Decreased NAD Activates STAT3 and Integrin Pathways to Drive Epithelial-Mesenchymal Transition
2018; Elsevier BV; Volume: 17; Issue: 10 Linguagem: Inglês
10.1074/mcp.ra118.000882
ISSN1535-9484
AutoresWeixuan Wang, Yadong Hu, Changmei Yang, Songbiao Zhu, Xiaofei Wang, Zhenyu Zhang, Haiteng Deng,
Tópico(s)Autophagy in Disease and Therapy
ResumoNicotinamide adenine dinucleotide (NAD) plays an essential role in all aspects of human life. NAD levels decrease as humans age, and supplementation with NAD precursors plays a protective role against aging and associated disease. Less is known about the effects of decreased NAD on cellular processes, which is the basis for understanding the relationship between cellular NAD levels and aging-associated disease. In the present study, cellular NAD levels were decreased by overexpression of CD38, a NAD hydrolase, or by treating cells with FK866, an inhibitor of nicotinamide phosphoribosyltransferase (NAMPT). Quantitative proteomics revealed that declining NAD levels downregulated proteins associated with primary metabolism and suppressed cell growth in culture and nude mice. Decreased glutathione synthesis caused a 4-fold increase in cellular reactive oxygen species levels, and more importantly upregulated proteins related to movement and adhesion. In turn, this significantly changed cell morphology and caused cells to undergo epithelial to mesenchymal transition (EMT). Secretomic analysis also showed that decreased NAD triggered interleukin-6 and transforming growth factor beta (TGFβ) secretion, which activated integrin-β-catenin, TGFβ-MAPK, and inflammation signaling pathways to sustain the signaling required for EMT. We further revealed that decreased NAD inactivated sirtuin 1, resulting in increased signal transducer and activator of transcription 3 (STAT3) acetylation and phosphorylation, and STAT3 activation. Repletion of nicotinamide or nicotinic acid inactivated STAT3 and reversed EMT, as did STAT3 inhibition. Taken together, these results indicate that decreased NAD activates multiple signaling pathways to promote EMT and suggests that age-dependent decreases in NAD may contribute to tumor progression. Consequently, repletion of NAD precursors has potential benefits for inhibiting cancer progression. Nicotinamide adenine dinucleotide (NAD) plays an essential role in all aspects of human life. NAD levels decrease as humans age, and supplementation with NAD precursors plays a protective role against aging and associated disease. Less is known about the effects of decreased NAD on cellular processes, which is the basis for understanding the relationship between cellular NAD levels and aging-associated disease. In the present study, cellular NAD levels were decreased by overexpression of CD38, a NAD hydrolase, or by treating cells with FK866, an inhibitor of nicotinamide phosphoribosyltransferase (NAMPT). Quantitative proteomics revealed that declining NAD levels downregulated proteins associated with primary metabolism and suppressed cell growth in culture and nude mice. Decreased glutathione synthesis caused a 4-fold increase in cellular reactive oxygen species levels, and more importantly upregulated proteins related to movement and adhesion. In turn, this significantly changed cell morphology and caused cells to undergo epithelial to mesenchymal transition (EMT). Secretomic analysis also showed that decreased NAD triggered interleukin-6 and transforming growth factor beta (TGFβ) secretion, which activated integrin-β-catenin, TGFβ-MAPK, and inflammation signaling pathways to sustain the signaling required for EMT. We further revealed that decreased NAD inactivated sirtuin 1, resulting in increased signal transducer and activator of transcription 3 (STAT3) acetylation and phosphorylation, and STAT3 activation. Repletion of nicotinamide or nicotinic acid inactivated STAT3 and reversed EMT, as did STAT3 inhibition. Taken together, these results indicate that decreased NAD activates multiple signaling pathways to promote EMT and suggests that age-dependent decreases in NAD may contribute to tumor progression. Consequently, repletion of NAD precursors has potential benefits for inhibiting cancer progression. Nicotinamide adenine dinucleotide (NAD) 1The abbreviations used are:NADnicotinamide adenine dinucleotideCD38ADP-ribosyl cyclase/cyclic ADP-ribose hydrolase 1SILACstable isotope labeling with amino acids in cell culturePRDX1peroxiredoxin-1PRDX6peroxiredoxin-6JAK1janus kinase1STAT3signal transducer and activator of transcription 3TGFβ1transforming growth factor beta-1TGFβ2transforming growth factor beta-2Smadmothers against decapentaplegic homologMKK6dual specificity mitogen-activated protein kinase kinase 6MKK4dual specificity mitogen-activated protein kinase kinase 4p38mitogen-activated protein kinase 14IL6interleukin-6NAMPTnicotinamide phosphoribosyltransferase. 1The abbreviations used are:NADnicotinamide adenine dinucleotideCD38ADP-ribosyl cyclase/cyclic ADP-ribose hydrolase 1SILACstable isotope labeling with amino acids in cell culturePRDX1peroxiredoxin-1PRDX6peroxiredoxin-6JAK1janus kinase1STAT3signal transducer and activator of transcription 3TGFβ1transforming growth factor beta-1TGFβ2transforming growth factor beta-2Smadmothers against decapentaplegic homologMKK6dual specificity mitogen-activated protein kinase kinase 6MKK4dual specificity mitogen-activated protein kinase kinase 4p38mitogen-activated protein kinase 14IL6interleukin-6NAMPTnicotinamide phosphoribosyltransferase. is essential to life and participates in all major biological processes (1Verdin E. 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We found that a 35% decrease in NAD levels in 293T cells caused significant changes in proteostasis and reactive oxygen species (ROS) homeostasis, with downregulation of glycolytic enzymes and antioxidant proteins leading to decreased cell proliferation rates and increased cell susceptibility to oxidative stress. Thus, the purpose of the present study was to examine the effect of decreased NAD on cellular processes in other cell lines. Herein, we established stable CD38-expressing cell lines to comprehensively determine how cellular NAD levels affect protein expression, cell proliferation, and cellular responses to oxidative stress. Our findings demonstrate that decreased cellular NAD levels cause cells to undergo epithelial-mesenchymal transition (EMT), whereas signal transducer and activator of transcription 3 (STAT3) inhibition reversed EMT, indicating that STAT3 is a vital regulator in NAD-mediated EMT. The human lung cancer cell line, A549, human liver cancer cell, HepG2 and human embryonic kidney cell line, 293T, were obtained from the cell bank of the Chinese Academy of Sciences (Shanghai, China). Cells were grown in RPMI 1640 medium or Dulbecco's Modified Eagle's Medium (Wisent, Montreal, QC, Canada). The medium was supplemented with 10% FBS (Wisent) and 1% penicillin/streptomycin (Wisent). For stable isotope labeling using amino acids (SILAC), cells were washed twice with PBS (Wisent) before replacing the culture medium with SILAC. A549 cells were grown in SILAC medium for 7 passages and tested for full incorporation before proteomic analysis. SILAC RPMI 1640 medium (Thermo Fisher Scientific, Waltham, MA) was supplemented with 10% dialyzed-FBS (Wisent), 1% penicillin/streptomycin, 40 mg/L isotope labeling l-13C615N2 lysine·HCl (Thermo Fisher Scientific) and 200 mg/L isotope labeling l-13C6 arginine·HCl (Thermo Fisher Scientific). Human CD38 cDNA was obtained from the U266 cell line. A FLAG tag was added at the C terminus and DNA sequence encoding amino acids 2–43 deleted from the N terminus. This recombinant human CD38 DNA was then cloned into PLVX-IRES-ZsGreen1 lentiviral transfer vector. The 293T cell line was transfected with PLVX-IRES-ZsGreen1 or PLVX-CD38-IRES-ZsGreen1 using lentiviral packaging vectors and polyethylenimine (Sigma, St Louis, MO). Supernatants were harvested after 48 h and concentrated with PEG6000. Precipitated lentiviral particles were resuspended in PBS. A549 and HepG2 cells were infected in the presence of 5 μg/ml polybrene (Sigma). Infected cells were sorted by flow cytometry. A single green fluorescent protein (GFP)-positive cell was seeded into a single well of a 96-well plate to select a clone with intense and uniform GFP expression for further analysis. NAD and NADH content were measured by NAD/NADH assay (BioAssay Systems, Hayward, CA), according to the manufacturer's instruction. Briefly, cells were washed with PBS and 4 × 105 cells counted for each cell line. NAD or NADH extraction buffer were added, and extracts heated at 60 °C for 5 min. Samples and NAD standards were then reacted with a working reagent. Absorbance at 565 nm was measured to quantify NAD and NADH concentrations. Cells were seeded in 96-well plates with 2000 cells/well. Cell proliferation rate was determined by the Cell Counting Kit-8 (CCK-8) (Dojindo Laboratories, Kumamoto, Japan). CCK-8 reagent was added to treated cells and incubated at 37 °C for 2 h. Optical density (OD) was measured at 450 nm with a microplate reader (Bio-Rad, Hercules). Relative cell number was represented as the ratio between absorbance in 450 nm at a particular hour and 0 h. All experiments were performed at least three times to ensure statistical power > 80%. Proteomic analysis was performed using biological triplicates. Mock-infected control cells (designated CD38(−) cells) were cultured in SILAC culture media with 13C615N2 lysine and 13C6 arginine. CD38-transfected cells were cultured in normal RMPI-1640 media and designated as CD38(+) cells. A Venn diagram was used to evaluate the number of overlapping proteins identified from proteomic studies using three biological replicates. Significantly changed proteins were screened by volcano plot analysis using R (V.3.3.2). Histograms of SILAC ratios showed protein fold-changes in proteomics data and demonstrated normal data distribution. Proteins with fold-change > 2 or < 0.5 and p values < 0.05 from t test statistics were considered significantly changed between CD38(−) and CD38(+) cells. Calculation of Pearson correlation was performed to ensure reproducibility of protein quantification. Protein (200 μg) was extracted from CD38(−) and CD38(+) cells and mixed. Protein disulfides were reduced by dithiothreitol at 5 mm for 60 min at room temperature. Next, free cysteine residues were alkylated with iodoacetamide at 12 mm for 45 min in the dark at room temperature. Protein samples were digested with trypsin for 14 h at 37 °C. Peptides were desalted with Sep-Pak C18 cartridges (Thermo-Pierce Biotechnology, Rockford, IL). Eluents were centrifuged by speedvac followed by HPLC separation. Collected eluents were combined into 12 fractions and analyzed by LC-MS/MS. For LC-MS/MS analysis, SILAC labeled peptides were separated by 135 min gradient elution at a flow rate of 0.3 μl/min with a Thermo-Dionex Ultimate 3000 HPLC system that was directly interfaced with a Thermo Orbitrap Fusion Lumos mass spectrometer. The analytical column was a homemade fused silica capillary column (75 μm inner-diameter, 150 mm length; Upchurch, Oak Harbor, WA) packed with C-18 resin (300 Å, 5 μm; Varian, Lexington, MA). Mobile phase A consisted of 0.1% formic acid, and mobile phase B consisted of 100% acetonitrile and 0.1% formic acid. The Thermo Orbitrap Fusion Lumos mass spectrometer was operated in the data-dependent acquisition mode using Xcalibur 4.0.27.10 software. A single full-scan mass spectrum was done in the Orbitrap (300–1500 m/z, 120,000 resolution). The spray voltage is 2500 V and the AGC target is 200,000. This was followed by 3 s data-dependent MS/MS scans in an ion routing multipole at 30% normalized collision energy (HCD). The charge state screening of ions was set at 2–7. The exclusion duration was set at 15 s. Mass window for precursor ion selection was set at 1.6 m/z. The MS/MS resolution was 30,000. The MS/MS maximum injection time was 60 ms and the AGC target was 200,000. Peak lists from LC-MS/MS analysis were generated with the SEQUESTTM searching algorithm using Proteome Discoverer software (version 2.1; Thermo Fisher Scientific). Spectra were searched against the UniProt human reference proteome (release on March 17, 2017, containing 21,042 entries) using an in-house Proteome Discoverer Searching Algorithm (version 2.1; Thermo Fisher Scientific). The search criteria were: full tryptic specificity was required; two missed cleavage sites were allowed; oxidation of methionine, 13C(6)15N(2) at lysine, 13C(6) at arginine, and acetylation of protein N terminus were set as variable modifications; carbamidomethylation of cysteine was set as the fixed modification; and precursor ion mass tolerance was set at 10 ppm for all MS and 20 mmu for all MS2 spectra. Peptide false discovery rate (FDR) was estimated using the percolator function provided by Proteome Discoverer, with a cutoff score of 1% based on decoy database searching. Proteome Discoverer Searching Algorithm was used for protein quantification. Briefly, relative protein expression ratios were calculated using the peak area of Lys0Arg0 divided by the peak area of Lys8Arg6. Only peptides assigned to a given protein group were considered unique. Proteins with two or more unique peptide matches were regarded as confident identifications and further quantified. Differences in protein abundance between sample and control groups were calculated by averaging unique peptide ratios for that protein. Quantitative precision was expressed as protein ratio variability. Proteins with fold-change > 2 or < 0.5 and p values < 0.05 by t test statistic were considered significantly changed. MS proteomic data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRoteomics IDEntifications (PRIDE) partner repository with the data set identifiers, PXD010284, PXD010286, PXD009916, and PXD009917. ROS levels in CD38(−) and CD38(+) A549 cells were detected using CellROX® Deep Red Reagents (Invitrogen, Grand Island, NY), according to the manufacturer's protocol. Briefly, cells were seeded into 6-well cell culture plates. CellROX® Deep Red Reagents were added to a final concentration of 5 μm and incubated at 37 °C for 30 min. Fluorescence was measured with a BD FACSAria II Flow Cytometer (BD Biosciences, San Jose, CA). Cells were washed twice with ice-cold PBS and extracted with 80% precooled methanol. Samples were dried by speedvac and redissolved in 80% methanol for LC-MS/MS analysis. Quantitative analysis of metabolites extracted from CD38(−) and CD38(+) A549 cells was performed using the Q-Exactive Mass Spectrometer. Atlantis HILIC silica columns (2.1 × 100 mm, 3 μm; Waters, Milford, MA) were used for positive separation. Metabolites were identified based on retention time on LC analysis. Accurate mass was measured with < 5 ppm mass accuracy. TraceFinder was used to identify peaks and extract quantitative information. CD38(−) and CD38(+) A549 cells were seeded into 96-well plates with 4000 cells/well. After 36 h incubation, cells were treated with hydrogen peroxide (Aladdin, Shanghai, China) and cisplatin (Selleck, Houston, TX) in triplicate for 24 h. Cell counting kit-8 (CCK-8) reagent was added to treated cells and incubated at 37 °C for 2 h. Optical density (OD) was measured at 450 nm with a microplate reader (Bio-Rad). Cell viability was represented as the percentage of viable cells compared with untreated cells. CD38(−) A549 cells were cultured in SILAC culture media and CD38(+) A549 cells were cultured in normal RMPI-1640 media. Cells were harvested and lysed for 30 min on ice with RIPA lysis buffer (Solarbio, Beijing, China) supplemented with 1% Protease Inhibitor Mixture and phosphatase inhibitor (Thermo Fisher Scie
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