SIRT3-IDH2 axis is a target of dietary fructose: implication of IDH2 as a key player in dietary carcinogen toxicity in mice colon

SIRT3-IDH2 axis is a target of dietary fructose: implication of IDH2 as a key player in dietary carcinogen toxicity in mice colon | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article SIRT3-IDH2 axis is a target of dietary fructose: implication of IDH2 as a key player in dietary carcinogen toxicity in mice colon Jae Kyeom Kim, Jeong Hoon Pan, Aykin-Burns Nukhet, Kimberly J. Krager, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6226269/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Nov, 2025 Read the published version in Experimental & Molecular Medicine → Version 1 posted 10 You are reading this latest preprint version Abstract Introduction The potential roles of fructose in colon cancer are growing concerns. Fructose consumption has been linked to oxidative stress and mitochondrial dysfunction, yet its specific molecular mechanisms in colon carcinogenesis remain underexplored. Objectives This study aimed to investigate the molecular mechanisms by which dietary fructose contributes to colon carcinogenesis, focusing on the role of mitochondrial NADP + -dependent isocitrate dehydrogenase (IDH2). Methods Using an unbiased multi-omics approach (transcriptomics and proteomics), liver and colon tissues from fructose-fed wild-type (WT) mice were analyzed to identify key genes involved in cancer-related pathways. Human liver transcriptomic data (GSE256398) was analyzed to confirm alterations in aryl hydrocarbon receptor (AhR) signaling and the SIRT3-IDH2 axis. IDH2 knockout (KO) mice were exposed to a dietary carcinogen, 2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine (PhIP), to validate IDH2's role in colon cancer development. In vitro, fructose’s effects on SIRT3 expression and IDH2 activity were assessed. Results Fructose-fed WT mice exhibited suppressed AhR signaling, increased oxidative stress, and mitochondrial dysfunction via the SIRT3-IDH2 axis. In human liver datasets, AhR-associated genes and SIRT3-IDH2 expression were reduced in MASLD and cirrhosis. IDH2 KO mice showed heightened DNA damage, colonic tumorigenesis, and mitochondrial and GSH-mediated detoxification disruptions following PhIP exposure. In vitro, fructose reduced SIRT3 expression and IDH2 activity, further supporting its role in promoting colon carcinogenesis. Conclusion Fructose promotes colon carcinogenesis by disrupting mitochondrial function and impairing DNA damage response mechanisms, particularly through SIRT3-IDH2 axis suppression. These findings highlight the critical role of mitochondrial dysfunction in fructose-induced carcinogenesis and suggest the SIRT3-IDH2 axis as a potential therapeutic target. Biological sciences/Molecular biology/DNA damage and repair Biological sciences/Molecular biology/RNA metabolism/RNA modification 2-amino-1-methyl-6-phenylimidazo[4 5-b]pyridine glutathione depletion multi-omics xenobiotic metabolism Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Fructose-containing sweeteners are widely used (e.g., beverages) and represent ≈ 30% of total sweeteners consumed in the US 1 . While fructose's role in metabolic syndromes has been studied, conflicting results exist, particularly in studies tied to food industry funding [e.g., reviewed in 2 ]. Recent epidemiological evidence links fructose intake to carcinogenesis, showing that consuming more than two servings of sweetened beverages daily increases early-onset colon cancer risk by 2.2-fold 3 . Animal studies also indicate that high fructose intake promotes colonic neoplastic lesions 4 and enhances tumor progression through lipid metabolism dysregulation, independent of metabolic syndrome 5 . The association between fructose and colon cancer has been demonstrated in multiple epidemiological studies 6 , 7 . Likewise, a recent epidemiological study estimated that more than 2 servings of sweetened beverages per day increase the risk of early onset of colon cancer by 2.2-fold 3 . In an early mouse study, a single high dose of fructose (10 g/kg bw) increased a chemical-induced colonic neoplastic lesion marker (i.e., aberrant crypt foci), compared to glucose 4 . Similarly, a recent study showed that a modest amount of high fructose corn syrup promoted colon tumor size/grade through dysregulation of lipid metabolism in the absence of metabolic syndrome 5 ; however, limitations to extrapolating to ‘healthy’ humans are 1) the study utilized an adenomatous polyposis coli mutant mouse model that is predisposed to intestinal adenoma formation, and 2) the animals were exposed to fructose ‘after’ tamoxifen injection to initiate carcinogenesis 8 . The mechanisms thought to play a role in the effects of fructose in colon cancer include increased reactive oxygen species (ROS), chronic inflammation 9 , 10 , and the production of advanced glycation end-products (which promote carcinogenesis) 11 . Furthermore, our previous work has shown that fructose suppressed hepatic Aryl Hydrocarbon Receptor (AhR) signaling, whereas glucose did not, indicating specific implications of fructose for carcinogen metabolism 12 Although the above studies underscore the importance of individual dietary factors, it is unknown how red meat and fructose, which are commonly consumed together, contribute jointly to colon cancer. Understanding the mechanistic link between fructose and colon cancer is critical, as it could reveal new insights into the potential carcinogenic effects of high fructose intake and inform strategies for mitigating the risks associated with excessive fructose consumption. In the present study, we utilized unbiased multi-omics techniques in conjunction with comprehensive bioinformatics analyses to find key molecular interactions responsible for the initiation of colon cancer. Specifically, liver tissues of fructose-fed mice were subjected to transcriptomics and proteomics to find potential key genes that may play crucial roles in carcinogenesis. After, the target gene [i.e., mitochondrial NADP + -dependent isocitrate dehydrogenase (IDH2)] was deleted in mice that were subsequently treated with a dietary carcinogen [i.e., 2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine (PhIP)] to validate predictions in transcriptomics and proteomics. Subsequently, colonic transcriptomics was carried out to analyze how IDH2 gene is interlinked with colonic carcinogenesis. Overall, herein, the use of a multi-omics approach allows us to capture the complexity of these molecular interactions, providing a more holistic view of how dietary risk factors (namely, fructose and PhIP) can contribute to carcinogenesis. Materials and Methods Animals experiment I: Ad libitum fructose intake study A total of 21 four-week-old male and female C57BL/6N mice (Central Lab Animal Inc; Seoul, Republic of Korea) were randomly divided into control (CON; drinking water; 4 males and 6 females) and fructose (FRU; 34% fructose water; 5 males and 6 females). After one week of acclimation, the mice were housed separately by sex under controlled temperature (23 ± 2°C), humidity (50 ± 5%), and 12/12 h light-dark cycles in the Korea University Animal Facility. Animal handling and experimental protocols were approved by the Ethical Committee of Korea University (Protocol Number: KUIACUC-2018-77). Animals experiment II: Time course effect of fructose on AhR A total of 28 four-week-old male C57BL/6N mice (Central Lab Animal Inc) were randomly assigned to the following experimental groups: 2 week-Control (5 males), 2 week-34% fructose (5 males), 4 week-Control (5 males), and 4 week-34% fructose (5 males). After a week of acclimation to AIN-93G diet, 8 mice were euthanized at the beginning of fructose intervention as a baseline group. Another 20 mice were euthanized in the second (2 wk) and fourth weeks (4 wk). Other experimental conditions including housing, diet, anesthesia, and tissue collections were identical to the experiment I-1. Animals experiments III and IV: Short-/long-term PhIP-induced models IDH2 knockout (IDH2 KO) mice and their littermate wild-type (WT) mice were maintained under the same housing conditions as described in the Animal experiment I. All animal handling and experiments were performed in accordance with a protocol approved by the Institutional Animal Care and Use Committee of the University of Delaware (IACUC protocol approval number: 1354-2020-A). For a short-term study, a total of 20 mice were randomly assigned to four experimental groups: WT control group, WT + PhIP group, IDH2 KO control group, and IDH2 KO + PhIP group. After acclimation, the PhIP groups received an intraperitoneal injection of PhIP (10 mg/kg of body weight, dissolved in corn oil; Toronto Research Chemicals; North York, ON, Canada). The injection volume of PhIP did not exceed 100 µL and was calculated based on body weight. The control group mice were treated with corn oil only (10 mL/kg of body weight). Twenty-four hours after the PhIP injection, the mice were euthanized by exposure to CO 2 gas, followed by cardiac puncture. For the long-term study, similarly to the short-term study, 60 mice were randomly divided into four groups. After the acclimation period, 100 mg/kg body weight of PhIP was orally administrated to mice in PhIP groups twice at three-day intervals. Four days after the second PhIP administration, 2.5% dextran sulfate sodium (DSS) —commonly used in colorectal cancer studies for its relevance to clinical features 13 , 14 — was added to drinking water for four days, followed by seven weeks of observation period. Finally, all mice were euthanized by exposure to CO 2 gas. Daily food intake was measured, and behavioral activity was monitored to assess animal health and well-being after PhIP or PhIP/DSS treatment. Harvested tissues were stored at -80°C in the RNALater solution or fixed with 10% neutral buffered formalin solution for further analyses. Cell culture validation Mouse hepatocyte (AML12; American Type Culture Collection; Manassa, VA, USA) was cultured in Dulbecco's Modified Eagle's Medium (also known as DMEM)/F12 media supplemented with 10% fetal bovine serum, 40 ng/mL dexamethasone, and Insulin-Transferrin-Selenium-G Supplement (Invitrogen; Carlsbad, CA, USA). Cells were incubated at 37ºC with 5% CO 2 and water saturation. Cells were treated with 5 mM fructose for 24 hours, and then cells were harvested for further analyses. RNA extraction and mRNA expression analysis Tissue or cellular RNAs were isolated using the RNeasy Plus Universal Mini Kit (Qiagen; Hilden, Germany) as described elsewhere 15 . For 84 mRNAs related to DNA damage/repair, RT 2 Profiler PCR Array (Qiagen) was used. Transcriptomics Total RNA isolated from liver and colon tissues was used for RNA sequencing. Transcriptomic analysis was performed on hepatic samples (n = 5 per group; 2 males and 3 females) and colonic samples (n = 6 per group; 3 males and 3 females) using a 1 × 50 bp single-end read on an Illumina HiSeq system (Illumina Inc; San Diego, CA, USA), as described previously 16 . The total mapped counts were log2-transformed based on the reads per million to stabilize the variance. The normalized values were then further processed to identify differentially expressed genes (DEGs). Secondary analysis of human liver transcriptome datasets The potential disruption of AhR signaling and the SIRT3-IDH2 axis was investigated in the context of xenobiotic detoxification. While our animal and cellular experiments focus on fructose-induced effects, we sought to determine whether similar molecular alterations occur in human liver disease by analyzing publicly available transcriptomic data. To support our hypothesis that fructose impairs AhR-mediated detoxification and suppresses the SIRT3-IDH2 axis, we first conducted a secondary analysis of human liver transcriptomic data (GSE256398). This analysis aims to contextualize our experimental results within human pathology, highlighting the potential implications of fructose-induced metabolic dysfunction in disease progression. Additionally, this human data will serve as the foundation for further validation in our animal and cellular experiments. Proteomics Protein fractions were isolated from harvested liver tissues obtained from Animal experiment I. The isolated proteins were reduced, alkylated, and digested using filter-aided sample preparation, as previously described 17 . The eluted peptides were ionized via electrospray (2.15 kV) and subjected to mass spectrometric analysis using an Orbitrap Fusion Tribrid mass spectrometer (Thermo-Fisher Scientific) with multi-notch MS3 parameters, as described 18 . Data were acquired in top-speed profile mode with a resolution of 240,000, covering a range of 375 to 1500 m/z. Following collision-induced dissociation (normalized collision energy of 35), MS/MS data were acquired using the ion trap analyzer in centroid mode, ranging from 400–2000 m/z. Up to 10 MS/MS precursors were selected for higher energy collision dissociation (normalized collision energy of 65.0), followed by MS3 reporter ion data acquisition in profile mode with a resolution of 30,000 over a range of 100–500 m/z. Proteins were identified, and reporter ions were quantified using MaxQuant software (Max Planck Institute; Munich, Germany) with a parent ion tolerance of 3 ppm, fragment ion tolerance of 0.5 Da, and reporter ion tolerance of 0.03 Da. Protein identifications were accepted with a false discovery rate (FDR) below 1% and at least two identified peptides. Results were compiled using the Scaffold program (Proteome Software; Portland, OR, USA). The detected protein data were log2-transformed, and the normalized values were used to create a short list. Proteins with a p-value 1.5 were considered significantly different, resulting in 179 differentially expressed proteins (DEPs), which were further analyzed using Ingenuity Pathway Analysis (IPA; Qiagen). Western blot Protein expression was analyzed using western blotting as we described elsewhere 19 , 20 . Each membrane included a reference sample, which was used across all blots. The final results were calculated by determining the ratio of the target protein to β-actin and normalizing it by dividing this ratio by the reference sample/β-actin ratio to account for inter-assay variation. Immunoprecipitation of IDH2 Immunoprecipitation for acetylated IDH2 was carried out using magnetic beads. Crude protein extracts from hepatocytes treated with either distilled water or 5 mM fructose were incubated with anti-acetyl-IDH2 antibody bound to the magnetic beads. Eluted antigens (i.e., acetyl-IDH2 proteins) were utilized for western blot analysis. Pathophysiological analyses Colon tissues fixed in 10% neutral buffered formalin in phosphate-buffered saline (PBS) (wt:vol), followed by dehydration with 30% sucrose solution were cut open and laid flat in between two cover slides. The slide sandwiches were frozen on dry ice. For embedding, Tissue-Tek Optimal Cutting Temperature (OCT) compound (Sakura Finetek; Torrance, CA, USA) was added to a plastic mold to make an OCT block with a flat surface. The OCT block was attached to a cryo-chuck in a cryostat. Colon tissues in the slide sandwich were transferred to the flat side of the OCT block with the mucosal surface facing up. The mucosal surface was covered with a generous amount of OCT compound. The embedded colon tissues were cut into 5 µm sections and stained with hematoxylin and eosin staining for morphological observation. Stained tissue sections were examined using a 5× objective on a Leica DM 500 microscope equipped with a Leica ICC50E (Leica Camera Inc; Wetzlar, Germany). The use of the low magnification (5×) was to capture a large area of the section. For immunofluorescence analyses, en face colon sections embedded in OCT blocks were incubated with specific primary antibodies overnight at 4°C, followed by washing cycles with PBS. Subsequently, tissue sections were incubated with fluorophores-conjugated secondary antibody for 1 hour at room temperature. The tissue sections were counterstained with 4, 6-diamidino-2-phenylindole, and sealed with cover glass. Obtained images were analyzed using a confocal microscope (Zeiss LSM880, Carl Zeiss AG; Baden-Wurttemberg, Germany). Enzyme activity assays For IDH2 activity, mitochondria of hepatocytes were isolated using a Mitochondrial Isolation Kit for Cultured Cells (Thermo Scientific) according to instructions of the manufacturer. IDH2 activity was measured using IDH Activity Assay Kit (Sigma-Aldrich; St-Louis, MO, USA) according to instructions of the manufacturer. Glutathione Reductase Assay kit (Sigma-Aldrich) was also used to measure hepatic glutathione reductase activity in response to fructose treatment. GSSG/GSH and NADPH/NADP assays Ratios for GSSG/GSH and NADPH/NADP + were measured using GSH/GSSG Ratio Detection Assay Kit and NADP + /NADPH Assay kit (Abcam; Cambridge, UK). Bioinformatics and statistical analyses As for secondary analyses to compare a dose-dependent effects of fructose intake on hepatic carcinogen metabolism, NCBI Gene Expression Omnibus DataSets was utilized to retrieve related transcriptomics datasets. GSE92502 and GSE51885 met our search criteria (i.e., fructose-fed C57BL/6 mice, lower or higher fructose dose than our study); thus, DEGs were acquired via differential gene expression analysis. Each DEG was subjected to the IPA pathway analysis, followed by comparison analysis of the three datasets. Partial least squares-discriminant analysis (PLS-DA) was performed on the colonic transcriptomics dataset prior to differential gene expression analysis. PLS-DA is a supervised classification method that extends the PLS algorithm to identify latent variables that explain the most variance in both predictors and response variables. The visualization for PLS-DA was conducted using the R software package version 4.4.1 ( www.r-project.org ). Our DEGs and DEPs were analyzed using multiple bioinformatics tools as follows. First, the gene ontology analysis was performed using the DAVID tool. Specifically, DEGs from the hepatic transcriptome were analyzed with the DAVID tool to identify enriched terms for Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Additionally, DEGs were subjected to analysis using the IPA software (Qiagen), where the Core Analysis feature of the software was performed to predict related pathways, including canonical pathway analysis and upstream regulator analysis. For all other markers, data are presented as mean ± standard error of the mean (SEM). We assessed whether the data followed a normal distribution using the Shapiro-Wilk test. When the data did not fit a normal distribution, the Mann-Whitney test was applied. Comparisons between two groups were analyzed using an unpaired t-test, while data involving two independent variables, and one dependent variable were first analyzed using two-way ANOVA followed by Tukey’s multiple comparison. In cases where a significant interaction effect was not observed, a One-way ANOVA was conducted, followed by Fisher’s LSD test. A p-value of 0.05 or less was considered statistically significant and GraphPad Prism (Ver. 7.00) was used for the analyses (GraphPad Software; San Diego, CA, USA). Results Fructose-associated suppression of AhR signaling and SIRT3-IDH2 axis in human liver disease In our analysis of human liver transcriptomic data, we observed a significant downregulation of AhR-associated genes in metabolic dysfunction-associated steatotic liver disease (MASLD) and cirrhosis patients compared to healthy controls, particularly those involved in xenobiotic metabolism, including Phase I (CYP1A1, CYP1A2) and Phase II (UGT1A1, UGT1A3, UGT2B4, GSTA1, GSTA2, GSTM3, GSTZ1) detoxification enzymes (Fig. 1 A). The suppression of these genes suggests a progressive decline in hepatic detoxification capacity, potentially increasing susceptibility to carcinogen accumulation. Additionally, we observed a trend of decrease in SIRT3 (p = 0.06) and IDH2 (p = 0.05) expression in MASLD and fibrosis, with the most pronounced reduction in cirrhosis patients. Fructose suppresses the xenobiotic AhR signaling pathway via ROS production Previously, we showed that 34% fructose intake suppresses the AhR signaling pathway in the liver 15 . The AhR signaling pathway is a key pathway that governs genes [e.g., cytochrome P450 (CYPs)] related to carcinogen metabolism in the liver 21 . Interestingly, we found that ‘Chemical carcinogenesis – DNA adduct’ KEGG pathway is predicted enriched in the FRU group, which includes PhIP-DNA adduct-mediated colon cancer ( Fig. S1 ). The prediction is likely due to changes in CYPs by fructose intake as highlighted as key genes of the pathway. As we previously reported, a few key genes governed by the AhR signaling pathway were downregulated including CYPs 15 . In order to further explore a dose-dependent implications of fructose intake on hepatic carcinogen metabolism, our transcriptomics dataset (34% fructose) was compared to two different publicly available RNA sequencing datasets that were treated with lower (20%; GSE92502) or higher (60%; GSE51885) fructose levels than our condition. In this secondary analysis, ‘Aryl Hydrocarbon Receptor Signaling Pathway’ and ‘Xenobiotic Metabolism Signaling Pathway’ were dose-dependently enriched (Fig. 1 B). In a follow-up validation study, we noted that Cyp1a2 and Ugt1a1 mRNA expressions were decreased in fructose-fed mice liver tissues; there was a stronger statistical significance when mice were fed fructose for longer periods (Fig. 1 C). Given that fructose is a known ROS inducer and an interaction between ROS and AhR is well established, the suppression of AhR genes is likely related to fructose-induced oxidative stress under our conditions. Confirming the previous studies as well as our speculation, the FRU group presented significantly increased hydrogen peroxide level (Fig. 1 D); related, mRNAs for AhR-signaling related genes (i.e., Ahr , Arnt , and Cyp1a2 ) were decreased in response to oxidative stress induced by hydrogen peroxide in AML12 hepatocytes (Fig. 1 E). Fructose-induced mitochondrial dysfunction is associated with SIRT3-IDH2 axis In our hepatic transcriptomics and proteomics datasets, ‘Sirtuin Signaling Pathway’ and ‘Mitochondrial Dysfunction’ were predicted the most enriched canonical signaling pathways in fructose-fed mice, respectively (Fig. 2 A). Sirtuins (SIRTs) are a family of proteins that include several sub-forms, such as SIRT1, SIRT3, and SIRT5, each of which plays distinct roles in cellular processes. Among these, SIRT3 is primarily localized in the mitochondria and is well known to regulate mitochondrial function by deacetylating enzymes involved in energy metabolism, such as IDH2. The SIRT3 plays a critical role in maintaining mitochondrial integrity and protecting against oxidative stress, particularly by regulating mitochondrial dynamics, metabolic syndromes, and ROS production. Interestingly, according to our transcriptomics dataset, mitochondrial SIRT3 was predicted decreased in FRU-fed mice, leading to a suppression of IDH2 (Fig. 2 B). As aforementioned, the SIRT3 is a mitochondrial NAD + -dependent deacetylase that directly deacetylates IDH2, which enhances the enzymatic activity of IDH2, thereby increasing its capacity to produce NADPH 22 . Therefore, we explored changes in IDH2 activity in response to SIRT3 KO to elaborate the mitochondrial SIRT3-IDH2 axis. As hypothesized, IDH2 activity and dimerization of IDH2 were significantly decreased in SIRT3 KO mice, showing a direct regulatory mechanism of IDH2 (Fig. 2 C and D ). IDH2 deficient mice are more sensitive to DNA damage response from short-term and long-term exposures to a dietary carcinogen Once we confirmed the implications of fructose intake on IDH2 (via SIRT3), we further aimed to validate the predicted the KEGG pathway, ‘Chemical Carcinogenesis – DNA adduct’. Of the four aromatic amines/amides included in the KEGG pathway [namely, 4-aminobiphenyl, PhIP, 2-amino-3-methylimidazo[4,5-f]quinoline (IQ in Fig. S1 ), and 2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline (MeIQx in Supplementary Fig. S1 )], involved in the pathway, we chose PhIP-induced colon cancer model for the validation as it is the most mass abundant carcinogen present in well-done meats 23 . PhIP can be detoxified via GSTs-mediated conjugation of GSH in the liver, hence GSH is known to be protective against the production of DNA adduct and possibly colon carcinogenesis 24 . Expected, depletion of hepatic GSH is a hallmark of IDH2 deficiency 25 , which led us to explore an implication of IDH2 in PhIP toxicity. In this study, we comprehensively assessed 86 genes involved in DNA damage signaling pathways using the R 2 Profiler qPCR assay in both WT and IDH2 KO mice following 24-hour exposure to PhIP. A heatmap highlighted several key genes related to DNA damage signaling that were significantly impacted by PhIP treatment in the colon of WT mice (Fig. 3 A). Additionally, Fig. 3 B shows 28 genes with statistically significant differences across the experimental groups (Fig. 3 B). IDH2 deficiency in the colon led to the upregulation of several mRNAs, though the effects were not as pronounced as those induced by PhIP exposure alone. Interestingly, in the IDH2 KO mice, some mRNA levels (e.g., Atr , Atrx , and Brca2 ) were further elevated following PhIP treatment compared to the WT + PhIP group. However, the majority of mRNA levels tended to decrease in the IDH2 KO + PhIP group relative to the WT + PhIP group. These findings suggest potential interactions between PhIP exposure and IDH2 deficiency, with complex effects on DNA damage signaling pathways. Following, it was further demonstrated that IDH2 KO mice exhibited significantly higher levels of colonic γH2AX, p53, and cCASP-3 compared to their WT littermates 24 hours after PhIP exposure (Fig. 4 A and B ). Notably, while PhIP treatment activated pATR and cPARP in WT mice, PhIP exposure in the IDH2 KO mice led to the suppression of these proteins. To confirm the implications of IDH2 deficiency in PhIP-induced toxicity from the short-term PhIP-induced model, we examined the effects of long-term PhIP exposure (8 weeks) in IDH2 KO mice; the mice were euthanized 7 weeks after receiving a 1-week PhIP/DSS treatment. Interestingly, the IDH2 KO mice developed more colonic isolated lymphoid follicles (ILFs), as identified by CD3 expression (Fig. 4 C and D ). Furthermore, higher expression levels of γH2AX and PCNA proteins were observed in the IDH2 KO mice compared to WT littermates (Fig. 4 E), aligning with the results of the short-term PhIP exposure study. IDH2 KO exacerbates PhIP-induced colonic damages via multiple networks Our findings clearly indicate that IDH2 KO exacerbates PhIP-induced colonic DNA damage and possibly promotes colon carcinogenesis. However, deletion of a certain gene results in multifaceted effects in general; thus, colonic transcriptomics of WT, WT + PhIP, IDH2 KO, and IDH2 KO + PhIP group was carried out to reveal mechanistic potentials of IDH2 KO. The transcriptomics dataset was applied to PLS-DA, a supervised classification method extending the PLS algorithm to determine axes, which explains the most variance in both predictors and the response variables (Fig. 5 A). As shown IDH2 KO + PhIP (Green in the figure) group seems well-separated and -clustered in the tilted 3D plot, particularly from the IDH2 KO group (Orange in the figure). After, the DEGs, retrieved from the colonic transcriptomics dataset, were utilized for pathway prediction analyses using the IPA software. Based on a comparison analysis of the four groups, mitochondrial function related pathways are important to note (Fig. 5 B). Both IDH2 deletion and PhIP affect mitochondrial dysfunction, leading to exacerbated dysfunction of mitochondria in IDH2 KO + PhIP group. Here, the complex content is systematically deconstructed and explained in each comparison for clarity and understanding. When WT and IDH2 KO groups were compared (see red and green colors as they are actual increased or decreased genes in DEGs, respectively, and orange and blue colors are predictions), IDH2 KO-mediated mitochondrial dysfunction might be more focused on the Complex IV and V ( Fig. S2 ), but PhIP is likely to affect Complex I and IV seen in the comparison between WT and WT + PhIP ( Fig. S3 ). These effects may lead to the overall suppression of the electron transport chain when IDH2 KO and PhIP are applied together ( Fig. S4 ). Interestingly, PhIP treatment in IDH2 KO mice appeared not to be effective on mitochondrial dysfunction compared to IDH2 KO mice (Fig. 5 B). This cannot be clearly addressed in the present study. However, it is possible that PhIP might have triggered a compensatory response aimed at maintaining cellular energy and survival under stress conditions resulting from PhIP treatment. In fact, our data somehow support the hypothesis. Specifically, a reason for that activation status of mitochondrial dysfunction in the comparison between IDH2 KO and IDH2 KO + PhIP was due to that recovery of multiple genes in the complexes which resulting in less significance ( Fig. S5 ). Other mitochondrial pathways [i.e., ‘Electron transport, ATP synthesis, and heat production by uncoupling proteins’, and ‘Oxidative Phosphorylation (OXPHOS)’] were not significantly affected by IDH2 KO, but they were aggravated when PhIP was treated to IDH2 KO mice. We speculate that the mitochondrial dysfunction caused by IDH2 KO might be from other signaling pathways. In fact, some canonical pathways altered by IDH2 KO were related to mitochondrial dysfunction although they were not highlighted. For instance, ‘TCA cycle and respiratory electron transport’ and ‘Glucose metabolism’ were predicted inhibited in IDH2 KO mice, which are crucial pathways for ATP production ( Table S1 ). Previous report supports the speculation as IDH2 deficiency led to depletion of ATP in different cells 26 , 27 . As we mentioned earlier in this study, GSH plays crucial role in PhIP detoxification, and IDH2 is highly associated with GSH recycling via producing NADPH 28 . Importantly, GSH-mediated detoxification pathway was predicted inhibited by IDH2 KO (Fig. 6 A), while PhIP activated it (Fig. 6 B). Moreover, several upstream regulator molecules were associated with the pathway (Fig. 6 C). Inhibition of GSH in IDH2 KO group was reasonable to expect given that knock out of IDH2 induces reductive TCA cycle 29 . Our study also confirmed that IDH2 deletion resulted in a shift of oxidative TCA cycle to reductive evidenced by higher plasma levels of citrate, aconitate, and isocitrate and lower level of α-ketoglutarate in IDH2 KO mice ( Fig. S6 ). However, GSH-mediated detoxification mainly occurs in the liver tissue, and suppression of hepatic GSH is well-known event in response to fructose intake 30 , 31 . Related, we speculated that fructose-induced GSH depletion could be due to the suppression of SIRT3-IDH2 axis, leading us to execute validation in vitro studies using hepatocytes. As expected, fructose treatment led to a reduction in SIRT3 protein expression (Fig. 7 A) and a corresponding decrease in IDH2 enzyme activity in mouse hepatocytes (Fig. 7 B), while IDH1 activity remained unaffected (Fig. 7 C). This indicates that fructose specifically impacts the SIRT3-IDH2 axis. Supporting this, fructose treatment increased the acetylation of IDH2 (Fig. 7 D), despite no changes in IDH2 protein levels (Fig. 7 E), further confirming that fructose acts through SIRT3-mediated deacetylation rather than altering IDH2 expression per se. Additionally, fructose treatment reduced intracellular levels of NADPH and GSH (Fig. 7 F and G ), key molecules involved in antioxidant defense, yet had minimal impact on NADPH-consuming glutathione reductase activity (Fig. 7 H). This suggests that the depletion of GSH is more likely due to impaired NADPH production via the SIRT3-IDH2 axis rather than increased consumption. Taken together, these findings strongly indicate that fructose-induced hepatic GSH depletion is closely linked to the inhibition of the SIRT3-IDH2 pathway. Discussion AhR is activated by binding to ligands such as environmental pollutants including polycyclic aromatic hydrocarbons 32 . Upon ligand binding, AhR translocates to the nucleus, where it dimerizes with the AhR nuclear translocator (also known as ARNT) and binds to xenobiotic response elements in the DNA, initiating transcription of target genes 33 , 34 . Activation of AhR by environmental toxins can lead to the production of ROS, either directly or through the induction of enzymes (e.g., CYPs), which metabolize xenobiotics and generate ROS as by-products 35 . The suppression of AhR in the FRU group could be a negative feedback loop of AhR; fructose-induced oxidative stress may create feedback mechanisms that inhibit AhR signaling. For instance, oxidative stress-induced transcription factors could upregulate inhibitors of AhR (e.g., Ncor ) as evidenced in our previous report 15 . SIRT3 activates several mitochondrial enzymes [e.g., superoxide dismutase 2 and IDH2 36 ]. By deacetylating and activating these enzymes, SIRT3 enhances the ability of cells to neutralize ROS, thereby reducing oxidative stress 37 . In SIRT3-deficient cells or organisms, the lack of deacetylation leads to impaired IDH2 activity, which in turn decreases NADPH being necessary for the reduction of GSH 28 , 38 , 39 . This not only results in an increase in ROS levels, but also suppresses the efficiency of detoxification of xenobiotics via GSH, which contributes to various pathologies, including aging-related diseases 40 , and cancers 41 . Based on the overall findings, it was reasonable to hypothesize that fructose-induced suppression of the SIRT3-IDH2 axis could have affected the enrichment of the chemical carcinogenesis KEGG term predicted in gene ontology analysis ( Fig. S1 ). DNA adduct formation and improper repair can lead to mutations that drive the development of cancer 42 , and defects in DNA repair pathways, such as mutations in BRCA1/2, are associated with increased cancer risk 43 . Additionally, GSH plays a protective role against DNA adduct formation by detoxifying harmful compounds and maintaining the redox environment necessary for proper DNA repair 44 . It is closely linked to both the prevention of DNA damage and the modulation of DNA repair mechanisms, making it a significant molecule in the context of genomic stability and cancer biology. The marked increase in γH2AX signifies substantial DNA damage, particularly in the form of double-strand breaks 45 . This observation is consistent with the elevated protein expression of p53 and cCASP-3 (Fig. 4 B), suggesting that the tissue underwent severe DNA damage, triggering p53-mediated apoptotic pathways. The reduction in pATR levels indicates that the cells may no longer be prioritizing DNA repair through ATR-mediated pathways 46 , and instead have shifted toward apoptosis (Fig. 4 B). As apoptosis progresses, the decrease in cPARP, despite being a marker of late-stage apoptosis, still coincides with the ongoing presence of γH2AX, suggesting continued DNA fragmentation, a hallmark of the final stages of apoptosis. The formation of additional colonic ILFs in IDH2 KO mice may indicate an enhanced chronic inflammation as they have been shown to expand in number and size during inflammatory conditions. The ILFs are known to contribute to tumorigenesis by providing a microenvironment conducive to cancer progression 47 . Along with this, the observed increase in γH2AX and PCNA levels in IDH2 KO mice also suggests that these ILFs might be responding to persistent DNA damage and cellular stress. This is consistent with the notion that chronic inflammation in the IDH2 KO mice, combined with ongoing DNA damage (as a result of PhIP exposure in our study), can promote colonic carcinogenesis 48 . Overall, as anticipated, our results show that IDH2 KO induces mitochondrial dysfunction, primarily by disrupting the redox balance, a well-documented outcome that we also observed in the present study 49 . While it was unclear whether PhIP would produce similar effects, our findings demonstrate that it does, likely through the inhibition of pathways such as 'Electron transport, ATP synthesis, and heat production by uncoupling proteins' and 'OXPHOS.' Mitochondrial dysfunction often leads to the overproduction of ROS, which can cause DNA damage, including double-strand breaks 50 . This, in turn, triggers the phosphorylation of H2AX, forming γH2AX, and initiating the DNA damage response 51 . Mitochondrial function is essential for maintaining cellular energy homeostasis, and widespread DNA damage, combined with inefficient repair mechanisms, can further impair mitochondrial function. This creates a vicious cycle in which damage to DNA exacerbates mitochondrial dysfunction, and mitochondrial dysfunction increases DNA damage 52 , 53 . Based on our comparative analysis, the observed mitochondrial dysfunction is likely the result of a combined effect of IDH2 KO and PhIP treatment. First, IDH2 deficiency leads to an overproduction of ROS, causing DNA damage. Second, PhIP exposure exacerbates this by inducing additional DNA damage, which contributes to further mitochondrial dysfunction. As we demonstrated, fructose suppressed IDH2 activity via SIRT3; this inhibition can lead to worsening oxidative stress and mitochondrial dysfunction; in our study, this notion was strengthened by the combination of IDH2 deficiency and PhIP exposure creating a compounded detrimental effect on mitochondrial function and DNA repair mechanisms, ultimately exacerbating cellular damages. Upstream analysis, one of the pathway prediction analyses, showed some interesting upstream regulators that also accounts for the phenotype and potential biofunctions. A total of 166 upstream regulators were predicted activated or inactivated in IDH2 KO + PhIP group compared to WT + PhIP group. We focused on the top 10 predicted activated and the other 10 predicted inhibited upstream regulators (Table 1 ). The top 10 predicted activated upstream regulators and their downstream targets were associated with several biological functions in organismal injury and abnormalities (i.e., ‘Tumorigenesis of tissue’, ‘Tumorigenesis of lymphocytes’, ‘Tumorigenesis of epithelial neoplasm’, Non-central nervous system malignant neoplasm’, and ‘Nonhematologic malignant neoplasm’; Fig. 5 C). Additionally, the top 10 predicted inhibited upstream regulator and their downstream targets were also associated with organismal injury and abnormalities (i.e., ‘Carcinoma’, ‘Intraabdominal organ tumor’, and ‘Non-central nervous system malignant neoplasm’; Fig. 5 D). These molecules can be categorized into immune and inflammatory responses, cell proliferation, tumor suppression and growth regulation, energy homeostasis, and RNA processing and gene regulation. Collectively, upstream analysis suggested that inflammatory and immune, cell proliferation and survival pathways were activated, likely due to IDH2 deletion and/or PhIP treatment. Simultaneously, the inhibition of tumor suppressors, metabolic regulators, and stress responses were inhibited. Such a profile could be seen in cancer, where cells hijack normal proliferative and survival pathways while suppressing controls that would otherwise limit growth 54 . The strong inflammatory signals could also point to a context where the immune system is heavily engaged, potentially working to combat an infection or responding to the tumor microenvironment 55 . Table 1 Top 10 upstream regulators predicted activated or inhibited by isocitrate dehydrogenase 2 (IDH2) deletion Molecules Z-score p-value Target molecules in DEG Predicted Activated (WT + PhIP vs IDH2 KO + PhIP) RICTOR 5.578 1.93E-18 ATP6V1G1, CD69, COX4I1, COX5A, COX6A1, Cox6c, COX7B, IFI16, IL1B, NDUFA5, NDUFB10, NDUFB2, NDUFB4, NDUFB5, NDUFB6, NDUFB9, NDUFC1, NDUFC2, Ndufs5, NDUFS6, NDUFV2, OAS2, PPA2, Rpl29 (includes others), RPL30, RPL41, RPLP2, RPS13, RPS24, Uba52, UQCR10, UQCR11, UQCRB, UQCRHL, UQCRQ CPT1B 4.081 5.4E-07 COX4I1, COX5A, Cox6c, COX7B, NDUFA5, NDUFB10, NDUFB2, NDUFB6, NDUFB9, NDUFC1, NDUFS6, NDUFV2, UQCR10, UQCR11, UQCRB, UQCRHL, UQCRQ TNF 3.948 0.000101 ABCC2, ACE, ADAM8, AGER, ANPEP, APOA1, APOBEC3B, AQP3, BBOX1, BCL2A1, BIRC3, C1QTNF4, CBR3, CCR6, CD69, CDX1, CNR2, COX4I1, CXCR4, CXCR5, CYP1A1, DIO1, DUSP2, ECH1, EGR2, FCER2, FGFRL1, FOSB, FPR1, FTH1, GBP4, GPR18, GSTP1, IDH2, IFI16, IL10RA, IL1B, IL1RL1, IL21R, IL4I1, INHBA, IRF5, KCNQ1OT1, LCP2, LY6D, LYZ, MEFV, MMP10, MMP12, MPC1, MT-CO3, MTTP, NLRP3, OAS2, PARP14, PTPRC, RGCC, RPS13, Slc5a4b, SOD2, ST8SIA4, STAT2, TLR9, TRPC6, TXN2, XDH IFNG 3.91 2.9E-08 ACE, AGER, AGPAT1, AIF1, BACH2, BATF, BCL2A1, BIRC3, C1QA, C1QB, CCR6, CD72, CDX1, CORO1A, COX4I1, CXCR4, DIABLO, DIO1, EGR2, FCER2, FCGR3A/FCGR3B, FGFRL1, FOSB, FTH1, GBP4, GLA, GPT, GSTP1, HAAO, HLA-DOB, IFI16, IFI44, Ighg2b, Ighg3, IGHM, IL10RA, IL1B, IL1RL1, IL4I1, INHBA, IRF5, KCNQ1OT1, LCP2, MEFV, MMP10, MMP12, NAPSA, NLRP3, OAS2, PARP14, PLA2G7, RGCC, SBNO2, Serpina3g (includes others), SIGLEC10, SLC28A2, SLFN12L, SOD2, SP110, SPRR1A, STAT2, TLR9, TMEM171 SPI1 3.506 3.35E-07 BTK, CCR6, CD19, CD72, CD79A, CD79B, COX4I1, CSF3R, CTSE, EGR2, FTH1, IFI44, IL1B, LILRB3, LYZ, MME, MS4A1, NDUFB11, PRDX5, PTPRC, SLC24A1, SP110 CLCF1 3.45 1.86E-09 CHCHD10, COX4I1, COX5A, MT-ATP6, MT-CO3, MT-ND3, NDUFB11, NDUFB9, NDUFC1, NDUFS6, TIMM10, UQCRQ NFKB1 3.443 0.00148 BATF, BCL2A1, BIRC3, BLK, CR2, CXCR5, FOSB, IFI16, IGHM, IL10RA, IL1B, MMP10, POU2F2, SOD2, TLR9 ZHX2 3.44 1.04E-09 COX5A, COX7B, NDUFAF5, NDUFB2, NDUFB6, NDUFB9, NDUFC1, NDUFS6, UQCR10, UQCR11, UQCRB, UQCRHL IL33 3.395 2.36E-10 ARHGAP30, ATXN1, BATF, BCL2A1, BIRC3, CD69, CD72, CLEC4A, CSF3R, DUSP2, EGR2, FAM162A, FGR, FPR1, IGHM, IKZF3, IL10RA, IL1B, IL1RL1, IL2RG, IL4I1, IRF5, MMP10, MMP12, NLRP3, NT5E, POU2F2, PTPRC, SOD2, UQCC2, UQCRQ KDM5A 3.357 3.97E-06 COX4I1, COX6A1, DUSP2, EXOSC4, GADD45GIP1, MCAT, MRPL11, MRPL12, MRPL17, MRPL55, NDUFA5, NDUFB10, SOD2, TXN2, UQCRQ Predicted inhibited (WT + PhIP vs IDH2 KO + PhIP) TEAD1 -4.796 1.17E-13 BBOX1, COX4I1, COX5A, Cox6c, COX7B, ECH1, ETFB, NDUFA12, NDUFA5, NDUFB10, NDUFB2, NDUFB4, NDUFB5, NDUFB6, NDUFC1, NDUFC2, Ndufs5, NDUFS6, NDUFV2, UQCR11, UQCRB, UQCRHL, UQCRQ DDX5 -3.845 7.07E-09 COX5A, COX7B, CXCR4, IL1B, NDUFA12, NDUFA5, NDUFB2, NDUFB4, NDUFB5, NDUFB6, NDUFS6, NFAT5, UQCR10, UQCRB, UQCRQ SIRT1 -3.825 3.57E-05 ABCC2, BIRC3, CD72, CD79B, CORO1A, COX4I1, CYP1A1, IDH2, IFI44, IGHM, Iglc3, IL1B, IL2RG, LRCH1, NDUFA5, NT5E, OAS2, PARP14, RNF213, SOD2, SP110, TBC1D10C, Trim30a/Trim30d CAB39L -3.742 2.82E-15 COX4I1, NDUFA12, NDUFB10, NDUFB11, NDUFB2, NDUFB5, NDUFB9, NDUFC1, NDUFS6, NDUFV2, UQCR10, UQCR11, UQCRB, UQCRQ PPARGC1A -3.619 1.05E-05 AGER, COX4I1, COX5A, COX7B, CYP1A1, DIO1, IL1B, INHBA, NCEH1, NDUFB4, NDUFB5, NDUFV2, NLRP3, PGAM1, PLA2G7, PRDX5, RECQL5, S100A1, SLC24A1, SLC25A39, SMC5, SOD2, TLR9, TXN2, XDH IRF2BP2 -3.582 1.16E-06 APOA1, BCL2A1, CD72, CLEC6A, FCGR3A/FCGR3B, IFI16, Ighg3, IGHM, IL2RG, LILRB3, LY6D, STAP1, Trim30a/Trim30d IGBP1 -3.573 1.05E-11 COX6A1, Cox6c, COX7B, NDUFA12, NDUFB10, NDUFB11, NDUFB2, NDUFB5, NDUFB6, NDUFB9, Ndufs5, UQCR11, UQCRQ CITED2 -3.208 9.02E-05 CD69, FCGR3A/FCGR3B, GBP4, IFI16, IFI44, IL1B, LCP2, LRCH1, PARP14, Serpina3g (includes others), SLC28A2, SLFN12L, TMEM171, Trim30a/Trim30d TFRC -3.207 3.73E-07 FTH1, MMP12, NDUFB10, NDUFB2, NDUFB4, NDUFB5, NDUFB6, NDUFB9, Ndufs5, NDUFS6, SPRR1A, UQCR11, UQCRHL, UQCRQ GFER -3.162 3.66E-10 CHCHD10, COX4I1, COX5A, COX6A1, NDUFB9, NDUFV2, UQCR10, UQCRB, UQCRHL, UQCRQ Abbreviations: DEG, differentially expressed genes; IDH2, isocitrate dehydrogenase 2; KO, knockout; PhIP, 2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine; WT, wild type In this study, we investigated the molecular mechanisms by which fructose contributes to PhIP-induced colon carcinogenesis, with a specific emphasis on the SIRT3-IDH2 axis. Our results show that fructose disrupts mitochondrial function and redox homeostasis by suppressing SIRT3, which normally deacetylates and activates IDH2. This suppression of SIRT3 leads to decreased NADPH production, weakening antioxidant defenses and increasing oxidative stress. Moreover, our experiments with IDH2 KO mice reveal that these mice exhibit heightened vulnerability to DNA damage and tumorigenesis when exposed to the dietary carcinogen PhIP, both in short- and long-term exposure models. These findings highlight the critical role of the SIRT3-IDH2 axis in preserving mitochondrial function and detoxification capacity, both of which are impaired by fructose consumption. The combined effects of fructose-induced oxidative stress and reduced detoxification likely play a central role in promoting colon carcinogenesis, especially in the presence of carcinogens like PhIP. Overall, these findings suggest that fructose-induced mitochondrial dysfunction through the SIRT3-IDH2 axis may significantly contribute to carcinogenesis, particularly under conditions of additional dietary carcinogen exposure. This study underscores the importance of further investigating how fructose modulates these pathways and highlights potential therapeutic targets to reduce the risks associated with high fructose intake, especially in relation to colon cancer." In the context of cancer, it is important to acknowledge that previous studies have reported carcinogenic effects of IDH2, which seem contradictory to our findings. However, those studies primarily focused on xenograft or IDH2 mutation models, rather than examining the role of IDH2 in the initiation stage of cancer 56 – 58 . In contrast, our study provides novel evidence that IDH2 deficiency (i.e., KO) may promote cancer initiation from a different perspective. In carcinogen-free IDH2 KO mice, we observed a significant upregulation of genes involved in DNA damage and repair signaling in colon tissue. Furthermore, multi-omics datasets mutually indicated enhanced carcinogenesis-associated signaling pathways and upstream molecules in these mice. Collectively, our findings suggest that IDH2 may play a protective role during the early stages of cancer development, offering a fresh perspective for cancer research. This opens new opportunities for investigating the role of wild-type IDH2 in the initiation of cancer, a topic that has not been explored previously. One of major challenges encountered in this study is that effects of fructose on PhIP-induced colon carcinogenesis were not directly examined. Despite the lack of a specific experiment, multiple previous reports used different models strongly suggest that fructose amplify carcinogenesis 59 , 60 . Nevertheless, our study also presents important benefits as multiple omics datasets from three sets of animal experiments including KO mice model were comprehensively analyzed and validated, which provides valuable evidence for different perspectives on wild-type IDH2 in the initiation of cancer, and a strong foundation for future research in various fields such as cancer research. This study highlights the critical role of the SIRT3-IDH2 axis in the context of chemical-induced colon carcinogenesis. Using unbiased multi-omics approaches as well as unique models (e.g., SIRT3 and IDH2 KO models), we demonstrated that fructose suppresses SIRT3 expression and IDH2 activity, leading to impaired mitochondrial detoxification, increased oxidative stress, and a weakened DNA damage response. These effects, in turn, exacerbate DNA damage and promote tumorigenesis, particularly in the absence of IDH2. By unraveling the mechanistic link between fructose-induced mitochondrial dysfunction and colon carcinogenesis, our findings emphasize the importance of the SIRT3-IDH2 axis in maintaining cellular redox homeostasis and genomic integrity. This study provides a strong foundation for targeting this pathway as a therapeutic strategy to mitigate the carcinogenic effects of dietary fructose and related environmental factors. Declarations Acknowledgements This research was supported by the Basic Science Research Program through the National Research Foundation of Korea, funded by the Ministry of Education (RS-2023-00245564); the Ministry of Food and Drug Safety of South Korea (RS-2024-00332492); and the BK21 Fostering Outstanding Universities for Research (FOUR) program. Author Contributions Conceptualization: JKK; Methodology: NAB, JHL, JKK; Validation: HRS, KCC, JHL, JKK; Formal analysis: JHP, KJK, BK; Investigation: JHP, KJK, HRS; Resources: NAB, BK, JKK; Data curation: BK, JKK; Writing – Original Draft: JHP, JKK; Writing – Review & Editing: NAB, HRS, KCC, JHL; Visualization: JHP, KJK; Supervision: JKK Competing interest The authors declare no competing financial interests. Additional information Supplementary information accompanies the manuscript on the Experimental & Molecular Medicine` website (http://www.nature.com/emm/). The following file formats are included: Supplementary Figures (.pdf) and Supplementary table (.docx) Correspondence and requests for materials should be addressed to Jae Kyeom Kim. Reprints and permission information is available at http://www.nature.com/ reprints References USDA. USDA ERS - Sugar and Sweeteners Yearbook Tables. 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A KEGG pathway ‘Chemical Carcinogenesis – DNA adduct’ enriched liver tissues from mice fed fructose water, which was retrieved from transcriptome for KEGG pathway terms. Abbreviations: KEGG, Kyoto Encyclopedia of Genes and Genomes Figure S2. Canonical Pathway: Mitochondrial dysfunction. Colonic transcriptomics suggests that IDH2 KO-induced mitochondrial dysfunction is linked to the suppression of Complex IV and V in comparison to WT mice. Blue/red indicate observed inhibition/activation, while green/orange represent predicted inhibition/activation. Abbreviations: IDH2, isocitrate dehydrogenase 2; KO, knockout; WT, wild type Figure S3. Canonical Pathway: Mitochondrial dysfunction. Colonic transcriptomics reveals that 2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine (PhIP)-mediated mitochondrial dysfunction is linked to the suppression of Complex I and IV in WT mice. Blue/red indicate observed inhibition/activation, while green/orange represent predicted inhibition/activation. Abbreviations: IDH2, isocitrate dehydrogenase 2; KO, knockout; PhIP, 2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine; WT, wild type Figure S4. Canonical Pathway: Mitochondrial dysfunction. Colonic transcriptomics suggests that IDH2 KO exacerbates PhIP-mediated mitochondrial dysfunction via overall suppression of the electron transport chain. Blue/red indicate observed inhibition/activation, while green/orange represent predicted inhibition/activation. Abbreviations: IDH2, isocitrate dehydrogenase 2; KO, knockout; PhIP, 2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine Figure S5. Canonical Pathway: Mitochondrial dysfunction. Colonic transcriptomics suggests that PhIP treatment in IDH2 KO mice did not significantly alter mitochondrial dysfunction in the colon compared to IDH2 KO mice alone. Red indicates observed inhibition/activation, while green represents predicted inhibition. Abbreviations: IDH2, isocitrate dehydrogenase 2; KO, knockout; PhIP, 2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine Figure S6. Plasma metabolomics revealed that isocitrate dehydrogenase 2 (IDH2) knockout (KO) may induce reductive TCA cycle. Key metabolites of the TCA cycle in plasma of mice to validate IDH2 KO-mediated metabolic shift. Data are present as mean ± standard error of the mean (n=6 per group). A p-value of 0.05 or less was considered statistically significant; *p<0.05. Abbreviations: IDH2, isocitrate dehydrogenase 2; KO, knockout; WT, wild type SupplementalFigwithlegendandTable.pdf Supplemental Figures and Table Cite Share Download PDF Status: Published Journal Publication published 13 Nov, 2025 Read the published version in Experimental & Molecular Medicine → Version 1 posted Editorial decision: revise 21 Apr, 2025 Review # 2 received at journal 20 Apr, 2025 Review # 1 received at journal 16 Apr, 2025 Reviewer # 2 agreed at journal 02 Apr, 2025 Reviewer # 1 agreed at journal 02 Apr, 2025 Reviewers invited by journal 02 Apr, 2025 Submission checks completed at journal 18 Mar, 2025 First submitted to journal 18 Mar, 2025 Unknown event 17 Mar, 2025 Editor assigned by journal 14 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6226269","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":437250853,"identity":"76d4bc74-28fa-4198-bcac-480c5b54561f","order_by":0,"name":"Jae Kyeom Kim","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsklEQVRIiWNgGAWjYBACxh42hgMMFQyMDexAHg/xWs4AtTATq4WBhw2or40ULcw9xxIP3Zx3WLafmYHxwds2YhzW23bgcO62w8YzmxmYDecSpaWfvQGkJXHDYQY2aV7itcw5nLj/MAP7b+K0gB3WALSFmYGNmTgtPccSDuccSzeecZixWXLOOSK0GPakGX/OqbGW7W9vPvjhTRkxWhoQFjbgVIUC5IlTNgpGwSgYBSMaAACfWDmXr3CkGgAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-2837-9302","institution":"School of Human Environmental Sciences, University of Arkansas, Fayetteville, AR, 72701, United States","correspondingAuthor":true,"prefix":"","firstName":"Jae","middleName":"Kyeom","lastName":"Kim","suffix":""},{"id":437250854,"identity":"109f856f-3523-402a-b2e7-5d3471213b19","order_by":1,"name":"Jeong Hoon Pan","email":"","orcid":"","institution":"Chosun University","correspondingAuthor":false,"prefix":"","firstName":"Jeong","middleName":"Hoon","lastName":"Pan","suffix":""},{"id":437250855,"identity":"7e308916-2696-44e7-82b7-3a9c4a79ec25","order_by":2,"name":"Aykin-Burns Nukhet","email":"","orcid":"","institution":"University of Arkansas","correspondingAuthor":false,"prefix":"","firstName":"Aykin-Burns","middleName":"","lastName":"Nukhet","suffix":""},{"id":437250856,"identity":"c8f903f1-b80d-492b-96c9-446b9a287962","order_by":3,"name":"Kimberly J. Krager","email":"","orcid":"","institution":"University of Arkansas","correspondingAuthor":false,"prefix":"","firstName":"Kimberly","middleName":"J.","lastName":"Krager","suffix":""},{"id":437250857,"identity":"d613684e-c505-44da-b4a3-29979f20b62a","order_by":4,"name":"Hyo Ri Shin","email":"","orcid":"","institution":"Korea University","correspondingAuthor":false,"prefix":"","firstName":"Hyo","middleName":"Ri","lastName":"Shin","suffix":""},{"id":437250858,"identity":"62145092-78a8-4277-bbae-010052c5205f","order_by":5,"name":"Kyung-Chul Choi","email":"","orcid":"","institution":"University of Ulsan College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Kyung-Chul","middleName":"","lastName":"Choi","suffix":""},{"id":437250859,"identity":"c36f7ae2-4cc0-4100-ba54-829b01f48299","order_by":6,"name":"Jin Hyup Lee","email":"","orcid":"","institution":"Department of Food and Biotechnology, Korea University","correspondingAuthor":false,"prefix":"","firstName":"Jin","middleName":"Hyup","lastName":"Lee","suffix":""},{"id":437250860,"identity":"696dc2db-a9f3-4ff7-83df-8339d3742eef","order_by":7,"name":"Byungwhi Kong","email":"","orcid":"","institution":"U.S. Department of Agriculture","correspondingAuthor":false,"prefix":"","firstName":"Byungwhi","middleName":"","lastName":"Kong","suffix":""}],"badges":[],"createdAt":"2025-03-14 12:25:59","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6226269/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6226269/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s12276-025-01584-0","type":"published","date":"2025-11-13T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":81144145,"identity":"7bf1333f-9fd0-47be-80d9-5ae862934d72","added_by":"auto","created_at":"2025-04-22 17:32:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1566585,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFructose suppresses hepatic Aryl Hydrocarbon Receptor (AhR) signaling pathway.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Changes in AhR-associated genes, Phase I/II detoxification enzymes, sirtuin 3 (SIRT3), and isocitrate dehydrogenase 2 (IDH2) expression in the liver transcriptome analysis of metabolic dysfunction-associated steatotic liver disease (MASLD) and cirrhosis patients. (B) Comparison analysis of three hepatic transcriptome datasets with different fructose doses. (C) Time course effect of fructose on \u003cem\u003eCyp1a2\u003c/em\u003e and \u003cem\u003eUgt1a1\u003c/em\u003emRNA expression in liver tissues of mice fed fructose 34% fructose water for 2 and 4 weeks. (D) In vitro tests to examine ROS producing effect of fructose and (E) to validate ROS-mediated AhR suppression using alpha mouse liver (AML)12 hepatocytes. Data are present as mean ± standard error of the mean (n=6 per group). A p-value of 0.05 or less was considered statistically significant; *p\u0026lt;0.05, ***p\u0026lt;0.001, ****p\u0026lt;0.0001.\u003c/p\u003e\n\u003cp\u003eAbbreviations: AhR, aryl hydrocarbon receptor; AML, alpha mouse liver; CON, control; FRU, fructose; IDH2, isocitrate dehydrogenase 2; MASH-cirrhosis, metabolic dysfunction-associated steatohepatitis cirrhosis; MASLD, metabolic dysfunction-associated steatotic liver disease; ROS, reactive oxygen species; RQ, relative quantity; SIRT3, sirtuin 3\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-6226269/v1/3e2d794c9c0f8886fe851d73.png"},{"id":81144147,"identity":"a1be7173-940d-4e42-9526-523cece8d594","added_by":"auto","created_at":"2025-04-22 17:32:51","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":322242,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFructose inhibits activities of both mitochondrial sirtuin 3 (SIRT3) and isocitrate dehydrogenase 2 (IDH2).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A and B) Predicted top canonical pathways enriched in hepatic transcriptome and proteome in response to fructose water (i.e., Sirtuin Signaling Pathway). (C) Decrease in IDH2 activity and (D) dimerization by SIRT3 deletion in hepatocytes. Data are present as mean ± standard error of the mean (n=6 per group). A p-value of 0.05 or less was considered statistically significant; *p\u0026lt;0.05\u003c/p\u003e\n\u003cp\u003eAbbreviations: IDH2, isocitrate dehydrogenase 2; KO, knockout; SIRT3, sirtuin 3; WT, wild type\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6226269/v1/03cbedbe38fe6bafbf0a9d51.jpg"},{"id":81144162,"identity":"97a2b458-f6df-4b8f-b748-f0ce423dd7ab","added_by":"auto","created_at":"2025-04-22 17:32:52","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":260650,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIsocitrate dehydrogenase 2 (IDH2) knockout (KO) exacerbates expressions of colonic DNA damage/repair genes in response to short-term 2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine (PhIP) exposure.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Heatmap analysis of 86 genes associated with DNA damage/repair signaling in WT, WT+PhIP, IDH2 KO, and IDH2 KO+PhIP groups. (B) mRNA expressions for categorized molecules involved in different DNA damage/repair signaling; Ataxia telangiectasia mutated (ATM)/Ataxia telangiectasia and Rad3 related (ATR) signaling, Double strand breaks (DSB) signaling, Nucleotide excision repair (NER)/Base excision repair (BER) signaling, Apoptosis/Cell cycle signaling, and others. Data are present as mean ± standard error of the mean. Different letters indicate statistically different between groups (n=6 per group). A p-value of 0.05 or less was considered statistically significant.\u003c/p\u003e\n\u003cp\u003eAbbreviations: ATM, Ataxia telangiectasia mutated; ATR, Ataxia telangiectasia and Rad3 related; BER, base excision repair; DSB, double strand break; KO, knockout; IDH2, isocitrate dehydrogenase 2; NER, nucleotide excision repair; PhIP, 2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine; WT, wild type\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6226269/v1/00e2f7874a92695e074f7d5a.jpg"},{"id":81144148,"identity":"52cdd6a1-5e8c-492d-9a86-789a1194be46","added_by":"auto","created_at":"2025-04-22 17:32:52","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":320399,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIsocitrate dehydrogenase 2 (IDH2) knockout (KO) promotes colonic DNA damage and isolated lymphoid follicles (ILF) formation in response to short- and long-term 2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine (PhIP) exposure.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Representative images and quantification of gamma phosphorylated histone H2AX (γH2AX) immunofluorescence in colon tissue sections from mice short-term exposed to PhIP. (B) Representative bands and quantification of DNA damage-related protein expressions in colon tissues from mice short-term exposed to PhIP. (C) Macroscopic image of colonic ILF and their quantification, and (D) identification of the ILF using hematoxylin \u0026amp; eosin (H\u0026amp;E) staining and immunofluorescence of cluster of differentiation 3 (CD3) and proliferating cell nuclear antigen (PCNA) from mice long-term exposed to PhIP/dextran sulfate sodium (DSS). (E) Representative bands and quantification for γH2AX and PCNA protein expressions in colon tissues from mice exposed to long-term PhIP/DSS. Data are present as mean ± standard error of the mean. * indicates statistical differences between groups (n=10 per group). A p-value of 0.05 or less was considered statistically significant.\u003c/p\u003e\n\u003cp\u003eAbbreviations: CD3, cluster of differentiation 3; cCASP-3, cleaved caspase 3; cPARP, cleaved poly(ADP-ribose) polymerase; DSS, dextran sulfate sodium; γH2AX, gamma phosphorylated histone H2AX; H\u0026amp;E, hematoxylin \u0026amp; eosin; IDH2, isocitrate dehydrogenase 2; ILF, isolated lymphoid follicles; KO, knockout; pATR: phosphorylated Ataxia Telangiectasia and Rad3 related protein; PCNA, proliferating cell nuclear antigen; PhIP, 2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine; p53, tumor protein p53; RQ, relative quantity; WT, wild type\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6226269/v1/1c1f6d89d9fcd5c259f1b1fe.jpg"},{"id":81144155,"identity":"3873a7d1-8f01-4fe1-b833-2147685f1be5","added_by":"auto","created_at":"2025-04-22 17:32:52","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":411254,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eColonic transcriptomics reveals that isocitrate dehydrogenase 2 (IDH2) knockout (KO) affects several organismal injury and abnormalities related diseases and biological functions.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Partial least squares discriminant analysis (PLS-DA) plot for wild type (WT) control (WTC; Grey color), WT+2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine (PhIP) (WTP; Blue color), IDH2 KO control (KOC; Orange color), and IDH2 KO+PhIP (KOP; Green color) groups long-term exposed to PhIP/dextran sulfate sodium (DSS). (B) Comparison analysis of four groups, WTC, WTP, KOC, and KOP for top 10 canonical pathways of colonic transcriptome. (C) Top 10 predicted activated and (D) top 10 predicted inhibited upstream regulators, and their association networks with diseases and biological functions.\u003c/p\u003e\n\u003cp\u003eAbbreviations: DSS, dextran sulfate sodium; IDH2, isocitrate dehydrogenase 2; KO, knockout; KOC, IDH2 knockout control; KOP, IDH2 knockout + PhIP; PhIP, 2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine; PLS-DA, partial least squares discriminant analysis; WT, wild type; WTC, wild type control; WTP, wild type + PhIP\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6226269/v1/5a908a2d6ab02f983b18a4d7.jpg"},{"id":81144149,"identity":"232d89b2-20b8-4c37-b7db-2f0a46b0f648","added_by":"auto","created_at":"2025-04-22 17:32:52","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":226996,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eColonic transcriptomics reveals that isocitrate dehydrogenase 2 (IDH2) knockout (KO) suppressed glutathione (GSH)-mediated detoxification pathway while PhIP activates it.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNetworks for GSH-mediated detoxification pathway (A) with IDH2 or (B) without IDH2 gene. (C) A merged network of upstream regulators linked to GSH-mediated detoxification pathway.\u003c/p\u003e\n\u003cp\u003eAbbreviations: GSH, glutathione; IDH2, isocitrate dehydrogenase 2; KO, knockout; PhIP, 2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6226269/v1/c566caf6dcad456b06403e8b.jpg"},{"id":81144714,"identity":"58b80056-bdf3-4af4-86a4-7744fcecee45","added_by":"auto","created_at":"2025-04-22 17:40:52","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":210305,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFructose-mediated inhibition of sirtuin 3 (SIRT3)-isocitrate dehydrogenase 2 (IDH2) axis depletes glutathione (GSH) in hepatocytes.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Suppression of SIRT3 protein expression in response to fructose treatment in hepatocytes. (B) Inhibition of mitochondrial IDH2 activity with (C) unchanged cytosolic isocitrate dehydrogenase 1 (IDH1) activity by fructose treatment in hepatocytes. (D) Increase in acetylation of IDH2 in response to fructose treatment in hepatocytes. (E) Unchanged IDH2 protein expression by fructose treatment in hepatocytes. Fructose-induced (F) GSH depletion by measuring a ratio of oxidized GSH (GSSG) and GSH and (G) nicotinamide adenine dinucleotide phosphate (NADPH) depletion measured by a ratio of NADPH and oxidized NADPH (NADP+). (H) Unchanged glutathione reductase (GR) activity by fructose treatment in hepatocytes. Data are present as mean ± standard error of the mean. * indicates statistically differences between groups (n=3-6 per group). A p-value of 0.05 or less was considered statistically significant; *p\u0026lt;0.05, **p\u0026lt;0.01.\u003c/p\u003e\n\u003cp\u003eAbbreviations: GSH, glutathione; GSSG, oxidized glutathione; GR, glutathione reductase; IDH1, isocitrate dehydrogenase 1; IDH2, isocitrate dehydrogenase 2; NADP+, oxidized nicotinamide adenine dinucleotide phosphate; NADPH, nicotinamide adenine dinucleotide phosphate; SIRT3, sirtuin 3.\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6226269/v1/07f312268f457fe09725f2a3.jpg"},{"id":96885654,"identity":"6a997877-fc84-4f82-91f5-77a0ac808106","added_by":"auto","created_at":"2025-11-27 08:09:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5141745,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6226269/v1/7b274a2b-5ad7-4ac3-a13a-88d08606914c.pdf"},{"id":81144160,"identity":"5e099f01-1545-49d3-a0a9-64dfcc3724c9","added_by":"auto","created_at":"2025-04-22 17:32:52","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16234,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary figure legends\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure S1. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway: Chemical Carcinogenesis – DNA adducts.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA KEGG pathway ‘Chemical Carcinogenesis – DNA adduct’ enriched liver tissues from mice fed fructose water, which was retrieved from transcriptome for KEGG pathway terms.\u003c/p\u003e\n\u003cp\u003eAbbreviations: KEGG, Kyoto Encyclopedia of Genes and Genomes\u003c/p\u003e","description":"","filename":"TableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6226269/v1/e43243477df0ac3965dd0cba.docx"},{"id":81144152,"identity":"30ffd264-c56e-4f37-a35e-292a07fcdf20","added_by":"auto","created_at":"2025-04-22 17:32:52","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":3278913,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary figure legends\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure S1. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway: Chemical Carcinogenesis – DNA adducts.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA KEGG pathway ‘Chemical Carcinogenesis – DNA adduct’ enriched liver tissues from mice fed fructose water, which was retrieved from transcriptome for KEGG pathway terms.\u003c/p\u003e\n\u003cp\u003eAbbreviations: KEGG, Kyoto Encyclopedia of Genes and Genomes\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure S2. Canonical Pathway: Mitochondrial dysfunction.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eColonic transcriptomics suggests that IDH2 KO-induced mitochondrial dysfunction is linked to the suppression of Complex IV and V in comparison to WT mice. Blue/red indicate observed inhibition/activation, while green/orange represent predicted inhibition/activation.\u003c/p\u003e\n\u003cp\u003eAbbreviations: IDH2, isocitrate dehydrogenase 2; KO, knockout; WT, wild type\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure S3. Canonical Pathway: Mitochondrial dysfunction.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eColonic transcriptomics reveals that 2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine (PhIP)-mediated mitochondrial dysfunction is linked to the suppression of Complex I and IV in WT mice. Blue/red indicate observed inhibition/activation, while green/orange represent predicted inhibition/activation.\u003c/p\u003e\n\u003cp\u003eAbbreviations: IDH2, isocitrate dehydrogenase 2; KO, knockout; PhIP, 2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine; WT, wild type\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure S4. Canonical Pathway: Mitochondrial dysfunction.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eColonic transcriptomics suggests that IDH2 KO exacerbates PhIP-mediated mitochondrial dysfunction via overall suppression of the electron transport chain. Blue/red indicate observed inhibition/activation, while green/orange represent predicted inhibition/activation.\u003c/p\u003e\n\u003cp\u003eAbbreviations: IDH2, isocitrate dehydrogenase 2; KO, knockout; PhIP, 2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure S5. Canonical Pathway: Mitochondrial dysfunction.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eColonic transcriptomics suggests that PhIP treatment in IDH2 KO mice did not significantly alter mitochondrial dysfunction in the colon compared to IDH2 KO mice alone. Red indicates observed inhibition/activation, while green represents predicted inhibition.\u003c/p\u003e\n\u003cp\u003eAbbreviations: IDH2, isocitrate dehydrogenase 2; KO, knockout; PhIP, 2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure S6. Plasma metabolomics revealed that isocitrate dehydrogenase 2 (IDH2) knockout (KO) may induce reductive TCA cycle.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKey metabolites of the TCA cycle in plasma of mice to validate IDH2 KO-mediated metabolic shift. Data are present as mean ± standard error of the mean (n=6 per group). A p-value of 0.05 or less was considered statistically significant; *p\u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003eAbbreviations: IDH2, isocitrate dehydrogenase 2; KO, knockout; WT, wild type\u003c/p\u003e","description":"","filename":"SupplementalFigwithlegend.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6226269/v1/de7e27f7fef1b8e9df238df8.pdf"},{"id":81144717,"identity":"3bb6bcb7-39d7-4169-89e3-34fc267fd39f","added_by":"auto","created_at":"2025-04-22 17:40:52","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":3284609,"visible":true,"origin":"","legend":"Supplemental Figures and Table","description":"","filename":"SupplementalFigwithlegendandTable.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6226269/v1/45a144dbde0295bb6fed7542.pdf"}],"financialInterests":"There is no conflict of interest","formattedTitle":"SIRT3-IDH2 axis is a target of dietary fructose: implication of IDH2 as a key player in dietary carcinogen toxicity in mice colon","fulltext":[{"header":"Introduction","content":"\u003cp\u003eFructose-containing sweeteners are widely used (e.g., beverages) and represent\u0026thinsp;\u0026asymp;\u0026thinsp;30% of total sweeteners consumed in the US\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. While fructose's role in metabolic syndromes has been studied, conflicting results exist, particularly in studies tied to food industry funding [e.g., reviewed in \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e]. Recent epidemiological evidence links fructose intake to carcinogenesis, showing that consuming more than two servings of sweetened beverages daily increases early-onset colon cancer risk by 2.2-fold\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Animal studies also indicate that high fructose intake promotes colonic neoplastic lesions\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e and enhances tumor progression through lipid metabolism dysregulation, independent of metabolic syndrome\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe association between fructose and colon cancer has been demonstrated in multiple epidemiological studies\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Likewise, a recent epidemiological study estimated that more than 2 servings of sweetened beverages per day increase the risk of early onset of colon cancer by 2.2-fold\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. In an early mouse study, a single high dose of fructose (10 g/kg bw) increased a chemical-induced colonic neoplastic lesion marker (i.e., aberrant crypt foci), compared to glucose\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Similarly, a recent study showed that a modest amount of high fructose corn syrup promoted colon tumor size/grade through dysregulation of lipid metabolism in the absence of metabolic syndrome\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e; however, limitations to extrapolating to \u0026lsquo;healthy\u0026rsquo; humans are 1) the study utilized an adenomatous polyposis coli mutant mouse model that is predisposed to intestinal adenoma formation, and 2) the animals were exposed to fructose \u0026lsquo;after\u0026rsquo; tamoxifen injection to initiate carcinogenesis\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe mechanisms thought to play a role in the effects of fructose in colon cancer include increased reactive oxygen species (ROS), chronic inflammation\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, and the production of advanced glycation end-products (which promote carcinogenesis)\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Furthermore, our previous work has shown that fructose suppressed hepatic Aryl Hydrocarbon Receptor (AhR) signaling, whereas glucose did not, indicating specific implications of fructose for carcinogen metabolism\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Although the above studies underscore the importance of individual dietary factors, it is unknown how red meat and fructose, which are commonly consumed together, contribute jointly to colon cancer.\u003c/p\u003e \u003cp\u003eUnderstanding the mechanistic link between fructose and colon cancer is critical, as it could reveal new insights into the potential carcinogenic effects of high fructose intake and inform strategies for mitigating the risks associated with excessive fructose consumption. In the present study, we utilized unbiased multi-omics techniques in conjunction with comprehensive bioinformatics analyses to find key molecular interactions responsible for the initiation of colon cancer. Specifically, liver tissues of fructose-fed mice were subjected to transcriptomics and proteomics to find potential key genes that may play crucial roles in carcinogenesis. After, the target gene [i.e., mitochondrial NADP\u003csup\u003e+\u003c/sup\u003e-dependent isocitrate dehydrogenase (IDH2)] was deleted in mice that were subsequently treated with a dietary carcinogen [i.e., 2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine (PhIP)] to validate predictions in transcriptomics and proteomics. Subsequently, colonic transcriptomics was carried out to analyze how IDH2 gene is interlinked with colonic carcinogenesis. Overall, herein, the use of a multi-omics approach allows us to capture the complexity of these molecular interactions, providing a more holistic view of how dietary risk factors (namely, fructose and PhIP) can contribute to carcinogenesis.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAnimals experiment I: Ad libitum fructose intake study\u003c/h2\u003e \u003cp\u003eA total of 21 four-week-old male and female C57BL/6N mice (Central Lab Animal Inc; Seoul, Republic of Korea) were randomly divided into control (CON; drinking water; 4 males and 6 females) and fructose (FRU; 34% fructose water; 5 males and 6 females). After one week of acclimation, the mice were housed separately by sex under controlled temperature (23\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C), humidity (50\u0026thinsp;\u0026plusmn;\u0026thinsp;5%), and 12/12 h light-dark cycles in the Korea University Animal Facility. Animal handling and experimental protocols were approved by the Ethical Committee of Korea University (Protocol Number: KUIACUC-2018-77).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAnimals experiment II: Time course effect of fructose on AhR\u003c/h3\u003e\n\u003cp\u003eA total of 28 four-week-old male C57BL/6N mice (Central Lab Animal Inc) were randomly assigned to the following experimental groups: 2 week-Control (5 males), 2 week-34% fructose (5 males), 4 week-Control (5 males), and 4 week-34% fructose (5 males). After a week of acclimation to AIN-93G diet, 8 mice were euthanized at the beginning of fructose intervention as a baseline group. Another 20 mice were euthanized in the second (2 wk) and fourth weeks (4 wk). Other experimental conditions including housing, diet, anesthesia, and tissue collections were identical to the experiment I-1.\u003c/p\u003e\n\u003ch3\u003eAnimals experiments III and IV: Short-/long-term PhIP-induced models\u003c/h3\u003e\n\u003cp\u003eIDH2 knockout (IDH2 KO) mice and their littermate wild-type (WT) mice were maintained under the same housing conditions as described in the Animal experiment I. All animal handling and experiments were performed in accordance with a protocol approved by the Institutional Animal Care and Use Committee of the University of Delaware (IACUC protocol approval number: 1354-2020-A). For a short-term study, a total of 20 mice were randomly assigned to four experimental groups: WT control group, WT\u0026thinsp;+\u0026thinsp;PhIP group, IDH2 KO control group, and IDH2 KO\u0026thinsp;+\u0026thinsp;PhIP group. After acclimation, the PhIP groups received an intraperitoneal injection of PhIP (10 mg/kg of body weight, dissolved in corn oil; Toronto Research Chemicals; North York, ON, Canada). The injection volume of PhIP did not exceed 100 \u0026micro;L and was calculated based on body weight. The control group mice were treated with corn oil only (10 mL/kg of body weight). Twenty-four hours after the PhIP injection, the mice were euthanized by exposure to CO\u003csub\u003e2\u003c/sub\u003e gas, followed by cardiac puncture.\u003c/p\u003e \u003cp\u003eFor the long-term study, similarly to the short-term study, 60 mice were randomly divided into four groups. After the acclimation period, 100 mg/kg body weight of PhIP was orally administrated to mice in PhIP groups twice at three-day intervals. Four days after the second PhIP administration, 2.5% dextran sulfate sodium (DSS) \u0026mdash;commonly used in colorectal cancer studies for its relevance to clinical features\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e\u0026mdash; was added to drinking water for four days, followed by seven weeks of observation period. Finally, all mice were euthanized by exposure to CO\u003csub\u003e2\u003c/sub\u003e gas. Daily food intake was measured, and behavioral activity was monitored to assess animal health and well-being after PhIP or PhIP/DSS treatment. Harvested tissues were stored at -80\u0026deg;C in the RNALater solution or fixed with 10% neutral buffered formalin solution for further analyses.\u003c/p\u003e\n\u003ch3\u003eCell culture validation\u003c/h3\u003e\n\u003cp\u003eMouse hepatocyte (AML12; American Type Culture Collection; Manassa, VA, USA) was cultured in Dulbecco's Modified Eagle's Medium (also known as DMEM)/F12 media supplemented with 10% fetal bovine serum, 40 ng/mL dexamethasone, and Insulin-Transferrin-Selenium-G Supplement (Invitrogen; Carlsbad, CA, USA). Cells were incubated at 37\u0026ordm;C with 5% CO\u003csub\u003e2\u003c/sub\u003e and water saturation. Cells were treated with 5 mM fructose for 24 hours, and then cells were harvested for further analyses.\u003c/p\u003e\n\u003ch3\u003eRNA extraction and mRNA expression analysis\u003c/h3\u003e\n\u003cp\u003eTissue or cellular RNAs were isolated using the RNeasy Plus Universal Mini Kit (Qiagen; Hilden, Germany) as described elsewhere\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. For 84 mRNAs related to DNA damage/repair, RT\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Profiler PCR Array (Qiagen) was used.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eTranscriptomics\u003c/h2\u003e \u003cp\u003eTotal RNA isolated from liver and colon tissues was used for RNA sequencing. Transcriptomic analysis was performed on hepatic samples (n\u0026thinsp;=\u0026thinsp;5 per group; 2 males and 3 females) and colonic samples (n\u0026thinsp;=\u0026thinsp;6 per group; 3 males and 3 females) using a 1 \u0026times; 50 bp single-end read on an Illumina HiSeq system (Illumina Inc; San Diego, CA, USA), as described previously \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. The total mapped counts were log2-transformed based on the reads per million to stabilize the variance. The normalized values were then further processed to identify differentially expressed genes (DEGs).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSecondary analysis of human liver transcriptome datasets\u003c/h3\u003e\n\u003cp\u003eThe potential disruption of AhR signaling and the SIRT3-IDH2 axis was investigated in the context of xenobiotic detoxification. While our animal and cellular experiments focus on fructose-induced effects, we sought to determine whether similar molecular alterations occur in human liver disease by analyzing publicly available transcriptomic data. To support our hypothesis that fructose impairs AhR-mediated detoxification and suppresses the SIRT3-IDH2 axis, we first conducted a secondary analysis of human liver transcriptomic data (GSE256398). This analysis aims to contextualize our experimental results within human pathology, highlighting the potential implications of fructose-induced metabolic dysfunction in disease progression. Additionally, this human data will serve as the foundation for further validation in our animal and cellular experiments.\u003c/p\u003e\n\u003ch3\u003eProteomics\u003c/h3\u003e\n\u003cp\u003eProtein fractions were isolated from harvested liver tissues obtained from Animal experiment I. The isolated proteins were reduced, alkylated, and digested using filter-aided sample preparation, as previously described \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. The eluted peptides were ionized via electrospray (2.15 kV) and subjected to mass spectrometric analysis using an Orbitrap Fusion Tribrid mass spectrometer (Thermo-Fisher Scientific) with multi-notch MS3 parameters, as described \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Data were acquired in top-speed profile mode with a resolution of 240,000, covering a range of 375 to 1500 m/z. Following collision-induced dissociation (normalized collision energy of 35), MS/MS data were acquired using the ion trap analyzer in centroid mode, ranging from 400\u0026ndash;2000 m/z. Up to 10 MS/MS precursors were selected for higher energy collision dissociation (normalized collision energy of 65.0), followed by MS3 reporter ion data acquisition in profile mode with a resolution of 30,000 over a range of 100\u0026ndash;500 m/z.\u003c/p\u003e \u003cp\u003eProteins were identified, and reporter ions were quantified using MaxQuant software (Max Planck Institute; Munich, Germany) with a parent ion tolerance of 3 ppm, fragment ion tolerance of 0.5 Da, and reporter ion tolerance of 0.03 Da. Protein identifications were accepted with a false discovery rate (FDR) below 1% and at least two identified peptides. Results were compiled using the Scaffold program (Proteome Software; Portland, OR, USA). The detected protein data were log2-transformed, and the normalized values were used to create a short list. Proteins with a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and a fold change\u0026thinsp;\u0026gt;\u0026thinsp;1.5 were considered significantly different, resulting in 179 differentially expressed proteins (DEPs), which were further analyzed using Ingenuity Pathway Analysis (IPA; Qiagen).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eWestern blot\u003c/h2\u003e \u003cp\u003eProtein expression was analyzed using western blotting as we described elsewhere \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Each membrane included a reference sample, which was used across all blots. The final results were calculated by determining the ratio of the target protein to β-actin and normalizing it by dividing this ratio by the reference sample/β-actin ratio to account for inter-assay variation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eImmunoprecipitation of IDH2\u003c/h2\u003e \u003cp\u003eImmunoprecipitation for acetylated IDH2 was carried out using magnetic beads. Crude protein extracts from hepatocytes treated with either distilled water or 5 mM fructose were incubated with anti-acetyl-IDH2 antibody bound to the magnetic beads. Eluted antigens (i.e., acetyl-IDH2 proteins) were utilized for western blot analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePathophysiological analyses\u003c/h2\u003e \u003cp\u003eColon tissues fixed in 10% neutral buffered formalin in phosphate-buffered saline (PBS) (wt:vol), followed by dehydration with 30% sucrose solution were cut open and laid flat in between two cover slides. The slide sandwiches were frozen on dry ice. For embedding, Tissue-Tek Optimal Cutting Temperature (OCT) compound (Sakura Finetek; Torrance, CA, USA) was added to a plastic mold to make an OCT block with a flat surface. The OCT block was attached to a cryo-chuck in a cryostat. Colon tissues in the slide sandwich were transferred to the flat side of the OCT block with the mucosal surface facing up. The mucosal surface was covered with a generous amount of OCT compound. The embedded colon tissues were cut into 5 \u0026micro;m sections and stained with hematoxylin and eosin staining for morphological observation. Stained tissue sections were examined using a 5\u0026times; objective on a Leica DM 500 microscope equipped with a Leica ICC50E (Leica Camera Inc; Wetzlar, Germany). The use of the low magnification (5\u0026times;) was to capture a large area of the section.\u003c/p\u003e \u003cp\u003eFor immunofluorescence analyses, \u003cem\u003een face\u003c/em\u003e colon sections embedded in OCT blocks were incubated with specific primary antibodies overnight at 4\u0026deg;C, followed by washing cycles with PBS. Subsequently, tissue sections were incubated with fluorophores-conjugated secondary antibody for 1 hour at room temperature. The tissue sections were counterstained with 4, 6-diamidino-2-phenylindole, and sealed with cover glass. Obtained images were analyzed using a confocal microscope (Zeiss LSM880, Carl Zeiss AG; Baden-Wurttemberg, Germany).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eEnzyme activity assays\u003c/h2\u003e \u003cp\u003eFor IDH2 activity, mitochondria of hepatocytes were isolated using a Mitochondrial Isolation Kit for Cultured Cells (Thermo Scientific) according to instructions of the manufacturer. IDH2 activity was measured using IDH Activity Assay Kit (Sigma-Aldrich; St-Louis, MO, USA) according to instructions of the manufacturer. Glutathione Reductase Assay kit (Sigma-Aldrich) was also used to measure hepatic glutathione reductase activity in response to fructose treatment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eGSSG/GSH and NADPH/NADP assays\u003c/h2\u003e \u003cp\u003eRatios for GSSG/GSH and NADPH/NADP\u003csup\u003e+\u003c/sup\u003e were measured using GSH/GSSG Ratio Detection Assay Kit and NADP\u003csup\u003e+\u003c/sup\u003e/NADPH Assay kit (Abcam; Cambridge, UK).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eBioinformatics and statistical analyses\u003c/h2\u003e \u003cp\u003eAs for secondary analyses to compare a dose-dependent effects of fructose intake on hepatic carcinogen metabolism, NCBI Gene Expression Omnibus DataSets was utilized to retrieve related transcriptomics datasets. GSE92502 and GSE51885 met our search criteria (i.e., fructose-fed C57BL/6 mice, lower or higher fructose dose than our study); thus, DEGs were acquired via differential gene expression analysis. Each DEG was subjected to the IPA pathway analysis, followed by comparison analysis of the three datasets.\u003c/p\u003e \u003cp\u003ePartial least squares-discriminant analysis (PLS-DA) was performed on the colonic transcriptomics dataset prior to differential gene expression analysis. PLS-DA is a supervised classification method that extends the PLS algorithm to identify latent variables that explain the most variance in both predictors and response variables. The visualization for PLS-DA was conducted using the R software package version 4.4.1 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.r-project.org\" target=\"_blank\"\u003ewww.r-project.org\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.r-project.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur DEGs and DEPs were analyzed using multiple bioinformatics tools as follows. First, the gene ontology analysis was performed using the DAVID tool. Specifically, DEGs from the hepatic transcriptome were analyzed with the DAVID tool to identify enriched terms for Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Additionally, DEGs were subjected to analysis using the IPA software (Qiagen), where the Core Analysis feature of the software was performed to predict related pathways, including canonical pathway analysis and upstream regulator analysis.\u003c/p\u003e \u003cp\u003eFor all other markers, data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error of the mean (SEM). We assessed whether the data followed a normal distribution using the Shapiro-Wilk test. When the data did not fit a normal distribution, the Mann-Whitney test was applied. Comparisons between two groups were analyzed using an unpaired t-test, while data involving two independent variables, and one dependent variable were first analyzed using two-way ANOVA followed by Tukey\u0026rsquo;s multiple comparison. In cases where a significant interaction effect was not observed, a One-way ANOVA was conducted, followed by Fisher\u0026rsquo;s LSD test. A p-value of 0.05 or less was considered statistically significant and GraphPad Prism (Ver. 7.00) was used for the analyses (GraphPad Software; San Diego, CA, USA).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eFructose-associated suppression of AhR signaling and SIRT3-IDH2 axis in human liver disease\u003c/h2\u003e \u003cp\u003eIn our analysis of human liver transcriptomic data, we observed a significant downregulation of AhR-associated genes in metabolic dysfunction-associated steatotic liver disease (MASLD) and cirrhosis patients compared to healthy controls, particularly those involved in xenobiotic metabolism, including Phase I (CYP1A1, CYP1A2) and Phase II (UGT1A1, UGT1A3, UGT2B4, GSTA1, GSTA2, GSTM3, GSTZ1) detoxification enzymes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). The suppression of these genes suggests a progressive decline in hepatic detoxification capacity, potentially increasing susceptibility to carcinogen accumulation. Additionally, we observed a trend of decrease in SIRT3 (p\u0026thinsp;=\u0026thinsp;0.06) and IDH2 (p\u0026thinsp;=\u0026thinsp;0.05) expression in MASLD and fibrosis, with the most pronounced reduction in cirrhosis patients.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eFructose suppresses the xenobiotic AhR signaling pathway via ROS production\u003c/h2\u003e \u003cp\u003ePreviously, we showed that 34% fructose intake suppresses the AhR signaling pathway in the liver \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. The AhR signaling pathway is a key pathway that governs genes [e.g., cytochrome P450 (CYPs)] related to carcinogen metabolism in the liver\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Interestingly, we found that \u0026lsquo;Chemical carcinogenesis \u0026ndash; DNA adduct\u0026rsquo; KEGG pathway is predicted enriched in the FRU group, which includes PhIP-DNA adduct-mediated colon cancer (\u003cb\u003eFig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e). The prediction is likely due to changes in CYPs by fructose intake as highlighted as key genes of the pathway. As we previously reported, a few key genes governed by the AhR signaling pathway were downregulated including CYPs\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn order to further explore a dose-dependent implications of fructose intake on hepatic carcinogen metabolism, our transcriptomics dataset (34% fructose) was compared to two different publicly available RNA sequencing datasets that were treated with lower (20%; GSE92502) or higher (60%; GSE51885) fructose levels than our condition. In this secondary analysis, \u0026lsquo;Aryl Hydrocarbon Receptor Signaling Pathway\u0026rsquo; and \u0026lsquo;Xenobiotic Metabolism Signaling Pathway\u0026rsquo; were dose-dependently enriched (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). In a follow-up validation study, we noted that \u003cem\u003eCyp1a2\u003c/em\u003e and \u003cem\u003eUgt1a1\u003c/em\u003e mRNA expressions were decreased in fructose-fed mice liver tissues; there was a stronger statistical significance when mice were fed fructose for longer periods (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Given that fructose is a known ROS inducer and an interaction between ROS and AhR is well established, the suppression of AhR genes is likely related to fructose-induced oxidative stress under our conditions. Confirming the previous studies as well as our speculation, the FRU group presented significantly increased hydrogen peroxide level (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD); related, mRNAs for AhR-signaling related genes (i.e., \u003cem\u003eAhr\u003c/em\u003e, \u003cem\u003eArnt\u003c/em\u003e, and \u003cem\u003eCyp1a2\u003c/em\u003e) were decreased in response to oxidative stress induced by hydrogen peroxide in AML12 hepatocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eFructose-induced mitochondrial dysfunction is associated with SIRT3-IDH2 axis\u003c/h2\u003e \u003cp\u003eIn our hepatic transcriptomics and proteomics datasets, \u0026lsquo;Sirtuin Signaling Pathway\u0026rsquo; and \u0026lsquo;Mitochondrial Dysfunction\u0026rsquo; were predicted the most enriched canonical signaling pathways in fructose-fed mice, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Sirtuins (SIRTs) are a family of proteins that include several sub-forms, such as SIRT1, SIRT3, and SIRT5, each of which plays distinct roles in cellular processes. Among these, SIRT3 is primarily localized in the mitochondria and is well known to regulate mitochondrial function by deacetylating enzymes involved in energy metabolism, such as IDH2. The SIRT3 plays a critical role in maintaining mitochondrial integrity and protecting against oxidative stress, particularly by regulating mitochondrial dynamics, metabolic syndromes, and ROS production.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eInterestingly, according to our transcriptomics dataset, mitochondrial SIRT3 was predicted decreased in FRU-fed mice, leading to a suppression of IDH2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). As aforementioned, the SIRT3 is a mitochondrial NAD\u003csup\u003e+\u003c/sup\u003e-dependent deacetylase that directly deacetylates IDH2, which enhances the enzymatic activity of IDH2, thereby increasing its capacity to produce NADPH\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Therefore, we explored changes in IDH2 activity in response to SIRT3 KO to elaborate the mitochondrial SIRT3-IDH2 axis. As hypothesized, IDH2 activity and dimerization of IDH2 were significantly decreased in SIRT3 KO mice, showing a direct regulatory mechanism of IDH2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eC \u003cb\u003eand D\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eIDH2 deficient mice are more sensitive to DNA damage response from short-term and long-term exposures to a dietary carcinogen\u003c/em\u003e \u003c/p\u003e \u003cp\u003eOnce we confirmed the implications of fructose intake on IDH2 (via SIRT3), we further aimed to validate the predicted the KEGG pathway, \u0026lsquo;Chemical Carcinogenesis \u0026ndash; DNA adduct\u0026rsquo;. Of the four aromatic amines/amides included in the KEGG pathway [namely, 4-aminobiphenyl, PhIP, 2-amino-3-methylimidazo[4,5-f]quinoline (IQ in \u003cb\u003eFig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e), and 2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline (MeIQx in \u003cb\u003eSupplementary Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e)], involved in the pathway, we chose PhIP-induced colon cancer model for the validation as it is the most mass abundant carcinogen present in well-done meats\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. PhIP can be detoxified via GSTs-mediated conjugation of GSH in the liver, hence GSH is known to be protective against the production of DNA adduct and possibly colon carcinogenesis\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Expected, depletion of hepatic GSH is a hallmark of IDH2 deficiency\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, which led us to explore an implication of IDH2 in PhIP toxicity.\u003c/p\u003e \u003cp\u003eIn this study, we comprehensively assessed 86 genes involved in DNA damage signaling pathways using the R\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Profiler qPCR assay in both WT and IDH2 KO mice following 24-hour exposure to PhIP. A heatmap highlighted several key genes related to DNA damage signaling that were significantly impacted by PhIP treatment in the colon of WT mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Additionally, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eB shows 28 genes with statistically significant differences across the experimental groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). IDH2 deficiency in the colon led to the upregulation of several mRNAs, though the effects were not as pronounced as those induced by PhIP exposure alone. Interestingly, in the IDH2 KO mice, some mRNA levels (e.g., \u003cem\u003eAtr\u003c/em\u003e, \u003cem\u003eAtrx\u003c/em\u003e, and \u003cem\u003eBrca2\u003c/em\u003e) were further elevated following PhIP treatment compared to the WT\u0026thinsp;+\u0026thinsp;PhIP group. However, the majority of mRNA levels tended to decrease in the IDH2 KO\u0026thinsp;+\u0026thinsp;PhIP group relative to the WT\u0026thinsp;+\u0026thinsp;PhIP group. These findings suggest potential interactions between PhIP exposure and IDH2 deficiency, with complex effects on DNA damage signaling pathways.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFollowing, it was further demonstrated that IDH2 KO mice exhibited significantly higher levels of colonic γH2AX, p53, and cCASP-3 compared to their WT littermates 24 hours after PhIP exposure (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eA \u003cb\u003eand B\u003c/b\u003e). Notably, while PhIP treatment activated pATR and cPARP in WT mice, PhIP exposure in the IDH2 KO mice led to the suppression of these proteins.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo confirm the implications of IDH2 deficiency in PhIP-induced toxicity from the short-term PhIP-induced model, we examined the effects of long-term PhIP exposure (8 weeks) in IDH2 KO mice; the mice were euthanized 7 weeks after receiving a 1-week PhIP/DSS treatment. Interestingly, the IDH2 KO mice developed more colonic isolated lymphoid follicles (ILFs), as identified by CD3 expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eC \u003cb\u003eand D\u003c/b\u003e). Furthermore, higher expression levels of γH2AX and PCNA proteins were observed in the IDH2 KO mice compared to WT littermates (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eE), aligning with the results of the short-term PhIP exposure study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eIDH2 KO exacerbates PhIP-induced colonic damages via multiple networks\u003c/h2\u003e \u003cp\u003eOur findings clearly indicate that IDH2 KO exacerbates PhIP-induced colonic DNA damage and possibly promotes colon carcinogenesis. However, deletion of a certain gene results in multifaceted effects in general; thus, colonic transcriptomics of WT, WT\u0026thinsp;+\u0026thinsp;PhIP, IDH2 KO, and IDH2 KO\u0026thinsp;+\u0026thinsp;PhIP group was carried out to reveal mechanistic potentials of IDH2 KO. The transcriptomics dataset was applied to PLS-DA, a supervised classification method extending the PLS algorithm to determine axes, which explains the most variance in both predictors and the response variables (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). As shown IDH2 KO\u0026thinsp;+\u0026thinsp;PhIP (Green in the figure) group seems well-separated and -clustered in the tilted 3D plot, particularly from the IDH2 KO group (Orange in the figure). After, the DEGs, retrieved from the colonic transcriptomics dataset, were utilized for pathway prediction analyses using the IPA software. Based on a comparison analysis of the four groups, mitochondrial function related pathways are important to note (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Both IDH2 deletion and PhIP affect mitochondrial dysfunction, leading to exacerbated dysfunction of mitochondria in IDH2 KO\u0026thinsp;+\u0026thinsp;PhIP group. Here, the complex content is systematically deconstructed and explained in each comparison for clarity and understanding. When WT and IDH2 KO groups were compared (see red and green colors as they are actual increased or decreased genes in DEGs, respectively, and orange and blue colors are predictions), IDH2 KO-mediated mitochondrial dysfunction might be more focused on the Complex IV and V (\u003cb\u003eFig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e\u003c/b\u003e), but PhIP is likely to affect Complex I and IV seen in the comparison between WT and WT\u0026thinsp;+\u0026thinsp;PhIP (\u003cb\u003eFig. S3\u003c/b\u003e). These effects may lead to the overall suppression of the electron transport chain when IDH2 KO and PhIP are applied together (\u003cb\u003eFig. S4\u003c/b\u003e). Interestingly, PhIP treatment in IDH2 KO mice appeared not to be effective on mitochondrial dysfunction compared to IDH2 KO mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). This cannot be clearly addressed in the present study. However, it is possible that PhIP might have triggered a compensatory response aimed at maintaining cellular energy and survival under stress conditions resulting from PhIP treatment. In fact, our data somehow support the hypothesis. Specifically, a reason for that activation status of mitochondrial dysfunction in the comparison between IDH2 KO and IDH2 KO\u0026thinsp;+\u0026thinsp;PhIP was due to that recovery of multiple genes in the complexes which resulting in less significance (\u003cb\u003eFig. S5\u003c/b\u003e). Other mitochondrial pathways [i.e., \u0026lsquo;Electron transport, ATP synthesis, and heat production by uncoupling proteins\u0026rsquo;, and \u0026lsquo;Oxidative Phosphorylation (OXPHOS)\u0026rsquo;] were not significantly affected by IDH2 KO, but they were aggravated when PhIP was treated to IDH2 KO mice. We speculate that the mitochondrial dysfunction caused by IDH2 KO might be from other signaling pathways. In fact, some canonical pathways altered by IDH2 KO were related to mitochondrial dysfunction although they were not highlighted. For instance, \u0026lsquo;TCA cycle and respiratory electron transport\u0026rsquo; and \u0026lsquo;Glucose metabolism\u0026rsquo; were predicted inhibited in IDH2 KO mice, which are crucial pathways for ATP production (\u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e). Previous report supports the speculation as IDH2 deficiency led to depletion of ATP in different cells \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs we mentioned earlier in this study, GSH plays crucial role in PhIP detoxification, and IDH2 is highly associated with GSH recycling via producing NADPH \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Importantly, GSH-mediated detoxification pathway was predicted inhibited by IDH2 KO (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e6\u003c/span\u003eA), while PhIP activated it (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). Moreover, several upstream regulator molecules were associated with the pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). Inhibition of GSH in IDH2 KO group was reasonable to expect given that knock out of IDH2 induces reductive TCA cycle \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Our study also confirmed that IDH2 deletion resulted in a shift of oxidative TCA cycle to reductive evidenced by higher plasma levels of citrate, aconitate, and isocitrate and lower level of α-ketoglutarate in IDH2 KO mice (\u003cb\u003eFig. S6\u003c/b\u003e). However, GSH-mediated detoxification mainly occurs in the liver tissue, and suppression of hepatic GSH is well-known event in response to fructose intake \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Related, we speculated that fructose-induced GSH depletion could be due to the suppression of SIRT3-IDH2 axis, leading us to execute validation in vitro studies using hepatocytes.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs expected, fructose treatment led to a reduction in SIRT3 protein expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e7\u003c/span\u003eA) and a corresponding decrease in IDH2 enzyme activity in mouse hepatocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e7\u003c/span\u003eB), while IDH1 activity remained unaffected (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e7\u003c/span\u003eC). This indicates that fructose specifically impacts the SIRT3-IDH2 axis. Supporting this, fructose treatment increased the acetylation of IDH2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e7\u003c/span\u003eD), despite no changes in IDH2 protein levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e7\u003c/span\u003eE), further confirming that fructose acts through SIRT3-mediated deacetylation rather than altering IDH2 expression per se. Additionally, fructose treatment reduced intracellular levels of NADPH and GSH (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e7\u003c/span\u003eF \u003cb\u003eand G\u003c/b\u003e), key molecules involved in antioxidant defense, yet had minimal impact on NADPH-consuming glutathione reductase activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e7\u003c/span\u003eH). This suggests that the depletion of GSH is more likely due to impaired NADPH production via the SIRT3-IDH2 axis rather than increased consumption. Taken together, these findings strongly indicate that fructose-induced hepatic GSH depletion is closely linked to the inhibition of the SIRT3-IDH2 pathway.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eAhR is activated by binding to ligands such as environmental pollutants including polycyclic aromatic hydrocarbons \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Upon ligand binding, AhR translocates to the nucleus, where it dimerizes with the AhR nuclear translocator (also known as ARNT) and binds to xenobiotic response elements in the DNA, initiating transcription of target genes \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Activation of AhR by environmental toxins can lead to the production of ROS, either directly or through the induction of enzymes (e.g., CYPs), which metabolize xenobiotics and generate ROS as by-products \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. The suppression of AhR in the FRU group could be a negative feedback loop of AhR; fructose-induced oxidative stress may create feedback mechanisms that inhibit AhR signaling. For instance, oxidative stress-induced transcription factors could upregulate inhibitors of AhR (e.g., \u003cem\u003eNcor\u003c/em\u003e) as evidenced in our previous report \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSIRT3 activates several mitochondrial enzymes [e.g., superoxide dismutase 2 and IDH2 \u003csup\u003e36\u003c/sup\u003e]. By deacetylating and activating these enzymes, SIRT3 enhances the ability of cells to neutralize ROS, thereby reducing oxidative stress \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. In SIRT3-deficient cells or organisms, the lack of deacetylation leads to impaired IDH2 activity, which in turn decreases NADPH being necessary for the reduction of GSH \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. This not only results in an increase in ROS levels, but also suppresses the efficiency of detoxification of xenobiotics via GSH, which contributes to various pathologies, including aging-related diseases \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e, and cancers \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Based on the overall findings, it was reasonable to hypothesize that fructose-induced suppression of the SIRT3-IDH2 axis could have affected the enrichment of the chemical carcinogenesis KEGG term predicted in gene ontology analysis (\u003cb\u003eFig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eDNA adduct formation and improper repair can lead to mutations that drive the development of cancer \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e, and defects in DNA repair pathways, such as mutations in BRCA1/2, are associated with increased cancer risk \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Additionally, GSH plays a protective role against DNA adduct formation by detoxifying harmful compounds and maintaining the redox environment necessary for proper DNA repair \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. It is closely linked to both the prevention of DNA damage and the modulation of DNA repair mechanisms, making it a significant molecule in the context of genomic stability and cancer biology.\u003c/p\u003e \u003cp\u003eThe marked increase in γH2AX signifies substantial DNA damage, particularly in the form of double-strand breaks \u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. This observation is consistent with the elevated protein expression of p53 and cCASP-3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eB), suggesting that the tissue underwent severe DNA damage, triggering p53-mediated apoptotic pathways. The reduction in pATR levels indicates that the cells may no longer be prioritizing DNA repair through ATR-mediated pathways \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e, and instead have shifted toward apoptosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). As apoptosis progresses, the decrease in cPARP, despite being a marker of late-stage apoptosis, still coincides with the ongoing presence of γH2AX, suggesting continued DNA fragmentation, a hallmark of the final stages of apoptosis.\u003c/p\u003e \u003cp\u003eThe formation of additional colonic ILFs in IDH2 KO mice may indicate an enhanced chronic inflammation as they have been shown to expand in number and size during inflammatory conditions. The ILFs are known to contribute to tumorigenesis by providing a microenvironment conducive to cancer progression \u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Along with this, the observed increase in γH2AX and PCNA levels in IDH2 KO mice also suggests that these ILFs might be responding to persistent DNA damage and cellular stress. This is consistent with the notion that chronic inflammation in the IDH2 KO mice, combined with ongoing DNA damage (as a result of PhIP exposure in our study), can promote colonic carcinogenesis \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOverall, as anticipated, our results show that IDH2 KO induces mitochondrial dysfunction, primarily by disrupting the redox balance, a well-documented outcome that we also observed in the present study \u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. While it was unclear whether PhIP would produce similar effects, our findings demonstrate that it does, likely through the inhibition of pathways such as 'Electron transport, ATP synthesis, and heat production by uncoupling proteins' and 'OXPHOS.' Mitochondrial dysfunction often leads to the overproduction of ROS, which can cause DNA damage, including double-strand breaks \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. This, in turn, triggers the phosphorylation of H2AX, forming γH2AX, and initiating the DNA damage response \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMitochondrial function is essential for maintaining cellular energy homeostasis, and widespread DNA damage, combined with inefficient repair mechanisms, can further impair mitochondrial function. This creates a vicious cycle in which damage to DNA exacerbates mitochondrial dysfunction, and mitochondrial dysfunction increases DNA damage \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e,\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. Based on our comparative analysis, the observed mitochondrial dysfunction is likely the result of a combined effect of IDH2 KO and PhIP treatment. First, IDH2 deficiency leads to an overproduction of ROS, causing DNA damage. Second, PhIP exposure exacerbates this by inducing additional DNA damage, which contributes to further mitochondrial dysfunction. As we demonstrated, fructose suppressed IDH2 activity via SIRT3; this inhibition can lead to worsening oxidative stress and mitochondrial dysfunction; in our study, this notion was strengthened by the combination of IDH2 deficiency and PhIP exposure creating a compounded detrimental effect on mitochondrial function and DNA repair mechanisms, ultimately exacerbating cellular damages.\u003c/p\u003e \u003cp\u003eUpstream analysis, one of the pathway prediction analyses, showed some interesting upstream regulators that also accounts for the phenotype and potential biofunctions. A total of 166 upstream regulators were predicted activated or inactivated in IDH2 KO\u0026thinsp;+\u0026thinsp;PhIP group compared to WT\u0026thinsp;+\u0026thinsp;PhIP group. We focused on the top 10 predicted activated and the other 10 predicted inhibited upstream regulators (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The top 10 predicted activated upstream regulators and their downstream targets were associated with several biological functions in organismal injury and abnormalities (i.e., \u0026lsquo;Tumorigenesis of tissue\u0026rsquo;, \u0026lsquo;Tumorigenesis of lymphocytes\u0026rsquo;, \u0026lsquo;Tumorigenesis of epithelial neoplasm\u0026rsquo;, Non-central nervous system malignant neoplasm\u0026rsquo;, and \u0026lsquo;Nonhematologic malignant neoplasm\u0026rsquo;; Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). Additionally, the top 10 predicted inhibited upstream regulator and their downstream targets were also associated with organismal injury and abnormalities (i.e., \u0026lsquo;Carcinoma\u0026rsquo;, \u0026lsquo;Intraabdominal organ tumor\u0026rsquo;, and \u0026lsquo;Non-central nervous system malignant neoplasm\u0026rsquo;; Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). These molecules can be categorized into immune and inflammatory responses, cell proliferation, tumor suppression and growth regulation, energy homeostasis, and RNA processing and gene regulation. Collectively, upstream analysis suggested that inflammatory and immune, cell proliferation and survival pathways were activated, likely due to IDH2 deletion and/or PhIP treatment. Simultaneously, the inhibition of tumor suppressors, metabolic regulators, and stress responses were inhibited. Such a profile could be seen in cancer, where cells hijack normal proliferative and survival pathways while suppressing controls that would otherwise limit growth \u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. The strong inflammatory signals could also point to a context where the immune system is heavily engaged, potentially working to combat an infection or responding to the tumor microenvironment \u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop 10 upstream regulators predicted activated or inhibited by isocitrate dehydrogenase 2 (IDH2) deletion\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMolecules\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eZ-score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTarget molecules in DEG\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePredicted Activated (WT\u0026thinsp;+\u0026thinsp;PhIP vs IDH2 KO\u0026thinsp;+\u0026thinsp;PhIP)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRICTOR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.578\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.93E-18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATP6V1G1, CD69, COX4I1, COX5A, COX6A1, Cox6c, COX7B, IFI16, IL1B, NDUFA5, NDUFB10, NDUFB2, NDUFB4, NDUFB5, NDUFB6, NDUFB9, NDUFC1, NDUFC2, Ndufs5, NDUFS6, NDUFV2, OAS2, PPA2, Rpl29 (includes others), RPL30, RPL41, RPLP2, RPS13, RPS24, Uba52, UQCR10, UQCR11, UQCRB, UQCRHL, UQCRQ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCPT1B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.4E-07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCOX4I1, COX5A, Cox6c, COX7B, NDUFA5, NDUFB10, NDUFB2, NDUFB6, NDUFB9, NDUFC1, NDUFS6, NDUFV2, UQCR10, UQCR11, UQCRB, UQCRHL, UQCRQ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.948\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eABCC2, ACE, ADAM8, AGER, ANPEP, APOA1, APOBEC3B, AQP3, BBOX1, BCL2A1, BIRC3, C1QTNF4, CBR3, CCR6, CD69, CDX1, CNR2, COX4I1, CXCR4, CXCR5, CYP1A1, DIO1, DUSP2, ECH1, EGR2, FCER2, FGFRL1, FOSB, FPR1, FTH1, GBP4, GPR18, GSTP1, IDH2, IFI16, IL10RA, IL1B, IL1RL1, IL21R, IL4I1, INHBA, IRF5, KCNQ1OT1, LCP2, LY6D, LYZ, MEFV, MMP10, MMP12, MPC1, MT-CO3, MTTP, NLRP3, OAS2, PARP14, PTPRC, RGCC, RPS13, Slc5a4b, SOD2, ST8SIA4, STAT2, TLR9, TRPC6, TXN2, XDH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIFNG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.9E-08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eACE, AGER, AGPAT1, AIF1, BACH2, BATF, BCL2A1, BIRC3, C1QA, C1QB, CCR6, CD72, CDX1, CORO1A, COX4I1, CXCR4, DIABLO, DIO1, EGR2, FCER2, FCGR3A/FCGR3B, FGFRL1, FOSB, FTH1, GBP4, GLA, GPT, GSTP1, HAAO, HLA-DOB, IFI16, IFI44, Ighg2b, Ighg3, IGHM, IL10RA, IL1B, IL1RL1, IL4I1, INHBA, IRF5, KCNQ1OT1, LCP2, MEFV, MMP10, MMP12, NAPSA, NLRP3, OAS2, PARP14, PLA2G7, RGCC, SBNO2, Serpina3g (includes others), SIGLEC10, SLC28A2, SLFN12L, SOD2, SP110, SPRR1A, STAT2, TLR9, TMEM171\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSPI1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.35E-07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBTK, CCR6, CD19, CD72, CD79A, CD79B, COX4I1, CSF3R, CTSE, EGR2, FTH1, IFI44, IL1B, LILRB3, LYZ, MME, MS4A1, NDUFB11, PRDX5, PTPRC, SLC24A1, SP110\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCLCF1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.86E-09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCHCHD10, COX4I1, COX5A, MT-ATP6, MT-CO3, MT-ND3, NDUFB11, NDUFB9, NDUFC1, NDUFS6, TIMM10, UQCRQ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNFKB1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBATF, BCL2A1, BIRC3, BLK, CR2, CXCR5, FOSB, IFI16, IGHM, IL10RA, IL1B, MMP10, POU2F2, SOD2, TLR9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZHX2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.04E-09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCOX5A, COX7B, NDUFAF5, NDUFB2, NDUFB6, NDUFB9, NDUFC1, NDUFS6, UQCR10, UQCR11, UQCRB, UQCRHL\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.36E-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eARHGAP30, ATXN1, BATF, BCL2A1, BIRC3, CD69, CD72, CLEC4A, CSF3R, DUSP2, EGR2, FAM162A, FGR, FPR1, IGHM, IKZF3, IL10RA, IL1B, IL1RL1, IL2RG, IL4I1, IRF5, MMP10, MMP12, NLRP3, NT5E, POU2F2, PTPRC, SOD2, UQCC2, UQCRQ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKDM5A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.97E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCOX4I1, COX6A1, DUSP2, EXOSC4, GADD45GIP1, MCAT, MRPL11, MRPL12, MRPL17, MRPL55, NDUFA5, NDUFB10, SOD2, TXN2, UQCRQ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePredicted inhibited (WT\u0026thinsp;+\u0026thinsp;PhIP vs IDH2 KO\u0026thinsp;+\u0026thinsp;PhIP)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTEAD1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-4.796\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.17E-13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBBOX1, COX4I1, COX5A, Cox6c, COX7B, ECH1, ETFB, NDUFA12, NDUFA5, NDUFB10, NDUFB2, NDUFB4, NDUFB5, NDUFB6, NDUFC1, NDUFC2, Ndufs5, NDUFS6, NDUFV2, UQCR11, UQCRB, UQCRHL, UQCRQ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDDX5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3.845\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.07E-09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCOX5A, COX7B, CXCR4, IL1B, NDUFA12, NDUFA5, NDUFB2, NDUFB4, NDUFB5, NDUFB6, NDUFS6, NFAT5, UQCR10, UQCRB, UQCRQ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSIRT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3.825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.57E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eABCC2, BIRC3, CD72, CD79B, CORO1A, COX4I1, CYP1A1, IDH2, IFI44, IGHM, Iglc3, IL1B, IL2RG, LRCH1, NDUFA5, NT5E, OAS2, PARP14, RNF213, SOD2, SP110, TBC1D10C, Trim30a/Trim30d\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCAB39L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3.742\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.82E-15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCOX4I1, NDUFA12, NDUFB10, NDUFB11, NDUFB2, NDUFB5, NDUFB9, NDUFC1, NDUFS6, NDUFV2, UQCR10, UQCR11, UQCRB, UQCRQ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePPARGC1A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3.619\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.05E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAGER, COX4I1, COX5A, COX7B, CYP1A1, DIO1, IL1B, INHBA, NCEH1, NDUFB4, NDUFB5, NDUFV2, NLRP3, PGAM1, PLA2G7, PRDX5, RECQL5, S100A1, SLC24A1, SLC25A39, SMC5, SOD2, TLR9, TXN2, XDH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIRF2BP2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3.582\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.16E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAPOA1, BCL2A1, CD72, CLEC6A, FCGR3A/FCGR3B, IFI16, Ighg3, IGHM, IL2RG, LILRB3, LY6D, STAP1, Trim30a/Trim30d\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIGBP1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3.573\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.05E-11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCOX6A1, Cox6c, COX7B, NDUFA12, NDUFB10, NDUFB11, NDUFB2, NDUFB5, NDUFB6, NDUFB9, Ndufs5, UQCR11, UQCRQ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCITED2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3.208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.02E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCD69, FCGR3A/FCGR3B, GBP4, IFI16, IFI44, IL1B, LCP2, LRCH1, PARP14, Serpina3g (includes others), SLC28A2, SLFN12L, TMEM171, Trim30a/Trim30d\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTFRC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3.207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.73E-07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFTH1, MMP12, NDUFB10, NDUFB2, NDUFB4, NDUFB5, NDUFB6, NDUFB9, Ndufs5, NDUFS6, SPRR1A, UQCR11, UQCRHL, UQCRQ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGFER\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3.162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.66E-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCHCHD10, COX4I1, COX5A, COX6A1, NDUFB9, NDUFV2, UQCR10, UQCRB, UQCRHL, UQCRQ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eAbbreviations: DEG, differentially expressed genes; IDH2, isocitrate dehydrogenase 2; KO, knockout; PhIP, 2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine; WT, wild type\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn this study, we investigated the molecular mechanisms by which fructose contributes to PhIP-induced colon carcinogenesis, with a specific emphasis on the SIRT3-IDH2 axis. Our results show that fructose disrupts mitochondrial function and redox homeostasis by suppressing SIRT3, which normally deacetylates and activates IDH2. This suppression of SIRT3 leads to decreased NADPH production, weakening antioxidant defenses and increasing oxidative stress. Moreover, our experiments with IDH2 KO mice reveal that these mice exhibit heightened vulnerability to DNA damage and tumorigenesis when exposed to the dietary carcinogen PhIP, both in short- and long-term exposure models. These findings highlight the critical role of the SIRT3-IDH2 axis in preserving mitochondrial function and detoxification capacity, both of which are impaired by fructose consumption. The combined effects of fructose-induced oxidative stress and reduced detoxification likely play a central role in promoting colon carcinogenesis, especially in the presence of carcinogens like PhIP. Overall, these findings suggest that fructose-induced mitochondrial dysfunction through the SIRT3-IDH2 axis may significantly contribute to carcinogenesis, particularly under conditions of additional dietary carcinogen exposure. This study underscores the importance of further investigating how fructose modulates these pathways and highlights potential therapeutic targets to reduce the risks associated with high fructose intake, especially in relation to colon cancer.\"\u003c/p\u003e \u003cp\u003eIn the context of cancer, it is important to acknowledge that previous studies have reported carcinogenic effects of IDH2, which seem contradictory to our findings. However, those studies primarily focused on xenograft or IDH2 mutation models, rather than examining the role of IDH2 in the initiation stage of cancer \u003csup\u003e\u003cspan additionalcitationids=\"CR57\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. In contrast, our study provides novel evidence that IDH2 deficiency (i.e., KO) may promote cancer initiation from a different perspective. In carcinogen-free IDH2 KO mice, we observed a significant upregulation of genes involved in DNA damage and repair signaling in colon tissue. Furthermore, multi-omics datasets mutually indicated enhanced carcinogenesis-associated signaling pathways and upstream molecules in these mice. Collectively, our findings suggest that IDH2 may play a protective role during the early stages of cancer development, offering a fresh perspective for cancer research. This opens new opportunities for investigating the role of wild-type IDH2 in the initiation of cancer, a topic that has not been explored previously.\u003c/p\u003e \u003cp\u003eOne of major challenges encountered in this study is that effects of fructose on PhIP-induced colon carcinogenesis were not directly examined. Despite the lack of a specific experiment, multiple previous reports used different models strongly suggest that fructose amplify carcinogenesis \u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e,\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. Nevertheless, our study also presents important benefits as multiple omics datasets from three sets of animal experiments including KO mice model were comprehensively analyzed and validated, which provides valuable evidence for different perspectives on wild-type IDH2 in the initiation of cancer, and a strong foundation for future research in various fields such as cancer research.\u003c/p\u003e \u003cp\u003eThis study highlights the critical role of the SIRT3-IDH2 axis in the context of chemical-induced colon carcinogenesis. Using unbiased multi-omics approaches as well as unique models (e.g., SIRT3 and IDH2 KO models), we demonstrated that fructose suppresses SIRT3 expression and IDH2 activity, leading to impaired mitochondrial detoxification, increased oxidative stress, and a weakened DNA damage response. These effects, in turn, exacerbate DNA damage and promote tumorigenesis, particularly in the absence of IDH2. By unraveling the mechanistic link between fructose-induced mitochondrial dysfunction and colon carcinogenesis, our findings emphasize the importance of the SIRT3-IDH2 axis in maintaining cellular redox homeostasis and genomic integrity. This study provides a strong foundation for targeting this pathway as a therapeutic strategy to mitigate the carcinogenic effects of dietary fructose and related environmental factors.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the Basic Science Research Program through the National Research Foundation of Korea, funded by the Ministry of Education (RS-2023-00245564); the Ministry of Food and Drug Safety of South Korea (RS-2024-00332492); and the BK21 Fostering Outstanding Universities for Research (FOUR) program.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConceptualization:\u003c/strong\u003e JKK; \u003cstrong\u003eMethodology:\u003c/strong\u003e NAB, JHL, JKK; \u003cstrong\u003eValidation:\u003c/strong\u003e HRS, KCC, JHL, JKK; \u003cstrong\u003eFormal analysis:\u003c/strong\u003e JHP, KJK, BK; \u003cstrong\u003eInvestigation:\u003c/strong\u003e JHP, KJK, HRS; \u003cstrong\u003eResources:\u003c/strong\u003e NAB, BK, JKK; \u003cstrong\u003eData curation:\u003c/strong\u003e BK, JKK; \u003cstrong\u003eWriting \u0026ndash; Original Draft:\u003c/strong\u003e JHP, JKK; \u003cstrong\u003eWriting \u0026ndash; Review \u0026amp; Editing:\u003c/strong\u003e NAB, HRS, KCC, JHL; \u003cstrong\u003eVisualization:\u003c/strong\u003e JHP, KJK; \u003cstrong\u003eSupervision:\u003c/strong\u003e JKK\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing financial interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary information\u003c/strong\u003e accompanies the manuscript on the Experimental \u0026amp; Molecular Medicine` website (http://www.nature.com/emm/). The following file formats are included: Supplementary Figures (.pdf) and Supplementary table (.docx)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrespondence\u003c/strong\u003e and requests for materials should be addressed to Jae Kyeom Kim.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReprints and permission information\u003c/strong\u003e is available at http://www.nature.com/ reprints\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eUSDA. USDA ERS - Sugar and Sweeteners Yearbook Tables. \u003cem\u003eSugar and Sweetners Yearbook Tables\u003c/em\u003e https://www.ers.usda.gov/data-products/sugar-and-sweeteners-yearbook-tables/sugar-and-sweeteners-yearbook-tables/#U.S. Consumption of Caloric Sweeteners (2021).\u003c/li\u003e\n\u003cli\u003eBes-Rastrollo, M., Schulze, M. B., Ruiz-Canela, M. \u0026amp; Martinez-Gonzalez, M. A. 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D. \u003cem\u003eet al.\u003c/em\u003e High-fructose corn syrup enhances intestinal tumor growth in mice. \u003cem\u003eScience (1979)\u003c/em\u003e \u003cstrong\u003e363\u003c/strong\u003e, 1345\u0026ndash;1349 (2019).\u003c/li\u003e\n\u003cli\u003eNakagawa, T. \u003cem\u003eet al.\u003c/em\u003e Fructose contributes to the Warburg effect for cancer growth. \u003cem\u003eCancer Metab\u003c/em\u003e\u003cstrong\u003e8\u003c/strong\u003e, 16 (2020).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"experimental-and-molecular-medicine","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"emm","sideBox":"Learn more about [Experimental \u0026 Molecular Medicine](http://www.nature.com/emm/)","snPcode":"12276","submissionUrl":"https://mts-emm.nature.com/cgi-bin/main.plex","title":"Experimental \u0026 Molecular Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine, glutathione depletion, multi-omics, xenobiotic metabolism ","lastPublishedDoi":"10.21203/rs.3.rs-6226269/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6226269/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe potential roles of fructose in colon cancer are growing concerns. Fructose consumption has been linked to oxidative stress and mitochondrial dysfunction, yet its specific molecular mechanisms in colon carcinogenesis remain underexplored.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study aimed to investigate the molecular mechanisms by which dietary fructose contributes to colon carcinogenesis, focusing on the role of mitochondrial NADP\u003csup\u003e+\u003c/sup\u003e-dependent isocitrate dehydrogenase (IDH2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing an unbiased multi-omics approach (transcriptomics and proteomics), liver and colon tissues from fructose-fed wild-type (WT) mice were analyzed to identify key genes involved in cancer-related pathways. Human liver transcriptomic data (GSE256398) was analyzed to confirm alterations in aryl hydrocarbon receptor (AhR) signaling and the SIRT3-IDH2 axis. IDH2 knockout (KO) mice were exposed to a dietary carcinogen, 2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine (PhIP), to validate IDH2's role in colon cancer development. In vitro, fructose’s effects on SIRT3 expression and IDH2 activity were assessed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFructose-fed WT mice exhibited suppressed AhR signaling, increased oxidative stress, and mitochondrial dysfunction via the SIRT3-IDH2 axis. In human liver datasets, AhR-associated genes and SIRT3-IDH2 expression were reduced in MASLD and cirrhosis. IDH2 KO mice showed heightened DNA damage, colonic tumorigenesis, and mitochondrial and GSH-mediated detoxification disruptions following PhIP exposure. In vitro, fructose reduced SIRT3 expression and IDH2 activity, further supporting its role in promoting colon carcinogenesis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFructose promotes colon carcinogenesis by disrupting mitochondrial function and impairing DNA damage response mechanisms, particularly through SIRT3-IDH2 axis suppression. These findings highlight the critical role of mitochondrial dysfunction in fructose-induced carcinogenesis and suggest the SIRT3-IDH2 axis as a potential therapeutic target.\u003c/p\u003e","manuscriptTitle":"SIRT3-IDH2 axis is a target of dietary fructose: implication of IDH2 as a key player in dietary carcinogen toxicity in mice colon","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-22 17:32:46","doi":"10.21203/rs.3.rs-6226269/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2025-04-21T05:39:08+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-04-21T02:25:57+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-04-16T07:26:57+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-04-02T15:36:31+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-04-02T07:50:33+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-04-02T07:08:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-19T00:06:20+00:00","index":"","fulltext":""},{"type":"submitted","content":"Experimental \u0026 Molecular Medicine","date":"2025-03-18T09:31:36+00:00","index":"","fulltext":""},{"type":"checksFailed","content":"","date":"2025-03-17T23:57:11+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-14T12:21:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"experimental-and-molecular-medicine","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"emm","sideBox":"Learn more about [Experimental \u0026 Molecular Medicine](http://www.nature.com/emm/)","snPcode":"12276","submissionUrl":"https://mts-emm.nature.com/cgi-bin/main.plex","title":"Experimental \u0026 Molecular Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"eaddbba1-0df1-4936-ae67-8b9d864523fe","owner":[],"postedDate":"April 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":46556638,"name":"Biological sciences/Molecular biology/DNA damage and repair"},{"id":46556639,"name":"Biological sciences/Molecular biology/RNA metabolism/RNA modification"}],"tags":[],"updatedAt":"2025-11-27T08:09:19+00:00","versionOfRecord":{"articleIdentity":"rs-6226269","link":"https://doi.org/10.1038/s12276-025-01584-0","journal":{"identity":"experimental-and-molecular-medicine","isVorOnly":false,"title":"Experimental \u0026 Molecular Medicine"},"publishedOn":"2025-11-13 05:00:00","publishedOnDateReadable":"November 13th, 2025"},"versionCreatedAt":"2025-04-22 17:32:46","video":"","vorDoi":"10.1038/s12276-025-01584-0","vorDoiUrl":"https://doi.org/10.1038/s12276-025-01584-0","workflowStages":[]},"version":"v1","identity":"rs-6226269","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6226269","identity":"rs-6226269","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}