Dynamic Metabolic and Transcriptional Responses of Proteasome-Inhibited Neurons

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

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.

PathwayNexus: a tool for interactive metabolic data analysis

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.

AVAILABILITY AND IMPLEMENTATION

The methodology presented here is implemented in PathwayNexus, an open-source add-on for Vanted available at www.cls.uni-konstanz.de/software/pathway-nexus.

CONTACT

falk.schreiber@unikonstanz.de.

SUPPLEMENTARY INFORMATION

Website: www.cls.uni-konstanz.de/software/pathway-nexus.

Definition of the Neurotoxicity-Associated Metabolic Signature Triggered by Berberine and Other Respiratory Chain Inhibitors

To characterize the hits from a phenotypic neurotoxicity screen, we obtained transcriptomics data for valinomycin, diethylstilbestrol, colchicine, rotenone, 1-methyl-4-phenylpyridinium (MPP), carbaryl and berberine (Ber). For all compounds, the concentration triggering neurite degeneration correlated with the onset of gene expression changes. The mechanistically diverse toxicants caused similar patterns of gene regulation: the responses were dominated by cell de-differentiation and a triggering of canonical stress response pathways driven by ATF4 and NRF2. To obtain more detailed and specific information on the modes-of-action, the effects on energy metabolism (respiration and glycolysis) were measured. Ber, rotenone and MPP inhibited the mitochondrial respiratory chain and they shared complex I as the target. This group of toxicants was further evaluated by metabolomics under experimental conditions that did not deplete ATP. Ber (204 changed metabolites) showed similar effects as MPP and rotenone. The overall metabolic situation was characterized by oxidative stress, an over-abundance of NADH (>1000% increase) and a re-routing of metabolism in order to dispose of the nitrogen resulting from increased amino acid turnover. This unique overall pattern led to the accumulation of metabolites known as biomarkers of neurodegeneration (saccharopine, aminoadipate and branched-chain ketoacids). These findings suggest that neurotoxicity of mitochondrial inhibitors may result from an ensemble of metabolic changes rather than from a simple ATP depletion. The combi-omics approach used here provided richer and more specific MoA data than the more common transcriptomics analysis alone. As Ber, a human drug and food supplement, mimicked closely the mode-of-action of known neurotoxicants, its potential hazard requires further investigation.

Proteomic responses in the human dopaminergic LUHMES cell line to imidacloprid and its metabolites imidacloprid-olefin and desnitro-imidacloprid

Neonicotinoids (neonics) are amongst the most commonly used class of pesticides globally. In the United States, imidacloprid (IMI) is extensively used for agriculture and in other common applications such as house-hold pest control. Regular exposure to IMI, and several of its known metabolites including IMI-olefin and desnitro-imidacloprid (DN-IMI), has been shown to be harmful to many organisms including mammals, birds, and fish. Studies show that neonics bind human nicotinicacetylcholine receptors (nAChRs) and cause cellular toxicity. In the dopaminergic Lund human mesencephalic (LUHMES) cell line, IMI and other neonics (10-100 μM) have been recently shown to activate intracellular calcium signaling through nAChRs. Thus, we examined proteomic responses of LUHMES cells to a 48-h treatment with 50 μM IMI, IMI-olefin, or DN-IMI. Our findings show differential effects of these neonics on cellular protein expression. Bioinformatic analysis of significantly altered proteins indicates an effect of IMI, IMI-olefin, and DN-IMI on protein synthesis and ribosomal function. These findings suggest a role for protein synthesis and transcriptional regulation in neonic-mediated dopaminergic neurotoxicity.

G × E interactions as a basis for toxicological uncertainty

To transfer toxicological findings from model systems, e.g. animals, to humans, standardized safety factors are applied to account for intra-species and inter-species variabilities. An alternative approach would be to measure and model the actual compound-specific uncertainties. This biological concept assumes that all observed toxicities depend not only on the exposure situation (environment = E), but also on the genetic (G) background of the model (G × E). As a quantitative discipline, toxicology needs to move beyond merely qualitative G × E concepts. Research programs are required that determine the major biological variabilities affecting toxicity and categorize their relative weights and contributions. In a complementary approach, detailed case studies need to explore the role of genetic backgrounds in the adverse effects of defined chemicals. In addition, current understanding of the selection and propagation of adverse outcome pathways (AOP) in different biological environments is very limited. To improve understanding, a particular focus is required on modulatory and counter-regulatory steps. For quantitative approaches to address uncertainties, the concept of "genetic" influence needs a more precise definition. What is usually meant by this term in the context of G × E are the protein functions encoded by the genes. Besides the gene sequence, the regulation of the gene expression and function should also be accounted for. The widened concept of past and present "gene expression" influences is summarized here as Ge. Also, the concept of "environment" needs some re-consideration in situations where exposure timing (Et) is pivotal: prolonged or repeated exposure to the insult (chemical, physical, life style) affects Ge. This implies that it changes the model system. The interaction of Ge with Et might be denoted as Ge × Et. We provide here general explanations and specific examples for this concept and show how it could be applied in the context of New Approach Methodologies (NAM).