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Computational Strategies for Assessing Adverse Outcome Pathways: Hepatic Steatosis as a Case Study

Nov 19, 2024 | 2024, International Journal of Molecular Sciences, Journal publications

Abstract

The evolving landscape of chemical risk assessment is increasingly focused on developing tiered, mechanistically driven approaches that avoid the use of animal experiments. In this context, adverse outcome pathways have gained importance for evaluating various types of chemical-induced toxicity. Using hepatic steatosis as a case study, this review explores the use of diverse computational techniques, such as structure–activity relationship models, quantitative structure–activity relationship models, read-across methods, omics data analysis, and structure-based approaches to fill data gaps within adverse outcome pathway networks. Emphasizing the regulatory acceptance of each technique, we examine how these methodologies can be integrated to provide a comprehensive understanding of chemical toxicity. This review highlights the transformative impact of in silico techniques in toxicology, proposing guidelines for their application in evidence gathering for developing and filling data gaps in adverse outcome pathway networks. These guidelines can be applied to other cases, advancing the field of toxicological risk assessment.

MolCompass: multi-tool for the navigation in chemical space and visual validation of QSAR/QSPR models

Nov 19, 2024 | 2024, Journal of Cheminformatics, Journal publications

Abstract

The exponential growth of data is challenging for humans because their ability to analyze data is limited. Especially in chemistry, there is a demand for tools that can visualize molecular datasets in a convenient graphical way. We propose a new, ready-to-use, multi-tool, and open-source framework for visualizing and navigating chemical space. This framework adheres to the low-code/no-code (LCNC) paradigm, providing a KNIME node, a web-based tool, and a Python package, making it accessible to a broad cheminformatics community. The core technique of the MolCompass framework employs a pre-trained parametric t-SNE model. We demonstrate how this framework can be adapted for the visualisation of chemical space and visual validation of binary classification QSAR/QSPR models, revealing their weaknesses and identifying model cliffs. All parts of the framework are publicly available on GitHub, providing accessibility to the broad scientific community.

PathwayNexus: a tool for interactive metabolic data analysis

Nov 19, 2024 | 2024, Bioinformatics, Journal publications

Abstract

Motivation

High-throughput omics methods increasingly result in large datasets including metabolomics data, which are often difficult to analyse.

Results

To help researchers to handle and analyse those datasets by mapping and investigating metabolomics data of multiple sampling conditions (e.g. different time points or treatments) in the context of pathways, PathwayNexus has been developed, which presents the mapping results in a matrix format, allowing users to easily observe the relations between the compounds and the pathways. It also offers functionalities like ranking, sorting, clustering, pathway views, and further analytical tools. Its primary objective is to condense large sets of pathways into smaller, more relevant subsets that align with the specific interests of the user.

Knowledge infrastructure for integrated data management and analysis supporting new approach methods in predictive toxicology and risk assessment

Nov 19, 2024 | 2024, Journal publications, Toxicology in Vitro

Abstract

The EU-ToxRisk project (2016–2021) was a large European project working towards shifting toxicological testing away from animal tests, towards a toxicological assessment based on comprehensive mechanistic understanding of cause-consequence relationships of chemical adverse effects. More than 40 partners from scientific institutions, industry and regulators coordinated their work towards this goal in a six-year long programme. The breadth and variety of data and knowledge generated, presented a challenging data management landscape.
Here, we describe our approach to data management as developed under EU-ToxRisk. The main building blocks of the data infrastructure are: 1) An easy-to-use, extensible data and metadata format; 2) A flexible system with protocols for data capture and sharing from the entire consortium; 3) A methods database for describing and reviewing data generation and processing protocols; 4) Data archiving using a sustainable resource; 5) Data transformation from the archive to the system that provides granular access; 6) Application Programming Interface (API) for access to individual data points; 7) Data exploration and analysis modules, based on a «web notebook» approach to executable data processing documentation; and 8) Knowledge portal that ties together all of the above and provides a collaboration space for information exchange across the consortium. This knowledge infrastructure is being extended and refined for the support of follow-up projects (RISK-HUNT3R, ASPIS cluster, European Open Science Cloud (2021–2026)).

Modeling ferroptosis in human dopaminergic neurons: Pitfalls and opportunities for neurodegeneration research

Nov 19, 2024 | 2024, Journal publications, Redox Biology

Abstract

The activation of ferroptosis is being pursued in cancer research as a strategy to target apoptosis-resistant cells. By contrast, in various diseases that affect the cardiovascular system, kidneys, liver, and central and peripheral nervous systems, attention is directed toward interventions that prevent ferroptotic cell death. Mechanistic insights into both research areas stem largely from studies using cellular in vitro models. However, intervention strategies that show promise in cellular test systems often fail in clinical trials, which raises concerns regarding the predictive validity of the utilized in vitro models.
In this study, the human LUHMES cell line, which serves as a model for human dopaminergic neurons, was used to characterize factors influencing the activation of ferroptosis. Erastin and RSL-3 induced cell death that was distinct from apoptosis. Parameters such as the differentiation state of LUHMES cells, cell density, and the number and timing of medium changes were identified as determinants of sensitivity to ferroptosis activation. In differentiated LUHMES cells, interventions at mechanistically divergent sites (iron chelation, coenzyme Q10, peroxidase mimics, or inhibition of 12/15-lipoxygenase) provide almost complete protection from ferroptosis. LUHMES cells allowed the experimental modulation of intracellular iron concentrations and demonstrated a correlation between intracellular iron levels, the rate of lipid peroxidation, as well as the sensitivity of the cells to ferroptotic cell death.
These findings underscore the importance of understanding the various factors that influence ferroptosis activation and highlight the need for well-characterized in vitro models to enhance the reliability and predictive value of observations in ferroptosis research, particularly when translating findings into in vivo contexts.

Preparation of Viable Human Neurites for Neurobiological and Neurodegeneration Studies

Nov 19, 2024 | 2024, Cells, Journal publications

Abstract

Few models allow the study of neurite damage in the human central nervous system. We used here dopaminergic LUHMES neurons to establish a culture system that allows for (i) the observation of highly enriched neurites, (ii) the preparation of the neurite fraction for biochemical studies, and (iii) the measurement of neurite markers and metabolites after axotomy. LUHMES-based spheroids, plated in culture dishes, extended neurites of several thousand µm length, while all somata remained aggregated. These cultures allowed an easy microscopic observation of live or fixed neurites. Neurite-only cultures (NOC) were produced by cutting out the still-aggregated somata. The potential application of such cultures was exemplified by determinations of their protein and RNA contents. For instance, the mitochondrial TOM20 protein was highly abundant, while nuclear histone H3 was absent. Similarly, mitochondrial-encoded RNAs were found at relatively high levels, while the mRNA for a histone or the neuronal nuclear marker NeuN (RBFOX3) were relatively depleted in NOC. Another potential use of NOC is the study of neurite degeneration. For this purpose, an algorithm to quantify neurite integrity was developed. Using this tool, we found that the addition of nicotinamide drastically reduced neurite degeneration. Also, the chelation of Ca2+ in NOC delayed the degeneration, while inhibitors of calpains had no effect. Thus, NOC proved to be suitable for biochemical analysis and for studying degeneration processes after a defined cut injury.