Mercury Alters B-Cell Protein Phosphorylation ... - ACS Publications

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Mercury Alters B-Cell Protein Phosphorylation Profiles Nicholas John Carruthers, Paul Martin Stemmer, Namhee Shin, Alan Anthony Dombkowski, Joseph Anthony Caruso, Randall Gill, and Allen Jay Rosenspire J. Proteome Res., Just Accepted Manuscript • Publication Date (Web): 13 Nov 2013 Downloaded from http://pubs.acs.org on November 26, 2013

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Journal of Proteome Research

Mercury Alters B-Cell Protein Phosphorylation Profiles

Nicholas J. Caruthers1, Paul M. Stemmer1,*, Namhee Shin1, Alan Dombkowski2, Joseph A. Caruso1, Randal Gill3, Allen Rosenspire3

1. Institute of Environmental Health Sciences, Wayne State University; 2. Department of Pediatrics, Wayne State University; 3. Department of Immunology, Wayne State University

ABSTRACT Environmental exposure to mercury is suggested to contribute to human immune dysfunction. To shed light on the mechanism we identified changes in the phosphoproteomic profile of the WEHI-231 B cell line after intoxication with Hg2+. These changes were compared to changes in the phosphoproteome that were induced by pervanadate or okadaic acid exposure. Both 250 µM HgCl2 and pervanadate, a known phosphotyrosine phosphatase inhibitor, caused an increase in the number of proteins identified after TiO2 affinity selection and LC-MS/MS analysis. Pervanadate treatment had a larger effect than Hg2+ on the number of Scansite motifs which were tyrosinephosphorylated, 17, and Ingenuity canonical signaling pathways activated, 4 with score > 5.0. However, Hg2+ had a more focused effect, primarily causing tyrosine1 ACS Paragon Plus Environment


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phosphorylation in SH2 domains in proteins that are in the B cell receptor signaling pathway. The finding that many of the changes induced by Hg2+ overlap with those of pervanadate, indicates that at high concentrations Hg2+ inhibits protein tyrosine phosphatases.

KEYWORDS mercury, Hg2+, toxicology, B cell, WEHI-231, phosphoproteomics, phosphoprotein, phosphotyrosine, TiO2, mass spectrometry

INTRODUCTION Mercury is distributed in the global environment by both natural geologic processes and human activities 12. Consequently large segments of the world’s population are exposed to the metal through water, air, food, and dental amalgam. Mercury is clearly toxic, and exposure to high or even moderate levels of organic methyl mercury (MeHg), inorganic mercury (Hg2+) or metallic mercury (Hg0) is well established to damage the nervous and immune systems, resulting in neurological and immunological deficiencies in humans 3-5. Epidemiological studies now suggest that exposure to environmental mercury at current common levels, which have been perceived to be non-toxic, may contribute to immune system dysfunction and development or progression of autoimmune disease in humans 612

. This view is supported by experiments in mouse models of autoimmune disease. In

most genetically autoimmune prone mouse strains, exposure to low levels of Hg2+

2 ACS Paragon Plus Environment

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exacerbates disease 13-16, and in mice not prone to autoimmunity low levels of Hg2+ exacerbate disease in several models of induced (acquired) autoimmunity 6,17,18.

Autoimmune disease arises when autoreactive B and T cells, which are normally held in check by mechanisms collectively known as central and peripheral tolerance, become desuppressed. Central tolerance refers to the mechanisms by which newly developing immature T cells and B cells are rendered non-reactive to self. These mechanisms are distinct from peripheral tolerance in that they involve the T Cell Receptor (TCR) and B Cell Receptor (BCR) clonotypic receptors and occur only in immature cells, prior to export into the periphery. Peripheral tolerance requires activation of other receptor systems and develops only after T and B cells mature and enter the periphery. Disruption of either mechanism can result in autoimmune disease. Unfortunately most of the studies connecting mercury to autoimmune disease give little guidance as to what the mechanism or mechanisms responsible for the linkage might be. In other words, we do not know how exposure to mercury compromises central and/or peripheral tolerance. This lack of information represents a major gap in our understanding of how environmental mercury interacts with the immune system to promote the development of autoimmune disease.

Recently there has been increased recognition of the essential role played by autoreactive B cells and of autoantibodies produced by B cell derived plasma cells in the pathology of a variety of autoimmune diseases 19. To a large extent B cell (as well as T cell) tolerance depends upon phosphoprotein mediated signaling. Since mercury inhibits cellular phosphatase activity 20, one possible mechanism for mercury disruption of central



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tolerance in B cells is the inhibition of critical phosphatases resulting in an aberrant increase in protein phosphorylation. In the studies described here, we have utilized modern mass spectroscopic technology to investigate the effect of mercury on the phosphoproteome in the WEHI-231 mouse B cell line, a well-studied model system known to possess many of the characteristics of immature B cells. The objectives of this study were to determine whether mercury caused an increase in protein phosphorylation in B cells and to identify specific phosphoproteins and their associated signaling pathways most likely to be molecular targets of mercury.

Global phosphoproteomic analysis has recently become possible through the application of affinity selection of phosphopeptides and mass spectrometric identification of those peptides 21-23. Specifically, the WEHI-231 cell line has been profiled resulting in identification of 107 phosphoproteins and 193 phosphorylation sites in one study 24 and over 400 proteins in another 25. This is a relatively modest slice of the entire phosphoproteome as it is predicted that up to 100,000 sites could be phosphorylated in the complete proteome 26 . Of equal or even greater importance in the profiling of phosphopeptides is the quantification of the change in phosphorylation after an experimental intervention or environmental exposure. Mass spectrometry enables multiplex analysis by using isotopically distinct labels for different samples 27,28 but can also be used in a label independent way by quantitating based on the number of spectra observed 29,30 . For instance a recent study utilizing these methods examining global protein phosphorylation dynamics during deoxyvynivalenol-induced ribotoxic stress in macrophages has identified extensive and unexpected changes to the macrophage


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phosphoproteome 31. For the work presented in this paper we quantified the abundance of phosphopeptides and phosphoproteins using the spectral counting strategy.

Material and Methods

Materials: Acetic Acid was from BDH Chemicals (through VWR, Radnor, PA), CaCl2 was from Orion, TFA (trifluoroacetic acid) was from Fisher Scientific (Pittsburgh, PA) and formic acid was from EMD. (Billerica, MA). TPCK (L-1-tosylamido-2-phenylethyl chloromethyl ketone)-treated bovine pancreas trypsin and all other reagents including solvents used for HPLC were the highest grade available from Sigma-Aldrich. (St Louis, MO). TiO2, 5 micron, was from GL Sciences.

Cell Culture: WEHI-231 cells were obtained from the American Type Culture Collection. Cells were maintained on RPMI 1640 supplemented with 10% fetal bovine serum, 2 mm glutamine, 50 µM mercaptoethanol, 100 U/ml penicillin and 100 µg/ml streptomycin in a humidified 5% CO2 atmosphere. Cells were passaged three times a week and harvested for experiments while in logarithmic growth.

Exposure and Harvesting: Cells were pelleted then resuspended at 5 x 106 cells per ml for exposure to HgCl2 (Hg2+) at 100 µM or 250 µM, pervanadate at 25 µM or okadaic acid at 100 nM. Following a 10 minute exposure in RPMI 1640 to the test agent the cells were washed twice in ice cold Hanks’ solution then pelleted and frozen. The treatments were divided into two separate experiments: the first experiment included 250 µM Hg2+,



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100 nM okadaic acid and an untreated control, the second experiment included 100 µM Hg2+, 25 µM pervanadate and an untreated control. The first experiment was carried out using 3 independent samples per treatment and the second experiment with 4 independent samples per treatment.

Sample Preparation: Cell pellets were lysed in Tris, 20 mM pH 8.0, SDS, 0.5%, LiFl, 1.0 mM and Na3VO4, 0.1 mM then supernatant from a 20,000 x g centrifugation was taken for analysis. Protein in lysates was determined using a BCA assay (bicinchoninic acid assay; Pierce, Rockford, IL). Samples were digested overnight with 1:100 trypsin at a sample protein concentration of 1.0 mg/ml in buffer containing Tris, 20 mM, SDS, 0.1%, LiF, 1.0 mM, Na3VO4, 0.1 mM and 10% acetonitrile. All samples were evaluated by SDS-PAGE to ensure full digestion of the samples before proceeding to phosphopeptide isolation. Phosphopeptides were isolated from 1 mg of digested cell protein using 2 sequential incubations each with 2 mg of 5 µ TiO2 beads for the first experiment. Phosphopeptide enrichment for the first and second affinity selections was 89 and 93 %, respectively, indicating that additional phosphopeptides could be harvested by increasing the ratio of TiO2 beads to protein without compromising the selectivity. Therefore, the second experiment used a single incubation with 6 mg of 5 µ TiO2 beads for each sample. The selectivity of the 6 mg of 5 µ TiO2 procedure was 98%. Cell digests were incubated with TiO2 in 2% TFA saturated with glutamic acid in 60% acetonitrile. The beads were washed three times with 1% TFA in 60% acetonitrile before eluting phosphopeptides with NH4OH in 50% acetonitrile. TiO2 eluates were neutralized with formic acid, dried


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under vacuum and stored at -80°C until analysis. Eluted peptides solubilized in 0.1% formic acid were then analyzed by LC-MS/MS without further purification.

Mass Spectrometry: All analyses were performed on a Thermo LTQ equipped with ETD (ThermoFisher Scientific, Watham, MA). Samples were loaded on a peptide Captrap (Michrom, Auburn, CA) trapping column and peptide separations achieved using a linear gradient of 5% to 35% acetonitrile to elute from a Majic 0.1 mm x 150 mm AQ C18 column (Michrom). The first experiment had data from two TiO2 selection steps that were run separately on the mass spec. The .raw files were combined during database searching and a total of 233,195 spectra from 9 samples were submitted for that experiment. The second experiment, with 100 µM Hg2+ or pervanadate, has only one TiO2 elution. Those 12 samples yielded a total of 239,443 spectra. LC-MS/MS for the second treatment group was run in a neutral loss mode so that high abundance precursor neutral losses of 24.25, 32.66, or 49.00 m/z found in an MS2 spectrum were selected for MS3 analysis. The first experiment LC-MS/MS did not incorporate a neutral loss scan.

Database Searching: Tandem mass spectra were extracted by Proteome Discoverer (ThermoFisher Scientific) version 1.4.0.288. Charge state deconvolution and deisotoping were not performed. All MS/MS data were analyzed using Mascot (Matrix Science, London, UK; version 2.4.0) and X! Tandem (The GPM, thegpm.org; version CYCLONE (2010.12.01.1)). Mascot and X!Tandem were each set up to search the 2013_04 release of the SwissProt database (selected for Mus musculus, 16611 entries) assuming the digestion enzyme trypsin. Spectra were searched with a fragment ion mass tolerance of



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0.70 Da and a parent ion tolerance of 3.5 Da. The iodoacetamide derivative of cysteine was specified as a fixed modification. Oxidation of methionine, acetylation of the nterminus and phosphorylation of serine, threonine and tyrosine were specified as variable modifications.

Criteria for Protein Identification: Scaffold (version 4.0.5, Proteome Software Inc., Portland, OR) was used to validate MS/MS based peptide and protein identifications. Peptide identifications were accepted if they could be established at greater than 95.0% probability by the Peptide Prophet algorithm32 . Protein identifications were accepted if they contained at least one identified phosphopeptide and had a Protein Prophet probability greater than 80%. Proteins that contained similar peptides and could not be differentiated based on MS/MS analysis alone were grouped to satisfy the principles of parsimony. All subsequent analysis of protein sets included all proteins or peptides that met the criteria for identification without weighting for the level of confidence in the identification.

Ascore Filtering: The Ascore algorithm was applied to phosphopeptides that met identification criteria and had multiple possible phosphorylation sites in order to determine which site or sites were likely to be modified and the confidence in those localizations33 . Site localization was accepted if the Ascore algorithm indicated at least 95% confidence in the assignment. Peptide identification data were imported into Scaffold PTM (Version 2.1.1, Proteome Software) software where the Ascore algorithm was implemented.


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Motif Analysis: Ascore-filtered phosphorylation sites were searched against a database of putative protein kinase target motifs and phosphorylation-dependent binding motifs predicted by Scansite 34. Scansite uses data from oriented peptide library and phagedisplay experiments to generate position-specific scoring matrices that are queried against sequence databases to predict kinase target and domain binding sites. Our data were searched against the high stringency Scansite data that only include sites that fell within the top 0.2% of scores for each motif. All identified proteins were submitted to the Scansite web service (http://scansite3.mit.edu). Motifs identified in those proteins were retrieved and the invariant residue (the modified residue) for each was searched against our Ascore-filtered phosphorylation sites

Pathway Enrichment Analysis: Sets of proteins that were modified by the treatments were examined for overrepresented pathways using the IPA (Ingenuity Systems Inc., Redwood City, CA) Global Canonical Pathway Analysis (Content version: 14855783 (Release Date: 2013-02-05)). Pathways in the ingenuity canonical pathway database were tested for significant associations with the protein sets described in the results section using Fisher’s exact test with all mouse genes in the ingenuity knowledgebase as background.

Statistical Analysis: Statistical tests were carried out in R version 3.0.0 except for the ANOVA tests of protein normalized spectral counts which were carried out in DanteR version 0.2 35. The sets of modified proteins were maximized for subsequent analysis by



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accepting statistical test results without correction for multiple testing unless otherwise stated. Proportional Venn diagrams were made with the EulerAPE tool available at http://www.eulerdiagrams.org/eulerAPE/. Where a value and range are reported, those values represent the mean and standard deviation.

RESULTS

The depth of phosphoproteome coverage and the magnitude of global phosphorylation changes observed in WEHI-231 cells treated with Hg2+, okadaic acid or pervanadate are shown in figure 1. Two separate experiments were run to evaluate the ability of Hg2+ to modulate the phosphoproteome in WEHI-231 cells. The TiO2 selection was effective for phosphopeptides, as indicated by 92% and 98% of all identified peptides being phosphopeptides in the first and second experiment, respectively. In the first experiment, (Figure 1, panels A & B; Supplemental Tables S1 and S3) WEHI-231 cells were exposed to 250 µM Hg2+ or 100 nM okadaic acid for 10 minutes. The concentrations of each agent were selected to achieve a maximal effect on Hg2+-responsive pathways and phosphatase Type-1 and Type-2A substrates, respectively. In this experiment 688 proteins were identified with 95% confidence at the peptide level and a 0.7% false discovery rate at the protein level. The names of proteins in the groups depicted in figure 1 A and B are provided in supplementary tables S1 and S2 respectively. In addition, for proteins that were identified by only one peptide, the Peptide Prophet scores and mass


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deviations are provided in supplementary tables S3 and S4. All protein identifications and mass spectra have been submitted to the PRIDE database. In an attempt to collect additional phosphopeptides and achieve greater depth of coverage the second experiment used 6 mg of TiO2 per mg of protein for the phosphopeptide selection, rather than the 4 mg used in the first experiment. Changing the experimental procedure for TiO2 selection of phosphopeptides had no discernible effect on the number of proteins or peptides identified in any run, indicating that a representative set of phosphopeptides was selected each time. The addition of a neutral loss scan in the second experiment resulted in a 4.3 % decrease in the number of phosphosites identified in control samples with no change in the distribution of spectra based on the type of phosphorylated residue. This indicates that for the TiO2 selected samples in this study the depth of coverage was limited by the degree of chromatographic fractionation after phosphopeptide selection. A review of the literature has shown that mercury can interact with cellular systems in a great variety of ways 36. It is also known that protein phosphatases, and protein tyrosine phosphatases in particular, are susceptible to oxidation because they contain cysteine residues in their active sites 37. As mercury is well known to irreversibly bind to cysteine residues38, we hypothesized that one prominent mechanism by which mercury could modulate the phosphoproteome would be via tyrosine phosphatase inhibition. In addition, several phosphoserine/phosphothreonine phosphatases are sensitive to oxidative stress39. Mercury could act to inhibit phosphatase activity by direct sulfhydryl binding in active site Cys residues or indirectly via oxidative stress.



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An increase in cellular protein phosphorylation should result in an increase in the number of phosphoproteins and phosphopeptides detected by mass spectrometry after TiO2 phosphopeptide selection. When the data for Hg2+ exposed cells were compared to control, the 250 µM Hg2+ caused the number of phosphoproteins and unique phosphopeptides to increase by 166 and 321. Normalized spectral counts were used to measure protein abundance and ANOVA to identify proteins that had altered abundance in response to treatment. This analysis identified 180 proteins that had changes (p < 0.05) in spectral count abundance. Treatment with 250 µM Hg2+, in addition to increasing the number of peptides and proteins identified, also increased the variability in the proteins that were identified between replicate runs so that 30.0% of the proteins identified in 250 µM Hg2+ treated cells were observed in just one of the three samples while only 21.4% were identified in just one control sample and 24.0% of proteins were identified in just one of the okadaic acid treated samples. Proteomics experiments using data-dependent analysis typically identify variable sets of proteins between technical replicates so that 30% or more of proteins in one analysis won’t be found in a replicate analysis 40. The data presented here were from independent biological samples that are expected to have greater variability than technical replicates so the estimate of 30% variability between samples represents a reasonable best case outcome.

In the second experiment (Figure 1, panels C & D; Supplemental Tables S2 and S4), the Hg2+ concentration was decreased to 100 µM to achieve greater specificity of action and pervanadate, a known inhibitor of phosphotyrosine phosphatases, was introduced as a positive control. Pervanadate acts, as we hypothesize mercury acts, by two mechanisms


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for inhibition of pTyr phosphatase activity: directly by competitive phosphatase inhibition or indirectly by oxidative inactivation41. It was used at 25 µM to achieve maximal inhibition of phosphotyrosine phosphatases. In the second experiment 607 proteins were identified with 95% confidence at the peptide level and a 1.8% false discovery rate at the protein level. Pervanadate treatment increased the number of phosphoproteins by 51 and phosphopeptides by 91 over control. ANOVA identified 160 proteins that had changes in normalized spectral counts (p < .05) due to pervanadate treatment and 53 that had changes due to 100 µM Hg2+. Like Hg2+, pervanadate increased the variability of protein identifications between samples, resulting in 24.7% of all identified proteins being identified in just one out of four samples, compared to 18.9% in controls. Cells treated with 100 µM Hg2+ had 22.4% of their proteins identified in just one out of four samples.

In the two experiments the 250 µM Hg2+ and the 25 µM pervanadate groups have the greatest number of phosphoproteins and phosphopeptides identified. In contrast, the actions of 100 nM okadaic acid and 100 µM Hg2+ were very modest. Okadaic acid caused an increase of only 56 proteins and 76 peptides over control and the 100 µM Hg2+ exposure group had a decrease of 8 proteins and 4 peptides compared to control (table 1). Protein spectral counts were compared between okadaic acid treated and control cells using ANOVA and 37 proteins were found to be different at the p2 fold unique to (p2 fold >2 fold Phospho Peptides unique to (P

Mercury Alters B-Cell Protein Phosphorylation ... - ACS Publications

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