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Originally published In Press as doi:10.1074/mcp.M700483-MCP200 on March 14, 2008.
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Molecular & Cellular Proteomics 7:1174-1185, 2008.
© 2008 by The American Society for Biochemistry and Molecular Biology, Inc.

Research

Quantitative and Temporal Proteome Analysis of Butyrate-treated Colorectal Cancer Cells*,S

Hwee Tong Tan{ddagger}, Sandra Tan§, Qingsong Lin§, Teck Kwang Lim§, Choy Leong Hew§ and Maxey C. M. Chung{ddagger},§,

From the {ddagger} Department of Biochemistry, Yong Loo Lin School of Medicine and § Department of Biological Sciences, Faculty of Science, National University of Singapore, 10 Kent Ridge Crescent, Singapore 117597, Singapore


   ABSTRACT
TOP
 ABSTRACT
EXPERIMENTAL PROCEDURES
 RESULTS AND DISCUSSION
 REFERENCES
 
Colorectal cancer is one of the most common cancers in developed countries, and its incidence is negatively associated with high dietary fiber intake. Butyrate, a short-chain fatty acid fermentation by-product of fiber induces cell maturation with the promotion of growth arrest, differentiation, and/or apoptosis of cancer cells. The stimulation of cell maturation by butyrate in colonic cancer cells follows a temporal progression from the early phase of growth arrest to the activation of apoptotic cascades. Previously we performed two-dimensional DIGE to identify differentially expressed proteins induced by 24-h butyrate treatment of HCT-116 colorectal cancer cells. Herein we used quantitative proteomics approaches using iTRAQ (isobaric tags for relative and absolute quantitation), a stable isotope labeling methodology that enables multiplexing of four samples, for a temporal study of HCT-116 cells treated with butyrate. In addition, cleavable ICAT, which selectively tags cysteine-containing proteins, was also used, and the results complemented those obtained from the iTRAQ strategy. Selected protein targets were validated by real time PCR and Western blotting. A model is proposed to illustrate our findings from this temporal analysis of the butyrate-responsive proteome that uncovered several integrated cellular processes and pathways involved in growth arrest, apoptosis, and metastasis. These signature clusters of butyrate-regulated pathways are potential targets for novel chemopreventive and therapeutic drugs for treatment of colorectal cancer.

In developed countries, colorectal cancer is a prevalent disease with high mortality and morbidity rates (1). This disease has emerged as the top malignancy in Singapore. Environmental factors are responsible for about 80% of the cases, whereas genetic predisposition accounts for the minority 20% of cases. Epidemiological evidence suggests that high intake of dietary fiber reduces the incidence and risk of this neoplasm (2, 3). A wealth of studies has shown that butyrate produced from anaerobic fermentation of indigestible carbohydrate is the molecule responsible for the chemopreventive properties of a fiber-rich diet (4–6).

Although butyrate serves as an energy source for normal colonocytes, in vivo and in vitro studies have shown that at physiological concentrations this natural short-chain fatty acid mediates cell maturation with the promotion of growth arrest followed by differentiation and/or apoptosis of cancer cells (7–11). These biological effects are crucial in colorectal cancer therapy as colonic transformation is characterized by multistage alterations of tissue homeostasis resulting in aberrant cell division and/or cell death (12, 13). Butyrate has been purported as a potential anticancer agent. This initiated notable research in identifying proteins that contribute to its biological effects (14, 15). However, most of these investigations focused on one target at any one time and were thus unable to systematically elucidate the mode of actions of butyrate in an integrated manner.

Through the use of DNA microarray technology, Mariadason et al. (16) showed that butyrate induced maximal genetic reprogramming after 16 h of treatment on colorectal cancer cells. In our earlier work, a functional proteomics approach using a prefractionation strategy coupled with two-dimensional (2-D)1 DIGE analysis was undertaken to identify candidate proteins regulated by 24-h butyrate treatment in HCT-116 cells (17). We have also demonstrated the high sensitivity of the cell line to butyrate-induced growth inhibition and apoptosis in a time- and dose-dependent manner (18). Therefore, the stimulation of cell maturation by butyrate implicated a temporal orchestration of various cellular processes.

In this study, we carried out a comparative proteome analysis of HCT-116 cells treated with butyrate at three time points with the aim to identify clusters of proteins (and pathways) that showed a consistent trend of differential expression over time. The synergistic influence of each cluster of proteins may result in the overall phenotypic response to butyrate. Herein the chosen period of treatment (24, 36, and 48 h) spans from the induction of growth arrest and early phase of apoptosis until the late phase of cell death. In addition to providing insights into the mechanism underlying the pleiotropic effects of butyrate, our study of the time dynamics of butyrate treatment could lead to the discovery of potential therapeutic targets associated with the progression of cell maturation in cancer cells. As the iTRAQ methodology permits multiplexing of four samples in a single experiment, it is well suited for the evaluation of the dynamic cellular response to butyrate in a time course study (19). Here we show the first experimental iTRAQ data for butyrate-treated HCT-116 cells carried out at 24, 36, and 48 h.


   EXPERIMENTAL PROCEDURES
TOP
 ABSTRACT
 EXPERIMENTAL PROCEDURES
RESULTS AND DISCUSSION
 REFERENCES
 
Cell Culture—
HCT-116 colorectal cancer cells were cultured and treated with 5 mM sodium butyrate as reported previously except that three treatment time points (24, 36, and 48 h) were used (17).

iTRAQ Labeling—
Four batches each of control cells (24-h mock-treated) and cells treated with 5 mM sodium butyrate for 24, 36, and 48 h, respectively, were harvested. 500 mM triethylammonium bicarbonate, 1.0% (w/v) SDS was used for extraction and denaturation of cellular proteins by boiling at 100 °C for 10 min. Cellular debris were removed after centrifugation at 18,800 x g for 1 h at 23 °C. iTRAQ labeling of each sample was performed according to the manufacturer's protocol (Applied Biosystems, Foster City, CA). 100 µg of protein was reduced with 5 mM tris-(2-carboxyethyl)phosphine at 60 °C for 1 h and subsequently alkylated with 10 mM methyl methanethiosulfonate for 10 min. After cysteine blocking, each sample was diluted to 0.05% (w/v) SDS prior to trypsinization at 37 °C for 16 h. Following this, each tryptic digest was labeled for 1 h with one of the four isobaric amine-reactive tags as follows: Tag114, 24-h control; Tag115, 24-h treated; Tag116, 36-h treated; and Tag117, 48-h treated samples. These four iTRAQ-derivatized samples were then pooled and passed through a strong cation exchange cartridge as recommended by the manufacturer (Applied Biosystems). This eluate (from the ion exchange step) was desalted using a Sep-Pak cartridge (Millipore), vacuum-dried, and reconstituted for 2-D LC.

cICAT Labeling—
The control and treated cells harvested from the three time points (24, 36, and 48 h) were lysed in 50 mM Tris, 1.0% (w/v) SDS, pH 8.5, and boiled at 100 °C for 10 min. They were then subjected to centrifugation at 18,800 x g for 1 h at 23 °C to remove cell debris. cICAT labeling and processing of the samples followed standard protocols (Applied Biosystems). 100 µg of protein from the control and butyrate-treated cell lysate of each time point was each reduced with 1.25 mM tris-(2-carboxyethyl)phosphine and subsequently labeled with the respective isotopic light and heavy forms of the cICAT reagents for 2 h at 37 °C. Each pair of heavy and light cICAT-derivatized proteins from each time point was then pooled and trypsinized at 37 °C for 16 h. Upon completion of in situ digestion, the digested peptide mixture was cleaned up with a strong cation exchange cartridge and then enriched with an avidin affinity cartridge. The cICAT-labeled peptides were then dried by speed vacuuming, dissolved in cleaving reagents, and incubated at 37 °C for 2 h. After the removal of biotin, peptides were brought to dryness again before being reconstituted for 2-D LC.

2-D LC Separation of Labeled Peptides—
Each of the iTRAQ- and cICAT-labeled peptide mixtures was separated using an UltimateTM dual gradient LC system (Dionex-LC Packings) equipped with a ProbotTM MALDI spotting device. A 2-D LC separation was performed as follows. The labeled peptide mixture was dissolved in 2% ACN with 0.05% TFA and injected into a 0.3 x 150-mm strong cation exchange column (FUS-15-CP, POROS 10S) (Dionex-LC Packings) for the first dimensional separation. Mobile phase A was 5 mM KH2PO4 buffer, pH 3, 5% ACN, and mobile phase B was 5 mM KH2PO4 buffer, pH 3, 5% ACN, 500 mM KCl, respectively. The flow rate was 6 µl/min. Nine fractions were obtained using step gradients of mobile phase B: unbound, 0–5, 5–10, 10–15, 15–20, 20–30, 30–40, 40–50, and 50–100%. The eluting fractions were captured alternatively onto two 0.3 x 1-mm trap columns (3-µm C18 PepMapTM, 100 Å) (Dionex-LC Packings) and washed with 0.05% TFA followed by gradient elution in a 0.2 x 50-mm reverse phase column (monolithic polystyrene-divinylbenzene) (Dionex-LC Packings). The mobile phases used for this second dimensional separation were 2% ACN with 0.05% TFA (A) and 80% ACN with 0.04% TFA (B). The gradient elution step was 0–60% B in 15 min at a flow rate of 2.7 µl/min. The LC fractions were mixed directly with MALDI matrix solution (7 mg/ml {alpha}-cyano-4-hydroxycinnamic acid and 130 µg/ml ammonium citrate in 75% ACN) at a flow rate of 5.4 µl/min via a 25-nl mixing tee (Upchurch Scientific) before they were spotted onto a 192-well stainless steel MALDI target plate (Applied Biosystems) using a Probot Micro Precision Fraction Collector (Dionex-LC Packings) at a speed of 5 s/well. 50 fmol of ACTH(18–39) peptide (m/z = 2465.199) was spiked into each well as internal standard.

Mass Spectrometry Analysis—
The samples on the MALDI target plates were analyzed using a 4700 Proteomics Analyzer mass spectrometer (Applied Biosystems). MS/MS analyses were performed using nitrogen at a collision energy of 1 kV and a collision gas pressure of 1 x 10–6 torr. The GPS ExplorerTM software version 3.6 (Applied Biosystems) was used to create and search files with the MASCOT search engine (version 2.1; Matrix Science) for peptide and protein identifications in both the cICAT- and iTRAQ-labeled samples. The International Protein Index (IPI) human database (version 3.30, 67,922 sequences) (20) was used for the search, and this was restricted to tryptic peptides.

iTRAQ-labeled Samples—
One thousand shots were accumulated for each MS spectrum. For MS/MS, 6,000 shots were combined for each precursor ion with signal to noise (S/N) ratio greater or equal to 100. For precursors with S/N ratio between 50 and 100, 10,000 shots were acquired. The resolution used to select the parent ion was 200. No smoothing was applied before peak detection for both MS and MS/MS, and the peaks were deisotoped. For MS/MS, only the peaks from 60 to 20 Da below each precursor mass and with S/N ≥ 10 were selected. Peak density was limited to 30 peaks per 200 Da, and the maximum number of peaks was set to 125. Cysteine methanethiolation, N-terminal iTRAQ labeling, and iTRAQ-labeled lysine were selected as fixed modifications; methionine oxidation was considered as a variable modification. One missed cleavage was allowed. Precursor error tolerance was set to 100 ppm; MS/MS fragment error tolerance was set to 0.4 Da. Maximum peptide rank was set to 2. iTRAQ quantification was performed using the GPS Explorer software and normalized among samples. iTRAQ ratios were calculated based on the cluster areas of the iTRAQ reporter fragment peaks (114, 115, 116, and 117), and the calculation of ratios included only peptides identified with C.I. percent above cutoff thresholds as described below.

The average iTRAQ ratio and S.D. were determined using the GPS Explorer software using the following equations.

Formula 1(Eq. 1)

where R is the average iTRAQ ratio, Xi is the natural log of the iTRAQ ratio of each iTRAQ pair, and N is the number of peptides with non-zero iTRAQ ratio.

Formula 2(Eq. 2

where S.D. is the standard deviation of iTRAQ ratio, and

Formula 3(Eq. 3)

where log S = sd and R is the average iTRAQ ratio.

Formula 4(Eq. 4)

where sd is the iTRAQ standard deviation and Xi is the natural log of the iTRAQ ratio of each peptide.

In this work, four biological replicates of iTRAQ-labeled samples were analyzed. Student's t test was performed, and the p values based on the iTRAQ ratios of peptides matched to each protein (48-h time point versus control) were used to assess the significance of temporal differential expression. Proteins that have p values <0.05 in at least one data set and showed consistent changes in all data sets were considered as significantly altered in the expression level.

To determine the cutoff threshold of -fold changes for proteins with a single peptide match, two equal amounts of trypsin-digested six-protein mixtures (Applied Biosystems) were labeled with iTRAQ reagents 114 and 117, respectively, and analyzed with 1-D LC MALDI-TOF/TOF MS (reverse phase liquid chromatography; similar to that mentioned above). The S.D. based on the ratios of all the identified peptides was 0.15; thus 1.3 (1 + 2 S.D.) was determined to be the significant cutoff threshold (p < 0.05) for the up-regulated proteins, and reciprocally 0.77 was the cutoff threshold for the down-regulated proteins (data are shown in the supplemental data). Similar cutoff thresholds have been used in other iTRAQ studies (21, 22).

cICAT-labeled Samples—
For MS analysis, typically 1,000 shots were accumulated for each sample well. MS/MS acquisition was performed in a result-dependent manner. Only cICAT pairs with a normalized ratio (normalized against the median ratio of all the cICAT pairs detected) greater than 40% were selected for fragmentation. Singletons were also selected as precursor ions. Stop conditions were implemented so that 3,000–6,000 shots were accumulated depending on the quality of the spectra. The resolution used for parent ion selection was 200. Peak processing and detection procedures were the same as those mentioned above. Heavy and light cICAT-labeled cysteine, N-terminal acetylation and pyroglutamation (Glu and Gln), and methionine oxidation were selected as variable modifications. One missed cleavage was allowed. Precursor error tolerance was set to 100 ppm, and MS/MS fragment error tolerance was set to 0.3 Da. Maximum peptide rank was set to 5. cICAT quantification was performed using GPS Explorer software and normalized against the median ratio obtained from all the cICAT peptide pairs detected in one sample. The ratios were calculated by comparison of the cluster area of the heavy ICAT-labeled peptide with that of the light ICAT-labeled peptide. Two equal amounts of trypsin-digested BSA were labeled with heavy and light cICAT tags and subjected to 1-D LC MALDI-TOF/TOF MS. The S.D. based on the ratios of all the identified cICAT-labeled peptides was 0.12; thus 1.36 (1 + 3 S.D.) was determined as the significant cutoff threshold (p < 0.01) for the significantly up-regulated proteins, and reciprocally 0.74 was the cutoff threshold for the down-regulated proteins.

Estimation of False Positive Rate to Determine Cutoff Score—
In addition to the IPI human database, a randomized database (67,922 sequences) generated using IPI human database version 3.30 (generated using a Pearl script downloaded from Matrix Science) was also used to search both the iTRAQ- and cICAT-labeled samples. The false positive rate was calculated by comparing the peptide hits obtained from these two databases at different ion score C.I. percent (peptide). The minimum ion score C.I. percent was set such that no more than a 5% false positive rate is achieved. Based on this cutoff threshold, all the proteins identified from the random database search were single peptide-matched. Hence proteins identified from the human database that are matched to at least two peptides are statistically confident. For single peptide-matched proteins, only those with ion score C.I. percent greater than the highest C.I. percent attained from the random database search were selected. With these cutoff thresholds, we essentially achieved a 0% false positive identification rate at the protein level. In addition, those single peptide-matched proteins must be identified based on a peptide that has been detected several times in one run or in replicate runs. The minimum ion score thresholds that were used for each iTRAQ- and cICAT-labeled sample are shown in the supplemental data.

Real Time PCR—
RNA was isolated from two batches of harvested HCT-116 cells using the RNeasy Plus minikit (Qiagen, Chatsworth, CA) according to the manufacturer's instructions. Purified RNA was quantified by UV spectrophotometry (A260 of 1 = 40 µg/ml) and assessed using denaturing agarose gel electrophoresis. MultiScribeTM reverse transcriptase (Applied Biosystems) was used to reverse transcribe RNA from each sample to cDNA following the manufacturer's protocol. Primers specific for each gene target were designed using Primer Express software (Applied Biosystems) and synthesized by 1st Base Pte. Ltd. (Singapore). Basic Local Alignment Search Tool (BLAST) searches for all primer sequences were performed to confirm gene specificity. For quantification of each gene in the samples, amplification was performed in triplicates with SYBR Green PCR Master Mix (Applied Biosystems) on the ABI PRISM 7000 Sequence Detection System instrument according to the manufacturer's instructions. Non-template controls were included for each run. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used as the endogenous control reference for normalization. Thermal cycling parameters were as follows: denaturation at 95 °C for 10 min followed by 40 cycles at 95 °C for 15 s and 60 °C for 1 min.

Two-dimensional Gel Electrophoresis (2-DE)—
2-DE was performed as described previously (17). Briefly harvested cells were lysed in the extraction buffer and clarified with centrifugation. 10 µg of each sample was then loaded onto rehydrated 7-cm pH 3–10 non-linear IPG strips and separated on the IPGphor unit (GE Healthcare) using the following parameters: (i) 100 V, 50 V-h; (ii) 200 V, 100 V-h; (iii) 500 V, 250 V-h; (iv) 1,000 V, 500 V-h; (v) 1,000–8,000 V, 2,250 V-h, and (vi) 8,000 V, 12,000 V-h. A two-step equilibration procedure using DTT and iodoacetamide was used to reduce and alkylate the separated proteins in the IPG strips, respectively, before the second dimensional SDS-PAGE step.

Western Blot—
Equal aliquots of proteins extracted from both control and treated cells of each time point were resolved by 1-D SDS-PAGE. Upon completion of electrophoresis, the proteins were electroblotted onto nitrocellulose membranes (Bio-Rad). The blots were then blocked using 5% (w/v) nonfat dry milk in TBS with 0.1% Tween 20 (TBS-T) overnight prior to immunoprobing with antibodies diluted in TBS-T with 1% (w/v) milk for 1 h each. The membranes were incubated with rabbit anti-GAPDH (1:200) from Santa Cruz Biotechnology, Inc., mouse anti-heat shock protein (HSP) 90-β (1:1,000) from Stressgen, mouse anti-galectin-1 (1:500), mouse anti-AKAP12 (1:500), mouse anti-SEC22b (1:750), or mouse anti-cytochrome c oxidase VIb (1:750) from Abnova. HRP-conjugated anti-rabbit IgG (1:2,500) from Santa Cruz Biotechnology, Inc., HRP-conjugated anti-mouse IgG (1:5,000) from GE Healthcare, or HRP-conjugated anti-mouse IgM (1:5,000) from Pierce were used as secondary antibodies. Three washes in TBS-T were carried out between each antibody incubation. Subsequent visualization was performed using ECL (GE Healthcare) with GAPDH levels as the loading control.


   RESULTS AND DISCUSSION
TOP
 ABSTRACT
 EXPERIMENTAL PROCEDURES
 RESULTS AND DISCUSSION
REFERENCES
 
Protein Identification from iTRAQ- and ICAT-labeled Peptides
783 unique proteins were identified from a total of 3,116 tryptic peptides for the iTRAQ-labeled samples. On the other hand, 137 unique proteins were identified from a total of 241 peptides obtained from cICAT (see supplemental data for the lists of iTRAQ- and ICAT-labeled proteins that showed temporal differential expression after butyrate treatment). Because of the difference in labeling chemistry, the result obtained from the cICAT approach complements the iTRAQ data. Recently quantitative proteomics incorporating stable isotope tagging such as postisolation labeling using ICAT or iTRAQ was demonstrated to be a strategy complementary to 2-DE (23, 24). Most notably, a comparative study of these three proteomics methods found limited overlapping proteins between them, and iTRAQ was considered to be the more sensitive technology as compared with ICAT and 2-D DIGE (25). This underscored the importance of using various technology platforms for a more comprehensive proteomics study of complex samples.

Interestingly a subset of proteins found in this study had also been identified in our previous work using 2-D DIGE (17), and they showed regulation in a similar manner by butyrate treatment. Such proteins include cytoskeletal 8, ornithine aminotransferase, cytochrome c oxidase polypeptide VIb, and Tu elongation factor.

Temporal Analysis of Proteins following Butyrate Treatment
From the list of differentially expressed proteins obtained from this temporal study, proteins that exhibited progressive up- or down-regulation were clustered into groups on the bases of their biological functions. They could be grouped into four cellular processes, viz. Cluster A, growth arrest; Cluster B, apoptosis; Cluster C, metabolism; and Cluster D, metastasis (Fig. 1; also see the supplemental data for the complete list of differentially expressed proteins). Subsequently some of these protein candidates were validated using quantitative real time PCR and/or Western blotting. These results are shown in Figs. 2 and 3, and they are in accord with the proteomics results.


Figure 1
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  		FIG. 1. Identification of protein clusters based on biological functions that showed similar trends of differential expression over time. These proteins exhibit progressive up- or down-regulation on a temporal basis and were clustered into groups of certain cellular processes modulated by butyrate: Cluster A, cell cycle progression; Cluster B, apoptosis (Cluster B1, tumor suppressors; Cluster B2, oxidative phosphorylation; Cluster B3, HSPs and chaperones; Cluster B4, ubiquitination-proteasome pathway); Cluster C, metabolism; and Cluster D, metastasis.

 

Figure 2
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  		FIG. 2. Validation of the iTRAQ results on selected proteins using real time PCR. The results verified differential regulation of these proteins upon butyrate treatment. -Fold change ratio assessed by real time PCR was expressed as mean values ± S.E. of two batches of cells performed in triplicates.

 

Figure 3
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  		FIG. 3. Western blots of proteins identified to have differential expression from iTRAQ data. a, Western blot confirmed differential expression of these proteins. GAPDH was used as the loading control. For AKAP12, decreased expression of full-length protein (~200 kDa) was detected, but an increased presence of a protein fragment (~40 kDa) was seen over time. b, 2-DE (pH 3–10) Western blot for AKAP12 was performed to confirm the increased expression of the fragment protein at ~40 kDa (circled in b). COX, cytochrome c oxidase.

 
An overview of the temporal anticancer effects of butyrate treatment on the various cellular processes is shown in Fig. 4. These data were obtained from the iTRAQ ratios of the proteins grouped under each cellular process at each time point. As seen here and discussed further below, our temporal analysis showed that butyrate induced a blockage of cell cycle progression as an early event (24 h), whereas the antimetastasis effect was most apparent at the later stage (48 h) of treatment.


Figure 4
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  		FIG. 4. An overview of the temporal effects of butyrate treatment on the various cellular processes. The differential regulation of the proteins from each cellular process was summarized to illustrate the overall temporal effects of butyrate treatment on HCT-116 cells.

 
Temporal Regulation of the Cellular Processes and Pathways Induced by Butyrate
This study has clearly identified clusters of proteins in pathways that correlate protein expression changes with the induction of anticancer effects. The synergistic influence of each cluster of proteins results in the overall phenotypic response to butyrate. On the bases of these observations, we propose a model to illustrate the integrated cellular mechanism initiated by butyrate in colorectal cancer cells (Fig. 5).


Figure 5
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  		FIG. 5. A model depicting pathways initiated by butyrate in mediating growth arrest and apoptosis in HCT-116 cells is proposed. A, reduced expression of cell cycle regulatory proteins and nucleotides biosynthesis proteins led to growth arrest induced by butyrate. B, butyrate increased the expression of tumor suppressors and proteins associated with MTP for the translocation of cytochrome c and modulated the expression of chaperones and proteasome pathways, resulting in the activation of apoptosis cascades. C, the metabolic machinery of the cells was altered with an increased expression of several metabolic enzymes. D, expression of cytoskeleton-associated proteins was increased to strengthen the cytoskeletal scaffold and lower the metastasis potential of HCT-116 cells. ER, endoplasmic reticulum; hnRNPs, heterogeneous nuclear ribonucleoproteins; ETC, electron transport chain; ECM, extracellular matrix; meta, metabolism.

 
Cluster A: Growth Arrest
Cell Cycle Progression—
Butyrate regulates several cell cycle genes including c-myc, p16, and p21 (14). Among the list of down-regulated proteins identified here, several function in nucleotide biosynthesis, cell cycle progression, and cellular proliferation (Fig. 1). These proteins include DNA replication licensing factor MCM7, Ran-specific GTPase-activating protein, caprin 1, and nucleosome assembly protein 1-like 1 (the latter two proteins were verified by real time PCR). The down-regulation of these cell cycle regulatory proteins is in concordance with the inhibition of DNA replication, hindrance of cell division, and hence blockage of cell cycle progression by butyrate as represented in Cluster A of our proposed model (Fig. 5). Our temporal analysis showed that butyrate induced an early reduction in the expression of these proteins, which plateaued after the 36-h time point (Fig. 4).

Signaling—
Protein kinase A-anchoring protein 12, a scaffold protein for kinases (26) that possesses tumor suppressor activity, was found to be dramatically down-regulated in both iTRAQ and cICAT data (also verified by real time PCR; Fig. 2). Multiple intracellular kinases in the oncogenic or survival signaling pathways have been illustrated to be key players in butyrate actions (27, 28). Western blotting using monoclonal antibody against the C terminus of AKAP12 showed decreased expression of the full-length protein and an appearance of a truncated isoform at a molecular mass of ~40 kDa over time (Fig. 3). Peptides from the MS/MS spectra of AKAP12 matched to only sequences from the N-terminal part of the protein, supporting the decreased presence of native AKAP12, which was verified in the Western blot band at ~200 kDa. The 2-DE Western blot clearly verified the increased abundance of the fragmented protein of ~40 kDa (Fig. 3). These preliminary data may indicate that targeting of kinases by AKAP12 may be regulated by butyrate, thus affecting downstream growth-associated signaling cascades. On the other hand, the N-terminal fragment of AKAP12 may contribute to the tumor suppressor property of this protein. These await further investigations.

Cluster B: Apoptosis
As demonstrated in Fig. 5, the proteins in Cluster B function as tumor suppressors, heat shock proteins, or chaperones, players in the oxidative phosphorylation pathway or ubiquitination-proteasome pathway. The temporal changes in expression of these proteins contribute to the initiation of apoptosis by butyrate in HCT-116 cells.

Tumor Suppressors—
As shown in Fig. 1, tumor suppressors, such as galectin-1, metallothionein-1X, prohibitin-2, and Ras-related protein Rap-1A, displayed a temporal increase in expression level upon butyrate treatment in this study. These proteins contribute to tumor growth suppression by butyrate. For example, galectins are multifunctional β-galactoside lectins with roles including cell adhesion, growth regulation, invasion, and apoptosis (29). The identification of up-regulated galectin-1 here (validated with Western blot in Fig. 3) corroborated with previous work that showed its association with the actions of butyrate (30, 31). We also found that metallothionein-1X was markedly up-regulated by butyrate, and this was confirmed by real time PCR (Fig. 2). The regulation of metallothioneins is not uniform in all tumors. For instance, this protein was overexpressed in bladder cancer but down-regulated in advanced prostate cancer (32, 33). Although other metallothioneins have been found to be up-regulated by butyrate in a paradigm of increased resistance to toxic metals in tetracarcinoma and hepatoma cells (34, 35), this is the first report on the regulation of metallothioneins by butyrate in colorectal cancer cells. Metallothioneins have a high metal binding affinity for metal homeostasis and detoxification. Exposure to metals such as chromium, nickel, iron, copper, and manganese has been shown to promote carcinogenesis. Thus, the increased expression of metallothionein by butyrate may be related to the regulation of metals associated with colorectal carcinogenesis.

Similarly our results also showed that voltage-dependent anion-selective channel protein 1 (VDAC1) and ADP/ATP translocase 2 (ANT2) were found to be concurrently up-regulated by butyrate. Their expression levels were shown to increase particularly after the 36-h time point (Figs. 1 and 4). These proteins are candidate regulators of cytochrome c release via the mitochondrial transition pore (MTP) for activation of apoptotic cascades. Mitochondria play a pivotal role in apoptosis (36, 37), and the release of proapoptotic proteins like cytochrome c, apoptosis-inducing factor, and Smac/Diablo from mitochondria is crucial in mediating apoptosis by chemotherapeutic agents. The extrinsic apoptotic pathway mediated by cytochrome c release was activated by butyrate treatment (38). VDAC1 has an increased expression level as seen from the cICAT results. It plays an essential role in the translocation of apocytochrome c for the activation of downstream caspases. Overexpression of this mitochondrial protein has been found to induce cell death (39). ANT2 catalyzes the exchange of ADP/ATP across the mitochondrial membrane and has been implicated in apoptosis mediated through the mitochondrial transition pore as well (40). The increased expression of these regulators of MTP may contribute to the activation of cytochrome c-mediated apoptotic cascades by butyrate. The measurement of these tumor suppressors in cancer cells could thus serve as monitors of the efficacy of proapoptotic drug treatment.

Oxidative Phosphorylation—
Our results clearly reflected a trend of increased expression of the electron transport chain complexes (Fig. 1). The rise in expression levels of these proteins was further increased after 36 h of butyrate treatment. Among the proteins, differential expression of cytochrome c oxidases Va and VIb were verified with real time PCR (Fig. 2). Cytochrome c oxidase VIb was also reported to be up-regulated by butyrate in our previous work (17), and Western blotting confirmed the result here (Fig. 3). The increased expression of proteins in the oxidative phosphorylation pathway may be related to the enhanced mitochondrial activity by butyrate and subsequent growth arrest and apoptosis in the colonic epithelial cells (41). Our study has also shown up-regulation of the ATP synthase subunit of Complex V upon butyrate treatment. ATP synthase was down-regulated in colorectal carcinoma as an avoidance mechanism toward reactive oxygen species (ROS)-mediated cell death (42). The study by Giardina et al. (43) has shown a role for butyrate influence on ROS generation in colon carcinogenesis. The changes in the expression levels of electron transport chain complexes, such as Complexes I, II, IV, and V, as seen here may result in unstable mitochondrial membrane potential and an increase in ROS production. Hence in addition to possible generation of ATP from the enhanced oxidative phosphorylation for the energy-dependent apoptosis, cytotoxic mitochondrial ROS production could sensitize butyrate-treated cells to oxidative stress-mediated cell death (schematized in Fig. 5, Cluster B).

HSPs and Chaperones—
A temporal decrease in the expression of chaperones, such as heat shock 27-kDa protein, HSP90, heat shock cognate 71-kDa protein, and thioredoxin, was detected in butyrate-treated HCT-116 cells (Fig. 1). The degree of down-regulation was shown to be reduced after the 36-h time point. HSPs act as molecular chaperones, thus playing an indispensable role in defense against cellular stress such as chemotherapy-induced apoptosis (44). HSP90, one of the down-regulated chaperones identified here (confirmed with real time PCR and Western blot), was advocated as a novel anticancer target (45), and its inhibitor 17-allylaminogeldanamycin is currently in an anticancer clinical trial. HSP90 is responsible for maintaining the stability of many oncogenic proteins with biological functions in cellular proliferation and apoptosis. HSP90 is known to be dysfunctional in tumors (46, 47) and was detected to be up-regulated in transformed cells. Inhibitors of this antiapoptotic protein triggered cancer cell death synergistically with butyrate treatment (48). The reduced expression of chaperones as shown here will deter proper protein folding leading to protein aggregation, ultimately resulting in cell death in cancer cells.

Ubiquitination-Proteasome Pathway—
Proteasome activator subunit 2, ubiquitin-activating enzyme E1, and F-box-only protein 2 are some of the proteins in the ubiquitination-proteasome pathway that were also noted to be differentially regulated by butyrate as shown in our results (Fig. 1). Degradation of proteins via the ATP/ubiquitin-dependent pathway mediates apoptosis (49). Targets of the 26 S proteasome include proteins in heat shock response and cell cycle control (50, 51); both systems were found to be down-regulated in this study (Figs. 1 and 4). The butyrate-induced apoptotic cascades are associated with the ubiquitin-degradation system, and inhibitors of the proteasome act synergistically with butyrate in anticarcinogenic therapy. In support of this, Pei et al. (52) found that the simultaneous application of a proteasome inhibitor and butyrate could induce apoptosis. Both Yu et al. (53) and Giuliano et al. (54) showed similar synergistic effects between proteasome activity and butyrate. Hence the butyrate-regulated ubiquitination-proteasome pathway would affect the levels of survival- and apoptosis-related proteins in cancer cells.

Cluster C: Metabolism
Our data identified a repertoire of biosynthetic enzymes, including those involved in the Krebs cycle and pentose phosphate pathway, to be up-regulated by butyrate in a time-dependent manner (Fig. 1). The change in the expression levels for most of these proteins was shown to be more pronounced after 36 h of treatment. Examples of these metabolic enzymes were malate dehydrogenase, oxoglutarate ({alpha}-ketoglutarate) dehydrogenase, transaldolase, and transketolase. This suggested that butyrate altered the metabolic machinery of HCT-116 cells. Most tumors including colorectal cancer depend on the enhanced glycolysis instead of oxidative phosphorylation for ATP production even in the presence of oxygen; this phenomenon is known as the "Warburg effect" (55). The metabolic enzymes found to be up-regulated by butyrate in this study are involved in various glucose metabolic pathways that thus promote glucose metabolism. However, unlike other metabolic enzymes, {alpha}-enolase was shown to be down-regulated by butyrate. This may retard the rate of glycolysis because enolase catalyzes the formation of phosphoenolpyruvate, a precursor of the glycolytic end product pyruvate. Furthermore several enzymes functioning in the oxidative phosphorylation pathway were up-regulated by butyrate (as discussed earlier).

Butyrate demonstrates phenotypical specificity whereby it causes growth arrest followed by differentiation and/or apoptosis in carcinoma cells but promotes proliferation in normal cells (56). Colonic carcinoma cells derive energy via metabolism of glucose, whereas normal colonic epithelial cells oxidize butyrate as the key fuel source for cellular proliferation (57–59). Butyrate has been reported to induce apoptosis in the presence of glucose and pyruvate but promote growth in the absence of these alternative energy sources (60). Herein butyrate altered the metabolic profile of cancer cells, resulting from an enhanced expression of several metabolic enzymes. Metabolism of other energy sources as fuel thus avails butyrate to effect its anticancer actions in HCT-116 cells.

In addition, proteins functioning in amino acids and lipid/cholesterol metabolic pathways, such as ornithine aminotransferase, asparagine synthetase, argininosuccinate synthase, {delta}1-pyrroline-5-carboxylate synthetase, and enoyl-CoA hydratase, were up-regulated in this study. Leschelle et al. (61) and Tabuchi et al. (62) have demonstrated stimulated lipogenesis by butyrate. Ruemmele et al. (63) and Della Ragione et al. (64) found that inhibiting protein synthesis by cycloheximide blocked butyrate-induced apoptosis. In this work, vesicular transport proteins (which function in protein synthesis), such as vesicle trafficking protein SEC22b (verified by real time PCR and Western blot), clathrin heavy chain 1, and N-ethylmaleimide-sensitive factor attachment protein-β protein, were identified to be up-regulated. These pathways were grouped under Cluster C in the proposed model (Fig. 5).

Cluster D: Metastasis and Cytoskeleton-associated Proteins
In correlation to previous reports on cytoskeletal organization of cancer cells (65, 66), the data here showed increased expression of various cytoskeleton-related proteins by butyrate (Fig. 1). The overall increase in the expression level of these proteins was higher after the 36-h time point. The concerted temporal up-regulation of these proteins such as cytoskeletal 18, cytoskeletal 19, epiplakin, and filamins may lead to a strengthened cytoskeletal scaffold and reduced metastasis potential of carcinoma cells (Cluster D in Fig. 5). Several of these identified proteins function as cross-linkers in the intermediate filament network, modulating cell adhesion, motility, and invasiveness. Real time PCR was conducted for cytoskeletal 19 (Fig. 2). LIM domain and actin-binding protein, also known as the elevated expression of epithelial protein lost in neoplasm (EPLIN), identified by cICAT, diminishes the invasiveness of cancer cells. EPLIN is a cytoskeleton-associated protein whose down-regulation in cancer cells may facilitate motility of these cancer cells (67). Our results showed that the antimetastasis effect was induced as a later event after growth inhibition and apoptosis (Figs. 1 and 4). The antimetastasis effect shown here corresponds to the in vivo study done by Velazquez et al. (68) that demonstrated inhibition of seeding and growth of colorectal metastases to the liver by intravenous infusion of butyrate in mice. Butyrate is currently being evaluated in clinical trials and has shown optimistic results (69).

Conclusion
A global quantitative proteomics approach was utilized in this analysis of the temporal effects of butyrate in HCT-116 cells. Differentially expressed proteins identified from this study were grouped according to their biochemical functions, and a model depicting the integrated cellular processes initiated by butyrate was proposed (Fig. 5). The temporal and synergistic effects of each pathway would lead to the antiproliferative and proapoptotic properties of butyrate.

As shown in Fig. 4, our study demonstrated that butyrate reduced expression of cell cycle regulatory proteins and nucleotide biosynthesis proteins that led to growth arrest at the early stage and tapered off after the 36-h time point. The regulation of HSPs and the ubiquitination-proteasome pathway by butyrate was less significant. On the other hand, the expression levels of proteins that function in oxidative phosphorylation, in metabolism, or as tumor suppressors increase on a temporal basis with a similar trend. Moreover there is a greater increase in their expression levels after the 36-h time point. The synergistic up-regulation of these proteins induces apoptosis in HCT-116 cells. The antimetastasis effect of butyrate was most significant and strongly accentuated at the late phase of treatment.

These signature clusters of butyrate-regulated pathways could serve as potential therapeutic targets or proteomics markers to assess the efficacy or toxicity of drug candidates. Our data clearly showed that in addition to targeting proteins involved in cell cycle blockage, apoptotic, and antimetastatic pathways, butyrate also alters the metabolic profile of the cancer cells to induce its anticancer effects. A better understanding of the mechanism whereby butyrate mediates its therapeutic actions would certainly aid in the design of better therapeutic intervention. Thus, a multidrug regimen(s) that has synergistic effects on these clusters of pathways may be a promising pharmacological strategy for chemoprevention of colorectal cancer.


  FOOTNOTES
 
Received, October 5, 2007, and in revised form, March 3, 2008.

Published, MCP Papers in Press, March 14, 2008, DOI 10.1074/mcp.M700483-MCP200

1 The abbreviations used are: 2-D, two-dimensional; iTRAQ, isobaric tags for relative and absolute quantitation; cICAT, cleavable ICAT; ACTH, adrenocorticotropic hormone; S/N, signal to noise; C.I., confidence interval; 1-D, one-dimensional; IPI, International Protein Index; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; 2-DE, two-dimensional gel electrophoresis; HRP, horseradish peroxidase; MTP, mitochondrial transition pore; ROS, reactive oxygen species; EPLIN, epithelial protein lost in neoplasm; VDAC1, voltage-dependent anion-selective channel protein 1; ANT2, ADP/ATP translocase 2. Back

* This work was supported by Singapore Cancer Syndicate Grant MU003, a National University of Singapore research scholarship (to H. T. T.), and a Singapore Millennium Foundation postdoctoral fellowship (to S. T.). The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. Back

S The on-line version of this article (available at http://www.mcponline.org) contains supplemental material. Back

To whom correspondence should be addressed: Dept. of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 10 Kent Ridge Crescent, Singapore 117597, Singapore. Tel.: 65-65163252; Fax: 65-67791453; E-mail: bchcm{at}nus.edu.sg


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