An Integrative Multi-Omics Workflow to Address Multifactorial Toxicology Experiments

Insights into toxicological mechanisms of per-/polyfluoroalkyl substances by using omics-centered approaches

The extensive presence of per-/polyfluoroalkyl substances (PFASs) in the environment and their adverse effects on organisms have garnered increasing concern. With the shift of industrial development from legacy to emerging PFASs, expanding the understanding of molecular responses to legacy and emerging PFASs is essential to accurately assess their risks to organisms. Compared with traditional toxicological approaches, omics technologies including transcriptomics, proteomics, metabolomics/lipidomics, and microbiomics allow comprehensive analysis of the molecular changes that occur in organisms after PFAS exposure. This paper comprehensively reviews the insights of omics approaches, especially the multi-omics approach, on the toxic mechanisms of both legacy and emerging PFASs in recent five years, focusing on hepatotoxicity, developmental toxicity, immunotoxicity, reproductive toxicity, neurotoxicity, and the endocrine-disrupting effect. PFASs exert various toxic effects via lipid and amino acid metabolism disruption, perturbations in several cell signal pathways, and binding to nuclear receptors. Notably, integrating multi-omics offers a thorough insight into the mechanisms of toxicity associated with PFASs. The gut microbiota plays an essential regulatory role in the toxic mechanisms of PFAS-induced hepatotoxicity. Finally, further research directions for PFAS toxicology based on omics technologies are prospected.

Exposure to low levels of antidiabetic glibenclamide had no evident adverse effects on intestinal microbial composition and metabolic profiles in amphibian larvae

Unmetabolized human pharmaceuticals may enter aquatic environments, and potentially exert adverse effects on the survival of non-target organisms. Here, Pelophylax nigromaculatus tadpoles were exposed to different concentrations of antidiabetic glibenclamide (GLB) for 30 days to evaluate its potential ecotoxicological effect in amphibians using intestinal microbiomic and metabolomic profiles. The mortality rate of GLB-exposed groups appeared to be lower than that of the control group. Despite not being statistically significant, there was a tendency for a decrease in intestinal microbial diversity after exposure. The relative abundance of bacteria phylum Firmicutes was shown to decrease, but those of other phyla did not in GLB-exposed tadpoles. Some potentially pathogenic bacteria (e.g., Clostridium, Bilophila, Hafnia) decrease unexpectedly, while some beneficial bacteria (e.g., Akkermansia, Faecalibacterium) increased in GLB-exposed tadpoles. Accordingly, GLB-induced changes in intestinal microbial compositions did not seem harmful to animal health. Moreover, minor changes in a few intestinal metabolites were observed after GLB exposure. Overall, our results suggested that exposure to low levels of GLB did not necessarily exert an adverse impact on amphibian larvae.

A unified strategy to rebalance multifactorial designs with unequal group sizes: application to analysis of variance multiblock orthogonal partial least squares

BACKGROUND

Adequately handling unbalanced groups remains one of the major challenges for the analysis of multivariate data collected from multifactorial experimental designs. While partial least squares-based methods, such as analysis of variance multiblock orthogonal partial least squares (AMOPLS), can offer better discrimination between factor levels, they can be more heavily affected by this issue, and unbalanced designs of experiments may lead to a substantial confusion of the effects. Even state-of-the-art analysis of variance (ANOVA) decomposition methodologies using general linear models (GLM) lack the ability to efficiently disentangle these sources of variation when combined with AMOPLS.

RESULTS

A versatile solution developed as an extension of a prior rebalancing strategy is proposed for the first decomposition step based on ANOVA. This approach has the advantage of yielding an unbiased estimation of the parameters and retaining the within-group variation in the rebalanced design, while preserving the orthogonality of effect matrices, even in presence of unequal group sizes. This property is of utmost importance for model interpretation because it avoids mixing sources of variation related to the different effects in the design. A real case study involving metabolomic data from in vitro toxicological experiments was used to demonstrate the potential of this strategy to handle unequal group sizes using a supervised approach. Primary 3D rat neural cell cultures were exposed to trimethyltin following a multifactorial design of experiments involving three fixed effect factors.

SIGNIFICANCE AND NOVELTY

The rebalancing strategy was demonstrated as a novel and potent solution to handle unbalanced experimental designs by offering unbiased parameter estimators and orthogonal submatrices, thus avoiding confusion of the effects and facilitating model interpretation. Moreover, it can be combined with any multivariate method used for the analysis of high-dimensional data collected from multifactorial designs.

Minor metabolomic disturbances induced by glyphosate-isopropylammonium exposure at environmentally relevant concentrations in an aquatic turtle, Pelodiscus sinensis

The ecotoxicological and environmental impacts of glyphosate-based herbicides have received considerable attention due to their extensive use globally. However, the potential for adverse effects in cultured non-fish vertebrate species are commonly ignored. In this study, effects on growth, indicators of functional performance, gut microbial diversity, liver antioxidant responses and metabolite profiles were evaluated in soft-shelled turtle hatchlings (Pelodiscus sinensis) exposed to different concentrations of glyphosate-isopropylammonium (0, 0.02, 0.2, 2 and 20 mg/L). No significant changes in growth or functional performance (food intake, swimming speed), gut microbiota, and liver antioxidant responses (SOD and CAT activities, MDA content) were observed in exposed turtles. However, hepatic metabolite profiles revealed distinct perturbations that primarily involved amino acid metabolism in turtles exposed to environmentally relevant concentrations. Overall, our results suggested that metabolite profiles may be more sensitive than phenotypic or general physiological endpoints and gut microbiota profiling, and indicate a potential mechanism of hepatotoxicity caused by glyphosate-isopropylammonium based on untargeted metabolomics analysis. Furthermore, the toxicity of glyphosate at environmentally relevant concentrations might be relatively minor in aquatic turtle species.

Metabolic perturbations in pregnant rats exposed to low-dose perfluorooctanesulfonic acid: An integrated multi-omics analysis

Emerging epidemiological evidence has linked per- and polyfluoroalkyl substances (PFAS) exposure could be linked to the disturbance of gestational glucolipid metabolism, but the toxicological mechanism is unclear, especially when the exposure is at a low level. This study examined the glucolipid metabolic changes in pregnant rats treated with relatively low dose perfluorooctanesulfonic acid (PFOS) through oral gavage during pregnancy [gestational day (GD): 1-18]. We explored the molecular mechanisms underlying the metabolic perturbation. Oral glucose tolerance test (OGTT) and biochemical tests were performed to assess the glucose homeostasis and serum lipid profiles in pregnant Sprague-Dawley (SD) rats randomly assigned to starch, 0.03 and 0.3 mg/kg·bw·d groups. Transcriptome sequencing combined with non-targeted metabolomic assays were further performed to identify differentially altered genes and metabolites in the liver of maternal rats, and to determine their correlation with the maternal metabolic phenotypes. Results of transcriptome showed that differentially expressed genes at 0.03 and 0.3 mg/kg·bw·d PFOS exposure were related to several metabolic pathways, such as peroxisome proliferator-activated receptors (PPARs) signaling, ovarian steroid synthesis, arachidonic acid metabolism, insulin resistance, cholesterol metabolism, unsaturated fatty acid synthesis, bile acid secretion. The untargeted metabolomics identified 164 and 158 differential metabolites in 0.03 and 0.3 mg/kg·bw·d exposure groups, respectively under negative ion mode of Electrospray Ionization (ESI-), which could be enriched in metabolic pathways such as α-linolenic acid metabolism, glycolysis/gluconeogenesis, glycerolipid metabolism, glucagon signaling pathway, glycine, serine and threonine metabolism. Co-enrichment analysis indicated that PFOS exposure may disturb the metabolism pathways of glycerolipid, glycolysis/gluconeogenesis, linoleic acid, steroid biosynthesis, glycine, serine and threonine. The key involved genes included down-regulated Ppp1r3c and Abcd2, and up-regulated Ogdhland Ppp1r3g, and the key metabolites such as increased glycerol 3-phosphate and lactosylceramide were further identified. Both of them were significantly associated with maternal fasting blood glucose (FBG) level. Our findings may provide mechanistic clues for clarifying metabolic toxicity of PFOS in human, especially for susceptible population such as pregnant women.

Divergent responses in the gut microbiome and liver metabolome to ammonia stress in three freshwater turtles

Ammonia is a common pollutant in aquaculture system, and toxic to all aquatic animals. However, different aquatic animals exhibit diverse physiological responses to high-level ammonia exposure, potentially indicating their divergent resistance to ammonia stress. In this study, juveniles of three freshwater turtles (Mauremys reevesii, Pseudemys nelsoni and Trachemys scripta elegans) were exposed to different concentrations of ammonia (0, 0.3 and 3.0 mg/L) for 30 days, and their swimming, growth performance, gut microbiota, and hepatic metabolites were measured to evaluate the interspecific difference in physiological responses to ammonia stress. Despite no differences in swimming ability, growth rate, and gut microbial diversity, observable changes in microbial community composition and hepatic metabolite profiles were shown in ammonia-exposed turtles. A relatively higher abundance of potentially pathogenic bacteria was found in M. reevesii than in the other two species. Moreover, microbial compositions and metabolic responses differed significantly among the three species. M. reevesii was, out of the three tested species, the one in which exposure to ammonia had the greatest effect on changes in bacterial genera and hepatic metabolites. Conversely, only a few metabolites were significantly changed in T. scripta elegans. Integrating these findings, we speculated that native M. reevesii should be more vulnerable to ammonia stress compared to the invasive turtle species. Our results plausibly reflected divergent potential resistance to ammonia among these turtles, in view of differential physiological responses to ammonia exposure at environmentally relevant concentrations.

Gut Microbial Composition and Liver Metabolite Changes Induced by Ammonia Stress in Juveniles of an Invasive Freshwater Turtle

As the most common pollutant in aquaculture systems, the toxic effects of ammonia have been extensively explored in cultured fish, molluscs, and crustaceans, but have rarely been considered in turtle species. In this study, juveniles of the invasive turtle, Trachemys scripta elegans, were exposed to different ammonia levels (0, 0.3, 3.0, and 20.0 mg/L) for 30 days to evaluate the physiological, gut microbiomic, and liver metabolomic responses to ammonia in this turtle species. Except for a relatively low growth rate of turtles exposed to the highest concentration, ammonia exposure had no significant impact on the locomotor ability and gut microbial diversity of turtles. However, the composition of the microbial community could be altered, with some pathogenic bacteria being increased in ammonia-exposed turtles, which might indicate the change in their health status. Furthermore, hepatic metabolite profiles via liquid chromatography-mass spectrometry revealed extensive metabolic perturbations, despite being primarily involved in amino acid biosynthesis and metabolism. Overall, our results show that ammonia exposure causes gut dysbacteriosis and disturbs various metabolic pathways in aquatic turtle species. Considering discrepant defense mechanisms, the toxic impacts of ammonia at environmentally relevant concentrations on physiological performance might be less pronounced in turtles compared with fish and other invertebrates.

The Metabolic Impact of Two Different Parenteral Nutrition Lipid Emulsions in Children after Hematopoietic Stem Cell Transplantation: A Lipidomics Investigation

Hematopoietic stem cell transplantation (HSCT) involves the infusion of either bone marrow or blood cells preceded by toxic chemotherapy. However, there is little knowledge about the clinical benefits of parenteral nutrition (PN) in patients receiving high-dose chemotherapy during HSCT. We investigated the lipidomic profile of plasma and the targeted fatty acid profiles of plasma and erythrocytes in children after HSCT using PN with either a fish oil-based lipid emulsion or a classic soybean oil emulsion. An untargeted liquid chromatography high-resolution mass spectrometry platform connected with a novel in silico annotation algorithm was utilized to determine the most relevant chemical subclasses affected. In addition, we explored the interrelation between the lipidomics profile in plasma, the targeted fatty acid profile in plasma and erythrocytes, several biomarkers of inflammation, and antioxidant defense using an innovative data integration analysis based on Latent Components. We observed that the fish oil-based lipid emulsion had an impact in several lipid subclasses, mainly glycerophosphocholines (PC), glycerophosphoserines (PS), glycerophosphoethanolamines (PE), oxidized PE (O-PE), 1-alkyl,2-acyl PS, lysophosphatidylethanolamines (LPE), oxidized PS (O-PS) and dicarboxylic acids. In contrast, the classic soybean oil emulsion did not. Several connections across the different blocks of data were found and aid in interpreting the impact of the lipid emulsions on metabolic health.

Metabonomics analysis of semen euphorbiae and semen Euphorbiae Pulveratum using UPLC-Q-TOF/MS

Semen Euphorbiae (SE), the dry and mature seed of Euphorbia lathyris L., a common traditional Chinese medicine, has significant pharmacological activity. However, its toxicity limits its clinical application, and less toxic Semen Euphorbiae Pulveratum (SEP) is often used clinically. To explore the possible mechanism of SE frost-making and attenuation, this study used ultrahigh-performance liquid chromatography coupled with quadrupole time of flight mass spectrometry to perform a comprehensive metabolomics analysis of serum and urine samples from rats treated with SE and SEP, and performed histopathological evaluation of liver, kidney and colon tissues. Meanwhile, the different metabolites were visualized through multivariate statistical analysis and the HMDB and KEGG databases were used to distinguish the differential metabolites of SE and SEP to reveal related metabolic pathways and their significance. In total, 32 potential biomarkers, 14 in serum and 18 in urine, were identified. The metabolic pathway analysis revealed that arachidonic acid metabolism, sphingolipid metabolism, tyrosine and tryptophan biosynthesis, the tricarboxylic acid cycle and seven other metabolic pathways were significantly altered. Importantly, compared with SE, SEP reduced the metabolic disorder related to endogenous components. The mechanism may be related to the regulation of lipid metabolism, intestinal flora metabolites, amino acid metabolism and energy metabolism. This study provided new insights into the possible mechanism of SE freezing and attenuation.

Nuclear Magnetic Resonance Spectroscopy in Clinical Metabolomics and Personalized Medicine: Current Challenges and Perspectives

Personalized medicine is probably the most promising area being developed in modern medicine. This approach attempts to optimize the therapies and the patient care based on the individual patient characteristics. Its success highly depends on the way the characterization of the disease and its evolution, the patient’s classification, its follow-up and the treatment could be optimized. Thus, personalized medicine must combine innovative tools to measure, integrate and model data. Towards this goal, clinical metabolomics appears as ideally suited to obtain relevant information. Indeed, the metabolomics signature brings crucial insight to stratify patients according to their responses to a pathology and/or a treatment, to provide prognostic and diagnostic biomarkers, and to improve therapeutic outcomes. However, the translation of metabolomics from laboratory studies to clinical practice remains a subsequent challenge. Nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are the two key platforms for the measurement of the metabolome. NMR has several advantages and features that are essential in clinical metabolomics. Indeed, NMR spectroscopy is inherently very robust, reproducible, unbiased, quantitative, informative at the structural molecular level, requires little sample preparation and reduced data processing. NMR is also well adapted to the measurement of large cohorts, to multi-sites and to longitudinal studies. This review focus on the potential of NMR in the context of clinical metabolomics and personalized medicine. Starting with the current status of NMR-based metabolomics at the clinical level and highlighting its strengths, weaknesses and challenges, this article also explores how, far from the initial “opposition” or “competition”, NMR and MS have been integrated and have demonstrated a great complementarity, in terms of sample classification and biomarker identification. Finally, a perspective discussion provides insight into the current methodological developments that could significantly raise NMR as a more resolutive, sensitive and accessible tool for clinical applications and point-of-care diagnosis. Thanks to these advances, NMR has a strong potential to join the other analytical tools currently used in clinical settings.

Statistical Integration of 'Omics Data Increases Biological Knowledge Extracted from Metabolomics Data: Application to Intestinal Exposure to the Mycotoxin Deoxynivalenol

The effects of low doses of toxicants are often subtle and information extracted from metabolomic data alone may not always be sufficient. As end products of enzymatic reactions, metabolites represent the final phenotypic expression of an organism and can also reflect gene expression changes caused by this exposure. Therefore, the integration of metabolomic and transcriptomic data could improve the extracted biological knowledge on these toxicants induced disruptions. In the present study, we applied statistical integration tools to metabolomic and transcriptomic data obtained from jejunal explants of pigs exposed to the food contaminant, deoxynivalenol (DON). Canonical correlation analysis (CCA) and self-organizing map (SOM) were compared for the identification of correlated transcriptomic and metabolomic features, and O2-PLS was used to model the relationship between exposure and selected features. The integration of both 'omics data increased the number of discriminant metabolites discovered (39) by about 10 times compared to the analysis of the metabolomic dataset alone (3). Besides the disturbance of energy metabolism previously reported, assessing correlations between both functional levels revealed several other types of damage linked to the intestinal exposure to DON, including the alteration of protein synthesis, oxidative stress, and inflammasome activation. This confirms the added value of integration to enrich the biological knowledge extracted from metabolomics.

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.

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 Vitro and In Vivo Models for Evaluating the Oral Toxicity of Nanomedicines

Toxicity studies for conventional oral drug formulations are standardized and well documented, as required by the guidelines of administrative agencies such as the US Food & Drug Administration (FDA), the European Medicines Agency (EMA) or European Medicines Evaluation Agency (EMEA), and the Japanese Pharmaceuticals and Medical Devices Agency (PMDA). Researchers tend to extrapolate these standardized protocols to evaluate nanoformulations (NFs) because standard nanotoxicity protocols are still lacking in nonclinical studies for testing orally delivered NFs. However, such strategies have generated many inconsistent results because they do not account for the specific physicochemical properties of nanomedicines. Due to their tiny size, accumulated surface charge and tension, sizeable surface-area-to-volume ratio, and high chemical/structural complexity, orally delivered NFs may generate severe topical toxicities to the gastrointestinal tract and metabolic organs, including the liver and kidney. Such toxicities involve immune responses that reflect different mechanisms than those triggered by conventional formulations. Herein, we briefly analyze the potential oral toxicity mechanisms of NFs and describe recently reported in vitro and in vivo models that attempt to address the specific oral toxicity of nanomedicines. We also discuss approaches that may be used to develop nontoxic NFs for oral drug delivery.

Disentangling of the ecotoxicological signal using "omics" analyses, a lesson from the survey of the impact of cyanobacterial proliferations on fishes

Omics technologies offer unprecedented perspectives for the rational investigation of complex biological systems. Indeed, omics present the ability of offering an extensive perception of the biochemistry and physiology of the cell and of any perturbing consequences of contaminants through the joint investigation of thousands of molecular responses simultaneously; then it has recently conducted to a fervent attention by research ecotoxicologists. Beyond the presentation of latest advances, exemplified here by omics investigation of cyanobacterial deleterious effects on various fishes (at various experimental and biological scales and with various analytical tools and pipeline), the present review paper re-explores the promising perspectives and also the pitfalls of such holistic investigations of the ecotoxicological response of organisms for environmental assessment.

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

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

Advances in Astrocyte Computational Models: From Metabolic Reconstructions to Multi-omic Approaches

The growing importance of astrocytes in the field of neuroscience has led to a greater number of computational models devoted to the study of astrocytic functions and their metabolic interactions with neurons. The modeling of these interactions demands a combined understanding of brain physiology and the development of computational frameworks based on genomic-scale reconstructions, system biology, and dynamic models. These computational approaches have helped to highlight the neuroprotective mechanisms triggered by astrocytes and other glial cells, both under normal conditions and during neurodegenerative processes. In the present review, we evaluate some of the most relevant models of astrocyte metabolism, including genome-scale reconstructions and astrocyte-neuron interactions developed in the last few years. Additionally, we discuss novel strategies from the multi-omics perspective and computational models of other glial cell types that will increase our knowledge in brain metabolism and its association with neurodegenerative diseases.