Project description:More than 80,000 chemicals in commerce present a challenge for hazard assessments that toxicity testing in the 21st century strives to address through high-throughput screening (HTS) assays. Assessing chemical effects on human development adds an additional layer of complexity to the screening, with a need to capture complex and dynamic events essential for proper embryo-fetal development. HTS data from ToxCast/Tox21 informs systems toxicology models, which incorporate molecular targets and biological pathways into mechanistic models describing the effects of chemicals on human cells, 3D organotypic culture models, and small model organisms. Adverse Outcome Pathways (AOPs) provide a useful framework for integrating the evidence derived from these in silico and in vitro systems to inform chemical hazard characterization. To illustrate this formulation, we have built an AOP for developmental toxicity through a mode of action linked to embryonic vascular disruption (Aop43). Here, we review the model for quantitative prediction of developmental vascular toxicity from ToxCast HTS data and compare the HTS results to functional vascular development assays in complex cell systems, virtual tissues, and small model organisms. ToxCast HTS predictions from several published and unpublished assays covering different aspects of the angiogenic cycle were generated for a test set of 38 chemicals representing a range of putative vascular disrupting compounds (pVDCs). Results boost confidence in the capacity to predict adverse developmental outcomes from HTS in vitro data and model computational dynamics for in silico reconstruction of developmental systems biology. Finally, we demonstrate the integration of the AOP and developmental systems toxicology to investigate the unique modes of action of two angiogenesis inhibitors.
Project description:Development of safe crop protection products is a complex process that traditionally relies on intensive animal use for hazard identification. Methods that capture toxicity at early stages of agrochemical discovery programs enable a more efficient and sustainable product development pipeline. Here we have explored whether the zebrafish model can be leveraged to identify mammalian-relevant toxicity. We used transgenic zebrafish to assess developmental toxicity following exposures to known mammalian teratogens, and captured larval morphological malformations, including bone and vascular perturbations. We further applied toxicogenomics to identify common biomarker signatures of teratogen exposure. The results show that the larval malformation assay predicted teratogenicity with 82.35% accuracy, 87.50% specificity, and 77.78% sensitivity. Slightly lower accuracy was obtained with the vascular and bone assays. A set of 20 biomarkers were identified that efficiently segregated teratogenic chemicals from non-teratogens. In conclusion, zebrafish are valuable, robust, and cost-effective models for toxicity testing at early stages of product development.
Project description:In this study, we differentiated mouse ESCs via 3D aggregates called embryoid bodies in presence of environmental and human relevant TBPPA concentrations for 28 days. We collected samples at different time points and analyzed TBBPA-dependent global gene expression changes by RNA-seq. Our analyses revealed a potential TBBPA multifaceted developmental toxicity with effects on the nervous and cardiac/skeletal muscle systems. Mechanistically, our findings suggest TBBPA endocrine disrupting activities in part via prolactin signaling.
Project description:Describing the architecture of robust, nonlinear cell signaling networks is essential to gain a predictive understanding of cellular behavior. The structure of the Drosophila Rho-signaling network, comprised of Rho-family GTPases, RhoGTP Exchange Factors (RhoGEFs), and RhoGTPase Activating Proteins (RhoGAPs), has been particularly difficult to infer due to the highly overlapping function and substrate specificity of network components. We developed a parameterized modeling approach to predict connectivity amongst components of the Rho-signaling network that was driven by hundreds of mRNA expression profiles derived from RNAi-mediated inhibition or overexpression of component genes. Our model incorporated rate kinetics, transcriptional feedback, and noise. We biochemically validated several novel predicted connections, and used this model to predict Rho-signaling response to particular conditions. While functional redundancy is a feature of all signaling systems that often prevents classical genetic methods from elucidating relationships between components, the methods described here provide the basis for describing any complex network architecture. Keywords: Genetic modification, RNAi-mediated gene inhibition 129 samples analyzed. Experiments were peformed in batches of 4 containing 1 control/reference sample (transfection of GFP alone) that was prepared in parallel with experimental samples. There are 30 reference samples. The majority of experiments were replicated 2-6 times.
Project description:Intestinal helminths cause iron-deficiency anemia in pregnant women, associated with premature delivery, low birth weight, maternal ill health, and maternal death. Although benzimidazole compounds such as mebendazole (MBZ) are highly efficacious against helminths, there are limited data on its use during pregnancy. In this study, we performed in vivo imaging of the retinas of zebrafish larvae exposed to MBZ, and found that exposure to MBZ during 2 and 3 days post-fertilization caused malformation of the retinal layers. To identify the molecular mechanism underlying the developmental toxicity of MBZ, we performed transcriptome analysis of zebrafish eyes. The analysis revealed that the DNA damage response was involved in the developmental toxicity of MBZ. We were also able to demonstrate that inhibition of ATM significantly attenuated the apoptosis induced by MBZ in the zebrafish retina. These results suggest that MBZ causes developmental toxicity in the zebrafish retina at least partly by activating the DNA damage response, including ATM signaling, providing a potential adverse outcome pathway in the developmental toxicity of MBZ in mammals.
Project description:Describing the architecture of robust, nonlinear cell signaling networks is essential to gain a predictive understanding of cellular behavior. The structure of the Drosophila Rho-signaling network, comprised of Rho-family GTPases, RhoGTP Exchange Factors (RhoGEFs), and RhoGTPase Activating Proteins (RhoGAPs), has been particularly difficult to infer due to the highly overlapping function and substrate specificity of network components. We developed a parameterized modeling approach to predict connectivity amongst components of the Rho-signaling network that was driven by hundreds of mRNA expression profiles derived from RNAi-mediated inhibition or overexpression of component genes. Our model incorporated rate kinetics, transcriptional feedback, and noise. We biochemically validated several novel predicted connections, and used this model to predict Rho-signaling response to particular conditions. While functional redundancy is a feature of all signaling systems that often prevents classical genetic methods from elucidating relationships between components, the methods described here provide the basis for describing any complex network architecture. Keywords: Genetic modification, RNAi-mediated gene inhibition