A metabolomics cell-based approach for anticipating and investigating drug-induced liver injury

Cyclosporine A-induced systemic metabolic perturbations in rats: A comprehensive metabolome analysis

A better understanding of cyclosporine A (CsA)-induced nephro- and hepatotoxicity at the molecular level is necessary for safe and effective use. Utilizing a sophisticated study design, this study explored metabolic alterations after long-term CsA treatment in vivo. Rats were exposed to CsA with 4, 10, and 25 mg/kg for 4 weeks and then sacrificed to obtain liver, kidney, urine, and serum for untargeted metabolomics analysis. Differential network analysis was conducted to explore the biological relevance of metabolites significantly altered by toxicity-induced disturbance. Dose-dependent toxicity was observed in all biospecimens. The toxic effects were characterized by alterations of metabolites related to energy metabolism and cellular membrane composition, which could lead to the cholestasis-induced accumulation of bile acids in the tissues. The unfavorable impacts were also demonstrated in the serum and urine. Intriguingly, phenylacetylglycine was increased in the kidney, urine, and serum treated with high doses versus controls. Differential correlation network analysis revealed the strong correlations of deoxycytidine and guanosine with other metabolites in the network, which highlighted the influence of repeated CsA exposure on DNA synthesis. Overall, prolonged CsA administration had system-level dose-dependent effects on the metabolome in treated rats, suggesting the need for careful usage and dose adjustment.

How do biomarkers dance? Specific moves of defense and damage biomarkers for biological interpretation of dose-response model trends

Omics studies are currently increasingly used in ecotoxicology to highlight the induction of known or novel biomarkers when organisms are exposed to contaminants. Although it is virtually impossible to identify all biomarkers from all organisms, biomarkers can be grouped as defense or damage biomarkers, exhibiting a limited number of response trends. Our working hypothesis is that defense and damage biomarkers follow different dose-response patterns. A meta-analysis of 156 articles and 2595 observations of dose-response curves of defense and damage biomarkers was carried out in order to characterize the response trends of these biological parameters in a large panel of living organisms (18 phyla) exposed to inorganic or organic contaminants (176 in total). Using multinomial logistic regression models, defense biomarkers were found to describe biphasic responses (bell- and U-shaped) to a greater extent (2.5 times) than damage biomarkers. In contrast, damage biomarkers varied mainly monotonically (decreasing or increasing), representing 85% of the observations. Neither the nature of the contaminant nor the type of organisms belonging to 4 kingdoms, influence these specific responses. This result suggests that cellular defense and damage mechanisms are not specific to stressors and are conserved throughout life. Trend analysis of dose-response models as a biological interpretation of biomarkers could thus be a valuable way to exploit large omics datasets.

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.

The Expectation and Reality of the HepG2 Core Metabolic Profile

To represent the composition of small molecules circulating in HepG2 cells and the formation of the "core" of characteristic metabolites that often attract researchers' attention, we conducted a meta-analysis of 56 datasets obtained through metabolomic profiling via mass spectrometry and NMR. We highlighted the 288 most commonly studied compounds of diverse chemical nature and analyzed metabolic processes involving these small molecules. Building a complete map of the metabolome of a cell, which encompasses the diversity of possible impacts on it, is a severe challenge for the scientific community, which is faced not only with natural limitations of experimental technologies, but also with the absence of transparent and widely accepted standards for processing and presenting the obtained metabolomic data. Formulating our research design, we aimed to reveal metabolites crucial to the Hepg2 cell line, regardless of all chemical and/or physical impact factors. Unfortunately, the existing paradigm of data policy leads to a streetlight effect. When analyzing and reporting only target metabolites of interest, the community ignores the changes in the metabolomic landscape that hide many molecular secrets.

Effects of differential regional PM2.5 induced hepatic steatosis and underlying mechanism

Emerging evidence suggests that exposure to PM_2.5 is associated with a high risk of nonalcoholic fatty liver disease (NAFLD). NAFLD is typically characterised by hepatic steatosis. However, the underlying mechanisms and critical components of PM_2.5-induced hepatic steatosis remain to be elucidated. In this study, ten-month-old C57BL/6 female mice were exposed to PM_2.5 from four cities in China (Taiyuan, Beijing, Hangzhou, and Guangzhou) via oropharyngeal aspiration every other day for four weeks. After the exposure period, hepatic lipid accumulation was evaluated by biochemical and histopathological analyses. The expression levels of genes related to lipid metabolism and metabolomic profiles were assessed in the mouse liver. The association between biomarkers of hepatic steatosis (hepatic Oil Red O staining area and serum and liver triglyceride contents) and typical components of PM_2.5 was identified using Pearson correlation analysis. Oil Red O staining and biochemical results indicated that PM_2.5 from four cities significantly induced hepatic lipid accumulation. The most severe hepatic steatosis was observed after Guangzhou PM_2.5 exposure. Moreover, Guangzhou PM_2.5-induced the most significant changes in gene expression associated with lipid metabolism, including increased hepatic fatty acid uptake and lipid droplet formation and decreased fatty acid synthesis and lipoprotein secretion. Contemporaneously, exposure to Guangzhou PM_2.5 significantly perturbed hepatic lipid metabolism. According to metabolomic analysis, disturbed hepatic lipid metabolism was primarily concentrated in linoleic acid, α-linoleic acid, and arachidonic acid metabolism. Finally, correlation analysis revealed that copper (Cu) and other inorganic components, as well as the majority of polycyclic aromatic hydrocarbons (PAHs), were related to changes in biomarkers of hepatic steatosis. These findings showed that PM_2.5 exposure caused hepatic steatosis in aged mice, which could be related to the critical chemical components of PM_2.5. This study provides critical information regarding the components of PM_2.5, which cause hepatic steatosis.

Integrated spatially resolved metabolomics and network toxicology to investigate the hepatotoxicity mechanisms of component D of Polygonum multiflorum Thunb

ETHNOPHARMACOLOGICAL RELEVANCE

The liver toxicity of Reynoutria multiflora (Thunb.) Moldenke. (Polygonaceae) (Polygonum multiflorum Thunb, PM) has always attracted much attention, but the related toxicity materials and mechanisms have not been elucidated due to multi-component and multi-target characteristics. In previous hepatotoxicity screening, different components of PM were first evaluated and the hepatotoxicity of component D [95% ethanol (EtOH) elution] in a 70% EtOH extract of PM (PM-D) showed the highest hepatotoxicity. Furthermore, the main components of PM-D were identified and their hepatotoxicity was evaluated based on a zebrafish embryo model. However, the hepatotoxicity mechanism of PM-D is unknown.

AIM OF THE STUDY

This work is to explore the hepatotoxicity mechanisms of PM-D by integrating network toxicology and spatially resolved metabolomics strategy.

MATERIALS AND METHODS

A hepatotoxicity interaction network of PM-D was constructed based on toxicity target prediction for eight key toxic ingredients and a hepatotoxicity target collection. Then the key signaling pathways were enriched, and molecular docking verification was implemented to evaluate the ability of toxic ingredients to bind to the core targets. The pathological changes of liver tissues and serum biochemical assays of mice were used to evaluate the liver injury effect of mice with oral administration of PM-D. Furthermore, spatially resolved metabolomics was used to visualize significant differences in metabolic profiles in mice after drug administration, to screen hepatotoxicity-related biomarkers and analyze metabolic pathways.

RESULTS

The contents of four key toxic compounds in PM-D were detected. Network toxicology identified 30 potential targets of liver toxicity of PM-D. GO and KEGG enrichment analyses indicated that the hepatotoxicity of PM-D involved multiple biological activities, including cellular response to endogenous stimulus, organonitrogen compound metabolic process, regulation of the apoptotic process, regulation of kinase, regulation of reactive oxygen species metabolic process and signaling pathways including PI3K-Akt, AMPK, MAPK, mTOR, Ras and HIF-1. The molecular docking confirmed the high binding activity of 8 key toxic ingredients with 10 core targets, including mTOR, PIK3CA, AKT1, and EGFR. The high distribution of metabolites of PM-D in the liver of administrated mice was recognized by mass spectrometry imaging. Spatially resolved metabolomics results revealed significant changes in metabolic profiles after PM-D administration, and metabolites such as taurine, taurocholic acid, adenosine, and acyl-carnitines were associated with PM-D-induced liver injury. Enrichment analyses of metabolic pathways revealed tht linolenic acid and linoleic acid metabolism, carnitine synthesis, oxidation of branched-chain fatty acids, and six other metabolic pathways were significantly changed. Comprehensive analysis revealed that the hepatotoxicity caused by PM-D was closely related to cholestasis, mitochondrial damage, oxidative stress and energy metabolism, and lipid metabolism disorders.

CONCLUSIONS

In this study, the hepatotoxicity mechanisms of PM-D were comprehensively identified through an integrated spatially resolved metabolomics and network toxicology strategy, providing a theoretical foundation for the toxicity mechanisms of PM and its safe clinical application.

Preliminary study to classify mechanisms of mitochondrial toxicity by in vitro metabolomics and bioinformatics

AIM

Mitochondrial toxicity is one of the causes for drug-induced liver injury, and the classification of phenotypes or mitochondrial toxicity are highly required though there are no molecular-profiling approaches for classifying mitochondrial toxicity. Therefore, the aim of this study was to classify the mechanisms of mitochondrial toxicity by metabolic profiling in vitro and bioinformatics.

MAIN METHODS

We applied an established gas chromatography tandem mass spectrometry-based metabolomics to human hepatoma grade 2 (HepG2) cells that were exposed to mitochondrial toxicants, whose mechanisms are different, such as rotenone (0.1 μM), carbonyl cyanide-3-chlorophenylhydrazone (CCCP, 0.5 μM), nefazodone (20 μM), perhexiline (6.25 μM), or digitonin (positive cytotoxic substance, 4 μM). These concentrations were determined by the Mitochondrial ToxGlo Assay. Galactose medium was used for suppressing the Warburg effect in HepG2 cells, and the metabolome analysis successfully identified 125 metabolites in HepG2 cells. Multivariate, metabolic pathway and network analyses were performed by the R software.

KEY FINDINGS

Metabolic profiling enabled the classifying the mitochondrial toxicity mechanisms of RCC inhibition and uncoupling. The metabolic profiles of respiratory chain complex (RCC) inhibitors (rotenone and nefazodone) and an uncoupler (CCCP) were fully differentiated from those of other compounds. The metabolic pathway analysis revealed that the RCC inhibitors and the uncoupler mainly disrupted TCA-cycle and related metabolic pathways. In addition, the correlation-based network analysis revealed that succinic acid, β-alanine, and glutamic acid were potential metabolic indicators for RCC inhibition and uncoupling.

SIGNIFICANCE

Our results provided new insights into classifying mechanisms of mitochondrial toxicity by in vitro metabolomics.

The serum acylcarnitines profile in epileptic children treated with valproic acid and the protective roles of peroxisome proliferator-activated receptor a activation in valproic acid-induced liver injury

Valproic acid (VPA) is widely used as a major drug in the treatment of epilepsy. Despite the undisputed pharmacological importance and effectiveness of VPA, its potential hepatotoxicity is still a major concern. Being a simple fatty acid, the hepatotoxicity induced by VPA has long been considered to be due primarily to its interference with fatty acid β-oxidation (β-FAO). The aim of this study was to investigate the biomarkers for VPA-induced abnormal liver function in epileptic children and to determine potential mechanisms of its liver injury. Targeted metabolomics analysis of acylcarnitines (ACs) was performed in children's serum. Metabolomic analysis revealed that VPA -induced abnormal liver function resulted in the accumulation of serum long-chain acylcarnitines (LCACs), and the reduced expression of β-FAO relevant genes (Carnitine palmitoyltrans-ferase (CPT)1, CPT2 and Long-chain acyl-CoA dehydrogenase (LCAD)), indicating the disruption of β-FAO. As direct peroxisome proliferator-activated receptor a (PPARα)- regulated genes, CPT1A, CPT2 and LCAD were up-regulated after treatment with PPARα agonist, fenofibrate (Feno), indicating the improvement of β-FAO. Feno significantly ameliorated the accumulation of various lipids in the plasma of VPA-induced hepatotoxic mice by activating PPARα, significantly reduced the plasma ACs concentration, and attenuated VPA-induced hepatic steatosis. Enhanced oxidative stress and induced by VPA exposure were significantly recovered using Feno treatment. In conclusion, this study indicates VPA-induced β-FAO disruption might lead to liver injury, and a significant Feno protective effect against VPA -induced hepatotoxicity through reversing fatty acid metabolism.

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.

From single-omics to interactomics: How can ligand-induced perturbations modulate single-cell phenotypes?

Cells suffer from perturbations by different stimuli, which, consequently, rise to individual alterations in their profile and function that may end up affecting the tissue as a whole. This is no different if we consider the effect of a therapeutic agent on a biological system. As cells are exposed to external ligands their profile can change at different single-omics levels. Detecting how these changes take place through different sequencing technologies is key to a better understanding of the effects of therapeutic agents. Single-cell RNA-sequencing stands out as one of the most common approaches for cell profiling and perturbation analysis. As a result, single-cell transcriptomics data can be integrated with other omics data sources, such as proteomics and epigenomics data, to clarify the perturbation effects and mechanism at the cell level. Appropriate computational tools are key to process and integrate the available information. This chapter focuses on the recent advances on ligand-induced perturbation and single-cell omics computational tools and algorithms, their current limitations, and how the deluge of data can be used to improve the current process of drug research and development.

Probing the metabolism of γ-glutamyl peptides in cyanobacteria via metabolite profiling and 13 C labeling

Cyanobacteria are attractive model organisms for the study of photosynthesis and diurnal metabolism and as hosts for photoautotrophic production of chemicals. Exposure to bright light or environmental pollutants and a diurnal lifestyle of these prokaryotes may result in significant oxidative stress. Glutathione is a widely studied γ-glutamyl peptide that plays a key role in managing oxidative stress and detoxification of xenobiotics in cyanobacteria. The functional role and biosynthesis pathways of this tripeptide have been studied in detail in various phyla, including cyanobacteria. However, other γ-glutamyl peptides remain largely unexplored. We use an integrated approach to identify a number of γ-glutamyl peptides based on signature mass fragments and mass shifts in them in ¹³ C and ¹⁵ N enriched metabolite extracts. The newly identified compounds include γ-glutamyl dipeptides and derivatives of glutathione. Carbon backbones of the former turn over much faster than that of glutathione, suggesting that they follow a distinct biosynthesis pathway. Further, transients of isotopic ¹³ C enrichment show positional labeling in these peptides, which allows us to delineate the alternative biosynthesis pathways. Importantly, the amino acid of γ-glutamyl dipeptides shows much faster turnover compared to the glutamate moiety. The significant accumulation of γ-glutamyl dipeptides under slow-growth conditions combined with the results from dynamic ¹³ C labeling suggests that these compounds may act as reservoirs of amino acids in cyanobacteria.

Untargeted metabolomic study of HepG2 cells under the effect of Fucus vesiculosus aqueous extract

RATIONALE

Fucus vesiculosus has been described with potential to develop functional foods containing bioactive compounds against various diseases. However, more studies are needed to better understand its functioning and its previously reported bioactivities, mainly at the molecular level.

METHODS

An untargeted metabolomic study was performed to analyse HepG2 cells exposed to F. vesiculosus aqueous extract, rich in phlorotannins and peptides, during 24 h. This study was carried out using liquid chromatography combined with high-resolution tandem mass spectrometry.

RESULTS

This metabolomic study showed significant changes in HepG2 metabolites in the presence of the extract, standing out being the increased intensity of various fatty acid amides (oleamide, (Z)-eicos-11-enamide, linoleamide, palmitamide, dodecanamide and stearamide). This group of metabolites is reported in the literature with anticancer and hypocholesterolemic activity, bioactivities also described for F. vesiculosus. The extract induced, likewise, the expression of glutathione indicating its antioxidant effect.

CONCLUSIONS

This study demonstrated the potential of the compounds present in the F. vesiculosus aqueous extract for the development of natural drugs, nutraceuticals or dietary supplements, justified at the molecular level by changes in cell metabolites related to anticancer and hypocholesterolemic activity. The results here described, using an untargeted metabolomic approach, may contribute to a better understanding of algal behaviour, when used as food, in health-promoting effects.

Factors that influence the quality of metabolomics data in in vitro cell toxicity studies: a systematic survey

REACH (Registration, Evaluation, Authorization and Restriction of Chemicals) is a global strategy and regulation policy of the EU that aims to improve the protection of human health and the environment through the better and earlier identification of the intrinsic properties of chemical substances. It entered into force on 1st June 2007 (EC 1907/2006). REACH and EU policies plead for the use of robust high-throughput "omic" techniques for the in vitro investigation of the toxicity of chemicals that can provide an estimation of their hazards as well as information regarding the underlying mechanisms of toxicity. In agreement with the 3R's principles, cultured cells are nowadays widely used for this purpose, where metabolomics can provide a real-time picture of the metabolic effects caused by exposure of cells to xenobiotics, enabling the estimations about their toxicological hazards. High quality and robust metabolomics data sets are essential for precise and accurate hazard predictions. Currently, the acquisition of consistent and representative metabolomic data is hampered by experimental drawbacks that hinder reproducibility and difficult robust hazard interpretation. Using the differentiated human liver HepG2 cells as model system, and incubating with hepatotoxic (acetaminophen and valproic acid) and non-hepatotoxic compounds (citric acid), we evaluated in-depth the impact of several key experimental factors (namely, cell passage, processing day and storage time, and compound treatment) and instrumental factors (batch effect) on the outcome of an UPLC-MS metabolomic analysis data set. Results showed that processing day and storage time had a significant impact on the retrieved cell's metabolome, while the effect of cell passage was minor. Meta-analysis of results from pathway analysis showed that batch effect corrections and quality control (QC) measures are critical to enable consistent and meaningful estimations of the effects caused by compounds on cells. The quantitative analysis of the changes in metabolic pathways upon bioactive compound treatment remained consistent despite the concurrent causes of metabolomic data variation. Thus, upon appropriate data retrieval and correction and by an innovative metabolic pathway analysis, the metabolic alteration predictions remained conclusive despite the acknowledged sources of variability.

Toxicometabolomics: Small Molecules to Answer Big Toxicological Questions

Given the high biological impact of classical and emerging toxicants, a sensitive and comprehensive assessment of the hazards and risks of these substances to organisms is urgently needed. In this sense, toxicometabolomics emerged as a new and growing field in life sciences, which use metabolomics to provide new sets of susceptibility, exposure, and/or effects biomarkers; and to characterize in detail the metabolic responses and altered biological pathways that various stressful stimuli cause in many organisms. The present review focuses on the analytical platforms and the typical workflow employed in toxicometabolomic studies, and gives an overview of recent exploratory research that applied metabolomics in various areas of toxicology.

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.

Metabolomic analysis to discriminate drug-induced liver injury (DILI) phenotypes

Drug-induced liver injury (DILI) is an adverse toxic hepatic clinical reaction associated to the administration of a drug that can occur both at early clinical stages of drug development, as well after normal clinical usage of approved drugs. Because of its unpredictability and clinical relevance, it is of medical concern. Three DILI phenotypes (hepatocellular, cholestatic, and mixed) are currently recognized, based on serum alanine aminotransferase (ALT) and alkaline phosphatase (ALP) values. However, this classification lacks accuracy to distinguish among the many intermediate mixed types, or even to estimate the magnitude and progression of the injury. It was found desirable to have additional elements for better evaluation criteria of DILI. With this aim, we have examined the serum metabolomic changes occurring in 79 DILI patients recruited and monitored using established clinical criteria, along the course of the disease and until recovery. Results revealed that free and conjugated bile acids, and glycerophospholipids were among the most relevant metabolite classes for DILI phenotype characterization. Using an ensemble of PLS-DA models, metabolomic information was integrated into a ternary diagram to display the disease phenotype, the severity of the liver damage, and its progression. The modeling implemented and the use of such compiled information in an easily understandable and visual manner facilitates a straightforward DILI phenotyping and allow to monitor its progression and recovery prediction, usefully complementing the concise information drawn out by the ALT and ALP classification.

The Antipsychotic Risperidone Alters Dihydroceramide and Ceramide Composition and Plasma Membrane Function in Leukocytes In Vitro and In Vivo

Atypical or second-generation antipsychotics are used in the treatment of psychosis and behavioral problems in older persons with dementia. However, these pharmaceutical drugs are associated with an increased risk of stroke in such patients. In this study, we evaluated the effects of risperidone treatment on phospholipid and sphingolipid composition and lipid raft function in peripheral blood mononuclear cells (PBMCs) of older patients (mean age >88 years). The results showed that the levels of dihydroceramides, very-long-chain ceramides, and lysophosphatidylcholines decreased in PBMCs of the risperidone-treated group compared with untreated controls. These findings were confirmed by in vitro assays using human THP-1 monocytes. The reduction in the levels of very-long-chain ceramides and dihydroceramides could be due to the decrease in the expression of fatty acid elongase 3, as observed in THP-1 monocytes. Moreover, risperidone disrupted lipid raft domains in the plasma membrane of PBMCs. These results indicated that risperidone alters phospholipid and sphingolipid composition and lipid raft domains in PBMCs of older patients, potentially affecting multiple signaling pathways associated with these membrane domains.

Untargeted LC-MS based metabolomic profiling of iPAMs to investigate lipid metabolic pathways alternations induced by different Pseudorabies virus strains

Owing to viral recombination, interspecies transmission, and evolution, variant pseudorabies virus (PRV) strains exhibit different biological characteristics and pathogenicity. To improve the understanding of common and specific metabolic changes that occur upon infection by different PRV strains, we herein describe the comprehensive analysis of metabolites of PRV vaccine strain (Bartha K61), classical strain (EA) and variant strain (HNX) infection in immortalized porcine alveolar macrophage cells. Compared with uninfected cells, cells infected with Bartha K61, EA and HNX had 246, 225, and 272 differing metabolites, respectively. In the three types of PRV-strain-infected cells, lipids and lipid-like molecules accounted for over 50 % of the altered metabolites. As these viruses are enveloped, viral replication, assembly and release occur on cellular membranes primed through the manipulation of the host metabolism. We analyzed the potential relationship between virus replication and the virus-mediated host metabolism. Our study resulted in the first reconstruction of the major lipid metabolic pathways involved in PRV infection, including those of glycerophospholipids, sphingolipids, glycerolipids, and fatty acyls. In addition, the metabolic perturbations caused by different PRV strain infections are consistent across many species, however, our results also revealed many specific metabolic alterations during HNX infection, such as the enrichment of phosphatidylinositol and 15R-PGE2 methyl ester 15-acetate, and the diminishment of phosphatidylethanolamine, phosphatidic acid, and ceramides. These strain-specific altered metabolites may be linked to the unique biological characteristics and pathogenicity of the HNX strain.

UPLC-orbitrap-MS-based metabolic profiling of HaCaT cells exposed to withanolides extracted from Datura metel.L: Insights from an untargeted metabolomics

In recent decades, more and more attention to the withanolides extracted from Datura metel.L has been paid due to their anti-psoriatic effects. Withanolides have also been reported to exhibit anti-inflammatory and anti-proliferative properties. Thus, withanolides have been considered as a promising candidate of anti-psoriatic drug. The aim of this study was to investigated the metabolic network of HaCaT cells after exposure to withanolides to identify anti-psoriatic mechanism induced by withanolides on skin cells. In this experiment, our results demonstrated that exposure to withanolides at concentrations beyond 50 μg/mL inhibited cell proliferation and induced cell apoptosis in a dose-dependent manner. In addition, withanolides-induced reactive oxygen species (ROS) generation and mitochondrial depolarization in HaCaT cells. In this research, ultra-high performance liquid chromatography coupled with orbitrap mass spectrometry (UPLC-orbitrap-MS) method was applied to profile metabolite changes in HaCaT cells exposed to withanolides. In total, significant variations in 38 differential metabolites were identified between withanolides exposure and untreated groups. The exposure of HaCaT cells to withanolides at the dose of 200 μg/mL for 24 h was revealed by the disturbance of energy metabolism, amino acid metabolism, lipid metabolism and nucleic acid metabolism. UPLC-orbitrap-MS-based cell metabolomics provided a comprehensive method for the identification of withanolides' anti-psoriasis mechanisms in vitro. And above metabolic disorders also reflected potential therapeutic targets for treating psoriasis.

High-Content Screening for the Detection of Drug-Induced Oxidative Stress in Liver Cells

Drug-induced liver injury (DILI) remains a major cause of drug development failure, post-marketing warnings and restriction of use. An improved understanding of the mechanisms underlying DILI is required for better drug design and development. Enhanced reactive oxygen species (ROS) levels may cause a wide spectrum of oxidative damage, which has been described as a major mechanism implicated in DILI. Several cell-based assays have been developed as in vitro tools for early safety risk assessments. Among them, high-content screening technology has been used for the identification of modes of action, the determination of the level of injury and the discovery of predictive biomarkers for the safety assessment of compounds. In this paper, we review the value of in vitro high-content screening studies and evaluate how to assess oxidative stress induced by drugs in hepatic cells, demonstrating the detection of pre-lethal mechanisms of DILI as a powerful tool in human toxicology.

Development of an LC-MS Targeted Metabolomics Methodology to Study Proline Metabolism in Mammalian Cell Cultures

A growing interest in metabolomics studies of cultured cells requires development not only untargeted methods capable of fingerprinting the complete metabolite profile but also targeted methods enabling the precise and accurate determination of a selected group of metabolites. Proline metabolism affects many crucial processes at the cellular level, including collagen biosynthesis, redox balance, energetic processes as well as intracellular signaling. The study aimed to develop a robust and easy-to-use targeted metabolomics method for the determination of the intracellular level of proline and the other two amino acids closely related to proline metabolism: glutamic acid and arginine. The method employs hydrophilic interaction liquid chromatography followed by high-resolution, accurate-mass mass spectrometry for reliable detection and quantification of the target metabolites in cell lysates. The sample preparation consisted of quenching by the addition of ice-cold methanol and subsequent cell scraping into a quenching solution. The method validation showed acceptable linearity (r > 0.995), precision (%RSD < 15%), and accuracy (88.5–108.5%). Pilot research using HaCaT spontaneously immortalized human keratinocytes in a model for wound healing was performed, indicating the usefulness of the method in studies of disturbances in proline metabolism. The developed method addresses the need to determine the intracellular concentration of three key amino acids and can be used routinely in targeted mammalian cell culture metabolomics research.

Metabolomic Approaches to Study Chemical Exposure-Related Metabolism Alterations in Mammalian Cell Cultures

Biological organisms are constantly exposed to an immense repertoire of molecules that cover environmental or food-derived molecules and drugs, triggering a continuous flow of stimuli-dependent adaptations. The diversity of these chemicals as well as their concentrations contribute to the multiplicity of induced effects, including activation, stimulation, or inhibition of physiological processes and toxicity. Metabolism, as the foremost phenotype and manifestation of life, has proven to be immensely sensitive and highly adaptive to chemical stimuli. Therefore, studying the effect of endo- or xenobiotics over cellular metabolism delivers valuable knowledge to apprehend potential cellular activity of individual molecules and evaluate their acute or chronic benefits and toxicity. The development of modern metabolomics technologies such as mass spectrometry or nuclear magnetic resonance spectroscopy now offers unprecedented solutions for the rapid and efficient determination of metabolic profiles of cells and more complex biological systems. Combined with the availability of well-established cell culture techniques, these analytical methods appear perfectly suited to determine the biological activity and estimate the positive and negative effects of chemicals in a variety of cell types and models, even at hardly detectable concentrations. Metabolic phenotypes can be estimated from studying intracellular metabolites at homeostasis in vivo, while in vitro cell cultures provide additional access to metabolites exchanged with growth media. This article discusses analytical solutions available for metabolic phenotyping of cell culture metabolism as well as the general metabolomics workflow suitable for testing the biological activity of molecular compounds. We emphasize how metabolic profiling of cell supernatants and intracellular extracts can deliver valuable and complementary insights for evaluating the effects of xenobiotics on cellular metabolism. We note that the concepts and methods discussed primarily for xenobiotics exposure are widely applicable to drug testing in general, including endobiotics that cover active metabolites, nutrients, peptides and proteins, cytokines, hormones, vitamins, etc.

Fast and ergonomic extraction of adherent mammalian cells for NMR-based metabolomics studies

Cellular metabolomics has become key to elucidate mechanistic aspects in various fields such as cancerology or pharmacology, and is rapidly becoming a standard phenotyping tool accessible to the broad biological community. Acquisition of reliable spectroscopic datasets, such as nuclear magnetic resonance (NMR) spectra, to characterize biological systems depends on the elaboration of robust methods for cellular metabolites extraction. Previous studies have addressed many issues raised by these protocols, however with little pondering on ergonomic and practical aspects of the methods that impact their scalability, reproducibility and hence their suitability to high-throughput studies or their use by non-metabolomics experts. Here, we optimize a fast and ergonomic protocol for extraction of metabolites from adherent mammalian cells for NMR metabolomics studies. The proposed extraction protocol, including cell washing, metabolism quenching and actual extraction of intracellular metabolites, was first optimized on HeLa cells. Efficiency of the protocol, in its globality and for the different individual steps, was assessed by NMR quantification of 27 metabolites from cellular extracts. We show that a single PBS wash provides a seemly compromise between contamination from growth medium and leakage of intracellular metabolites. In HeLa cells, extraction using pure methanol, without cell scraping, recovered a higher amount of intracellular metabolites than the reference methanol/water/chloroform method with cell scraping, with yields varying across metabolite classes. Optimized and reference protocols were further tested on eight cell lines of miscellaneous nature, and inter-operator reproducibility was demonstrated. Our results stress the need for tailored extraction protocols and show that fast protocols minimizing time-consuming steps, without compromising extraction yields, are suitable for high-throughput metabolomics studies. Graphical abstract.

Qualitative and quantitative detection of liver injury with terahertz time-domain spectroscopy

Terahertz technology has been widely used as a nondestructive and effective detection method. Herein, terahertz time-domain spectroscopy was used to detect drug-induced liver injury in mice. Firstly, the boxplots were used to detect abnormal data. Then the maximal information coefficient method was used to search for the features strongly correlated with the degree of injury. After that, the liver injury model was built using the random forests method in machine learning. The results show that this method can effectively identify the degree of liver injury and thus provide an auxiliary diagnostic method for detecting minor liver injury.

Metabolomics in pharmacology - a delve into the novel field of pharmacometabolomics

Introduction: Pharmacometabolomics is an emerging science pursuing the application of precision medicine. Combining both genetic and environmental factors, the so-called pharmacometabolomic approach guides patient selection and stratification in clinical trials and optimizes personalized drug dosage, improving efficacy and safety.Areas covered: This review illustrates the progressive introduction of pharmacometabolomics as an innovative solution for enhancing the discovery of novel drugs and improving research and development (R&D) productivity of the pharmaceutical industry. An extended analysis on published pharmacometabolomics studies both in animal models and humans includes results obtained in several areas such as hepatology, gastroenterology, nephrology, neuropsychiatry, oncology, drug addiction, embryonic cells, neonatology, and microbiomics.Expert opinion: a tailored, individualized therapy based on the optimization of pharmacokinetics and pharmacodynamics, the improvement of drug efficacy, and the abolition of drug toxicity and adverse drug reactions is a key issue in precision medicine. Genetics alone has become insufficient for deciphring intra- and inter-individual variations in drug-response, since they originate both from genetic and environmental factors, including human microbiota composition. The association between pharmacogenomics and pharmacometabolomics may be considered the new strategy for an in-deep knowledge on changes and alterations in human and microbial metabolic pathways due to the action of a drug.

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.

Glutamine/glutamate metabolism rewiring in reprogrammed human hepatocyte-like cells

Human dermal fibroblasts can be reprogrammed into hepatocyte-like (HEP-L) cells by the expression of a set of transcription factors. Yet, the metabolic rewiring suffered by reprogrammed fibroblasts remains largely unknown. Here we report, using stable isotope-resolved metabolic analysis in combination with metabolomic-lipidomic approaches that HEP-L cells mirrors glutamine/glutamate metabolism in primary cultured human hepatocytes that is very different from parental human fibroblasts. HEP-L cells diverge glutamine from multiple metabolic pathways into deamidation and glutamate secretion, just like periportal hepatocytes do. Exceptionally, glutamine contribution to lipogenic acetyl-CoA through reductive carboxylation is increased in HEP-L cells, recapitulating that of primary cultured human hepatocytes. These changes can be explained by transcriptomic rearrangements of genes involved in glutamine/glutamate metabolism. Although metabolic changes in HEP-L cells are in line with reprogramming towards the hepatocyte lineage, our conclusions are limited by the fact that HEP-L cells generated do not display a complete mature phenotype. Nevertheless, our findings are the first to characterize metabolic adaptation in HEP-L cells that could ultimately be targeted to improve fibroblasts direct reprogramming to HEP-L cells.

Butyrate prevents valproate-induced liver injury: In vitro and in vivo evidence

Sodium valproate (VPA), an antiepileptic drug, may cause dose- and time-dependent hepatotoxicity. However, its iatrogenic molecular mechanism and the rescue therapy are disregarded. Recently, it has been demonstrated that sodium butyrate (NaB) reduces hepatic steatosis, improving respiratory capacity and mitochondrial dysfunction in obese mice. Here, we investigated the protective effect of NaB in counteracting VPA-induced hepatotoxicity using in vitro and in vivo models. Human HepG2 cells and primary rat hepatocytes were exposed to high VPA concentration and treated with NaB. Mitochondrial function, lipid metabolism, and oxidative stress were evaluated, using Seahorse analyzer, spectrophotometric, and biochemical determinations. Liver protection by NaB was also evaluated in VPA-treated epileptic WAG/Rij rats, receiving NaB for 6 months. NaB prevented VPA toxicity, limiting cell oxidative and mitochondrial damage (ROS, malondialdehyde, SOD activity, mitochondrial bioenergetics), and restoring fatty acid oxidation (peroxisome proliferator-activated receptor α expression and carnitine palmitoyl-transferase activity) in HepG2 cells, primary hepatocytes, and isolated mitochondria. In vivo, NaB confirmed its activity normalizing hepatic biomarkers, fatty acid metabolism, and reducing inflammation and fibrosis induced by VPA. These data support the protective potential of NaB on VPA-induced liver injury, indicating it as valid therapeutic approach in counteracting this common side effect due to VPA chronic treatment.

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.

1H-NMR metabolomics reveals the Glabrescione B exacerbation of glycolytic metabolism beside the cell growth inhibitory effect in glioma

BACKGROUND

Glioma is the most common and primary brain tumors in adults. Despite the available multimodal therapies, glioma patients appear to have a poor prognosis. The Hedgehog (Hh) signaling is involved in tumorigenesis and emerged as a promising target for brain tumors. Glabrescione B (GlaB) has been recently identified as the first direct inhibitor of Gli1, the downstream effector of the pathway.

METHODS

We established the overexpression of Gli1 in murine glioma cells (GL261) and GlaB effect on cell viability. We used ¹H-nuclear magnetic resonance (NMR) metabolomic approach to obtain informative metabolic snapshots of GL261 cells acquired at different time points during GlaB treatment. The activation of AMP activated protein Kinase (AMPK) induced by GlaB was established by western blot. After the orthotopic GL261 cells injection in the right striatum of C57BL6 mice and the intranasal (IN) GlaB/mPEG_5kDa-Cholane treatment, the tumor growth was evaluated. The High Performance Liquid Chromatography (HPLC) combined with Mass Spectrometry (MS) was used to quantify GlaB in brain extracts of treated mice.

RESULTS

We found that GlaB affected the growth of murine glioma cells both in vitro and in vivo animal model. Using an untargeted ¹H-NMR metabolomic approach, we found that GlaB stimulated the glycolytic metabolism in glioma, increasing lactate production. The high glycolytic rate could in part support the cytotoxic effects of GlaB, since the simultaneous blockade of lactate efflux with α-cyano-4-hydroxycinnamic acid (ACCA) affected glioma cell growth. According to the metabolomic data, we found that GlaB increased the phosphorylation of AMPK, a cellular energy sensor involved in the anabolic-to-catabolic transition.

CONCLUSIONS

Our results indicate that GlaB inhibits glioma cell growth and exacerbates Warburg effect, increasing lactate production. In addition, the simultaneous blockade of Gli1 and lactate efflux amplifies the anti-tumor effect in vivo, providing new potential therapeutic strategy for this brain tumor.

Three-Dimensional Leukemia Co-Culture System for In Vitro High-Content Metabolomics Screening

Metabolomics is increasingly applied to investigate different individuals and time-dependent responses to environmental stimuli. Rapid data acquisition and improved detection limits of direct infusion mass spectrometry (DIMS) are paving the way for applications of metabolomics in preclinical screening, opening new opportunities in drug discovery and personalized medicine. Three-dimensional (3D) cell culture systems, which mimic the in vivo cell microenvironment, are well recognized as tissue and organ substitutes. Here, we investigated cell viability and induction of reactive oxygen species (ROS) in stromal cells cultured in various 3D systems as well as the standard monolayer culture to evaluate which system provides the most favorable growing conditions. The selected 3D system was then tested for use in 3D co-culture of leukemia and stromal cells for DIMS-based high-throughput/high-content metabolic drug screens. The NanobioMatrix-poly(ε-caprolactone) (NBM-PCL) scaffold resulted in the lowest ROS production, supported rapid cell proliferation, and was suitable for the 96- and 384-well plate formats. Doxorubicin treatment in leukemia co-cultured with stromal cells induced some unique metabolic responses that drastically differed from those observed in leukemia cells alone. The DIMS results also showed that the drug-induced metabolic modulations in both normal and cancer cells were weakened by co-culturing even at high treatment doses, thereby demonstrating the value of the 3D co-culture high-content metabolic drug screen. In conclusion, we optimized a high sample throughput method for 3D co-culture with a DIMS-based high-content metabolic drug screen and drug development.

Hair Metabolomics in Animal Studies and Clinical Settings

Metabolomics is a powerful tool used to understand comprehensive changes in the metabolic response and to study the phenotype of an organism by instrumental analysis. It most commonly involves mass spectrometry followed by data mining and metabolite assignment. For the last few decades, hair has been used as a valuable analytical sample to investigate retrospective xenobiotic exposure as it provides a wider window of detection than other biological samples such as saliva, plasma, and urine. Hair contains functional metabolomes such as amino acids and lipids. Moreover, segmental analysis of hair based on its growth rate can provide information on metabolic changes over time. Therefore, it has great potential as a metabolomics sample to monitor chronic diseases, including drug addiction or abnormal conditions. In the current review, the latest applications of hair metabolomics in animal studies and clinical settings are highlighted. For this purpose, we review and discuss the characteristics of hair as a metabolomics sample, the analytical techniques employed in hair metabolomics and the consequence of hair metabolome alterations in recent studies. Through this, the value of hair as an alternative biological sample in metabolomics is highlighted.

Metabolomics and Cell Therapy in Diabetes Mellitus

Diabetes with a broad spectrum of complications has become a global epidemic metabolic disorder. Till now, several pharmaceutical and non-pharmaceutical therapeutic approaches were applied for its treatment. Cell-based therapies have become promising methods for diabetes treatment. Better understanding of diabetes pathogenesis and identification of its specific biomarkers along with evaluation of different treatments efficacy, can be possible by clarification of specific metabolic modifications during the diabetes progression. Subsequently, metabolomics technology can support this goal as an effective tool. The present review tried to show how metabolomics quantifications can be useful for diabetic monitoring before and after cell therapy. Cell therapy is an alternative approach to achieve diabetes treatments goals including insulin resistance amelioration, insulin independence reparation, and control of glycemia. OMICs approaches provide a comprehensive insight into the molecular mechanisms of cells features and functional mechanism of their genomics, transcriptomics, proteomics, and metabolomics profile which can be useful for their therapeutic application. As a modern technology for the detection and analysis of metabolites in biological samples, metabolomica can identify many of the metabolic and molecular pathways associated with diabetes and its following complications.

Different Toxic Effects of Racemate, Enantiomers, and Metabolite of Malathion on HepG2 Cells Using High-Performance Liquid Chromatography-Quadrupole-Time-of-Flight-Based Metabolomics

Commercial malathion is a racemic mixture that contains two enantiomers, and malathion has adverse effects on mammals. However, whether these two enantiomers have different effects on animals remains unclear. In this study, we tested the effect of racemate, enantiomers, and metabolite of malathion on the metabolomics profile of HepG2 cells. HepG2 cells showed distinct metabolic profiles when treated with rac-malathion, malaoxon, R-(+)-malathion, and S-(-)-malathion, and these differences were attributed to pathways in amino acid metabolism, oxidative stress, and inflammatory response. In addition, malathion treatment caused changes in amino acid levels, antioxidant activity, and expression of inflammatory genes in HepG2 cells. S-(-)-Malathion exhibited stronger metabolic perturbation than its enantiomer and racemate, consistent with the high level of cytotoxicity of S-(-)malathion. R-(+)-Malathion treatment caused significant oxidative stress in HepG2 cells but induced a weaker disturbance in the amino acid metabolism and a pro-inflammatory response compared to S-(-)-malathion and rac-malathion. Malaoxon caused more significant perturbation on antioxidase and a stronger antiapoptosis effect than its parent malathion. Our results provide insight into the risk assessment of malathion enantiomers and metabolites. We also demonstrate that a metabolomics approach can identify the discrepancy of the toxic effects and underlying mechanisms for enantiomers and metabolites of chiral pesticides.

An Untargeted Metabolomics Approach to Investigate the Metabolic Modulations of HepG2 Cells Exposed to Low Doses of Bisphenol A and 17β-Estradiol

The model xeno-estrogen bisphenol A (BPA) has been extensively studied over the past two decades, contributing to major advances in the field of endocrine disrupting chemicals research. Besides its well documented adverse effects on reproduction and development observed in rodents, latest studies strongly suggest that BPA disrupts several endogenous metabolic pathways, with suspected steatogenic and obesogenic effects. BPA's adverse effects on reproduction are attributed to its ability to activate estrogen receptors (ERs), but its effects on metabolism and its mechanism(s) of action at low doses are so far only marginally understood. Metabolomics based approaches are increasingly used in toxicology to investigate the biological changes induced by model toxicants and chemical mixtures, to identify markers of toxicity and biological effects. In this study, we used proton nuclear magnetic resonance (1H-NMR) based untargeted metabolite profiling, followed by multivariate statistics and computational analysis of metabolic networks to examine the metabolic modulation induced in human hepatic cells (HepG2) by an exposure to low and very low doses of BPA (10-6M, 10-9M, and 10-12M), vs. the female reference hormone 17β-estradiol (E2, 10-9M, 10-12M, and 10-15M). Metabolomic analysis combined to metabolic network reconstruction highlighted different mechanisms at lower doses of exposure. At the highest dose, our results evidence that BPA shares with E2 the capability to modulate several major metabolic routes that ensure cellular functions and detoxification processes, although the effects of the model xeno-estrogen and of the natural hormone can still be distinguished.

Paeonol exhibits anti-tumor effects by apoptotic and anti-inflammatory activities in 7,12-dimethylbenz(a)anthracene induced oral carcinogenesis

We investigated the preventive potential of paeonol on 7,12-dimethylbenz(a)anthracene (DMBA) induced oral carcinogenesis. Oral tumors were developed in the buccal pouches of Syrian golden hamsters using topical application of 0.5% DMBA three times/week for 10 weeks. DMBA treated hamsters developed hyperplasia, dysplasia and well-differentiated squamous cell carcinoma. The animals also exhibited increased lipid oxidation, decreased antioxidant status and altered levels of detoxification agents. Paeonol treatment of DMBA treated hamsters for 14 weeks decreased tumor incidence, volume and burden Paeonol treatment also increased antioxidant activity and decreased lipid oxidation to near normal levels. Histomorphology and the expression patterns of mutant p53, cyclo-oxygenase (COX-2) and caspase-9 were investigated in the oral buccal mucosa. Paeonol exhibited protective effects against DMBA induced oral carcinogenesis owing to its antitumor, antioxidant, anti-inflammatory and apoptosis inducing properties.

Metabolomics study of early metabolic changes in hepatic HepaRG cells in response to rosemary diterpenes exposure

Rosemary diterpenes have demonstrated diverse biological activities, such as anti-cancer, antiinflammatory, as well as other beneficial effects against neurological and metabolic disorders. In particular, carnosic acid (CA), carnosol (CS) and rosmanol (RS) diterpenes have shown interesting results on anti-cancer activity. However, little is known about the toxic effects of rosemary diterpenes at the concentrations needed to exert their antiproliferative effect on cancer cells. In our study, CA, CS and RS exhibited a concentration-dependent effect on cell viability of two human colon cancer cell lines (HT-29 and HCT116) after 24 h exposure. HT-29 cell line was more resistant to the inhibitory effect of the three diterpenes than HCT116 cell line. Among the three diterpenes, RS exerted the strongest effect in both cell lines. To investigate the hepatotoxicity of CA, CS and RS, undifferentiated and differentiated HepaRG cells were exposed to increasing concentrations of the diterpenes (from 10 to 100 μM). Differentiated cells were found to be more resistant to the toxic activity of the three diterpenes than undifferentiated HepaRG, probably related to a higher detoxifying function of differentiated HepaRG cells compared with the undifferentiated cells. The metabolic profiles of differentiated HepaRG cells in response to CA, CS and RS were examined to determine biochemical alterations and deepen the study of the effects of rosemary phenolic diterpenes at molecular level. A multiplatform metabolomics study based on liquid- and gas-chromatography hyphenated to high resolution mass spectrometry revealed that rosemary diterpenes exerted different effects when HepaRG cells were treated with the same concentration of each diterpene. RS revealed a greater metabolome alteration followed by CS and CA, in agreement with their observed cytotoxicity. Metabolomics provided valuable information about early events in the metabolic profiles after the treatment with the investigated diterpenes from rosemary.

Experimental design and reporting standards for metabolomics studies of mammalian cell lines

Metabolomics is an analytical technique that investigates the small biochemical molecules present within a biological sample isolated from a plant, animal, or cultured cells. It can be an extremely powerful tool in elucidating the specific metabolic changes within a biological system in response to an environmental challenge such as disease, infection, drugs, or toxins. A historically difficult step in the metabolomics pipeline is in data interpretation to a meaningful biological context, for such high-variability biological samples and in untargeted metabolomics studies that are hypothesis-generating by design. One way to achieve stronger biological context of metabolomic data is via the use of cultured cell models, particularly for mammalian biological systems. The benefits of in vitro metabolomics include a much greater control of external variables and no ethical concerns. The current concerns are with inconsistencies in experimental procedures and level of reporting standards between different studies. This review discusses some of these discrepancies between recent studies, such as metabolite extraction and data normalisation. The aim of this review is to highlight the importance of a standardised experimental approach to any cultured cell metabolomics study and suggests an example procedure fully inclusive of information that should be disclosed in regard to the cell type/s used and their culture conditions. Metabolomics of cultured cells has the potential to uncover previously unknown information about cell biology, functions and response mechanisms, and so the accurate biological interpretation of the data produced and its ability to be compared to other studies should be considered vitally important.

Prediction of liver toxicity and mode of action using metabolomics in vitro in HepG2 cells

Liver toxicity is a leading systemic toxicity of drugs and chemicals demanding more human-relevant, high throughput, cost effective in vitro solutions. In addition to contributing to animal welfare, in vitro techniques facilitate exploring and understanding the molecular mechanisms underlying toxicity. New ‘omics technologies can provide comprehensive information on the toxicological mode of action of compounds, as well as quantitative information about the multi-parametric metabolic response of cellular systems in normal and patho-physiological conditions. Here, we combined mass-spectroscopy metabolomics with an in vitro liver toxicity model. Metabolite profiles of HepG2 cells treated with 35 test substances resulted in 1114 cell supernatants and 3556 intracellular samples analyzed by metabolomics. Control samples showed relative standard deviations of about 10–15%, while the technical replicates were at 5–10%. Importantly, this procedure revealed concentration–response effects and patterns of metabolome changes that are consistent for different liver toxicity mechanisms (liver enzyme induction/inhibition, liver toxicity and peroxisome proliferation). Our findings provide evidence that identifying organ toxicity can be achieved in a robust, reliable, human-relevant system, representing a non-animal alternative for systemic toxicology.

PPARα activation protects against cholestatic liver injury

Intrahepatic cholestasis induced by drug toxicity, bile salt export pump (BSEP) deficiency, or pregnancy frequently causes cholestatic liver damage, which ultimately may lead to liver fibrosis and cirrhosis. Here, the preventive and therapeutic effects of peroxisome proliferator-activated receptor α (PPARα) signaling activated by fenofibrate was evaluated on cholestatic liver damage. Metabolomic analysis revealed that alpha-naphthyl isothiocyanate (ANIT)-induced intrahepatic cholestasis resulted in the accumulation of serum long-chain acylcarnitines and triglyceride, and the reduced expression of four fatty acid β-oxidation (β-FAO) relevant genes (Cpt1b, Cpt2, Mcad and Hadha), indicating the disruption of β-FAO. The increase of acylcarnitines in hepatic cell resulted in the enhanced expression of anti-oxidative genes glutathione S-transferases (Gsta2 and Gstm3) directly. As direct PPARα-regulated genes, Cpt1b, Cpt2, and Mcad were up-regulated after pretreatment with PPARα agonist, fenofibrate, indicating the improvement of β-FAO. In the end, the disrupted bile acid metabolism in the enterohepatic circulation and the enhanced oxidative stress and inflammation cytokines induced by ANIT exposure were significantly recovered with the improvement of β-FAO using fenofibrate treatment. These findings provide the rationale for the use of PPARα agonists as therapeutic alternatives for cholestatic liver damage.

A lipidomic cell-based assay for studying drug-induced phospholipidosis and steatosis

Phospholipidosis and steatosis are two toxic effects, which course with overaccumulation of different classes of lipids in the liver. MS-based lipidomics has become a powerful tool for the comprehensive determination of lipids. LC-MS lipid profiling of HepG2 cells is proposed as an in vitro assay to study and anticipate phospholipidosis and steatosis. Cells with and without preincubation with a mixture of free fatty acids (FFA; i.e. oleic and palmitic) were exposed to a set of well-known steatogenic and phospholipidogenic compounds. The use of FFA preloading accelerated the accumulation of phospholipids, thus leading to a better discrimination of phospholipidosis, and magnified the lipidomic alterations induced by steatogenic drugs. Phospholipidosis was characterized by increased levels of phosphatidylcholines, phosphatidylethanolamines, phosphatidylserines, and phosphatidylinositols, while steatosis induced alterations in FA oxidation and triacylglyceride (TG) synthesis pathways (with changes in the levels of FFA, acylcarnitines, monoacylglycerides, diacylglycerides, and TG). Interestingly, palmitic and oleic acids incorporation into lipids differed. A characteristic pattern was observed in the fold of change of particular TG species in the case of steatosis (TG(54:3) > TG(52:2) > TG(50:1) > TG(48:0)). Based on the levels of those lipids containing only palmitic and/or oleic acid moieties a partial least squares-discriminant analysis model was built, which showed good discrimination among nontoxic, phospholipidogenic and steatogenic compounds. In conclusion, it has been shown that the use of FFA preincubation together with intracellular LC-MS based lipid profiling could be a useful approach to identify the potential of drug candidates to induce phospholipidosis and/or steatosis.