Metabolomics profiling of steatosis progression in HepaRG® cells using sodium valproate

ChREBP is activated by reductive stress and mediates GCKR-associated metabolic traits

Common genetic variants in glucokinase regulator (GCKR), which encodes GKRP, a regulator of hepatic glucokinase (GCK), influence multiple metabolic traits in genome-wide association studies (GWASs), making GCKR one of the most pleiotropic GWAS loci in the genome. It is unclear why. Prior work has demonstrated that GCKR influences the hepatic cytosolic NADH/NAD+ ratio, also referred to as reductive stress. Here, we demonstrate that reductive stress is sufficient to activate the transcription factor ChREBP and necessary for its activation by the GKRP-GCK interaction, glucose, and ethanol. We show that hepatic reductive stress induces GCKR GWAS traits such as increased hepatic fat, circulating FGF21, and circulating acylglycerol species, which are also influenced by ChREBP. We define the transcriptional signature of hepatic reductive stress and show its upregulation in fatty liver disease and downregulation after bariatric surgery in humans. These findings highlight how a GCKR-reductive stress-ChREBP axis influences multiple human metabolic traits.

Application of high throughput in vitro metabolomics for hepatotoxicity mode of action characterization and mechanistic-anchored point of departure derivation: a case study with nitrofurantoin

Omics techniques have been increasingly recognized as promising tools for Next Generation Risk Assessment. Targeted metabolomics offer the advantage of providing readily interpretable mechanistic information about perturbed biological pathways. In this study, a high-throughput LC-MS/MS-based broad targeted metabolomics system was applied to study nitrofurantoin metabolic dynamics over time and concentration and to provide a mechanistic-anchored approach for point of departure (PoD) derivation. Upon nitrofurantoin exposure at five concentrations (7.5 µM, 15 µM, 20 µM, 30 µM and 120 µM) and four time points (3, 6, 24 and 48 h), the intracellular metabolome of HepG2 cells was evaluated. In total, 256 uniquely identified metabolites were measured, annotated, and allocated in 13 different metabolite classes. Principal component analysis (PCA) and univariate statistical analysis showed clear metabolome-based time and concentration effects. Mechanistic information evidenced the differential activation of cellular pathways indicative of early adaptive and hepatotoxic response. At low concentrations, effects were seen mainly in the energy and lipid metabolism, in the mid concentration range, the activation of the antioxidant cellular response was evidenced by increased levels of glutathione (GSH) and metabolites from the de novo GSH synthesis pathway. At the highest concentrations, the depletion of GSH, together with alternations reflective of mitochondrial impairments, were indicative of a hepatotoxic response. Finally, a metabolomics-based PoD was derived by multivariate PCA using the whole set of measured metabolites. This approach allows using the entire dataset and derive PoD that can be mechanistically anchored to established key events. Our results show the suitability of high throughput targeted metabolomics to investigate mechanisms of hepatoxicity and derive point of departures that can be linked to existing adverse outcome pathways and contribute to the development of new ones.

Predicting Valproate-Induced Liver Injury Using Metabolomic Analysis of Ex Ovo Chick Embryo Allantoic Fluid

The use of sensitive animals in toxicological studies tends to be limited. Even though cell culture is an attractive alternative, it has some limitations. Therefore, we investigated the potential of the metabolomic profiling of the allantoic fluid (AF) from ex ovo chick embryos to predict the hepatotoxicity of valproate (VPA). To this end, the metabolic changes occurring during embryo development and following exposure to VPA were assessed using ¹H-NMR spectroscopy. During embryonic development, our findings indicated a metabolism progressively moving from anaerobic to aerobic, mainly based on lipids as the energy source. Next, liver histopathology of VPA-exposed embryos revealed abundant microvesicles indicative of steatosis and was metabolically confirmed via the determination of lipid accumulation in AF. VPA-induced hepatotoxicity was further demonstrated by (i) lower glutamine levels, precursors of glutathione, and decreased β-hydroxybutyrate, an endogenous antioxidant; (ii) changes in lysine levels, a precursor of carnitine, which is essential in the transport of fatty acids to the mitochondria and whose synthesis is known to be reduced by VPA; and (iii) choline accumulation that promotes the export of hepatic triglycerides. In conclusion, our results support the use of the ex ovo chick embryo model combined with the metabolomic assessment of AF to rapidly predict drug-induced hepatotoxicity.

In vitro to in vivo extrapolation and high-content imaging for simultaneous characterization of chemically induced liver steatosis and markers of hepatotoxicity

Chemically induced steatosis is characterized by lipid accumulation associated with mitochondrial dysfunction, oxidative stress and nucleus distortion. New approach methods integrating in vitro and in silico models are needed to identify chemicals that may induce these cellular events as potential risk factors for steatosis and associated hepatotoxicity. In this study we used high-content imaging for the simultaneous quantification of four cellular markers as sentinels for hepatotoxicity and steatosis in chemically exposed human liver cells in vitro. Furthermore, we evaluated the results with a computational model for the extrapolation of human oral equivalent doses (OED). First, we tested 16 reference chemicals with known capacities to induce cellular alterations in nuclear morphology, lipid accumulation, mitochondrial membrane potential and oxidative stress. Then, using physiologically based pharmacokinetic modeling and reverse dosimetry, OEDs were extrapolated from data of any stimulated individual sentinel response. The extrapolated OEDs were confirmed to be within biologically relevant exposure ranges for the reference chemicals. Next, we tested 14 chemicals found in food, selected from thousands of putative chemicals on the basis of structure-based prediction for nuclear receptor activation. Amongst these, orotic acid had an extrapolated OED overlapping with realistic exposure ranges. Thus, we were able to characterize known steatosis-inducing chemicals as well as data-scarce food-related chemicals, amongst which we confirmed orotic acid to induce hepatotoxicity. This strategy addresses needs of next generation risk assessment and can be used as a first chemical prioritization hazard screening step in a tiered approach to identify chemical risk factors for steatosis and hepatotoxicity-associated events.

Derivation of metabolic point of departure using high-throughput in vitro metabolomics: investigating the importance of sampling time points on benchmark concentration values in the HepaRG cell line

Amongst omics technologies, metabolomics should have particular value in regulatory toxicology as the measurement of the molecular phenotype is the closest to traditional apical endpoints, whilst offering mechanistic insights into the biological perturbations. Despite this, the application of untargeted metabolomics for point-of-departure (POD) derivation via benchmark concentration (BMC) modelling is still a relatively unexplored area. In this study, a high-throughput workflow was applied to derive PODs associated with a chemical exposure by measuring the intracellular metabolome of the HepaRG cell line following treatment with one of four chemicals (aflatoxin B₁, benzo[a]pyrene, cyclosporin A, or rotenone), each at seven concentrations (aflatoxin B₁, benzo[a]pyrene, cyclosporin A: from 0.2048 μM to 50 μM; rotenone: from 0.04096 to 10 μM) and five sampling time points (2, 6, 12, 24 and 48 h). The study explored three approaches to derive PODs using benchmark concentration modelling applied to single features in the metabolomics datasets or annotated metabolites or lipids: (1) the 1st rank-ordered unannotated feature, (2) the 1st rank-ordered putatively annotated feature (using a recently developed HepaRG-specific library of polar metabolites and lipids), and (3) 25th rank-ordered feature, demonstrating that for three out of four chemical datasets all of these approaches led to relatively consistent BMC values, varying less than tenfold across the methods. In addition, using the 1st rank-ordered unannotated feature it was possible to investigate temporal trends in the datasets, which were shown to be chemical specific. Furthermore, a possible integration of metabolomics-driven POD derivation with the liver steatosis adverse outcome pathway (AOP) was demonstrated. The study highlights that advances in technologies enable application of in vitro metabolomics at scale; however, greater confidence in metabolite identification is required to ensure PODs are mechanistically anchored.

Metabolomics coupled with network pharmacology study on the protective effect of Keguan-1 granules in LPS-induced acute lung injury

CONTEXT

Keguan-1 (KG-1) plays a vital role in enhancing the curative effects, improving quality of life, and reducing the development of acute lung injury (ALI).

OBJECTIVE

To unravel the protective effect and underlying mechanism of KG-1 against ALI.

MATERIALS AND METHODS

C57BL/6J mice were intratracheally instilled with lipopolysaccharide to establish the ALI model. Then, mice in the KG-1 group received a dose of 5.04 g/kg for 12 h. The levels of proinflammatory cytokines, chemokines, and pathological characteristics were determined to explore the effects of KG-1. Next, untargeted metabolomics was used to identify the differential metabolites and involved pathways for KG-1 anti-ALI. Network pharmacology was carried out to predict the putative active components and drug targets of KG-1 anti-ALI.

RESULTS

KG-1 significantly improved the levels of TNF-α (from 2295.92 ± 529.87 pg/mL to 1167.64 ± 318.91 pg/mL), IL-6 (from 4688.80 ± 481.68 pg/mL to 3604.43 ± 382.00 pg/mL), CXCL1 (from 4361.76 ± 505.73 pg/mL to 2981.04 ± 526.18 pg/mL), CXCL2 (from 5034.09 ± 809.28 pg/mL to 2980.30 ± 747.63 pg/mL), and impaired lung histological damage. Untargeted metabolomics revealed that KG-1 significantly regulated 12 different metabolites, which mainly related to lipid, amino acid, and vitamin metabolism. Network pharmacology showed that KG-1 exhibited anti-ALI effects through 17 potentially active components acting on seven putative drug targets to regulate four metabolites.

DISCUSSION AND CONCLUSIONS

This work elucidated the therapeutic effect and underlying mechanism by which KG-1 protects against ALI from the view of the metabolome, thus providing a scientific basis for the usage of KG-1.

In Vitro Models for Studying Chronic Drug-Induced Liver Injury

Drug-induced liver injury (DILI) is a major clinical problem in terms of patient morbidity and mortality, cost to healthcare systems and failure of the development of new drugs. The need for consistent safety strategies capable of identifying a potential toxicity risk early in the drug discovery pipeline is key. Human DILI is poorly predicted in animals, probably due to the well-known interspecies differences in drug metabolism, pharmacokinetics, and toxicity targets. For this reason, distinct cellular models from primary human hepatocytes or hepatoma cell lines cultured as 2D monolayers to emerging 3D culture systems or the use of multi-cellular systems have been proposed for hepatotoxicity studies. In order to mimic long-term hepatotoxicity in vitro, cell models, which maintain hepatic phenotype for a suitably long period, should be used. On the other hand, repeated-dose administration is a more relevant scenario for therapeutics, providing information not only about toxicity, but also about cumulative effects and/or delayed responses. In this review, we evaluate the existing cell models for DILI prediction focusing on chronic hepatotoxicity, highlighting how better characterization and mechanistic studies could lead to advance DILI prediction.

Metabolic Signature of Ethanol-Induced Hepatotoxicity in HepaRG Cells by Liquid Chromatography-Mass Spectrometry-Based Untargeted Metabolomics

Alcoholic liver disease is highly prevalent but poorly identified and characterized, leading to knowledge gaps, which impairs early diagnosis. Excessive alcohol consumption is known to alter lipid metabolism, followed by progressive intracellular lipid accumulation, resulting in alcoholic fatty liver disease. In this study, HepaRG cells were exposed to ethanol at IC₁₀ and 1/10 IC₁₀ for 24 and 48 h. Metabolic alterations were investigated intra- and extracellularly with liquid chromatography-high-resolution mass spectrometry. Ion mobility was added as an extra separation dimension for untargeted lipidomics to improve annotation confidence. Distinctive patterns between exposed and control cells were consistently observed, with intracellular upregulation of di- and triglycerides, downregulation of phosphatidylcholines and phosphatidylethanolamines, sphingomyelins, and S-adenosylmethionine, among others. Several intracellular metabolic patterns could be related to changes in the extracellular environment, such as increased intracellular hydrolysis of sphingomyelins, leading to increased phosphorylcholine secretion. Carnitines showed alterations depending on the size of their carbon chain, which highlights the interplay between β-oxidation in mitochondria and peroxisomes. Potential new biomarkers of ethanol-induced hepatotoxicity have been observed, such as ceramides with a sphingadienine backbone, octanoylcarnitine, creatine, acetylcholine, and ethoxylated phosphorylcholine. The combination of the metabolic fingerprint and footprint enabled a comprehensive investigation of the pathophysiology behind ethanol-induced hepatotoxicity.

From NAFLD to MAFLD: Aligning Translational In Vitro Research to Clinical Insights

Although most same-stage non-alcoholic fatty liver disease (NAFLD) patients exhibit similar histologic sequelae, the underlying mechanisms appear to be highly heterogeneous. Therefore, it was recently proposed to redefine NAFLD to metabolic dysfunction-associated fatty liver disease (MAFLD) in which other known causes of liver disease such as alcohol consumption or viral hepatitis do not need to be excluded. Revised nomenclature envisions speeding up and facilitating anti-MAFLD drug development by means of patient stratification whereby each subgroup would benefit from distinct pharmacological interventions. As human-based in vitro research fulfils an irrefutable step in drug development, action should be taken as well in this stadium of the translational path. Indeed, most established in vitro NAFLD models rely on short-term exposure to fatty acids and use lipid accumulation as a phenotypic benchmark. This general approach to a seemingly ambiguous disease such as NAFLD therefore no longer seems applicable. Human-based in vitro models that accurately reflect distinct disease subgroups of MAFLD should thus be adopted in early preclinical disease modeling and drug testing. In this review article, we outline considerations for setting up translational in vitro experiments in the MAFLD era and allude to potential strategies to implement MAFLD heterogeneity into an in vitro setting so as to better align early drug development with future clinical trial designs.

Integrating in vitro metabolomics with a 96-well high-throughput screening platform

INTRODUCTION

High-throughput screening (HTS) is emerging as an approach to support decision-making in chemical safety assessments. In parallel, in vitro metabolomics is a promising approach that can help accelerate the transition from animal models to high-throughput cell-based models in toxicity testing.

OBJECTIVE

In this study we establish and evaluate a high-throughput metabolomics workflow that is compatible with a 96-well HTS platform employing 50,000 hepatocytes of HepaRG per well.

METHODS

Low biomass cell samples were extracted for metabolomics analyses using a newly established semi-automated protocol, and the intracellular metabolites were analysed using a high-resolution spectral-stitching nanoelectrospray direct infusion mass spectrometry (nESI-DIMS) method that was modified for low sample biomass.

RESULTS

The method was assessed with respect to sensitivity and repeatability of the entire workflow from cell culturing and sampling to measurement of the metabolic phenotype, demonstrating sufficient sensitivity (> 3000 features in hepatocyte extracts) and intra- and inter-plate repeatability for polar nESI-DIMS assays (median relative standard deviation < 30%). The assays were employed for a proof-of-principle toxicological study with a model toxicant, cadmium chloride, revealing changes in the metabolome across five sampling times in the 48-h exposure period. To allow the option for lipidomics analyses, the solvent system was extended by establishing separate extraction methods for polar metabolites and lipids.

CONCLUSIONS

Experimental, analytical and informatics workflows reported here met pre-defined criteria in terms of sensitivity, repeatability and ability to detect metabolome changes induced by a toxicant and are ready for application in metabolomics-driven toxicity testing to complement HTS assays.

Cell Models and Omics Techniques for the Study of Nonalcoholic Fatty Liver Disease: Focusing on Stem Cell-Derived Cell Models

Nonalcoholic fatty liver disease (NAFLD) is now the leading cause of chronic liver disease in western countries. The molecular mechanisms leading to NAFLD are only partially understood, and effective therapeutic interventions are clearly needed. Therefore, preclinical research is required to improve knowledge about NAFLD physiopathology and to identify new therapeutic targets. Primary human hepatocytes, human hepatic cell lines, and human stem cell-derived hepatocyte-like cells exhibit different hepatic phenotypes and have been widely used for studying NAFLD pathogenesis. In this paper, apart from employing the different in vitro cell models for the in vitro assessment of NAFLD, we also reviewed other approaches (metabolomics, transcriptomics, and high-content screening). We aimed to summarize the characteristics of different cell types and methods and to discuss their major advantages and disadvantages for NAFLD modeling.

Safety assessment of cosmetics by read across applied to metabolomics data of in vitro skin and liver models

As a result of the cosmetics testing ban, safety evaluations of cosmetics ingredients must now be conducted using animal-free methods. A common approach is read across, which is mainly based on structural similarities but can also be conducted using biological endpoints. Here, metabolomics was used to assess biological effects to enable a read across between a candidate cosmetic ingredient, DIV665, only studied using in vitro assays, and a structurally similar reference compound, PA102, previously investigated using traditional in vivo toxicity methods. The (1) cutaneous distribution after topical application, (2) skin metabolism, (3) liver metabolism and (4) effect on the intracellular metabolomic profiles of in vitro skin and hepatic models, SkinEthic^®RHE model and HepaRG^® cells were investigated. The compounds exhibited similar skin penetration and skin and liver metabolism, with small differences attributed to their physicochemical properties. The effects of both compounds on the metabolome of RHE and HepaRG^® cells were similarly small, both in terms of the metabolites modulated and the magnitude of changes. The patterns of metabolome changes did not fit with any known signature relating to a mode of action known to be linked to liver toxicity e.g. modification of the Krebs cycle, urea synthesis and lipid metabolism, were more reflective of transient adaptive responses. Overall, these studies indicate that PA102 is biologically similar to DIV665, allowing read across of safety endpoints, such as in vivo sub-chronic (but not reproduction toxicity) studies, for the former to be applied to DIV665. Based on this, in the absence of animal data (which is prohibited for new chemicals), it could be concluded that DIV665 applied according to the consumer topical use scenario, is similar to PA102, and is predicted to exhibit low local skin and systemic toxicity.

Analytical and Omics-Based Advances in the Study of Drug-Induced Liver Injury

Drug-induced liver injury (DILI) is a significant clinical issue, affecting 1-1.5 million patients annually, and remains a major challenge during drug development-toxicity and safety concerns are the second-highest reason for drug candidate failure. The future prevalence of DILI can be minimized by developing a greater understanding of the biological mechanisms behind DILI. Both qualitative and quantitative analytical techniques are vital to characterizing and investigating DILI. In vitro assays are capable of characterizing specific aspects of a drug's hepatotoxic nature and multiplexed assays are capable of characterizing and scoring a drug's association with DILI. However, an even deeper insight into the perturbations to biological pathways involved in the mechanisms of DILI can be gained through the use of omics-based analytical techniques: genomics, transcriptomics, proteomics, and metabolomics. These omics analytical techniques can offer qualitative and quantitative insight into genetic susceptibilities to DILI, the impact of drug treatment on gene expression, and the effect on protein and metabolite abundance. This review will discuss the analytical techniques that can be applied to characterize and investigate the biological mechanisms of DILI and potential predictive biomarkers.

Association of CYP1A1 and CYP1B1 inhibition in in vitro assays with drug-induced liver injury

Drug-induced liver injury (DILI) is one of the major causes for the discontinuation of drug development and withdrawal of drugs from the market. Since it is known that reactive metabolite formation and being substrates or inhibitors of cytochrome P450s (P450s) are associated with DILI, we systematically investigated the association between human P450 inhibition and DILI. The inhibitory activity of 266 DILI-positive drugs (DILI drugs) and 92 DILI-negative drugs (no-DILI drugs), which were selected from Liver Toxicity Knowledge Base (US Food and Drug Administration), against 8 human P450 forms was assessed using recombinant enzymes and luminescent substrates, and the threshold values showing the highest balanced accuracy for DILI discrimination were determined for each P450 enzyme using receiver operating characteristic analyses. The results showed that among the P450s tested, CYP1A1 and CYP1B1 were inhibited by DILI drugs more than no-DILI drugs with a statistical significance. We found that 91% of drugs that showed inhibitory activity greater than the threshold values against CYP1A1 or CYP1B1 were DILI drugs. The results of internal 5-fold cross-validation confirmed the usefulness of CYP1A1 and CYP1B1 inhibition data for the threshold-based discrimination of DILI drugs. Although the contribution of these P450s to drug metabolism in the liver is considered minimal, our present findings suggest that the assessment of CYP1A1 and CYP1B1 inhibition is useful for screening DILI risk of drug candidates at the early stage of drug development.

Drug-induced hepatic steatosis in absence of severe mitochondrial dysfunction in HepaRG cells: proof of multiple mechanism-based toxicity

Steatosis is a liver lesion reported with numerous pharmaceuticals. Prior studies showed that severe impairment of mitochondrial fatty acid oxidation (mtFAO) constantly leads to lipid accretion in liver. However, much less is known about the mechanism(s) of drug-induced steatosis in the absence of severe mitochondrial dysfunction, although previous studies suggested the involvement of mild-to-moderate inhibition of mtFAO, increased de novo lipogenesis (DNL), and impairment of very low-density lipoprotein (VLDL) secretion. The objective of our study, mainly carried out in human hepatoma HepaRG cells, was to investigate these 3 mechanisms with 12 drugs able to induce steatosis in human: amiodarone (AMIO, used as positive control), allopurinol (ALLO), D-penicillamine (DPEN), 5-fluorouracil (5FU), indinavir (INDI), indomethacin (INDO), methimazole (METHI), methotrexate (METHO), nifedipine (NIF), rifampicin (RIF), sulindac (SUL), and troglitazone (TRO). Hepatic cells were exposed to drugs for 4 days with concentrations decreasing ATP level by less than 30% as compared to control and not exceeding 100 × Cmax. Among the 12 drugs, AMIO, ALLO, 5FU, INDI, INDO, METHO, RIF, SUL, and TRO induced steatosis in HepaRG cells. AMIO, INDO, and RIF decreased mtFAO. AMIO, INDO, and SUL enhanced DNL. ALLO, 5FU, INDI, INDO, SUL, RIF, and TRO impaired VLDL secretion. These seven drugs reduced the mRNA level of genes playing a major role in VLDL assembly and also induced endoplasmic reticulum (ER) stress. Thus, in the absence of severe mitochondrial dysfunction, drug-induced steatosis can be triggered by different mechanisms, although impairment of VLDL secretion seems more frequently involved, possibly as a consequence of ER stress.

Bile acids, lipid and purine metabolism involved in hepatotoxicity of first-line anti-tuberculosis drugs

OBJECTIVES

Rifampin (RIF), isoniazid (INH) and pyrazinamide (PZA) are essential components of the short-term first-line anti-tuberculosis (anti-TB) chemotherapy regimen and can cause hepatotoxicity. However, the mechanism of anti-TB drug-induced hepatotoxicity (ATDH) is currently unclear. We investigate the relevant contributions to liver injury and the pathway of the above-mentioned drugs administered alone or in combination.

METHODS

UPLC-Q-TOF/MS-based metabolomics, bile acids (BAs) analysis and FXR/SHP detection were used to evaluate the toxicity of these drugs and clarify the underlying metabolism-related pathway.

RESULTS

In C57BL/6 mice administered the corrected clinical doses, RIF, INH and PZA could induced hepatotoxicity; with less toxicity in the combination therapy than RIF. The pathological biochemistry, BAs concentration and metabolically regulated FXR/SHP gene expression analyzes in mice were consistent with the metabolomics results. FXR played a role in the hepatotoxicity of anti-tuberculosis drugs in the obeticholic acid treated and FXR^-/- mice. Additionally, the purine and lipid metabolic pathways were involved in ATDH.

CONCLUSION

ATDH was involved in bile acids and lipid and purine metabolism. The BAs metabolic pathway involvement in mice was validated in TB patients. The noninvasive metabolomics approach is more systemic than routine toxicity evaluation and can be used to assess compound toxicity and the underlying mechanism.

Metabolomic-based assessment reveals dysregulation of lipid profiles in human liver cells exposed to environmental obesogens

Significant attention has been given to the potential of environmental chemicals to disrupt lipid homeostasis at the cellular level. These chemicals, classified as obesogens, are abundantly used in a wide variety of consumer products. However, there is a significant lack of information regarding the mechanisms by which environmental exposure can contribute to the onset of obesity and non-alcoholic fatty liver disease (NAFLD). Several studies have described the interaction of potential obesogens with lipid-related peroxisome proliferator-activated receptors (PPAR). However, no studies have quantified the degree of modification to lipidomic profiles in relevant human models, making it difficult to directly link PPAR agonists to the onset of lipid-related diseases. A quantitative metabolomic approach was used to examine the dysregulation of lipid metabolism in human liver cells upon exposure to potential obesogenic compounds. The chemicals rosiglitazone, perfluorooctanoic acid, di-2-ethylexylphthalate, and tributyltin significantly increased total lipids in liver cells, being diglycerides, triglycerides and phosphatidylcholines the most prominent. Contrarily, perfluorooctane sulfonic acid and the pharmaceutical fenofibrate appeared to lower total lipid concentrations, especially those belonging to the acylcarnitine, ceramide, triglyceride, and phosphatidylcholine groups. Fluorescence microscopy analysis for cellular neutral lipids revealed significant lipid bioaccumulation upon exposure to obesogens at environmentally relevant concentrations. This integrated omics analysis provides unique mechanistic insight into the potential of these environmental pollutants to promote diseases like obesity and NAFLD. Furthermore, this study provides a significant contribution to advance the understanding of molecular signatures related to obesogenic chemicals and to the development of alternatives to in vivo experimentation.

Analytical techniques for metabolomic studies: a review

Metabolomics is the comprehensive study of small-molecule metabolites. Obtaining a wide coverage of the metabolome is challenging because of the broad range of physicochemical properties of the small molecules. To study the compounds of interest spectroscopic (NMR), spectrometric (MS) and separation techniques (LC, GC, supercritical fluid chromatography, CE) are used. The choice for a given technique is influenced by the sample matrix, the concentration and properties of the metabolites, and the amount of sample. This review discusses the most commonly used analytical techniques for metabolomic studies, including their advantages, drawbacks and some applications.

Early detection of metabolic changes in drug-induced steatosis using metabolomics approaches

Steatosis is the accumulation of triglycerides in hepatic cells wherein fats exceed 5% of the entire liver weight. Although steatotic liver damage is reversible due to the liver's regenerative capability, protracted damage often and typically leads to irreversible conditions such as cirrhosis and hepatocellular carcinoma (HCC). Therefore, early steatotic detection is critical for preventing progression to advanced liver diseases. This also becomes particularly important given the higher prevalence of drug usage, as drugs are a frequent cause of liver damage. Currently, the recommendation to diagnose steatosis is using liver enzymes and performing a liver biopsy. Liver biopsy remains the gold standard method of detection, but the procedure is invasive and an unreliable diagnostic tool. Non-invasive, specific and sensitive diagnostic solutions such as biomarkers are therefore needed for the early detection of steatosis. Our aim is to identify changes in urinary metabolites in tetracycline-induced hepatic steatotic rats at different stages of the diseases using metabolomic-based techniques. Sprague Dawley male rats are treated by intraperitoneal injection (I.P.) with either 62.5 mg kg⁻¹ or 125 mg kg⁻¹ tetracycline, an antibiotic previously known to induce steatosis. We analyse the metabolic profile of the urinary tetracycline induced hepatic steatotic rats using ¹H nuclear magnetic resonance (NMR), 2D ¹H–¹H TOCSY (total correlation spectroscopy) and electrospray liquid chromatography-mass spectrometry (ESI-LC-MS/MS) based metabolomics. The combined analysis of haematoxylin & eosin (H&E), oil red O (ORO) and direct measurement of triglyceride content in the liver tissues of the control samples against 125 mg kg⁻¹ and 62.5 mg kg⁻¹ treated samples, reveals that 125 mg kg⁻¹ tetracycline exposure potentially induces steatosis. The combination of ¹H NMR, 2D ¹H–¹H TOCSY and ESI-LC-MS/MS alongside multivariate statistical analysis, detected a total of 6 urinary metabolites changes, across 6 metabolic pathways. Furthermore, lysine concentration correlates with liver damage as tetracycline dose concentration increases, whilst both H&E and ORO fail to detect hepatocellular damage at the lowest dose concentration. We conclude that the combination of ¹H NMR and ESI-LC-MS/MS suggests that these are suitable platforms for studying the pathogenesis of steatosis development, prior to morphological alterations observed in staining techniques and offer a more detailed description of the severity of the steatotic disease.

Urinary metabolic profiling of tetracycline induced hepatic steatotic rats were investigated using ¹H nuclear magnetic resonance, 2D ¹H–¹H total correlation spectroscopy and electrospray liquid chromatography-mass spectrometry based metabolomics.

Exposure of HepaRG Cells to Sodium Saccharin Underpins the Importance of Including Non-Hepatotoxic Compounds When Investigating Toxicological Modes of Action Using Metabolomics

Metabolites represent the most downstream information of the cellular organisation. Hence, metabolomics experiments are extremely valuable to unravel the endogenous pathways involved in a toxicological mode of action. However, every external stimulus can introduce alterations in the cell homeostasis, thereby obscuring the involved endogenous pathways, biasing the interpretation of the results. Here we report on sodium saccharin, which is considered to be not hepatotoxic and therefore can serve as a reference compound to detect metabolic alterations that are not related to liver toxicity. Exposure of HepaRG cells to high levels of sodium saccharin (>10 mM) induced cell death, probably due to an increase in the osmotic pressure. Yet, a low number (n = 15) of significantly altered metabolites were also observed in the lipidome, including a slight decrease in phospholipids and an increase in triacylglycerols, upon daily exposure to 5 mM sodium saccharin for 72 h. The observation that a non-hepatotoxic compound can affect the metabolome underpins the importance of correct experimental design and data interpretation when investigating toxicological modes of action via metabolomics.

Structure-activity relationship study: Mechanism of cyto-genotoxicity of Nitropyrazole-derived high energy density materials family

Stringent toxicological tests have to be performed prior to the industrial development of alternative chemicals particularly high energy dense materials (HEDMs) such as explosives. The properties (e.g., power, stability) of these compounds are constantly being improved, the current axis of research being the nitration of nitrogen heterocycles leading to HEDMs such as nitropyrazole-derived molecules. However, except for 3,4,5-trinitropyrazole (3,4,5-TNP), which was shown to be highly toxic in mice, the toxicological impact of these HEDMs has so far not been investigated. Furthermore, as industrials are strongly advised to develop alternative safety testing assays to in vivo experiments, we herein focused on determining the cytotoxic and genotoxic effects of seven Nitropyrazole-derived HEDMs on three rodent cell lines (mouse embryonic BALB/3T3 clone A31 cells, Chinese hamster ovary cells CHO-K1 and mouse lymphoma L5178Y TK +/- clone (3.7.2C) cells), two human fibroblast lines (CRC05, PFS04062) and on the human hepatic HepaRG model (both in proliferative and differentiated cells). A stronger cytotoxic effect was observed for 1,3-dinitropyrazole (1, 3-DNP) and 3,4,5-TNP in all cell lines, though differentiated HepaRG cells clearly displayed fewer likely due to the metabolism and elimination of these molecules by their functional biotransformation pathways. At the mechanistic level, the sub-chronic cytotoxic and genotoxic effects were linked to ROS/RNS production (experimental assays), HA2.X and to transcriptomic data highlighting the increase in DNA repair mechanisms.

Untargeted liquid chromatography-mass spectrometry metabolomics to assess drug-induced cholestatic features in HepaRG® cells

Cholestasis is a liver disease associated with retention of bile in the liver, which leads to local hepatic inflammation and severe liver damage. In order to investigate the mode of action of drug-induced cholestasis, in vitro models have shown to be able to recapitulate important elements of this disease. In this study, we applied untargeted metabolomics to investigate the metabolic perturbances in HepaRG® cells exposed for 24 h and 72 h to bosentan, a cholestatic reference toxicant. Intracellular profiles were extracted and analysed with liquid chromatography and accurate-mass spectrometry. Metabolites of interest were selected using partial least-squares discriminant analysis and random forest classifier models. The observed metabolic patterns associated with cholestasis in vitro were complex. Acute (24 h) exposure revealed metabolites related to apoptosis, such as ceramide and triglyceride accumulation, in combination with phosphatidylethanolamine, choline and carnitine depletion. Metabolomic alterations during exposure to lower dosages and a prolonged exposure (72 h) included carnitine upregulation and changes in the polyamine metabolism. These metabolites were linked to changes in phospholipid metabolism, mitochondrial pathways and energy homeostasis. The metabolic changes confirmed the mitotoxic effects of bosentan and revealed the potential involvement of phospholipid metabolism as part of the mode of action of drug-induced cholestasis.

Comparing normalization methods and the impact of noise

INTRODUCTION

Failure to properly account for normal systematic variations in OMICS datasets may result in misleading biological conclusions. Accordingly, normalization is a necessary step in the proper preprocessing of OMICS datasets. In this regards, an optimal normalization method will effectively reduce unwanted biases and increase the accuracy of downstream quantitative analyses. But, it is currently unclear which normalization method is best since each algorithm addresses systematic noise in different ways.

OBJECTIVE

Determine an optimal choice of a normalization method for the preprocessing of metabolomics datasets.

METHODS

Nine MVAPACK normalization algorithms were compared with simulated and experimental NMR spectra modified with added Gaussian noise and random dilution factors. Methods were evaluated based on an ability to recover the intensities of the true spectral peaks and the reproducibility of true classifying features from orthogonal projections to latent structures-discriminant analysis model (OPLS-DA).

RESULTS

Most normalization methods (except histogram matching) performed equally well at modest levels of signal variance. Only probabilistic quotient (PQ) and constant sum (CS) maintained the highest level of peak recovery (> 67%) and correlation with true loadings (> 0.6) at maximal noise.

CONCLUSION

PQ and CS performed the best at recovering peak intensities and reproducing the true classifying features for an OPLS-DA model regardless of spectral noise level. Our findings suggest that performance is largely determined by the level of noise in the dataset, while the effect of dilution factors was negligible. A minimal allowable noise level of 20% was also identified for a valid NMR metabolomics dataset.

Inhibition of adenosine deaminase and xanthine oxidase by valproic acid abates hepatic triglyceride accumulation independent of corticosteroids in female rats treated with estrogen-progestin

Elevated circulating uric acid has been postulated to play an important pathophysiological role in estrogen-progestin combined oral contraceptive (COC)-induced hypertension and endothelial dysfunction. We hypothesized that disruption of glucoregulation and liver triglyceride (TG) accumulation induced by COC use would be abated by valproic acid (VPA) treatment through suppression of adenosine deaminase (ADA) and xanthine oxidase (XO) activities. Female Wistar rats aged 9-10 weeks were treated with a combination of estrogen-progestin COC steroids (1.0 μg ethinylestradiol and 5.0 μg levonorgestrel; p.o.) with or without VPA (100.0 mg/kg; p.o.) daily for 6 weeks. The result shows that the disrupted glucoregulation and associated elevated hepatic ADA activity, plasma and hepatic XO activity, uric acid (UA), TG/HDL-cholesterol, total cholesterol, and malondialdehyde induced by COC treatment were attenuated by VPA treatment. However, VPA did not have any effect on plasma aldosterone, corticosterone, ADA, circulating and hepatic free fatty acid. Our results demonstrate that suppression of plasma and hepatic XO activities, along with hepatic ADA activity and UA by VPA treatment, protects against disrupted glucoregulation and increased liver TG by COC independent of elevated corticosteroids. The findings imply that VPA would provide protection against the development of cardiometabolic disorder via inhibition of the ADA/XO/UA-mediated pathway.