Skip Navigation
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Internet Explorer is no longer a supported browser.

This website may not display properly with Internet Explorer. For the best experience, please use a more recent browser such as the latest versions of Google Chrome, Microsoft Edge, and/or Mozilla Firefox. Thank you.

Your Environment. Your Health.

Texas A&M University

Superfund Research Program

Inter-Tissue and -Individual Variability in Response to Mixtures

Project Leader: Ivan Rusyn
Co-Investigator: David W. Threadgill
Grant Number: P42ES027704
Funding Period: 2017-2022
View this project in the NIH Research Portfolio Online Reporting Tools (RePORT)

Learn More About the Grantee

Visit the grantee's eNewsletter page Visit the grantee's Twitter page Visit the grantee's Facebook page

Project Summary (2017-2022)

The research team is developing a tiered translational in vitro-to-in vivo experimental testing strategy for evaluating the inter-tissue and inter-individual variability in responses to complex environmental mixtures. This goal is a critical part of the overall strategy of the Texas A&M University Superfund Research Program (TAMU SRP) Center to characterize and manage the human health risks associated with exposure to environmental emergency-mobilized hazardous substances through the development of tools that can be used by first responders, the impacted communities, and the government bodies involved in site management and cleanup.

The research team has demonstrated that organotypic and population-based experimental models for toxicology can enable not only a more rapid identification of chemical hazards, but also serve as the opportunity to test real-life exposures. Their overall hypothesis is that a tiered, risk-based strategy for safety evaluation consisting of human and mouse organotypic in vitro cultures and Collaborative Cross mouse strains, combined with a population-based reverse toxicokinetics, is a sensible "fit-for-purpose" approach to characterizing hazards of complex mixtures from contamination events during environmental emergencies.

The researchers are developing a multi-tissue "biological read-across" approach for complex environmental mixtures using high-content/-throughput assays with human induced pluripotent stem cells (iPSC). Data from high-content screening and high-throughput genomic analyses with human iPSC-derived organotypic cultures (hepatocytes, cardiomyocytes, endothelial cells, macrophages, neurons, etc.) is used to categorize the effects of mixtures with respect to the magnitude and tissue-specificity of the hazard. They are also developing a population-based in vitro-in vivo approach in mice to characterize inter-tissue and inter-individual variability in responses to complex environmental mixtures, including the Galveston Bay/Houston Ship Channel site samples that are collected in the Dynamic Exposure Pathways Under Conditions of Environmental Emergencies project. They use the Collaborative Cross, a panel of genetically diverse mouse strains that model human population variability, to establish a library of mouse iPSC-derived embryoid bodies that encompass diverse cell lineages. This population-based in vitro model is being used in toxicity screening of chemicals and mixtures.

The research team is also developing a high-throughput reverse toxicokinetics modeling approach for in vitro-to-in vivo extrapolation (IVIVE) of quantitative estimates of hazard for complex environmental mixtures. In partnership with the TAMU SRP Center Exposure Science Core, they utilize modern untargeted metabolomics methods to deconvolute complex mixtures into toxicokinetically-similar components on which high-throughput IVIVE can be performed. Finally, they demonstrate the utility of their biological read-across approach for quantitative estimation of hazard for complex environmental mixtures. They are partnering with the Data Science Core and Decision Science Core to show how in vitro toxicity and transcriptomic data, properly adjusted for toxicokinetics with IVIVE, can identify biological analogues to complex mixtures from a library of reference compounds. These data and methods are being translated into tools that can protect human health during and after environmental disaster emergencies.

Back
to Top