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Integration of Genomic Data Streams in an In Vitro Network Development Model
Citation:
Gallegos, D., C. Marable, B. Chorley, K. Wallace, T. Freudenrich, AND T. Shafer. Integration of Genomic Data Streams in an In Vitro Network Development Model. Society of Toxicology 2021 Virtual Annual Meeting, Virtual, North Carolina, March 12 - 26, 2021. https://doi.org/10.23645/epacomptox.14466096
Impact/Purpose:
Poster presented to the Society of Toxicology 2021 virtual annual meeting March 2021. Adverse outcome pathways will increase the confidence in the use of data from NAMs assays by providing biological context. Recently, a network formation assay has been developed as a NAM to detect developmental neurotoxicity hazard. The present study provides methods by which data from this NAM can be combined with transcriptomic data in order to develop putative adverse outcome pathways that link the key event of altered network development to other cellular events and adverse outcomes.
Description:
Developmental neurotoxicity (DNT) represents a critical hazard for which less than 1% of environmental chemicals have been screened. Despite this backlog, in-vivo guideline studies of DNT are resource intensive, low throughput, and yield little insight into the molecular mechanisms underlying chemical-induced DNT. In response, batteries of in-vitro assays have been developed to elucidate the phenotypic and mechanistic underpinnings contributing to DNT attributed to environmental chemical exposure. Recently, we utilized a screening approach using rodent neurons grown on microelectrode arrays (MEA) to assess the effects of chemical compounds on neural network formation in rat cortical cultures. These assays collect and characterize multiple neural network parameters including neuronal firing rates, burst frequency/character, and coordinated network activity, alongside common measures of cell viability and morphology. Here we have coupled these data to high-throughput transcriptomics to resolve molecular key events mediating disruption of neural circuit formation. Using data from the MEA assay, we have identified “tipping point” concentrations at which chemical exposures elicit irreversible divergences from normal cortical circuit development. Specifically, we examined 18 chemicals in the classes of organophosphates, metals, and GABA modulators and report cognate changes in gene expression and associated cellular pathways. Gene Ontology analysis reveals that across classes at tipping point concentrations, there are unique transcriptional perturbations in gene programs for Neuronal Development, Neuron Migration, and Axonogeneis, among others. Despite this overlap, we see very distinct sets of genes affected by each chemical and class individually, suggesting that a characterization of the molecular events occuring in each cortical cell type will be key to understanding the complex interplay of transcriptional and circuit plasticities elicited by these compounds. As such, we are currently generating a combination of our MEA assay with single-cell sequencing data in order to identify key molecular events with cell-type resolution. These data will aid in developing putative adverse outcome pathways by linking key events associated with altered neural network development. This abstract does not necessarily reflect EPA policy.
URLs/Downloads:
DOI: Integration of Genomic Data Streams in an In Vitro Network Development Model
GALLEGOSSOT2021_DKBLUE_44X88V6.PDF (PDF, NA pp, 2219.327 KB, about PDF)