Article pubs.acs.org/jpr
Identification of New Mechanisms of Cellular Response to Chemotherapy by Tracking Changes in Post-Translational Modifications by Ubiquitin and Ubiquitin-Like Proteins Thomas Bonacci,† Stéphane Audebert,† Luc Camoin,† Emilie Baudelet,† Ghislain Bidaut,† Maxime Garcia,† Ini-Isabée Witzel,‡,§ Neil D. Perkins,‡ Jean-Paul Borg,† Juan-Lucio Iovanna,† and Philippe Soubeyran*,† †
CRCM, INSERM U1068; Institut Paoli-Calmettes; Aix-Marseille Université, UM105; CNRS, UMR7258, 163 Av de Luminy, F-13009 Marseille, France ‡ Institute for Cell and Molecular Biosciences, Newcastle University, Medical School, Catherine Cookson Building, Framlington Place, Newcastle Upon Tyne NE2 4HH, United Kingdom S Supporting Information *
ABSTRACT: Pancreatic ductal adenocarcinoma (PDAC) is a very aggressive malignancy characterized by an excessive resistance to all known anticancer therapies, a still largely elusive phenomenon. To identify original mechanisms, we have explored the role of post-translational modifications (PTMs) mediated by members of the ubiquitin family. Although alterations of these pathways have been reported in different cancers, no methodical search for these kinds of anomalies has been performed so far. Therefore, we studied the ubiquitin-, Nedd8-, and SUMO1-specific proteomes of a pancreatic cancer cell line (MiaPaCa-2) and identified changes induced by gemcitabine, the standard PDAC’s chemotherapeutic drug. These PTMs profiles contained both known major substrates of all three modifiers as well as original ones. Gemcitabine treatment altered the PTM profile of proteins involved in various biological functions, some known cancer associated genes, many potentially cancer-associated genes, and several cancer-signaling networks, including canonical and noncanonical WNT and PI3K/Akt/MTOR pathways. Some of these altered PTMs formed groups of functionally and physically associated proteins. Importantly, we could validate the gemcitabine-induced PTMs variations of relevant candidates and we could demonstrate the biological significance of such altered PTMs by studying in detail the sumoylation of SNIP1, one of these new targets. KEYWORDS: pancreatic cancer, anticancer drugs resistance, gemcitabine, stress response, post-translationnal modification, ubiquitin, ubiquitin-like proteins, Nedd8, SUMO1
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Stress responses are mediated through quick and fine-tuning of implicated protein functions. This process is mainly achieved through post-translational modifications (PTMs) that regulate the activity, localization, and/or interactions of key proteins. Phosphorylation, as well as acetylation and methylation, are chemical PTMs, which have been shown to play major role in different pathways, and alterations of these PTMs have been vastly described in oncogenesis.4 During the past decade, PTMs by members of the ubiquitin family have also emerged as major regulators of cellular functions.5 Modification by ubiquitin (8.5 kDa), also named ubiquitylation, results in the formation of an isopeptide bond between the C-terminal glycine residue of ubiquitin and an internal lysine residue of the modified protein.
INTRODUCTION
Pancreatic ductal adenocarcinoma (PDAC) remains one of the worst forms of cancers, usually being at an advanced state when discovered and displaying exacerbated resistance to anticancer therapies.1,2 Only gemcitabine-based therapy was shown to partially increase patient survival.3 Therefore, new ways to improve current treatments for this cancer are still heavily required. One way to do so is to focus on the specific defense mechanisms of pancreatic cancer cells that allow them to resist the cellular stress induced by anticancer treatment. In normal cells, stress activates rapidly, and temporally, these mechanisms to favor cell survival. In pancreatic cancer cells, some of these resistance pathways must be constitutively overactivated and others particularly strongly induced in response to treatment. Identifying and understanding these mechanisms should point at important clues explaining therapeutic escape of PDACs. © 2014 American Chemical Society
Received: December 17, 2013 Published: March 21, 2014 2478
dx.doi.org/10.1021/pr401258d | J. Proteome Res. 2014, 13, 2478−2494
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monoclonal anti-PAF1 (ab56773, Abcam), mouse monoclonal anti-p53 (DO-1, Santa Cruz Biotechnology), rabbit serum antiSNIP1,13 rabbit anti-USP11 antibody (Bethyl lab), rabbit antiGST (Molecular Probes A5800), mouse anti-SUMO2 (Abcam ab81371), Ni2+-NTA agarose beads (Qiagen), imidazole (I2399, Sigma), anti-flag M2 agarose beads (A2220, Sigma), and flag peptide (F3290, Sigma). PD169316 and SB203580 were from Calbiochem (cat nos. 513030 and 559389, respectively).
Ubiquitylation requires the successive action of three enzymes, a ubiquitin-activating enzyme (E1), a conjugating enzyme (E2), and a ubiquitin ligase (E3),6 and is balanced by ubiquitin hydrolases also called deubiquitylases (DUBs).7 Ubiquitin itself can be conjugated to another ubiquitin through one of its seven lysine residues or through its N-terminal methionine, resulting in the formation of eight different types of polyubiquitin chains. Hence, a protein may be modified by one ubiquitin moiety (monoubiquitylation) and several monoubiquitylation results in multiubiquitylation or by polyubiquitin chains, resulting in polyubiquitylation. These different types of ubiquitylation can modulate different aspects of a protein function (degradation, localization, activity).6 The diversity of target proteins and of ubiquitylation types explains why this PTM is involved in a large variety of biological functions, from protein degradation to endocytosis, and from chromatin remodeling to immune signaling. This pleiotropic role of ubiquitin is further increased by 13 ubiquitinlike (Ubls) modifiers distributed in nine families.8 Despite their primary structure, which can be highly different, they all share a similar specific ternary structure, the ubiquitin fold, and they all follow the same scheme of activation, conjugation, and ligation to lysine residues of their target proteins.9 According to their central role in the maintenance of cellular homeostasis, dysfunctions within Ubls-mediated PTMs have been associated with oncogenesis,10 with a few examples for PDAC,11 such as low expression of the deubiquitylase USP9X.12 Therefore, our goal was to identify, by using a proteomicbased approach, variations in ubiquitin-like-dependent modifications induced by anticancer treatment of pancreatic cancer, as some of them could be involved in cell resistance. As a first attempt, we have generated the profiles of proteins modified by ubiquitin, Nedd8, and SUMO1 in MiaPaCa-2 cells, a particularly aggressive pancreatic cancer cell line. Comparison of these Ubls-specific proteomes between gemcitabine-treated and untreated cells led to the identification of specific alterations of modifications. Further studies showed that gemcitabine treatment induced the modification or demodification of proteins already known as involved in cancer and cancer-associated signaling networks linked to apoptosis and cell proliferation. Some of these altered PTMs formed groups of functionally and physically associated proteins such as ubiquitylated proteasomal subunits. We could validate the gemcitabine-induced alteration of PTMs of relevant candidates, and we have been able to show that sumoylation of SNIP1 in response to gemcitabine treatment is one mechanism that favors MiaPaCa-2 cells survival.
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DNAs and Transductions
Lentiviral vectors (pCCL-WPS-PGK) coding for 6His-flagtagged ubiquitin, Nedd8, and SUMO1 have been built and used to transduce MiaPaCa-2 cells, as described in the Experimental Procedures section in the Supporting Information. Two-Step Purification of 6His-Flag-Ubiquitin, -Nedd8, and -SUMO1 Conjugates
MiaPaCa-2 cells expressing the 6HF-ubiquitin-like constructs or GFP were seeded in 150 mm dishes, at 106 cells per dish, and when they reached 70% confluence, half were treated for 36 h with 10 μM of gemcitabine. Approximately 100 (MiaPaCa-2-6HF-ubiquitin and -SUMO1) or 150 mg (MiaPaCa-2-6HF-Nedd8) of proteins was used to isolate modified substrates. For each dish of untreated or treated cells, 2 mL of buffer 1 (6 M guanidinium-HCl, 0.1 M Na2HPO4/ NaH2PO4, pH 8.0 plus 0.5% Triton X-100) was added directly to the cell monolayer. Lysates were sonicated three times for 30 s with a 1 min break between pulses, to reduce viscosity. Protein concentration was adjusted between untreated and treated samples using Protein-Assay (Bio-Rad), and Ni2+-NTA agarose resin (Qiagen) was added with a ratio of 2 μL of resin for 1 mg of proteins. Samples were rotated at room temperature for 2 h 30 min, and beads were then washed once with 1 mL of buffer 1 and twice with 1 mL of prechilled buffer 2 (50 mM NaH2PO4, 150 mM NaCl, 1% Tween20, 5% Glycerol, pH 8.0) plus 10 mM imidazole. Purified proteins were eluted for 2 h at 4 °C in 600 μL of buffer 2 plus 250 mM imidazole. Eluted proteins were then incubated with 50 μL of anti-flag M2 agarose beads (Sigma) and rotated at 4 °C for 2 h 30 min. Beads were then washed twice with 500 μL of prechilled buffer 2. Purified proteins were eluted in 100 μL of buffer 2 containing 0.1 μg/μL of flag peptide by rotating at 4 °C for 1 h 30 min. Eluted proteins were collected and analyzed by mass spectrometry. Mass Spectrometry Analysis
Protein extracts were loaded on NuPAGE 4−12% bis−tris acrylamide gels according to the manufacturer’s instructions (Invitrogen). Running of protein was stopped as soon as proteins stacked in a single band. Protein-containing bands were stained with Imperial Blue (Pierce), cut from the gel, and digested with high-sequencing-grade trypsin (Promega, Madison, WI) before mass spectrometry analysis according to Shevchenko et al.14 Mass spectrometry analysis was carried out by LC−MS/MS using an LTQ-Velos-Orbitrap (Thermo Electron, Bremen, Germany) online with a nanoLC Ultimate 3000 chromatography system (Dionex, Sunnyvale, CA). Five microliters corresponding to 1/5 of the whole sample were injected in quadruplicate on the system. After preconcentration and washing of the sample on a Dionex Acclaim PepMap 100 C18 column (2 cm × 100 μm i.d. 100 A, 5 μm particle size), peptides were separated on a Dionex Acclaim PepMap RSLC
MATERIALS AND METHODS
Cell Lines, Antibodies, and Reagents
HEK-293T cells and pancreatic cancer-derived cell line MiaPaCa-2, parental and transduced, were maintained in DMEM (Invitrogen) supplemented with 10% FBS at 37 °C, 5% CO2 in a humidified atmosphere and manipulated following ATCC’s recommendations. The following antibodies and reagents were used: mouse monoclonal anti-flag (M2, Sigma), mouse monoclonal anti-β-tubulin (T4026, Sigma), rabbit polyclonal anti-flag (D-8, Santa Cruz Biotechnology), mouse monoclonal anti-ubiquitin (P4D1, Santa Cruz Biotechnology), rabbit polyclonal anti-Nedd8 (Z32.HJ, Invitrogen), rabbit monoclonal anti-SUMO1 (#4930, Cell Signaling Technology), mouse monoclonal anti-PCNA (PC10, DAKO), mouse 2479
dx.doi.org/10.1021/pr401258d | J. Proteome Res. 2014, 13, 2478−2494
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C18 column (15 cm × 75 μm i.d., 100 A, 2 μm particle size) at a flow rate of 300 nL/min, a two-step linear gradient (4−20% acetonitrile/H2O; 0.1% formic acid for 90 min and 20−45% acetonitrile/H2O; 0.1% formic acid for 30 min). The separation of the peptides was monitored by a UV detector (absorption at 214 nm). For peptides ionization in the nanospray source, spray voltage was set at 1.4 kV and the capillary temperature at 275 °C. All samples were measured in a data-dependent acquisition mode. Each run was preceded by a blank MS run to monitor system background. The peptide masses were measured in a survey full scan (scan range 300−1700 m/z, with 30 K fwhm resolution at m/z = 400, target AGC value of 1.00 × 106, and maximum injection time of 500 ms). In parallel to the high-resolution full scan in the Orbitrap, the datadependent CID scans of the 10 most intense precursor ions were fragmented and measured in the linear ion trap (normalized collision energy of 35%, activation time of 10 ms, target AGC value of 1.00 × 104, maximum injection time 100 ms, and isolation window 2 Da). Parent masses obtained in Orbitrap analyzer were automatically calibrated on 445.1200 locked mass. The fragment ion masses were measured in the linear ion trap to have a maximum sensitivity and the maximum amount of MS/MS data. Dynamic exclusion was implemented with a repeat count of 1 and exclusion duration of 30 s.
V 1 = v 1 · (∑ v 1 +
∑ v2)/(2· ∑ v1); V 2 = v 2·(∑ v1 + ∑ v 2)/(2· ∑ v 2)
K1 = k1·(∑ k1 +
∑ k 2)/(2· ∑ k1); K 2 = k 2·(∑ k1 + ∑ k 2)/(2· ∑ k 2)
b. Specific to Background Values. To get a value for the specific number of identified peptides per protein (V′1 and V′2) and for each protein, we subtracted the number of peptides identified in control samples (GFP) from values (ubiquitin, Nedd8, and SUMO1) V ′1 = V 1 − K1 if V 1 − K1 ≥ 0; V ′1 = 0 if V 1 − K1 < 0 V ′2 = V 2 − K 2 if V 2 − K 2 ≥ 0; V ′2 = 0 if V 2 − K 2 < 0
c. Variation of Post-Translational Modification. To obtain a rate for positive and negative variations of PTMs induced by gemcitabine, we used the following formula where the difference between the treated and untreated specific values was divided by the sum of all peptides including those in control (to penalize proteins identified with peptides in control sample) and multiplied by 100. var = (V ′2 − V ′1)/(V 1 + K1 + V 2 + K 2)*100; − 100
Mass Spectrometry Data Analysis
< Var < 100
Raw files generated from mass spectrometry analysis were processed with Proteome Discoverer 1.1 (Thermo Fisher Scientific). This software was used to search data via in-house Mascot server (version 2.3.0; Matrix Science, London, U.K.) against the Human database subset of the SwissProt database (version 2012.02). A database search was done using the following settings: a maximum of two trypsin miscleavage allowed, methionine oxidation and/or GlyGly motifs on lysine or cysteine as variable modifications, and cysteine carbamidomethylation as fixed modification. A peptide mass tolerance of 6 ppm and a fragment mass tolerance of 0.8 Da were allowed for search analysis. Only peptides with higher Mascot threshold (identity) were selected. FDR < 1% was used. For relative labelfree quantification, raw data (for each sample, three runs among quadruplicate runs) were processed using Progenesis LC−MS software according to manufacturer instructions (Nonlinear Dynamics, Newcastle, U.K.). In addition, a differential proteomics analysis using isobaric tag for relative and absolute quantification (iTRAQ) was done to access the global proteome. (Details are given in Experimental Procedures in the Supporting Information.)
Variations were considered as significant if below −50 or above 50 d. Confidence in %. To obtain a confidence value between 0 and 100%, we used the following formula. The first part of the formula takes into account the proportion of peptides in control samples, and the second part further reduces the final value of proteins identified with few peptides. conf = ((V 1 + V 2)2 /(1 + V 1 + V 2 + K1 + K 2)2 ) *100 − 100/(1 + V ′1 + V ′2); = 0 if
