Activation of Human Peripheral Blood Eosinophils by Cytokines in a

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Activation of Human Peripheral Blood Eosinophils by Cytokines in a Comparative Time-Course Proteomic/ Phosphoproteomic Study. Kizhake V Soman, Susan J Stafford, Konrad Pazdrak, Zheng Wu, Xuemei Luo, Wendy I White, John E Wiktorowicz, William J Calhoun, and Alexander Kurosky J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.6b00367 • Publication Date (Web): 05 Jul 2017 Downloaded from http://pubs.acs.org on July 7, 2017

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Journal of Proteome Research

Activation of Human Peripheral Blood Eosinophils by Cytokines in a Comparative Time-Course Proteomic/ Phosphoproteomic Study Kizhake V. Soman, *,†,ᵵ Susan J. Stafford,† Konrad Pazdrak,†,ᵵ,§ Zheng Wu,† Xuemei Luo,† Wendy I. White,∆ John E. Wiktorowicz,†,ᵵ,§,┴ William J. Calhoun,# and Alexander Kurosky,*,†,ᵵ †

Department of Biochemistry & Molecular Biology, University of Texas Medical Branch, Galveston, Texas 77555

ᵵ

Sealy Center for Molecular Medicine, University of Texas Medical Branch, Galveston, Texas 77555

§

Institute for Translational Sciences, University of Texas Medical Branch, Galveston, Texas 77555

┴

Institute for Human Immunity & Infection, University of Texas Medical Branch, Galveston, Texas 77555

#

Department of Internal Medicine, University of Texas Medical Branch, Galveston, Texas 77555

∆

MedImmune LLC, One MedImmune Way, Gaithersburg, Maryland 20878

(S) Supporting Information *

Corresponding authors:

Kizhake V. Soman Alexander Kurosky

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ABSTRACT: Activated eosinophils contribute to airway dysfunction and tissue remodeling in asthma and thus are considered to be important factors in asthma pathology. We report here comparative proteomic and phosphoproteomic changes upon activation of eosinophils using eight cytokines individually and in selected cytokine combinations in time-course reactions. Differential protein and phosphoprotein expressions were determined by mass spectrometry after 2-dimensional gel electrophoresis (2DGE) and by LC-MS/MS. We found that each cytokine-stimulation produced significantly different changes in the eosinophil proteome and phosphoproteome, with phosphoproteomic changes being more pronounced and having an earlier onset. Furthermore, we observed that IL-5, GM-CSF, and IL-3 showed the greatest change in protein expression and phosphorylation, and this expression differed markedly from those of the other five cytokines evaluated. Comprehensive univariate and multivariate statistical analyses were employed to evaluate the comparative results. We also monitored eosinophil activation using flow cytometry (FC) analysis of CD69. In agreement with our proteomic studies, FC indicated that IL-5, GM-CSF, and IL-3 were more effective than the other five cytokines studied in stimulating a cell surface CD69 increase indicative of eosinophil activation. Moreover, selected combinations of cytokines revealed proteomic patterns with many proteins in common with single cytokine expression patterns but also showed a greater effect of the two cytokines employed, indicating a more complex signaling pathway that was reflective of a more typical inflammatory pathology.

KEYWORDS: Eosinophils, cytokines, proteomics, phosphoproteomics, activation, mass spectrometry, flow cytometry, asthma


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INTRODUCTION Considerable research shows that the eosinophil represents a major factor in the development of allergic bronchial asthma. Many research studies on eosinophil biology suggest that eosinophils function in modulating bronchomotor tone, antigen presentation, cytokine production, and in the development of airway inflammation. However, their direct causal relationship to asthma symptoms has not yet been defined.1,

2

These unique

activities and their association with allergen-induced pulmonary pathologies led to the development of several therapies targeting eosinophil-specific factors in regulating maturation, activation, survival and chemotaxis.3 Recent clinical trials targeting specific cytokines or their receptors indicated the therapeutic benefits of blocking IL-5, IL-4 and IL-13 stimulation in a selected group of severe asthmatics with hypereosinophilia.4-7 The reported outcomes including effects on exacerbations of asthma, airway inflammation, remodeling and lung function were variable between asthmatics. Our current understanding of the signaling biology of eosinophils in asthma entails multiple proinflammatory signals with overlapping activities and the existence of heterogeneous subpopulations of asthmatics displaying specific molecular mechanisms and responses to treatment. So far six asthma subphenotypes (endotypes) have been proposed for asthma, with airway eosinophilia being a major classifying criterion.8 Clearly, there is a need for better eosinophil- and cytokine-specific therapies and the development of novel and more precise markers of activated eosinophils that would enable us to identify asthmatic patients who might best benefit from such anti-eosinophilic therapy. Thus, this report addresses cytokine stimulation of eosinophils and resulting protein expression with the view to obtaining a better understanding of the underlying associated signaling phenomena. Comprehensive reviews of eosinophil multifunctionality and pleiotropic character are available.9,10 Investigations of eosinophil cellular priming and activation are well reported in the allergic asthma pathology literature; however, information regarding the comparative protein expression resulting from different cytokines during activation has been largely unexplored. In this report we have focused on comparative eosinophil activation rather than priming; priming “pre-activates” eosinophils during recruitment allowing the cells to respond faster and be physiologically more effective.11 Eosinophils are granular leukocytes that secrete molecules in asthma pathology which include cytotoxic granule constituents EPO, MBP, ECP and EDN, ~15 3 ACS Paragon Plus Environment


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cytokines, chemokines eotaxin-1, RANTES, MIP-1α, lipid mediators leukotrienes and PAF, as well as neuro mediators such as substance P, NGF, and VIP.12,13 Clearly, IL-5 is a major reported player in eosinophil activation and asthma but what are the comparative activities of other cytokines also implicated in asthma? IL5 is known to be the most prominent cytokine regulating homeostasis of eosinophils in bone marrow and peripheral blood eosinophils. Other eosinophilic cytokines such as GM-CSF and IL-3 have a related activation mechanism similar to IL-5 since they share the same receptor β chain.14,15 GM-CSF constitutes most of the prosurvival activity present in BAL fluid from asthmatic patients16 and thus overlaps some of the IL-5 function in the airways. Similarly, IL-3 receptor upregulation in airway eosinophils suggests a possible compensatory role for any inadequate IL-5 therapy on lung eosinophilia.17 Eotaxins (CCL11 and CCL24) are considered to be important chemokines involved in the recruitment of eosinophils into the airways,18,19 an effect that gives more than a 50-fold enrichment of eosinophils in BAL fluid over the other motile cell types, and at higher concentrations induce eosinophil degranulation. IL-4 and IL-3 are reported to be overexpressed in the airways of severe asthmatics and their blockade showed clinical efficacy in decreasing airway eosinophilia and exacerbations of asthma of the hypereosinophilic phenotype.4,5 Besides Th2-type cytokines, IFNs and TNFα also upregulate eosinophils and prolong their survival, although their role in asthma is not yet well established.20,21 Thus, given the multiplicity of growth factors and activating stimuli present in the allergic airways and the possible synergistic activity of other combinatory signals elicited in stimulated eosinophils, the question of relative contributions to disease pathology coming from different cytokine signals arises. The effector cytokine molecules selected and evaluated in this report were known from the scientific literature to be prominent in eosinophil activation and were considered most likely to provide some evidence of comparative cytokine activity during eosinophil activation. Although single cytokine eosinophil activation is typically not physiologic and multiple cytokine effects most likely function in concert in asthma, our separate cytokine studies of protein expression provided an experimental comparative benefit and opportunity.

EXPERIMENTAL METHODS AND MATERIALS Histopaque-1077 and dextran were obtained from Sigma-Aldrich (St. Louis, MO). Sypro Ruby fluorescent protein gel stain, iodoacetamide, Precision Plus molecular weight standards, Criterion Tris-HCl precast gels 4 ACS Paragon Plus Environment

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(8–16%), and RC DC protein assay kit were products from Bio-Rad (Hercules, CA). IPG strips (11 cm, pH 3– 11NL), DeStreak rehydration buffer, IPG buffer/ampholytes, and Ettan DALT IPGphor II isoelectric focusing (IEF) cell were obtained from GE Healthcare Lifesciences (Houston, TX). Tri-(2-carboxyethyl) phosphine was purchased from G-Biosciences (St. Louis, MO) Pro-Q Diamond fluorescent phosphoprotein gel stain was obtained from Invitrogen (Carlsbad, CA). Hank’s balanced saline solution (HBSS) without Mg2+ or Ca2+ was from Gibco/Thermo Fisher Scientific, Inc. (Waltham, MA). Eotaxin-1, eotaxin-2, GM-CSF, IL-3, IL-4, IL-5 IL-13, and RANTES were newly purchased from PeproTech, Rocky Hill, NJ. V450 conjugated mouse anti-human CD69 monoclonal antibody and V450 mouse IgG1, κ isotype control antibody were from BD Biosciences (Franklin Lakes, NJ).

Experimental Design

Eosinophil Isolation from Peripheral Human Blood Quiescent human eosinophils were purified from 120 ml of blood drawn from allergy and asthma free healthy subjects (four males and one female) under a research protocol approved by the Institutional Review Board committee at the University of Texas Medical Branch (IRB no. 04371) as we previously described.11 Eosinophil isolation utilized Ficoll-Hypague gradient centrifugation, elimination of erythrocytes by hypotonic lysis, and negative selection using a combination of anti-CD16, anti-CD3, anti-CD35A and anti-CD14 microbeads with a MACS system (Miltenyi Biotec, Auburn, CA). Eosinophil purity was assayed by microscopic examination using a Wright-stained cytospin preparation. Eosinophil homogeneity of preparations was ≥ 98%, with activation levels typically less than 1% as evaluated by CD69 flow cytometry. These purified preparations were used immediately.

Single Cytokine Activation of Eosinophils The sample set consisted of quiescent eosinophils stimulated separately by eight different cytokines (IL-5, eotaxin-1, eotaxin-2, GM-CSF, IL-3, IL-13, IL-4, and RANTES) for four different durations: 15 min, 1 h, 4 h, and 5 ACS Paragon Plus Environment


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24 h. The activation reaction mixture consisted of 1.0 ml of RPMI-1640 medium containing 3-4 X 106 cells and supplemented with 10% FBS, 0.3% L-glutamine, 25 mM HEPES, and 2 g/L sodium bicarbonate, pH 7.4, containing 10 ng/ml of the selected cytokine except for eotaxin-2, which was 25 ng/ml. Overall, we used cytokine levels exceeding 5-fold ED50 as calculated in assays with TF-1 cells that are much less responsive to cytokines than eosinophils are. Cytokine reactions were conducted in an incubator at 37 oC with 5% CO2. The numbers of replicates were three to eight depending on availability of donors. Eosinophil cells were extracted from cells in Destreak Rehydration Buffer (GE Healthcare Lifesciences) and analyzed by 2DGE employing a Pharmacia’s IPGphor multiple sample IEF device (GE Healthcare Lifesciences) for the first dimension and BioRad’s multiple gel SDS-PAGE system (Criterion Dodeca cells, Bio-Rad Laboratories) for the second dimension. IEF was performed with 11 cm precast immobilized pH gradient (IPG) strips (Bio-Rad Laboratories). Sample aliquots were loaded onto dehydrated IPG strips, and rehydrated overnight. IEF was performed at 20 oC with the following parameters: 50 Volts (V), 11 h; 250 V, 1 h: 500 V, 1 h; 1000 V, 1 h; 8000 V, 6 h. The IPG strips were then incubated in 4 ml of equilibration buffer (6 M urea, 2% SDS, 50 mM Tris-HCL, pH 8.8, 20% glycerol) containing 10 µl/ml (500 mM) tri-2 (2-carboxyethyl) phosphine (Geno Technology, Inc., St. Louis, MO) for 15 min at 20 oC with shaking. The samples were then incubated in another 4 ml of equilibration buffer with 25 mg/ml iodoacetamide for 15 min at 20 oC with shaking in order to ensure protein Salkylation. Electrophoresis was performed at 150 v for 2.25 h, 4 oC with precast 8-16% polyacrylamide gels in Tris-glycine buffer, (25 mM Tris-HCI, 192 mM glycine, 0.1% SDS, pH 8.3).

Fluorescent Staining and Imaging of 2DE Gels The protocols used for 2DE gel staining with Pro-Q Diamond and SYPRO Ruby have been described in detail.22 Briefly, after fixing overnight in 50% methanol, 10% acetic acid in ddH2O, the gels were stained for 90 min with Pro-Q Diamond (Invitrogen). After destaining in 20% acetonitrile, in ddH2O containing 50 mM sodium acetate, pH 4.0, the gels were scanned at a 100 µm resolution using the GE Healthcare Typhoon Trio System with a 532 nm excitation laser and a 560 nm (long pass) emission filter. The voltage of the photomultiplier tube was adjusted to achieve a value of 85-97% maximum pixel intensity (16-bit) on the most intense protein spots


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on the gel.


Subsequently, the gels were stained overnight with SYPRO Ruby (Bio-Rad Laboratories),

destained in 10% ethanol, and scanned using a 488 nm excitation laser and 560 nm (long pass) emission filter.

Activation with Pairs of Cytokines In addition to the single cytokine stimulation described above, 2DGE, MS/MS, and label-free LC-MS/MS experiments were performed on eosinophils stimulated with two cytokines in combination, paired as follows: IL5 plus eotaxin-2 and GM-CSF plus IL-3. For 2DGE, triplicate samples stimulated for the same durations and conditions as described above were used. For label-free LC-MS/MS, duplicate samples were stimulated for 1 h and 24 h.

2DGE Protein and Phosphoprotein Differential Expression 2DE gel analysis was performed with SameSpots v4.6 software (TotalLab, Newcastle upon Tyne, UK). After importing the Sypro Ruby and Pro-Q Diamond stained gel images into the SameSpots software program, the first major analytical operation was pixel intensity-based image alignment. The program automatically selected one of the images as the reference for alignment. Vectors were then drawn manually from prominent pixel intensities of each gel to those of the corresponding pixels of the reference image. Using these manual vectors as anchors, the program added a number of vectors (typically a few hundred) automatically. A subset of gels representative of the different sample groups (cytokine treatment, time duration of stimulation) was selected, based on which, the program then performed automated spot detection. Protein spot outlines were drawn and spots were numbered for all gels in the analysis. This procedure ensured that (1) there were the same number of spots on all gels, with no “missing” spots, and (2) a given spot number on any gel in the experiment referred to the same protein. Inappropriate protein spots were excluded prior to manual editing to correct for any errors in spot splitting and merging. Summing up the pixel intensities within each spot boundary, the program calculated a spot “volume” for each protein spot. After protein spot detection, the program performed protein spot volume normalization with respect to a “normalization reference” gel. Normalized protein spot volumes (“protein spot intensities”) were the basic measurements used for the quantitative comparisons between/among sample groups. To determine protein differential abundances for each stimulation duration 7 ACS Paragon Plus Environment


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each cytokine-stimulated sample was compared to the control for the same time point, using Student’s t-test and fold-change, with the following cutoffs: p ≤ 0.00625 (=0.05/8; Bonferroni correction for multiple comparisons), and |FC| ≥ 1.5. Differential phosphorylation was determined from the Pro-Q Diamond stained gels in an identical fashion. Protein spots that showed significant differential expression or phosphorylation were selected for protein identification.

Protein Gel Spot Picking and Identification Significant protein spots were excised, trypsin-digested, and identified by Matrix-Assisted Laser Desorption/Ionization (MALDI) Time-of-Flight (TOF) mass spectrometry, as we previously described.22,23 Briefly, protein plugs of stained gel spots were picked robotically (ProPick II, Digilab, Ann Arbor, MI), incubated with 10 µl of a 10 ng/µl Trypsin Gold in 50 µl of 25 mM ammonium bicarbonate, pH 8.0 (MS grade, Promega, Madison WI) and incubated at 37 ºC overnight (Shevchenko, 2007). After digestion, 1 µl of sample solutions were spotted onto a 384 well MALDI plate and analyzed with an AB Sciex 5800 MALDI/TOF/TOF Proteomics Analyzer (Sciex, Foster City, CA). ProteinPilot (Sciex) software was used in conjunction with Mascot (Matrix Science, Inc., Boston, MA) to analyze the results against the UniProt human database; both MS and MS/MS data were included. Protein spot IDs with protein scores ≥ 62 and/or expectation values ≤ 0.05 were considered significant. Protein probabilities were assigned by the Protein Prophet algorithm.

Multivariate Statistics Unlike single-variate analyses such as t-test and analysis of variance (ANOVA) that are used to query the significance of each variable (e.g. protein spot) individually, multivariate methods search for patterns in the data based on the values of multiple variables. This method can be used to seek patterns among proteins or samples.24,25 We used hierarchical clustering (HC) and Principal Components Analyses (PCA), a “dimension reduction” algorithm, to look for grouping among samples based on their similarities in the proteomic data. The TIBCO Spotfire software v6.5.3 (OmicsOffice Suite, PerkinElmer, Boston, MA) was employed for both calculations (spotfire.tibco.com). HC began with each sample considered as a separate cluster. In each iteration the two most similar clusters were combined to form a new cluster, using a selected distance measure 8 ACS Paragon Plus Environment

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and a selected clustering method. The iterations continued until there was only one cluster that contained all the elements. PCA transformed the set of original variables in the data to a set of new orthogonal variables, and represented the data graphically. Visualizing the data using the top few components made it easier to perceive patterns, e.g. clustering.

Label-Free Proteomics and Data Analysis Label-free experiments were performed to provide a second evaluation of comparative protein eosinophil expression changes resulting from cytokine related eosinophil activation. Protein samples were digested with Trypsin Gold in 50 µl of 25 mM ammonium bicarbonate, pH 8.0, overnight at 37 ºC.26 After digestion label-free samples were injected into a mass spectrometer using an LC auto sampler. Randomized sample order queue was used, and blanks were run between samples. Nano-LC-MS/MS was performed on a Thermo Fisher an Orbitrap Fusion system with CID (collision-induced dissociation) and ETD (electron transfer dissociation) capabilities, coupled with a Dionex Ultimate 3000 nano LC with auto sampler and 40 well standard trays (Thermo Fisher Scientific, Waltham, MA). The samples were injected onto a nano trap (100 µm x 1 cm, C18 PepMap 100) and then followed by C18 reversed-phase using an in-house packed column (SB-C18, ZORBAX, 5 micron from Agilent, Santa Clara, CA). The flow rate was 400 nL/min with a 60 min LC gradient, where the mobile phases were A (5% ACN, 0.1% FA) and B (100% ACN, 0.1% FA). Once the samples were eluted from the column, they were sprayed into the mass spectrometer through a charged 10+/- 1 µm PicoTip Emitter (New Objective, Woburn, MA). Parameters used included the following: tip voltage: +2.2 kV, FTMS mode for MS acquisition of precursor ions (resolution 120,000), ITMS mode for subsequent MS/MS of top 10 precursors was selected for each cycle. MS/MS was accomplished via CID. Progenesis QI for Proteomics (QI-P) software was used for LC MS/MS data analysis (Waters). The mass spectra of peptides generated in the process were used to search the UniProt protein database with MASCOT (Matrix Science) to analyze peptide masses and identify proteins. A high confidence protein identification procedure was based on the identifications of at least two peptides one of which was proteotypic (uniquely mapping to a single protein). The label-free MS/MS raw proteomics

data

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ProteomeXchange

Consortium27


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(http://proteomecentral.proteomexchange.org) using PRIDE repository software28 with the data set identifier PXD004043.

Flow Cytometry Experiments and Analysis Flow cytometry analysis of eosinophil activation provided a third evaluative procedure for comparative protein expression changes. An LSRII Fortessa machine was used for flow cytometry analysis as we previously described.29 After incubating eosinophils with the same eight cytokines used for the 2DE gel and label-free experiments, for the same durations and conditions, flow cytometry analysis of the expression of CD69 on the surface of eosinophils was performed by staining cells with V450 conjugated mouse anti-human CD69 monoclonal antibody (BD Biosciences, Franklin Lakes, NJ) following the manufacturer’s protocol. The matched isotype control antibody (V450 mouse IgG1, κ BD 560373) was used to define the placement of the negative marker. Flow cytometry analyses of eosinophils activated with six pairs of cytokines were performed using the identical procedure and conditions as described above for single cytokine stimulation.

RESULTS 2DGE Analysis The 36 sample groups (the control and the eight cytokine-stimulated samples, at each of the four time points) in different replicate numbers (triplicate or more) produced 121 2DE gels which were separately stained with Pro-Q Diamond and also with Sypro Ruby, giving a total of 242 stained images for analysis. The gels represented controls as well as stimulated samples in replicate numbers three to eight. After TotalLab SameSpots detection and editing, 821 protein spots were selected for analysis. Protein spot intensities of each cytokine-stimulated sample were compared to its control at the same time-point by t-test, and fold-change ≥ 1.5, criteria to determine significant differential abundance and phosphorylation. The results are summarized in Table 1, and graphically plotted in Figure 1 in the form of time-course plots of the number of proteins that changed abundance (Figure 1A) or phosphorylation (Figure 1B) upon eosinophil activation. The results shown represent the number of protein spots observed, changed by cytokine stimulation (up or down compared to control) for the time-point shown. In the differential protein abundance plot, (Figure 1A), the 24 h time point showed three cytokines (GM-CSF, IL-5, and IL-3) that gave the highest levels of protein expression (We note, 10 ACS Paragon Plus Environment

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with reference to Table 1 and Figure 1A, that the difference in the number of proteins stimulated by IL-5 and IL4 is small. However, other results and analyses presented in the rest of this report support our conclusion that IL-5 stimulation groups with those of GM-CSF and IL-3). In the differential phosphorylation plots (Figure 1B) the largest increase in protein phosphorylation was at the 1 h time-point for the same top three cytokines. These results indicated clearly that the impact of eosinophil activation on phosphoprotein expression (Figure 1B) was greater than that on total protein abundance (Figure 1A). Also, phosphoprotein expression changes appeared at an earlier time-point (1 h) than the protein abundance changes (24 h). Furthermore it is noteworthy that the three cytokines (GM-CSF, IL-5, and IL-3) caused a greater increase in total protein expression (24 h) and phosphoprotein expression (1 h) than did the other five cytokines studied, forming a group that was distinct for the three cytokine-stimulated samples. This clustering was especially apparent with regard to phosphoprotein expression (Figure 1B). Figures S1:1 to S1:37 (Supporting Information) are a detailed compilation of raw and calculated results of protein and phosphoprotein expression associated with the single cytokine-, and selected cytokine pair-, stimulation experiments using 2DE gels stained with Pro-Q diamond and Sypro Ruby. Table S1 lists the proteins and phosphoproteins identified in those experiments, and in addition those from label-free experiments, and compares them to proteins we previously reported for the eosinophil proteome.30

The observations with regard to total protein expression and phosphoprotein expression changes were tested by two multivariate statistical techniques: Hierarchical Clustering (HC) and Principal Components Analysis (PCA). HC was performed on the protein expression intensities of the 39 spots that showed a differential abundance after 24 h of cytokine stimulation. These results were obtained from 33 samples of which a combined ten were either IL-5, IL-3, or GM-CSF stimulated as shown in the heat map (Figure 2A). The clustering of the 39 proteins resulting from the calculation is represented by the dendrogram to the left of the heat map where the corresponding protein spot numbers are also shown. The dendrogram at the top of Figure 2A represents the clustering pattern of the samples. The two major clusters of this dendrogram consisted of 13 and 20 samples, on the left and on the right, respectively (Note: We use “major clusters” to refer to the two clusters produced by the first binary split of the full sample set.) Visually, the most striking feature of the map is 11 ACS Paragon Plus Environment


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the predominance of proteins (green cells) that indicated lower than average abundances in the left major cluster (the left 13 columns). We observed that of the 13 samples in the left major cluster, nine were either IL5, IL-3, or GM-CSF-stimulated. One IL-5 stimulated sample found in the second (right) major cluster was an outlier. In general this distribution was in agreement with their similarity determined from the t-tests (see Supporting Information) applied to the data for Figure 1. PCA was used to further examine the patterns in the same protein expression results. While PCA is not per se a clustering method (TIBCO Spotfire user manual), it is capable of revealing clustering patterns when they occur. In the PCA plot shown in Figure 2B, the blue dots represented IL-5 stimulated samples, green IL-3, red GM-CSF, and grey the other five cytokines and controls. Nine colored dots occupied the right bottom corner of the map, close to one another, indicating their moderately strong clustering, and in agreement with the observation from HC (Figure 2A). The blue dot (IL-5) in the bottom left quarter of the map, among the grey dots, represented the same outlier sample observed in HC.

Figures 3A and 3B depict HC and PCA, respectively, for the phosphorylated protein expression results. The inputs were the intensities of 50 spots each from 29 samples of which nine constituted IL-5, IL-3, or GM-CSF that showed a changed phosphoprotein expression after 1 h of cytokine stimulation. The calculations were identical to those for total protein abundance described above. In the heat map shown in Figure 3A one of the two major clusters was composed exclusively of IL-5, IL-3, or GM-CSF-stimulated samples (left panel, 9 samples). The other 20 samples constituted the second major cluster (right panel). Similarly, the PCA plot (Figure 3B) showed a clear separation of the three groups of samples (right side of the figure) away from the samples of the other five cytokines and controls shown on the left side. Compared with protein abundancebased multivariate analysis, the separation in the phosphoprotein expression was highly significant, with no outliers. Taken together with results of the univariate analysis described above these results suggested that eosinophil activation by IL-5, IL-3, and GM-CSF was very different from that demonstrated by the other five cytokines investigated here.

Identification of Differentially Expressed Proteins 12 ACS Paragon Plus Environment

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The significant protein spots described above in Figure 1 and Table S1 add up to a total of 175 unique protein spots. These spots were robotically picked and were identified by MALDI-MS. Of the 175 spots picked, 131 were successfully identified with high confidence (Protein Mascot Scores ≥ 62) and represent part of the data in Table S1. These identified protein spots are shown on the reference gel in Figure 4; each spot was identified with the protein’s gene name. The full data for the identified spots including spot intensities for the different samples, the p-values, and fold-changes for all the pairwise comparisons, the protein names, and other details are listed in Supporting Table S2 for protein expression and Table S3 for protein phosphorylation. Of note, signed fold changes of expression and phosphorylation are listed in these tables, in their appropriate columns, wherever the changes are statistically significant as indicated by their p-values.

Label-Free LC-MS/MS Analysis Label-free analysis of single cytokine stimulation consisted of eosinophils stimulated with the same eight cytokines (IL-5, eotaxin-1, eotaxin-2, GM-CSF, IL-3, IL-13, IL-4, and RANTES) and control samples, for 1 h and 24 h. Each sample was analyzed in duplicate which resulted in 36 samples total. We detected a total of 355 proteins in these samples, using the criterial described on p. 9 (at least two peptides, at least one proteotypic peptide) though only the ones showing differential protein abundance are reported here. The analysis software Progenesis QI-P (Waters) used aligned normalized peak intensities as the basis for protein and peptide abundance. In each case, the stimulated sample was compared to the control at the same timepoint (1 h or 24 h) as in 2DE gel analysis. Sixteen proteins were differentially expressed (p ≤ 0.00625, |FC| ≥ 1.5) and are listed in Table 2. Protein abundance changes for each sample are shown in two columns representing the 1 h and 24 h time-points. Protein abundance in stimulated sample compared to control was designated as either up or down regulation. A blank cell represented lack of significant differential abundance of that protein. Table 2 contains many proteins that also showed differential abundance in the 2DGE results (see Table S1).

2DGE and Label-Free LC-MS/MS Results of Stimulation by Pairs of Cytokines 13 ACS Paragon Plus Environment


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The paired cytokine 2DGE experiments consisted of eosinophils stimulated with two pairs of cytokines: IL-5 plus eotaxin-2 and GM-CSF plus IL-3 for 15 min, 1 h, 4 h, and 24 h and their respective controls. All 2DE gels were in triplicate and stained with both Pro-Q Diamond and SYPRO Ruby consecutively. Each sample set was compared to the control at the same time-point by t-test, for differential abundance and phosphorylation. Since each control was compared with two different samples, the p-value cutoff used was 0.025 (Bonferroni correction). Out of the 223 protein spots that displayed differential abundance or phosphorylation or both, a total of 136 high-confidence IDs were obtained that included 39 proteins that were also identified in the single cytokine stimulation experiments and are listed in Table S1. The significant proteins from the label-free MS/MS analysis (p ≤ 0.025, |FC| ≥ 1.5) are listed in Table 3.

Differential Effects of Single and Paired Cytokines on Protein Expression We compared the protein and phosphoprotein expression of eosinophil stimulation by pairs of cytokines with IL-5 and eotaxin-2, and with GM-CSF and IL-3 using the following three approaches. First, a global view of the differences was obtained using multivariate analysis. Figures 5A,B show results of hierarchical clustering based on the expression of protein abundance and protein phosphorylation, respectively. The columns are the different samples involved in this analysis and the rows are the 102 unique proteins identified. Both display the results of clustering analysis. Along the top are the samples IL-5, extoxin-2, GM-CSF, and IL-3, and the combinations IL-5 plus eotaxin-2 and GM-CSF plus IL-3, and the controls for the single and paired cytokine stimulation experiments. The dendrogram above the sample names represent their clustering. Two features stood out: 1) All the paired cytokine samples, marked by a “plus” sign, clustered together in the same major cluster on the right, indicating a different pattern; 2) samples at the same time point clustered together remarkably well. This suggested that the duration of stimulation may be the most important variable. A second approach was to compare the fold changes of the identified proteins. A total of 37 proteins were found that had a protein abundance or phosphoprotein fold-change of ≥2 or ≤ -2 each with respect to its appropriate control. From these results, the protein expressions which increased most from paired cytokine stimulation (greater fold-changes) than the relevant single cytokine activations are listed in Table S1. Figures S1:1-37 compare, in time-course, the cytokine stimulation comparison between single cytokines and cytokine pairs. 14 ACS Paragon Plus Environment

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A third approach was to look for potential biological/mechanistic differences between the two modes of stimulation, i.e. single vs paired cytokines. For this evaluation, two separate IPA (Ingenuity Pathway Analysis program from Qiagen, Inc., Germantown, MD, USA) runs were performed using the significant proteins identified in the single cytokine stimulation experiments and those from the paired cytokine experiments, each consisting of all significant proteins identified in the 2DE gel and label-free analyses. The program grouped the input proteins into functional classes based on its knowledge base. It associated each functional group with a “score”, defined as -log(p-value), where p is the probability that the specific combination of proteins found in the group occur in it purely by chance. The top ten biological functions obtained by IPA are shown, for the single and paired cytokine stimulations, in Figures 6A,B, respectively. The lower the p, the longer the bar, and the more confident the predicted involvement of the biological function in question. Four of the top ten functions in both Figures 6A,B were immunological disease, inflammatory disease, inflammatory response, and respiratory disease which are all relevant to asthma and airway inflammation, confirming that the proteomic data are indeed capturing the biology under investigation. Comparing Figure 6A with 6B, we observed that eight of the top ten functions were the same though the score and rank of each function were not the same. This indicated that the eosinophil activation process resulting from single and paired cytokine stimulations were substantially the same for the cytokines and pairs used in the present study. The results from the flow cytometry analysis of the single and paired cytokine-stimulated experiments are shown in Figures 7A,B. CD69 is one of the major markers of eosinophil activation and is not constitutively expressed on quiescent cells, as for example CD44 which upregulates upon activation.31 In order to explore the involvement of pathways in eosinophil activation, we used the pathway tools available at http://www.reactome.org/, and the canonical pathway tools in IPA. The common input for both were the proteins we have identified in the analysis described above (2DGE and Label-free protein differential expression and phosphoprylation results combined). We noted and compared the significant pathways, with pvalues ≤ 0.05, implicated by each of the programs. Those common between Reactome and IPA included pathways known to be involved in receptor biology (clathrin-mediated endocytosis), cell communication (gap junction trafficking and regulation), trafficking (RHO GTPases), gluconeogenesis pathway, glycolysis pathway, 15 ACS Paragon Plus Environment


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and pentose phosphate pathway. Examination of the importance and relevance of these and others to eosinophil activation requires further experimentation which is outside the scope of the present study.

DISCUSSION In this comparative proteomics study, we have employed three analytical methods to investigate protein expression of cytokine activation of quiescent purified peripheral blood eosinophils at a molecular level: 2DE gel analysis with MALDI MS, label-free LC-MS/MS analysis, and flow cytometric analysis. Our investigations involved the application of eight well known cytokines whose activities have been well studied, generally individually, but whose signaling pathways have been less investigated at the molecular level. We applied both single cytokine treatment as well as cytokine combinations. We are well aware that the pathology associated with eosinophil activation-related diseases involves at least multiple cytokines concertedly and we have addressed this issue to a limited extent given the investigative constraints.

In this study of eosinophil activation by single and paired cytokine stimulations, a total of 147 unique proteins were identified by the application of 2DGE and label-free LC-MS/MS platforms combined. These are listed in Table S1. Ten proteins were similarly modulated regardless of the cytokine or the combination of cytokines employed, suggesting a common role for their cellular function. Since all the cytokines used for eosinophil stimulation are known to inhibit eosinophil survival at the concentrations tested, it is possible that the commonly modulated proteins participated in antiapoptotic and prosurvival signaling. Furthermore, all cytokines employed are also known to modulate the expression of adhesion molecules and hence they would affect eosinophil motility, migration, and responsiveness to degranulating stimuli albeit at different concentrations. Table 2 lists 16 identified proteins that showed either up or down expression changes using the label-free analytical method with fold-changes of 1.5 or greater.

Figures S1:1 to S1:37 (Supporting

Information) show the significant protein expression changes of 37 proteins in time-course between single cytokine stimulation. These figures also compare single and combined cytokine stimulations. These results were very striking for: 1) showing protein expression differences between phospho-proteins and total proteins for the majority (although not all) of the proteins with observed fold-changes, and for 2) demonstrating clearly 16 ACS Paragon Plus Environment

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that the protein and phosphoprotein expression patterns for cytokine combinations were very different from expression patterns from their single cytokine expression patterns. These results of single cytokine and cytokine combinations give strong evidence the cytokine stimulation of quiescent eosinophils proceeds by different signaling pathways, and that there is crosstalk between cytokines as observed in the cytokine combination investigation. Figures S1:1 to S1:37 represent many features of protein expression resulting from cytokine stimulation of eosinophils. To discuss each of these features in detail was beyond the scope of this report; however, clearly evident in these time-course figures was the fact that the cytokine activity affecting eosinophil protein expression was considerably variable and complex. To highlight some of the expression features we address the differential signaling associated with protein expression of a few significant examples from our results and their possible impact on eosinophil functions. The main methodology used in the present study was 2D-gels. As a means of comparing 2D-gel results to those from another proteomic platform, labelfree experiments were performed, but the sample sets used in the latter were more limited, and did not permit as thorough an analysis as for the 2-D gel data. There is no phosphorylation change information in the labelfree data. Table S1 contains many examples of the same protein being detected as differentially abundant by both methods, providing some internal confirmation of our results.

An important example of protein expression upregulation from cytokine stimulation related to VasodilatorStimulated Phosphoprotein (VASP) is shown in Figure S1:1. This protein is a member of the Ena-VASP protein family that was reported to be synergistically upregulated by IL-5 and eotaxin-2 after 24 h of stimulation.32 VASP is associated with focal adhesions and areas of dynamic membrane activity, where it is thought to have an important role in cytoskeleton reorganization and cell motility.33 VASP contains a central proline-rich sequence which recruits the G-actin binding protein profilin. Localization of VASP to the leading edge of a migrating cell can lead to local accumulation of profilin, which in turn can supply actin monomers to growing filament ends.34 VASP binds to the focal adhesion proteins vinculin and zyxin and this probably directs the phosphoprotein to focal adhesions and the leading edge of stimulated cells.35 VASP functions as a binding intermediate between profilin and focal adhesion proteins.34 VASP is also associated with filamentous actin formation and plays a widespread role in cell adhesion and motility. VASP is also involved in the intracellular 17 ACS Paragon Plus Environment


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signaling pathways that regulate integrin-extracellular matrix interactions and we previously reported that VASP interacts with the common β-chains of receptors for IL-5, IL3 and GM-CSF.11 VASP is regulated by the cyclic nucleotide-dependent kinases PKA and PKG and is a part of the Rap1 signaling pathway.36,37 Rap 1 is a small GTPase that controls cell adhesion and cell polarity and like all G proteins, Rap1 cycles between an inactive GDP-bound and an active GTP-bound conformation. Another important protein whose expression is increased synergistically by IL-5 and eotaxin was gelsolin (Table S1), a Ca2+-regulated actin filament severing, capping, and nucleating protein.38 Recently, it was shown that the protein level of gelsolin affects β1-integrin affinity and cell adhesion in the L1210 and U937 cell lines.39 2DE gel electrophoresis showed that adherent growing L1210-A cells with active β1-integrins contained an almost four-fold increase in gelsolin level when compared with suspensions of growing cells (L1210-S) with inactive β1-integrins suggesting that the gelsolin level can affect β-integrin affinity, without the need to stimulate the cells. Mechanistically, we propose that the observed increased levels of gelsolin in eosinophils exposed to IL-5 and eotaxins decrease the cytoskeletal constrains enabling partial activation of β-integrins. To further compare protein expression during eosinophil activation by the eight cytokines selected, we evaluated the surface expression of CD69, an early activation antigen of T cells and a marker of eosinophil activation. Under our experimental conditions we consistently observed very little expression of CD69 on quiescent eosinophils but a significant, 30-50-fold increase upon stimulation with IL-5, GM-CSF, or IL-3 using flow cytometry (Figures 7A,B). Interestingly, and importantly, we did not observe any appreciable upregulation of CD69 with some cytokines, e.g., IL-13 and RANTES under the reaction conditions described40-42 although eosinophils are known to have receptors on them to all cytokines used in our investigation.20,43-47 The lack of upregulation of eosinophils by these cytokines indicates their lower capacity to induce activation. All cytokines used in our comparisons were newly purchased. Of note, CD69 exists as preformed granules in the cytoplasm of eosinophils and neutrophils;48 however, it is upregulated only on the cell surface of eosinophils. CD69 upregulation follows the initiation of the degranulation process48 and in one study CD69 was the only surface molecule out of 340 investigated to be upregulated on eosinophils in blood and BAL after allergen challenge.42


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Quiescent circulating eosinophils constitutively express integrins in a non-active state, and changes in affinity and avidity are brought about via an inside-out-mediated mechanism, induced by activation of other membrane receptors for growth factors (GM-CSF), cytokines (IL-5) and chemoattractants (eotaxins). Exposure to these cytokines leads to integrin unfolding, allowing accessibility for ligand binding (affinity change).49 These conformational changes are accompanied by clustering of the receptors on the plasma membrane and association of integrins with the cytoskeleton, leading to changes in surface expression and lateral mobility (avidity changes). Proteins affecting the inside-out signaling are thought to directly associate with the integrins, and we previously showed that L-plastin, paxilin, ezrin and Pyk2 can interact with αMβ2.11 Importantly, our identified modified proteins including profilin-1, VASP, and gelsolin interact with Rap-1 and integrin signaling indicating that changes in their expression and phosphorylation may precede processes leading to integrin activated conformations. The 2DGE/MS and label-free/MS results clearly showed that all eight cytokines evaluated for protein expression changes, when compared with control untreated eosinophils, effected a differential expression pattern with GM-CSF, IL-3, and IL-5 showing the greatest protein expression changes. However, what is the significance of the lesser protein expression changes associated with stimulation by the other five cytokines? Several reports from flow cytometry or survival measurements, sometimes using cytokines in combination, have indicated the occurrence of cytokine synergy. Luttmann et al. showed this effect from their studies with IL4, IL-13, and TNFα while Horie et al. described this effect relating to IL-4 and IL-13 studies.50,51. Our results have confirmed and significantly extended the evidence for a cytokine synergy effect both by flow cytometry as well as by label-free-MS/MS. Furthermore, our results have shown that eosinophil stimulations using eight cytokine combinations evaluated by flow cytometry and label-free MS gave results for several cytokines (RANTES, IL-13, eotaxin-1, eotaxin-2) that showed considerably lower CD69 stimulation under the reaction conditions described when compared with other reports.52 Reasons for this difference were not clear. However, we emphasize here that we isolated eosinophils with a comprehensive panel of four antibodies using negative selection with the MACS magnetic bead system from Miltenyi Biotec which may have removed cells or cellular contaminants with activities that affected CD69 expression. Percopo et al. have reported that eosinophils 19 ACS Paragon Plus Environment


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prepared using a multiple-antibody isolation method does offer substantial advantages.53 Alternatively, the 2DGE/MS and label-free/MS results from the five low stimulating cytokines may actually not be reflecting significant activation eosinophil changes. We speculate that their observed effects on protein expression may have been due to other pathways not directly involved in activation, but have either an indirect effect on activation (e.g., paracrine signaling) or perform other functions that contribute to inflammatory pathology. Our protein expression results gave evidence of several signaling cascades including, for example; 1) 14-3-3 kinase involved in the regulation of Raf-1/MAP, Bad/Bcl2, and Akt54-55; 2) Cofilin-1 that is regulated by PI3K and Raf-1-related cascades56; 3) Rho-protein GDP dissociation inhibitor involved in the activation of oxygen superoxide-generating NADPH oxidase and activated by phospholipases57; and 4) alpha-actinin which interacts and regulates the serine/threonine protein kinase MEKK1, an upstream activator of the MAP kinases (JNK/SAPK, Erk, P38), as well as NF-κB58. The 14-3-3 protein, cofilin-1, and alpha actinin-4, undergo changes in both abundance and phosphorylation and are listed in Table S1 (results of stimulation by individual cytokines). The rho protein undergoes changes in protein abundance and phosphorylation, and are listed in Table S1 and Table 3 (cytokine pair results). The possibility that these proteins represent critical nodes of crosstalk signaling cascades governing particular eosinophil functions represents exciting integrative processes that need further studies. A combination of interference approaches targeting these molecules together with loss of function assays will provide a mechanistic understanding of their roles in signaling network nodes and shed light on their biological role in eosinophil function. We detected several proteins related to the GM-CSF pathway, including VASP, profilin-1 and cofilin-1. We also detected L-Plastin (Plastin-2) in our label-free samples, though it does not appear in our tables because it did not meet the criteria for differential abundance. These proteins are part of the cascade propagating priming and cytoskeletal rearrangement in primed eosinophils. Interestingly, in the 2-D gel data, we could not identify phosphorylation of L-plastin to meet differential significance in spite of previous reporting verified by Western blotting (reference 11 in the body of the paper). This may be due to the variance of L-plastin expression in tested donor population as L-plastin was reported to be the cytosolic protein with the most variance among healthy donors.59 Given our relatively stringent cutoffs for significance and the reported L-plastin abundance 20 ACS Paragon Plus Environment

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variability (up to 4-fold), our selection did not find L-plastin significantly modified in our analysis. This may be also the case for a few other reported components of signaling cascades activated by GM-CSF or IL-5 including MAP/Erk kinases. Several signaling cascades implicated in activation of eosinophils with cytokines, including Ras-Raf-MAP/Erk, Jak-STAT, PKC-dependent pathways, PI3K and p38 cascades, are known. Our studies have contributed to a significant part of this knowledge.11, 60-62 Interestingly, the present study did not reveal changes in expression and phosphorylation of JAK, STAT or Erk kinases. This was most likely due to the transient and early nature of the posttranslational modification (phosphorylation) of these molecules, and their low abundance preventing detection by MS. Of note, the present report is based on a “discovery” approach where only the proteins showing differential expression or phosphorylation are detected and our significance criterial are quite stringent (see Methods). Recently, Wilkerson et al.63 have published a peripheral blood eosinophil proteome study in which comparative proteomic expression and phosphorylation after a five minute-stimulation with IL-5 were described. They reported a large number of proteins in common with our earlier eosinophil proteome study.22 The results reported here are from a more comprehensive time-course stimulation with eight cytokines and two combinations, for four different durations, using multiple proteomic platforms (2DGE-MALDI, label-free MS/MS, and flow cytometry). Also, our focus in this study has been protein expression/phosphorylation in the context of mechanisms of eosinophil activation.

CONCLUSIONS This is the first comparative proteomics report to describe protein and phosphoprotein expression changes in peripheral blood eosinophils as a result of cytokine stimulation. We have treated highly purified quiescent eosinophils with eight cytokines that have been well reported to play important roles in inflammatory diseases, namely, IL-3, IL-4, IL-5, IL-13, GM-CSF, eotaxin-2, IFNɣ and TNFα. In addition, two cytokine pairs (IL-5 plus eotaxin-2 and GM-CSF plus IL-3) were similarly evaluated for protein expression using 2DGE and label-free MS/MS. Six additional cytokine combinations GM-CSF plus IL-3, IFNɣ plus IL-13, IFNɣ plus TNFα, IL-2 plus IL4, IL-5 plus eotaxin-2, and IL-5 plus IL-13 were evaluated using flow cytometric analysis of CD69 expression 21 ACS Paragon Plus Environment


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after 24 h of stimulation (Figures 7A,B). These results were obtained using three independent proteomic methods, namely, 2DGE/MALDI/MS, label-free MS/MS, and flow cytometry. These time-course expression results demonstrate that phosphoprotein changes occurred earlier (~ 1 h) than total protein changes which were maximal at 24 h. Time-course patterns of protein expression changes were highly variable and fairly unique for each cytokine investigated (Figures S1-1 to S1-37, Supporting Information). These results and the results of stimulations with combinations of cytokines strongly reflect the multifunctional character of the eosinophil and the complex differential signal translocation phenomena that occur during cell activation. The expression results with cytokine combinations using label-free MS/MS and flow cytometry also gave strong evidence of synergy between cytokine stimulations, especially notable with flow cytometric analysis of combinations of GM-CSF plus IL-3 and IFNɣ plus TNFα. The fact that other cytokine combinations were not as effective may relate to a requirement for a specific cytokine sequence to occur; also not all combinations were evaluated. Thus, our protein expression results have shown a number of major findings that impacted significantly on our understanding of the biology of eosinophil activation by cytokine processes: 1) the eight cytokines individually gave a unique pattern of protein and phosphoprotein expression indicating pathway differences; 2) phosphoprotein expression changes with time-course analysis was more dramatic than total protein expression changes; 3) phosphoprotein expression changes peaked at 1 h and total protein expression changes peaked at 24 h; 4) the phosphoprotein expression patterns for eosinophil activation were significantly greater from GMCSF, IL-5, and IL-3 stimulation using all three activation procedures (2DGE/MS, label-free LC-MS/MS, and flow cytometry); 5) flow cytometry measurements of the CD69 activation marker especially indicated the dramatic stimulation of eosinophils by the three cytokines (IL-3, GM-CSF, and IL-5) when compared with five other cytokines studied; 6) two selected cytokine combinations (IL-5 plus eotaxin-2 and GM-CSF plus IL-3) demonstrated protein and phosphoprotein expression patterns that were different when compared with a summation pattern of protein and phosphoprotein expression resulting from the separate cytokines; 7) there was reasonable agreement between the three analytical comparative procedures employed, which was especially noteworthy for 2DGE MS and label-free LC-MS/MS; and 8) six cytokine combinations were


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evaluated by flow cytometry analysis of CD69 of which two were especially notable (IFNγ plus TNFα and GMCSF plus IL-3) (Figures 7A,B). Finally, and importantly, these results provide a strong basis for continued research defining signaling pathways in eosinophil activation and how eosinophils contribute to the pathophysiology of a number of diseases.

ASSOCIATED CONTENT (S) Supporting Information Figure S1 - Average time-course fold-changes in 37 proteins and phosphoproteins in selected single cytokineand paired cytokine- stimulation experiments. Table S1 - Identified proteins found to display significant protein or phosphoprotein expression in our 2DGE or label-free LC-MS/MS experiments on single or paired cytokine-stimulated eosinophil samples. Each column includes results from all time points sampled. Table S2 – Detailed results for the 69 protein spots showing differential protein abundance in 2DGE experiments with single cytokine stimulations of eosinophils. Table S3 - . Detailed results for the 114 protein spots showing differential protein phosphorylation in 2DGE experiments with single cytokine stimulations of eosinophils. This material is available free of charge at The Supporting Information on the ACS Publications website at DOI:______________.

AUTHOR INFORMATION * Corresponding Authors *

A.K.: Tel: 409-772-2271, Fax: 409-772-8025.

E-mail: [email protected] 23 ACS Paragon Plus Environment


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*

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K.S.: Tel: 409-772-8062. Fax: 409-772-8025

E-mail: [email protected]

CONFLICT OF INTEREST DISCLOSURE This research was supported by funding from MedImmune, LLC, Gaithersburg, Maryland, USA.

ACKNOWLEDGEMENTS This research was supported by an NIH/NHLBI contract HHSN268201000037-C-0-01 (N01-HV-00245) (A.K.) and a MedImmune grant MA-409325.

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(46) Ponath, P. D.; Qin, S.; Post, T. W.; Wang, J.; Wu, L.; Gerard, N. P.; Newman, W.; Gerard, C.; Mackay, C. R. Molecular cloning and characterization of a human eotaxin receptor expressed selectively on eosinophils. J. Exp. Med. 1996, 183 (6), 2437-2448. (47) Yamaguchi, T.; Kimura, H.; Kurabayashi, M.; Kozawa, K.; Kato, M. Interferon-gamma enhances human eosinophil effector functions induced by granulocyte-macrophage colony-stimulating factor or interleukin-5. Immunol. Lett. 2008, 118 (1), 88-95. (48) Nopp, A.; Lundahl, J.; Hallden, G. Quantitative, rather than qualitative, differences in CD69 upregulation in human blood eosinophils upon activation with selected stimuli. Allergy 2000, 55 (2), 148-156. (49) Askari, J. A.; Buckley, P. A.; Mould, A. P.; Humphries, M. J. Linking integrin conformation to function. J. Cell. Sci. 2009, 122 (Pt 2), 165-170. (50) Horie, S.; Okubo, Y.; Hossain, M.; Sato, E.; Nomura, H.; Koyama, S.; Suzuki, J.; Isobe, M.; Sekiguchi, M. Interleukin-13 but not interleukin-4 prolongs eosinophil survival and induces eosinophil chemotaxis. Intern. Med. 1997, 36 (3), 179-185. (51) Luttmann, W.; Matthiesen, T.; Matthys, H.; Virchow, J. C., Jr. Synergistic effects of interleukin-4 or interleukin-13 and tumor necrosis factor-alpha on eosinophil activation in vitro. Am. J. Respir. Cell. Mol. Biol. 1999, 20 (3), 474-480. (52) Luttmann, W.; Knoechel, B.; Foerster, M.; Matthys, H.; Virchow, J. C., Jr.; Kroegel, C. Activation of human eosinophils by IL-13. Induction of CD69 surface antigen, its relationship to messenger RNA expression, and promotion of cellular viability. J. Immunol. 1996, 157 (4), 1678-1683. (53) Percopo, C. M.; Dyer, K. D.; Killoran, K. E.; Rosenberg, H. F. Isolation of human eosinophils: microbead method has no impact on IL-5 sustained viability. Exp. Dermatol. 2010, 19 (5), 467-469. (54) Dhillon, A.S.;, Yip, Y. Y.; Grindlay, G.J.;, Pakay, J. L.; Dangers, M.; Hillmann, M.; Clark, W.; Pitt, A.; Mischak, H.; Kolch, W.; The C-terminus of Raf-1 acts as a 14-3-3-dependent activation switch. Cell Signal. 2009, 21(11), 1645-1651. (55) Rácz, B.; Gasz, B.; Gallyas, F. Jr; Kiss, P.; Tamás, A.; Szántó, Z.; Lubics, A.; Lengvári, I.; Tóth, G.; Hegyi, O.; Roth, E.; Reglodi, D. PKA-Bad-14-3-3 and Akt-Bad-14-3-3 signaling pathways are involved in the protective



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Table 1. Summary of 2DGE results from eosinophil stimulation with eight different cytokines. Shown are the number of spots exhibiting protein differential abundance or phosphorylation (up or down) compared to controls at the same time point (p ≤ 0.00625) Cytokine IL-5 Eotaxin-1 Eotaxin-2 GM-CSF IL-3 IL-13 IL-4 RANTES Combined, unique, protein spots

Protein property measured Abundance Phosphorylation Abundance Phosphorylation Abundance Phosphorylation Abundance Phosphorylation Abundance Phosphorylation Abundance Phosphorylation Abundance Phosphorylation Abundance Phosphorylation Abundance Phosphorylation

15 min 5 8 2 2 1 0 9 13 4 4 0 2 5 5 1 1 20 25

Duration of eosinophil stimulation 1h 4h 8 2 29 6 0 0 2 2 0 1 3 1 1 1 29 6 3 2 20 7 0 1 1 1 2 1 0 3 2 1 4 1 10 7 50 21


24 h 7 6 2 2 1 2 22 7 20 4 1 3 6 4 2 8 39 31


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48

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Table 2. Significant proteins from single cytokine stimulation label-free LC-MS/MS experiments (p ≤ 0.00625, |FC| ≥ 1.5) No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Name Annexin A4 GN=ANXA4 SV=4 Aspartate--tRNA ligase, cytoplasmic GN=DARS ATP-binding cassette sub-family A member 12 GN=ABCA12 Glucose-6-phosphate 1dehydrogenase GN=G6PD SV=4 Histone H1.1 GN=HIST1H1A Keratin, type I cytoskeletal 17 GN=KRT17 Keratin, type II cytoskeletal 74 GN=KRT74 Leucine-rich repeat-containing protein 8D GN=LRRC8D SV=1 Lon protease homolog 2, peroxisomal GN=LONP2 SV=1 Low-density lipoprotein receptorrelated protein 1B GN=LRP1B Mitotic spindle assembly checkpoint protein MAD1 GN=MAD1L1 Nuclear autoantigen Sp-100 GN=SP100 Nuclear autoantigen Sp-100 GN=SP100 Retinal dehydrogenase 2 GN=ALDH1A2 Serine/threonine-protein kinase Nek3 GN=NEK3 Spindle assembly abnormal protein 6 homolog GN=SASS6 SV=1 Tumor necrosis factor receptor

Experiment IL3, 24h

Fold changea -1.56

p 0.00078

29

RANTES, 1h

2.65

0.00566

3

93

IL3, 24h

-1.94

0.00198

3 7

2 1

56 266

IL5, 24h RANTES, 24h

-1.68 1000

0.00307 0.00042

Q04695

7

1

286

IL13, 1h

3.40

0.00388

Q7RTS7

3

1

57

IL13, 24h

-1000

0.00033

Q7L1W4

2

1

48

IL3, 1h

-1.62

0.00356

Q86WA8

4

2

70

IL5, 24h

-1.90

0.00495

Q9NZR2

11

7

133

IL3, 24h

4.53

0.00240

Q9Y6D9

3

2

65

IL13, 24h

-3.66

0.00100

P23497

5

2

78

GM-CSF, 24h

-1.78

0.00252

P23497

5

2

78

RANTES, 24h

3.63

0.00013

O94788

4

3

44

IL4, 1h

1.65

0.00119

P51956

3

2

50

IL3, 24h

-6.29

0.00585

Q6UVJ0 O00220

3 5

1 4

63 45

IL5, 24h Eot2, 24h

-1.72 -1.97

0.00477 0.00012

Accession Number P09525

Peptide count 5

Unique peptides 2

Score 101

P14868

2

1

Q86UK0

6

P11413 Q02539


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superfamily member 10A GN=TNFRSF10A a Fold change of +/- 1000 stands for +/- infinity



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48

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Table 3. Significant proteins from paired cytokine stimulation label-free LC-MS/MS experiments (p ≤ 0.025, |FC| ≥ 1.5) No.

1

2 3 4 5 6 7 8 9 10 11 12 13 14

Description 6-phosphogluconate dehydrogenase, decarboxylating GN=PGD 6-phosphogluconate dehydrogenase, decarboxylating GN=PGD 6-phosphogluconate dehydrogenase, decarboxylating GN=PGD Actin-related protein 2/3 complex subunit 3 GN=ARPC3 Actin-related protein 2/3 complex subunit 3 GN=ARPC3 Annexin A5 GN=ANXA5 Annexin A5 GN=ANXA5 Coactosin-like protein GN=COTL1 Galectin-10 GN=CLC Glucose-6-phosphate isomerase GN=GPI Glucose-6-phosphate isomerase GN=GPI Glutathione S-transferase P GN=GSTP1 Histone H2B type 1-B GN=HIST1H2BB Histone H3.1t GN=HIST3H3 Histone H3.1t GN=HIST3H3 Moesin GN=MSN Myosin light polypeptide 6 GN=MYL6 Myosin light polypeptide 6 GN=MYL6 Non-histone chromosomal protein HMG-17 GN=HMGN2 Protein S100-A6 GN=S100A6 Purine nucleoside phosphorylase

Accession Number

Peptide count

Unique peptides

Score

P52209

6

5

388

IL5+Eot2, 1h

1.52 0.00783

P52209

6

5

388

GMCSF+IL3, 1h

1.66 0.01887

P52209

6

5

388

GMCSF+IL3, 24h

-1.86 0.02371

O15145

2

2

72

IL5+Eot2, 1h

O15145 P08758 P08758 Q14019 Q05315

2 3 3 5 11

2 3 3 4 5

72 193 193 258 671

GMCSF+IL3, 1h GMCSF+IL3, 1h GMCSF+IL3, 24h IL5+Eot2, 1h IL5+Eot2, 1h

P06744

16

14

982

IL5+Eot2, 1h

2.00 0.00278

P06744

16

14

982

GMCSF+IL3, 1h

1.98 0.01186

P09211

6

6

476

GMCSF+IL3, 1h

2.40 0.02364

P33778 Q16695 Q16695 P26038 P60660 P60660

11 3 3 17 2 2

2 1 1 10 2 2

684 127 127 973 102 102

GMCSF+IL3, 24h IL5+Eot2, 1h GMCSF+IL3, 24h GMCSF+IL3, 1h IL5+Eot2, 1h GMCSF+IL3, 1h

-1.56 -2.25 -2.04 1.96 3.08 2.96

P05204 P06703 P00491

2 2 2

2 2 2

62 71 121

GMCSF+IL3, 1h GMCSF+IL3, 1h IL5+Eot2, 1h

16.59 0.00896 2.03 0.00533 2.41 0.01823


Experiment

Fold changea

p

2.97 0.00311 3.46 1.91 -2.70 2.54 3.97

0.00032 0.01540 0.02019 0.01261 0.02398

0.01904 0.00155 0.02151 0.01391 0.01023 0.01120

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48


GN=PNP Purine nucleoside phosphorylase GN=PNP Putative neutrophil cytosol factor 1B 15 GN=NCF1B Rho GDP-dissociation inhibitor 2 GN=ARHGDIB 16 Rho GDP-dissociation inhibitor 2 GN=ARHGDIB 17 Transketolase GN=TKT a Defined in Table 2.

P00491

2

2

121

GMCSF+IL3, 1h

2.46 0.00885

A6NI72

5

5

269

GMCSF+IL3, 1h

1.64 0.01418

P52566

6

6

374

GMCSF+IL3, 1h

1.64 0.00252

P52566 P29401

6 32

6 31

374 1787

GMCSF+IL3, 24h GMCSF+IL3, 1h

-1.52 0.00857 1.64 0.01525



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FIGURE LEGENDS Figure 1. Stimulation of purified quiescent eosinophils by eight cytokines for four durations. A) Sypro ruby stained abundance changes; and B), ProQ diamond stained phosphoprotein expression changes. Figure 2. Multivariate analysis of 2DGE results from 24 h single cytokine stimulated eosinophils. A, heat map of hierarchical clustering. Thirty-nine unique spots that changed abundance at the 24 h time-point (33 samples) were used as input. Protein spot intensities were normalized to Zscores before the calculation. The sample names and spot numbers used in this map are marked along the top and left side, respectively. The dendrograms drawn above and to the left of the map represent the independent clustering of samples and spots, respectively. Red cells represent higher than average protein expression compared to the mean value for each row; green, lower than average, and black, in between. Clustering method: unweighted average (UPGMA), similarity measure: Euclidean distance, ordering function: average value. For discussion, see text; and B) Principal Component Analysis of differential protein abundance after 24 h of stimulation (same input data as Figure 2A). Shown is a 3-D plot of Principal Components 1, 2, and 3 (PC1 vs. PC2 vs PC3), with dots representing samples. The color coding is: blue, IL-5; green, IL-3; red, GM-CSF; and grey, the remaining five cytokines used in the study. The variability’s preserved along PC1 was 45.8%, PC2, 8.6%, and PC3 7.6%. Figure 3. A) Hierarchical clustering of phosphoprotein changes after 1 h of cytokine stimulation displayed as a heat map. 50 unique spots changed phosphorylation at the 1 h time-point (29 samples) formed the input. PQD spot intensities normalized to Z-scores were used. The sample names and spot numbers used in this map are marked along the top and left side, respectively. The dendrogram drawn above and to the left of the map represent the independent clustering of samples and spots, respectively. Red cells represent high expression of protein phosphorylation


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compared to mean values; green, low; and black, in between. For discussion, see text; B) Principal Components Analysis of protein abundance after 24 h of stimulation (same data as Figure 3A). Shown is the plot of PC1 vs. PC2, with dots representing samples. Color coding: blue, IL-5; green, IL-3; red, GM-CSF, and grey, the remaining cytokines used in the study. The variability’s preserved along PC1 was 48.0%, PC2, 7.1%, and PC3, 6.0%. Figure 4. 2DE gel protein spot positions of the 131 proteins and phosphoproteins identified with high confidence in the single cytokine-stimulated experiments. The pI and MW scales are indicated. Proteins are represented by their gene symbols (more mnemonic than protein accession codes) that follow in alphabetical order: ACTB - Actin, cytoplasmic 1; ACTG1 - Actin, cytoplasmic 2; ACTN4, Alpha actin 4, short isoform; ACTR3, Actin-related protein 3; ALDOA, Fructose-bisphosphate aldolase; ANXA1 – Annexin A1; ANXA6, Annexin (Fragment); ARHGDIB, Rho GDP-dissociation inhibitor 2 (fragment); BID - Isoform 2 of BH3-interacting domain death agonist; CAP1 - Adenylyl cyclase-associated protein 1; CAPZB - Isoform 2 of Factin-capping protein subunit beta; CAT - Catalase; CFL1 - Cofilin 1 (Non-muscle), isoform CRA_a; CLC - Eosinophil lysophospholipase; CORO1A - Coronin-1A; CS - Citrate synthase, mitochondrial; EEF1G - Elongation factor 1-gamma; ENO1 - Alpha-enolase; EPX - Eosinophil peroxidase;

G6PD

-

Glucose-6-phosphate

1-dehydrogenase

(Fragment);

GAPDH

-

Glyceraldehyde-3-phosphate dehydrogenase; GCA – Grancalcin; GSN – Gelsolin; GSS Glutathione synthetase; HBA1 – Hemoglobin subunit alpha; HBB – Hemoglobin submit beta; HDHD2 - Haloacid dehalogenase-like hydrolase domain-containing protein 2 (Fragment); HIST1H4A

-

Histone

H4;

HNRNPA2B1

-

Isoform

A2

of

Heterogeneous

nuclear

ribonucleoproteins A2/B1; HNRNPD - Isoform 3 of Heterogeneous nuclear ribonucleoprotein; HSPA9 - Stress-70 protein, mitochondrial (Fragment); KRT1 - Keratin, type II cytoskeletal 1; KRT10 - Keratin, type I cytoskeletal 10; KRT16 - Keratin, type I cytoskeletal 16; KRT2 - Keratin, type II cytoskeletal 2 epidermal; KRT9 - Keratin, type I cytoskeletal 9; LSP1 - Lymphocyte-



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specific protein 1 (Fragment); LTF - Isoform Delta Lf of Lactotransferrin; MSN – Moesin; MYL12A - Myosin regulatory light chain 12A; NCF1C - Putative neutrophil cytosol factor 1C; NONO - Non-POU domain-containing octamer-binding protein; PDIA3 - Protein disulfide isomerase family A, member 3, isoform CRA_b; PFN1 - Profilin 1, isoform CRA_b; PGK1 Phosphoglycerate kinase 1; PGLS - 6-phosphogluconolactonase; PKM - Pyruvate kinase (Fragment); POTEF - POTE ankyrin domain family member F; PPBP - Platelet basic protein; PRDX1 – Peroxiredoxin 1; PSMA4 - Proteasome subunit alpha type (Fragment); RPA2 Replication protein A 32 kDa subunit; S100A8 - Protein S100-A8; SERPINB1 - Leukocyte elastase inhibitor; SH3BGRL3 - SH3 domain-binding glutamic acid-rich-like protein 3; STIP1 Stress-induced-phosphoprotein 1; STMN1 - Stathmin (Fragment); TAGLN2 - Transgelin-2; TALDO1 – Transaldolase; TKT – Transketolase; TPT1 - TPT1 protein; TUBA1B - Tubulin alpha1B chain; TUFM - Elongation factor Tu, mitochondrial; UGP2 - Isoform 2 of UTP--glucose-1phosphate uridylyltransferase; VASP - Vasodilator-stimulated phosphoprotein; VCL – Vinculin; YWHAZ – 14-3-3 protein zeta/delta. Figure 5. Hierarchical clustering comparison of paired cytokines with single cytokine eosinophil stimulation. A) Sypro Ruby stained protein expression results from 102 proteins; B) Heat map same as 5A but using results of ProQ Diamond staining of the same 102 protein spots. Figure 6. Functional classification of the combined set of significant proteins from the 2DGE and Label-free MS analyses, obtained by Ingenuity Pathway Analysis. The lengths of the bars are -log10(p), where p is the probability that the specific combination of proteins found in the group occur in it at random. The longer the bar, the higher the probability that the disease or function is associated with eosinophil activation. A) Based on the proteins identified in the single cytokine stimulation; and B) based on paired cytokine stimulations in 2DGE and label-free experiments.


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Figure 7. Flow cytometry results: CD69 expression, of eosinophil activation was monitored using a fluorescent antibody. Purified quiescent peripheral blood eosinophils were stimulated with cytokines as shown. The y-axis shows fold-change in CD69 expression with respect to control. A) Stimulation with single cytokines for thedurations shown; and B) separate experiment: stimulation for 24 h with single cytokines compared with paired (blue).



30

B Number of spots showing differential phosphorylation

A Number of spots showing differential abundance

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25 20 15 10 5 0 15min

1h

4h

30 25 20 15 10 5 0 15min

24h

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1h

4h

24h

IL-5

Eot-1

Eot-2

IL-5

Eot-1

Eot-2

GM-CSF

IL-3

IL-13

GM-CSF

IL-3

IL-13

IL-4

RANTES

IL-4

RANTES

Figure 1 40 ACS Paragon Plus Environment

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A

Figure 2A



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B

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PC2

PC1 PC3

Figure 2B 42 ACS Paragon Plus Environment

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A

Figure 3A



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PC2

B

PC1

PC3

Figure 3B


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Figure 4



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A


Figure 5A

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B


Figure 5B


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48

-log(p value)

threshold 0

2

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4

6

8

10

12

14

16

18

Cellular movement ------------------Immunological disease ------------Hematological disease ------------Inflammatory disease --------------Inflammatory response ------------Respiratory disease ----------------Free radical scavenging -----------Cell death and survival ------------Dermatol. Diseasses & conditions Cellular growth & proliferation ----

Figure 6A


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threshold 0

2.5

-log(p value) 5.0

7.5

10.0

12.5

15.0

17.5

20.0

22.5

Immunological disease ------------Cellular movement ------------------Hematological disease ------------Inflammatory disease --------------Inflammatory response ------------Respiratory disease ----------------Dermatol. Diseasses & conditions Cell death and survival ------------Cancer---------------------------------Dermatol. Diseasses & conditions

Figure 6B


50

ACS Paragon Plus Environment

Figure 7

IL-5 + IL-13

IL-5 + Eotaxin-2

IL-2 + IL-4

IFNγ + TNFα

IFNγ + IL-13

GM-CSF + IL-3

TNFα

IL-13

IL-5

IL-4

IL-3

IL-2

IFNγ

unlabeled cells isotype control control-1 h control-4 h control-24 h Eotaxin-1-1 h Eotaxin-1-4 h Eotaxin-1-24 h Eotaxin-2-1 h Eotaxin-2-4 h Eotaxin-2-24 h GM-CSF-1 h GM-CSF-4 h GM-CSF-24 h IL-3-1 h IL-3-4 h IL-3-24 h IL-4-1 h IL-4-4 h IL-4-24 h IL-5-1 h IL-5-4 h IL-5-24 h IL-13-1 h IL-13-4 h IL-13-24 h RANTES-1 h RANTES-4 h RANTES-24 h

A

GM-CSF

Eotaxin-2

B

Control

Isotype Control

Unlabeled cells

CD69 Foldchange

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 CD69 Fold-change

Journal of Proteome Research Page 50 of 51

Single cytokine stimulation

9.0

8.0

7.0

6.0

5.0

4.0

3.0

2.0

1.0

0.0

Single and paired cytokine stimualtion

9.0

8.0

7.0

6.0

5.0

4.0

3.0

2.0

1.0

0.0

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For TOC Only

Eotaxin 2

GM-CSF

Eotaxin 1

EOSINOPHIL ACTIVATION

IL-3

— Proteins — Phosphoproteins

IL-4

IL-5 IL-13

RANTES

ACS Paragon Plus Environment

PROTEOME ANALYSIS

Activation of Human Peripheral Blood Eosinophils by Cytokines in a

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