Metabolomics is a widely used technology in academic research, yet its application to regulatory science has been limited. The most commonly cited barrier to its translation is lack of performance and reporting standards. The MEtabolomics standaRds Initiative in Toxicology (MERIT) project brings together international experts from multiple sectors to address this need. Here, we identify the most relevant applications for metabolomics in regulatory toxicology and develop best practice guidelines, performance and reporting standards for acquiring and analysing untargeted metabolomics and targeted metabolite data. We recommend that these guidelines are evaluated and implemented for several regulatory use cases.

The integrated European project, EU-ToxRisk, proudly sees itself as “flagship” exploring new alternative-to-animal approaches to chemical safety evaluation. It promotes mechanism-based toxicity testing and risk assessment according to the principles laid down for toxicology for the twenty-first century. The project was officially launched in January 2016 with a kickoff meeting in Egmond aan Zee, the Netherlands. Over 100 scientists representing academia and industry as well as regulatory authorities attended the inaugural meeting. The project will integrate advances in in vitro and in silico toxicology, read-across methods, and adverse outcome pathways. EU-ToxRisk will continue to make use of the case study strategy deployed in SEURAT-1, a FP7 initiative ended in December 2015. Even though the development of new non-animal methods is one target of EU-ToxRisk, the project puts special emphasis on their acceptance and implementation in regulatory contexts. This €30 million Horizon 2020 project involves 38 European partners and one from the USA. EU-ToxRisk aims at the “development of a new way of risk assessment.”

Drug-induced liver injury (DILI) is the most prevalent adversity encountered in drug development and clinical settings leading to urgent needs to understand the underlying mechanisms. In this study, we have systematically investigated the dynamics of the activation of cellular stress response pathways and cell death outcomes upon exposure of a panel of liver toxicants using live cell imaging of fluorescent reporter cell lines. We established a comprehensive temporal dynamic response profile of a large set of BAC-GFP HepG2 cell lines representing the following components of stress signaling: i) unfolded protein response (UPR) [ATF4, XBP1, BIP and CHOP]; ii) oxidative stress [NRF2, SRXN1, HMOX1]; iii) DNA damage [P53, P21, BTG2, MDM2]; and iv) NF-κB pathway [A20, ICAM1]. We quantified the single cell GFP expression as a surrogate for endogenous protein expression using live cell imaging over > 60 h upon exposure to 14 DILI compounds at multiple concentrations. Using logic-based ordinary differential equation (Logic-ODE), we modelled the dynamic profiles of the different stress responses and extracted specific descriptors potentially predicting the progressive outcomes. We identified the activation of ATF4-CHOP axis of the UPR as the key pathway showing the highest correlation with cell death upon DILI compound perturbation. Knocking down main components of the UPR provided partial protection from compound-induced cytotoxicity, indicating a complex interplay among UPR components as well as other stress pathways. Our results suggest that a systematic analysis of the temporal dynamics of ATF4-CHOP axis activation can support the identification of DILI risk for new candidate drugs.

Succinate dehydrogenase complex II inhibitors (SDHIs) are widely used fungicides since the 1960s. Recently, based on published in vitro cell viability data, potential health effects via disruption of the mitochondrial respiratory chain and tricarboxylic acid cycle have been postulated in mammalian species. As primary metabolic impact of SDH inhibition, an increase in succinate, and compensatory ATP production via glycolysis resulting in excess lactate levels was hypothesized. To investigate these hypotheses, genome-scale metabolic models of Rattus norvegicus and Homo sapiens were used for an in silico analysis of mammalian metabolism. Moreover, plasma samples from 28-day studies with the SDHIs boscalid and fluxapyroxad were subjected to metabolome analyses, to assess in vivo metabolite changes induced by SDHIs. The outcome of in silico analyses indicated that mammalian metabolic networks are robust and able to compensate different types of metabolic perturbation, e.g., partial or complete SDH inhibition. Additionally, the in silico comparison of rat and human responses suggested no noticeable differences between both species, evidencing that the rat is an appropriate testing organism for toxicity of SDHIs. Since no succinate or lactate accumulation were found in rats, such an accumulation is also not expected in humans as a result of SDHI exposure.

Toxicity is not only a function of damage mechanisms, but is also determined by cellular resilience factors. Glutathione has been reported as essential element to counteract negative influences. The present work hence pursued the question how intracellular glutathione can be elevated transiently to render cells more resistant toward harmful conditions. The antibiotic nitrofurantoin (NFT) was identified to stimulate de novo synthesis of glutathione in the human hepatoma cell line, HepG2, and in primary human hepatocytes. In intact cells, activation of NFT yielded a radical anion, which subsequently initiated nuclear-factor-erythroid 2-related-factor-2 (Nrf2)-dependent induction of glutamate cysteine ligase (GCL). Application of siRNA-based intervention approaches confirmed the involvement of the Nrf2-GCL axis in the observed elevation of intracellular glutathione levels. Quantitative activation of Nrf2 by NFT, and the subsequent rise in glutathione, were similar as observed with the potent experimental Nrf2 activator diethyl maleate. The elevation of glutathione levels, observed even 48 h after withdrawal of NFT, rendered cells resistant to different stressors such as the mitochondrial inhibitor rotenone, the redox cycler paraquat, the proteasome inhibitors MG-132 or bortezomib, or high concentrations of NFT. Repurpose of the antibiotic NFT as activator of Nrf2 could thus be a promising strategy for a transient and targeted activation of the endogenous antioxidant machinery.

Cell-based metabolomics provides multiparametric physiologically relevant readouts that can be highly advantageous for improved, biologically based decision making in early stages of compound development. Here, we present the development of a 96-well plate LC-MS/MS-based targeted metabolomics screening platform for the classification of liver toxicity modes of action (MoAs) in HepG2 cells. Different parameters of the workflow (cell seeding density, passage number, cytotoxicity testing, sample preparation, metabolite extraction, analytical method, and data processing) were optimized and standardized to increase the efficiency of the testing platform. The applicability of the system was tested with seven substances known to be representative of three different liver toxicity MoAs (peroxisome proliferation, liver enzyme induction, and liver enzyme inhibition). Five concentrations per substance, aimed at covering the complete dose-response curve, were analyzed and 221 uniquely identified metabolites were measured, annotated, and allocated in 12 different metabolite classes such as amino acids, carbohydrates, energy metabolism, nucleobases, vitamins and cofactors, and diverse lipid classes. Multivariate and univariate analyses showed a dose response of the metabolic effects, a clear differentiation between liver toxicity MoAs and resulted in the identification of metabolite patterns specific for each MoA. Key metabolites indicative of both general and mechanistic specific hepatotoxicity were identified. The method presented here offers a multiparametric, mechanistic-based, and cost-effective hepatotoxicity screening that provides MoA classification and sheds light into the pathways involved in the toxicological mechanism. This assay can be implemented as a reliable compound screening platform for improved safety assessment in early compound development pipelines. Graphical abstract