Hennicke Kamp

Objective: The gut microbiome catalyzes biotransformation reactions that influence intestinal absorption as a basis of microbiome–host interactions. A better understanding of microbiota biotransformation capacity, and its modulation in dysregulated states, could enable prediction of individual responses to drugs and toxins and improve safety assessment. Methods: Here, we used chemical activity profiling to quantify biotransformation capacity modulations in rat gut microbiome ex vivo following oral exposure to eight drugs and dietary compounds: tobramycin, colistin, acesulfame potassium, saccharin, bovine serum albumin (BSA), meropenem, doripenem, and daidzein. We implemented an approach involving inoculation with metabolic probes during microbiota fermentations and measured their degradation rates. Results: In most exposure groups, we observed no modulation of microbiota biotransformation capacity; however, we detected significant modulations in biotransformation rates after exposure to meropenem, doripenem, and tobramycin. Interestingly, common patterns of biotransformation capacity were observed in the gut microbiomes from rats exposed to carbapenems and partially shared in microbiomes exposed to tobramycin. These results aligned well with prior metagenomic and metabolomic findings. Furthermore, correlations between microbial taxa and reaction rates were assessed to establish a link between specific bacteria and probe degradation. Conclusion: This functional relevance strategy revealed modulations of microbiota biotransformation capacity, as induced by in vivo exposures. Significance statement: This research provides a framework to predict how exposure to drugs or dietary compounds modulates the gut microbial capacity to biotransform xenobiotics, which is crucial for understanding individual drug responses and host–microbiome interactions.

The gut microbiome catalyzes biotransformation reactions that influence intestinal absorption as a basis of microbiome-host interactions. A better understanding of microbiota biotransformation capacity, and its alteration in dysregulated states, would enable the prediction of individual responses to drugs and toxins and improve safety assessment. Here, we profiled chemical activities in rat gut microbiota ex vivo, and quantified biotransformation capacity changes induced by oral exposure to eight drugs and dietary compounds: tobramycin, colistin, acesulfame potassium, saccharin, bovine serum albumin (BSA), meropenem, doripenem, and daidzein. We implemented an approach involving inoculation with metabolic probes during microbiota fermentations and measured their degradation. In most exposure groups, we observed no alteration of microbiota biotransformation capacity, however, we detected significant alterations in biotransformation rates after exposure to meropenem, doripenem and tobramycin. Interestingly, common patterns of biotransformation capacity were observed in the gut microbiomes from rats exposed to carbapenems and partially shared in microbiomes exposed to tobramycin. These results aligned well with prior metagenomic and metabolomic findings. Further, correlations between microbial taxa and reaction rates were assessed to establish a link between specific bacteria and probe degradation. This functionally relevant strategy revealed alterations of microbiota biotransformation capacity, as induced by in vivo exposures.

Xylene substances have wide industrial and consumer uses and are currently undergoing dossier and substance evaluation under Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) for further toxicological testing including consideration of an additional neurotoxicological testing cohort to an extended one-generation reproduction toxicity (EOGRT) study. New repeated dose study data on xylenes identify the thyroid as a potential target tissue, and therefore a weight of evidence review is provided to investigate whether or not xylene-mediated changes on the hypothalamus-pituitary-thyroid (HPT) axis are secondary to liver enzymatic induction and are of a magnitude that is relevant for neurological human health concerns. Multiple published studies confirm xylene-mediated increases in liver weight, hepatocellular hypertrophy, and liver enzymatic induction via the oral or inhalation routes, including an increase in uridine 5'-diphospho-glucuronosyltransferase (UDP-GT) activity, the key step in thyroid hormone metabolism in rodents. Only minimal to slight increases in thyroid follicular cell hypertrophy have been observed in some xylene repeated dose studies, with no associated robust or consistent perturbance of thyroid hormone changes across the studies or carried through to offspring indicating adaptive homeostatic maintenance of the HPT axis. Also importantly, in vitro human cell line data from the United States Environmental Protection Agency (US EPA) Toxicity Forecasting (ToxCast) provides supporting evidence of xylene's inability to directly perturb thyroidal functionality. A further supplemental in-depth metabolomics analysis (MetaMap^®Tox) of xylene showed a tentative match to compounds that also demonstrate extra-thyroidal effects on the HPT axis as a consequence of liver enzyme induction. Lastly, the slight HPT axis changes mediated by xylene were well-below the published literature thresholds for developmental neurotoxicological outcomes established for thyroidal changes in animals and humans. In summary, the data and various lines of scientific evidence presented herein individually and collectively demonstrate that xylene's mediated changes in the HPT axis, via a secondary extra-thyroidal MOA (i.e. liver enzyme induction), do not raise a human health concern with regards to developmental neurotoxicity. As such, the available toxicological data do not support the classification of xylene as a known or suspected endocrine disruptor, specifically through the thyroid modality, per Regulations Commission Delegated Regulation (EU) 2023/707 of 19 December 2022 amending Regulation (EC) No 1272/2008 and do not support the need for a neurotoxicological cohort evaluation in any subsequent EOGRTS.

Structure-based grouping of chemicals for targeted testing and read-across is an efficient way to reduce resources and animal usage. For substances of unknown or variable composition, complex reaction products, or biological materials (UVCBs), structure-based grouping is virtually impossible. Biology-based approaches such as metabolomics could provide a solution. Here, 15 steam-cracked distillates, registered in the EU through the Lower Olefins Aromatics Reach Consortium (LOA), as well as six of the major substance constituents, were tested in a 14-day rat oral gavage study, in line with the fundamental elements of the OECD 407 guideline, in combination with plasma metabolomics. Beyond signs of clinical toxicity, reduced body weight (gain), and food consumption, pathological investigations demonstrated the liver, thyroid, kidneys (males only), and hematological system to be the target organs. These targets were confirmed by metabolome pattern recognition, with no additional targets being identified. While classical toxicological parameters did not allow for a clear distinction between the substances, univariate and multivariate statistical analysis of the respective metabolomes allowed for the identification of several subclusters of biologically most similar substances. These groups were partly associated with the dominant (> 50%) constituents of these UVCBs, i.e., indene and dicyclopentadiene. Despite minor differences in clustering results based on the two statistical analyses, a proposal can be made for the grouping of these UVCBs. Both analyses correctly clustered the chemically most similar compounds, increasing the confidence that this biological approach may provide a solution for the grouping of UVCBs.

Changes in thyroid hormone (TH) levels in rat brain at early developmental stages are correlated with adverse effects on offspring development. To characterize the ability of substances to interfere with the TH concentrations in, e.g., rat brain, it is essential to know the mean TH concentrations in this tissue under control conditions. In this publication, an online solid-phase extraction (SPE) liquid chromatography (LC) tandem mass spectrometry (MS/MS) method was validated and used to measure TH metabolites (T4, T3, rT3, T2 and T1) in the brains of untreated rats. Data on TH concentrations in the whole brain and separate data from the cerebellum and the cortex are shown. The corresponding samples were gathered from young rats at postnatal days (PND) 4 and 21/22 and from adult rats. The results show inter alia the high accuracy and precision of the method, and LOQs of 0.02 ng/mL were determined for T1, T2 and rT3 and of 0.15 ng/mL for T3 and T4. Technical variability is low, as shown by the relative standard deviations of 7.5–20%. For our rat model, we found that T4, T3 and T2 concentrations rise from PND4 to PND21, whereas the rT3 concentration decreases; as well as there is no statistical difference between TH concentrations in the male and female rat brain. This method is suitable to analyze TH metabolites in the brain and build up a database of historical TH concentrations in control rats. Together, this yields a robust diagnostic tool to detect potentially adverse disturbances of TH homeostasis in the most vulnerable anatomic structure.

Omics techniques have been increasingly recognized as promising tools for Next Generation Risk Assessment. Targeted metabolomics offer the advantage of providing readily interpretable mechanistic information about perturbed biological pathways. In this study, a high-throughput LC–MS/MS-based broad targeted metabolomics system was applied to study nitrofurantoin metabolic dynamics over time and concentration and to provide a mechanistic-anchored approach for point of departure (PoD) derivation. Upon nitrofurantoin exposure at five concentrations (7.5 µM, 15 µM, 20 µM, 30 µM and 120 µM) and four time points (3, 6, 24 and 48 h), the intracellular metabolome of HepG2 cells was evaluated. In total, 256 uniquely identified metabolites were measured, annotated, and allocated in 13 different metabolite classes. Principal component analysis (PCA) and univariate statistical analysis showed clear metabolome-based time and concentration effects. Mechanistic information evidenced the differential activation of cellular pathways indicative of early adaptive and hepatotoxic response. At low concentrations, effects were seen mainly in the energy and lipid metabolism, in the mid concentration range, the activation of the antioxidant cellular response was evidenced by increased levels of glutathione (GSH) and metabolites from the de novo GSH synthesis pathway. At the highest concentrations, the depletion of GSH, together with alternations reflective of mitochondrial impairments, were indicative of a hepatotoxic response. Finally, a metabolomics-based PoD was derived by multivariate PCA using the whole set of measured metabolites. This approach allows using the entire dataset and derive PoD that can be mechanistically anchored to established key events. Our results show the suitability of high throughput targeted metabolomics to investigate mechanisms of hepatoxicity and derive point of departures that can be linked to existing adverse outcome pathways and contribute to the development of new ones.

The thyroid hormones (THs) regulate various physiological mechanisms in mammals, such as cellular metabolism, cell structure, and membrane transport. The therapeutic drugs propylthiouracil (PTU) and phenytoin are known to induce hypothyroidism and decrease blood thyroid hormone levels. To analyze the impact of these two drugs on systemic metabolism, we focused on metabolic changes after treatment. Therefore, in a rat model, the metabolome of thyroid and liver tissue as well as from the blood plasma, after 2-week and 4-week administration of the drugs and after a following 2-week recovery phase, was investigated using targeted LC-MS/MS and GC-MS. Both drugs were tested at a low dose and a high dose. We observed decreases in THs plasma levels, and higher doses of the drugs were associated with a high decrease in TH levels. PTU administration had a more pronounced effect on TH levels than phenytoin. Both drugs had little or no influence on the metabolomes at low doses. Only PTU exhibited apparent metabolome alterations at high doses, especially concerning lipids. In plasma, acylcarnitines and triglycerides were detected at decreased levels than in the controls after 2- and 4-week exposure to the drug, while sphingomyelins and phosphatidylcholines were observed at increased levels. Interestingly, in the thyroid tissue, triglycerides were observed at increased concentrations in the 2-week exposure group to PTU, which was not observed in the 4-week exposure group and in the 4-week exposure group followed by the 2-week recovery group, suggesting an adaptation by the thyroid tissue. In the liver, no metabolites were found to have significantly changed. After the recovery phase, the thyroid, liver, and plasma metabolomic profiles showed little or no differences from the controls. In conclusion, although there were significant changes observed in several plasma metabolites in PTU/Phenytoin exposure groups, this study found that only PTU exposure led to adaptation-dependent changes in thyroid metabolites but did not affect hepatic metabolites.

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