Superfund Research Program
Computational Modeling Core
Project Leader: Qiang Zhang (The Hamner Institutes for Health Sciences)
Grant Number: P42ES004911
Funding Period: 2022-2027
- Project Summary
Project Summary (2022-2027)
Pharmacokinetics (PK) and pharmacodynamics (PD) together define the continuum from toxicant exposure to biological perturbations that can cause adverse outcomes. Toxicology increasingly involves computational approaches that complement laboratory studies and provide a more integrated, quantitative, and mechanistic basis for human health risk assessment. The Computational Modeling Core (CMC) provides a suite of computational capabilities to support both the Biomedical and Environmental Engineering Projects. The CMC: (i) develops physiologically based PK (PBPK) and PD models of dioxins and dioxin-like compounds, (ii) develops project-oriented bioinformatic support for high-dimensional -omic studies and, (iii) provides cross-disciplinary training in computational toxicology. Model development is coordinated iteratively with laboratory experiments carried out by the projects. Prior CMC interactions with the Michigan State University (MSU) Superfund Research Program projects have shown that this iterative approach is efficient for hypothesis generation and evaluation.
In Aim 1, the team is developubg PBPK models for 2,3,7,8-tetrachlorodiben-p-dioxin (TCDD) and Superfund site-relevant polychlorinated dibenzo-p-dioxins and furans (PCDD/Fs). The models include induction of hepatic CYP1A2 as a dioxin-binding protein and liver lipid accumulation for more accurate predictions of free PCDD/F concentrations. The models support hepatotoxicity studies in mice in the The Role of HMGCR in Modulating TCDD-Induced, AHR-Mediated NAFLD project and PCDD/F bioavailability studies of activated carbon-treated soil in the Bioavailability as a Central Concept in Determining Remediation Goals and Strategies for PCDD/F-Contaminated Superfund Sites project. Human PBPK models are also being developed to help establish tissue dose equivalency between mice and humans for The Role of HMGCR in Modulating TCDD-Induced, AHR-Mediated NAFLD project and for extrapolation of in vivo PCDD/F exposure levels based on in vitro assays in the Dioxin-Like Compounds Suppress IgM Responses by Targeting CD5+ (Innate-like) B Cells, Which Can Serve as a Biomarker of Susceptibility to Environmental AHR Ligand project and the Coupling Bioengineered and Computational Models of Thyroid Homeostasis to Support Human PCDD/F Risk-Assessment project.
As part of Aim 2, bioinformatic tools are used to parse out aryl hydrocarbon receptor (AHR)-mediated cell state trajectories from single-cell RNA sequencing data in human CD5+ B cells (Dioxin-Like Compounds Suppress IgM Responses by Targeting CD5+ (Innate-like) B Cells, Which Can Serve as a Biomarker of Susceptibility to Environmental AHR Ligands) and mouse hepatocytes (The Role of HMGCR in Modulating TCDD-Induced, AHR-Mediated NAFLD) and apply nonlinear dynamical systems analysis to identify novel biomarkers predictive of onset of AHR-mediated toxicity. The AHR-perturbed gene regulatory networks are being identified to inform pathway modeling in Aim 3.
In Aim 3, dynamical pathway modeling for the Dioxin-Like Compounds Suppress IgM Responses by Targeting CD5+ (Innate-like) B Cells, Which Can Serve as a Biomarker of Susceptibility to Environmental AHR Ligands project is addressing the effects of AHR activation on the PD-1 inhibitory signal transduction pathway in CD5+ B cells. For the Coupling Bioengineered and Computational Models of Thyroid Homeostasis to Support Human PCDD/F Risk-Assessment project, a model of induction of hepatic thyroid hormone metabolism by PCDD/Fs is being developed to support population health risk assessment. For The Role of HMGCR in Modulating TCDD-Induced, AHR-Mediated NAFLD project, pathway modeling focuses on disruption of hepatic lipid metabolism through AHR-mediated transcriptional alteration of key liver enzymes. These models support rigorous investigation of nonlinear dose-responses and provide a strong foundation for research supporting mechanistically driven risk assessment.
CMC also supports the Design Principles and Field-Deployable Models for Economical Remediation of Dioxin-Contaminated Sites project to model the vitamin B12 salvaging and de novo synthesis pathways in bacteria dehalogenating PCDD/Fs. In SA4, in collaboration with the Research Experience and Training Coordination Core, a three-day course on PBPK modeling and a 5-day course on Computational Systems Toxicology: Modeling and Informatics is being offered in alternate years to SRP and risk-assessment communities.