Histone acetylation and arachidonic acid cytotoxicity in HepG2 cells overexpressing CYP2E1

Hołownia, Adam; Mróz, Robert; Wielgat, Przemysław; Jakubów, Piotr; Jabłoński, J; Braszko, Jan J.

doi:10.1007/s00210-013-0942-4

Cited by 6 publications

(4 citation statements)

References 39 publications

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“…The activation of PPAR-γ was shown to have a relationship with expression of collagen type I induced by TGF-β1 (Bian et al, 2013) and inhibit hepatic stellate cell activation and progression of fibrosis (Attia et al, 2013). Studies have indicated that arachidonic acid is involved in oxidative stress and in inflammatory response (Holownia et al, 2014;Le et al, 2012;Xie et al, 2015) which was also been proved in our GO analysis. ALDH2 and ALDH7A1 were involved in glycolysis/Gluconeogenesis and glycerolipid metabolism, and the results of qRT-PCR and Western blot showed that the expression of ALDH2 and ALDH7A1 decreased after liver injury.…”

Section: Discussionsupporting

confidence: 72%

Mechanisms of CCl<sub>4</sub>-induced liver fibrosis with combined transcriptomic and proteomic analysis

et al. 2016

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-The classic toxicity of carbon tetrachloride (CCl 4 ) is to induce liver lesion and liver fibrosis. Liver fibrosis is a consequence of chronic liver lesion, which can progress into liver cirrhosis even hepatocarcinoma. However, the toxicological mechanisms of CCl 4 -induced liver fibrosis remain not fully understood. We combined transcriptomic and proteomic analysis and biological network technology, predicted toxicological targets and regulatory networks of CCl 4 in liver fibrosis. Wistar rats were treated with CCl 4 for 9 weeks. Histopathological changes, hydroxyproline (Hyp) contents, serum ALT and AST in the CCl 4 -treated group were significantly higher than that of CCl 4 -untreated group. CCl 4 -treated and -untreated liver tissues were examined by microarray and iTRAQ. The results showed that 3535 genes (fold change ≥ 1.5, P < 0.05) and 1412 proteins (fold change ≥ 1.2, P < 0.05) were differentially expressed. Moreover, the integrative analysis of transcriptomics and proteomics data showed 523 overlapped proteins, enriched in 182 GO terms including oxidation reduction, response to oxidative stress, inflammatory response, extracellular matrix organization, etc. Furthermore, KEGG pathway analysis showed that 36 pathways including retinol metabolism, PPAR signaling pathway, glycolysis/gluconeogenesis, arachidonic acid metabolism, metabolism of xenobiotics by cytochrome P450 and drug metabolism. Network of protein-protein interaction (PPI) and key function with their related targets were performed and the degree of network was calculated with Cytoscape. The expression of key targets such as CYP4A3, ALDH2 and ALDH7A1 decreased after CCl 4 treatment. Therefore, the toxicological mechanisms of CCl 4 -induced liver fibrosis may be related with multi biological process, pathway and targets which may provide potential protection reaction mechanism for CCl 4 detoxication in the liver.

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Section: Discussionsupporting

confidence: 72%

Mechanisms of CCl<sub>4</sub>-induced liver fibrosis with combined transcriptomic and proteomic analysis

et al. 2016

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“…Chronic alcohol consumption induces CYP2E1, which plays a pivotal part in ROS production [64]. Studies have shown increased expression of CYP2E1 induced by 100 mM ethanol resulting in alcohol-induced liver injury [65]. The extant study indicates that cotreatment of a probiotic V and Met in ethanol-exposed HepG2 cells and ethanol-fed rats showed reduced mRNA expression levels of CYP2E1 as compared to the ethanol group as well as the individual treatment of either probiotic V and Met.…”

Section: Mediators Of Inflammationmentioning

confidence: 99%

Metformin and Probiotics Interplay in Amelioration of Ethanol-Induced Oxidative Stress and Inflammatory Response in an In Vitro and In Vivo Model of Hepatic Injury

Patel

Parwani

Patel

et al. 2021

Mediators of Inflammation

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Alcohol-induced liver injury implicates inflammation and oxidative stress as important mediators. Despite rigorous research, there is still no Food and Drug Administration (FDA) approved therapies for any stage of alcoholic liver disease (ALD). Interestingly, metformin (Met) and several probiotic strains possess the potential of inhibiting alcoholic liver injury. Therefore, we investigated the effectiveness of combination therapy using a mixture of eight strains of lactic acid-producing bacteria, commercialized as Visbiome® (V) and Met in preventing the ethanol-induced hepatic injury using in vitro and in vivo models. Human HepG2 cells and male Wistar rats were exposed to ethanol and simultaneously treated with probiotic V or Met alone as well as in combination. Endoplasmic reticulum (ER) stress markers, inflammatory markers, lipid metabolism, reactive oxygen species (ROS) production, and oxidative stress were evaluated, using qRT-PCR, Oil red O staining, fluorimetry, and HPLC. In vitro, probiotic V and Met in combination prevented ethanol-induced cellular injury, ER stress, oxidative stress, and regulated lipid metabolism as well as inflammatory response in HepG2 cells. Probiotic V and Met also promoted macrophage polarization towards the M2 phenotype in ethanol-exposed RAW 264.7 macrophage cells. In vivo, combined administration of probiotic V and Met ameliorated the histopathological changes, inflammatory response, hepatic markers (liver enzymes), and lipid metabolism induced by ethanol. It also improved the antioxidant markers (HO-1 and Nrf-2), as seen by their protein levels in both HepG2 cells as well as liver tissue using ELISA. Hence, probiotic V may act, in addition to the Met, as an effective preventive treatment against ethanol-induced hepatic injury.

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“…As shown in Table 3, the top 20 targets are enriched in 7 pathways. Among them, 5 out of 7 pathways have been experimentally validated involved with liver injury, including arachidonic acid metabolism pathway (Holownia et al, 2014) ( P = 4.5 × 10 −4 ), linoleic acid metabolism pathway (Lu et al, 2014) ( P = 6.3 × 10 −7 ), retinol metabolism pathway (Freund and Gotthardt, 2017) ( P = 5.2 × 10 −4 ), metabolism of xenobiotics by cytochrome P450 pathway (Gonzalez, 2005) ( P = 7.6 × 10 −4 ), and drug metabolism-cytochrome P450 pathway (Gabbia et al, 2017) ( P = 2.3 × 10 −7 ). Taking retinol metabolism pathway as an example, the pathway has been demonstrated to regulate hepatic immunological response to cholestatic injury and alleviate hepatic fibrosis in different rodent models (Freund and Gotthardt, 2017).…”

Section: Resultsmentioning

confidence: 99%

In silico Identification and Mechanism Exploration of Hepatotoxic Ingredients in Traditional Chinese Medicine

Cai

Guo

et al. 2019

Front. Pharmacol.

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Backgrounds and Aims Recently, a growing number of hepatotoxicity cases aroused by Traditional Chinese Medicine (TCM) have been reported, causing increasing concern. To date, the reported predictive models for drug induced liver injury show low prediction accuracy and there are still no related reports for hepatotoxicity evaluation of TCM systematically. Additionally, the mechanism of herb induced liver injury (HILI) still remains unknown. The aim of the study was to identify potential hepatotoxic ingredients in TCM and explore the molecular mechanism of TCM against HILI. Materials and Methods In this study, we developed consensus models for HILI prediction by integrating the best single classifiers. The consensus model with best performance was applied to identify the potential hepatotoxic ingredients from the Traditional Chinese Medicine Systems Pharmacology database (TCMSP). Systems pharmacology analyses, including multiple network construction and KEGG pathway enrichment, were performed to further explore the hepatotoxicity mechanism of TCM. Results 16 single classifiers were built by combining four machine learning methods with four different sets of fingerprints. After systematic evaluation, the best four single classifiers were selected, which achieved a Matthews correlation coefficient (MCC) value of 0.702, 0.691, 0.659, and 0.717, respectively. To improve the predictive capacity of single models, consensus prediction method was used to integrate the best four single classifiers. Results showed that the consensus model C-3 (MCC = 0.78) outperformed the four single classifiers and other consensus models. Subsequently, 5,666 potential hepatotoxic compounds were identified by C-3 model. We integrated the top 10 hepatotoxic herbs and discussed the hepatotoxicity mechanism of TCM via systems pharmacology approach. Finally, Chaihu was selected as the case study for exploring the molecular mechanism of hepatotoxicity. Conclusion Overall, this study provides a high accurate approach to predict HILI and an in silico perspective into understanding the hepatotoxicity mechanism of TCM, which might facilitate the discovery and development of new drugs.

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Histone acetylation and arachidonic acid cytotoxicity in HepG2 cells overexpressing CYP2E1

Cited by 6 publications

References 39 publications

Mechanisms of CCl<sub>4</sub>-induced liver fibrosis with combined transcriptomic and proteomic analysis

Mechanisms of CCl<sub>4</sub>-induced liver fibrosis with combined transcriptomic and proteomic analysis

Metformin and Probiotics Interplay in Amelioration of Ethanol-Induced Oxidative Stress and Inflammatory Response in an In Vitro and In Vivo Model of Hepatic Injury

In silico Identification and Mechanism Exploration of Hepatotoxic Ingredients in Traditional Chinese Medicine

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