Proteomic Analysis of Different Temporal Expression Patterns Induced by N-Methyl-N′-nitro-N-nitrosoguanidine Treatment Jing Shen,† Wenzhang Chen,‡ Xuefeng Yin,*,‡ and Yingnian Yu*,† Department of Pathology and Pathophysiology, Zhejiang University School of Medicine, Hangzhou 310058, China, and Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou 310027, China Received February 18, 2008
We have previously shown that N-methyl-N′-nitro-N-nitrosoguanidine (MNNG), a well-known DNA alkylating agent and carcinogen, can induce multiple cellular responses with dynamic characteristics, including such responses as nontargeted mutations (NTM) at undamaged bases in DNA, up-regulation of low fidelity DNA polymerases, clustering of epidermal growth factor receptor (EGFR) and interference with its downstream signaling pathway. A dose-related analysis also revealed that different concentrations of MNNG can trigger diverse proteome changes associated with different cytotoxic effects. To further understand the dynamic cellular responses and hazardous effects caused by environmental carcinogen, a proteomic time-course study of whole cellular proteins from human amniotic epithelial cells after MNNG treatment was performed. Analysis at three different time points (3, 12 and 24 h after exposure) revealed that the major changes were taking place around 3 and 12 h after exposure. Using MALDI-TOF MS coupled with a micro solid-phase extraction (SPE) device, 90% (n ) 70) differentially expressed proteins were identified. Functional assignment revealed that many important pathways were affected, including the protein biosynthesis pathway and Ran GTPase system. We also carried out a network analysis of these proteins and the data suggest a central role for some key regulators in different pathways. Keywords: N-Methyl-N′-nitro-N-nitrosoguanidine • Proteomic profiling • Two-dimensional gel electrophoresis • Mass spectrometry
Introduction Agents exhibiting DNA methylating properties are highly potent in their ability to induce genotoxic and carcinogenic effects. They are of great significance both as environmental carcinogens (e.g., nitrosamines) and tumor therapeutic drugs (e.g., Temozolomide, procarbazine and dacarbazine). The model methylating mutagen most often used in experimental mutagenesis is N-methyl-N′-nitro-N-nitrosoguanidine (MNNG) which induces, among many other lesions, O6-methylguanine (O6MeG) in DNA. It is used in many animal models of carcinogenesis, and its use is particularly well-established in gastric cancer research. As exposure to environmental hazardous agents always leads to highly dynamic spatiotemporal responses before finally resulting in human diseases, MNNGinduced cellular responses also change in waves over time and turn out to be very complicated. It has been shown that both p53 up-regulation/phosphorylation and DNA strand breaks are induced rapidly after MNNG treatment,1 whereas apoptosis and * To whom correspondence should be addressed. Prof. Yingnian Yu, Department of Pathology and Pathophysiology, Zhejiang University School of Medicine, Hangzhou 310058, China. E-mail,
[email protected]; fax, +86571-88208209. Prof. Xuefeng Yin, Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou 310027, China. E-mail,
[email protected]; fax, +86-571-87952070. † Zhejiang University School of Medicine. ‡ Department of Chemistry, Zhejiang University. 10.1021/pr800133q CCC: $40.75
2008 American Chemical Society
mismatch repair (MMR)-dependent G2 arrest always occur as late responses (beyond 20-24 h after exposure).2–5 Our previous studies have shown that even low concentrations of MNNG (0.2∼2 µM) can trigger multiple cellular responses. Also, versatile cellular reactions with variable timecourse characteristics were revealed. For instance, phasic analysis indicated that the frequency of MNNG-induced nontargeted mutations (NTMs), which occurred at undamaged DNA bases increased gradually, reached a peak at 12 h after MNNG treatment, and then declined to the control level at 24 h after exposure.6 Similarly, DNA polymerase β and the catalytic subunit REV3 of human pol ξ were both up-regulated at the transcriptional level around 6-24 h following MNNG treatment.7,8 In contrast, some cellular responses occurred almost immediately. We found cell surface receptors for epidermal growth factor (EGF) and tumor necrosis factor R (TNFR) clustered at the cellular membrane as early as 15 min after MNNG exposure. Additionally, ER stress and several signal transduction pathways such as the c-Jun N-terminal Kinase (JNK) and cAMP-PKA-CREB pathways were also observed to be activated from 30 min to 2.5 h after MNNG treatment.9–13 All these findings provided a complicated and dynamic overview of cellular responses induced by this mutagen. With the help of some high-throughput techniques, such as microarray and proteomic analysis, we are now able to capture Journal of Proteome Research 2008, 7, 2999–3009 2999 Published on Web 06/13/2008
research articles the global view of cellular responses instead of a keyhole view. Since proteins rather than mRNA are usually the functional executors in cells, it is crucial to understand the expression and/or regulation of proteins under stress. We have shown previously with a proteomic approach that exposure to different concentrations of MNNG can induce comprehensive and various changes in the protein expression profile.14 The results indicated that with an increase in the concentrations of MNNG and the enhancement of its cytotoxic effects, the proportion of up-regulated proteins decreased, while down-regulated proteins gradually increased. As the concentrations of environmental carcinogens in DNA damage analysis are always much higher than what might be encountered in the environment, it is important to study dynamic cellular responses under low concentrations of carcinogens. In this study, we monitored the proteomic changes at three different time points (3, 12 and 24 h) following 1 µM MNNG treatment. This MNNG concentration was chosen for its relatively low cytotoxic effect and more evident cellular response compared to high concentrations of MNNG, as confirmed by our previous experiments. As reported here, 78 proteins were found to be differentially regulated, and 70 of them were identified by MALDI-MS. To probe the proteins affected by MNNG treatment as much as possible, we applied a solid-phase extraction (SPE) device after the traditional enzyme digestion process, which turned out to be quite efficient, increasing the protein detection sensitivity by MS from 80% to 90%. Our results revealed that the major changes were taking place around 3 and 12 h after exposure (82.5% proteins were altered in expression at these two time points). A network analysis of the differentially expressed proteins revealed some of these proteins to be key regulators, suggesting that these proteins may play a central role in a variety of different cytotoxic pathways.
Materials and Methods Cell Culture and Treatment. The human amniotic epithelial cell (FL cell) (ATCC CCL-62), with typical morphology and epithelial cell biomarker expression, was selected as the model cell for this study. Cells were cultured in Eagle’s minimal essential medium (MEM) supplemented with 10% newborn bovine serum, 100 units/mL penicillin, 100 µg/mL streptomycin and 200 µg/mL kanamycin in a water-saturated, 5% CO2 atmosphere at 37 °C. When cells achieved logarithmic growth, they were exposed to 1 µM MNNG (Sigma, St. Louis, MO) for 2 h, a dose which did not significantly affect cell viability. Dimethyl sulfoxide (DMSO) was used as solvent control. After removing the chemicals completely, cells were recovered in fresh medium and collected at three different time points before lysis. Sample Preparation. Cells were harvested with 0.02% EDTA and 0.025% trypsin and pelleted by centrifugation. The pellet was subsequently rinsed with PBS and solubilized in lysis buffer containing 7 M urea, 2 M thiourea, 4% CHAPS, 40 mM Tris base, 1% DTT, 2% IPG buffer, pH 3-10, 35 µg/mL PMSF, 0.5 µg/mL leupeptin and 2 µg/mL aprotinin. After intermittent sonication at 4 °C by 30 s/60 s for 1-2 min, cell lysates were incubated at room temperature for 60 min and further centrifuged at 20 000g for 60 min at 4 °C. Supernatant was collected and stored at -70 °C prior to electrophoresis. Protein concentrations were determined by Bradford assay. Two Dimensional Gel Electrophoresis (2-DE). 2-DE was performed in Ettan IPGphor II IEF and DALT II systems (Amersham Biosciences, Sweden) according to the manufac3000
Journal of Proteome Research • Vol. 7, No. 7, 2008
Shen et al. turer’s instructions. Briefly, 300 µg of total proteins was diluted with a rehydration solution (7 M urea, 2 M thiourea, 2% CHAPS, 0.4% DTT, 0.5% IPG buffer, pH 4-7, 0.002% bromophenol blue) to 450 µL and applied to 24 cm Immobiline Drystrips (pH 4-7, Amersham Biosciences). For each time point group (control or MNNG-treated), three protein samples obtained from three independent experiments were analyzed. Rehydration and IEF were carried out on the Amersham Biosciences IPGphor as follows: rehydration was begun with 50 V for 12 h, followed by 200 V for 1 h, 500 V for 1 h, 1000 V for 1 h, 1000-8000 V for 30 min and 8000 V was applied until the total Vh reached 67.0-70.0 kVh at 20 °C. After IEF separation, the strips were equilibrated for 15 min in an equilibration buffer (50 mM TrisHCl, 6 M Urea, 30% glycerol, 2% SDS and 0.002% bromophenol blue) containing 1% DTT, then equilibrated again for another 15 min in the same buffer, except that DTT was replaced with 2.5% iodoacetamide. Second-dimension SDS electrophoresis was carried out on 12.5% slab gels using the ETTAN DALT II electrophoresis system (Amersham Biosciences) at 15 °C. SDSPAGE was run at a constant power of 2.5 W/gel for 15 min, and switched to 15 W/gel until the bromophenol blue frontier reached the bottom of the gel. Gel Visualization, Image Acquisition, and Statistical Analysis. Silver staining, one of the most sensitive and MS compatible staining techniques for protein detection in 2-DE based proteomic analysis, was performed as we previously described.14 The silver-stained gels were scanned and analyzed by PDQuest version7.4.0 (Bio-Rad) according to following procedures: spot detection, spot editing, background subtraction, spot matching and normalization (each spot volume/total spot volume × 100). The resulting data were exported to Microsoft Excel, and statistical analysis was performed with Student’s t test. A probability level of P < 0.05 was considered significant. In-Gel Digestion. Spots of interest were chosen from the gels and subjected to in-gel digestion. Briefly, the spots were destained in a freshly prepared 1:1 solution of 30 mM potassium ferricyanide and 100 mM sodium thiosulfate for 1-2 min until the brownish color disappeared. They were then rinsed three times with distilled water to stop the reaction. Next, the gel pieces were incubated in 100 mM ammonium bicarbonate for 5 min, dehydrated with acetonitrile (ACN), and dried in a Speed-Vac (Thermo Savant). Then they were further swollen in a digestion buffer containing 40 mM ammonium bicarbonate, 9% ACN and 20 µg/mL trypsin (Sigma, proteomics sequencing grade) in an ice-cold bath. After 30 min, the extra liquid was removed, the same buffer without trypsin was added to keep the gels wet, and they were incubated at 37 °C overnight. Peptides were extracted twice with 50% ACN and 5% trifluoroacetic acid (TFA) at room temperature and dried in a vacuum centrifuge. Dried-Droplet Sample Preparation Method. Peptides were dissolved in 0.1% TFA, and 1 µL of the mixture was mixed with an equal volume of 10 mg/mL CHCA saturated with 50% ACN in 0.1% TFA. The total 2 µL solution was applied onto a target and allowed to air-dry. Protocol for Sample Cleanup/Enrichment of the Micro SPE Column. The micro SPE chip was fabricated on a glass substrate using photolithographic and wet chemical etching methods as we previously described.15 Sample preparation for the micro SPE column was performed according to the following scheme: (1) equilibration with 1 µL of 0.1% TFA; (2) sample injection after acidifying with TFA to a concentration of ∼0.1% (v/v); (3) washing with 1 µL of 0.1% (v/v) TFA; (4) running the
Proteomics of Temporal Patterns Induced by MNNG Treatment column completely dry by passing air through the column for a few seconds; (5) the addition of 0.5 µL eluent, also containing the MALDI matrix (saturated CHCA solution (50% ACN/0.1% TFA)-80% ACN/0.1% TFA; 1:1) into the access hole, and pressing the plastic injector gently. When 50 nL of CHCA solution had been added into the channel, the residual CHCA solution was aspirated completely away from the access hole using a pipet. Then, under the air pressure generated by pressing the plastic injector, the 50 nL of CHCA, which filled the channel, was moved slowly though the column and deposited onto the MALDI-TOF-MS target directly and airdried. Protein Identification by MS. The spectra were obtained using a Voyager-DE STR MALDI-TOF mass spectrometer (Applied Biosystems, Foster City, CA) in a reflector/delayed extraction mode. Peptide mass mapping was performed in the positive ion reflector mode, and 200 single-shot spectra were accumulated with a mass range from 800 to 4000 Da. External calibration was carried out using ACTH18-39 and P14R (Sigma) and the internal calibration was performed using the autolytic peaks of trypsin. Proteins were identified using the Mascot software (http:// www.matrixscience.com) and the nrNCBI database, based on peptide mass fingerprinting. The search parameters were defined as follows: cysteine as carbamidomethylated, methionine as oxidized, maximal mass tolerance of 100 ppm and up to 1 missed enzymatic cleavage. Western Blot Analysis. After SDS-PAGE, gels were transferred electrophoretically onto a nitrocellulose membrane (Micron Separations, Inc., Westborough, MA) and blocked for 2 h with Tris-buffered saline (TBS) containing 5% skim milk. Primary antibodies included goat anti-human EIF3S3 (Santa Cruz, CA) and mouse anti-human 14-3-3ε (Santa Cruz, CA,). Membranes were incubated with the primary antibody overnight at 4 °C, washed three times with TBS containing 0.1% Tween-20, incubated with a horseradish peroxidase-conjugated secondary antibody for 1 h at room temperature, and then developed with a chemiluminescence reagent (EZ-ECL Chemiluminescence Detection Kit, Israel). For detecting actin as a loading control, the same blot was first washed several times with TBS containing 0.1% Tween-20 and then stripped by incubation with a stripping buffer containing 65 mM Tris-HCl, pH 7.5, 100 mM β-mercaptoethanol, and 2% SDS for 30 min at 50 °C, followed by washing four times with TBS at room temperature. Actin was then probed by incubating the membrane with a rabbit anti-human actin antibody (Santa Cruz, CA), followed by the same steps used to detect EIF3S3 and 14-3-3ε. Biological Network Analysis. After obtaining the list of proteins which were differentially expressed after MNNG treatment from the MALDI-TOF MS analysis, a corresponding gene list was created from this protein list. The list was then analyzed by Pathway Studio software (http://www.ariadnegenomics.com, Ariadne Genomics, Rockville, MD). Briefly, the gene list was run against the ResNet database that is equipped with functional relationships from other scientific literature and commercial databases. The filters that we applied included ‘all shortest paths between selected entities’ and ‘expand pathway’. The information received was narrowed down to our protein list of interest in which their involvement and regulatory functions were observed. Protein entities which belong to different functional groups were represented as different shapes according to the default settings of the software, such as “sickle” for kinases, “rhomb” for ligands and “stick” for receptors.
research articles
Figure 1. Representative 2-DE gel image indicating differentially expressed protein spots identified by MS analysis after MNNG exposure. The global cellular proteins extracted from FL cells (300 µg) were separated on a pH 4-7 linear IPG strip, followed by 12.5% SDS-PAGE. The gel was visualized by silver staining and differentially expressed proteins were numbered.
Results Analysis of Differentially Expressed Proteins after MNNG Treatment. Protein lysates obtained from control and MNNGtreated FL cells at different time points after exposure were analyzed by 2-DE. In our previous studies, many of the cellular responses observed following MNNG treatment were more apparent around 12 h after treatment, including such responses as nontargeted mutations (NTMs) and up-regulation of low fidelity DNA polymerases pol-β and pol-ξ. Because of this, the 12 h proteomic profile was chosen for analysis. In addition, one early (3 h) and one late (24 h) time point were chosen in an attempt to distinguish between early and late effects induced by MNNG. All the changes were assumed to be at the proapoptosis stage, since apoptosis is known as a late response which occurs over 24 h after MNNG treatment.2,3 A representative gel image with silver staining is shown in Figure 1. Using the PDQuest 7.4 analysis software, 1904 ( 119 and 1890 ( 135 protein spots were detected in control and MNNG-treated cells in the 3 h group, whereas 1836 ( 183 and 1906 ( 148 spots were detected in the 12 h group and 1905 ( 153 and 1886 ( 167 spots in the 24 h group, respectively. Among them, 29, 37 and 14 spots were observed as differentially expressed at the time points of 3 h, 12 and 24 h after MNNG exposure, respectively. Most proteins (82.5% of all) found to be differentially regulated were detected at the 3 and 12 h time points. The relative volumes and the spot volume ratios between treated and untreated cells are listed in Tables 1–3. Identification of Proteins by MALDI-TOF MS Coupled with a Micro SPE Device. The differentially expressed spots were excised from the sliver-stained gels, followed by in-gel digestion with trypsin, and were identified by MALDI-TOF-MS analysis and the database search. To facilitate the identification of low-abundance proteins, we have developed a nanoscale solid-phase extraction (SPE) device to increase the detection sensitivity in MALDI-TOF-MS analysis.15 Among the identified proteins summarized in Tables 1–3, 62 protein spots were identified with the traditional dried-droplet sample preparation method, while 8 more spots with low abundance were successfully identified after enrichment with the micro SPE device. Journal of Proteome Research • Vol. 7, No. 7, 2008 3001
3002
4.80 6.10
4.95 5.54 5.32 5.54
59.7 26.6 38.0
50.5
27.6 29.5
59.7
23.3 31.2 36.4 39.8
19.8
26.8
14.3
48.4 117.2
13.5 30.6
46.5 16.0 25.8 33.1
6618 7205 7424
6618
2312 2315
6618
Journal of Proteome Research • Vol. 7, No. 7, 2008
0301 1420 2414 7419
0025
1409
4005
2601 6802
0027 0310, 6211 2611 3010 3213 4306
6/18 8/12, 11/25 15/22 9/25 9/30 9/27
28/40 15/23
7/19
10/32
7/14
6/12 9/18 17/37 9/20
8/24
9/21 7/16
9/24
8/24 12/25 10/18
16/46 11/32
7/18 14/29
peptide match
43 21, 27 44 61 46 40
62 18
58
59
35
32 28 40 16
18
31 38
25
18 58 37
28 30
60 33
cov. (%)
b
protein description
89 117, 103 210 119 104 101
protein disulfide isomerase family A, member 5 coactosin-like 1 adrenal gland protein AD-003 pyrophosphatase 1
Unkown Huntingtin interacting protein K penta-EF hand domain-containing protein 1(Peflin)
361 keratin 17 135 vinculin
Microtubule or Cytoskeleton Organization
89 programmed cell death 5
NP_006801 NP_066972 NP_054783 NP_066952.1
NP_057484.3 NP_036524
NP_000413 NP_054706
NP_004699.1
NP_004485
Apoptosis
NP_006462.1
Cell Proliferation 112 hepatoma-derived growth factor
NP_005585 NP_001951 NP_004085 NP_003747
NP_002970
Development 98 myosin regulatory light chain MRCL3
93 90 158 94
Protein Biosynthesis nascent-polypeptide-associated complex alpha subunit isoform b eukaryotic translation elongation factor 1 delta isoform 2 eukaryotic translation initiation factor 2, subunit 1 alpha eukaryotic translation initiation factor 3, subunit 3 gamma
Transport 155 sterol carrier protein-X/sterol carrier protein-2
PTPN1
SCP2 IDI1 PCBP1
HMGCS1 SULT1A3
TCEB2 ACTL6A
coding gene
PDIA5 COTL1 C9orf32 PPA1
HYPK PEF1
KRT17 VCL
PDCD5
HDGF
MRCL3
NACA EEF1D EIF2S1 EIF3H
SCP2
NP_001026854 SFRS7 NP_112420 HMRPA1
NP_002818
Signal Transduction 155 protein tyrosine phosphatase, nonreceptor type 1 RNA Splicing and Processing 92 splicing factor, arginine/serine-rich 7, 35 kDa, isoform 1 90 heterogeneous nuclear ribonucleoprotein A1
NP_002970 NP_004499 NP_006187.1
NP_002121 NP_003157.1
NP_996896 NP_004292.1
RefSeq no.
Metabolism 128 3-hydroxy-3-methylglutaryl-Coenzyme A synthase 1 (soluble) 115 sulfotransferase family, cytosolic, 1A, phenol-preferring, member3 155 sterol carrier protein-X/sterol carrier protein-2 173 isopentenyl-diphosphate delta-isomerase 1 133 poly(rC) binding protein 1
Regulation of Transcription 103 transcription elongation factor B polypeptide 2 147 Actin-like 6A
score
Mascot search results treatedc
0.031 ( 0.007 (0.68)V 0.146 ( 0.014 (0.81)V
0.077 ( 0.012 (2.14) v
0.072 ( 0.007 0.110 ( 0.015 0.102 ( 0.002 0.231 ( 0.029 0.140 ( 0.020 0.119 ( 0.009 0.116 ( 0.003
0.131 ( 0.005 0.025 ( 0.003
0.075 ( 0.015
0.025 ( 0.009
0.112 ( 0.019
0.024 ( 0.014 0.028 ( 0.002 0.041 ( 0.006 0.082 ( 0.017
0.036 ( 0.007
( ( ( (
0.032 0.004 0.004 0.023
(3.51) v (0.70)V (0.69)V (1.80) v
0.116 0.082 0.088 0.137 0.189 0.090 0.098
c
( ( ( ( ( ( (
The number in
0.020 (1.60) v 0.007 (0.75) V, 0.008 (0.86)V 0.049 (0.59)V 0.016 (1.35) v 0.007(0.75)V 0.009 (0.85)V
0.098 ( 0.009 (0.75)V 0.014 ( 0.004 (0.56)V
0.123 ( 0.021 (1.64) v
0.072 ( 0.021 (2.90) v
0.180 ( 0.010 (1.61) v
0.085 0.020 0.029 0.148
0.077 ( 0.012 (2.14) v
0.057 ( 0.009 0.034 ( 0.011 (0.59)V 0.027 ( 0.003 0.018 ( 0.003 (0.68)V
0.036 ( 0.007
0.036 ( 0.007 0.077 ( 0.012 (2.14) v 0.192 ( 0.013 0.156 ( 0.017 (0.81)V 0.067 ( 0.012 0.092 ( 0.009 (1.37) v
0.045 ( 0.004 0.180 ( 0.002
0.216 ( 0.051 0.315 ( 0.019 (1.46) v 0.075 ( 0.005 0.090 ( 0.006 (1.20) v
control
spot volume/total volume (%)
a Number of peptides that matched those from the nrNCBI database entry and number of peptides searched. b Percentage of the protein sequence covered by the matching peptides. parentheses denotes the ratio of the relative spot volume of treated and control (treated/control) and the upward arrow indicates up-regulation, the downward arrow indicates down-regulation.
4.97 5.83
5.77
4.70
4.72
4.52 4.90 5.02 5.96
6.30
11.83 9.19
5.88
6.30 5.93 6.66
5.22 5.68
57.8 34.3
3702 5313
4.73 5.39
13.2 47.9
pI
0022 4604
index no. MW (kDa)
a
Table 1. Identification of the Differentially Expressed Proteins in FL Cells at 3 h after MNNG Exposure
research articles Shen et al.
4.76
5.02 4.97 5.30
4.74 4.83 9.79 4.96 5.98
5.24 6.05 6.15
27.9 88.9
57.5
27.2 34.7 47.2
31.2
37.8
27.5
26.8
41.1
33.3 22.0 14.4 42.4 22.8
35.3 24.8 83.9
2405 3922
1702, 1704 2310 2327 3527
1323,1426
7401
4307
1409
1318
0318 2305 2327 2502 3214, 3216 3401 6222 6815
7/18 15/30 6/18 12/35 6/8, 5/8 9/19 7/10 25/29
9/14
10/32
13/31
9/17
11/26, 15/24
23/38, 20/33 9/22 10/18 12/34
12/37 20/57
15/38 14/28
12/29
15/30
7/16 10/21 14/20 12/25 11/23
17/37 9/27 9/18
7/17 11/23 8/22
Peptide matcha
34 31 33
32 56 56 22 33, 26
30
59
43
34
24, 51
48 32 46
45, 37
41 27
20 25
44
61
45 34 33 58 33
50 39 26
59 14 43
cov. (%)b
87 206 193 105 106, 82 104 115 315
108
112
140
105
101, 213
264, 232 120 193 133
301 133
111 131
129
162
101 130 190 173 131
301 102 114
115 85 105
score
NP_112604 NP_005868.1 NP_000909.2
Transport prolyl 4-hydroxylase, beta subunit
NP_004485 NP_002264 NP_112594.1 NP_001272.2 NP_987091 NP_783163.1 NP_001531.1
Microtubule or Cytoskeleton Organization keratin 8 Unkown deoxyhypusine hydroxylase/monooxygenase tubulin folding cofactor B COMM domain containing 6 adhesion regulating molecule 1 heat shock 27 kDa protein 1
NP_004679.1 NP_005380 NP_006830
NP_002809
Cell Proliferation hepatoma-derived growth factor
N-myc and STAT interactor protein-L-isoaspartate (D-aspartate) O-methyltransferase mitochondrial inner membrane protein, (mitofilin)
NP_006828.2
Immune Response proteasome activator subunit 2
NP_001951
Protein Biosynthesis eukaryotic translation elongation factor 1 delta isoform 2 COP9 signalosome subunit 5
NP_001279.2 NP_955474 NP_005808
chloride intracellular channel 1 epsilon subunit of coatomer protein complex isoform a mannose-6-phosphate receptor binding protein 1
NP_006817.1
RNA Splicing and Processing heterogeneous nuclear ribonucleoprotein C splicing factor 3a, subunit 1, 120 kDa isoform 1
NP_000843 NP_006388.2 NP_005521.1 NP_004499 NP_005882
Metabolism glutathione S-transferase pi ribonuclease H2 subunit A isocitrate dehydrogenase 3 (NAD+) alpha isopentenyl-diphosphate delta-isomerase 1 acetyl-Coenzyme A acetyltransferase 2
NP_003861 NP_002874
NP_006695 NP_004147 NP_002803.1
Cell Cycle SGT1B protein protein phosphatase type 2A catalytic subunit proteasome 26S non-ATPase subunit 8
NP_006752.1
NP_005639.1 NP_942596.1 NP_005197.3
Regulation of Transcription transcription elongation factor B polypeptide 1 zinc finger protein 160 v-crk sarcoma virus CT10 oncogene homologue isoform b
Signal Transduction tyrosine 3-monooxygenase/ tryptophan 5-monooxygenase activation protein, epsilon polypeptide tyrosine 3-monooxygenase/ tryptophan 5-monooxygenase activation protein, theta polypeptide IQ motif containing GAPase activating protein 1 RAN GAPase activating protein 1
RefSeq no.
protein description
Mascot search results
NMI PCMT1 IMMT
DOHH TBCB COMMD6 ADRM1 HSPB1
KRT8
HDGF
PSME2
COPS5
EEF1D
CLIC1 COPE M6PRBP1
P4HB
HNRPC SF3A1
IQGAP1 RANGAP1
YWHAQ
YWHAE
GSTP1 RNASEH2A IDH3A IDI1 ACAT2
SUGT1 PPP2CB PSMD8
TCEB1 ZNF160 CRK
coding gene
0.036 ( 0.002 0.043 ( 0.010 0.134 ( 0.024 0.066 ( 0.004 0.146 ( 0.021, 0.094 ( 0.016 0.044 ( 0.006 0.051 ( 0.017 0.037 ( 0.005
0.038 ( 0.002
0.053 ( 0.001
0.531 ( 0.055
0.040 ( 0.001, 0.196 ( 0.008 0.074 ( 0.011
0.049 ( 0.004, 0.239 ( 0.011 0.062 ( 0.016 0.134 ( 0.024 0.116 ( 0.034
0.052 ( 0.006 0.014 ( 0.006
( ( ( ( (
0.002 0.017 0.023 0.030 0.010
(0.77) V, (0.76)V (1.81) v (1.54) v (0.34)V
0.050 0.080 0.206 0.094 0.076 0.059 0.067 0.082 0.020
c
( ( ( ( ( ( ( ( (
(1.39) v (1.88) v (1.54) v (1.43) v (0.52) V, (0.62)V (1.54) v (1.61) v (0.53)V The number in
0.003 0.011 0.030 0.016 0.017 0.009 0.011 0.007 0.009
0.031 ( 0.004 (0.80)V
0.044 ( 0.003 (0.83)V
0.692 ( 0.009 (1.30) v
0.057 ( 0.007 (1.42) v, 0.236 ( 0.013 (1.21) v 0.121 ( 0.022 (1.64) v
0.038 0.183 0.112 0.206 0.039
0.070 ( 0.007 (1.36) v 0.031 ( 0.003 (2.19) v
0.386 ( 0.098 (1.78) v 0.018 ( 0.002 (0.61)V 0.014 ( 0.002 (1.41) v
(0.58)V (1.23) v (1.79) v (1.72) v (1.51) v
0.217 ( 0.011
0.005 0.007 0.044 0.021 0.043
0.030 ( 0.005 0.010 ( 0.001
( ( ( ( (
0.905 ( 0.161 (2.14) v
0.023 0.106 0.323 0.240 0.236
0.070 ( 0.007 (1.36) v 0.057 ( 0.003 (1.17) v 0.123 ( 0.014 (1.53) v
0.181 ( 0.033 (0.42) V 0.136 ( 0.025 (0.63) V 0.042 ( 0.003 (1.60) v
0.423 ( 0.065
0.040 ( 0.005 0.086 ( 0.002 0.181 ( 0.007 0.140 ( 0.050 0.156 ( 0.018
0.052 ( 0.006 0.048 ( 0.003 0.081 ( 0.011
0.429 ( 0.114 0.214 ( 0.037 0.026 ( 0.004
treatedc
spot volume/total volume (%) control
a Number of peptides that matched those from the nrNCBI database entry and number of peptides searched. b Percentage of the protein sequence covered by the matching peptides. parentheses denotes the ratio of the relative spot volume of treated and control (treated/control) and the upward arrow indicates up-regulation, the downward arrow indicates down-regulation.
4.94
4.70
5.44
6.10
4.90
4.55 5.15
5.64 4.63
4.68
4.63
28.0
29.3
0214
5.43 5.05 6.47 5.93 6.27
108.0 63.5
23.6 33.7 40.0 26.6 41.7
2214 2313 6402 7205 8408
5.07 5.21 6.85
0218
41.3 36.2 30.2
2405 4407 7211
4.74 9.45 5.33
pI
1818 1827
12.6 96.8 22.9
MW (kDa)
0023 2814 3218
index no.
Table 2. Identification of the Differentially Expressed Proteins in FL Cells at 12 h after MNNG Exposure
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Journal of Proteome Research • Vol. 7, No. 7, 2008 3003
3004
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The number in c a Number of peptides that matched those from the nrNCBI database entry and number of peptides searched. b Percentage of the protein sequence covered by the matching peptides. parentheses denotes the ratio of the relative spot volume of treated and control (treated/control) and the upward arrow indicates up-regulation, the downward arrow indicates down-regulation.
0.099 ( 0.013 (0.72)V 0.138 ( 0.003 RCN1 NP_002892.1 reticulocalbin 1 102 24 9/21 38.9 0505
4.86
0.084 ( 0.024 (0.66)V 0.128 ( 0.006 KRT18 NP_954657.1 150 48.0 4534
5.34
16/38
34
Microtubule or Cytoskeleton Organization keratin 18
Unkown
0.368 ( 0.005 (1.39) v 0.265 ( 0.035 NP_000249 Development myosin light chain 3 17.1 0024
4.51
9/24
70
128
MYL3
0.559 ( 0.083 (1.43) v 0.138 ( 0.014 (0.79)V 0.391 ( 0.039 0.175 ( 0.018 NP_002873.1 NP_036269.1 Signal Transduction RAN binding protein 1 dimethylarginine dimethylaminohydrolase 1 23.4 31.4 3203 4421
5.19 5.53
10/20 9/18
60 36
141 117
RANBP1 DDAH1
(1.35) v (1.59) v (0.65)V (0.66)V (0.74)V (0.56)V 0.031 0.005 0.004 0.029 0.025 0.011 ( ( ( ( ( ( 0.487 0.090 0.037 0.183 0.139 0.054 0.360 ( 0.043 0.057 ( 0.016 0.058 ( 0.007 0.278 ( 0.025 0.188 ( 0.011 0.096 ( 0.021 NP_000840.2 NP_000473 NP_000169.1 NP_006321.1 NP_000294.1 NP_005882 27.0 43.4 52.5 25.0 28.4 41.7 3208 4225 5612 7114 7215 7429
5.37 5.22 5.67 6.29 6.35 6.27
13/28 11/27 14/24 7/19 10/17 7/16
47 23 29 44 37 23
159 110 152 94 134 83
GSTM3 APOA4 GSS LYPLA1 PMM2 ACAT2
0.082 ( 0.008 (0.67) V 0.121 ( 0.017 NP_006387.1
Metabolism glutathione S-transferase M3 apolipoprotein A-IV precursor glutathione synthetase lysophospholipase I phosphomannomutase 2 acetyl-Coenzyme A acetyltransferase 2
102 21.9 2222
5.12
9/22
61
Cell Cycle Sjogren’s syndrome/scleroderma autoantigen 1
SSSCA1
treatedc control RefSeq no. protein description score cov. (%)b peptidematcha pI MW (kDa)
Mascot search results
Shen et al.
index no.
Table 3. Identification of the Differentially Expressed Proteins in FL Cells at 24 h after MNNG Exposure
coding gene
spot volume/total volume (%)
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In this way, the protein detection sensitivity of MS was increased from 80% to 90%. Furthermore, micro SPE also remarkably improved the sequence coverage of 3 spots identified with the traditional method. The comparison between the two methods is shown in Table 4. With the use of the Gene Ontology (GO) hierarchy and the KEGG database, identified proteins were categorized by different functional classes, such as transcription regulator, protein biosynthesis modulator, signal transducer, structure molecule and transporter, and so forth, with the categories reflecting the wide variety of cellular processes in which these proteins take part. Interestingly, 7 identified proteins were represented in more than one spot, suggesting that they were undergoing post-translational modification (PTM) or possibly alternative splicing (indicated in Tables 1–3). Network Analysis. Considering that most proteins do not act as single entities but work together in networks, we analyzed all the pathways and interactions connected to these differentially expressed proteins, aiming to find the possible key node proteins in cellular responses. Identified proteins that had undergone more than a 1.5-fold change (n ) 40) were chosen for further network analysis using Pathway Studio software. Analysis revealed that 14 of these proteins appeared to hold a central place in a variety of different networks (Figure 2), including v-crk avian sarcoma virus CT10 oncogene homologue (CRK), 14-3-3 ε (YWHAE), 14-3-3 θ (YWHAQ), heat shock 27 kDa protein 1 (HSPB1), Vinculin (VCL), heterogeneous nuclear ribonucleoprotein A1 (HNRPA1), elongin C (TCEB1), sterol carrier protein 2 (SCP2), protein tyrosine phosphatase (nonreceptor type 1, PTPN1), N-myc and STAT interactor (NMI), glutathione S-transferase pi (GSTP1), COP9 signalosome subunit 5 (COPS5), IQ motif containing GTPase activating protein 1 (IQGAP1) and keratin 18 (KRT18). This suggests that these proteins may play an important role in the modulation of cellular responses after MNNG treatment. Western Blot. From the identified candidates, 14-3-3 ε and EIF3S3 were further analyzed by Western blot as shown in Figure 3 and Figure 4. The expression change of the selected proteins was consistent with the 2-DE and silver-staining results. 14-3-3 ε was observed to be up-regulated at the 12 h time point following MNNG treatment, whereas EIF3S3 was increased at the earlier time point of 3 h.
Discussion As the identification of specific effector proteins in cellular responses is of major interest for understanding cellular responses induced by environmental carcinogens, we analyzed different temporal expression patterns induced by low concentration MNNG treatment, using the proteomic approach in our analysis. At three different time points (3, 12 and 24 h) after exposure, 78 protein spots were differentially expressed and 70 of them were identified by MALDI-MS coupled with a solidphase extraction (SPE) device. Since cellular responses to hazardous agents in the environment have different time windows in which they occur, from minutes to hours for short-term changes and hours to days even weeks for long-term changes, the three different time points in this study were chosen in an attempt to distinguish between early and late effects induced by MNNG. Most of the proteins that were identified in each time point group were different from those identified in the other time point groups, and were found to belong to a broad range of different classes and functional pathways (Table
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Proteomics of Temporal Patterns Induced by MNNG Treatment Table 4. Comparison of Micro SPE Device-Based Sample Preparation to Traditional Sample Preparation SPE-based sample preparation index no.
protein description
peptide matches
0027 0318 1323 6211 7401 7429 1818 3922
Identified Huntingtin interacting protein K deoxyhypusine hydroxylase/monooxygenase eukaryotic translation elongation factor 1 delta isoform 2 penta-EF hand domain-containing protein 1(Peflin) COP9 signalosome subunit 5 acetyl-Coenzyme A acetyltransferase 2 IQ motif containing GAPase activating protein 1 splicing factor 3a, subunit 1
2214 3527 4407
glutathione S-transferase pi Mannose-6-phosphate receptor binding protein 1 protein phosphatase type 2A catalytic subunit
a
traditional sample preparation cov (%)b
cov (%)
peptide matches
6 8 11 11 9 7 15 20
43 46 24 27 42 23 20 27
1 2 5 2 2 3 2 7
-
7 12 9
45 46 39
5 6 7
26 24 31
Improved
a Number of peptides that matched those from the nrNCBI database entry and number of peptides searched. b Percentage of the protein sequence covered by the matching peptides. Those spots could not be identified with the traditional dried-droplet sample preparation method were represented as “-“.
Figure 2. Network analysis of all the pathways and interactions connected to the differentially expressed proteins. Identified proteins that had undergone more than a 1.5-fold change (n ) 40) were chosen for network analysis. Colored circles represent proteins that were identified in this study, and gray circles represent interconnecting proteins revealed by the network software program. Upregulated proteins were colored red, and down-regulated proteins green.
1–3), indicating that rapid and diverse cellular responses were trigged after MNNG exposure. Interestingly, most of the proteins were assembled at the time points of 3 and 12 h after exposure, and both the number and alteration level of differentially expressed proteins decreased at the late time
point of 24 h, suggesting that the ‘early response’ or ‘stress response’ was induced around 3-12 h after MNNG treatment. In addition, the functional classification analysis revealed that the category profile of the 24 h group was distinct from the 3 and 12 h groups, with some classes such Journal of Proteome Research • Vol. 7, No. 7, 2008 3005
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Figure 3. Magnified 2-DE maps and Western blot analysis of 143-3 ε. (A) Magnified images of spot 0214 at the 12 h time point after MNNG exposure. The spot was identified as 14-3-3 ε by MALDI-TOF MS. (B) Detection of 14-3-3 ε at different time points by Western blotting. The blot was also probed with actin antibody as a control for loading. (C) Intensities of protein bands were quantified by densitometry and data were normalized to actin signals. Data were indicated as means ( SD from three independent experiments. The unpaired Student’s t test showed a significant difference (*p < 0.05) between the control and MNNG exposure groups at the 12 h time point.
as proteins related to protein biosynthesis and RNA splicing and processing absent from the 24 h group obviously (Figure 5). One of our previous studies has shown that the expression level of more than 80 proteins was affected by different concentrations of MNNG.14 Some proteins were also differentially expressed in this study, such as eukaryotic translation elongation factor 1 delta (EEF1D), Ran GTPase activating protein 1 (RANGAP1), hepatoma-derived growth factor (HDGF), glutathione S-transferase M3 (GSTM3), heterogeneous nuclear ribonucleoprotein A1 (HNRPA1), keratin 8 (KRT8), protein tyrosine phosphatase (nonreceptor type 1, PTPN1), and so forth. and the functional category profiles of all the differentially regulated proteins in these two studies were also similar (Figure 5), indicating that exposure to MNNG may influence some same or related pathways or fuctional modules in different cellular responses. For the purpose of revealing the possible key node proteins in MNNG-induced cellular responses, identified proteins that had undergone more than a 1.5-fold change were placed in an interaction network analysis (Figure 2). The proteins found to play central roles in different networks can be mainly classified into several groups including (i) adapter proteins (CRK, NMI 3006
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Figure 4. Magnified 2-DE maps and Western blot analysis of EIF3S3. (A) Magnified images of spot 7419 at the 3 h time point after MNNG exposure. The spot was identified as EIF3S3 by MALDI-TOF MS. (B) Detection of EIF3S3 at different time points by Western blotting. The blot was also probed with actin antibody as a control for loading. (C) Intensities of protein bands were quantified by densitometry and data were normalized to actin signals. Data were indicated as means ( SD from three independent experiments. The unpaired Student’s t test showed a significant difference (*p < 0.05) between the control and MNNG exposure groups at the 3 h time point.
and 14-3-3s); (ii) signaling pathway regulators (HSPB1, COPS5 and IQGAP1); (iii) cytoskeletal proteins (VCL, KRT18); (iV) RNA metabolism related proteins (HNRPA1, TCEB1). Among them, all adapter proteins were found to be up-regulated, which was consistent with their expected role as positive modulators in cellular pathways. In contrast, some of the down-regulated proteins, such as the heat shock protein HSPB1 and the cytoskeletal protein VCL, either have a shift in pI or MW, suggesting that they are undergoing post-translational modification (PTM) or possibly alternative splicing. The other two proteins, protein tyrosine phosphatase PTPN1 and sterol carrier protein SCP2, were identified from the same spot. Therefore, it is at present not possible to conclude which of these two proteins actually changed expression upon treatment. Further analysis using narrow pH range zoom strips could tackle this problem. One of the key regulators, known as 14-3-3 proteins, especially drew our attention for their diverse biological functions and huge amount of binding partners.16–21 The 14-3-3 protein family contains seven distinct isoforms in mammalian cells. In the previous dose-related proteomic analysis, we had already
Proteomics of Temporal Patterns Induced by MNNG Treatment
Figure 5. Proteins with altered expression in previous doserelated study and present time-course study were organized into different functional categories. Circles represent the number of proteins in a given category of biological activity identified in these studies. The size of a circle is proportional to the number of expressed proteins (smallest circles, one protein; largest, 15 proteins).
found that the expression level of 14-3-3 β and γ were increased in 0.25 and 10 µM MNNG treatment groups, respectively.14 Interestingly, in this study, the other two isoforms, 14-3-3 ε and θ, were also observed to be up-regulated at the 12 h time point after MNNG treatment. The alteration of 14-3-3 ε was further confirmed by Western blot (Figure 3). It has been reported that these two isoforms participate in many crucial cellular processes, such as regulation of the cell cycle, apoptosis, and DNA damage responses, and play an important role in survival and apoptotic pathway integrations.17 Both of them were found to function at several key points in G1/S- and G2/M-transition by binding to regulatory proteins and modulating their functions.18 Isoform ε can also bind to the nuclear localization signal (NLS) region of DP-3 (a component of E2F), and this interaction alters the cell cycle and apoptotic properties of E2F.22 The two isoforms also exhibit an IR-specific interaction with wild-type p53, and contribute to the activation of p53 in response to IR induced DNA damages.23 As MNNG can also induce DNA damage, G2/M arrest and apoptosis, 14-3-3 proteins may be involved in the central part of all these responses induced by MNNG. Further investigation is currently underway in our laboratory, with the initial results showing that the nuclear distribution of 14-3-3s is also changed after MNNG treatment. During the functional categorization of differentially expressed proteins, several effectors were found that related to protein synthesis pathways, including eukaryotic translation initiation factor 2 subunit 1 alpha (EIF2S1), eukaryotic translation initiation factor 3 subunit 3 gamma (EIF3S3), COP9 signalosome subunit 5 (COPS5), eukaryotic translation elongation factor 1 delta (EEF1D) and nascent-polypeptide-associated complex (NAC) alpha polypeptide (NACA) (Figure 6). Most of them exhibited an increased expression profile compared with the control, with all the alterations taking placed at the 3 or 12 h time points. It is thus suggested that the protein biosynthesis rate is enhanced after MNNG exposure, which could serve as a positive cellular response to environmental hazardous agents. Protein biosynthesis is known to proceed in three
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Figure 6. Zoom image of differentially expressed proteins of RanGAP1, RanBP1, EIF2S1, EEF1D, COPS5 and NACA.
phases: initiation, elongation and termination, each of which involves a distinct set of protein factors. Three of the differentially regulated proteins, EIF2S1, EIF3S3 and COPS5, are components of the translation initiation complex, while EEF1D belongs to the translation elongation complex. Notably, three spots (1420, 1323, 1426) were identified to be the same protein EEF1D, which indicated some post-translational modifications (PTMs), phosphorylation for example, may exist. Among these proteins, the deregulation of EIF3S3 was further confirmed by Western blot (Figure 4). Many reports have demonstrated that the EIF3S3 gene is amplified and overexpressed in many tumors, including breast and prostate cancer.24–26 Further studies revealed that overexpression of this gene can promote cell growth and viability, which may provide growth advantage to the cancer cells.27 The other protein is NACA, the alpha polypeptide of NAC, which is involved in transferring growing nascent polypeptides to appropriate cotranslationally acting factors, through its interaction with the nascent chains on the ribosome.28 Recent large-scale phosphoproteomic analysis showed that the NACA protein was phosphorylated upon DNA damage, probably by ATM or ATR.29 In this study, NACA was also up-regulated (3.5-fold) and it appeared that in its modified form (perhaps phosphorylated) as there was an apparent acidic pI shift on the 2-D gel, implying its possible role in MNNG induced DNA damage responses. Another pathway that seems to be affected after MNNG treatment is the Ran GTPase system, which has been implicated in many cellular processes including cell cycle progression, nuclear envelope structure and function, and nucleocytoplasmic transport.30 Ran is regulated by a cytosolic GTPaseactivating protein, RanGAP1, and by a chromatin-bound nucleotide exchange factor, RCC1. The cytoplasmic Ran GAP1, not the SUMO-1 conjugated form, was found to be upregulated after MNNG treatment in our previous dose-related proteomic analysis,14 and showed the same alteration in the present study at the 12 h time point after exposure (Figure 6). In addition, we found that another important component of this system, RanBP1, was also up-regulated at the 24 h time point after MNNG treatment (Figure 6). It has been reported that RanBP1 is a costimulator of RanGAP activity and can inhibit RCC1-stimulated release of GTP from Ran.31,32 All the expression changes related to RanGAP1 and RanBP1 reflected Journal of Proteome Research • Vol. 7, No. 7, 2008 3007
research articles a deregulation effect on the Ran GTPase system induced by MNNG, which can in turn affect nucleocytoplasmic transport and cell cycle progression. It is difficult to assess exactly how many proteins are involved in the dynamic cellular responses that follow MNNG treatment. Although the proteome changes obtained in the present study were detected at three different time points, this is still not sufficient to completely explain all the phenomena induced by this mutagen. In addition, some of the MNNG-induced protein changes identified by other methods were not found in this study, such as the increase of p53 protein. There are several reasons that might account for the missing information: (i) the protein patterns of cellular response change in waves over time and the ‘snapshot’ taken by the time points set in this study were unable to capture some important changes; (ii) a weak point of 2-DE in general is the limitation of protein separation for extreme molecular weight and pI, low abundance, or membrane proteins, thus, only a fraction of the total proteome can be monitored; (iii) the post-translational modifications, such as phosphorylation, which may be more important in responses to DNA damaging agents, cannot be fully detected or analyzed by the present study. However, some newly developed techniques may be used to overcome these problems, such as prefractionation of the sample and the recently developed high-resolution 2-DE devices in combination with protein identification by new highly sensitive mass spectrometric techniques.33 Furthermore, a parallel profile analysis of the phosphoproteome such as enrichment of phosphorylated proteins/peptides by immunoprecipitation/chromatography, phosphorspecific fluorescence stain, autoradiography or immunoblotting may be necessary to fully understand the global responses to MNNG and the underlying mechanisms of these responses.34 Abbreviations: MNNG, N-methyl-N′-nitro-N-nitrosoguanidine; SPE, solid-phase extraction.
Acknowledgment. This work is supported by National key Basic Research and Development Program (No. 2002CB512901) of China. We thank Dr. Jimin Shao (this laboratory) for his administrative help and Dr. Jessica Watters (Loma Linda University Medical Center) for her critical review of the manuscript. References (1) Adamson, A. W.; Kim, W. J.; Shangary, S.; Baskaran, R.; Brown, K. D. ATM is activated in response to N-methyl-N’-nitro-Nnitrosoguanidine-induced DNA alkylation. J. Biol. Chem. 2002, 277, 38222–9. (2) Roos, W.; Baumgartner, M.; Kaina, B. Apoptosis triggered by DNA damage O6-methylguanine in human lymphocytes requires DNA replication and is mediated by p53 and Fas/CD95/Apo-1. Oncogene 2004, 23, 359–67. (3) Dunkern, T.; Roos, W.; Kaina, B. Apoptosis induced by MNNG in human TK6 lymphoblastoid cells is p53 and Fas/CD95/Apo-1 related. Mutat. Res. 2003, 544, 167–72. (4) Cejka, P.; Stojic, L.; Mojas, N.; Russell, A. M.; Heinimann, K.; Cannavo, E.; di Pietro, M.; Marra, G.; Jiricny, J. Methylationinduced G(2)/M arrest requires a full complement of the mismatch repair protein hMLH1. EMBO J. 2003, 22, 2245–54. (5) Stojic, L.; Mojas, N.; Cejka, P.; Di Pietro, M.; Ferrari, S.; Marra, G.; Jiricny, J. Mismatch repair-dependent G2 checkpoint induced by low doses of SN1 type methylating agents requires the ATR kinase. Genes Dev. 2004, 18, 1331–44. (6) Sun, X.; Yu, Y.; Zhang, X.; Chen, X. Phasic analysis of MNNG induced nontargeted mutation in mammalian cells. Chin. J. Pharmacol. Toxicol. 1996, 10, 77–8. (7) Feng, Z.; Yu, Y.; Chen, X. mRNA expression of DNA polymerase beta in MNNG induced genetically unstable cells. Chin. J. Pathophysiol. 1999, 15, 699–702.
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Shen et al. (8) Zhu, F.; Jin, C. X.; Song, T.; Yang, J.; Guo, L.; Yu, Y. N. Response of human REV3 gene to gastric cancer inducing carcinogen Nmethyl-N’-nitro-N-nitrosoguanidine and its role in mutagenesis. World J. Gastroenterol. 2003, 9, 888–93. (9) Gao, Z.; Yang, J.; Huang, Y.; Yu, Y. N-methyl-N’-nitro-N-nitrosoguanidine interferes with the epidermal growth factor receptor-mediated signaling pathway. Mutat. Res. 2005, 570, 175–84. (10) Wang, Z.; Wang, G.; Yang, J.; Guo, L.; Yu, Y. Activation of protein kinase A and clustering of cell surface receptors by N-methyl-N’nitro-N-nitrosoguanidine are independent of genomic DNA damage. Mutat. Res. 2003, 528, 29–36. (11) Liu, G.; Shang, Y.; Yu, Y. Induced endoplasmic reticulum (ER) stress and binding of over-expressed ER specific chaperone GRP78/BiP with dimerized epidermal growth factor receptor in mammalian cells exposed to low concentration of N-methyl-N’-nitro-N-nitrosoguanidine. Mutat. Res. 2006, 596, 12–21. (12) Wang, G.; Yu, Y.; Chen, X.; Xie, H. Low concentration N-methylN’-nitro-N-nitrosoguanidine activates DNA polymerase-beta expression via cyclic-AMP-protein kinase A-cAMP response element binding protein pathway. Mutat. Res. 2001, 478, 177–84. (13) Lu, J.; Yu, Y.; Xie, H. Activation of JNK/SAPK pathway in Vero cells induced by N-methyl-N’-nitro-N-nitrosoguanidine. Chin. J. Pathophysiol. 2000, 16, 481–85. (14) Shen, J.; Wu, M.; Yu, Y. Proteomic profiling for cellular responses to different concentrations of N-methyl-N’-nitro-N-nitrosoguanidine. J. Proteome Res. 2006, 5, 385–95. (15) Chen, W.; Shen, J.; Yin, X.; Yu, Y. Optimization of microfabricated nanoliter-scale solid-phase extraction device for detection of gelseparated proteins in low abundance by matrix-assisted laser desorption/ionization mass spectrometry. Rapid Commun. Mass Spectrom. 2007, 21, 35–43. (16) Tzivion, G.; Gupta, V. S.; Kaplun, L.; Balan, V. 14-3-3 proteins as potential oncogenes. Semin. Cancer Biol. 2006, 16, 203–13. (17) Porter, G. W.; Khuri, F. R.; Fu, H. Dynamic 14-3-3/client protein interactions integrate survival and apoptotic pathways. Semin. Cancer Biol. 2006, 16, 193–202. (18) Hermeking, H.; Benzinger, A. 14-3-3 proteins in cell cycle regulation. Semin. Cancer Biol. 2006, 16, 183–92. (19) Benzinger, A.; Muster, N.; Koch, H. B.; Yates, J. R.; Hermeking, H. Targeted proteomic analysis of 14-3-3 sigma, a p53 effector commonly silenced in cancer. Mol. Cell. Proteomics 2005, 4, 785– 95. (20) Jin, J.; Smith, F. D.; Stark, C.; Wells, C. D.; Fawcett, J. P.; Kulkarni, S.; Metalnikov, P.; O’Donnell, P.; Taylor, P.; Taylor, L.; Zougman, A.; Woodgett, J. R.; Langeberg, L. K.; Scott, J. D.; Pawson, T. Proteomic, functional, and domain-based analysis of in vivo 143-3 binding proteins involved in cytoskeletal regulation and cellular organization. Curr. Biol. 2004, 14, 1436–50. (21) Pozuelo Rubio, M.; Geraghty, K. M.; Wong, B. H.; Wood, N. T.; Campbell, D. G.; Morrice, N.; Mackintosh, C. 14-3-3-affinity purification of over 200 human phosphoproteins reveals new links to regulation of cellular metabolism, proliferation and trafficking. Biochem. J. 2004, 379, 395–408. (22) Milton, A. H.; Khaire, N.; Ingram, L.; O’Donnell, A. J.; La Thangue, N. B. 14-3-3 proteins integrate E2F activity with the DNA damage response. EMBO J. 2006, 25, 1046–57. (23) Stavridi, E. S.; Chehab, N. H.; Malikzay, A.; Halazonetis, T. D. Substitutions that compromise the ionizing radiation-induced association of p53 with 14-3-3 proteins also compromise the ability of p53 to induce cell cycle arrest. Cancer Res. 2001, 61, 7030–3. (24) Saramaki, O.; Willi, N.; Bratt, O.; Gasser, T. C.; Koivisto, P.; Nupponen, N. N.; Bubendorf, L.; Visakorpi, T. Amplification of EIF3S3 gene is associated with advanced stage in prostate cancer. Am. J. Pathol. 2001, 159, 2089–94. (25) Nupponen, N. N.; Isola, J.; Visakorpi, T. Mapping the amplification of EIF3S3 in breast and prostate cancer. Genes, Chromosomes Cancer 2000, 28, 203–10. (26) Okamoto, H.; Yasui, K.; Zhao, C.; Arii, S.; Inazawa, J. PTK2 and EIF3S3 genes may be amplification targets at 8q23-q24 and are associated with large hepatocellular carcinomas. Hepatology 2003, 38, 1242–9. (27) Savinainen, K. J.; Helenius, M. A.; Lehtonen, H. J.; Visakorpi, T. Overexpression of EIF3S3 promotes cancer cell growth. Prostate 2006, 66, 1144–50. (28) Rospert, S.; Dubaquie, Y.; Gautschi, M. Nascent-polypeptideassociated complex. Cell. Mol. Life Sci. 2002, 59, 1632–9. (29) Matsuoka, S.; Ballif, B. A.; Smogorzewska, A.; McDonald, E. R., III; Hurov, K. E.; Luo, J.; Bakalarski, C. E.; Zhao, Z.; Solimini, N.; Lerenthal, Y.; Shiloh, Y.; Elledge, S. J. ATM and ATR substrate analysis reveals extensive protein networks responsive to DNA damage. Science 2007, 316, 1160–6.
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Proteomics of Temporal Patterns Induced by MNNG Treatment (30) Sazer, S.; Dasso, M. Theran decathlon: multiple roles of Ran. J. Cell Sci. 2000, 113 (7), 1111–8. (31) Bischoff, F. R.; Krebber, H.; Smirnova, E.; Dong, W.; Ponstingl, H. Co-activation of RanGTPase and inhibition of GTP dissociation by Ran-GTP binding protein RanBP1. EMBO J. 1995, 14, 705–15. (32) Lounsbury, K. M.; Macara, I. G. Ran-binding protein 1 (RanBP1) forms a ternary complex with Ran and karyopherin beta and reduces Ran GTPase-activating protein (RanGAP) inhibition by karyopherin beta. J. Biol. Chem. 1997, 272, 551–5.
(33) Wittmann-Liebold, B.; Graack, H. R.; Pohl, T. Two-dimensional gel electrophoresis as tool for proteomics studies in combination with protein identification by mass spectrometry. Proteomics 2006, 6, 4688–703. (34) Delom, F.; Chevet, E. Phosphoprotein analysis: from proteins to proteomes. Proteome Sci 2006, 4, 15.
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