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. 2015 Oct 1:3:e1292.
doi: 10.7717/peerj.1292. eCollection 2015.

Investigation into the effects of antioxidant-rich extract of Tamarindus indica leaf on antioxidant enzyme activities, oxidative stress and gene expression profiles in HepG2 cells

Nurhanani Razali  1 , Azlina Abdul Aziz  1 , Chor Yin Lim  1 , Sarni Mat Junit  1
Affiliations

Investigation into the effects of antioxidant-rich extract of Tamarindus indica leaf on antioxidant enzyme activities, oxidative stress and gene expression profiles in HepG2 cells

Nurhanani Razali et al. PeerJ. .

Abstract

The leaf extract of Tamarindus indica L. (T. indica) had been reported to possess high phenolic content and showed high antioxidant activities. In this study, the effects of the antioxidant-rich leaf extract of the T. indica on lipid peroxidation, antioxidant enzyme activities, H2O2-induced ROS production and gene expression patterns were investigated in liver HepG2 cells. Lipid peroxidation and ROS production were inhibited and the activity of antioxidant enzymes superoxide dismutase, catalase and glutathione peroxidase was enhanced when the cells were treated with the antioxidant-rich leaf extract. cDNA microarray analysis revealed that 207 genes were significantly regulated by at least 1.5-fold (p < 0.05) in cells treated with the antioxidant-rich leaf extract. The expression of KNG1, SERPINC1, SERPIND1, SERPINE1, FGG, FGA, MVK, DHCR24, CYP24A1, ALDH6A1, EPHX1 and LEAP2 were amongst the highly regulated. When the significantly regulated genes were analyzed using Ingenuity Pathway Analysis software, "Lipid Metabolism, Small Molecule Biochemistry, Hematological Disease" was the top biological network affected by the leaf extract, with a score of 36. The top predicted canonical pathway affected by the leaf extract was the coagulation system (P < 2.80 × 10(-6)) followed by the superpathway of cholesterol biosynthesis (P < 2.17 × 10(-4)), intrinsic prothrombin pathway (P < 2.92 × 10(-4)), Immune Protection/Antimicrobial Response (P < 2.28 × 10(-3)) and xenobiotic metabolism signaling (P < 2.41 × 10(-3)). The antioxidant-rich leaf extract of T. indica also altered the expression of proteins that are involved in the Coagulation System and the Intrinsic Prothrombin Activation Pathway (KNG1, SERPINE1, FGG), Superpathway of Cholesterol Biosynthesis (MVK), Immune protection/antimicrobial response (IFNGR1, LEAP2, ANXA3 and MX1) and Xenobiotic Metabolism Signaling (ALDH6A1, ADH6). In conclusion, the antioxidant-rich leaf extract of T. indica inhibited lipid peroxidation and ROS production, enhanced antioxidant enzyme activities and significantly regulated the expression of genes and proteins involved with consequential impact on the coagulation system, cholesterol biosynthesis, xenobiotic metabolism signaling and antimicrobial response.

Keywords: Antioxidant; Enzyme-Linked Immunosorbent Assay (ELISA); Gene expression; Ingenuity Pathway Analysis; Tamarindus indica leaf; Western blotting; cDNA microarray; qRT-PCR.

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Conflict of interest statement

The authors declare there are no competing interests.

Figures

Figure 1
Figure 1. Analyses of lipid peroxidation, antioxidant enzymes and ROS.
(A–F): Analyses of lipid peroxidation, antioxidant enzymes and reactive oxygen species (ROS) in untreated, untreated + H2O2-induced and leaf-pre-treated + H2O2-induced HepG2 cells. (A–B) The effects of the leaf extract on lipid peroxidation, measured as MDA levels (A) and 4-HNE protein adduct level (B) in HepG2 cells. Results for MDA levels were expressed as nmol MDA equivalents/mg of protein while 4-HNE levels were expressed as nmol 4-HNE adduct/mg of protein. MDA-malondialdehyde; 4-HNE-4-hydroxynonenal (C–E) Superoxide dismutase (C), catalase (D) and glutathione peroxidase (E) activities were determined using commercial assay kits (Cayman Chemicals). (F) ROS production in HepG2 cells was measured using fluorescence multi-detection microplate reader and the results were expressed as Relative Fluorescence Unit (RFU). Values with different lower case letters are significantly different (p < 0.05).
Figure 2
Figure 2. Image-based ROS measurement captured by fluorescence microscopy.
(A–C) Image-based ROS measurement captured by fluorescence microscopy in HepG2 cells; (A) Untreated and unchallenged HepG2, (B) Untreated and H2O2-challenged HepG2 and (C) Leaf-pre-treated and H2O2-challenged HepG2.
Figure 3
Figure 3. PCA plot.
(A) A Principal Component Analysis (PCA) plot generated using Partek software of HepG2 cells grown in the presence or absence of the methanol leaf extract of T. indica. (Data are clustered based on three biological replicates (n = 3) of control and treated samples. Arrays for the untreated group are in blue and those for the treated group are in green. Each ball represents a sample. (B) Hierarchical clustering of highly significantly expressed genes that are associated to different pathways generated by Genesis software. The gene expression was regulated in response to the treatment with leaf extract on HepG2 cells. The regulation pattern was differentiated with 2 colours; green for down regulation and red for up regulation. The clustering was generated using Genesis software.
Figure 4
Figure 4. Validation of microarray data using qRT-PCR.
The bar chart shows the gene expression patterns (presented as fold change) of selected significantly regulated genes calculated using qRT–PCR and microarray analysis. The down-regulated genes selected were CYP24A1, ANXA3 and AREG, while the up-regulated genes were LEAP2, FGA, FGG, SERPINE1, IFNGR1, MVK, DHCR24, ALDH6A1 and ADH6. All qRT-PCR data were normalized to that of GAPDH, a housekeeping gene.
Figure 5
Figure 5. IPA graphical representation.
(A) IPA graphical representation of the molecular relationships between the significantly regulated genes to the predicted canonical pathways in response to the leaf treatment in HepG2 cells. The network is displayed graphically as nodes (genes) and edges (the biological relationships between the nodes). Nodes in red indicate up-regulated genes while those in green represent down-regulated genes. Various shapes of the nodes represent functional class of the proteins. Edges are displayed with various labels that describe the nature of the relationship between the nodes. Name of genes with their corresponding abbreviations are as follows: ADH6, Alcohol dehydrogenase 6; ALDH6A1, Aldehyde dehydrogenase 6 family, member A1; ALDH9A1, Aldehyde dehydrogenase 9 family, member A1; ANXA3, Annexin A3; CYP24A1, Cytochrome P450, family 24, subfamily A, polypeptide 1; DHCR24, 24-dehydrocholesterol reductase; EPHX1, Epoxide hydrolase 1; FGA, Fibrinogen alpha chain; FGG, Fibrinogen gamma chain; GSTM4, Glutathione S-transferase mu 4; IFNGR1, Interferon gamma receptor 1; KNG1, Kininogen 1; LEAP2, Liver-expressed antimicrobial peptide; LSS, Lanosterol synthase; MVK, Mevalonate kinase; MX1, Myxovirus resistance 1; SERPINC1, Serpin peptidase inhibitor, clade C (antithrombin), member 1; SERPIND1, Serpin peptidase inhibitor, clade D (heparin cofactor), member 1, SERPINE1, Serpin peptidase inhibitor, clade E (Nexin, Plasminogen activator inhibitor, type 1), member 1; TM7SF2, Transmembrane 7 superfamily member 2. (B) IPA graphical representation showing the effect of significantly regulated genes, ALDH6A1, ALDH6 and GSTM4 in the detoxification process of 4-HNE and MDA. This figure demonstrates that the three genes are involved in the xenobiotic metabolism signaling pathway as on one of the top canonical pathway generated by IPA. The process is displayed graphically as nodes (genes) and edges (the biological relationships between the nodes). Nodes in red indicate up-regulated genes. Various shapes of the nodes represent functional class of the proteins. Edges are displayed with various labels that describe the nature of the relationship between the nodes. (C) IPA graphical representation of the molecular relationships between KNG1, SERPINE1, SERPINC1, SERPIND1 and Fibrinogen that are involved in “Coagulation System”, the top predicted canonical pathway in HepG2 cells affected by the methanol leaf extract of T. indica. The network is displayed graphically as nodes (genes) and edges (the biological relationships between the nodes). Nodes in red indicate up-regulated genes. Various shapes of the nodes represent functional class of the proteins. Edges are displayed with various labels that describe the nature of the relationship between the nodes. Name of genes/proteins with their corresponding abbreviations are as follows: A2M, Alpha-2-macroglobulin; BDK, Bradykinin; BDKR, Bradykinin receptor; F2, Coagulation factor II (thrombin); F2a, Coagulation factor IIa (thrombin); F2R, Coagulation factor II receptor; F3, Coagulation factor III (thromboplastin, tissue factor); F5a, Coagulation factor V (proaccelerin, labile factor); F7, Coagulation factor VII (serum prothrombin conversion accelerator); F7a, Coagulation factor VIIa (serum prothrombin conversion accelerator); F8, Coagulation factor VIII (procoagulant component); F8a, Coagulation factor VIIIa (procoagulant component); F9, Coagulation factor IX; F9a, Coagulation factor IXa; F10, Coagulation factor X; F10a, Coagulation factor Xa; F11, Coagulation factor XI; F11a, Coagulation factor XIa; F12, Coagulation factor XII (Hageman factor); F12a, Coagulation factor XIIa (Hageman factor); F13, Coagulation factor XIII; F13a, Coagulation factor XIIIa; KLKB1a, Kallikrein B plasma 1a; PLG, Plasminogen; SERPINA1, Serpin peptidase inhibitor, clade A, member 1; SERPINA5, Serpin peptidase inhibitor, clade A, member 5; SERPINF2, Serpin peptidase inhibitor, clade F, member 2; TFPI, Tissue factor pathway inhibitor; THBD, Thrombomodulin; TPA, Tissue plasminogen activator; UPA, Urokinase plasminogen activator; UPAR, Urokinase plasminogen activator receptor; vWF, von Willebrand factor.
Figure 6
Figure 6. ELISA analyses of selected proteins.
(A) Enzyme-Linked Immunosorbent Assay (ELISA) analyses of the human IFNGR1, LEAP2, SERPINE1, ANXA3, KNG1, MX1, FGG, MVK, ALDH6A1 and ADH6 antibodies level in the untreated and leaf-treated HepG2 cells. ELISA analyses were done according to manufacturer’s protocols (Cloud-clone, Houston, Texas, USA; Cusabio Biotech, Wuhan, China). Bars not sharing the same superscript letter indicate significant difference at p < 0.05 (B) Up regulation of IFNGR1 (a) and SERPINE1 (b) after treatment with IC20 concentration of the leaf extract for 24 h. Protein levels were measured with specific antibodies by western blot analysis; β-actin was the loading control. Untreated cells were used as control. The experiments were repeated in triplicates and the representative blot was shown. Bars not sharing the same superscript letter indicate significant difference at p < 0.05.
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Grants and funding

This research project was funded by research grants (PV116-2012A and H-20001-00-E000009-B29000) from University of Malaya, Kuala Lumpur, Malaysia and FP015-2013B from the Ministry of Education, Malaysia. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.