Acidosis-Induced Changes in Proteome Patterns of ... - ACS Publications

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Journal of Proteome Research

Acidosis-Induced Changes in Proteome Patterns of the Prostate Cancer-Derived Tumor Cell Line AT-1

Angelika Ihling1, Christian H. Ihling2, Andrea Sinz2, Michael Gekle1*

1

Julius Bernstein Institute of Physiology, Martin-Luther University Halle-Wittenberg,

Magdeburgerstrasse 6, D-06112 Halle (Saale), Germany 2

Department of Pharmaceutical Chemistry & Bioanalytics, Institute of Pharmacy, Martin-

Luther University Halle-Wittenberg, Wolfgang-Langenbeck-Str. 4, D-06120 Halle (Saale), Germany

*Address correspondence to: Michael Gekle, Julius Bernstein Institute of Physiology, Martin-Luther University Halle-Wittenberg, Magdeburger Straße 6, D-06112 Halle (Saale), Germany; Tel.: +49 345 557 1886; Fax: +49 345 557 4019; E-mail: [email protected]

Running title: Acidosis-Induced Changes in Proteome Pattern of AT-1 Cells Keywords: Acidosis, Cancer cell, Gene expression, Labelling, LC-MS/MS

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ABSTRACT Under various pathological conditions, such as inflammation, ischemia and solid tumors, physiological parameters (local oxygen tension or extracellular pH) show distinct tissue abnormalities (hypoxia and acidosis). For tumors, the prevailing microenvironment exerts a strong influence on the phenotype in respect to proliferation, invasion, and metastasis formation and therefore influences prognosis. In this study, we investigate the impact of extracellular metabolic acidosis (pH 7.4 versus pH 6.6) on the proteome patterns of a prostate cancer-derived tumor cell type (AT-1) using isobaric labeling and LC-MS/MS analysis. In total, 2710 proteins were identified and quantified across four biological replicates, of which seven were significantly affected with changes >50 % and used for validation. Glucose transporter 1 and farnesyl pyrophosphatase were found to be down-regulated after 48 h of acidic treatment, while metallothionein 2A was reduced after 24 h and returned to control values after 48 h. After 24 h and 48 hours at pH 6.6, glutathione S transferase A3 and NAD(P)H dehydrogenase 1, cellular retinoic acid-binding protein 2 and Na-bicarbonate transporter 3 levels were found to be increased. The changes in protein levels were confirmed by transcriptome and functional analyses. In addition to the experimental in depth investigation of proteins with changes >50 %, functional profiling (statistical enrichment analysis) including proteins with changes >20 % revealed that acidosis up-regulates GSH-metabolic processes, citric acid cycle and respiratory electron transport. Metabolism of lipids and cholesterol biosynthesis were downregulated. Our data are the first comprehensive report on acidosis-induced changes in proteome patterns of a tumor cell line.


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INTRODUCTION Under various pathological conditions, such as inflammation, ischemia and solid tumors, physiological parameters, i.e., local oxygen tension or extracellular pH, show distinct abnormalities (hypoxia or acidosis) in the tissue. These factors in turn impair cell function and phenotype and modulate pathological processes, either aggravating or ameliorating them. The development of an extracellular acidosis is the result of the production and release of metabolic acids by the cells (metabolic acidosis) or a hampered removal of CO2 (non-metabolic acidosis). Extracellular acidosis acts on all cells in the tissue and may lead to a number of cellular responses, resulting in the activation of distinct signaling or transcription processes. However, the impact of acidosis on different signaling networks and protein expression patterns is not comprehensively understood. For tumors, the prevailing microenvironment can exert a strong influence on the phenotype concerning proliferation, invasion, and metastasis formation. The tumor microenvironment is characterized by structural and functional aberrations of the vascular network leading to insufficient supply of the tumor with oxygen and nutrients, which will ultimately result in a changed tumor metabolism. Tumor cells undergo metabolic reprogramming, switching the energy metabolism towards glycolysis [1,2]. Elevated formation of lactic acid by glycolysis in combination with the reduced ability to remove tumor-derived protons due to poor perfusion leads to pronounced extracellular acidosis with pH values of lower than 6.0 [3–6]. The acidic tumor microenvironment promotes angiogenesis [7,8], suppresses antitumoral immune response [9,10], and affects invasiveness and metastasis formation [6,11,12]. Recently, we have described the effect of metabolic acidosis on selected signaling pathways and the expression of a number of inflammation-related genes in fibroblasts and tumor cells [13–15]. We characterized the behavior of AT-1 cells under acidic condition with respect to pHhomeostasis and signaling in detail, giving us now the opportunity to investigate changes of 3 ACS Paragon Plus Environment


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the proteome under well-defined conditions. AT-1 cells establish a reverse pH-gradient (pHi > pHe) during extracellular acidosis in comparison to normal physiological conditions (pHe>pHi) [13], which is in agreement with the situation already described for tumor cells [12,16,17]. Maintenance of this reversed pH gradient results from the ability of cancer cells to sense pH changes and respond to sustain pH homeostasis [3,18]. Furthermore, we showed that the activity of important signaling pathways is affected, leading to an altered expression of pathologically relevant genes. Although these studies – in concurrence with various other reports [19–21] - underscore the impact of extracellular acidosis on gene expression, they do neither provide a comprehensive picture of the effects on transcription, nor on changes in protein expression patterns, as changes in mRNA levels do not necessarily translate to changes in protein synthesis that are fundamental for an altered cellular phenotype. Therefore, we investigated the impact of extracellular acidosis (pH 7.4 versus pH 6.6) on the proteome pattern of the prostate cancer-derived tumor cell line AT-1 at 24 and 48 hours incubation times using isobaric peptide mass tags TMT 10-plex for reporter ion quantification after LC-MS/MS analysis. Differences in expression levels were assessed by high stringency criteria, including (i) 4 out of 4 biological replicates exhibited qualitatively identical changes in the acidosis group, (ii) a minimum of two unique peptides were identified per protein with high confidence and (iii) at least 4 PSMs of unique peptides contributed to the quantification of the protein. The detected changes in protein levels were verified on the mRNA level and also by functional analysis. To our best knowledge, our data are the first report on acidosis-induced changes in the proteome pattern of a tumor cell line.


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EXPERIMENTAL SECTION General --- If not stated otherwise, chemicals were purchased from Sigma-Aldrich, Munich, Germany. All reagents for MS analysis were obtained at the highest purity. All nano-HPLC solvents (LC/MS grade) were obtained from VWR. TMT 10-plex (tandem mass tag) labeling reagents were obtained from Thermo Fisher Scientific.

Cell culture --- The subline AT-1 of the rat R-3327 Dunning prostate carcinoma (CLS, Eppelheim) was used as described before [22]. Cells were grown in RPMI medium supplemented with 10% fetal calf serum (FCS) at 37°C under a humidified 5% CO2 atmosphere and sub-cultivated twice per week. For the experiments, cells were transferred to a medium without additional FCS supplementation 24 h before starting incubation. Control cells were exposed to bicarbonate-HEPES buffered Ringer solution adjusted to pH 7.4 (24 mM NaHCO3, 0.8 mM Na2HPO4, 0.2 mM NaH2PO4, 86.5 mM NaCl, 5.4 mM KCl, 1.2 mM CaCl2, 0.8 mM MgCl2, 20 mM HEPES; pH was adjusted with 1 N NaOH). Extracellular acidosis (pH 6.6) was applied using bicarbonate-MES (morpholinoethanesulfonic acid) buffered Ringer solution (4.5 mM NaHCO3, 0.8 mM Na2HPO4, 0.2 mM NaH2PO4, 106.0 mM NaCl, 5.4 mM KCl, 1.2 mM CaCl2, 0.8 mM MgCl2, 20 mM MES; pH was adjusted to 6.6 with 1 N NaOH). The buffer capacity (β) was 5.9 mM·∆pH for the bicarbonate-HEPES buffered Ringer solution at pH 7.4 and 3.9 mM·∆pH for the bicarbonate-MES buffered Ringer solution. For incubation periods longer than 6 h, RPMI medium buffered with 10 mM HEPES and 10 mM MES was used and adjusted to pH 7.4 or pH 6.6 with 1 M HCl.

Protein isolation and TMT labeling --- For TMT labeling experiments, tumor cells were cultured in 6-cm culture dishes and collected after incubation periods of 24 h and 48 h. Cells were washed, harvested, and lysed in 150 µl RIPA buffer (50 mM Tris HCl, pH 7.4, 150 mM NaCl, 1 mM EDTA, 1% Triton X-100, 1% sodium deoxycholate, 0.1% SDS with protease 5 ACS Paragon Plus Environment


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inhibitors). The samples were homogenized by sonication on ice and the soluble proteins were quantified by BCA analysis (Thermo Fisher Scientific). Aliquots of cell lysates (100 µg total protein) were mixed with a fourfold volume of ice-cold acetone and incubated overnight at 20 °C. Precipitated proteins were pelleted by centrifugation at 14,000 g for 30 min. Pellets were resuspended in 30 µl of an aqueous solution of 8 M urea, 0.5 M HEPES, pH 8.5 and 10 mM TCEP (tris[2-carboxyethyl]phosphine). The solutions were kept at 37 °C for 1 h to allow for a full denaturation of proteins and reduction of disulfide bonds. Protein concentrations were determined by Bradford assay (Thermo Fisher Scientific); 40-µg aliquots were taken and the volumes were adjusted to 25 µl with 8 M urea, 0.5 M HEPES, pH 8.5. 1 µl of a 0.5 M iodoacetamide solution was added (final concentration 20 mM). Samples were incubated for 30 min at room temperature to alkylate cysteine residues. For protein digestion, 1 µg LysC was added and samples were incubated at 37 °C for 2 h. Afterwards, samples were diluted with water to a final concentration of 1 M urea and 1 µg trypsin was added before incubation at 37 °C overnight. For isobaric labeling, amine-reactive N-hydroxysuccinimide ester TMT-10 plex reagents (Thermo Fisher Scientific) were used: Using eight out of the ten labeling reagents, for each biological replicate, two technical replicates could be processed in parallel. The resulting eight individual samples were labeled as follows: replicate 1, 24 h at pH 7.4 (TMT 126); repl. 1, 24 h at pH 6.6 (TMT 127C); repl. 2, 24 h at pH 7.4 (TMT 127N); repl. 2, 24 h at pH 6.6 (TMT 128C); repl. 1, 48 h at pH 6.6 (TMT 129C); repl. 1, 48 h at pH 7.4 (TMT 130C); repl. 2, 48 h at pH 6.6 (TMT 129N); and repl 2, 48 h at pH 7.4 (TMT 131).The respective TMT label (0.4 µg) was added to each individual sample and incubated at room temperature for 1 h before the labeling reaction was quenched by addition of excess NH4OH. Equal volumes of all 8 samples were mixed, concentrated in a vacuum concentrator (Savant, Thermo Fisher Scientific) and acidified with TFA for LC-MS/MS analysis.


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LC-MS/MS Analysis --- Samples were injected on an Ultimate 3000 RSLC nano-HPLC system (Thermo Fisher Scientific) and separated using reversed phase C18 columns (trapping column: Acclaim PepMap C18, 100 µm x 20 mm, 3 µm, 100 Å, separation column: EASYSpray column, Acclaim PepMap C18, 75 µm x 500 mm, 2 µm, 100 Å, Thermo Fisher Scientific). After washing the peptides on the trapping column for 15 min with 0.1% TFA at a flow rate of 20 µL/min, peptides were eluted and separated using 420-min gradients from 1 to 35% solvent B (solvent A: 0.1% formic acid in water, solvent B: 0.08% formic acid in acetonitrile) at a flow rate of 270 nL/min. The nano-HPLC system was directly coupled to the nano-ESI source (EASY-Spray source, Thermo Fisher Scientific) of an Orbitrap Fusion Tribrid mass spectrometer (Thermo Fisher Scientific). Samples were analyzed with a combined CID/HCD MS/MS strategy for peptide identification and reporter ion quantification, respectively. FTMS scans were acquired over the m/z range 300-1700 every 5 seconds (R=120,000 at m/z 200, AGC (automated gain control) target value 5x105, max. injection time 100 ms). Within these 5 sec, the most abundant signals of the full scans were selected for MS/MS experiments: CID product ion spectra were acquired in the linear ion trap (LTQ; quadrupole isolation window 2 Th, 30 % normalized collision energy, AGC target 1x104, max. injection time 100 ms). The same precursor ions were selected for HCD experiments (quadrupole isolation window 1 Th, 55% normalized collision energy, AGC target 5x104, max. injection time 200 ms), HCD product ion spectra were acquired in the orbitrap analyzer (R=60,000 at m/z 200) to resolve reporter ions with the same nominal mass. Dynamic exclusion was enabled, exclusion time was set to 45 s. After the first LC/MS analysis, all samples were reanalyzed with the same experimental settings, but with targeted exclusion (exclusion mass width ± 25 ppm, 3 min retention time window) of ions corresponding to unambiguously identified peptides of the first run (FDR < 1 %).



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MS data analysis --- Raw data of all eight LC/MS analyses (first run and rerun with targeted exclusion of four biological replicates) were combined and processed using the Proteome Discoverer (version 2, Thermo Fisher Scientific). For peptide identification, MS/MS data were searched against the NCBI database (version 140812, taxonomy rattus, 81,970 entries) using the Sequest HT algorithm (Thermo Fisher Scientific). A maximum mass deviation of 20 ppm was applied for precursor ions, while for product ions max. 0.6 Da (linear ion trap data) and 0.02 Da (orbitrap data) were allowed. Oxidation of Met, acetylation of protein N-termini and modification of peptide N-termini by the TMT label were set as variable modifications, carbamidomethylation of cysteines as well as modifications of Lys by the TMT label were included as fixed modification. A maximum of two missed cleavage sites were considered for peptides in the mass range between 350 and 5000 Da with a minimum length of 6 amino acids. An FDR was calculated using Percolator and peptides with an FDR > 1% were filtered out. With an additional database search using same settings but modification of Lys by the TMT label as variable modification the labeling efficiency was determined. Quantification was performed based on the reporter ion ratios derived from the FT-HCD spectra (only unique peptides were considered), integration tolerance was 20 ppm. Quantitative data were normalized on the protein median, proteins with less than four quantified peptides were excluded.

Quantitative PCR --- Total RNA was isolated from AT-1 cells using the InviTrap Spin Tissue RNA Mini kit (Invitek). 1 µg of RNA was subjected to reverse transcription with SuperScript II reverse transcriptase (Invitrogen, Carlsbad, CA, USA) and analyzed by qPCR using the Platinum SYBR Green qPCR Supermix (Invitrogen). Relative gene expression quantification was calculated according to the comparative cycle threshold (Ct) method using Rn18S for normalization. Each sample was analyzed in triplicate. The following primers were used: 8 ACS Paragon Plus Environment

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Target Glut-1 GSTA3 NQO1 FPPS MT-2A CRABP2 NBC3 Rn18s

Forward primer ATGATGCGGGAGAAGAAGGT AGACCAGAGCCATTCTCAAC CGCAGAGAGGACATCATTCA TTCAGTGTCTGCTACGAGCC GCTCCTGCAAATGCAAACAAT GCAGACTGTGGATGGGAGAC GCTCTGGGTGATCAAAGCCT CTGAGAAACGGCTACCACATC

Reverse primer GAACAGCGACACCACAGTGA GCCACTCCTTCTGCATACAT GTGGTGATGGAAAGCAAGGT TCGTACAGTGCTTTCACCCG GCAGCTGCACTTGTCCGAA GCAGGACTCACCAGGATTAGC GGCTTTTCAGGGCTATATTTTAGGG CCCAAGATCCAACTACGAGC

Subcellular fractionation and Western blotting --- AT-1 cells were cultivated in 10-cm culture dishes. After 24 h in serum-free medium, cells were incubated at pH 7.4 or pH 6.6 for 3 h. The isolation of the nuclear extract was performed using the Nuclear Extract Kit from Active Motif (Rixensart) as recommended by the manufacturer. The protein content was determined using Bradford reagent (Bio-Rad). Subsequently, nuclear fractions were analyzed by Western blot. Proteins were separated by SDS-PAGE and transferred to a nitrocellulose membrane. For Western blotting, antibodies used were anti-Nrf2 (ab89443, Abcam) and HSP90 (SantaCruz). The bound primary antibody was visualized using horseradish peroxidase (HRP)-conjugated secondary antibodies and Serva chemiluminescence reagent for HRP (Serva) with the Molecular Imager ChemiDoc XRS System (Biorad). Quantitative analysis was performed with Quantity One software (Biorad).

Caspase-3 activity assay --- Cells were incubated in RPMI 1640 medium (pH 7.4 or pH 6.6). After 24 hours, mitomycin C (Sigma) was added to a final concentration of 0.01, 0.1, 0.5, 1 and 5 µM for additional 24 h. Afterwards, cells were washed once with PBS buffer at 4°C and incubated with 100 µl cell lysis buffer (10 mM TRIS, 100 mM NaCl, 1 mM EDTA, 0.01% Triton X-100, pH 7.5) for 10 min on ice, harvested, and centrifuged at 16,000g for 10 min at 4°C. 60 µl of the supernatant was incubated with 65 µl reaction buffer (20 mM PIPES, 4 mM EDTA, 0.2% CHAPS, 10 mM DTT, pH 7.4) containing 42 µM DEVD-AFC (final 9 ACS Paragon Plus Environment


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concentration)

at

37°C,

and

fluorescence

of

the

cleaved

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product,

7-amino-4-

trifluoromethylcoumarin (AFC), was measured at 400 nm excitation and 505 nm emission wavelength using a multi-well counter (Infinite). Cleaved AFC was quantified by a calibration curve using known AFC concentrations. Protein content was determined by BCA analysis (Thermo Fisher Scientific); each experiment was performed in duplicate.

Glucose quantification --- AT-1 cells were incubated in RPMI 1640 medium adjusted to pH 7.4 or pH 6.6. After 48 h of incubation, medium was replaced by bicarbonate HEPESbuffered Ringer's solution at pH 7.4 containing 11 mM glucose. After 1, 3, and 6 hrs, the glucose content in 5-µl culture supernatant was measured using the glucose (HK) assay kit (Sigma, G3293) according to the manufacturer's instructions and normalized by protein content. Each experiment was performed in triplicate.

Analysis of glutathione S-transferase (GST) activity --- For measuring GST activity, cells were harvested, homogenized and sonicated in 1 ml of cold buffer (100 mM K3PO4, pH 7.0, containing 2 mM EDTA) after an incubation period of 48 h (pH 7.4 or pH 6.6).The total GST activity was determined using the GST Assay Kit (Cayman) according to the manufacturer's instruction. Each experiment was performed in triplicate.

Data analysis --- Data are presented as mean ± SEM. For all experiments, n equals the total number of experiments and N the number of cell passages used. All experiments were performed with at least three different passages. Statistical significance was determined by unpaired Student's t-test or ANOVA with post hoc testing as applicable (Sigma Plot 12.5 software). Differences were considered statistically significant if p < 0.05. In addition to the experimental in depth investigation of proteins with changes >50 %, we also performed functional profiling of candidate gene lists (supplementary table 1) was performed 10 ACS Paragon Plus Environment

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using g:Profiler, a web server (http://biit.cs.ut.ee/gprofiler/) for functional interpretation and integration of gene lists in the context of versatile biological evidence. g:GOSt (statistical enrichment analysis) was used for interpreting gene lists in the context of biomedical ontologies, pathways, transcription factor and microRNA regulatory motifs and protein– protein interactions. Additionally, g:Convert was used for ID mapping. We performed separate analysis for proteins showing a ≥20 or 30 % up- or down-regulation with a z-score >1. In addition the results were verified using PANTHER gene analysis tools (pantherdb.org).



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RESULTS MS analysis of protein levels --- To obtain a comprehensive overview of protein expression levels in AT-1 prostate carcinoma cells under acidic conditions (pH 6.6) were compared to cells grown at physiological conditions (pH 7.4). In previous studies [13–15] we have shown that an extracellular acidosis of pH 6.6 leads to a sustained intracellular acidosis (pHi ~ 6.75), whereby the drop in intracellular pH is less than expected from passive distribution, indicating the existence of pH-regulatory transport mechanisms. We identified Na+-dependent HCO3transport to be primarily responsible for pH regulation in AT-1 cells. Whole cell lysates of AT-1 cells that had been exposed for 24 h and 48 h to either pH 7.4 or pH 6.6 were analyzed by LC- MS/MS and proteins were differentially quantified (i.e. pH 7.4 versus pH 6.6) using TMT 10-plex labels for reporter ion quantification (see experimental section for details). In total, four biological replicates and two technical replicates were analyzed to account for biological variability as well as for experimental deviations. In this study, a total of 3377 proteins were identified (3167, 3177, 3188 and 2975 for the four biological replicates; see supplementary table 2). The application of the rerun strategy, i.e., a second LC-MS/MS analysis of each sample excluding precursor masses that had been unambiguously assigned after the first analysis, resulted in an increase in protein identifications by about 5-20 % (Supplementary Figure 1). 2710 proteins were shared across all replicates (Supplementary Figure 2), representing 80 % of the totally identified proteins in all replicates. To probe the efficiency of the amine-reactive labeling an additional database search with setting the TMT label as variable modification was conducted. The efficiency of TMT labeling was found to be over 99 % for Lys residues (data not shown), thus excluding incomplete labeling as source for ratio distortions. Roughly 80 % of the identified proteins could be differentially quantified based on at least 4 PSMs. The calculated standard error for the ratios was below 20 % between the replicates for more than 90 % of the quantified proteins. 95 % of the quantified proteins showed ratios between 0.8 and 1.2 after 24 h and 48 12 ACS Paragon Plus Environment

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h acidosis compared to the control group. In order to classify a protein as differentially expressed and include it into further validation the following high stringency criteria were applied in a first approach: (i) 4 out of 4 biological replicates showed qualitatively identical changes in the acidosis group (more than 1.8 fold or less than 0.5 fold level), (ii) at least two unique peptides were identified per protein with high confidence (FDR < 1 %) and (iii) at least 4 PSMs of unique peptides contributed to the quantification of the protein. Intriguingly, only four proteins were significantly up-regulated, while three further proteins were significantly downregulated by at least 50% at one or both time points (Figure 1). Glucose transporter 1 (Glut-1) and farnesyl pyrophosphatase (FPPS) were found to be down-regulated after 48 h acidic treatment, while the metallothionein 2A (MT-2A) protein level was clearly reduced after 24 h and returned to control values after 48 h. After 24 h of acidosis conditions, a weak increase in glutathione S transferase A3 (GSTA3) and NAD(P)H dehydrogenase 1 (NQO1) levels was observed, which became more pronounced after 48 h of incubation. Cellular retinoic acidbinding protein 2 (CRABP2) and Na-bicarbonate transporter (SLC4A7 or NBC3 or NBCn1) were similarly up-regulated at 24 and 48 hrs of incubation. All proteins identified exert function with known or putative relevance for tumor cells. Glut-1 contributes to basal glucose supply of cells and has been proposed as a prognostic marker [23]. FPPS is involved in isoprenoide synthesis and thereby for example in the farnesylation or geranylation of Gproteins. In addition, it is a target of experimental bisphosphonate tumor therapy [24]. MT-2A contributes to the homeostasis of trans-metals and confers chemoresistence [25]. GSTA3 may play a role in detoxification by conjugation, besides its impact on ∆5∆4 isomerization of steroids [26]. NQO1 plays an important role in anti-tumor drug activation, e.g. of mitomycin but can also exert cytoprotective functions [27]. CRABP2 translocates retinoic acid into the nucleus where it activates the RAR receptor, leading to cell differentiation and an anti-oncotic action [28]. NBC3 is an important membrane transporter involved in cellular pH homeostasis, also in AT-1 cells and associated with breast cancer. Interestingly, the Na+-dependent HCO313 ACS Paragon Plus Environment


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transporter NBC3 was described before as one of few acidosis-induced proteins [29] in renal epithelial cells and therefore served a putative positive control. The MS analysis data show for the first time on the one hand the remarkable stability of the cellular proteome during metabolic acidosis and on the other hand an unexpected specificity of protein expression changes, at least in the cell type investigated here. Down-regulation of Glut-1, FPPS and MT-2A as well as up-regulation of CRABP2 is potentially detrimental for the tumor cell, whereas up-regulation of GSTA3 and NBC3 is beneficial. Up-regulation of NQO1 is supposed to enhance the chemosensitivity towards certain classes of drug but may be beneficial in the absence of chemotherapy. Thus, our data emphasize the importance of a more detailed understanding of acidosis-induced changes in protein expression in the tumor micromilieu.

Comparison of changes at the protein level with changes at the mRNA levels --- To confirm our data obtained on the protein level and to test whether transcriptional changes are involved, we evaluated the expression levels of the 7 proteins differentially regulated >50% by quantitative real-time PCR at different time points (Figure 2). The mRNA levels of the four proteins GSTA3, NQO1, CRABP2, and NBC3 were found to be up-regulated, which confirmed to the results obtained from proteome analysis (Figure 1). Increased mRNA levels were most pronounced for NBC3 (6.35 fold) and NQO1 (4.52 fold). Consistent with the alteration in protein levels, the levels of MT-2A mRNA became remarkably diminished over time. Glut-1 and FPPS expression was also significantly decreased after 24 h of acidosis as assessed by proteomic analysis. In order to gain further evidence for the functional relevance of the observed changes we aimed to determine the effects of acidosis on protein activity or related cellular effects.


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Caspase-3 activity assay --- The cytosolic flavoenzyme NQO1 catalyzes the reduction of various quinones, utilizing either NADH or NADPH as electron donors. NQO1 has been reported to be involved in the bioactivation of several antitumor quinones, such as Mitomycin C (MMC), resulting in DNA interstrand cross-linking [27]. The metabolic activation of MMC in AT-1 cells was assessed by measuring caspase-3 activity as a marker of apoptosis under acidic (pH 6.6) and physiological (pH 7.4) conditions (Figure 3). Compared with control conditions, extracellular acidosis led to a remarkable increase in caspase-3 activity that was observed at 24 hours after treatment with MMC in a concentration-dependent manner. After the exposure to increasing MMC concentrations (0.5, 1 and 5 µM), caspase-3 activation was found to be significantly higher in the acidic environment.

Glutathione-S transferase (GST) assay --- GST consists of a large family of GSH-utilizing enzymes playing an important role in reactive oxygen species and xenobiotic detoxification [26]. To determine whether increased GSTA3 protein and mRNA levels are associated with an increase in enzymatic activity, total GST activity, attributed to all isoenzymes, was measured after 48 h of acidosis. As shown in Figure 3, an increase in GST activity was observed in an acidic extracellular environment clearly reflecting similar changes both on the protein and the mRNA level.

Nrf2 Western blotting --- The transcription factor Nrf2 is known to regulate the expression and coordinated induction of genes encoding detoxifying enzymes including NQO1 and GSTs in response to antioxidants [30]. To determine if the increased expression of NQO1 and GSTA3 is associated with changes in the distribution of Nrf2, Western blot analysis was performed on nuclear protein extracts of AT-1 cells. The results presented in figure 4 show an increase in relative nuclear localization of NRF2 after 3 hours under acidic conditions.



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Consistent with our previous analysis these results demonstrate that the nuclear accumulation of Nrf2 precedes induction of target gene expression.

Glucose consumption --- The increased protein and mRNA expression of glucose transporter GLUT1 could potentially contribute to differences in glucose uptake efficiency. To test whether acidic priming of tumor cells has an impact on glucose consumption, AT-1 cells were preincubated for 48 h in RPMI medium at pH 7.4 or pH 6.6. Afterwards cells were transferred into Ringer solution at pH 7.4 and glucose consumption was measured after different time points. As expected, glucose-consumption rates shown in Figure 3 were reduced to ~50 % after acidic priming of the cells.

Functional profiling by statistical enrichment analysis --- Analysis using a lower threshold (> 20 or 30 %; supplementary table 1 and supplementary figure 3) revealed that the number of proteins affected was greater for up-regulation as compared to down-regulation and that the number increases with time.

Functional profiling using these protein lists unveiled the

statistical enrichment of proteins belonging to defined functional clusters. Acidosis induced the significantly overrepresented up-regulation of proteins involved in GSH-metabolic processes, xenobiotic metabolism, stress response, citric acid cycle and respiratory electron transport. These alterations can be interpreted as protective cellular responses. Significantly overrepresented acidosis-induced down-regulation concerned proteins involved in metabolism of lipids and cholesterol biosynthesis. The cell biological impact of these effects is not known at the moment and has to be investigated in future studies.


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DISCUSSION Mass Spectrometric Protein Quantification – The use of isobaric mass tags for differential quantification of proteins is especially beneficial when more than two states have to be compared for several replicates as it allows multiplexing of experiments, i.e. up to ten samples can be analyzed in parallel instead of running all samples sequentially [31,32]. For the experiment described herein, 64 hours of mass spectrometer time were required to analyze three states in 8 replicates, compared to 512 hours that would have been necessary for a label free approach under identical conditions. Alternative quantification approaches with the potential for multiplexing, like metabolic labeling [33] are limited in their applicability as they require several generations of cell culture for a complete labeling. Moreover, isobaric tags do not cause additional complexity on the MS level during mass spectrometric analysis as peptides from all samples are detected in one single peak. The rate of quantified proteins is high as only one MS/MS spectrum is required for quantification. On the other hand, quantification on the MS/MS level harbors the risk of ratio interference because of co-isolation of peptides, resulting in MS/MS spectra yielding reporter ions from different sources. In most cases, this would lead to an underestimation of regulation. As the majority of peptides is not regulated, the ratios of regulated peptides would be lowered in case of co-isolation. The fact, that the majority of comparatively quantified proteins showed ratios in the range between 0.8 and 1.2 (95 % of all quantified proteins), indicates that they were not regulated. This might be partially caused by the leveling effect of co-isolation. The low standard error between the replicates (below 20 % for 80 % of quantified proteins) and the applied stringent criteria for protein quantification (at least 4 PSMs of unique peptides for one protein) however validate our results and greatly increase confidence in the identification of those proteins that were found to be significantly regulated during acidosis.



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Differentially Regulated Proteins – In the present study we applied advanced proteomic techniques to a well-established tumor cell model, AT-1 cells, and tested comprehensively the impact of controlled metabolic acidosis on the proteome. Furthermore, we investigated the mRNA abundance of affected proteins and show that at least part of the effects is transcriptional. Finally, we assessed the functional relevance for a subgroup of identified proteins. Regulation of cellular pH can be mediated by a number of different membrane proteins, including the electroneutral Na+, HCO3− cotransporter [NBCn1 or NBC3 (SLC4A7)], which has been proposed as an important acid-base transporter in cancer cell lines [34,35]. Interestingly, this Na+-dependent HCO3- transporter was described as one of few acidosisinduced proteins [29] in renal epithelial cells and therefore represents an internal positive control in AT-1 cells. Because Na+-HCO3− cotransport is the predominant mechanisms involved in pH-homeostasis of AT-1 cells, the observed up-regulation of SLC4A7 indicates on the one hand, that this transporter contributes substantially to pH-homeostasis of AT-1 cells and on the other hand serves as a validation of the applied analysis strategy. Transport across the plasma membrane is a rate-limiting step in glucose metabolism and is mediated by a family of glucose transporters, primarily GLUT1, known to be overexpressed in a variety of both solid and hematological malignancies [23,36,37]. Our findings are consistent with previous reports of decreased glucose consumption under acidosis [4,20,38]. It has been shown that under physiological pH, tumor cells are initially glycolytic by converting most of the glucose molecules to lactic acid. and the resulting extracellular acidification may switch cells to a non-glycolytic phenotype with a concomitant decrease in glucose consumption [38]. The above results suggest an important role of Glut1 in modulating glucose metabolism in cancer cells under acidic conditions. Metabolic acidosis also augments the expression of both mRNA and protein levels of GSTA3 and NQO1 in tumor cells. NQO1 and GSTA3 are phase II metabolizing enzymes that have 18 ACS Paragon Plus Environment

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been shown to play an essential role in the metabolism of xenobiotics and are expressed at high levels in most human solid tumors [39–41]. Overexpression of NQO1 in solid tumors in combination with the ability to reduce various quinone-containing antitumor drugs, thereby activating them, has drawn attention to NQO1 as a potential molecular target in cancer treatment [27]. MMC is such a quinone-containing antibiotic drug that is clinically used in anticancer therapy. Demonstration of significantly increased caspase-3 activity in a MMC concentration-dependent manner implies a reductive activation by NQO1 as a toxic event upon acidosis in AT-1 cells. It is known that NQO1 and GST gene expression is regulated by the transcription factor Nuclear factor erythroid-2 related factor 2 (NRF2) [42]. The NRF2-regulated transcriptional program includes a broad spectrum of genes encoding antioxidants and xenobiotic metabolism enzymes including NQO1 and GST isoenzymes. Further Nrf2-target gene, that were affected by acidosis are (although less than 20%) are aldehyde dehydrogenase (up, 48h), peroxiredoxin (up, 48h), thioredoxin reductase (up, 48h), metallothionein (up, 48h). In the present study, it is demonstrated that acidosis significantly increases Nrf2 transcription factor activity in AT-1 cells by nuclear translocation. Nrf2 was found to be overexpressed in head and neck squamous cell carcinomas [43] and increased Nrf2 expression levels are correlated with aggressiveness and chemoresistance of endometrial tumors [44]. This indicates that the activity of Nrf2, which protects normal cells from oxidative stress and DNA damage, is possibly exploited by tumor cells to better tolerate the cellular stress-inducing conditions of the tumor microenvironment. In order to survive, even cancer cells must adapt to this toxic environment, regulating ROS levels to maintain redox homeostasis [45]. These findings are in agreement with our previous results showing elevated ROS production in AT-1 cells upon acidosis [13]. MT-2A, down-regulated both at the protein and the mRNA level during the first 24h, belongs to the MT family, a class of low-molecular weight, intracellular and cysteine-rich proteins 19 ACS Paragon Plus Environment


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with high affinity for metal ions [25]. Changes in the expression status of MT-2A plays an important role in various types of human tumors and could affect

proliferation or

differentiation during tumor progression [46]. It was reported that a loss of MT-2A induced NF-κB signaling in a transgenetic mouse model (MT-2A-knock out) [47]. Furthermore, decreased MT-2A expression was detected in cell lines and primary tumors of gastric cancer, which activated the NF-κB pathway [48]. Activation of NF-κB in turn is associated with cell inflammation, malignancy, and tumor progression [49]. It is also reported that downregulation of MT-2A expression occurred when human cells become immortal phenotypes, a key event in tumorigenesis [50]. Another up-regulated protein identified by our study, CRABP2, belongs to the family of fatty acid-binding proteins and can bind retinoic acid (RA) with high affinity. CRABP2 transports RA from the cytoplasm to the nucleus and facilitates its binding to the nuclear receptors (RARs). Some studies revealed abnormal CRABP expression in human cancers, which can be associated with clinicopathological characteristics and clinical prognosis [28]. Functional profiling including protein with changes >20 %, unveiled especially acidosissensitive functional clusters and thereby possibly cellular functions. Interestingly, acidosis induced the significantly overrepresented up-regulation of proteins involved in GSHmetabolic processes, xenobiotic metabolism, stress response, citric acid cycle and respiratory electron transport. These alterations serve on the one side as protective cellular responses (detoxification, energy supply) and on the other hand help to explain the acidosis-induced increase in mitochondrial reactive oxygen species generation. Surprisingly, acidosis-induced down-regulation concerned functional clusters involved in the metabolism of lipids and cholesterol biosynthesis. The functional relevance and the cell biological impact of these effects have to be investigated in future studies. Nevertheless, our data show that acidosis has the potential to affect specifically certain biological processes.


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CONCLUSIONS Our study provides the first comprehensive analysis of acidosis-induced changes of the protein pattern in a tumor cell under conditions of controlled metabolic acidosis, a pathologically relevant condition. The data show a surprising overall stability of the proteome with, nevertheless, functionally significant changes of a subset of proteins that are all potentially relevant for tumor cell biology in terms of xenobiotic metabolism as well as mitochondrial function. The observed acidosis-induced alterations of the proteome are either beneficial (GSTA3, NBC3), detrimental (Glut-1, FPPS, MT-2A, CRABP2) or of context dependent relevance (NQO1). Thus, our data emphasize the importance of a more detailed understanding of acidosis-induced changes in protein expression in the tumor micromilieu. Mechanistically, altered transcription with unexpected specificity contributes substantially to the effect of acidosis, although we cannot exclude posttranscriptional mechanism. Future studies will have to address the question whether the alterations determined herein are of general validity or whether there are cell type specific pattern. Furthermore, the underlying common molecular mechanisms should be unveiled in order to broaden our understanding of tumor micromilieu biology and thereby the possibilities of therapeutic intervention.

SUPPORTING

INFORMATION

(this

material is available

free of

http://pubs.acs.org/): Supplementary Figures 1 & 2 - Protein quantification in replicates Supplementary Figure 3 - Analysis of acidosis-induced changes in AT1 proteome Supplementary Table 1 - Protein list for functional profiling Supplementary Table 2 - Complete protein list - TMTquan


charge

via


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ACKNOWLEDGEMENTS AS acknowledges financial support by the DFG (projects Si 867/13-1, 15-1, 16-1) and the region of Saxony-Anhalt. MG acknowledges financial support by the BMBF (project ProNetT3 Ta04) and the Deutsche Krebshilfe (Grants 106774/106906).


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FIGURE LEGENDS Fig. 1. Differentially expressed proteins in AT-1 cells after the stated incubation periods at pH 6.6 (compared to pH 7.4), n/N = 4. (*) p < 0.05 versus pH 7.4. Glut-1 = facilitative glucose transporter 1, MT-2A =

metallothionein

2A,

GSTA3

=

glutathione S-transferase alpha-3, CRABP2 = cellular retinoic acid-binding protein 2, NQO1 = NAD(P)H dehydrogenase [quinone] 1, NBC3

= sodium bicarbonate cotransporter 3,

FPPS = farnesyl pyrophosphate synthase. Fig. 2. Quantitative real-time PCR analysis of acidosis-induced mRNA expression of (A) Glut-1, (B) MT-2A, (C) GSTA3 and (D) CRABP2, (E) NQO1, (F) NBC3, (G) FPPS. Fold regulation and ∆∆Cq values of pH 6.6 compared to pH 7.4 at 3 h, 6 h and 24 h are shown, n = 18–39, N = 6–13. (*) p < 0.05 versus pH 7.4. Fig. 3. (A) Induction of caspase-3 activity in AT-1 cells treated with mitomycin C. Cells were incubated in RPMI 1640 medium adjusted to pH 7.4 or pH 6.6. After 24 hours cells were treated with the indicated concentrations of MMC for additional 24 h. (B) Total GST activity after an incubation period of 48 h at pH 7.4 or pH 6.6. (C) Impact of acidosis on glucose consumption. AT-1 cells were incubated in RPMI 1640 medium adjusted to pH 7.4 or pH 6.6. After 48 hours of incubation, medium was replaced by bicarbonate HEPES-buffered Ringer's solution adjusted to pH 7.4 containing 11 mM glucose. After 1, 3 and 6 hours, glucose level was monitored. Values are expressed as the mean ± s.e.m of N=3, n=9. (*) p < 0.05 versus pH 7.4. Fig. 4. Impact of acidosis on the activity of Nrf2 in AT-1 cells. (A) Representative Western blot of nuclear Nrf2 after an incubation period of 3 h at pH 7.4 or pH 6.6. (B) Semiquantitative analysis of Western blots showing nuclear translocation of Nrf2 after 3 h incubation periods with pH 6.6 (compared to pH 7.4). n/N = 10. (*) p < 0.05 versus pH 7.4. 23 ACS Paragon Plus Environment


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