Mar 3, 2023 | 2022, Journal of Neurochemistry, Journal publications
Abstract
Metabolic glycoengineering (MGE) has been developed to visualize carbohydrates on live cells. The method allows the fluorescent labeling of sialic acid (Sia) sugar residues on neuronal plasma membranes. For instance, the efficiency of glycosylation along neurite membranes has been characterized as cell health measure in neurotoxicology. Using human dopaminergic neurons as model system, we asked here, whether it was possible to separately label diverse classes of biomolecules and to visualize them selectively on cells. Several approaches suggest that a large proportion of Sia rather incorporated in non-protein components of cell membranes than into glycoproteins. We made use here of deoxymannojirimycin (dMM), a non-toxic inhibitor of protein glycosylation, and of N-butyl-deoxynojirimycin (NBdNM) a well-tolerated inhibitor of lipid glycosylation, to develop a method of differential labeling of sialylated membrane lipids (lipid-Sia) or sialylated N-glycosylated proteins (protein-Sia) on live neurons. The time resolution at which Sia modification of lipids/proteins was observable was in the range of few hours. The approach was then extended to several other cell types. Using this technique of target-specific MGE, we found that in dopaminergic or sensory neurons >60% of Sia is lipid bound, and thus polysialic acid-neural cell adhesion molecule (PSA-NCAM) cannot be considered the major sialylated membrane component. Different from neurons, most Sia was bound to protein in HepG2 hepatoma cells or in neural crest cells. Thus, our method allows visualization of cell-specific sialylation processes for separate classes of membrane constituents.
Mar 3, 2023 | 2022, Chemosphere, Journal publications
Abstract
Developmental neurotoxicity (DNT) is a major safety concern for all chemicals of the human exposome. However, DNT data from animal studies are available for only a small percentage of manufactured compounds. Test methods with a higher throughput than current regulatory guideline methods, and with improved human relevance are urgently needed. We therefore explored the feasibility of DNT hazard assessment based on new approach methods (NAMs). An in vitro battery (IVB) was assembled from ten individual NAMs that had been developed during the past years to probe effects of chemicals on various fundamental neurodevelopmental processes. All assays used human neural cells at different developmental stages. This allowed us to assess disturbances of: (i) proliferation of neural progenitor cells (NPC); (ii) migration of neural crest cells, radial glia cells, neurons and oligodendrocytes; (iii) differentiation of NPC into neurons and oligodendrocytes; and (iv) neurite outgrowth of peripheral and central neurons. In parallel, cytotoxicity measures were obtained. The feasibility of concentration-dependent screening and of a reliable biostatistical processing of the complex multi-dimensional data was explored with a set of 120 test compounds, containing subsets of pre-defined positive and negative DNT compounds. The battery provided alerts (hit or borderline) for 24 of 28 known toxicants (82% sensitivity), and for none of the 17 negative controls. Based on the results from this screen project, strategies were developed on how IVB data may be used in the context of risk assessment scenarios employing integrated approaches for testing and assessment (IATA).
Mar 3, 2023 | 2022, Altex, Journal publications
Abstract
Banning or reduction of the use of animals for laboratory experiments is a frequently-discussed societal and scientific issue. Moreover, the usefulness of animals needs to be considered in any decision process on the permission of specific animal studies. This complex issue is often simplified and generalized in the media around the question, “Are animals useful as a model?” To render an often emotional discussion about animal experimentation more rational, it is important to define “usefulness” in a structured and transparent way. To achieve such a goal, many sub-questions need to be asked, and the following aspects require clarification: (i) consistency of animal-derived data (robustness of the model system); (ii) scientific domain investigated (e.g., toxicology vs disease modelling vs therapy); (iii) measurement unit for “benefit” (inte-grating positive and negative aspects); (iv) benchmarking to alternatives; (v) definition of success criteria (how good is good enough); (vi) the procedure to assess benefit and necessity. This series of articles discusses the overall benchmarking process by specifying the six issues. The goal is to provide guidance on what needs to be clarified in scientific and political discussions. This framework should help in the future to structure available information, to identify and fill information gaps, and to arrive at rational decisions in various sub-fields of animal use. In part I of the series, we focus on the robustness of animal models. This describes the capacity of models to produce the same output/response when faced with the “same” input. Follow-up articles will cover the remaining usefulness aspects.
Mar 3, 2023 | 2022, Frontiers in Molecular Biosciences, Journal publications
Abstract
During the past few decades, the direct analysis of metabolic intermediates in biological samples has greatly improved the understanding of metabolic processes. The most used technologies for these advances have been mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. NMR is traditionally used to elucidate molecular structures and has now been extended to the analysis of complex mixtures, as biological samples: NMR-based metabolomics. There are however other areas of small molecule biochemistry for which NMR is equally powerful. These include the quantification of metabolites (qNMR); the use of stable isotope tracers to determine the metabolic fate of drugs or nutrients, unravelling of new metabolic pathways, and flux through pathways; and metabolite-protein interactions for understanding metabolic regulation and pharmacological effects. Computational tools and resources for automating analysis of spectra and extracting meaningful biochemical information has developed in tandem and contributes to a more detailed understanding of systems biochemistry. In this review, we highlight the contribution of NMR in small molecule biochemistry, specifically in metabolic studies by reviewing the state-of-the-art methodologies of NMR spectroscopy and future directions.
Mar 3, 2023 | 2022, International Journal of Molecular Sciences, Journal publications
Human peripheral neuropathies are poorly understood, and the availability of experimental models limits further research. The PeriTox test uses immature dorsal root ganglia (DRG)-like neurons, derived from induced pluripotent stem cells (iPSC), to assess cell death and neurite damage. Here, we explored the suitability of matured peripheral neuron cultures for the detection of sub-cytotoxic endpoints, such as altered responses of pain-related P2X receptors. A two-step differentiation protocol, involving the transient expression of ectopic neurogenin-1 (NGN1) allowed for the generation of homogeneous cultures of sensory neurons. After >38 days of differentiation, they showed a robust response (Ca2+-signaling) to the P2X3 ligand α,β-methylene ATP. The clinical proteasome inhibitor bortezomib abolished the P2X3 signal at ≥5 nM, while 50−200 nM was required in the PeriTox test to identify neurite damage and cell death. A 24 h treatment with low nM concentrations of bortezomib led to moderate increases in resting cell intracellular Ca2+ concentration but signaling through transient receptor potential V1 (TRPV1) receptors or depolarization-triggered Ca2+ influx remained unaffected. We interpreted the specific attenuation of purinergic signaling as a functional cell stress response. A reorganization of tubulin to form dense structures around the cell somata confirmed a mild, non-cytotoxic stress triggered by low concentrations of bortezomib. The proteasome inhibitors carfilzomib, delanzomib, epoxomicin, and MG-132 showed similar stress responses. Thus, the model presented here may be used for the profiling of new proteasome inhibitors in regard to their side effect (neuropathy) potential, or for pharmacological studies on the attenuation of their neurotoxicity. P2X3 signaling proved useful as endpoint to assess potential neurotoxicants in peripheral neurons.
Mar 2, 2023 | 2022, Frontiers in Pharmacology, Journal publications
Abstract
SimRFlow is a high-throughput physiologically based pharmacokinetic (PBPK) modelling tool which uses Certara’s Simcyp® simulator. The workflow is comprised of three main modules: 1) a Data Collection module for automated curation of physicochemical (from ChEMBL and the Norman Suspect List databases) and experimental data (i.e.: clearance, plasma-protein binding, and blood-to-plasma ratio, from httk-R package databases), 2) a Simulation module which activates the Simcyp® simulator and runs Monte Carlo simulations on virtual subjects using the curated data, and 3) a Data Visualisation module for understanding the simulated compound-specific profiles and predictions. SimRFlow has three administration routes (oral, intravenous, dermal) and allows users to change some simulation parameters including the number of subjects, simulation duration, and dosing. Users are only expected to provide a file of the compounds they wish to simulate, and in return the workflow provides summary statistics, concentration-time profiles of various tissue types, and a database file (containing in-depth results) for each simulated compound. This is presented within a guided and easy-to-use R Shiny interface which provides many plotting options for the visualisation of concentration-time profiles, parameter distributions, trends between the different parameters, as well as comparison of predicted parameters across all batch-simulated compounds. The in-built R functions can be assembled in user-customised scripts which allows for the modification of the workflow for different purposes. SimRFlow proves to be a time-efficient tool for simulating a large number of compounds without any manual curation of physicochemical or experimental data necessary to run Simcyp® simulations.
