Special Issue: NMR-Based Metabolomics.

Nuclear magnetic resonance (NMR) spectroscopy remains one of the core analytical platforms for metabolomics, providing complementary chemical information to others, such as mass spectrometry, and offering particular advantages in some areas of research on account of its inherent robustness, reproducibility, and phenomenal dynamic range [...].

Simultaneous Enantiospecific Detection of Multiple Compounds in Mixtures using NMR Spectroscopy.

Chirality plays a fundamental role in nature, but its detection and quantification still face many limitations. To date, the enantiospecific analysis of mixtures necessarily requires prior separation of the individual components. The simultaneous enantiospecific detection of multiple chiral molecules in a mixture represents a major challenge, which would lead to a significantly better understanding of the underlying biological processes; for example, via enantiospecifically analysing metabolites in their native environment. Here, we report on the first in situ enantiospecific detection of a thirty-nine-component mixture. As a proof of concept, eighteen essential amino acids at physiological concentrations were simultaneously enantiospecifically detected using NMR spectroscopy and a chiral solvating agent. This work represents a first step towards the simultaneous multicomponent enantiospecific analysis of complex mixtures, a capability that will have substantial impact on metabolism studies, metabolic phenotyping, chemical reaction monitoring, and many other fields where complex mixtures containing chiral molecules require efficient characterisation.

Acyl glucuronide reactivity in perspective.

Acyl glucuronidation is a common metabolic fate for acidic drugs and their metabolites and, because these metabolites are reactive, they have been linked to adverse drug reactions (ADRs) and drug withdrawals. However, alternative routes of metabolism leading to reactive metabolites (e.g., oxidations and acyl-CoA thioesters) mean that unambiguous proof that acyl glucuronides are toxic is lacking. Here, we review the synthesis and reactivity of these metabolites, and describe the use of molecular modelling and in vitro and in vivo reactivity assessment of acyl glucuronide reactivity. Based on the emerging structure-dependent differences in reactivity and protein adduction methods for risk assessment for acyl glucuronide-forming acid drugs or drug candidates in drug discovery/development are suggested.

Kinetic modelling of acyl glucuronide and glucoside reactivity and development of structure-property relationships.

Acyl glucuronide metabolites have been implicated in the toxicity of several carboxylic acid-containing drugs, and the rate of their degradation via intramolecular transacylation and hydrolysis has been associated with the degree of protein adduct formation. Although not yet proven, the formation of protein adducts in vivo - and subsequent downstream effects - has been proposed as a mechanism of toxicity for carboxylic acid-containing xenobiotics capable of forming acyl glucuronides. A structurally-related series of metabolites, the acyl glucosides, have also been shown to undergo similar degradation reactions and consequently the potential to display a similar mode of toxicity. Here we report detailed kinetic models of each transacylation and hydrolysis reaction for a series of phenylacetic acid acyl glucuronides and their analogous acyl glucosides. Differences in reactivity were observed for the individual transacylation steps between the compound series; our findings suggest that the charged carboxylate ion and neutral hydroxyl group in the glucuronide and glucoside conjugates, respectively, are responsible for these differences. The transacylation reaction was modelled using density functional theory and the calculated activation energy for this reaction showed a close correlation with the degradation rate of the 1-ß anomer. Comparison of optimised geometries between the two series of conjugates revealed differences in hydrogen bonding which may further explain the differences in reactivity observed. Together, these models may find application in drug discovery for prediction of acyl glucuronide and glucoside metabolite behaviour.

Brake dust exposure exacerbates inflammation and transiently compromises phagocytosis in macrophages.

Studies have emphasised the importance of combustion-derived particles in eliciting adverse health effects, especially those produced by diesel vehicles. In contrast, few investigations have explored the potential toxicity of particles derived from tyre and brake wear, despite their significant contributions to total roadside particulate mass. The objective of this study was to compare the relative toxicity of compositionally distinct brake abrasion dust (BAD) and diesel exhaust particles (DEP) in a cellular model that is relevant to human airways. Although BAD contained considerably more metals/metalloids than DEP (as determined by inductively coupled plasma mass spectrometry) similar toxicological profiles were observed in U937 monocyte-derived macrophages following 24 h exposures to 4-25 µg ml-1 doses of either particle type. Responses to the particles were characterised by dose-dependent decreases in mitochondrial depolarisation (p ≤ 0.001), increased secretion of IL-8, IL-10 and TNF-α (p ≤ 0.05 to p ≤ 0.001) and decreased phagocytosis of S. aureus (p ≤ 0.001). This phagocytic deficit recovered, and the inflammatory response resolved when challenged cells were incubated for a further 24 h in particle-free media. These responses were abrogated by metal chelation using desferroxamine. At minimally cytotoxic doses both DEP and BAD perturbed bacterial clearance and promoted inflammatory responses in U937 cells with similar potency. These data emphasise the requirement to consider contributions of abrasion particles to traffic-related clinical health effects.

Determinants of the urinary and serum metabolome in children from six European populations.

BACKGROUND: Environment and diet in early life can affect development and health throughout the life course. Metabolic phenotyping of urine and serum represents a complementary systems-wide approach to elucidate environment-health interactions. However, large-scale metabolome studies in children combining analyses of these biological fluids are lacking. Here, we sought to characterise the major determinants of the child metabolome and to define metabolite associations with age, sex, BMI and dietary habits in European children, by exploiting a unique biobank established as part of the Human Early-Life Exposome project ( http://www.projecthelix.eu ). METHODS: Metabolic phenotypes of matched urine and serum samples from 1192 children (aged 6-11) recruited from birth cohorts in six European countries were measured using high-throughput 1H nuclear magnetic resonance (NMR) spectroscopy and a targeted LC-MS/MS metabolomic assay (Biocrates AbsoluteIDQ p180 kit). RESULTS: We identified both urinary and serum creatinine to be positively associated with age. Metabolic associations to BMI z-score included a novel association with urinary 4-deoxyerythreonic acid in addition to valine, serum carnitine, short-chain acylcarnitines (C3, C5), glutamate, BCAAs, lysophosphatidylcholines (lysoPC a C14:0, lysoPC a C16:1, lysoPC a C18:1, lysoPC a C18:2) and sphingolipids (SM C16:0, SM C16:1, SM C18:1). Dietary-metabolite associations included urinary creatine and serum phosphatidylcholines (4) with meat intake, serum phosphatidylcholines (12) with fish, urinary hippurate with vegetables, and urinary proline betaine and hippurate with fruit intake. Population-specific variance (age, sex, BMI, ethnicity, dietary and country of origin) was better captured in the serum than in the urine profile; these factors explained a median of 9.0% variance amongst serum metabolites versus a median of 5.1% amongst urinary metabolites. Metabolic pathway correlations were identified, and concentrations of corresponding metabolites were significantly correlated (r > 0.18) between urine and serum. CONCLUSIONS: We have established a pan-European reference metabolome for urine and serum of healthy children and gathered critical resources not previously available for future investigations into the influence of the metabolome on child health. The six European cohort populations studied share common metabolic associations with age, sex, BMI z-score and main dietary habits. Furthermore, we have identified a novel metabolic association between threonine catabolism and BMI of children.

Paracetamol metabolism, hepatotoxicity, biomarkers and therapeutic interventions: a perspective.

After over 60 years of therapeutic use in the UK, paracetamol (acetaminophen, N-acetyl-p-aminophenol, APAP) remains the subject of considerable research into both its mode of action and toxicity. The pharmacological properties of APAP are the focus of some activity, with the role of the metabolite N-arachidonoylaminophenol (AM404) still a topic of debate. However, that the hepatotoxicity of APAP results from the production of the reactive metabolite N-acetyl-p-benzoquinoneimine (NAPQI/NABQI) that can deplete glutathione, react with cellular macromolecules, and initiate cell death, is now beyond dispute. The disruption of cellular pathways that results from the production of NAPQI provides a source of potential biomarkers of the severity of the damage. Research in this area has provided new diagnostic markers such as the microRNA miR-122 as well as mechanistic biomarkers associated with apoptosis, mitochondrial dysfunction, inflammation and tissue regeneration. Additionally, biomarkers of, and systems biology models for, glutathione depletion have been developed. Furthermore, there have been significant advances in determining the role of both the innate immune system and genetic factors that might predispose individuals to APAP-mediated toxicity. This perspective highlights some of the progress in current APAP-related research.

Pre-diagnostic blood immune markers, incidence and progression of B-cell lymphoma and multiple myeloma: Univariate and functionally informed multivariate analyses.

Recent prospective studies have shown that dysregulation of the immune system may precede the development of B-cell lymphomas (BCL) in immunocompetent individuals. However, to date, the studies were restricted to a few immune markers, which were considered separately. Using a nested case-control study within two European prospective cohorts, we measured plasma levels of 28 immune markers in samples collected a median of 6 years before diagnosis (range 2.01-15.97) in 268 incident cases of BCL (including multiple myeloma [MM]) and matched controls. Linear mixed models and partial least square analyses were used to analyze the association between levels of immune marker and the incidence of BCL and its main histological subtypes and to investigate potential biomarkers predictive of the time to diagnosis. Linear mixed model analyses identified associations linking lower levels of fibroblast growth factor-2 (FGF-2 p = 7.2 × 10-4 ) and transforming growth factor alpha (TGF-α, p = 6.5 × 10-5 ) and BCL incidence. Analyses stratified by histological subtypes identified inverse associations for MM subtype including FGF-2 (p = 7.8 × 10-7 ), TGF-α (p = 4.08 × 10-5 ), fractalkine (p = 1.12 × 10-3 ), monocyte chemotactic protein-3 (p = 1.36 × 10-4 ), macrophage inflammatory protein 1-alpha (p = 4.6 × 10-4 ) and vascular endothelial growth factor (p = 4.23 × 10-5 ). Our results also provided marginal support for already reported associations between chemokines and diffuse large BCL (DLBCL) and cytokines and chronic lymphocytic leukemia (CLL). Case-only analyses showed that Granulocyte-macrophage colony stimulating factor levels were consistently higher closer to diagnosis, which provides further evidence of its role in tumor progression. In conclusion, our study suggests a role of growth-factors in the incidence of MM and of chemokine and cytokine regulation in DLBCL and CLL.

A multivariate approach to investigate the combined biological effects of multiple exposures.

Epidemiological studies provide evidence that environmental exposures may affect health through complex mixtures. Formal investigation of the effect of exposure mixtures is usually achieved by modelling interactions, which relies on strong assumptions relating to the identity and the number of the exposures involved in such interactions, and on the order and parametric form of these interactions. These hypotheses become difficult to formulate and justify in an exposome context, where influential exposures are numerous and heterogeneous. To capture both the complexity of the exposome and its possibly pleiotropic effects, models handling multivariate predictors and responses, such as partial least squares (PLS) algorithms, can prove useful. As an illustrative example, we applied PLS models to data from a study investigating the inflammatory response (blood concentration of 13 immune markers) to the exposure to four disinfection by-products (one brominated and three chlorinated compounds), while swimming in a pool. To accommodate the multiple observations per participant (n=60; before and after the swim), we adopted a multilevel extension of PLS algorithms, including sparse PLS models shrinking loadings coefficients of unimportant predictors (exposures) and/or responses (protein levels). Despite the strong correlation among co-occurring exposures, our approach identified a subset of exposures (n=3/4) affecting the exhaled levels of 8 (out of 13) immune markers. PLS algorithms can easily scale to high-dimensional exposures and responses, and prove useful for exposome research to identify sparse sets of exposures jointly affecting a set of (selected) biological markers. Our descriptive work may guide these extensions for higher dimensional data.

Metabolic Hydrolysis of Aromatic Amides in Selected Rat, Minipig, and Human In Vitro Systems.

The release of aromatic amines from drugs and other xenobiotics resulting from the hydrolysis of metabolically labile amide bonds presents a safety risk through several mechanisms, including geno-, hepato- and nephrotoxicity. Whilst multiple in vitro systems used for studying metabolic stability display serine hydrolase activity, responsible for the hydrolysis of amide bonds, they vary in their efficiency and selectivity. Using a range of amide-containing probe compounds (0.5-10 µM), we have investigated the hydrolytic activity of several rat, minipig and human-derived in vitro systems - including Supersomes, microsomes, S9 fractions and hepatocytes - with respect to their previously observed human in vivo metabolism. In our hands, human carboxylesterase Supersomes and rat S9 fractions systems showed relatively poor prediction of human in vivo metabolism. Rat S9 fractions, which are commonly utilised in the Ames test to assess mutagenicity, may be limited in the detection of genotoxic metabolites from aromatic amides due to their poor concordance with human in vivo amide hydrolysis. In this study, human liver microsomes and minipig subcellular fractions provided more representative models of human in vivo hydrolytic metabolism of the aromatic amide compounds tested.

Oxidative Stress and Inflammation Induced by Environmental and Psychological Stressors: A Biomarker Perspective.

SIGNIFICANCE: The environment can elicit biological responses such as oxidative stress (OS) and inflammation as a consequence of chemical, physical, or psychological changes. As population studies are essential for establishing these environment-organism interactions, biomarkers of OS or inflammation are critical in formulating mechanistic hypotheses. Recent Advances: By using examples of stress induced by various mechanisms, we focus on the biomarkers that have been used to assess OS and inflammation in these conditions. We discuss the difference between biomarkers that are the result of a chemical reaction (such as lipid peroxides or oxidized proteins that are a result of the reaction of molecules with reactive oxygen species) and those that represent the biological response to stress, such as the transcription factor NRF2 or inflammation and inflammatory cytokines. CRITICAL ISSUES: The high-throughput and holistic approaches to biomarker discovery used extensively in large-scale molecular epidemiological exposome are also discussed in the context of human exposure to environmental stressors. FUTURE DIRECTIONS: We propose to consider the role of biomarkers as signs and to distinguish between signs that are just indicators of biological processes and proxies that one can interact with and modify the disease process. Antioxid. Redox Signal. 28, 852-872.

Yale school of public health symposium on lifetime exposures and human health: the exposome; summary and future reflections.

The exposome is defined as "the totality of environmental exposures encountered from birth to death" and was developed to address the need for comprehensive environmental exposure assessment to better understand disease etiology. Due to the complexity of the exposome, significant efforts have been made to develop technologies for longitudinal, internal and external exposure monitoring, and bioinformatics to integrate and analyze datasets generated. Our objectives were to bring together leaders in the field of exposomics, at a recent Symposium on "Lifetime Exposures and Human Health: The Exposome," held at Yale School of Public Health. Our aim was to highlight the most recent technological advancements for measurement of the exposome, bioinformatics development, current limitations, and future needs in environmental health. In the discussions, an emphasis was placed on moving away from a one-chemical one-health outcome model toward a new paradigm of monitoring the totality of exposures that individuals may experience over their lifetime. This is critical to better understand the underlying biological impact on human health, particularly during windows of susceptibility. Recent advancements in metabolomics and bioinformatics are driving the field forward in biomonitoring and understanding the biological impact, and the technological and logistical challenges involved in the analyses were highlighted. In conclusion, further developments and support are needed for large-scale biomonitoring and management of big data, standardization for exposure and data analyses, bioinformatics tools for co-exposure or mixture analyses, and methods for data sharing.

Metabolic profiling in human exposome studies.

The human metabolome-the complement of small molecule metabolites present in biofluids and tissues-represents a significant part of the internal chemical milieu and is therefore an important aspect of the human exposome. Metabolic profiling approaches, commonly referred to as metabonomics or metabolomics, permit detailed and efficient characterisation of human biospecimens; application to population studies holds great promise for uncovering new associations and causal relationships between environmental factors and chronic disease. In addition to the insight metabolic information can provide, metabolic phenotypes anchor other molecular readouts and help formulate a systems-level interpretation of biological phenomena. In this commentary, we discuss the general approach for applying metabolic profiling in exposome studies, alongside recent exemplars. We also comment on the complexity and dynamism of the metabolome and highlight both the limitations such properties impart and the requirements for dealing with such issues in real-world phenotyping studies. Given that several large-scale exposome studies are now underway, we offer a perspective on current and future challenges that will need to be addressed to maximise their utility in environmental health research.

The human early-life exposome (HELIX): project rationale and design.

BACKGROUND: Developmental periods in early life may be particularly vulnerable to impacts of environmental exposures. Human research on this topic has generally focused on single exposure-health effect relationships. The "exposome" concept encompasses the totality of exposures from conception onward, complementing the genome. OBJECTIVES: The Human Early-Life Exposome (HELIX) project is a new collaborative research project that aims to implement novel exposure assessment and biomarker methods to characterize early-life exposure to multiple environmental factors and associate these with omics biomarkers and child health outcomes, thus characterizing the "early-life exposome." Here we describe the general design of the project. METHODS: In six existing birth cohort studies in Europe, HELIX will estimate prenatal and postnatal exposure to a broad range of chemical and physical exposures. Exposure models will be developed for the full cohorts totaling 32,000 mother-child pairs, and biomarkers will be measured in a subset of 1,200 mother-child pairs. Nested repeat-sampling panel studies (n = 150) will collect data on biomarker variability, use smartphones to assess mobility and physical activity, and perform personal exposure monitoring. Omics techniques will determine molecular profiles (metabolome, proteome, transcriptome, epigenome) associated with exposures. Statistical methods for multiple exposures will provide exposure-response estimates for fetal and child growth, obesity, neurodevelopment, and respiratory outcomes. A health impact assessment exercise will evaluate risks and benefits of combined exposures. CONCLUSIONS: HELIX is one of the first attempts to describe the early-life exposome of European populations and unravel its relation to omics markers and health in childhood. As proof of concept, it will form an important first step toward the life-course exposome.

Evaluation of 1H NMR metabolic profiling using biofluid mixture design.

A strategy for evaluating the performance of quantitative spectral analysis tools in conditions that better approximate background variation in a metabonomics experiment is presented. Three different urine samples were mixed in known proportions according to a {3, 3} simplex lattice experimental design and analyzed in triplicate by 1D (1)H NMR spectroscopy. Fifty-four urinary metabolites were subsequently quantified from the sample spectra using two methods common in metabolic profiling studies: (1) targeted spectral fitting and (2) targeted spectral integration. Multivariate analysis using partial least-squares (PLS) regression showed the latent structure of the spectral set recapitulated the experimental mixture design. The goodness-of-prediction statistic (Q(2)) of each metabolite variable in a PLS model was calculated as a metric for the reliability of measurement, across the sample compositional space. Several metabolites were observed to have low Q(2) values, largely as a consequence of their spectral resonances having low s/n or strong overlap with other sample components. This strategy has the potential to allow evaluation of spectral features obtained from metabolic profiling platforms in the context of the compositional background found in real biological sample sets, which may be subject to considerable variation. We suggest that it be incorporated into metabolic profiling studies to improve the estimation of matrix effects that confound accurate metabolite measurement. This novel method provides a rational basis for exploiting information from several samples in an efficient manner and avoids the use of multiple spike-in authentic standards, which may be difficult to obtain.

A combination of transcriptomics and metabolomics uncovers enhanced bile acid biosynthesis in HepG2 cells expressing CCAAT/enhancer-binding protein ß (C/EBPß), hepatocyte nuclear factor 4α (HNF4α), and constitutive androstane receptor (CAR).

The development of hepatoma-based in vitro models to study hepatocyte physiology is an invaluable tool for both industry and academia. Here, we develop an in vitro model based on the HepG2 cell line that produces chenodeoxycholic acid, the main bile acid in humans, in amounts comparable to human hepatocytes. A combination of adenoviral transfections for CCAAT/enhancer-binding protein ß (C/EBPß), hepatocyte nuclear factor 4α (HNF4α), and constitutive androstane receptor (CAR) decreased intracellular glutamate, succinate, leucine, and valine levels in HepG2 cells, suggestive of a switch to catabolism to increase lipogenic acetyl CoA and increased anaplerosis to replenish the tricarboxylic acid cycle. Transcripts of key genes involved in bile acid synthesis were significantly induced by approximately 160-fold. Consistently, chenodeoxycholic acid production rate was increased by more than 20-fold. Comparison between mRNA and bile acid levels suggest that 12-alpha hydroxylation of 7-alpha-hydroxy-4-cholesten-3-one is the limiting step in cholic acid synthesis in HepG2 cells. These data reveal that introduction of three hepatocyte-related transcription factors enhance anabolic reactions in HepG2 cells and provide a suitable model to study bile acid biosynthesis under pathophysiological conditions.

Delineation of the key aspects in the regulation of epithelial monolayer formation.

The formation, maintenance, and repair of epithelial barriers are of critical importance for whole-body homeostasis. However, the molecular events involved in epithelial tissue maturation are not fully established. To this end, we investigated the molecular processes involved in renal epithelial proximal-tubule monolayer maturation utilizing transcriptomic, metabolomic, and functional parameters. We uncovered profound dynamic alterations in transcriptional regulation, energy metabolism, and nutrient utilization over the maturation process. Proliferating cells exhibited high glycolytic rates and high transcript levels for fatty acid synthesis genes (FASN), whereas matured cells had low glycolytic rates, increased oxidative capacity, and preferentially expressed genes for beta oxidation. There were dynamic alterations in the expression and localization of several adherens (CDH1, -4, and -16) and tight junction (TJP3 and CLDN2 and -10) proteins. Genes involved in differentiated proximal-tubule function, cilium biogenesis (BBS1), and transport (ATP1A1 and ATP1B1) exhibited increased expression during epithelial maturation. Using TransAM transcription factor activity assays, we could demonstrate that p53 and FOXO1 were highly active in matured cells, whereas HIF1A and c-MYC were highly active in proliferating cells. The data presented here will be invaluable in the further delineation of the complex dynamic cellular processes involved in epithelial cell regulation.

Advancing the application of omics-based biomarkers in environmental epidemiology.

The use of omics represents a shift in approach for environmental epidemiology and exposure science. In this article, the aspects of the use of omics that will require further development in the near future are discussed, including (a) the underlying causal interpretation and models; (b) the "meet-in-the-middle" concept, with examples; (c) the role of "calibration" of measurements; and (d) the role of life-course epidemiology and the related development of adequate biostatistical models.

Development of quantitative structure-metabolism (QSMR) relationships for substituted anilines based on computational chemistry.

A novel stepwise classification approach for predicting the metabolic fate of substituted anilines, based on calculated physicochemical parameters of the parent anilines, was developed. Based on multivariate pattern recognition methods (PLS-DA or soft independent modelling of class analogy [SIMCA]), these models allowed prediction of N-acetylation and subsequent N-oxanilic acid formation. These classification methods provided an improved classification success when compared with existing quantitative structure-metabolism relationship models for substituted anilines. Modelling the physicochemical properties of the N-acetylated compounds was considered as an addition to the stepwise model. Inclusion of parameters describing the N-acetyl moiety had little effect on the predictive ability of a stepwise parent to N-acetyl to N-oxanilic acid PLS-DA model, and had a negative impact on that of SIMCA models. This was attributed to the relatively small contribution to the total parameter variance caused by differences arising as a result of N-acetylation compared to the contribution made by the substituent effects. Calculation of physicochemical properties incorporating the effect of solvation using ab initio methods improved the classification model in terms of both the visual separation in multivariate projections and prediction accuracy.

Performance in omics analyses of blood samples in long-term storage: opportunities for the exploitation of existing biobanks in environmental health research.

BACKGROUND: The suitability for omic analysis of biosamples collected in previous decades and currently stored in biobanks is unknown. OBJECTIVES: We evaluated the influence of handling and storage conditions of blood-derived biosamples on transcriptomic, epigenomic (CpG methylation), plasma metabolomic [UPLC-ToFMS (ultra performance liquid chromatography-time-of-flight mass spectrometry)], and wide-target proteomic profiles. METHODS: We collected fresh blood samples without RNA preservative in heparin, EDTA, or citrate and held them at room temperature for ≤ 24 hr before fractionating them into buffy coat, erythrocytes, and plasma and freezing the fractions at -80oC or in liquid nitrogen. We developed methodology for isolating RNA from the buffy coats and conducted omic analyses. Finally, we analyzed analogous samples from the EPIC-Italy and Northern Sweden Health and Disease Study biobanks. RESULTS: Microarray-quality RNA could be isolated from buffy coats (including most biobank samples) that had been frozen within 8 hr of blood collection by thawing the samples in RNA preservative. Different anticoagulants influenced the metabolomic, proteomic, and to a lesser extent transcriptomic profiles. Transcriptomic profiles were most affected by the delay (as little as 2 hr) before blood fractionation, whereas storage temperature had minimal impact. Effects on metabolomic and proteomic profiles were noted in samples processed ≥ 8 hr after collection, but no effects were due to storage temperature. None of the variables examined significantly influenced the epigenomic profiles. No systematic influence of time-in-storage was observed in samples stored over a period of 13-17 years. CONCLUSIONS: Most samples currently stored in biobanks are amenable to meaningful omics analysis, provided that they satisfy collection and storage criteria defined in this study.