of Heidelberg. Peripheral blood mononuclear cells (PBMC) were isolated using Ficoll-Plaque Plus (GE Healthcare) sedimentation. Mice All mice used for experiments were generated at the mouse breeding facilities of the DKFZ in Heidelberg. Male and female C57BL/6 mice 6–30 weeks of age were used. Mast cell-deficient C57BL/6 Cpacre/+mice were obtained after backcrossing of the Cpa3cre allele for > 20 generations onto C57BL/6J (Feyerabend et al., 2011). All animal experiments were performed in accordance with institutional €sidium, Karlsruhe, Germany. and governmental regulations, and were approved by the Regierungspra Human tissue digestion and mast cell isolation Collected human specimens, free of overt abnormalities or cancer, were minced and incubated with DMEM (Thermo Fisher Scientific) containing 1 mg/mL collagenase 8 (Sigma), and 0.025 mg/mL DNase I (Sigma). For digestion of skin tissues 1 mg/mL hyaluronidase 1 (Sigma) was added. Enzymatic digestion was carried out for 30 min at 37 C after which the suspension was filtered through gauze, and centrifuged at 400 g for 5 min. Undigested tissue clumps were subjected to two further digestion rounds with fresh enzyme mix, after which most of the tissue was completely digested. Pellets were washed with phosphate buffered saline (PBS) supplemented with 5% fetal calf serum (FCS) and 2 mM EDTA and filtered through 100 mm cell strainers. The single cell suspension was enriched for CD117+ cells by magnetic bead-separation according to the manufacturer’s instructions (Miltenyi Biotec). To achieve final purity, the eluted cells were stained with the dead-live stain SytoxBlue and specific antibodies (see antibody list). Live CD45+CD117+FcεRIa+ mast cells were sorted at the Flow Cytometry Core Facility of the German Cancer Research Center on a BD Fusion (Becton Dickinson) cell sorter. We addressed the possibility that the mast cell proteome was altered by the enzymatic tissue digestion described above. We isolated mouse peritoneal cells by lavage and incubated half of the cells with collagenase, hyaluronidase, and DNase at 37 C for 30 min (conditions to which human fat and skin mast cells were exposed during tissue processing) and left the other half untreated on ice. We chose one cycle of treatment because in the human tissue experiments, in each round after 30 min released cells were harvested and the enzyme digestion stopped. Peritoneal mast cells were sorted (see below ‘‘Mouse cell isolation and sorting’’) from treated and untreated samples and analyzed side-by-side by mass spectrometry. We could not find, at the false discovery rate of < 0.01 used throughout all experiments, any differentially expressed proteins comparing treated and untreated mast cells (Figure S3B; Table S6). Raising the false discovery rate from < 0.01 to < 0.05 we found only 4 differentially expressed proteins (ANXA2, THBS1, CD99, DHX30) (Figure S3B; Table S6). These results demonstrate that tissue digestion has only a minor effect on protein detection by mass spectrometry. Flow cytometry Single cell suspensions of organs or peripheral blood were centrifuged and resuspended in PBS supplemented with 5% FCS. Prior to antibody staining, cells were incubated for 20 min with 0.28 mg/mL mouse IgG (Jackson ImmunoResearch Laboratories) to block Fcg-receptors. Cells were stained with the diluted fluorochrome-coupled antibodies or respective isotype control antibodies (see antibody list) for 30 min on ice protected from light. After staining, cells were washed once with PBS + 5% FCS + 100nM SytoxBlue and analyzed on a BD LSRFortessa (Becton Dickinson). PBMC subsets were sorted by the following phenotypes: Eosinophils (SSChiCD45+CD193+), neutrophils (SSCintCD45+CD16+), monocytes (SSClowCD45+CD14+), basophils (SSClowCD45+CD123+FcεRIahi), plasmacytoid dendritic cells (SSClowCD45+CD123+FcεRIalow), B cells (CD45+CD19+), CD4 T cells (CD45+CD3+CD4+), and CD8 T cells (CD45+CD3+CD8+). Data are displayed as dot plots or histograms using FlowJo software (Treestar). Flow cytometry data was normalized across experiments by calculating the staining index = (MFI marker – MFI isotype control) / (2 x SD MFI isotype control) (Maecker et al., 2004). Number of experiments (n) in Figure 4 were: CD171 (fat n = 6; skin n = 3; lung n = 1; colon n = 2; PBMC n = 3–4), MRGPRX2 (fat n = 6; skin n = 3; lung n = 3; colon n = 2; PBMC n = 3–5), SIGLEC6 (fat n = 6; skin n = 3; lung n = 3; colon n = 2; PBMC n = 3–5), CD117 (fat n = 6; skin n = 3; lung n = 1; colon n = 2; PBMC n = 3–4), CD203c (fat n = 6; skin n = 3; lung n = 1; colon n = 2; PBMC n = 3–4), CD51 (fat n = 6; skin n = 3; lung n = 3; colon n = 3; PBMC n = 3–4). Number of experiments (n) in Figure S7 were: CD82 (fat n = 6; skin n = 3; lung n = 3; colon n = 3; PBMC n = 3–5), CD63 (fat n = 6; skin n = 3; lung n = 3; colon n = 3; PBMC n = 3–5), CD312 (fat n = 6; skin n = 3; lung n = 3; colon n = 3; PBMC n = 3–5), CD107a (fat n = 6; skin n = 3; lung n = 1; colon n = 3; PBMC n = 3), CD92 (fat n = 6; skin n = 3; colon n = 3; PBMC n = 3), CD44 (fat n = 6; skin n = 3; lung n = 1; colon n = 3; PBMC n = 3–4), CD26 (fat n = 6; skin n = 3; lung n = 1; colon n = 3; PBMC n = 3–4), SIGLEC8 (fat n = 6; skin n = 3; colon n = 3; PBMC n = 2–3), CD59 (fat n = 6; skin n = 3; lung n = 1; colon n = 3; PBMC n = 3), CD54 (fat n = 6; skin n = 3; lung n = 1; colon n = 3; PBMC n = 3). Mouse cell isolation and sorting C57BL/6 mice of 6–30 weeks age were euthanized by CO2 asphyxiation, and the peritoneal cavity was flushed with 10 mL 37 C pre-warmed PBS + 5% FCS. CD117+ cells were enriched by magnetic bead-separation according to the manufacturer’s instructions e3 Immunity 52, 1–13.e1–e5, February 18, 2020

Please cite this article in press as: Plum et al., Human Mast Cell Proteome Reveals Unique Lineage, Putative Functions, and Structural Basis for Cell Ablation, Immunity (2020), https://doi.org/10.1016/j.immuni.2020.01.012

(Miltenyi Biotec). To achieve final purity, eluted cells were stained with the dead-live stain SytoxBlue and specific antibodies (see antibody list). Live CD45+CD117+FcεRIa+ cells mast cells were sorted on a FACSAria cell sorter (Becton Dickinson). Cytospins and microscopy Toluidine blue staining of mast cells was performed as previously described (Kulka and Metcalfe, 2010). Briefly, sorted mast cells were resuspended at 10,000 cells per 200 mL in PBS and centrifuged in a Cytospin 4 (Thermo Fisher Scientific) cytocentrifuge at 700 rpm for 5 min. On the slides, mast cells were fixed in Mota’s fixative for 10 min and rinsed with 66% ethanol and water. Cells were stained with 0.5% acidic toluidine blue (pH 1.5) for 10 min at room temperature. Slides were rinsed with 66% ethanol and water, air-dried, and mounted with coverslips using Eukitt (Kindler). Images were taken on a Zeiss Axioplan (Zeiss) upright microscope with a 40x or 63x objective using the ZEN 2011 lite software suite. Sample preparation and mass spectrometry For analysis of human cells, sorted fat and skin mast cells as well as PBMCs were collected by centrifugation and cell pellets were frozen in liquid nitrogen. For analysis of mouse cells, sorted peritoneal mast cells as well as total peritoneal exudate cells (PEC) from C57BL/6 Cpa3+/+ and Cpa3cre/+ mice were collected by centrifugation and cell pellets were frozen in liquid nitrogen. On average, we isolated 105 highly purified (R 96%) mast cells; at least 5 3 104 cells per sample were required for dimethyl-labeling and protein quantitation by mass spectrometry. Cells were lysed in 0.1% RapiGest (Waters) and 50 mM (NH4)HCO3, extracted proteins were reduced and alkylated with 5 mM dithiothreitol and 10 mM iodoacetamide. After precipitation with trichloroacetic acid and washing with acetone (all chemicals from Sigma), proteins were digested overnight with sequencing-grade modified trypsin (Promega). Peptides were differentially labeled with stable isotope-coded dimethyl labels on a column as described previously (Boersema et al., 2009). The light and heavy labels were swapped between the two technical replicates. Labeled peptides were mixed 1:1:1 (i.e., equally from the three samples) according to cell number (50,000 cells per sample) and separated by offline high pH reverse phase fractionation over a 90-min gradient on a C18 column (Phenomenex) with an Agilent 1200 Infinity high-performance liquid chromatography (HPLC) system. Thirty-two fractions were collected and subsequently pooled into 10 fractions. Pooled peptide fractions were separated with the nanoACQUITY UPLC system (Waters) fitted with a trapping column (nanoAcquity Symmetry C18). Peptides were separated on a 120-min gradient and were analyzed by electrospray ionization-tandem mass spectrometry (ESI-MS/MS) on a linear trap quadrupole Orbitrap Velos Pro (Thermo Fisher Scientific). Full-scan spectra from a mass/charge ratio of 300 to 1,700 at a resolution of 30,000 full width at half maximum were acquired in the Orbitrap mass spectrometer. From each full-scan spectrum, the 15 ions with the highest intensity were selected for fragmentation in the ion trap. A lock-mass correction with a background ion (mass/charge ratio of 445.12003) was applied. Relative quantification of proteins with stable dimethyl labels MS raw files were processed with MaxQuant software (version 1.6.3.4). MS/MS spectra were searched against the human Uniprot FASTA database (Version January 26, 2019, 73,920 entries) or mouse Uniprot FASTA database (Version February 18, 2019, 55,153 entries). N-terminal acetylation, and methionine oxidation were set as variable modifications. Enzyme specificity was selected as trypsin with a maximum of 2 missed cleavages and a minimum peptide length of 7 amino acids. A false discovery rate (FDR) of 1% was applied. Peptide identification was performed with an allowed initial precursor mass deviation of up to 7 ppm and an allowed fragment mass deviation of 20 ppm. Nonlinear retention time alignment of all measured samples was performed in MaxQuant. Peptide identifications were matched across all samples within a time window of 1 min of the aligned retention times. Protein identification required at least 1 ‘razor peptide’ in MaxQuant. Processed raw data files were further analyzed with Bioconductor using the packages: Biobase, BiocGenerics, and Parallel. Contaminants and reverse sequences were removed. The peptides were mapped to the Uniprot database. Using the protein identifier, the peptides were mapped to the associated Ensembl genes as reported by Uniprot. For each Ensembl gene ID a generic protein was selected. Among all proteins that cover most peptides, the longest was selected. Peptides not mapping to the longest protein were not considered in the subsequent analysis. Peptide intensities of 0 were interpreted as missing values and therefore replaced by NA. The expression data was normalized using the variance stabilizing normalization (vsn) (Huber et al., 2002). Computing the mean summarized the technical replicates. For statistical analysis of the comparisons (e.g., Skin MC/PMBC), the vsn-normalized peptide intensities in the two conditions were subtracted from each other. The peptide log-ratios are averaged for each protein. The p value was computed by a moderated t test as implemented in the R/Bioconductor package limma (Lo¨nnstedt and Speed, 2002; Smyth, 2004). p values were corrected for multiple testing (adjusted p) by the method of Benjamini-Hochberg (Benjamini and Hochberg, 1995). Side-by-side proteomic analysis of mouse mast cells and macrophages For side-by-side analysis of mast cells and macrophages, both cell populations were sorted from PEC of C57BL/6 mice, centrifuged, and frozen in liquid nitrogen. Protein extraction and digestion was done as described before. In contrast to the previous experiments, the samples were not labeled. After digestion the peptides were cleaned up by using an OASIS HLB mElution Plate (Waters). Fractionation was carried out as before with minor modification. 12 fractions were collected by offline high pH reverse phase fractionation on an Agilent 1200 Infinity high-performance liquid chromatography system, equipped with a Gemini C18 column (Phenomenex). Pooled peptide fractions were separated with the UltiMate 3000 RSLC nano LC system (Dionex) fitted with a trapping cartridge Immunity 52, 1–13.e1–e5, February 18, 2020 e4

Please cite this article in press as: Plum et al., Human Mast Cell Proteome Reveals Unique Lineage, Putative Functions, and Structural Basis for Cell Ablation, Immunity (2020), https://doi.org/10.1016/j.immuni.2020.01.012

(m-Precolumn C18 PepMap 100, Waters) and an analytical column (nanoEase M/Z HSS T3 column C18, Waters). Peptides were separated on a 50-min gradient and were analyzed by electrospray ionization-tandem mass spectrometry (ESI-MS/MS) on a Fusion Lumos (Thermo Fisher Scientific) mass spectrometer using the proxeon nanoflow source in positive ion mode. Full-scan spectra with mass/charge range of 300–1,500 at a resolution of 120,000 full width at half maximum were acquired in the orbitrap mass spectrometer. The ion trap filling time was set at a maximum of 250 ms with a limitation of 2x105 ions. The ion trap scan rate was set to 35 ms, and MS2 spectra were measured by data-dependent acquisition in centroid mode. MS raw files were processed with MaxQuant software (version 1.6.3.4). MS/MS spectra were searched against the mouse Uniprot FASTA database (Version February 18, 2019, 55,153 entries). MaxQuant settings were as described above, proteins were quantified via MaxLFQ. Gene set enrichment analysis Enrichment of gene sets was analyzed for all genes that were upregulated in mast cells with Gene Ontology Consortium (www. geneontology.org) gene sets using Fisher’s exact tests. p values were corrected for multiple testing by the method of BenjaminiHochberg (Benjamini and Hochberg, 1995), and only Gene Ontology terms with adjusted p value less than 0.05 were kept. Comparison of human mast cell proteomes with human immune cells proteomes The MS raw files of human skin mast cells, fat mast cells, PBMC, and other human blood cell types published previously (Rieckmann et al., 2017) were re-analyzed with MaxQuant software, and proteins were quantified via MaxLFQ. A minimum ratio count of 2 was required for valid quantification events. The LFQ intensity values of the human blood samples were taken to compare human mast cells and PBMC protein expression values of this study. The empirical Bayes-based ComBat algorithm (available in the R package sva, version 3.30.1) was used to adjust the expression values obtained from the two experiments, to ensure that the values were comparable. In addition, serving as internal controls, pseudo PBMC samples were created based on the human blood samples by summing up protein abundance of B, CD4, Treg, CD8, DC, MO, NK cells with weights proportional to the corresponding cell percentages in PBMCs. Heatmap and PCA analyses were carried out based on the ComBat normalized protein expression values. Ward’s method with Euclidean distance was used for hierarchical clustering of cell types. The Euclidian distance shown in Figure S3 was calculated within the space formed by the first three principal components. All pairs of available hematopoietic cell types were considered, and the average values were used to merge their sample repeats. Conjugation of MRGPX2 antibody with IR700DX and depletion of human mast cells in skin punch biopsies The monoclonal antibody clone K125H4 targeting MRGPRX2 (Biolegend) was conjugated to the photosensitizer IR700DX (Li-Cor) according to the manufacturers’ instructions. Skin punch biopsy culture was prepared as described (Stoitzner et al., 2014). Briefly, skin samples were cleaned off subcutaneous fat, and 12 mm punch biopsies (Acuderm inc.) were prepared and placed onto a rat tail collagen matrix (Corning) in DMEM supplemented with 10% FCS (Millipore) and 1% Penicillin/Streptomycin (Thermo Fisher Scientific). After 6 h in culture, 0.25 mg labeled or unlabeled antibody were injected into the skin biopsies. On the next day, the biopsies were illuminated with 48 J/cm2 (20 min and 16 s) near infrared (NIR) light using a 300mW NIR light emitting (660nm) laser diode (Mitsubishi). 24 h after illumination, single cell suspensions were prepared, and remaining mast cells were quantified by flow-cytometric analysis. DATA AND CODE AVAILABILITY Analyzed mass spectrometry proteomics are given in the Tables S1–S7. The raw data have been deposited to the PRIDE (Perez-Riverol et al., 2019) repository as PXD014978 (human) and PXD015040 (mouse).

e5 Immunity 52, 1–13.e1–e5, February 18, 2020