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Engineering a Computable Epiblast for in silico Modeling of Developmental Toxicity (SOT 24)
Citation:
Barham, K., R. Spencer, Nancy C. Baker, AND T. Knudsen. Engineering a Computable Epiblast for in silico Modeling of Developmental Toxicity (SOT 24). Society of Toxicology (SOT) 63rd Annual Meeting and ToxExpo, Salt Lake CIty, UT, March 10 - 14, 2024. https://doi.org/10.23645/epacomptox.25488040
Impact/Purpose:
Presentation to the Society of Toxicology (SOT) 63rd Annual Meeting and ToxExpo March 2024
Description:
Background and Purpose: A virtual embryo may be conceptualized as a compendium of computational systems models that integrate biological systems information with chemical specific information to make predictions about developmental toxicity in a digital twin. A challenge toward a fully computable virtual embryo is construction and calibration of effective models that can be used to assess chemical risks during pregnancy. The epiblast layer of an early postimplantation embryo gives rise to most cell lineages during gastrulation. Recapitulating epiblast morphogenesis requires contextual information such as cell position, physical constraints, and self-organizing potential. Methods: We engineered a fully computable model of the epiblast to simulate the self-emergence of 4 mesodermal domains (chordamesoderm, paraxial, lateral plate, posterior/extraembryonic). Biological information mined from the literature used PubMed Abstract Sifter [Baker et al. 2017, F1000]. Information on epiblast morphogenesis derived mostly from mouse studies but included information on human cells where available. The computer model, referred to as Epiblast Stem Cell Agent-Based Model (ESABM), was engineered as a three-dimensional (3D) simulation in CompuCell3D [https://compucell3d.org/]. Although most information was from mouse, initial rendering was disc-shaped rather than cup-shaped to better reflect anatomy of the human embryo at Carnegie Stages CS6 – CS7 versus mouse at embryonic days E6.25 – E7.25. For sensitivity analysis, the model was perturbed at specific nodes or relationships in key signaling pathways. Resultant in silico morphologies (cybermorphs) were compared against phenotypes defined from literature where available. Several ligand-receptor nodes in the biological control network of ESABM were then mapped to specific assay targets available in ToxCast. This provided use-case scenarios for translating in vitro chemical-bioactivity effects data from EPA’s CompTox Chemicals Dashboard [https://comptox.epa.gov/dashboard/] into predicted phenotypes. Results: ESABM’s cell fate and behavior was driven by an autonomous homeobox (HOX) clock and a network of morphogenetic signals (FGF4/8, BMP4, NODAL, LEFTY1, WNT3, ATRA, CDX2/4) executing the embryo’s transformation from bilaminar (epiblast, hypoblast) to trilaminar (epiblast, hypoblast, mesoderm) primary germ layers. Epiblast cells drawn to the midline undergo epithelial-mesenchymal transition (EMT) formed a primitive streak. Endodermal signal centers polarized the streak from proximal (posterior) to distal (anterior) regions. Mesodermal specification was an emergent feature based on cell position and timing of EMT, fated for chordamesoderm (axial), paraxial (somite), lateral (limbs), and posterior (caudal, blood) domains. This specification was paced by FGF4-WNT-ATRA regulation of the CDX-HOX axis. Cell-level computation was output for each mesodermal field.......... Conclusions: The ESABM platform enables integration of in vitro chemical bioactivity data for specific molecular targets with known embryology to test mechanistic veracity and quantitative prediction of epiblast development. Virtual embryo is a novel approach to visualize cellular trajectories, map toxicodynamics, and predict adverse phenotype in ways difficult to accomplish in vivo. The temporality of ESABM at present covers a morphogenetic series of events from pre-gastrulation (E6.25) through mid-gastrulation (E7.25) but can be linked with other virtual tissue models for mechanistic prediction of developmental toxicity. This abstract does not necessarily reflect Agency policy.
URLs/Downloads:
DOI: Engineering a Computable Epiblast for in silico Modeling of Developmental Toxicity (SOT 24)
SOT_POSTER_BARHAM_FINAL 2.PDF (PDF, NA pp, 1659.815 KB, about PDF)