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Article

iTRAQ-Based Quantitative Proteomics Reveals the Energy Metabolism Alterations Induced by Chlorogenic Acid in HepG2 Cells

Health Nutrition, Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan
*
Author to whom correspondence should be addressed.
Nutrients 2022, 14(8), 1676; https://doi.org/10.3390/nu14081676
Submission received: 25 February 2022 / Revised: 7 April 2022 / Accepted: 16 April 2022 / Published: 18 April 2022
(This article belongs to the Collection Coffee and Caffeine Consumption for Health and Performance)

Abstract

:
Epidemiological studies have suggested that coffee consumption is associated with a decrease in the risk of developing obesity and diabetes; however, the detailed mechanisms underlying these effects of coffee consumption remain poorly understood. In this study, we examined the effects of chlorogenic acid on energy metabolism in vitro. Hepatocellular carcinoma G2 (HepG2) cells were cultured in a medium containing chlorogenic acid. Chlorogenic acid increased the activity of mitochondrial enzymes, including citrate synthase, isocitrate dehydrogenase, and malate dehydrogenase (MDH), which are involved in the tricarboxylic acid (TCA) cycle. Proteome analysis using the isobaric tags for the relative and absolute quantitation (iTRAQ) method revealed the upregulation of proteins involved in the glycolytic system, electron transport system, and ATP synthesis in mitochondria. Therefore, we propose a notable mechanism whereby chlorogenic acid enhances energy metabolism, including the TCA cycle, glycolytic system, electron transport, and ATP synthesis. This mechanism provides important insights into understanding the beneficial effects of coffee consumption.

1. Introduction

Coffee has been consumed by humans for thousands of years and is currently one of the most popular beverages worldwide. Accumulating epidemiological evidence suggests that coffee, as a functional food, plays a role in the prevention of diseases. Therefore, understanding the effects of coffee intake on health is desirable. Lines of evidence, including those from epidemiological studies, have suggested that the intake of coffee may reduce the risk of developing obesity and diabetes [1,2]. A meta-analysis of prospective cohort research [3] revealed that the intake of coffee ingredients helped decrease the risk of type 2 diabetes. However, the detailed mechanisms underlying the beneficial effects of coffee consumption are still poorly understood.
Many studies on the effects of coffee have focused on liver tissue, including a meta-analysis of four cohort studies by Larsson and Wolk [4], which revealed that consuming two cups of coffee per day decreased the risk of hepatic cancer by 43%. The effects of coffee ingredients on hepatic cells have been examined in several studies, some of which used human hepatocellular carcinoma G2 (HepG2) cells to explore the physiological action of coffee ingredients. HepG2 cells are considered a feasible model for in vitro analysis of xenobiotic metabolism and hepatotoxicity since they perform the majority of the physiological functions like normal human hepatocytes [5,6]. For example, Riedel et al. [7] studied the effects of trigonelline on hepatic glucose metabolism, while Vaynshteyn and Jeong [8] and Kalthoff et al. [9] reported the effects of caffeine on the expression of cytochrome P450 1A2 (CYP1A2) and glucuronosyltransferase in HepG2 cells, respectively. Since coffee ingredients and/or their metabolites remain in the blood after the coffee is consumed, the findings of these in vitro studies using coffee ingredients could shed some light on the bioactivity of coffee. As a model of metabolically active cells, HepG2 was also used in this experiment.
Our previous in vivo studies, conducted with multi-omics analyses (transcriptomics, proteomics, and metabolomics), suggested that coffee intake activates the urea cycle and the tricarboxylic acid (TCA) cycle in the livers of C57BL/6J mice fed a high-fat diet [10,11]. To the best of our knowledge, there have been no studies on the effects of coffee ingredients and hepatic energy metabolism in cultured hepatic cells. In the present study, we explored the effects of coffee and chlorogenic acid (CGA) on energy metabolism in an in vitro experiment using HepG2 cells.

2. Materials and Methods

2.1. Cell Culture

Human hepatocyte HepG2 cells (American Type Culture Collection, Rockville, MD, USA) were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM)-D5796 (Sigma-Aldrich, Tokyo, Japan) containing 10% fetal bovine serum (FBS) (Nichirei Bioscience, Tokyo, Japan) and 1% 100 U/mL penicillin/streptomycin (Sigma-Aldrich, Tokyo, Japan). Each assay described below was performed by culturing approximately 2.5 × 105 cells/well seeded in 24-well plates for 48 h. HepG2 cells were cultured at 37 °C with 5% CO2.

2.2. Coffee Ingredients

Caffeinated coffee powder (Goldblend, Nestle Japan, Hyogo, Japan), decaffeinated coffee powder (Goldblend, Nestle, Hyogo, Japan), and CGA (Sigma-Aldrich, Tokyo, Japan) were used for the experiments. HepG2 cells were cultured in DMEM containing these ingredients (50, 100, and 200 μg/mL).

2.3. MTT (3-[4,5-Dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide) Assay

HepG2 cells were cultured in DMEM containing coffee ingredients for 24 h, and after being washed with phosphate-buffered saline (PBS), they were incubated at 37 °C for 3 h in DMEM containing 0.5 mg/mL of MTT solution M5655 (thiazolyl blue tetrazolium bromide, Sigma-Aldrich, Tokyo, Japan). The MTT solution was removed and 0.04 N HCl/isopropanol was added, and 5 min later, the absorbance of the supernatant was measured (OD at 540 nm).

2.4. Enzyme Activity Measurement

Spectrophotometric analysis of the enzymes was performed as described [12,13]. Briefly, citrate synthase (CS): The cell solution was mixed with 100 mM Tris-HCl (pH 8.0), 10 mM DTNB (5,5′-dithio-bis-(2-nitrobenzoic acid)), and 2.5 mM acetyl-CoA, and the absorbance was measured using Biolis 24i (Tokyo-Boeki, Tokyo, Japan) (37 °C and 412 nm) after the addition of 50 mM oxaloacetic acid. Isocitrate dehydrogenase (IDH): The cell solution was mixed with 250 mM glycylglycine buffer (pH 7.4), 18 mM manganese chloride, and 20 mM nicotinamide adenine dinucleotide phosphate (NADP), and the absorbance was measured using Biolis 24i (37 °C, 340 nm) after the addition of 6.6 mM DL-isocitric acid. Malate dehydrogenase (MDH): The cell solution was mixed with 100 mM potassium phosphate buffer (pH 7.5) and 0.14 mM β-NADH, and the absorbance was measured using Biolis 24i (37 °C, 340 nm) after the addition of 7.6 mM oxaloacetic acid. Specific activity is defined as units per milligram protein and the data were presented as ratios of the untreated control.

2.5. Total RNA Extraction

Total RNA was isolated from HepG2 cells using the TRIzol reagent (Invitrogen Life Technologies, Tokyo, Japan). After culturing the cells under the above conditions, the medium was removed, the cells were washed with PBS, and 500 μL of TRIzol reagent was added and recovered. After standing at room temperature for 5 min, 0.1 mL of chloroform was added and stirred, and the mixture was allowed to stand at room temperature for 2-3 min, then centrifuged at 4 °C and 12,000× g for 15 min. An amount of 125 μL of the upper layer was recovered and 250 μL of isopropanol was added. After standing at room temperature for 10 min, it was centrifuged at 12,000× g for 10 min at 4 °C. Cells were washed with 75% ethanol, evaporated to dryness and dissolved in 30 µL of RNase-free water. RNA purity was assessed by the ratio of spectrophotometric absorbance at 260 and 280 nm (A260/280 nm) using a NanoDrop ND-1000 spectrophotometer (NanoDrop Products, Wilmington, DE, USA).

2.6. Quantitative Real-Time RT-PCR Analysis

Total RNA was used for mRNA analysis by quantitative real-time reverse transcription polymerase chain reaction (RT-PCR). Primers were designed using a web application (PRIMER3), and the sequence information is as follows: since the peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC1a) gene has a long sequence, two primers were designed, both near the 3′ end and 5′ end. PGC1a (3′ end) sense: GCAGAGAGGGAACTTTGCAC, antisense: ACAGCCATCAAGAAAGGACA. PGC1a (5′ end) sense: CCTGTGGATGAAGACGGATT, antisense: TGGAGGAAGGACTAGCCTCA. SYBR Green EX (Takara Bio, Madison, WI, USA) was used for the PCR on a real-time PCR detection system (Takara Bio). The relative amounts of mRNA were normalized to glyceraldehyde-3-phosphate dehydrogenase (GAPDH sense: 5′-CGCCTGGAGAAACCTGCCAA-3′, antisense: 5′-GGAGACAACCTGGTCCTCAG-3′) mRNA levels and were expressed as fold-change values.

2.7. Proteomics Using Isobaric Tags for Relative and Absolute Quantitation (iTRAQ) Methods and Identification of Regulated Proteins

We performed differential proteomic analysis of HepG2 cells using iTRAQ, as described in our previous study [14]. iTRAQ is a non-gel-based technique used to quantify proteins from different sources in a single experiment. It uses isotope-coded covalent tags. Total protein was extracted using lysis buffer and separated by centrifugation at 12,000× g for 30 min at 4 °C. Protein concentrations were determined using the Bradford assay, and pooled proteins (20 μg) for each group (0, 50, 100 and 200 μg/mL of CGA treatment) were subjected to iTRAQ using the iTRAQ® kit, performed according to the manufacturer’s protocol (AB SCIEX, Framingham, MA, USA) with liquid chromatography–tandem mass spectrometry (LC/MS/MS) (TripleTOF TM 5600 + System with Eksigent nanoLC, AB SCIEX). Within an iTRAQ run, differentially changed proteins were determined by ProteinPilot software (AB SCIEX) based on the p-values, which are generated using the peptides used to quantitate the respective protein and give a measure of confidence (95%). In this study, the data of proteins with significantly changed (p-value < 0.1) levels were uploaded to the statistical analysis tool Ingenuity Pathway Analysis (IPA), and enrichment analysis was performed [14].

2.8. Statistical Analysis

Data were presented as the mean ± standard error (SE). Statistical analysis was performed using a one-way analysis of variance (ANOVA) accompanied by a Tukey’s test. A p-value < 0.05 was considered statistically significant.

3. Results

3.1. The Effect of Coffee Powder and Chlorogenic Acid (CGA) on HepG2 Cell Viability

The potential effects of coffee powder and CGA on the viability and number of HepG2 cells were determined by MTT assay. HepG2 cells were incubated with DMEM containing caffeinated coffee powder, and the results are shown in Figure 1A. HepG2 cells were incubated with caffeinated coffee powder for 24 h, and the cell viability was significantly affected by the caffeinated coffee powder doses used (100 and 200 μg/mL). In addition, CGA also increased the cell viability in a dose-dependent manner (Figure 1B) with the greatest effect at a dose of 200 μg/mL.

3.2. Mitochondrial Enzyme Activity Analysis

Since HepG2 cell viability was increased by CGA, we next focused on the effect of CGA on the activities of three enzymes: IDH, CS, and MDH, which are key to the mitochondrial TCA cycle. The results revealed that the activities of all three enzymes were increased by CGA in a concentration-dependent manner (Figure 2). However, CGA addition did not alter the mRNA levels of these enzymes.

3.3. Proteomics Using the iTRAQ Method

To explore the effect of CGA on HepG2 cells in a more comprehensive manner, we subjected the proteins extracted from the HepG2 cells treated, as described above, to a proteomic analysis using the iTRAQ method. Using this analysis, 2172 proteins were identified, and 1409 proteins were successfully quantified. Among the identified proteins, 33, 80, and 64 proteins were significantly altered (p < 0.1) by CGA at 50, 100, and 200 μg/mL, respectively. Table 1 shows the 64 proteins whose expression was significantly changed by the addition of 200 μg/mL CGA. The data of the proteins whose levels were significantly altered were uploaded to the statistical analysis tool IPA, and the analysis revealed that the differentially expressed proteins were encoded by genes involved in pathways related to the glycolytic system (ALDOA, GAPDH, PGK1, and ENO1) and mitochondrial proteins (NDUFAB1, NDUFAF2, COX5B, ATP5B, and ATP5J). The increase in the levels of a protein involved in the glycolytic system suggests that the signals regulating glucose metabolism and the TCA cycle were enhanced by CGA (Table 1).

4. Discussion

The effects of coffee ingredients and coffee polyphenols on cultured hepatic cells have been examined in many studies. First, to evaluate the validity of the study design in which coffee ingredients were directly added to the culture medium, we referenced a previous study that reported the concentrations of coffee ingredients in the blood after the participants drank coffee [15]. The authors reported that the maximum blood concentration of CGA was 5 μM (1.77 μg/mL) after the participants orally ingested 40 g of coffee powder. Another study revealed that after participants drank a cup of coffee, the concentration of the sum of CGA metabolites (including dihydrocaffeic acid and dihydroferulic acid) in their blood was approximately 1 μM [16].
Furthermore, the effect of chlorogenic acid directly added to cultured hepatic cells on lipid metabolism was reported by Liu et al. [17]. In that study, the effects of chlorogenic acid, caffeic acid, and ferulic acid (20–100 μg/mL, respectively) on oleic acid-induced hepatosteatosis were examined, and these coffee polyphenols were found to inhibit the accumulation of lipids in hepatic cells. These studies suggest that coffee polyphenols in the blood could exert physiological actions. Therefore, the present study design in which coffee ingredients were directly added into the culture medium aimed to mimic the conditions after a long-term coffee consumption to some extent.
We performed this study to further investigate the effects of coffee and CGA on energy metabolism in an in vitro experiment using HepG2 cells. Considering the results of the MTT assay, we found that coffee powder and CGA treatment increased cell viability and cell numbers (Figure 1); moreover, our results indicate that CGA at the concentrations tested is not cytotoxic to HepG2 cells, but rather exerts a slight proliferative effect. In addition, PGC1α is reported to be a genetic marker for mitochondrial biogenesis, so we measured its expression by analyzing total RNA extracted from HepG2 cells. The results showed no difference in PGC1α levels with or without the addition of CGA (Figure S1). Therefore, further studies are needed to confirm whether the proliferative effect of CGA is related to mitochondrial activity.
Based on our enzyme activity measurement, CGA increased the activities of three key enzymes, CS, IDH, and MDH (Figure 2). However, the mRNA expression levels of the three genes were not affected by CGA, as observed in the quantitative PCR analysis (data not shown). thus, we speculated that CGA influences the activities of enzymes and not their mRNA levels. Nevertheless, further investigation on the changes in the different isoforms and the time-dependent mRNA expression of the three enzymes, is warranted.
To obtain a more comprehensive view of the mechanism underlying this phenomenon, we performed a proteomic analysis using the iTRAQ method. The enrichment analysis of the proteins whose levels were differentially altered by the addition of 200 μg/mL of CGA revealed that these proteins were either involved in pathways of the glycolytic system (ALDOA, GAPDH, PGK1, and ENO1) or mitochondrial proteins (NDUFAB1, DUFAF2, COX5B, ATP5B, and ATP5J). The increased levels of proteins involved in the glycolytic system suggest that signals between glucose metabolism and the TCA cycle are enhanced by CGA. NADH dehydrogenases (NDUFAB1 and NDUFAF2) are the first enzymes of the electron transport system in mitochondria, and COX5B is an enzyme that is also known to be involved in the electron transport system. ATP synthases (ATP5B, ATP5J) synthesize ATP from the electron transport system in the mitochondria. The increased levels of these mitochondrial proteins suggest that CGA not only enhances the TCA cycle but also other mitochondrial activities, including the electron transport chain and ATP synthesis.
However, additional studies are needed to pinpoint the potential transcriptional factors involved in these processes and clarify the detailed mechanisms impacting the regulation of NADH dehydrogenases and ATP synthases. Although HepG2 cells are widely used to study hepatocyte metabolism as well as hepatocyte physiology, the results presented here should be interpreted with caution owing to their cancerous characteristics. Further studies of primary cell models are needed to confirm the effect of CGA and coffee extract on energy metabolism.
Together, the results of the present in vitro study provide novel insights into the mechanism whereby CGA enhances energy metabolism, that is, by increasing hepatic mitochondrial activities, including the TCA cycle, electron transport, and ATP synthesis (Figure 3). Our findings demonstrated that CGA induced hepatic alterations in mitochondrial enzyme activities, and increased expression of proteins involved in the glycolytic system, electron transport system, and ATP synthesis in the mitochondria. This proposed mechanism could be a key aspect in elucidating the beneficial effects of coffee intake.

5. Conclusions

In summary, we examined the effects of CGA on energy metabolism in vitro. We propose a mechanism whereby CGA enhances energy metabolism by increasing hepatic mitochondrial activity, including the TCA cycle, glycolysis, electron transport, and ATP synthesis. This study suggests that these alterations provide important insights into the beneficial effects of coffee intake.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/nu14081676/s1, Figure S1: The effects of chlorogenic acid on the mRNA expression of PGC1a. HepG2 cells were cultured in DMEM containing chlorogenic acid (200 μg/mL), and the mRNA expression at each time point was measured by RT-PCR. A: Using the primer designed near the 3′ end. B: Using the primer designed near the 5′ end.

Author Contributions

Conceptualization, H.K. and S.T.; methodology, S.T. and H.J.; formal analysis, S.T.; investigation, X.L., K.S. and H.J.; data curation, S.T., K.S. and H.J.; writing—original draft preparation, S.T. and X.L.; writing—review and editing, H.J. and H.K.; project administration, H.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research was partly funded by a grant from the All Japan Coffee Association.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. The effects of coffee powder and chlorogenic acid on hepatocellular carcinoma G2 (HepG2) cell viability. HepG2 cells were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM) containing coffee powder or chlorogenic acid for 24 h. The results of the 3-[4,5-Dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide (MTT) assay of cells cultured with (A) caffeinated coffee powder and (B) chlorogenic acid. The data are shown as mean ± SE (n = 4). * p < 0.05, ** p < 0.01 vs. control group.
Figure 1. The effects of coffee powder and chlorogenic acid on hepatocellular carcinoma G2 (HepG2) cell viability. HepG2 cells were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM) containing coffee powder or chlorogenic acid for 24 h. The results of the 3-[4,5-Dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide (MTT) assay of cells cultured with (A) caffeinated coffee powder and (B) chlorogenic acid. The data are shown as mean ± SE (n = 4). * p < 0.05, ** p < 0.01 vs. control group.
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Figure 2. The effects of chlorogenic acid on mitochondrial enzyme activity in HepG2 cells. Confluent cultures of HepG2 cells were cultured with DMEM. Thereafter, different concentrations of chlorogenic acid were added and cells were cultured for 24 h. The enzyme activities of (A) isocitrate dehydrogenase (IDH), (B) citrate synthase (CS), and (C) malate dehydrogenase (MDH) were measured. The data are shown as mean ± SE (n = 4). * p < 0.05, ** p < 0.01 vs. control group.
Figure 2. The effects of chlorogenic acid on mitochondrial enzyme activity in HepG2 cells. Confluent cultures of HepG2 cells were cultured with DMEM. Thereafter, different concentrations of chlorogenic acid were added and cells were cultured for 24 h. The enzyme activities of (A) isocitrate dehydrogenase (IDH), (B) citrate synthase (CS), and (C) malate dehydrogenase (MDH) were measured. The data are shown as mean ± SE (n = 4). * p < 0.05, ** p < 0.01 vs. control group.
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Figure 3. A schematic representation of the proposed mechanism underlying the effects of chlorogenic acid on metabolism as determined by the present in vitro study using HepG2 cells.
Figure 3. A schematic representation of the proposed mechanism underlying the effects of chlorogenic acid on metabolism as determined by the present in vitro study using HepG2 cells.
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Table 1. Differentially expressed proteins between control and chlorogenic acid treatment groups by iTRAQ method.
Table 1. Differentially expressed proteins between control and chlorogenic acid treatment groups by iTRAQ method.
ProteinNameProtein ID50 μg/mL100 μg/mL200 μg/mL
FCp-ValueFCp-ValueFCp-Value
SPTAN1Isoform 3 of Spectrin alpha chain, brainQ13813-30.930.010.890.000.880.00
HMGB1High mobility group protein B1P094290.590.000.420.000.550.00
AHNAKNeuroblast differentiation-associated protein AHNAKQ096660.960.360.830.000.860.00
VSNL1Visinin-like protein 1P627601.070.631.270.011.460.00
PSAPProactivator polypeptideP076020.950.831.120.110.520.01
HPCAL1Hippocalcin-like protein 1P372351.080.501.100.211.330.01
ZC3H15Zinc finger CCCH domain-containing protein 15Q8WU900.850.190.720.000.820.01
GAPDHGlyceraldehyde-3-phosphate dehydrogenaseP044061.300.161.220.001.380.01
CPLX2Complexin-2Q6PUV41.340.141.330.011.700.01
CFL1Cofilin-1P235280.470.010.960.540.660.01
PGK1Phosphoglycerate kinase 1P005581.080.431.160.001.210.01
KRT18Keratin, type I cytoskeletal 18P057831.200.021.170.021.210.02
GLUD1Glutamate dehydrogenase 1, mitochondrialP003671.080.231.070.121.120.02
ATP5BATP synthase subunit beta, mitochondrialP065761.100.511.080.101.180.02
IDH1Isocitrate dehydrogenase [NADP] cytoplasmicO758741.110.341.160.011.210.03
EIF3AEukaryotic translation initiation factor 3 subunit AQ141520.950.320.960.390.900.03
TPRNucleoprotein TPRP122700.990.920.880.060.870.04
PRDX6Peroxiredoxin-6P300410.830.110.960.540.880.04
SRRTSerrate RNA effector molecule homologQ9BXP50.790.120.990.950.810.05
LMO7LIM domain only protein 7Q8WWI10.970.640.780.010.860.05
NASPNuclear autoantigenic sperm proteinP493210.840.070.870.070.850.05
CALRCalreticulinP277970.830.300.870.010.860.05
PNPOPyridoxine-5′-phosphate oxidaseQ9NVS91.060.601.110.151.170.05
HSPA578 kDa glucose-regulated proteinP110211.240.011.040.361.120.05
CALD1Isoform HELA L-CAD II of CaldesmonQ05682-50.810.040.750.020.820.05
PTGES3Prostaglandin E synthase 3Q151850.360.070.920.780.670.05
VDAC1Voltage-dependent anion-selective channel protein 1P217961.200.141.220.111.320.05
WDR1WD repeat-containing protein 1O750831.110.381.140.051.190.05
ENO1Alpha-enolaseP067331.260.141.170.021.280.05
ATICBifunctional purine biosynthesis protein PURHP319391.090.311.100.181.140.06
RPLP260S acidic ribosomal protein P2P053871.370.221.100.271.500.06
HSPA9Stress-70 protein, mitochondrialP386460.850.220.910.300.850.06
MYL6Myosin light polypeptide 6P606601.120.221.090.341.240.06
FKBP4Peptidyl-prolyl cis-trans isomerase FKBP4Q027901.160.251.110.331.230.06
RPL23A60S ribosomal protein L23aP627500.700.210.630.010.680.06
TPD52L2Tumor protein D54O433990.870.270.750.020.820.06
NIPSNAP3AProtein NipSnap homolog 3AQ9UFN00.820.171.080.341.200.06
TPM3Isoform TM30nm of Tropomyosin alpha-3 chainP06753-21.280.291.090.351.450.06
NDUFAB1Acyl carrier protein, mitochondrialO145611.350.331.300.111.870.06
CYCSCytochrome cP999990.730.030.690.020.800.07
PDLIM5PDZ and LIM domain protein 5Q96HC40.830.020.810.020.870.07
ANPEPAminopeptidase NP151440.920.130.910.090.900.07
ADKAdenosine kinaseP552630.810.150.910.360.790.07
ATP5JATP synthase-coupling factor 6, mitochondrialP188592.100.121.460.232.290.08
PCBD1Pterin-4-alpha-carbinolamine dehydrataseP614571.100.541.120.251.370.08
UGDHUDP-glucose 6-dehydrogenaseO607011.100.381.100.081.150.08
NDUFAF2Mimitin, mitochondrialQ8N1831.180.221.110.371.310.08
TTC1Tetratricopeptide repeat protein 1Q996141.010.891.050.561.170.09
LASP1LIM and SH3 domain protein 1Q148470.940.600.980.821.250.09
ALDOAFructose-bisphosphate aldolase AP040751.270.051.340.041.350.09
FTH1Ferritin heavy chainP027940.590.090.650.080.700.09
ACAA23-ketoacyl-CoA thiolase, mitochondrialP427651.180.111.130.341.210.09
ENSAIsoform 8 of Alpha-endosulfineO43768-82.260.191.570.172.770.09
BAT1Spliceosome RNA helicase BAT1Q138380.760.221.040.620.760.09
RPL1360S ribosomal protein L13P263731.240.221.160.681.240.09
UGGT1UDP-glucose:glycoprotein glucosyltransferase 1Q9NYU21.000.990.830.060.880.09
UBQLN1Ubiquilin-1Q9UMX01.110.281.130.221.210.10
MESDC2LDLR chaperone MESDQ146960.830.120.720.060.820.10
NUTF2Nuclear transport factor 2P619701.370.051.580.011.420.10
STRAPSerine-threonine kinase receptor-associated proteinQ9Y3F41.160.121.250.041.180.10
COX5BCytochrome c oxidase subunit 5B, mitochondrialP106061.090.751.060.611.340.10
Differentially expressed proteins (p < 0.1) were treated with 50, 100, and 200 μg/mL of chlorogenic acid. FC: fold change. iTRAQ: isobaric tags for relative and absolute quantitation.
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Takahashi, S.; Saito, K.; Li, X.; Jia, H.; Kato, H. iTRAQ-Based Quantitative Proteomics Reveals the Energy Metabolism Alterations Induced by Chlorogenic Acid in HepG2 Cells. Nutrients 2022, 14, 1676. https://doi.org/10.3390/nu14081676

AMA Style

Takahashi S, Saito K, Li X, Jia H, Kato H. iTRAQ-Based Quantitative Proteomics Reveals the Energy Metabolism Alterations Induced by Chlorogenic Acid in HepG2 Cells. Nutrients. 2022; 14(8):1676. https://doi.org/10.3390/nu14081676

Chicago/Turabian Style

Takahashi, Shoko, Kenji Saito, Xuguang Li, Huijuan Jia, and Hisanori Kato. 2022. "iTRAQ-Based Quantitative Proteomics Reveals the Energy Metabolism Alterations Induced by Chlorogenic Acid in HepG2 Cells" Nutrients 14, no. 8: 1676. https://doi.org/10.3390/nu14081676

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