Metabolomics in toxicology: preclinical and clinical applications

Application of a molecular networking approach using LC-HRMS combined with the MetWork webserver for clinical and forensic toxicology

Backgrounds and aims

In toxicology, LC-HRMS for untargeted screening yields a great deal of high quality spectral data. However, there we lack tools to visualize/organize the MS data. We applied molecular networking (MN) to untargeted screening interpretation. Our aims were to compare theoretical MS libraries obtained in silico with our experimental dataset in patients to broaden its application, and to use the MetWork web application for metabolite identification.

Methods

Samples were analyzed using an LC-HRMS system. For MN, data was generated using MZmine, and analyzed and visualized using MetGem. MetWork annotations were filtered and this file was used for annotation of the previously obtained MN.

Results

155 compounds including drugs found in patients were recorded. Using this dataset, we confirmed in 60 patients intake of tramadol, amitriptyline bromazepam, and cocaine. The results obtained by the reference methods were confirmed by MN approaches. Eighty percent of the compounds were common to both conventional and MN approaches. Using MetWork, metabolites and parent drugs such as amitriptyline, its metabolite nortriptyline and amitriptyline glucuronide phase 2 metabolites were anticipated and proposed as putative annotations.

Conclusion

The workflow increases confidence in toxicological screening by highlighting putative structures in biological matrices in combination with CFM-ID (Competitive Fragmentation Modeling for Metabolite Identification) and MetWork to extend the annotation of potential drugs even without a reference standard.

Artificial Intelligence in Metabolomics: A Current Review

Metabolomics and artificial intelligence (AI) form a synergistic partnership. Metabolomics generates large datasets comprising hundreds to thousands of metabolites with complex relationships. AI, aiming to mimic human intelligence through computational modeling, possesses extraordinary capabilities for big data analysis. In this review, we provide a recent overview of the methodologies and applications of AI in metabolomics studies in the context of systems biology and human health. We first introduce the AI concept, history, and key algorithms for machine learning and deep learning, summarizing their strengths and weaknesses. We then discuss studies that have successfully used AI across different aspects of metabolomic analysis, including analytical detection, data preprocessing, biomarker discovery, predictive modeling, and multi-omics data integration. Lastly, we discuss the existing challenges and future perspectives in this rapidly evolving field. Despite limitations and challenges, the combination of metabolomics and AI holds great promises for revolutionary advancements in enhancing human health.

Lipid responses to perfluorooctane sulfonate exposure for multiple rat organs

Perfluorooctane sulfonate (PFOS) is a persistent chemical that has long been a threat to human health. However, the molecular effects of PFOS on various organs are not well studied. In this study, male Sprague-Dawley rats were treated with various doses of PFOS through gavage for 21 days. Subsequently, the liver, lung, heart, kidney, pancreas, testis, and serum of the rats were harvested for lipid analysis. We applied a focusing lipidomic analytical strategy to identify key lipid responses of phosphorylcholine-containing lipids, including phosphatidylcholines and sphingomyelins. Partial least squares discriminant analysis revealed that the organs most influenced by PFOS exposure were the liver, kidney, and testis. Changes in the lipid profiles of the rats indicated that after exposure, levels of diacyl-phosphatidylcholines and 22:6-containing phosphatidylcholines in the liver, kidney, and testis of the rats decreased, whereas the level of 20:3-containing phosphatidylcholines increased. Furthermore, levels of polyunsaturated fatty acids-containing plasmenylcholines decreased. Changes in sphingomyelin levels indicated organ-dependent responses. Decreased levels of sphingomyelins in the liver, nonmonotonic dose responses in the kidney, and irregular responses in the testis after PFOS exposure are observed. These lipid responses may be associated with alterations pertaining to phosphatidylcholine synthesis, fatty acid metabolism, membrane properties, and oxidative stress in the liver, kidney, and testis. Lipid responses in the liver could have contributed to the observed increase in liver to body weight ratios. The findings suggest potential toxicity and possible mechanisms associated with PFOS in multiple organs.

Molecular mechanisms of cadmium-induced cytotoxicity in human ovarian granulosa cells identified using integrated omics

Epidemiological and clinical data have demonstrated that exposure to cadmium (Cd), a toxic heavy metal, is associated with an increased risk of female infertility. Granulosa cells, the main somatic cells comprising ovarian follicles, are one of the main targets of Cd in the ovaries. However, the mechanism by which Cd induces cytotoxicity in granulosa cells has not been fully elucidated. In this study, we exposed human ovarian granulosa cells (KGN cells) to Cd and conducted in vitro cell experiments and multi-omics (metabolomics and transcriptomics) methods to elucidate these mechanisms. Cd exposure was found to not only induce the apoptosis of the KGN cells but also further reduced mitochondrial function by decreasing mitochondrial membrane potential, ATP production, and respiratory chain complex activity as well as increasing mitochondrial reactive oxygen species (ROS) production. A total of 443 differentially expressed metabolites (160 upregulated and 283 downregulated) and 5200 differentially expressed genes (4634 upregulated and 566 downregulated) were observed in the Cd exposed-cells. The multi-omics data showed that Cd interfered with citric acid cycle (TCA cycle), amino acid (including alanine, glycine, serine, threonine, arginine, and proline) metabolism, and calcium signaling. These findings help to better elucidate the potential toxicity mechanisms of Cd on granulosa cells and the ovary.

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.

Deeper insights into the effects of low dietary levels of polychlorinated biphenyls on pig metabolism using gas chromatography-high resolution mass spectrometry metabolomics

Polychlorinated biphenyls (PCBs) are a class of contaminants of great concern, linked to the development of many chronic diseases. Adverse effects of PCBs have been documented in humans after accidental and massive exposure. However, little is known about the effect of chronic exposure to low-dose PCB mixtures, and studies regarding scattered lifetime exposures to non-dioxin-like (NDL)-PCBs are especially missing. In this work, serum samples from pigs chronically exposed through their diet during 22 days to Aroclor 1260 (i.e. a commercially available mixture of NDL-PCBs) underwent a metabolomics analysis using gas chromatography-high resolution mass spectrometry (GC-HRMS), with the objective to investigate the effect of exposure to low doses of NDL-PCBs (few ng/kg body weight (b.w.) per day). The study showed that the serum profiles of 84 metabolites are significantly altered by the administration of Aroclor 1260, of which 40 could be identified at level 1. The aggregate interpretation of the results of this study, together with the outcome of a previous one involving LC-HRMS profiling, provided a substantial and concise overview of the effect of low dose exposure to NDL-PCBs, reflecting the hepatotoxic and neurotoxic effects already reported in literature at higher and longer exposures. These results are intended to contribute to the debate on the current toxicological reference values for these substances.

Emerging trends and applications of metabolomics in food science and nutrition

The study of all chemical processes involving metabolites is known as metabolomics. It has been developed into an essential tool in several disciplines, such as the study of plant physiology, drug development, human diseases, and nutrition. The field of food science, diagnostic biomarker research, etiological analysis in the field of medical therapy, and raw material quality, processing, and safety have all benefited from the use of metabolomics recently. Food metabolomics includes the use of metabolomics in food production, processing, and human diets. As a result of changing consumer habits and the rising of food industries all over the world, there is a remarkable increase in interest in food quality and safety. It requires the employment of various technologies for the food supply chain, processing of food, and even plant breeding. This can be achieved by understanding the metabolome of food, including its biochemistry and composition. Additionally, Food metabolomics can be used to determine the similarities and differences across crop kinds, as an indicator for tracking the process of ripening to increase crops' shelf life and attractiveness, and identifying metabolites linked to pathways responsible for postharvest disorders. Moreover, nutritional metabolomics is used to investigate the connection between diet and human health through detection of certain biomarkers. This review assessed and compiled literature on food metabolomics research with an emphasis on metabolite extraction, detection, and data processing as well as its applications to the study of food nutrition, food-based illness, and phytochemical analysis. Several studies have been published on the applications of metabolomics in food but further research concerning the use of standard reproducible procedures must be done. The results published showed promising uses in the food industry in many areas such as food production, processing, and human diets. Finally, metabolome-wide association studies (MWASs) could also be a useful predictor to detect the connection between certain diseases and low molecular weight biomarkers.

Metabolomics of Respiratory Diseases

Metabolomics is an expanding field of systems biology that is gaining significant attention in respiratory research. As a unique approach to understanding and diagnosing diseases, metabolomics provides a snapshot of all metabolites present in biological samples such as exhaled breath condensate, bronchoalveolar lavage, plasma, serum, urine, and other specimens that may be obtained from patients with respiratory diseases. In this article, we review the rapidly expanding field of metabolomics in its application to respiratory diseases, including asthma, chronic obstructive pulmonary disease (COPD), pneumonia, and acute lung injury, along with its more severe form, adult respiratory disease syndrome. We also discuss the potential applications of metabolomics for monitoring exposure to aerosolized occupational and environmental materials. With the latest advances in our understanding of the microbiome, we discuss microbiome-derived metabolites that arise from the gut and lung in asthma and COPD that have mechanistic implications for these diseases. Recent literature has suggested that metabolomics analysis using nuclear magnetic resonance (NMR) and mass spectrometry (MS) approaches may provide clinicians with the opportunity to identify new biomarkers that may predict progression to more severe diseases which may be fatal for many patients each year.

Multigenerational Exposure to Uranium Changes Sperm Metabolome in Rats

Male infertility is a major public health issue that can be induced by a host of lifestyle risk factors such as environment, nutrition, smoking, stress, and endocrine disruptors. Regarding the human population exposed to uranium, it is necessary to explore these effects on male reproduction in multigenerational studies. The sensitivity of mass spectrometry (MS)-based methods has already proved to be extremely useful in metabolite identification in rats exposed to low doses of uranium, but also in human sperm. We applied this method to rat sperm over three generations (F0, F1 and F2) with multigenerational uranium exposure. Our results show a significant content of uranium in generation F0, and a reduction in the pregnancy rate only in generation F1. Based on principal component analysis (PCA), we observed discriminant profiles between generations. The partial least squares discriminant analysis (PLS-DA) of the 48 annotated variables confirmed that parental exposure of generation F0 (during both the preconceptional and prenatal periods) can have metabolic effects on spermatozoa for the next two generations. Metabolomics applied to epididymal spermatozoa is a novel approach to detecting the multigenerational effects of uranium in an experimental model, but could be also recommended to identify potential biomarkers evaluating the impact of uranium on sperm in exposed infertile men.

A Multi-Omics Approach to Evaluate the Toxicity Mechanisms Associated with Silver Nanoparticles Exposure

Silver nanoparticles (AgNPs) are currently used in many different industrial, commercial and health fields, mainly due to their antibacterial properties. Due to this widespread use, humans and the environment are increasingly exposed to these types of nanoparticles, which is the reason why the evaluation of the potential toxicity associated with AgNPs is of great importance. Although some of the toxic effects induced by AgNPs have already been shown, the elucidation of more complete mechanisms is yet to be achieved. In this sense, and since the integration of metabolomics and transcriptomics approaches constitutes a very useful strategy, in the present study targeted and untargeted metabolomics and DNA microarrays assays have been combined to evaluate the molecular mechanisms involved in the toxicity induced by 10 nm AgNPs. The results have shown that AgNPs induce the synthesis of glutathione as a cellular defense mechanism to face the oxidative environment, while inducing the depletion of relevant molecules implicated in the synthesis of important antioxidants. In addition, it has been observed that AgNPs completely impair the intracellular energetic metabolism, especially affecting the production of adenosine triphosphate (ATP) and disrupting the tricarboxylic acids cycle. It has been demonstrated that AgNPs exposure also affects the glycolysis pathway. The effect on such pathway differs depending on the step of the cycle, which a significant increase in the levels of glucose as way to counterbalance the depleted levels of ATP.

Aloe vera and Artemisia vulgaris hydrogels: Exploring the toxic effects of structural transformation of the biocompatible materials

OBJECTIVES

This study was aimed to evaluate the toxicity profile of hydrogels of plant-derived mucilage from Aloe vera and Artemisia vulgaris used for various drug delivery applications, yet no such toxicity study has been reported for the toxicity evaluation of 3D structures. New Drug carrier should be harmless for drug delivery applications.

METHODS

Acute and sub-acute (repeated dose) oral toxicity studies were conducted following OECD 407 and 425 guidelines. In vitro toxicity through hemolysis and MTT assay were checked against RBC's and human macrophages respectively.

RESULTS

The hemolysis and MTT assay showed good compatibility of hydrogels with blood components. Mutagenicity testing showed no genotoxic effects of hydrogels. In vivo toxicity evaluation was done in female albino rats and rabbits. General behavior, adverse effects, clinical signs and symptoms, and mortality were recorded for 14 days post-treatment which showed no significant (p < 005) abnormality. Hematological and biochemical parameters including LFTs and RFTs appeared to be normal with slight variations in the treated groups. Normal architecture of kidney, liver, heart, and intestine was evident upon histopathological analyses.

CONCLUSION

Hence, the results suggested that the 3D structure of Aloe vera and Artemisia vulgaris based hydrogels is safe upon ingestion and can be used for drug delivery science being cheap, natural and biocompatible.

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.

Unravelling the Anticancer Mechanisms of Traditional Herbal Medicines with Metabolomics

Metabolite profiling of cancer cells presents many opportunities for anticancer drug discovery. The Chinese, Indian, and African flora, in particular, offers a diverse source of anticancer therapeutics as documented in traditional folklores. In-depth scientific information relating to mechanisms of action, quality control, and safety profile will promote their extensive usage in cancer therapy. Metabolomics may be a more holistic strategy to gain valuable insights into the anticancer mechanisms of action of plants but this has remained largely unexplored. This review, therefore, presents the available metabolomics studies on the anticancer effects of herbal medicines commonly used in Africa and Asia. In addition, we present some scientifically understudied ‘candidate plants’ for cancer metabolomics studies and highlight the relevance of metabolomics in addressing other challenges facing the drug development of anticancer herbs. Finally, we discussed the challenges of using metabolomics to uncover the underlying mechanisms of potential anticancer herbs and the progress made in this regard.

Current State of Metabolomics Research in Meat Quality Analysis and Authentication

In the past decades, as an emerging omic, metabolomics has been widely used in meat science research, showing promise in meat quality analysis and meat authentication. This review first provides a brief overview of the concept, analytical techniques, and analysis workflow of metabolomics. Additionally, the metabolomics research in quality analysis and authentication of meat is comprehensively described. Finally, the limitations, challenges, and future trends of metabolomics application in meat quality analysis and meat authentication are critically discussed. We hope to provide valuable insights for further research in meat quality.

An integrative approach based on GC-qMS and NMR metabolomics data as a comprehensive strategy to search potential breast cancer biomarkers

INTRODUCTION

Globally, breast cancer (BC) is leading at the top of women's diseases and, as a multifactorial disease, there is the need for the development of new approaches to aid clinicians on monitoring BC treatments. In this sense, metabolomic studies have become an essential tool allowing the establishment of interdependency among metabolites in biological samples.

OBJECTIVE

The combination of nuclear magnetic resonance (NMR) and gas chromatography-quadrupole mass spectrometry (GC-qMS) based metabolomic analyses of urine and breast tissue samples from BC patients and cancer-free individuals was used.

METHODS

Multivariate statistical tools were used in order to obtain a panel of metabolites that could discriminate malignant from healthy status assisting in the diagnostic field. Urine samples (n = 30), cancer tissues (n = 30) were collected from BC patients, cancer-free tissues were resected outside the tumor margin from the same donors (n = 30) while cancer-free urine samples (n = 40) where obtained from healthy subjects and analysed by NMR and GC-qMS methodologies.

RESULTS

The orthogonal partial least square discriminant analysis model showed a clear separation between BC patients and cancer-free subjects for both classes of samples. Specifically, for urine samples, the goodness of fit (R²Y) and predictive ability (Q²) was 0.946 and 0.910, respectively, whereas for tissue was 0.888 and 0.813, revealing a good predictable accuracy. The discrimination efficiency and accuracy of tissue and urine metabolites was ascertained by receiver operating characteristic curve analysis that allowed the identification of metabolites with high sensitivity and specificity. The metabolomic pathway analysis identified several dysregulated pathways in BC, including those related with lactate, valine, aspartate and glutamine metabolism. Additionally, correlations between urine and tissue metabolites were investigated and five metabolites (e.g. acetone, 3-hexanone, 4-heptanone, 2-methyl-5-(methylthio)-furan and acetate) were found to be significant using a dual platform approach.

CONCLUSION

Overall, this study suggests that an improved metabolic profile combining NMR and GC-qMS may be useful to achieve more insights regarding the mechanisms underlying cancer.

A Metabolic Model of Intestinal Secretions: The Link between Human Microbiota and Colorectal Cancer Progression

The human gut microbiota plays a dual key role in maintaining human health or inducing disorders, for example, obesity, type 2 diabetes, and cancers such as colorectal cancer (CRC). High-throughput data analysis, such as metagenomics and metabolomics, have shown the diverse effects of alterations in dynamic bacterial populations on the initiation and progression of colorectal cancer. However, it is well established that microbiome and human cells constantly influence each other, so it is not appropriate to study them independently. Genome-scale metabolic modeling is a well-established mathematical framework that describes the dynamic behavior of these two axes at the system level. In this study, we created community microbiome models of three conditions during colorectal cancer progression, including carcinoma, adenoma and health status, and showed how changes in the microbial population influence intestinal secretions. Conclusively, our findings showed that alterations in the gut microbiome might provoke mutations and transform adenomas into carcinomas. These alterations include the secretion of mutagenic metabolites such as H₂S, NO compounds, spermidine and TMA (trimethylamine), as well as the reduction of butyrate. Furthermore, we found that the colorectal cancer microbiome can promote inflammation, cancer progression (e.g., angiogenesis) and cancer prevention (e.g., apoptosis) by increasing and decreasing certain metabolites such as histamine, glutamine and pyruvate. Thus, modulating the gut microbiome could be a promising strategy for the prevention and treatment of CRC.

Benchmark Concentrations for Untargeted Metabolomics Versus Transcriptomics for Liver Injury Compounds in In Vitro Liver Models

Interpretation of untargeted metabolomics data from both in vivo and physiologically relevant in vitro model systems continues to be a significant challenge for toxicology research. Potency-based modeling of toxicological responses has served as a pillar of interpretive context and translation of testing data. In this study, we leverage the resolving power of concentration-response modeling through benchmark concentration (BMC) analysis to interpret untargeted metabolomics data from differentiated cultures of HepaRG cells exposed to a panel of reference compounds and integrate data in a potency-aligned framework with matched transcriptomic data. For this work, we characterized biological responses to classical human liver injury compounds and comparator compounds, known to not cause liver injury in humans, at 10 exposure concentrations in spent culture media by untargeted liquid chromatography-mass spectrometry analysis. The analyte features observed (with limited metabolites identified) were analyzed using BMC modeling to derive compound-induced points of departure. The results revealed liver injury compounds produced concentration-related increases in metabolomic response compared to those rarely associated with liver injury (ie, sucrose, potassium chloride). Moreover, the distributions of altered metabolomic features were largely comparable with those observed using high throughput transcriptomics, which were further extended to investigate the potential for in vitro observed biological responses to be observed in humans with exposures at therapeutic doses. These results demonstrate the utility of BMC modeling of untargeted metabolomics data as a sensitive and quantitative indicator of human liver injury potential.

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.

Investigating metabolism by mass spectrometry: From steady state to dynamic view

Metabolism is the set of life-sustaining reactions in organisms. These biochemical reactions are organized in metabolic pathways, in which one metabolite is converted through a series of steps catalyzed by enzymes in another chemical compound. Metabolic reactions are categorized as catabolic, the breaking down of metabolites to produce energy, and/or anabolic, the synthesis of compounds that consume energy. The balance between catabolism of the preferential fuel substrate and anabolism defines the overall metabolism of a cell or tissue. Metabolomics is a powerful tool to gain new insights contributing to the identification of complex molecular mechanisms in the field of biomedical research, both basic and translational. The enormous potential of this kind of analyses consists of two key aspects: (i) the possibility of performing so-called targeted and untargeted experiments through which it is feasible to verify or formulate a hypothesis, respectively, and (ii) the opportunity to run either steady-state analyses to have snapshots of the metabolome at a given time under different experimental conditions or dynamic analyses through the use of labeled tracers. In this review, we will highlight the most important practical (e.g., different sample extraction approaches) and conceptual steps to consider for metabolomic analysis, describing also the main application contexts in which it is used. In addition, we will provide some insights into the most innovative approaches and progress in the field of data analysis and processing, highlighting how this part is essential for the proper extrapolation and interpretation of data.

Characterization of Monophasic Solvent-Based Tissue Extractions for the Detection of Polar Metabolites and Lipids Applying Ultrahigh-Performance Liquid Chromatography-Mass Spectrometry Clinical Metabolic Phenotyping Assays

Metabolic phenotyping of tissues uses metabolomics and lipidomics to measure the relative polar and nonpolar (lipid) metabolite levels in biological samples. This approach aims to understand disease biochemistry and identify biochemical markers of disease. Sample preparation methods must be reproducible, sensitive (high metabolite and lipid yield), and ideally rapid. We evaluated three biphasic methods for polar and nonpolar compound extraction (chloroform/methanol/water, dichloromethane/methanol/water, and methyl tert-butyl ether [MTBE]/methanol/water), a monophasic method for polar compound extraction (acetonitrile/methanol/water), and a monophasic method for nonpolar compound extraction (isopropanol/water). All methods were applied to mammalian heart, kidney, and liver tissues. Polar extracts were analyzed by hydrophilic interaction chromatography (HILIC) ultrahigh-performance liquid chromatography-mass spectrometry (UHPLC-MS) and nonpolar extracts by C₁₈ reversed-phase UHPLC-MS. Method reproducibility and yield were assessed using multiple annotated endogenous compounds (putatively and MS/MS annotated). Monophasic methods had the highest yield and high reproducibility for both polar (positive ion: median relative standard deviation (RSD) < 18%; negative ion: median RSD < 28%) and nonpolar (positive and negative ion: median RSD < 15%) extractions for heart, kidneys, and liver. The polar monophasic method extracted higher levels of lipid than biphasic polar extractions, and these lipids caused minimal detection suppression for other compounds during HILIC UHPLC-MS. The nonpolar monophasic method had similar or greater detection responses of all detected lipid classes compared to biphasic methods (including increased phosphatidylinositol, phosphatidylserine, and cardiolipin responses). Monophasic methods are quicker and simpler than biphasic methods and are therefore most suited for future automation.

Mining the effect of the neonicotinoids imidacloprid and clothianidin on the chemical homeostasis and energy equilibrium of primary mouse neural stem/progenitor cells using metabolomics

The projection of plant protection products' (PPPs) toxicity to non-target organisms at early stages of their development is challenging and demanding. Recent developments in bioanalytics, however, have facilitated the study of fluctuations in the metabolism of biological systems in response to treatments with bioactives and the discovery of corresponding toxicity biomarkers. Neonicotinoids are improved insecticides that target nicotinic acetylocholine receptors (nAChR) in insects which are similar to mammals. Nonetheless, they have sparked controversy due to effects on non-target organisms. Within this context, mammalian cell cultures represent ideal systems for the development of robust models for the dissection of PPPs' toxicity. Thus, we have investigated the toxicity of imidacloprid, clothianidin, and their mixture on primary mouse (Mus musculus) neural stem/progenitor (NSPCs) and mouse neuroblastoma-derived Neuro-2a (N2a) cells, and the undergoing metabolic changes applying metabolomics. Results revealed that NSPCs, which in vitro resemble those that reside in the postnatal and adult central nervous system, are five to seven-fold more sensitive than N2a to the applied insecticides. The energy equilibrium of NSPCs was substantially altered, as it is indicated by fluctuations of metabolites involved in energy production (e.g. glucose, lactate), Krebs cycle intermediates, and fatty acids, which are important components of cell membranes. Such evidence plausibly suggests a switch of cells' energy-producing mechanism to the direct metabolism of glucose to lactate in response to insecticides. The developed pipeline could be further exploited in the discovery of unintended effects of PPPs at early steps of development and for regulatory purposes.

Metabolomics in the study of spontaneous animal diseases

Using analytical chemistry techniques such as nuclear magnetic resonance (NMR) spectroscopy and liquid or gas chromatography-mass spectrometry (LC/GC-MS), metabolomics allows detection of most endogenous and exogenous metabolites in a biological sample. Metabolomics has a wide range of applications, and has been employed in nutrition science, toxicology, environmental studies, and systems biology. Metabolomics is particularly useful in biomedical science, and has been used for diagnostic laboratory testing, identifying targets for drug development, and monitoring drug metabolism, mode of action, and toxicity. Despite its immense potential, metabolomics remains underutilized in the study of spontaneous animal diseases. Our aim was to comprehensively review the existing literature on the use of metabolomics in spontaneous veterinary diseases. Three databases were used to find journal articles that applied metabolomics in veterinary medicine. A screening process was then conducted to eliminate references that did not meet the eligibility criteria; only primary research studies investigating spontaneous animal disease were included; 38 studies met the inclusion criteria. The main techniques used were NMR and MS. All studies detected metabolite alterations in diseased animals compared with non-diseased animals. Metabolomics was mainly used to study diseases of the digestive, reproductive, and musculoskeletal systems. Inflammatory conditions made up the largest proportion of studies when articles were categorized by disease process. Following a comprehensive analysis of the literature on metabolomics in spontaneous veterinary diseases, we concluded that metabolomics, although in its early stages in veterinary research, is a promising tool regarding diagnosis, biomarker discovery, and in uncovering new insights into disease pathophysiology.

Triphenyl phosphate permeates the blood brain barrier and induces neurotoxicity in mouse brain

Concerns have been raised over the neurotoxicity of triphenyl phosphate (TPP), but there have been few studies of the neurotoxic effects of TPP on mammals and the underlying mechanisms. In this study, weaned male mice (C57/BL6) were used and exposed to 0, 50, or 150 mg/kg TPP daily by oral gavage for 30 days. The blood brain barrier (BBB) permeability of TPP and its metabolite diphenyl phosphate (DPP) in the brain, and TPP induced metabolomic and transcriptomic changes of the brain were investigated. The results showed that TPP and DPP can cross the BBB of mice. Histopathological examination of the brain revealed abnormalities in the hippocampus, cortex and thalamus, and mice treated with high doses showed a potential inflammation in the thalamus and hippocampus. Untargeted metabolomic results revealed that the changed level of glutamic acid, N-acetyl CoA metabolites, and organic acid in the brain of treated mice, suggest that amino acid and lipid metabolism was interfered. RNA-seq data indicated that neuronal transcription processes and cell apoptosis pathway (forkhead box (FOXO), and mitogen-activated protein kinase (MAPK) signaling pathways) were significantly affected by TPP exposure. RT-PCR showed proinflammation cytokine tumor necrosis factor alpha (TNF-α) and interleukin-6 (IL-6)) levels were increased, while antioxidant genes including nuclear factor-E2-related factor 2 (Nrf2), heme oxygenase1 (HO-1) and superoxide dismutase (SOD1) decreased. These results suggest that TPP could cause a degree of neurotoxicity by inducing neuroinflammation and neuronal apoptosis, which are related to oxidative stress. The potential implications for neurophysiology and behavioral regulation cannot be ignored.

Metabolomic biomarkers in urine of rats following long-term low-dose exposure of cadmium and/or chlorpyrifos

Heavy metals and pesticides can be easily enriched in food chains and accumulated in organisms, thus pose significant threat to human health. However, their combined effects for long-term exposure at low dose has not been thoroughly investigated; especially there was no biofluid biomarker available to noninvasively diagnose the toxicosis of the combined exposure of the two chemicals at their low levels. In this study, we investigated the change of urine metabolites of rats with 90-day exposure to heavy metal cadmium (Cd) and/or organophosphorus pesticide chlorpyrifos (CPF) using gas chromatography-mass spectrometry (GC-MS)-based metabolomics approach. Our results showed that the interaction of Cd and CPF mainly displayed an antagonistic effect. We identified the panels of metabolite biomarkers in urine: benzoic acid and mannose were unique biomarkers for Cd exposure; creatinine and N-phenylacetyl glycine were unique biomarkers for CPF exposure; anthranilic acid, ribitol, and glucose were unique biomarkers for Cd plus CPF exposure. Our results suggest that 90-day exposure to Cd and/or CPF could cause a disturbance in energy and amino acid metabolism. And urine metabolomics analysis can help understand the toxicity of low dose exposure to mixed environmental chemicals.

Metabolomics in the development and progression of rheumatoid arthritis: A systematic review

OBJECTIVE

A systematic review and analysis of data from several rheumatoid arthritis metabolomics studies attempts to determine which metabolites can be used as potential biomarkers for the diagnosis of rheumatoid arthritis and to explore the pathogenesis of rheumatoid arthritis.

METHODS

We searched all the subject-related documents published by EMBASE, PubMed, Web of Science, and Cochrane Library from the database to the September 2019 publication. Two researchers independently screened the literature and extracted the data. QUADOMICS tool was used to assess the quality of studies included in this systematic review.

RESULTS

A total of 10 studies met the inclusion criteria of systematic review, including 502 patients with rheumatoid arthritis and 373 healthy people. Among them, the biological samples utilised for metabolomic analysis include: serum (n=8), urine (n=1) and synovial fluid (n=1). Some metabolites play an important role in rheumatoid arthritis: glucose, lactic acid, citric acid, leucine, methionine, isoleucine, valine, phenylalanine, threonine, serine, proline, glutamate, histidine, alanine, cholesterol, glycerol, and ribose.

CONCLUSIONS

Metabolomics provides important new opportunities for further research in rheumatoid arthritis and is expected to elucidate the pathogenesis of rheumatoid arthritis that has not been fully understood before.

Identification of metabolite biomarkers in serum of rats exposed to chlorpyrifos and cadmium

Chlorpyrifos (CPF) and cadmium (Cd) are widespread environmental pollutants, which are often present in drinking water and foods. However, the combined effects of CPF and Cd were not entirely clear at present. There was also no biomarker available to diagnose the poisoning of the two chemicals at low dose for long-term exposures. In this study, we investigated the change of serum metabolites of rats with subchronic exposure to CPF, Cd, and CPF plus Cd using gas chromatography-mass spectrometer-based metabolomics approach. We performed a stepwise optimization algorithm based on receiver operating characteristic to identify serum metabolite biomarkers for toxic diagnosis of the chemicals at different doses after 90-day exposure. We found that aminomalonic acid was the biomarker for the toxicity of Cd alone administration, and serine and propanoic acid were unique biomarkers for the toxicities of CPF plus Cd administrations. Our results suggest that subchronic exposure to CPF and Cd alone, or in combination at their low doses, could cause disturbance of energy and amino acid metabolism. Overall, we have shown that analysis of serum metabolomics can make exceptional contributions to the understanding of the toxic effects following long-term low-dose exposure of the organophosphorus pesticide and heavy metal.

Genome-Scale Model-Based Identification of Metabolite Indicators for Early Detection of Kidney Toxicity

Identifying early indicators of toxicant-induced organ damage is critical to provide effective treatment. To discover such indicators and the underlying mechanisms of toxicity, we used gentamicin as an exemplar kidney toxicant and performed systematic perturbation studies in Sprague Dawley rats. We obtained high-throughput data 7 and 13 h after administration of a single dose of gentamicin (0.5 g/kg) and identified global changes in genes in the liver and kidneys, metabolites in the plasma and urine, and absolute fluxes in central carbon metabolism. We used these measured changes in genes in the liver and kidney as constraints to a rat multitissue genome-scale metabolic network model to investigate the mechanism of gentamicin-induced kidney toxicity and identify metabolites associated with changes in tissue gene expression. Our experimental analysis revealed that gentamicin-induced metabolic perturbations could be detected as early as 7 h postexposure. Our integrated systems-level analyses suggest that changes in kidney gene expression drive most of the significant metabolite alterations in the urine. The analyses thus allowed us to identify several significantly enriched injury-specific pathways in the kidney underlying gentamicin-induced toxicity, as well as metabolites in these pathways that could serve as potential early indicators of kidney damage.

Metabolomics describes previously unknown toxicity mechanisms of isoniazid and rifampicin

Isoniazid and rifampicin are well-known anti-mycobacterial agents and are widely used to treat pulmonary tuberculosis (TB) as part of the combined therapy approach, recommended by the World Health Organization. The ingestion of these first-line TB drugs are, however, not free of side effects, and are toxic to the liver, kidney, and central nervous system. These side effects are associated with poor treatment compliance, resulting in TB treatment failure, relapse and drug resistant TB. This occurrence has subsequently led to the recent application of novel research technologies, towards a better understanding of the underlying toxicity mechanisms of TB drugs in humans, mostly focussing on the 2 most important TB drugs: isoniazid and rifampicin. In this review, we discuss the contribution that one such an approach, termed metabolomics has made toward this field, and also highlight the impact that this might have towards the development of improved TB treatment regimens.

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.

Assessment of human plasma and urine sample preparation for reproducible and high-throughput UHPLC-MS clinical metabolic phenotyping

In this study we assess multiple sample preparation methods for UHPLC-MS metabolic phenotyping analysis of human urine and plasma. All methods are discussed in terms of metabolite and lipid coverage and reproducibility.

Multi-Organ NMR Metabolomics to Assess In Vivo Overall Metabolic Impact of Cisplatin in Mice

This work describes, to our knowledge, the first NMR metabolomics analysis of mice kidney, liver, and breast tissue in response to cisplatin exposure, in search of early metabolic signatures of cisplatin biotoxicity. Balb/c mice were exposed to a single 3.5 mg/kg dose of cisplatin and then euthanized; organs (kidney, liver, breast tissue) were collected at 1, 12, and 48 h. Polar tissue extracts were analyzed by NMR spectroscopy, and the resulting spectra were studied by multivariate and univariate analyses. The results enabled the identification of the most significant deviant metabolite levels at each time point, and for each tissue type, and showed that the largest metabolic impact occurs for kidney, as early as 1 h post-injection. Kidney tissue showed a marked depletion in several amino acids, comprised in an overall 13-metabolites signature. The highest number of changes in all tissues was noted at 12 h, although many of those recovered to control levels at 48 h, with the exception of some persistently deviant tissue-specific metabolites, thus enabling the identification of relatively longer-term effects of cDDP. This work reports, for the first time, early (1-48 h) concomitant effects of cDDP in kidney, liver, and breast tissue metabolism, thus contributing to the understanding of multi-organ cDDP biotoxicity.

Targeted metabolome analysis of the dog brain exposed to PCBs suggests inhibition of oxidative phosphorylation by hydroxylated PCBs

Canis lupus familiaris (domestic dog) possess a high capacity to metabolize higher-chlorinated polychlorinated biphenyls (PCBs) to thyroid hormone (TH)-like hydroxylated PCB metabolites (OH-PCBs). As a result, the brain could be at high risk of toxicity caused by OH-PCBs. To evaluate the effect of OH-PCBs on dog brain, we analyzed OH-PCB levels in the brain and the metabolome of the frontal cortex following exposure to a mixture of PCBs (CB18, 28, 70, 77, 99, 101, 118, 138, 153, 180, 187, and 202). 4-OH-CB202 and 4-OH-CB107 were major OH-PCBs in the brain of PCB-exposed dogs. These OH-PCBs were associated with metabolites involved in urea cycle, proline-related compounds, and purine, pyrimidine, glutathione, and amino-acid metabolism in dog brain. Moreover, adenosine triphosphate levels in the PCBs exposure group were significantly lower than in the control group. These results suggest that OH-PCB exposure is associated with a disruption in TH homeostasis, generation of reactive oxygen species, and/or disruption of oxidative phosphorylation (OXPHOS) in brain cells. Among them, OXPHOS disturbance could be associated with both disruptions in cellular amino-acid metabolism and urea cycle. Therefore, an OXPHOS activity assay was performed to evaluate the disruption of OXPHOS by OH-PCBs. The results indicated that 4-OH-CB107 inhibits the function of Complexes III, IV, and V of the electron transport chain, suggesting that 4-OH-CB107 inhibit these complexes in OXPHOS. The neurotoxic effects of PCB exposure may be mediated through mitochondrial toxicity of OH-PCBs in the brain.

Biological monitoring of workers exposed to engineered nanomaterials

As the number of nanomaterial workers increase there is need to consider whether biomonitoring of exposure should be used as a routine risk management tool. Currently, no biomonitoring of nanomaterials is mandated by authoritative or regulatory agencies. However, there is a growing knowledge base to support such biomonitoring, but further research is needed as are investigations of priorities for biomonitoring. That research should be focused on validation of biomarkers of exposure and effect. Some biomarkers of effect are generally nonspecific. These biomarkers need further interpretation before they should be used. Overall biomonitoring of nanomaterial workers may be important to supplement risk assessment and risk management efforts.

Alterations in urinary metabolomic profiles due to lead exposure from a lead-acid battery recycling site

Lead poisoning is considered a public health threat, particularly in developing countries. Health problems from Pb exposure occur in many parts of the world, especially near Pb mines, Pb smelters, and used lead-acid battery (ULAB) recycling plants. In this study, we analyzed the urine metabolome of residents in a village located near a ULAB recycling facility to investigate the biological effects of Pb exposure (ULAB: n = 44, Reference: n = 51). Lasso linear regression models were moderately predictive of blood Pb levels, as evaluated by a training set (R² = 0.813) and against an external test set (R²_EXT = 0.647). In lasso logistic regression models, areas under receiver operating characteristic curves, as measured by 5-fold cross-validation (AUC_CV = 0.871) and against an external test set (AUC_EXT = 0.917), indicated accurate classification of urine samples from the affected village and from a reference site. Ten candidate biomarkers identified at false discovery rates of <0.05 were associated with ATP-binding cassette (ABC) transporters, possibly related to the disruption of small-molecule transport in the kidney; amino acid, porphyrin, and chlorophyll metabolism; and the heme biosynthetic pathway. Collectively, the results suggest that lead Pb is related to the health effects in individuals residing in ULAB site by alteration of these biological pathways.

Determination of Five Sex Hormones in Urine Samples for Early Evaluation of Male Reproductive Toxicity Induced by Phthalate Esters in Rats

In this work, male rats were exposed to multiple phthalate esters (MIXPs) in a long-term low-dose model for the early evaluation of reproductive toxicity. An ananlysis method with better sensitivity, accuracy and precision was established to determine the five sex hormones (androstenedione, testosterone, dehydroepiandrosterone, dihydrotestosterone, and estrone) in collected urine samples. The results showed that all the analytes in the MIXPs treated group changed in a time-dependent manner. Specifically, estrone significantly decreased from the 30th day and the other four changed from the 30th day and then significantly increased on the 60th day, while no obvious changes were found in the control group. Therefore, a possible way was provided for the early evaluation of male reproductive toxicity induced by Phthalate esters (PEs) . The reliability of judgment was improved by observing the changes of five target hormones simultaneously. Furthermore, good compliance was predicted for the practical application due to the noninvasive and convenient urine sample collection.

GC-MS metabolomics reveals disturbed metabolic pathways in primary mouse hepatocytes exposed to subtoxic levels of 3,4-methylenedioxymethamphetamine (MDMA)

3,4-Methylenedioxymethamphetamine (MDMA, ecstasy) is a well-known hepatotoxic drug. Although its toxicity has been thoroughly studied at high concentrations, there is still insufficient knowledge on possible alterations of cell function at subtoxic concentrations, which are in fact more representative concentrations of intoxication scenarios. In this study, a gas chromatography-mass spectrometry (GC-MS) metabolomics approach was used to investigate the metabolic changes in primary mouse hepatocytes (PMH) exposed to two subtoxic concentrations of MDMA (LC₀₁ and LC₁₀) for 24 h. Metabolomic profiling of both intracellular metabolites and volatile metabolites in the extracellular medium of PMH was performed. Multivariate analysis showed that the metabolic pattern of cells exposed to MDMA discriminates from the controls in a concentration-dependent manner. Exposure to LC₁₀ MDMA induces a significant increase in some intracellular metabolites, including oleic acid and palmitic acid, and a decrease in glutamate, aspartate, 5-oxoproline, fumarate, malate, phosphoric acid, α-ketoglutarate and citrate. Extracellular metabolites such as acetophenone, formaldehyde, pivalic acid, glyoxal and 2-butanone were found significantly increased after exposure to MDMA, compared to controls, whereas 4-methylheptane, 2,4-dimethyl-1-heptene, nonanal, among others, were found significantly decreased. The panel of discriminatory metabolites is mainly involved in tricarboxylic acid (TCA) cycle, fatty acid metabolism, glutamate metabolism, antioxidant defenses and possibly changes in the liver enzyme machinery. Overall, these results highlight the potential of the intra- and extracellular metabolome to study alterations triggered by subtoxic concentrations of MDMA in hepatic cell functions, which represents a more realistic appraisal of early toxicity events posed by exposure to this drug. In addition, these results also revealed some metabolites that may be used as potential biomarkers indicative of early events in the hepatotoxicity induced by MDMA.

Screening Strategies and Methods for Better Off-Target Liability Prediction and Identification of Small-Molecule Pharmaceuticals

Pharmaceutical discovery and development is a long and expensive process that, unfortunately, still results in a low success rate, with drug safety continuing to be a major impedance. Improved safety screening strategies and methods are needed to more effectively fill this critical gap. Recent advances in informatics are now making it possible to manage bigger data sets and integrate multiple sources of screening data in a manner that can potentially improve the selection of higher-quality drug candidates. Integrated screening paradigms have become the norm in Pharma, both in discovery screening and in the identification of off-target toxicity mechanisms during later-stage development. Furthermore, advances in computational methods are making in silico screens more relevant and suggest that they may represent a feasible option for augmenting the current screening paradigm. This paper outlines several fundamental methods of the current drug screening processes across Pharma and emerging techniques/technologies that promise to improve molecule selection. In addition, the authors discuss integrated screening strategies and provide examples of advanced screening paradigms.

Toxicologic Pathology Forum Opinion Paper*: Recommendations for a Tiered Approach to Nonclinical Mechanistic Nephrotoxicity Evaluation

Nephrotoxicity is one of the more common causes of attrition in nonclinical drug development. Like most tissues, the kidney has a limited number of ways of responding to toxicological insults from diverse mechanistic pathways, which can limit the ability to determine mechanisms of renal injury using the assays routinely performed in preclinical toxicologic studies. In situations where the renal injury is unusual in morphology or if a therapeutic margin is low, additional investigative techniques may be needed to identify a potential mechanism of toxicity in order to inform clinical risk assessment or establish human relevance and translatability of the toxicity. While routine microscopic evaluation can suggest a specific pathogenesis, understanding the mechanism of renal injury often requires additional hypothesis-driven investigations and specialized techniques to obtain the data necessary to identify a nephrotoxic mechanism. Nonclinical mechanistic investigations can be resource-intensive and often yield limited new information. Although there are multiple avenues to investigate renal toxicity, no single mechanistic study or prescriptive battery of tests will identify the pathophysiologic basis for every potential mechanism of renal injury. To aid the nonclinical investigator, we outline a tiered approach for prioritizing investigations to provide a rational and linear road map for the exploration of mechanisms of drug-induced kidney injury.

[Box: see text]

Metabolomics Discovers Early-Response Metabolic Biomarkers that Can Predict Chronic Reproductive Fitness in Individual Daphnia magna

Chemical risk assessment remains entrenched in chronic toxicity tests that set safety thresholds based on animal pathology or fitness. Chronic tests are resource expensive and lack mechanistic insight. Discovering a chemical's mode-of-action can in principle provide predictive molecular biomarkers for a toxicity endpoint. Furthermore, since molecular perturbations precede pathology, early-response molecular biomarkers may enable shorter, more resource efficient testing that can predict chronic animal fitness. This study applied untargeted metabolomics to attempt to discover early-response metabolic biomarkers that can predict reproductive fitness of Daphnia magna, an internationally-recognized test species. First, we measured the reproductive toxicities of cadmium, 2,4-dinitrophenol and propranolol to individual Daphnia in 21-day OECD toxicity tests, then measured the metabolic profiles of these animals using mass spectrometry. Multivariate regression successfully discovered putative metabolic biomarkers that strongly predict reproductive impairment by each chemical, and for all chemicals combined. The non-chemical-specific metabolic biomarkers were then applied to metabolite data from Daphnia 24-h acute toxicity tests and correctly predicted that significant decreases in reproductive fitness would occur if these animals were exposed to cadmium, 2,4-dinitrophenol or propranolol for 21 days. While the applicability of these findings is limited to three chemicals, they provide proof-of-principle that early-response metabolic biomarkers of chronic animal fitness can be discovered for regulatory toxicity testing.

Integration of metabolomics and transcriptomics in nanotoxicity studies

Biomedical research involving nanoparticles has produced useful products with medical applications. However, the potential toxicity of nanoparticles in biofluids, cells, tissues, and organisms is a major challenge. The '-omics' analyses provide molecular profiles of multifactorial biological systems instead of focusing on a single molecule. The 'omics' approaches are necessary to evaluate nanotoxicity because classical methods for the detection of nanotoxicity have limited ability in detecting miniscule variations within a cell and do not accurately reflect the actual levels of nanotoxicity. In addition, the 'omics' approaches allow analyses of in-depth changes and compensate for the differences associated with high-throughput technologies between actual nanotoxicity and results from traditional cytotoxic evaluations. However, compared with a single omics approach, integrated omics provides precise and sensitive information by integrating complex biological conditions. Thus, these technologies contribute to extended safety evaluations of nanotoxicity and allow the accurate diagnoses of diseases far earlier than was once possible in the nanotechnology era. Here, we review a novel approach for evaluating nanotoxicity by integrating metabolomics with metabolomic profiling and transcriptomics, which is termed "metabotranscriptomics". [BMB Reports 2018; 51(1): 14-20].

Toxicity and Detoxification Effects of Herbal Caowu via Ultra Performance Liquid Chromatography/Mass Spectrometry Metabolomics Analyzed using Pattern Recognition Method

Background:

Caowu (Radix Aconiti kusnezoffii, CW), the root of Aconitum kusnezoffii Reichb., has widely used clinically in rheumatic arthritis, painful joints, and tumors for thousands of years. However, the toxicity of heart and central nervous system induced by CW still limited the application.

Materials and Methods:

Metabolomics was performed to identify the sensitive and reliable biomarkers and to characterize the phenotypically biochemical perturbations and potential mechanisms of CW-induced toxicity, and the detoxification by combinatorial intervention of CW with Gancao (Radix Glycyrrhizae) (CG), Baishao (Radix Paeoniae Alba) (CB), and Renshen (Radix Ginseng) (CR) was also analyzed by pattern recognition methods.

Results:

As a result, the metabolites were characterized and responsible for pentose and glucuronate interconversions, tryptophan metabolism, amino sugar and nucleotide sugar metabolism, taurine and hypotaurine metabolism, fructose and mannose metabolism, and starch and sucrose metabolism, six networks of which were the same to the metabolic pathways of Chuanwu (Radix Aconiti, CHW) group. The ascorbate and aldarate metabolism was also characterized by CW group. The urinary metabolomics also revealed CW-induced serious toxicity to heart and liver. Thirteen significant metabolites were identified and had validated as phenotypic toxicity biomarkers of CW, five biomarkers of which were commonly owned in Aconitum. The changes of toxicity metabolites obtained from combinatorial intervention of CG, CB, and CR also were analyzed to investigate the regulation degree of toxicity biomarkers adjusted by different combinatorial interventions at 6^th month.

Conclusion:

Metabolomics analyses coupled with pattern recognition methods in the evaluation of drug toxicity and finding detoxification methods were highlighted in this work.

SUMMARY

Metabolomics was performed to characterize the biochemical potential mechanisms of Caowu toxicity

Thirteen significant metabolites were identified and validated as phenotypic toxicity biomarkers of Caowu

Metabolite changes of toxicity obtained can be adjusted by different combinatorial interventions.

Pattern recognition plot reflects the toxicity effects tendency of the urine metabolic fluctuations according to time after treatment of herbal Caowu.

Abbreviations used: CW: Caowu (Radix Aconiti kusnezoffii); CHW: Chuanwu (Radix Aconiti); TCM: Traditional Chinese Medicine; CG: Caowu and Gancao; CB: Caowu and Baishao; CR: Caowu and Renshen; QC: Quality control; UPLC: Ultra performance liquid chromatography; MS: Mass spectrometry; PCA: Principal component analysis; PLS-DA: Partial least squares-discriminant analysis; OPLS: Orthogonal projection to latent structures analysis.

Exploration of potential biomarkers and related biological pathways for PCB exposure in maternal and cord serum: A pilot birth cohort study in Chiba, Japan

Polychlorinated biphenyls (PCBs) have been associated with adverse human reproductive and fetal developmental measures or outcomes because of their endocrine-disrupting effects; however, the biological mechanisms of adverse effects of PCB exposure in humans are not currently well established. In this study, we aimed to identify the biological pathways and potential biomarkers of PCB exposure in maternal and umbilical cord serum using a hydrophilic interaction chromatography-tandem mass spectrometry (HILIC-MS/MS) metabolomics platform. The median concentration of total PCBs in maternal (n=93) and cord serum (n=93) were 350 and 70pgg^-1 wet wt, respectively. PCB levels in maternal and fetal serum from the Chiba Study of Mother and Children's Health (C-MACH) cohort are comparable to those of earlier cohort studies conducted in Japan, the USA, and European countries. We used the random forest model with the metabolome profile to predict exposure levels of PCB (first quartile [Q1] and fourth quartile [Q4]) for pregnant women and fetuses. In the prediction model for classification of Q1 versus Q4 (area-under-curve [AUC]: pregnant women=0.812 and fetuses=0.919), citraconic acid level in maternal serum and ethanolamine, p-hydroxybenzoate, and purine levels in cord serum had >0.70 AUC values. These candidate biomarkers and metabolite included in composited models were related to glutathione and amino acid metabolism in maternal serum and the amino acid metabolism and ubiquinone and other terpenoid-quinone biosynthesis in cord serum (FDR <0.10), indicating disruption of metabolic pathways by PCB exposure in pregnant women and fetuses. These results showed that metabolome analysis might be useful to explore potential biomarkers and related biological pathways for PCB exposure. Thus, more detailed studies are needed to verify sensitivity of the biomarkers and clarify the biochemical changes resulting from PCB exposure.