Gabriela G. Cezar

Identifying developmental toxicity pathways for a subset of ToxCast chemicals using human embryonic stem cells and metabolomics

Metabolomics analysis was performed on the supernatant of human embryonic stem (hES) cell cultures exposed to a blinded subset of 11 chemicals selected from the chemical library of EPAs ToxCast™ chemical screening and prioritization research project. Metabolites from hES cultures were evaluated for known and novel signatures that may be indicative of developmental toxicity. Significant fold changes in endogenous metabolites were detected for 83 putatively annotated mass features in response to the subset of ToxCast chemicals. The annotations were mapped to specific human metabolic pathways. This revealed strong effects on pathways for nicotinate and nicotinamide metabolism, pantothenate and CoA biosynthesis, glutathione metabolism, and arginine and proline metabolism pathways. Predictivity for adverse outcomes in mammalian prenatal developmental toxicity studies used ToxRefDB and other sources of information, including Stemina Biomarker Discoverys predictive DevTox® model trained on 23 pharmaceutical agents of known developmental toxicity and differing potency. The model initially predicted developmental toxicity from the blinded ToxCast compounds in concordance with animal data with 73% accuracy. Retraining the model with data from the unblinded test compounds at one concentration level increased the predictive accuracy for the remaining concentrations to 83%. These preliminary results on a 11-chemical subset of the ToxCast chemical library indicate that metabolomics analysis of the hES secretome provides information valuable for predictive modeling and mechanistic understanding of mammalian developmental toxicity.

Non-Cell-Autonomous Effect of Human SOD1G37R Astrocytes on Motor Neurons Derived from Human Embryonic Stem Cells

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by motor neuron death. ALS can be induced by mutations in the superoxide dismutase 1 gene (SOD1). Evidence for the non-cell-autonomous nature of ALS emerged from the observation that wild-type glial cells extended the survival of SOD1 mutant motor neurons in chimeric mice. To uncover the contribution of astrocytes to human motor neuron degeneration, we cocultured hESC-derived motor neurons with human primary astrocytes expressing mutated SOD1. We detected a selective motor neuron toxicity that was correlated with increased inflammatory response in SOD1-mutated astrocytes. Furthermore, we present evidence that astrocytes can activate NOX2 to produce superoxide and that effect can be reversed by antioxidants. We show that NOX2 inhibitor, apocynin, can prevent the loss of motor neurons caused by SOD1-mutated astrocytes. These results provide an assay for drug screening using a human ALS in vitro astrocyte-based cell model.

Predicting human developmental toxicity of pharmaceuticals using human embryonic stem cells and metabolomics.

Teratogens, substances that may cause fetal abnormalities during development, are responsible for a significant number of birth defects. Animal models used to predict teratogenicity often do not faithfully correlate to human response. Here, we seek to develop a more predictive developmental toxicity model based on an in vitro method that utilizes both human embryonic stem (hES) cells and metabolomics to discover biomarkers of developmental toxicity. We developed a method where hES cells were dosed with several drugs of known teratogenicity then LC-MS analysis was performed to measure changes in abundance levels of small molecules in response to drug dosing. Statistical analysis was employed to select for specific mass features that can provide a prediction of the developmental toxicity of a substance. These molecules can serve as biomarkers of developmental toxicity, leading to better prediction of teratogenicity. In particular, our work shows a correlation between teratogenicity and changes of greater than 10% in the ratio of arginine to asymmetric dimethylarginine levels. In addition, this study resulted in the establishment of a predictive model based on the most informative mass features. This model was subsequently tested for its predictive accuracy in two blinded studies using eight drugs of known teratogenicity, where it correctly predicted the teratogenicity for seven of the eight drugs. Thus, our initial data shows that this platform is a robust alternative to animal and other in vitro models for the prediction of the developmental toxicity of chemicals that may also provide invaluable information about the underlying biochemical pathways.

Genome-Wide Epigenetic Alterations in Cloned Bovine Fetuses

Abstract To gain a better understanding of global methylation differences associated with development of nuclear transfer (NT)-generated cattle, we analyzed the genome-wide methylation status of spontaneously aborted cloned fetuses, cloned fetuses, and adult clones that were derived from transgenic and nontransgenic cumulus, genital ridge, and body cell lines. Cloned fetuses were recovered from ongoing normal pregnancies and were morphologically normal. Fetuses generated by artificial insemination (AI) were used as controls. In vitro fertilization (IVF) fetuses were compared with AI controls to assess effects of in vitro culture on the 5-methylcytosine content of fetal genomes. All of the fetuses were female. Skin biopsies were obtained from cloned and AI-generated adult cows. All of the adult clones were phenotypically normal and lactating and had no history of health or reproductive disorders. Genome-wide cytosine methylation levels were monitored by reverse-phase HPLC, and results indicated reduced levels of methylated cytosine in NT-generated fetuses. In contrast, no differences were observed between adult, lactating clones and similarly aged lactating cows produced by AI. These data imply that survivability of cloned cattle may be closely related to the global DNA methylation status. This is the first report to indicate that global methylation losses may contribute to the developmental failure of cloned bovine fetuses.

Metabolomics as a Tool for Discovery of Biomarkers of Autism Spectrum Disorder in the Blood Plasma of Children

Background The diagnosis of autism spectrum disorder (ASD) at the earliest age possible is important for initiating optimally effective intervention. In the United States the average age of diagnosis is 4 years. Identifying metabolic biomarker signatures of ASD from blood samples offers an opportunity for development of diagnostic tests for detection of ASD at an early age. Objectives To discover metabolic features present in plasma samples that can discriminate children with ASD from typically developing (TD) children. The ultimate goal is to identify and develop blood-based ASD biomarkers that can be validated in larger clinical trials and deployed to guide individualized therapy and treatment. Methods Blood plasma was obtained from children aged 4 to 6, 52 with ASD and 30 age-matched TD children. Samples were analyzed using 5 mass spectrometry-based methods designed to orthogonally measure a broad range of metabolites. Univariate, multivariate and machine learning methods were used to develop models to rank the importance of features that could distinguish ASD from TD. Results A set of 179 statistically significant features resulting from univariate analysis were used for multivariate modeling. Subsets of these features properly classified the ASD and TD samples in the 61-sample training set with average accuracies of 84% and 86%, and with a maximum accuracy of 81% in an independent 21-sample validation set. Conclusions This analysis of blood plasma metabolites resulted in the discovery of biomarkers that may be valuable in the diagnosis of young children with ASD. The results will form the basis for additional discovery and validation research for 1) determining biomarkers to develop diagnostic tests to detect ASD earlier and improve patient outcomes, 2) gaining new insight into the biochemical mechanisms of various subtypes of ASD 3) identifying biomolecular targets for new modes of therapy, and 4) providing the basis for individualized treatment recommendations.

Stemina Biomarker Discovery

Stemina Biomarker Discovery was established in 2006 to commercialize technology developed by Dr Gabriela Cezar at the University of Wisconsin (WI, USA). Steminas cell-based assays arise from the strategic convergence of two cutting edge technologies: metabolomics and human embryonic stem (hES) cells. Stemina analyzes the small molecules secreted by hES cells and differentiated cell types such as neural and heart cells derived from hES cells by liquid chromatography mass spectrometry at its state-of-the-art facilities in Madison, WI, USA. Steminas first technology platform has identified a dynamic set of small molecules in the extracellular secretome of hES cells secreted in response to exposure to a library of known teratogens. Alterations to small molecules in the biochemical pathway(s) of hES cells are mapped in silico to identify biomarkers of toxicity for drug screening and development in an all human system. These small human molecules may then be translated in vivo as biomarkers of toxic response and disease.

Embryonic Stem Cells: A New Avenue to Evaluate the Effects of Chemicals in Humans

The predictive toxicity of chemicals to humans is largely based on scientific investigation in animal models. However, interspecies variability impacts the ability of certain animal models to emulate human response, which ultimately influences attrition rates in pharmaceutical development and safety assessment of new drugs. The availability of scalable human in vitro models for predictive toxicology may increase our confidence in risk assessment of chemicals in parallel to animal studies.Embryonic stem (ES) cells are pluripotent, not genetically modified cells isolated from preimplantation embryos. The establishment of human ES cells enables the production of large numbers of human cell types to evaluate the effects of chemicals on disease and toxic response. This review provides an overview of key opportunities for stem cell technology to produce in vitro models of disease and toxicity related to chemical exposure in humans. Specifically, the generation of neurons from ES cells is an innovative resource to elucidate mechanisms of neurotoxicity involved in neurodegeneration (Parkinson’s disease) or neurodevelopmental disorders (autism). This review reports the use of cardiomyocytes from ES cells as cellular substrates for preclinical safety assessment of compounds. QT prolongation may be evaluated in cardiomyocytes from ES cells on the basis of functional cardiac ion channels.The applications of ES cells in predictive toxicology may be as diverse as the cell types they generate, thus, we anticipate that this technology will significantly benefit our understanding of debilitating diseases and toxic effects associated with chemicals in humans.