Use of metabolic glycoengineering and pharmacological inhibitors to assess lipid and protein sialylation on cells.

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.

Neurotoxicity and underlying cellular changes of 21 mitochondrial respiratory chain inhibitors.

Inhibition of complex I of the mitochondrial respiratory chain (cI) by rotenone and methyl-phenylpyridinium (MPP +) leads to the degeneration of dopaminergic neurons in man and rodents. To formally describe this mechanism of toxicity, an adverse outcome pathway (AOP:3) has been developed that implies that any inhibitor of cI, or possibly of other parts of the respiratory chain, would have the potential to trigger parkinsonian motor deficits. We used here 21 pesticides, all of which are described in the literature as mitochondrial inhibitors, to study the general applicability of AOP:3 or of in vitro assays that are assessing its activation. Five cI, three complex II (cII), and five complex III (cIII) inhibitors were characterized in detail in human dopaminergic neuronal cell cultures. The NeuriTox assay, examining neurite damage in LUHMES cells, was used as in vitro proxy of the adverse outcome (AO), i.e., of dopaminergic neurodegeneration. This test provided data on whether test compounds were unspecific cytotoxicants or specifically neurotoxic, and it yielded potency data with respect to neurite degeneration. The pesticide panel was also examined in assays for the sequential key events (KE) leading to the AO, i.e., mitochondrial respiratory chain inhibition, mitochondrial dysfunction, and disturbed proteostasis. Data from KE assays were compared to the NeuriTox data (AO). The cII-inhibitory pesticides tested here did not appear to trigger the AOP:3 at all. Some of the cI/cIII inhibitors showed a consistent AOP activation response in all assays, while others did not. In general, there was a clear hierarchy of assay sensitivity: changes of gene expression (biomarker of neuronal stress) correlated well with NeuriTox data; mitochondrial failure (measured both by a mitochondrial membrane potential-sensitive dye and a respirometric assay) was about 10-260 times more sensitive than neurite damage (AO); cI/cIII activity was sometimes affected at > 1000 times lower concentrations than the neurites. These data suggest that the use of AOP:3 for hazard assessment has a number of caveats: (i) specific parkinsonian neurodegeneration cannot be easily predicted from assays of mitochondrial dysfunction; (ii) deriving a point-of-departure for risk assessment from early KE assays may overestimate toxicant potency.

Time and space-resolved quantification of plasma membrane sialylation for measurements of cell function and neurotoxicity.

While there are many methods to quantify the synthesis, localization, and pool sizes of proteins and DNA during physiological responses and toxicological stress, only few approaches allow following the fate of carbohydrates. One of them is metabolic glycoengineering (MGE), which makes use of chemically modified sugars (CMS) that enter the cellular biosynthesis pathways leading to glycoproteins and glycolipids. The CMS can subsequently be coupled (via bio-orthogonal chemical reactions) to tags that are quantifiable by microscopic imaging. We asked here, whether MGE can be used in a quantitative and time-resolved way to study neuronal glycoprotein synthesis and its impairment. We focused on the detection of sialic acid (Sia), by feeding human neurons the biosynthetic precursor N-acetyl-mannosamine, modified by an azide tag. Using this system, we identified non-toxic conditions that allowed live cell labeling with high spatial and temporal resolution, as well as the quantification of cell surface Sia. Using combinations of immunostaining, chromatography, and western blotting, we quantified the percentage of cellular label incorporation and effects on glycoproteins such as polysialylated neural cell adhesion molecule. A specific imaging algorithm was used to quantify Sia incorporation into neuronal projections, as potential measure of complex cell function in toxicological studies. When various toxicants were studied, we identified a subgroup (mitochondrial respiration inhibitors) that affected neurite glycan levels several hours before any other viability parameter was affected. The MGE-based neurotoxicity assay, thus allowed the identification of subtle impairments of neurochemical function with very high sensitivity.

Development of a neural rosette formation assay (RoFA) to identify neurodevelopmental toxicants and to characterize their transcriptome disturbances.

The first in vitro tests for developmental toxicity made use of rodent cells. Newer teratology tests, e.g. developed during the ESNATS project, use human cells and measure mechanistic endpoints (such as transcriptome changes). However, the toxicological implications of mechanistic parameters are hard to judge, without functional/morphological endpoints. To address this issue, we developed a new version of the human stem cell-based test STOP-tox(UKN). For this purpose, the capacity of the cells to self-organize to neural rosettes was assessed as functional endpoint: pluripotent stem cells were allowed to differentiate into neuroepithelial cells for 6 days in the presence or absence of toxicants. Then, both transcriptome changes were measured (standard STOP-tox(UKN)) and cells were allowed to form rosettes. After optimization of staining methods, an imaging algorithm for rosette quantification was implemented and used for an automated rosette formation assay (RoFA). Neural tube toxicants (like valproic acid), which are known to disturb human development at stages when rosette-forming cells are present, were used as positive controls. Established toxicants led to distinctly different tissue organization and differentiation stages. RoFA outcome and transcript changes largely correlated concerning (1) the concentration-dependence, (2) the time dependence, and (3) the set of positive hits identified amongst 24 potential toxicants. Using such comparative data, a prediction model for the RoFA was developed. The comparative analysis was also used to identify gene dysregulations that are particularly predictive for disturbed rosette formation. This 'RoFA predictor gene set' may be used for a simplified and less costly setup of the STOP-tox(UKN) assay.

SUIKER: Quantification of antigens in cell organelles, neurites and cellular sub-structures by imaging.

Quantification of fluorescence colocalization and intensity of strongly overlapping cells, e.g., neuronal cultures, is challenging for programs that use image segmentation to identify cells as individual objects. Moreover, learning to use and apply one of the large imaging packages can be very time- and/or resource-demanding. Therefore, we developed the free and highly interactive image analysis program SUIKER (program for SUperImposing KEy Regions) that quantifies colocalization of different proteins or other features over an entire image field. The software allows definition of cellular subareas by subtraction ("punching out") of structures identified in one channel from structures in a second channel. This allows, e.g., definition of neurites without cell bodies. Moreover, normalization to live or total cell numbers is possible. Providing a detailed manual that contains image analysis examples, we demonstrate how the program uses a combination of colocalization information and fluorescence intensity to quantify carbohydrate-specific stains on neurites. SUIKER can import any multichannel histology or cell culture image, builds on user-guided threshold setting, batch processes large image stacks, and exports all data (including the settings, results and metadata) in flexible formats to be used in Excel.