Metabolomics in toxicology and preclinical research

Metabolomics in human SGBS cells as new approach method for studying adipogenic effects: Analysis of the effects of DINCH and MINCH on central carbon metabolism

Growing evidence suggests that exposure to certain metabolism-disrupting chemicals (MDCs), such as the phthalate plasticizer DEHP, might promote obesity in humans, contributing to the spread of this global health problem. Due to the restriction on the use of phthalates, there has been a shift to safer declared substitutes, including the plasticizer diisononyl-cyclohexane-1,2-dicarboxylate (DINCH). Notwithstanding, recent studies suggest that the primary metabolite monoisononyl-cyclohexane-1,2-dicarboxylic acid ester (MINCH), induces differentiation of human adipocytes and affects enzyme levels of key metabolic pathways. Given the lack of methods for assessing metabolism-disrupting effects of chemicals on adipose tissue, we used metabolomics to analyze human SGSB cells exposed to DINCH or MINCH. Concentration analysis of DINCH and MINCH revealed that uptake of MINCH in preadipocytes was associated with increased lipid accumulation during adipogenesis. Although we also observed intracellular uptake for DINCH, the solubility of DINCH in cell culture medium was limited, hampering the analysis of possible effects in the μM concentration range. Metabolomics revealed that MINCH induces lipid accumulation similar to peroxisome proliferator-activated receptor gamma (PPARG)-agonist rosiglitazone through upregulation of the pyruvate cycle, which was recently identified as a key driver of de novo lipogenesis. Analysis of the metabolome in the presence of the PPARG-inhibitor GW9662 indicated that the effect of MINCH on metabolism was mediated at least partly by a PPARG-independent mechanism. However, all effects of MINCH were only observed at high concentrations of 10 μM, which are three orders of magnitudes higher than the current concentrations of plasticizers in human serum. Overall, the assessment of the effects of DINCH and MINCH on SGBS cells by metabolomics revealed no adipogenic potential at physiologically relevant concentrations. This finding aligns with previous in vivo studies and supports the potential of our method as a New Approach Method (NAM) for the assessment of adipogenic effects of environmental chemicals.

Multivariate curve resolution-based data fusion approaches applied in 1H NMR metabolomic analysis of healthy cohorts

BACKGROUND

Metabolomics plays a critical role in deciphering metabolic alterations within individuals, demanding the use of sophisticated analytical methodologies to navigate its intricate complexity. While many studies focus on single biofluid types, simultaneous analysis of multiple matrices enhances understanding of complex biological mechanisms. Consequently, the development of data fusion methods enabling multiblock analysis becomes essential for comprehensive insights into metabolic dynamics.

RESULTS

This study introduces a novel guideline for jointly analyzing diverse metabolomic datasets (serum, urine, metadata) with a focus on metabolic differences between groups within a healthy cohort. The guideline presents two fusion strategies, 'Low-Level data fusion' (LLDF) and 'Mid-Level data fusion' (MLDF), employing a sequential application of Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS), linking the outcomes of successive analyses. MCR-ALS is a versatile method for analyzing mixed data, adaptable at various stages of data processing-encompassing resonance integration, data compression, and exploratory analysis. The LLDF and MLDF strategies were applied to 1H NMR spectral data extracted from urine and serum samples, coupled with biochemical metadata sourced from 145 healthy volunteers.

SIGNIFICANCE

Both methodologies effectively integrated and analysed multiblock datasets, unveiling the inherent data structure and variables associated with discernible factors among healthy cohorts. While both approaches successfully detected sex-related differences, the MLDF strategy uniquely revealed components linked to age. By applying this analysis, we aim to enhance the interpretation of intricate biological mechanisms and uncover variations that may not be easily discernible through individual data analysis.

Dynamic alterations in physiological and biochemical indicators of Cirrhinus mrigala hatchlings: A sublethal exposure of triclosan

Triclosan (TCS), a biocide used in various day-to-day products, has been associated with several toxic effects in aquatic organisms. In the present study, biochemical and hematological alterations were evaluated after 14 d (sublethal) exposure of tap water (control), acetone (solvent control), 5, 10, 20, and 50 μg/L (environmentally relevant concentrations) TCS to the embryos/hatchlings of Cirrhinus mrigala, a major freshwater carp distributed in tropic and sub-tropical areas of Asia. A concentration-dependent increase in the content of urea and protein carbonyl, while a decrease in the total protein, glucose, cholesterol, triglycerides, uric acid, and bilirubin was observed after the exposure. Hematological analysis revealed a decrease in the total erythrocyte count, hemoglobin, and partial pressure of oxygen, while there was an increase in the total leucocyte count, carbon dioxide, and partial pressure of carbon dioxide and serum electrolytes. Comet assay demonstrates a concentration-dependent increase in tail length, tail moment, olive tail moment, and percent tail DNA. An amino acid analyzer showed a TCS-dose-dependent increase in various amino acids. Sodium dodecyl sulphate polyacrylamide gel electrophoresis analysis revealed different proteins ranging from 6.5 to 200 kDa, demonstrating TCS-induced upregulation. Fourier transform infrared spectra analysis exhibited a decline in peak area percents with an increase in the concentration of TCS in water. Curve fitting of amide I (1,700-1600 cm-1) showed a decline in α-helix and turns and an increase in β-sheets. Nuclear magnetic resonance study also revealed concentration-dependent alterations in the metabolites after 14 d exposure. TCS caused alterations in the biomolecules and heamatological parameters of fish, raising the possibility that small amounts of TCS may change the species richness in natural aquatic habitats. In addition, consuming TCS-contaminated fish may have detrimental effects on human health. Consequently, there is a need for the proper utilisation and disposal of this hazardous compound in legitimate quantities.

Do wearing masks and preservatives have a combined effect on skin health?

Chemical exposure and local hypoxia caused by mask-wearing may result in skin physiology changes. The effects of methylparaben (MeP), a commonly used preservative in personal care products, and hypoxia on skin health were investigated by HaCaT cell and ICR mouse experiments. MeP exposure resulted in lipid peroxidation and interfered with cellular glutathione metabolism, while hypoxia treatment disturbed phenylalanine, tyrosine, and tryptophan biosynthesis pathways and energy metabolism to respond to oxidative stress. A hypoxic environment increased the perturbation of MeP on the purine metabolism in HaCaT cells, resulting in increased expression of proinflammatory cytokines. The synergistic effects were further validated in a mouse model with MeP dermal exposure and "mask-wearing" treatment. CAT, PPARG, and MMP2 were identified as possible key gene targets associated with skin health risks posed by MeP and hypoxia. Network toxicity analysis suggested a synergistic effect, indicating the risk of skin inflammation and skin barrier aging.

Metabolomics in Preclinical Drug Safety Assessment: Current Status and Future Trends

Metabolomics is emerging as a powerful systems biology approach for improving preclinical drug safety assessment. This review discusses current applications and future trends of metabolomics in toxicology and drug development. Metabolomics can elucidate adverse outcome pathways by detecting endogenous biochemical alterations underlying toxicity mechanisms. Furthermore, metabolomics enables better characterization of human environmental exposures and their influence on disease pathogenesis. Metabolomics approaches are being increasingly incorporated into toxicology studies and safety pharmacology evaluations to gain mechanistic insights and identify early biomarkers of toxicity. However, realizing the full potential of metabolomics in regulatory decision making requires a robust demonstration of reliability through quality assurance practices, reference materials, and interlaboratory studies. Overall, metabolomics shows great promise in strengthening the mechanistic understanding of toxicity, enhancing routine safety screening, and transforming exposure and risk assessment paradigms. Integration of metabolomics with computational, in vitro, and personalized medicine innovations will shape future applications in predictive toxicology.

Recent Advances in Drug Discovery Toxicology

Major advances in scientific discovery and insights that stem from the development and use of new techniques and models can bring remarkable progress to conventional toxicology. Although animal testing is still considered as the "gold standard" in traditional toxicity testing, there is a necessity for shift from animal testing to alternative methods regarding the drug safety testing owing to the emerging state-of-art techniques and the proposal of 3Rs (replace, reduce, and refine) towards animal welfare. This review describes some recent research methods in drug discovery toxicology, including in vitro cell and organ-on-a-chip, imaging systems, model organisms (C. elegans, Danio rerio, and Drosophila melanogaster), and toxicogenomics in modern toxicology testing.

The Exposome and Nutritional Pharmacology and Toxicology: A New Application for Metabolomics

The exposome refers to all of the internal and external life-long exposures that an individual experiences. These exposures, either acute or chronic, are associated with changes in metabolism that will positively or negatively influence the health and well-being of individuals. Nutrients and other dietary compounds modulate similar biochemical processes and have the potential in some cases to counteract the negative effects of exposures or enhance their beneficial effects. We present herein the concept of Nutritional Pharmacology/Toxicology which uses high-information metabolomics workflows to identify metabolic targets associated with exposures. Using this information, nutritional interventions can be designed toward those targets to mitigate adverse effects or enhance positive effects. We also discuss the potential for this approach in precision nutrition where nutrients/diet can be used to target gene-environment interactions and other subpopulation characteristics. Deriving these "nutrient cocktails" presents an opportunity to modify the effects of exposures for more beneficial outcomes in public health.

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.

Apical and mechanistic effects of 6PPD-quinone on different life-stages of the fathead minnow (Pimephales promelas)

N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine-quinone (6PPD-quinone) is an emerging contaminant of concern that is generated through the environmental oxidation of the rubber tire anti-degradant 6PPD. Since the initial report of 6PPD-quinone being the cause of urban runoff mortality syndrome of Coho salmon, numerous species have been identified as either sensitive or insensitive to acute lethality caused by 6PPD-quinone. In sensitive species, acute lethality might be caused by uncoupling of mitochondrial respiration in gills. However, little is known about effects of 6PPD-quinone on insensitive species. Here we demonstrate that embryos of fathead minnows (Pimephales promelas) are insensitive to exposure to concentrations as great as 39.97 μg/L for 168 h, and adult fathead minnows are insensitive to exposure to concentrations as great as 9.4 μg/L for 96 h. A multi-omics approach using a targeted transcriptomics array, (EcoToxChips), and proton nuclear magnetic resonance (1H NMR) was used to assess responses of the transcriptomes and metabolomes of gills and livers from adult fathead minnows exposed to 6PPD-quinone for 96 h to begin to identify sublethal effects of 6PPD-quinone. There was little agreement between results of the EcoToxChip and metabolomics analyses, likely because genes present on the EcoToxChip were not representative of pathways suggested to be perturbed by metabolomic analysis. Changes in abundances of transcripts and metabolites in livers and gills suggest that disruption of one‑carbon metabolism and induction of oxidative stress might be occurring in gills and livers, but that tissues differ in their sensitivity or responsiveness to 6PPD-quinone. Overall, several pathways impacted by 6PPD-quinone were identified as candidates for future studies of potential sublethal effects of this chemical.

Simultaneously discovering the fate and biochemical effects of pharmaceuticals through untargeted metabolomics

Untargeted metabolomics is an established approach in toxicology for characterising endogenous metabolic responses to xenobiotic exposure. Detecting the xenobiotic and its biotransformation products as part of the metabolomics analysis provides an opportunity to simultaneously gain deep insights into its fate and metabolism, and to associate the internal relative dose directly with endogenous metabolic responses. This integration of untargeted exposure and response measurements into a single assay has yet to be fully demonstrated. Here we assemble a workflow to discover and analyse pharmaceutical-related measurements from routine untargeted UHPLC-MS metabolomics datasets, derived from in vivo (rat plasma and cardiac tissue, and human plasma) and in vitro (human cardiomyocytes) studies that were principally designed to investigate endogenous metabolic responses to drug exposure. Our findings clearly demonstrate how untargeted metabolomics can discover extensive biotransformation maps, temporally-changing relative systemic exposure, and direct associations of endogenous biochemical responses to the internal dose.

The toxicity of nanoparticles and their interaction with cells: an in vitro metabolomic perspective

Nowadays, nanomaterials (NMs) are widely present in daily life due to their significant benefits, as demonstrated by their application in many fields such as biomedicine, engineering, food, cosmetics, sensing, and energy. However, the increasing production of NMs multiplies the chances of their release into the surrounding environment, making human exposure to NMs inevitable. Currently, nanotoxicology is a crucial field, which focuses on studying the toxicity of NMs. The toxicity or effects of nanoparticles (NPs) on the environment and humans can be preliminary assessed in vitro using cell models. However, the conventional cytotoxicity assays, such as the MTT assay, have some drawbacks including the possibility of interference with the studied NPs. Therefore, it is necessary to employ more advanced techniques that provide high throughput analysis and avoid interferences. In this case, metabolomics is one of the most powerful bioanalytical strategies to assess the toxicity of different materials. By measuring the metabolic change upon the introduction of a stimulus, this technique can reveal the molecular information of the toxicity induced by NPs. This provides the opportunity to design novel and efficient nanodrugs and minimizes the risks of NPs used in industry and other fields. Initially, this review summarizes the ways that NPs and cells interact and the NP parameters that play a role in this interaction, and then the assessment of these interactions using conventional assays and the challenges encountered are discussed. Subsequently, in the main part, we introduce the recent studies employing metabolomics for the assessment of these interactions in vitro.

The assessment of the potential hepatotoxicity of new drugs by in vitro metabolomics

Drug hepatotoxicity assessment is a relevant issue both in the course of drug development as well as in the post marketing phase. The use of human relevant in vitro models in combination with powerful analytical methods (metabolomic analysis) is a promising approach to anticipate, as well as to understand and investigate the effects and mechanisms of drug hepatotoxicity in man. The metabolic profile analysis of biological liver models treated with hepatotoxins, as compared to that of those treated with non-hepatotoxic compounds, provides useful information for identifying disturbed cellular metabolic reactions, pathways, and networks. This can later be used to anticipate, as well to assess, the potential hepatotoxicity of new compounds. However, the applicability of the metabolomic analysis to assess the hepatotoxicity of drugs is complex and requires careful and systematic work, precise controls, wise data preprocessing and appropriate biological interpretation to make meaningful interpretations and/or predictions of drug hepatotoxicity. This review provides an updated look at recent in vitro studies which used principally mass spectrometry-based metabolomics to evaluate the hepatotoxicity of drugs. It also analyzes the principal drawbacks that still limit its general applicability in safety assessment screenings. We discuss the analytical workflow, essential factors that need to be considered and suggestions to overcome these drawbacks, as well as recent advancements made in this rapidly growing field of research.

Prenatal Exposure to Potentially Toxic Metals and Their Effects on Genetic Material in Offspring: a Systematic Review

In recent years, the background level of environmental pollutants, including metals, has increased. Pollutant exposure during the earliest stages of life may determine chronic disease susceptibility in adulthood because of genetic or epigenetic changes. The objective of this review was to identify the association between prenatal and early postnatal exposure to potentially toxic metals (PTMs) and their adverse effects on the genetic material of offspring. A systematic review was carried out following the Cochrane methodology in four databases: PubMed, Scopus, Web of Science, and the Cochrane Library. Eligible papers were those conducted in humans and published in English between 2010/01/01 and 2021/04/30. A total of 57 articles were included, most of which evaluated prenatal exposure. Most commonly evaluated PTMs were As, Cd, and Pb. Main adverse effects on the genetic material of newborns associated with PTM prenatal exposure were alterations in telomere length, gene or protein expression, mitochondrial DNA content, metabolomics, DNA damage, and epigenetic modifications. Many of these effects were sex-specific, being predominant in boys. One article reported a synergistic interaction between As and Hg, and two articles observed antagonistic interactions between PTMs and essential metals, such as Cu, Se, and Zn. The findings in this review highlight that the problem of PTM exposure persists, affecting the most susceptible populations, such as newborns. Some of these associations were observed at low concentrations of PTMs. Most of the studies have focused on single exposures; however, three interactions between essential and nonessential metals were observed, highlighting that metal mixtures need more attention.

Closing the gap between in vivo and in vitro omics: using QA/QC to strengthen ex vivo NMR metabolomics

Metabolomics aims to achieve a global quantitation of the pool of metabolites within a biological system. Importantly, metabolite concentrations serve as a sensitive marker of both genomic and phenotypic changes in response to both internal and external stimuli. NMR spectroscopy greatly aids in the understanding of both in vitro and in vivo physiological systems and in the identification of diagnostic and therapeutic biomarkers. Accordingly, NMR is widely utilized in metabolomics and fluxomics studies due to its limited requirements for sample preparation and chromatography, its non-destructive and quantitative nature, its utility in the structural elucidation of unknown compounds, and, importantly, its versatility in the analysis of in vitro, in vivo, and ex vivo samples. This review provides an overview of the strengths and limitations of in vitro and in vivo experiments for translational research and discusses how ex vivo studies may overcome these weaknesses to facilitate the extrapolation of in vitro insights to an in vivo system. The application of NMR-based metabolomics to ex vivo samples, tissues, and biofluids can provide essential information that is close to a living system (in vivo) with sensitivity and resolution comparable to those of in vitro studies. The success of this extrapolation process is critically dependent on high-quality and reproducible data. Thus, the incorporation of robust quality assurance and quality control checks into the experimental design and execution of NMR-based metabolomics experiments will ensure the successful extrapolation of ex vivo studies to benefit translational medicine.

Environmental phenol exposure associates with urine metabolome alteration in young Northeast Indian females

Urinary biomonitoring delivers the most accurate environmental phenols exposure assessment. However, environmental phenol exposure-related biomarkers are required to improve risk assessment to understand the internal processes perturbed, which may link exposure to specific health outcomes. This study aimed to investigate the association between environmental phenols exposure and the metabolome of young adult females from India. Urinary metabolomics was performed using liquid chromatography-mass spectrometry. Environmental phenols-related metabolic biomarkers were investigated by comparing the low and high exposure of environmental phenols. Seven potential biomarkers, namely histidine, cysteine-s-sulfate, 12-KETE, malonic acid, p-hydroxybenzoic acid, PE (36:2), and PS (36:0), were identified, revealing that environmental phenol exposure altered the metabolic pathways such as histidine metabolism, beta-Alanine metabolism, glycerophospholipid metabolism, and other pathways. This study also conceived an innovative strategy for the early prediction of diseases by combining urinary metabolomics with machine learning (ML) algorithms. The differential metabolites predictive accuracy by ML models was >80%. This is the first mass spectrometry-based metabolomics study on young adult females from India with environmental phenols exposure. The study is valuable in demonstrating multiple urine metabolic changes linked to environmental phenol exposure and a better understanding of the mechanisms behind environmental phenol-induced effects in young female adults.

Investigation of dichlorodiphenyltrichloroethane (DDT) on xenobiotic enzyme disruption and metabolomic bile acid biosynthesis in DDT-sprayed areas using wild rats

Dichlorodiphenyltrichloroethane (DDT) is an organochlorine insecticide used worldwide. Several studies have reported the toxic effects of DDT and its metabolites on steroid hormone biosynthesis; however, its environmental effects are not well understood. This study examined wild rats collected in DDT-sprayed areas of South Africa and quantified plasma metabolites using liquid chromatography quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS). Fold change analysis of the metabolome revealed the effect of DDT on bile acid biosynthesis. Gene expression of the related enzyme in rat liver samples was also quantified. Significant association was found between DDT and gene expression levels related to constitutive androstane receptor mediated enzymes, such as Cyp2b1 in rat livers. However, our results could not fully demonstrate that enzymes related to bile acid biosynthesis were strongly affected by DDT. The correlation between DDT concentration and gene expression involved in steroid hormone synthesis in testis was also evaluated; however, no significant correlation was found. The disturbance of metabolic enzymes occurred in rat liver in the target area. Our results suggest that DDT exposure affects gene expression in wild rats living in DDT-sprayed areas. Therefore, there is a need for DDT toxicity evaluation in mammals living in DDT-sprayed areas. We could not find an effective biomarker that could reflect the mechanism of DDT exposure; however, this approach can provide new insights for future research to evaluate DDT effects in sprayed areas.

A Novel Nanosafety Approach Using Cell Painting, Metabolomics, and Lipidomics Captures the Cellular and Molecular Phenotypes Induced by the Unintentionally Formed Metal-Based (Nano)Particles

Additive manufacturing (AM) or industrial 3D printing uses cutting-edge technologies and materials to produce a variety of complex products. However, the effects of the unintentionally emitted AM (nano)particles (AMPs) on human cells following inhalation, require further investigations. The physicochemical characterization of the AMPs, extracted from the filter of a Laser Powder Bed Fusion (L-PBF) 3D printer of iron-based materials, disclosed their complexity, in terms of size, shape, and chemistry. Cell Painting, a high-content screening (HCS) assay, was used to detect the subtle morphological changes elicited by the AMPs at the single cell resolution. The profiling of the cell morphological phenotypes, disclosed prominent concentration-dependent effects on the cytoskeleton, mitochondria, and the membranous structures of the cell. Furthermore, lipidomics confirmed that the AMPs induced the extensive membrane remodeling in the lung epithelial and macrophage co-culture cell model. To further elucidate the biological mechanisms of action, the targeted metabolomics unveiled several inflammation-related metabolites regulating the cell response to the AMP exposure. Overall, the AMP exposure led to the internalization, oxidative stress, cytoskeleton disruption, mitochondrial activation, membrane remodeling, and metabolic reprogramming of the lung epithelial cells and macrophages. We propose the approach of integrating Cell Painting with metabolomics and lipidomics, as an advanced nanosafety methodology, increasing the ability to capture the cellular and molecular phenotypes and the relevant biological mechanisms to the (nano)particle exposure.

NMR-Based Metabolomics to Evaluate Individual Response to Treatments

The aim of this chapter is to highlight the various aspects of metabolomics in relation to health and diseases, starting from the definition of metabolic space and of how individuals tend to maintain their own position in this space. Physio-pathological stimuli may cause individuals to lose their position and then regain it, or move irreversibly to other positions. By way of examples, mostly selected from our own work using ¹H NMR on biological fluids, we describe the effects on the individual metabolomic fingerprint of mild external interventions, such as diet or probiotic administration. Then we move to pathologies (such as celiac disease, various types of cancer, viral infections, and other diseases), each characterized by a well-defined metabolomic fingerprint. We describe the effects of drugs on the disease fingerprint and on its reversal to a healthy metabolomic status. Drug toxicity can be also monitored by metabolomics. We also show how the individual metabolomic fingerprint at the onset of a disease may discriminate responders from non-responders to a given drug, or how it may be prognostic of e.g., cancer recurrence after many years. In parallel with fingerprinting, profiling (i.e., the identification and quantification of many metabolites and, in the case of selected biofluids, of the lipoprotein components that contribute to the ¹H NMR spectral features) can provide hints on the metabolic pathways that are altered by a disease and assess their restoration after treatment.

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.

Health impact assessment of pet cats caused by organohalogen contaminants by serum metabolomics and thyroid hormone analysis

Companion animals are in close contact with the human surroundings, and there is growing concern about the effects of harmful substances on the health of pet cats. In this study, we investigated the potential health effects of organohalogen compounds (OHCs) on thyroid hormone (TH) homeostasis and metabolomics in Japanese pet cats. There was a significant negative correlation between concentrations of several contaminants, such as polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), hydroxylated PCBs (OH-PCBs), hydroxylated PBDEs (OH-PBDEs), and THs in cat serum samples. These results suggested that exposure to OHCs causes a decrease in serum TH levels in pet cats. In this metabolomics study, each exposure level of parent compounds (PCBs and PBDEs) and their hydroxylated compounds (OH-PCBs and OH-PBDEs) were associated with their own unique primary metabolic pathways, suggesting that parent and phenolic compounds exhibit different mechanisms of action and biological effects. PCBs were associated with many metabolic pathways, including glutathione and purine metabolism, and the effects were replicated in in-vivo cat PCB administration studies. These results demonstrated that OHC exposure causes chronic oxidative stress in pet cats. PBDEs were positively associated with alanine, aspartate, and glutamate metabolism. Due to the chronic exposure of cats to mixtures of these contaminants, the combination of their respective metabolic pathways may have a synergistic effect.

Transcriptomic-Metabolomic Profiling in Mouse Lung Tissues Reveals Sex- and Strain-Based Differences

Omics analyses are commonly used for identifying pathways and genes responsible for physiologic and pathologic processes. Though sex is considered a biological variable in rigorous assessments of pulmonary responses to oxidant exposures, the contribution of the murine strain is largely ignored. This study utilized an unbiased integrated assessment of high-resolution metabolomic profiling and RNA-sequencing to explore sex- and strain-dependent pathways in adult mouse lungs. The results indicated that strain exhibited a greater influence than sex on pathways associated with inflammatory and oxidant/antioxidant responses and that interaction metabolites more closely resembled those identified as differentially expressed by strain. Metabolite analyses revealed that the components of the glutathione antioxidant pathway were different between strains, specifically in the formation of mixed disulfides. Additionally, selenium metabolites such as selenohomocystiene and selenocystathionine were similarly differentially expressed. Transcriptomic analysis revealed similar findings, as evidenced by differences in glutathione peroxidase, peroxiredoxin, and the inflammatory transcription factors RelA and Jun. In summary, an multi-omics integrated approach identified that murine strain disproportionately impacts baseline expression of antioxidant systems in lung tissues. We speculate that strain-dependent differences contribute to discrepant pulmonary responses in preclincal mouse models, with deleterious effects on clinical translation.

Toxicity of 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) in early development: A wide-scope metabolomics assay in zebrafish embryos

The tobacco-specific nitrosamine 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) is a carcinogenic and ubiquitous environmental pollutant for which toxic activity has been thoroughly investigated in murine models and human tissues. However, its potential deleterious effects on vertebrate early development are yet poorly understood. In this work, we characterized the impact of NNK exposure during early developmental stages of zebrafish embryos, a known alternative model for mammalian toxicity studies. Embryos exposed to different NNK concentrations were monitored for lethality and for the appearance of malformations during the first five days after fertilization. LC-MS based untargeted metabolomics was subsequently performed for a wide-scope assay of NNK-related metabolic alterations. Our results revealed the presence of not only the parental compound, but also of two known NNK metabolites, 4-Hydroxy-4-(3-pyridyl)-butyric acid (HPBA) and 4-(Methylnitrosamino)-1-(3-pyridyl-N-oxide)-1-butanol (NNAL-N-oxide) in exposed embryos likely resulting from active CYP450-mediated α-hydroxylation and NNK detoxification pathways, respectively. This was paralleled by a disruption in purine and pyrimidine metabolisms and the activation of the base excision repair pathway. Our results confirm NNK as a harmful embryonic agent and demonstrate zebrafish embryos to be a suitable early development model to monitor NNK toxicity.

Particle Safety Assessment in Additive Manufacturing: From Exposure Risks to Advanced Toxicology Testing

Additive manufacturing (AM) or industrial three-dimensional (3D) printing drives a new spectrum of design and production possibilities; pushing the boundaries both in the application by production of sophisticated products as well as the development of next-generation materials. AM technologies apply a diversity of feedstocks, including plastic, metallic, and ceramic particle powders with distinct size, shape, and surface chemistry. In addition, powders are often reused, which may change the particles’ physicochemical properties and by that alter their toxic potential. The AM production technology commonly relies on a laser or electron beam to selectively melt or sinter particle powders. Large energy input on feedstock powders generates several byproducts, including varying amounts of virgin microparticles, nanoparticles, spatter, and volatile chemicals that are emitted in the working environment; throughout the production and processing phases. The micro and nanoscale size may enable particles to interact with and to cross biological barriers, which could, in turn, give rise to unexpected adverse outcomes, including inflammation, oxidative stress, activation of signaling pathways, genotoxicity, and carcinogenicity. Another important aspect of AM-associated risks is emission/leakage of mono- and oligomers due to polymer breakdown and high temperature transformation of chemicals from polymeric particles, both during production, use, and in vivo, including in target cells. These chemicals are potential inducers of direct toxicity, genotoxicity, and endocrine disruption. Nevertheless, understanding whether AM particle powders and their byproducts may exert adverse effects in humans is largely lacking and urges comprehensive safety assessment across the entire AM lifecycle—spanning from virgin and reused to airborne particles. Therefore, this review will detail: 1) brief overview of the AM feedstock powders, impact of reuse on particle physicochemical properties, main exposure pathways and protective measures in AM industry, 2) role of particle biological identity and key toxicological endpoints in the particle safety assessment, and 3) next-generation toxicology approaches in nanosafety for safety assessment in AM. Altogether, the proposed testing approach will enable a deeper understanding of existing and emerging particle and chemical safety challenges and provide a strategy for the development of cutting-edge methodologies for hazard identification and risk assessment in the AM industry.

Untargeted Metabolomics Profiling of Arabidopsis WT, lbr-2-2 and bak1-4 Mutants Following Treatment with Two LPS Chemotypes

Plants perceive pathogenic threats from the environment that have evaded preformed barriers through pattern recognition receptors (PRRs) that recognise microbe-associated molecular patterns (MAMPs). The perception of and triggered defence to lipopolysaccharides (LPSs) as a MAMP is well-studied in mammals, but little is known in plants, including the PRR(s). Understanding LPS-induced secondary metabolites and perturbed metabolic pathways in Arabidopsis will be key to generating disease-resistant plants and improving global plant crop yield. Recently, Arabidopsis LPS-binding protein (LBP) and bactericidal/permeability-increasing protein (BPI)-related proteins (LBP/BPI related-1) and (LBP/BPI related-2) were shown to perceive LPS from Pseudomonas aeruginosa and trigger defence responses. In turn, brassinosteroid insensitive 1 (BRI1)-associated receptor kinase 1 (BAK1) is a well-established co-receptor for several defence-related PRRs in plants. Due to the lack of knowledge pertaining to LPS perception in plants and given the involvement of the afore-mentioned proteins in MAMPs recognition, in this study, Arabidopsis wild type (WT) and mutant (lbr2-2 and bak1-4) plants were pressure-infiltrated with LPSs purified from Pseudomonas syringae pv. tomato DC3000 (Pst) and Xanthomonas campestris pv. campestris 8004 (Xcc). Metabolites were extracted from the leaves at four time points over a 24 h period and analysed by UHPLC-MS, generating distinct metabolite profiles. Data analysed using unsupervised and supervised multivariate data analysis (MVDA) tools generated results that reflected time- and treatment-related variations after both LPS chemotypes treatments. Forty-five significant metabolites were putatively annotated and belong to the following groups: glucosinolates, hydroxycinnamic acid derivatives, flavonoids, lignans, lipids, oxylipins, arabidopsides and phytohormones, while metabolic pathway analysis (MetPA) showed enrichment of flavone and flavanol biosynthesis, phenylpropanoid biosynthesis, alpha-linolenic acid metabolism and glucosinolate biosynthesis. Distinct metabolite accumulations depended on the LPS chemotype and the genetic background of the lbr2-2 and bak1-4 mutants. This study highlights the role of LPSs in the reprogramming Arabidopsis metabolism into a defensive state, and the possible role of LBR and BAK1 proteins in LPSs perception and thus plant defence against pathogenic bacteria.

Associations between the Maternal Exposome and Metabolome during Pregnancy

BACKGROUND

Maternal exposure to environmental chemicals during pregnancy can influence various maternal and offspring health parameters. Modification of maternal metabolism by environmental exposure may be an important pathway for these impacts. However, there is limited evidence regarding exposure to a wide array of chemicals and the metabolome during pregnancy.

OBJECTIVES

We investigated the relationship between the urinary exposome and metabolome during pregnancy.

METHODS

Urine samples were collected in the first and third trimesters from 1,024 pregnant women recruited in prenatal clinics in Jiangsu Province, China. The exposome was analyzed using the first trimester sample with ultra-high performance liquid chromatography-high resolution accurate mass spectrometry (UHPLC-HRMS) and inductively coupled plasma mass spectrometry. The metabolome was analyzed using the third trimester sample with UHPLC-HRMS. We evaluated associations between each of 106 exposures in the first trimester with 139 metabolites in the third trimester.

RESULTS

We identified 1,245 significant associations (p<3.39×10-6, Bonferroni correction) between chemical exposures and maternal metabolism during pregnancy. Among elements, the largest number of the significant metabolic associations were observed for magnesium, and among organic compounds, for 4-tert-octylphenol. We used exposome-metabolome associations to explore mechanisms underlying published associations between prenatal chemical exposures and offspring health outcomes. This integration of the literature with our results suggests that reported associations between 10 analytes and birth weight, gestational age, fat deposition, neurobehavioral development, immunological disorders, and hypertension may be partially mediated by metabolites associated with these exposures.

DISCUSSION

This high-dimensional analysis of the urinary exposome and metabolome identified many associations between chemical exposures and maternal metabolism during pregnancy. Integration of these associations with the literature on health outcomes of exposure suggests that environmental modulation of the maternal metabolome may play a role in the association between prenatal exposure on pregnancy and child health outcomes. https://doi.org/10.1289/EHP9745.

Computational analyses of mechanism of action (MoA): data, methods and integration

The elucidation of a compound's Mechanism of Action (MoA) is a challenging task in the drug discovery process, but it is important in order to rationalise phenotypic findings and to anticipate potential side-effects. Bioinformatic approaches, advances in machine learning techniques and the increasing deposition of high-throughput data in public databases have significantly contributed to recent advances in the field, but it is not straightforward to decide which data and methods are most suitable to use in a given case. In this review, we focus on these methods and data and their applications in generating MoA hypotheses for subsequent experimental validation. We discuss compound-specific data such as -omics, cell morphology and bioactivity data, as well as commonly used supplementary prior knowledge such as network and pathway data, and provide information on databases where this data can be accessed. In terms of methodologies, we discuss both well-established methods (connectivity mapping, pathway enrichment) as well as more developing methods (neural networks and multi-omics integration). Finally, we review case studies where the MoA of a compound was successfully suggested from computational analysis by incorporating multiple data modalities and/or methodologies. Our aim for this review is to provide researchers with insights into the benefits and drawbacks of both the data and methods in terms of level of understanding, biases and interpretation - and to highlight future avenues of investigation which we foresee will improve the field of MoA elucidation, including greater public access to -omics data and methodologies which are capable of data integration.

Metabolomic Alteration in the Plasma of Wild Rodents Environmentally Exposed to Lead: A Preliminary Study

Lead poisoning is often considered a traditional disease; however, the specific mechanism of toxicity remains unclear. The study of Pb-induced alterations in cellular metabolic pathways is important to understand the biological response and disorders associated with environmental exposure to lead. Metabolomics studies have recently been paid considerable attention to understand in detail the biological response to lead exposure and the associated toxicity mechanisms. In the present study, wild rodents collected from an area contaminated with lead (N = 18) and a control area (N = 10) were investigated. This was the first ever experimental metabolomic study of wildlife exposed to lead in the field. While the levels of plasma phenylalanine and isoleucine were significantly higher in a lead-contaminated area versus the control area, hydroxybutyric acid was marginally significantly higher in the contaminated area, suggesting the possibility of enhancement of lipid metabolism. In the interregional least-absolute shrinkage and selection operator (lasso) regression model analysis, phenylalanine and isoleucine were identified as possible biomarkers, which is in agreement with the random forest model. In addition, in the random forest model, glutaric acid, glutamine, and hydroxybutyric acid were selected. In agreement with previous studies, enrichment analysis showed alterations in the urea cycle and ATP-binding cassette transporter pathways. Although regional rodent species bias was observed in this study, and the relatively small sample size should be taken into account, the present results are to some extent consistent with those of previous studies on humans and laboratory animals.

Spatially Mapping the Baseline and Bisphenol-A Exposed Daphnia magna Lipidome Using Desorption Electrospray Ionization-Mass Spectrometry

Untargeted lipidomics has previously been applied to the study of daphnids and the discovery of biomarkers that are indicative of toxicity. Typically, liquid chromatography—mass spectrometry is used to measure the changes in lipid abundance in whole-body homogenates of daphnids, each only ca. 3 mm in length which limits any biochemical interpretation of site-specific toxicity. Here, we applied mass spectrometry imaging of Daphnia magna to combine untargeted lipidomics with spatial resolution to map the molecular perturbations to defined anatomical regions. A desorption electrospray ionization—mass spectrometry (DESI-MS) method was optimized and applied to tissue sections of daphnids exposed to bisphenol-A (BPA) compared to unexposed controls, generating an untargeted mass spectrum at each pixel (35 µm²/pixel) within each section. First, unique lipid profiles from distinct tissue types were identified in whole-body daphnids using principal component analysis, specifically distinguishing appendages, eggs, eye, and gut. Second, changes in the lipidome were mapped over four stages of normal egg development and then the effect of BPA exposure on the egg lipidome was characterized. The primary perturbations to the lipidome were annotated as triacylglycerides and phosphatidylcholine, and the distributions of the individual lipid species within these classes were visualized in whole-body D. magna sections as ion images. Using an optimized DESI-MS workflow, the first ion images of D. magna tissue sections were generated, mapping both their baseline and BPA-perturbed lipidomes.

Emerging nanosensor platforms and machine learning strategies toward rapid, point-of-need small-molecule metabolite detection and monitoring

Speedy, point-of-need detection and monitoring of small-molecule metabolites are vital across diverse applications ranging from biomedicine to agri-food and environmental surveillance. Nanomaterial-based sensor (nanosensor) platforms are rapidly emerging as excellent candidates for versatile and ultrasensitive detection owing to their highly configurable optical, electrical and electrochemical properties, fast readout, as well as portability and ease of use. To translate nanosensor technologies for real-world applications, key challenges to overcome include ultralow analyte concentration down to ppb or nM levels, complex sample matrices with numerous interfering species, difficulty in differentiating isomers and structural analogues, as well as complex, multidimensional datasets of high sample variability. In this Perspective, we focus on contemporary and emerging strategies to address the aforementioned challenges and enhance nanosensor detection performance in terms of sensitivity, selectivity and multiplexing capability. We outline 3 main concepts: (1) customization of designer nanosensor platform configurations via chemical- and physical-based modification strategies, (2) development of hybrid techniques including multimodal and hyphenated techniques, and (3) synergistic use of machine learning such as clustering, classification and regression algorithms for data exploration and predictions. These concepts can be further integrated as multifaceted strategies to further boost nanosensor performances. Finally, we present a critical outlook that explores future opportunities toward the design of next-generation nanosensor platforms for rapid, point-of-need detection of various small-molecule metabolites.

Overview of the current status on emerging, multi-faceted nanosensor platform designs and data analysis strategies for rapid, point-of-need detection and monitoring of small-molecule metabolites.

An Extensive Metabolomics Workflow to Discover Cardiotoxin-Induced Molecular Perturbations in Microtissues

Discovering modes of action and predictive biomarkers of drug-induced structural cardiotoxicity offers the potential to improve cardiac safety assessment of lead compounds and enhance preclinical to clinical translation during drug development. Cardiac microtissues are a promising, physiologically relevant, in vitro model, each composed of ca. 500 cells. While untargeted metabolomics is capable of generating hypotheses on toxicological modes of action and discovering metabolic biomarkers, applying this technology to low-biomass microtissues in suspension is experimentally challenging. Thus, we first evaluated a filtration-based approach for harvesting microtissues and assessed the sensitivity and reproducibility of nanoelectrospray direct infusion mass spectrometry (nESI-DIMS) measurements of intracellular extracts, revealing samples consisting of 28 pooled microtissues, harvested by filtration, are suitable for profiling the intracellular metabolome and lipidome. Subsequently, an extensive workflow combining nESI-DIMS untargeted metabolomics and lipidomics of intracellular extracts with ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS/MS) analysis of spent culture medium, to profile the metabolic footprint and quantify drug exposure concentrations, was implemented. Using the synthetic drug and model cardiotoxin sunitinib, time-resolved metabolic and lipid perturbations in cardiac microtissues were investigated, providing valuable data for generating hypotheses on toxicological modes of action and identifying putative biomarkers such as disruption of purine metabolism and perturbation of polyunsaturated fatty acid levels.

Altered metabolic pathways elucidated via untargeted in vivo toxicometabolomics in rat urine and plasma samples collected after controlled application of a human equivalent amphetamine dose

Amphetamine is widely consumed as drug of abuse due to its stimulating and cognitive enhancing effects. Since amphetamine has been on the market for quite a long time and it is one of the most commonly used stimulants worldwide, to date there is still limited information on its effects on the metabolome. In recent years, untargeted toxicometabolomics have been increasingly used to study toxicity-related pathways of such drugs of abuse to find and identify important endogenous and exogenous biomarkers. In this study, the acute effects of amphetamine intake on plasma and urinary metabolome in rats were investigated. For this purpose, samples of male Wistar rats after a single dose of amphetamine (5 mg/kg) were compared to a control group using an untargeted metabolomics approach. Analysis was performed using normal and reversed phase liquid chromatography coupled to high-resolution mass spectrometry using positive and negative ionization mode. Statistical evaluation was performed using Welch's two-sample t test, hierarchical clustering, as well as principal component analysis. The results of this study demonstrate a downregulation of amino acids in plasma samples after amphetamine exposure. Furthermore, four new potential biomarkers N-acetylamphetamine, N-acetyl-4-hydroxyamphetamine, N-acetyl-4-hydroxyamphetamine glucuronide, and amphetamine succinate were identified in urine. The present study complements previous data and shows that several studies are necessary to elucidate altered metabolic pathways associated with acute amphetamine exposure.

An 'Omics Approach to Unraveling the Paradoxical Effect of Diet on Perfluorooctanesulfonic Acid (PFOS) and Perfluorononanoic Acid (PFNA)-Induced Hepatic Steatosis

Perfluoroalkyl substances (PFAS) are a family of toxicants universally detected in human serum and known to cause dyslipidemia in animals and humans. Hepatic steatosis, which is defined as lipid deposition in the liver, is known to be a consequence of poor diet. Similarly, PFAS are known to induce hepatic steatosis in animals on a low-fat chow. This study explored diet-PFAS interactions in the liver and their potential to modulate hepatic steatosis. Male C57BL/6J mice were fed with either a low-fat diet (10% kcal from fat, LFD) or a moderately high-fat diet (45% kcal from fat, HFD) with or without perfluorooctanesulfonic acid (3 ppm, PFOS) or perfluorononanoic acid (3 ppm, PFNA) in feed for 12 weeks. Livers were excised for histology and quantification of PFAS and lipids. The PFOS and PFNA coadministration with HFD reduced the hepatic accumulation of lipid and PFAS relative to the LFD treatment groups. Furthermore, transcriptomic analysis revealed that PFAS administration in the presence of an HFD significantly reduces expression of known hepatic PFAS uptake transporters, organic anion transporter proteins. Transcriptomics and proteomics further revealed several pathways related to lipid metabolism, synthesis, transport, and storage that were modulated by PFAS exposure and further impacted by the presence of dietary fat. Both dietary fat content and the chemical functional head group exerted significant influence on hepatic PFAS accumulation and the resulting biochemical signature, suggesting that diet and structure should be considered in the design and interpretation of research on PFAS induced hepatic steatosis.

Deciphering the mechanism of action of antitubercular compounds with metabolomics

Tuberculosis (TB), one of the oldest and deadliest bacterial diseases, continues to cause serious global economic, health, and social problems. Current TB treatments are lengthy, expensive, and routinely ineffective against emerging drug resistant strains. Thus, there is an urgent need for the identification and development of novel TB drugs possessing comprehensive and specific mechanisms of action (MoAs). Metabolomics is a valuable approach to elucidating the MoA, toxicity, and potency of promising chemical leads, which is a critical step of the drug discovery process. Recent advances in metabolomics methodologies for deciphering MoAs include high-throughput screening techniques, the integration of multiple omics methods, mass spectrometry imaging, and software for automated analysis. This review describes recently introduced metabolomics methodologies and techniques for drug discovery, highlighting specific applications to the discovery of new antitubercular drugs and the elucidation of their MoAs.

Gut Microbiome Critically Impacts PCB-induced Changes in Metabolic Fingerprints and the Hepatic Transcriptome in Mice

Polychlorinated biphenyls (PCBs) are ubiquitously detected and have been linked to metabolic diseases. Gut microbiome is recognized as a critical regulator of disease susceptibility; however, little is known how PCBs and gut microbiome interact to modulate hepatic xenobiotic and intermediary metabolism. We hypothesized the gut microbiome regulates PCB-mediated changes in the metabolic fingerprints and hepatic transcriptome. Ninety-day-old female conventional and germ-free mice were orally exposed to the Fox River Mixture (synthetic PCB mixture, 6 or 30 mg/kg) or corn oil (vehicle control, 10 ml/kg), once daily for 3 consecutive days. RNA-seq was conducted in liver, and endogenous metabolites were measured in liver and serum by LC-MS. Prototypical target genes of aryl hydrocarbon receptor, pregnane X receptor, and constitutive androstane receptor were more readily upregulated by PCBs in conventional conditions, indicating PCBs, to the hepatic transcriptome, act partly through the gut microbiome. In a gut microbiome-dependent manner, xenobiotic, and steroid metabolism pathways were upregulated, whereas response to misfolded proteins-related pathways was downregulated by PCBs. At the high PCB dose, NADP, and arginine appear to interact with drug-metabolizing enzymes (ie, Cyp1-3 family), which are highly correlated with Ruminiclostridium and Roseburia, providing a novel explanation of gut-liver interaction from PCB-exposure. Utilizing the Library of Integrated Network-based Cellular Signatures L1000 database, therapeutics targeting anti-inflammatory and endoplasmic reticulum stress pathways are predicted to be remedies that can mitigate PCB toxicity. Our findings demonstrate that habitation of the gut microbiota drives PCB-mediated hepatic responses. Our study adds knowledge of physiological response differences from PCB exposure and considerations for further investigations for gut microbiome-dependent therapeutics.

Metabolomics in asthma: A platform for discovery

Asthma, characterized by airway hyperresponsiveness, inflammation and remodeling, is a chronic airway disease with complex etiology. Severe asthma is characterized by frequent exacerbations and poor therapeutic response to conventional asthma therapy. A clear understanding of cellular and molecular mechanisms of asthma is critical for the discovery of novel targets for optimal therapeutic control of asthma. Metabolomics is emerging as a powerful tool to elucidate novel disease mechanisms in a variety of diseases. In this review, we summarize the current status of knowledge in asthma metabolomics at systemic and cellular levels. The findings demonstrate that various metabolic pathways, related to energy metabolism, macromolecular biosynthesis and redox signaling, are differentially modulated in asthma. Airway smooth muscle cell plays pivotal roles in asthma by contributing to airway hyperreactivity, inflammatory mediator release and remodeling. We posit that metabolomic profiling of airway structural cells, including airway smooth muscle cells, will shed light on molecular mechanisms of asthma and airway hyperresponsiveness and help identify novel therapeutic targets.

Evaluation of metabolomics behavior of human colon cancer HT29 cell lines treated with ionic liquid graviola fruit pulp extract

ETHNOPHARMACOLOGICAL RELEVANCE

Medicinal plants have been used by indigenous people across the world for centuries to help individuals preserve their wellbeing and cure diseases. Annona muricata L. (Graviola) which is belonging to the Annonaceae family has been traditionally used due to its medicinal abilities including antimicrobial, anti-inflammatory, antioxidant and cancer cell growth inhibition. Graviola is claimed to be a potential antitumor due to its selective cytotoxicity against several cancer cell lines. However, the metabolic mechanism information underlying the anticancer activity remains limited.

AIM OF THE STUDY

This study aimed to investigate the effect of ionic liquid-Graviola fruit pulp extract (IL-GPE) on the metabolomics behavior of colon cancer (HT29) by using an untargeted GC-TOFMS-based metabolic profiling.

MATERIALS AND METHODS

Multivariate data analysis was used to determine the metabolic profiling, and the ingenuity pathway analysis (IPA) was used to predict the altered canonical pathways after treating the HT29 cells with crude IL-GPE and Taxol (positive control).

RESULTS

The principal components analysis (PCA) identified 44 metabolites with the most reliable factor loading, and the cluster analysis (CA) separated three groups of metabolites: metabolites specific to the non-treated HT29 cells, metabolites specific to the treated HT29 cells with the crude IL-GPE and metabolites specific to Taxol treatment. Pathway analysis of metabolomic profiles revealed an alteration of many metabolic pathways, including amino acid metabolism, aerobic glycolysis, urea cycle and ketone bodies metabolism that contribute to energy metabolism and cancer cell proliferation.

CONCLUSION

The crude IL-GPE can be one of the promising anticancer agents due to its selective inhibition of energy metabolism and cancer cell proliferation.

Approaches in metabolomics for regulatory toxicology applications

Innovative methodological approaches are needed to conduct human health and environmental risk assessments on a growing number of marketed chemicals. Metabolomics is progressively proving its value as an efficient strategy to perform toxicological evaluations of new and existing substances, and it will likely become a key tool to accelerate chemical risk assessments. However, additional guidance with widely accepted and harmonized procedures is needed before metabolomics can be routinely incorporated in decision-making for regulatory purposes. The aim of this review is to provide an overview of metabolomic strategies that have been successfully employed in toxicity assessment as well as the most promising workflows in a regulatory context. First, we provide a general view of the different steps of regulatory toxicology-oriented metabolomics. Emphasis is put on three key elements: robustness of experimental design, choice of analytical platform, and use of adapted data treatment tools. Then, examples in which metabolomics supported regulatory toxicology outputs in different scenarios are reviewed, including chemical grouping, elucidation of mechanisms of toxicity, and determination of points of departure. The overall intention is to provide insights into why and how to plan and conduct metabolomic studies for regulatory toxicology purposes.

PET nanoplastics interactions with water contaminants and their impact on human cells

In recent years, many studies are focusing on the negative effects of plastic pollution, and in particular on the nanosized plastic fragments and their implications on the environment and human health. Nanoplastics in the environment interact with a great number of substances, many of which are dangerous to humans, but the interaction mechanisms, the complexes formation processes, and their biological impact are still poorly understood. Here we report a study on the interactions of polyethylene terephthalate nanoplastics, produced by laser ablation, with three different types of contaminants: glyphosate, levofloxacin and Hg²⁺ ions, and we demonstrate that the nanoplastics form complexes with all three contaminants through their favorable binding. Most importantly, this study highlights that to demonstrate the overall effect of the nanoplastics internalized by cells in vitro, it is important to combine alternative methodologies, such as metabolomics, with standard biological assays (i.e., cell viability and ROS production). In this way it becomes possible to better understand the body's response to this new class of pollutants and their possible chronic toxicity. Summary: PET nanoplastics, fabricated by laser ablation, interact with aqueous pollutants forming nanoclusters. The nanoclusters affect the cells metabolism, suggesting long-term risks.

Fumonisin B1 regulates LDL receptor and ABCA1 expression in an LXR dependent mechanism in liver (HepG2) cells

The metabolic toxicity of Fumonisin B₁ (FB₁) converges at the accumulation of sphingoid bases and reduced ceramide levels. Several studies have alluded to a hypercholesterolemic endpoint after FB₁ exposure, yet the molecular mechanisms remain elusive. Cell surface receptors are important regulators of cholesterol metabolism by regulating influx of lipids and efflux of cholesterol. Western blot analysis showed that FB₁ elevates the expression of ABCA1 (a cholesterol efflux promoter) in an LXR dependent mechanism. We further highlight the potential role of PCSK9 in the degradation of LDL receptor. These data provide important evidence for the mechanism underlying hypercholesterolemia in FB₁ treated models. The disruption of lipid homeostasis by FB₁ is beginning to shift away from canonical ceramide synthase inhibition, and this changed perspective may shed light on diseases caused by dysregulated cholesterol metabolism such as cancer initiation and promotion.

Systematic Review of Multi-Omics Approaches to Investigate Toxicological Effects in Macrophages

Insights into the modes of action (MoAs) of xenobiotics are of utmost importance for the definition of adverse outcome pathways (AOPs), which are essential for a mechanism-based risk assessment. A well-established strategy to reveal MoAs of xenobiotics is the use of omics. However, often an even more comprehensive approach is needed, which can be achieved using multi-omics. Since the immune system plays a central role in the defense against foreign substances and pathogens, with the innate immune system building a first barrier, we systematically reviewed multi-omics studies investigating the effects of xenobiotics on macrophages. Surprisingly, only nine publications were identified, combining proteomics with transcriptomics or metabolomics. We summarized pathways and single proteins, transcripts, or metabolites, which were described to be affected upon treatment with xenobiotics in the reviewed studies, thus revealing a broad range of effects. In summary, we show that macrophages are a relevant model system to investigate the toxicological effects induced by xenobiotics. Furthermore, the multi-omics approaches led to a more comprehensive overview compared to only one omics layer with slight advantages for combinations that complement each other directly, e.g., proteome and metabolome.

In vivo toxicometabolomics reveals multi-organ and urine metabolic changes in mice upon acute exposure to human-relevant doses of 3,4-methylenedioxypyrovalerone (MDPV)

3,4-Methylenedioxypyrovalerone (MDPV) is consumed worldwide, despite its potential to cause toxicity in several organs and even death. There is a recognized need to clarify the biological pathways through which MDPV elicits general and target-organ toxicity. In this work, a comprehensive untargeted GC-MS-based metabolomics analysis was performed, aiming to detect metabolic changes in putative target organs (brain, heart, kidneys and liver) but also in urine of mice after acute exposure to human-relevant doses of MDPV. Male CD-1 mice received binge intraperitoneal administrations of saline or MDPV (2.5 mg/kg or 5 mg/kg) every 2 h, for a total of three injections. Twenty-four hours after the first administration, target organs, urine and blood samples were collected for metabolomics, biochemical and histological analysis. Hepatic and renal tissues of MDPV-treated mice showed moderate histopathological changes but no significant differences were found in plasma and tissue biochemical markers of organ injury. In contrast, the multivariate analysis significantly discriminated the organs and urine of MDPV-treated mice from the control (except for the lowest dose in the brain), allowing the identification of a panoply of metabolites. Those levels were significantly deviated in relation to physiological conditions and showed an organ specific response towards the drug. Kidneys and liver showed the greatest metabolic changes. Metabolites related with energetic metabolism, antioxidant defenses and inflammatory response were significantly changed in the liver of MDPV-dosed animals, while the kidneys seem to have developed an adaptive response against oxidative stress caused by MDPV. On the other hand, the dysregulation of metabolites that contribute to metabolic acidosis was also observed in this organ. The heart showed an increase of fatty acid biosynthesis, possibly as an adaptation to maintain the cardiac energy homeostasis. In the brain, changes in 3-hydroxybutyric acid levels may reflect the activation of a neurotoxic pathway. However, the increase in metabolites with neuroprotective properties seems to counteract this change. Metabolic profiling of urine from MDPV-treated mice suggested that glutathione-dependent antioxidant pathways may be particularly involved in the compensatory mechanism to counteract oxidative stress induced by MDPV. Overall, this study reports, for the first time, the metabolic profile of liver, kidneys, heart, brain, and urine of MDPV-dosed mice, providing unique insights into the biological pathways of toxicity. Our findings also underline the value of toxicometabolomics as a robust and sensitive tool for detecting adaptive/toxic cellular responses upon exposure to a physiologically relevant dose of a toxic agent, earlier than conventional toxicity tests.

Dissemination and analysis of the quality assurance (QA) and quality control (QC) practices of LC-MS based untargeted metabolomics practitioners

INTRODUCTION

The metabolomics quality assurance and quality control consortium (mQACC) evolved from the recognized need for a community-wide consensus on improving and systematizing quality assurance (QA) and quality control (QC) practices for untargeted metabolomics.

OBJECTIVES

In this work, we sought to identify and share the common and divergent QA and QC practices amongst mQACC members and collaborators who use liquid chromatography-mass spectrometry (LC-MS) in untargeted metabolomics.

METHODS

All authors voluntarily participated in this collaborative research project by providing the details of and insights into the QA and QC practices used in their laboratories. This sharing was enabled via a six-page questionnaire composed of over 120 questions and comment fields which was developed as part of this work and has proved the basis for ongoing mQACC outreach.

RESULTS

For QA, many laboratories reported documenting maintenance, calibration and tuning (82%); having established data storage and archival processes (71%); depositing data in public repositories (55%); having standard operating procedures (SOPs) in place for all laboratory processes (68%) and training staff on laboratory processes (55%). For QC, universal practices included using system suitability procedures (100%) and using a robust system of identification (Metabolomics Standards Initiative level 1 identification standards) for at least some of the detected compounds. Most laboratories used QC samples (>86%); used internal standards (91%); used a designated analytical acquisition template with randomized experimental samples (91%); and manually reviewed peak integration following data acquisition (86%). A minority of laboratories included technical replicates of experimental samples in their workflows (36%).

CONCLUSIONS

Although the 23 contributors were researchers with diverse and international backgrounds from academia, industry and government, they are not necessarily representative of the worldwide pool of practitioners due to the recruitment method for participants and its voluntary nature. However, both questionnaire and the findings presented here have already informed and led other data gathering efforts by mQACC at conferences and other outreach activities and will continue to evolve in order to guide discussions for recommendations of best practices within the community and to establish internationally agreed upon reporting standards. We very much welcome further feedback from readers of this article.

FUNCTIONAL METABOLOMICS DECIPHER BIOCHEMICAL FUNCTIONS AND ASSOCIATED MECHANISMS UNDERLIE SMALL-MOLECULE METABOLISM

Metabolism is the collection of biochemical reactions enabled by chemically diverse metabolites, which facilitate different physiological processes to exchange substances and synthesize energy in diverse living organisms. Metabolomics has emerged as a cutting-edge method to qualify and quantify the metabolites in different biological matrixes, and it has the extraordinary capacity to interrogate the biological significance that underlies metabolic modification and modulation. Liquid chromatography combined with mass spectrometry (LC/MS), as a robust platform for metabolomics analysis, has increased in popularity over the past 10 years due to its excellent sensitivity, throughput, and versatility. However, metabolomics investigation currently provides us with only phenotype data without revealing the biochemical functions and associated mechanisms. This limitation indeed weakens the core value of metabolomics data in a broad spectrum of the life sciences. In recent years, the scientific community has actively explored the functional features of metabolomics and translated this cutting-edge approach to be used to solve key multifaceted questions, such as disease pathogenesis, the therapeutic discovery of drugs, nutritional issues, agricultural problems, environmental toxicology, and microbial evolution. Here, we are the first to briefly review the history and applicable progression of LC/MS-based metabolomics, with an emphasis on the applications of metabolic phenotyping. Furthermore, we specifically highlight the next era of LC/MS-based metabolomics to target functional metabolomes, through which we can answer phenotype-related questions to elucidate biochemical functions and associated mechanisms implicated in dysregulated metabolism. Finally, we propose many strategies to enhance the research capacity of functional metabolomics by enabling the combination of contemporary omics technologies and cutting-edge biochemical techniques. The main purpose of this review is to improve the understanding of LC/MS-based metabolomics, extending beyond the conventional metabolic phenotype toward biochemical functions and associated mechanisms, to enhance research capability and to enlarge the applicable scope of functional metabolomics in small-molecule metabolism in different living organisms.

An Optimized Dual Extraction Method for the Simultaneous and Accurate Analysis of Polar Metabolites and Lipids Carried out on Single Biological Samples

The functional understanding of metabolic changes requires both a significant investigation into metabolic pathways, as enabled by global metabolomics and lipidomics approaches, and the comprehensive and accurate exploration of specific key pathways. To answer this pivotal challenge, we propose an optimized approach, which combines an efficient sample preparation, aiming to reduce the variability, with a biphasic extraction method, where both the aqueous and organic phases of the same sample are used for mass spectrometry analyses. We demonstrated that this double extraction protocol allows working with one single sample without decreasing the metabolome and lipidome coverage. It enables the targeted analysis of 40 polar metabolites and 82 lipids, together with the absolute quantification of 32 polar metabolites, providing comprehensive coverage and quantitative measurement of the metabolites involved in central carbon energy pathways. With this method, we evidenced modulations of several lipids, amino acids, and energy metabolites in HepaRG cells exposed to fenofibrate, a model hepatic toxicant, and metabolic modulator. This new protocol is particularly relevant for experiments involving limited amounts of biological material and for functional metabolic explorations and is thus of particular interest for studies aiming to decipher the effects and modes of action of metabolic disrupting compounds.

Hepatoxicity mechanism of cantharidin-induced liver LO2 cells by LC-MS metabolomics combined traditional approaches

Hepatotoxicity induced by Mylabris has been reported in both clinical and animal experiments. Cantharidin (CTD), the main active compound of Mylabris was responsible for the hepatotoxicity, which aroused widespread concern. However, the mechanism of CTD hepatotoxicity remained unclear. In this study, LO2 cells were exposed to two doses of CTD (6.25 and 25 μM) for 12 h, the levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST) and lactate dehydrogenase (LDH) were measured. The metabolites in LO2 cells were profiled by LC-MS. Partial least squares discriminant analysis and orthogonal partial least squares discriminant analysis were used for screening potential biomarkers. The MetPA software was used for clustering and pathway analysis. Network pharmacology was used to predict the genes acted with potential biomarkers. Compared with the control group, the levels of ALT, AST, and LDH was significantly increased after CTD treatment. A total of 46 potential biomarkers for hepatotoxicity induced by CTD were identified. And downregulated potential biomarkers reflected the inhibitory effects of CTD toxicity on metabolism of LO2. Moreover, CTD-induced liver toxicity of LO2 cells is mainly related to three pathways: cysteine and methionine metabolism; glutathione metabolism; and glycine, serine, and threonine metabolism. Furtherly, the mRNA expression of CES2, DNMT1, NOS1, NOS3, S1PR2, and CES1 screened by network pharmacology were regulated by CTD. These studies provide valuable mechanistic insights into CTD-associated hepatotoxicity that will aid in the development of therapeutic prevention and treatment options for this liver disease.

Multi-omics reveals the mechanisms of antidepressant-like effects of the low polarity fraction of Bupleuri Radix

ETHNOPHARMACOLOGICAL RELEVANCE

Radix Bupleuri (Bupleurum chinense DC.) is a traditional Chinese medicine that has the effect of soothing the liver and relieving depression, and widely used in the field of antidepression.

AIM OF THE STUDY

The low polarity fraction of Bupleuri Radix (PBR) has proved to be effective for the treatment of depression based on the results of our previous study. However, mechanisms of definite antidepressant-like effects remained unclear. The purpose of this study is to reveal mechanisms of antidepressant-like effects of PBR with multi-dimensional omics.

MATERIALS AND METHODS

LC-MS metabolomics combined with 16S rRNA gene sequencing were used to investigate the effects of PBR on gut microbiota and metabolites in CUMS-induced depression, and Pearson correlation analysis was carried out on gut microbiota and metabolites.

RESULTS

PBR significantly improved depression-like behaviors in the CUMS model rats. Moreover, PBR significantly increased the levels of BDNF in the hippocampus. Cecum contents metabolomics revealed that 16 biomarkers associated with PBR antidepressant effect were screened, which were involved 3 metabolic pathways including primary bile acid biosynthesis, taurine and hypotaurine metabolism, glyoxylate and dicarboxylate metabolism. Gut microbiota further analysis demonstrated that PBR increased the diversity of gut microbiota, and significantly inhibited the growth of [Prevotella] and Ochrobactrum. Furthermore, Pearson analysis revealed there was a strong correlation between cecum contents of metabolites and gut microbiota.

CONCLUSIONS

PBR improved depression-like behavior by regulating metabolic profiles and gut microbiota, and contributing to further understand the entailed antidepressant-like mechanisms of PBR.

Antibiotic-Induced Changes in Microbiome-Related Metabolites and Bile Acids in Rat Plasma

Various environmental factors can alter the gut microbiome’s composition and functionality, and modulate host health. In this study, the effects of oral and parenteral administration of two poorly bioavailable antibiotics (i.e., vancomycin and streptomycin) on male Wistar Crl/Wi(Han) rats for 28 days were compared to distinguish between microbiome-derived or -associated and systemic changes in the plasma metabolome. The resulting changes in the plasma metabolome were compared to the effects of a third reference compound, roxithromycin, which is readily bioavailable. A community analysis revealed that the oral administration of vancomycin and roxithromycin in particular leads to an altered microbial population. Antibiotic-induced changes depending on the administration routes were observed in plasma metabolite levels. Indole-3-acetic acid (IAA) and hippuric acid (HA) were identified as key metabolites of microbiome modulation, with HA being the most sensitive. Even though large variations in the plasma bile acid pool between and within rats were observed, the change in microbiome community was observed to alter the composition of the bile acid pool, especially by an accumulation of taurine-conjugated primary bile acids. In-depth investigation of the relationship between microbiome variability and their functionality, with emphasis on the bile acid pool, will be necessary to better assess the potential adverseness of environmentally induced microbiome changes.