Demonstrating the reliability of in vivo metabolomics based chemical grouping: towards best practice.

While grouping/read-across is widely used to fill data gaps, chemical registration dossiers are often rejected due to weak category justifications based on structural similarity only. Metabolomics provides a route to robust chemical categories via evidence of shared molecular effects across source and target substances. To gain international acceptance, this approach must demonstrate high reliability, and best-practice guidance is required. The MetAbolomics ring Trial for CHemical groupING (MATCHING), comprising six industrial, government and academic ring-trial partners, evaluated inter-laboratory reproducibility and worked towards best-practice. An independent team selected eight substances (WY-14643, 4-chloro-3-nitroaniline, 17α-methyl-testosterone, trenbolone, aniline, dichlorprop-p, 2-chloroaniline, fenofibrate); ring-trial partners were blinded to their identities and modes-of-action. Plasma samples were derived from 28-day rat tests (two doses per substance), aliquoted, and distributed to partners. Each partner applied their preferred liquid chromatography-mass spectrometry (LC-MS) metabolomics workflows to acquire, process, quality assess, statistically analyze and report their grouping results to the European Chemicals Agency, to ensure the blinding conditions of the ring trial. Five of six partners, whose metabolomics datasets passed quality control, correctly identified the grouping of eight test substances into three categories, for both male and female rats. Strikingly, this was achieved even though a range of metabolomics approaches were used. Through assessing intrastudy quality-control samples, the sixth partner observed high technical variation and was unable to group the substances. By comparing workflows, we conclude that some heterogeneity in metabolomics methods is not detrimental to consistent grouping, and that assessing data quality prior to grouping is essential. We recommend development of international guidance for quality-control acceptance criteria. This study demonstrates the reliability of metabolomics for chemical grouping and works towards best-practice.

Integrated histopathological and urinary metabonomic investigation of the pathogenesis of microcystin-LR toxicosis.

Patterns of change of endogenous metabolites may closely reflect systemic and organ-specific toxic changes. The authors examined the metabolic effects of the cyanobacterial (blue-green algal) toxin microcystin-LR by (1)H-nuclear magnetic resonance (NMR) analysis of urinary endogenous metabolites. Rats were treated with a single sublethal dose, either 20 or 80 µg/kg intraperitoneally, and sacrificed at 2 or 7 days post dosing. Changes in the high-dose, 2-day sacrifice group included centrilobular hepatic necrosis and congestion, accompanied in some animals by regeneration and neovascularization. By 7 days, animals had recovered, the necrotizing process had ended, and the centrilobular areas had been replaced by regenerative, usually hypertrophic hepatocytes. There was considerable interanimal variation in the histologic process and severity, which correlated with the changes in patterns of endogenous metabolites in the urine, thus providing additional validation of the biomarker and biochemical changes. Similarity of the shape of the metabolic trajectories suggests that the mechanisms of toxic effects and recovery are similar among the individual animals, albeit that the magnitude and timing are different for the individual animals. Initial decreases in urinary citrate, 2-oxoglutarate, succinate, and hippurate concentrations were accompanied by a temporary increase in betaine and taurine, then creatine from 24 to 48 hours. Further changes were an increase in guanidinoacetate, dimethylglycine, urocanic acid, and bile acids. As a tool, urine can be repeatedly and noninvasively sampled and metabonomics utilized to study the onset and recovery after toxicity, thus identifying time points of maximal effect. This can help to employ histopathological examination in a guided and effective fashion.

Bidirectional correlation of NMR and capillary electrophoresis fingerprints: a new approach to investigating Schistosoma mansoni infection in a mouse model.

We demonstrate the statistical integration of nuclear magnetic resonance (NMR) spectroscopy and capillary electrophoresis (CE) data in order to describe a pathological state caused by Schistosoma mansoni infection in a mouse model based on urinary metabolite profiles. Urine samples from mice 53 days post infection with S. mansoni and matched controls were analyzed via NMR spectroscopy and CE. The two sets of metabolic profiles were first processed and analyzed independently and were subsequently integrated using statistical correlation methods in order to facilitate cross assignment of metabolites. Using this approach, metabolites such as 3-ureidopropionate, p-cresol glucuronide, phenylacetylglycine, indoxyl sulfate, isocitrate, and trimethylamine were identified as differentiating between infected and control animals. These correlation analyses facilitated structural elucidation using the identification power of one technique to enhance and validate the other, but also highlighted the enhanced ability to detect functional correlations between metabolites, thereby providing potential for achieving deeper mechanistic insight into the biological process.