Grantee Research Project Results
2022 Progress Report: Integrating tissue chips, rapid untargeted analytical methods and molecular modeling for toxicokinetic screening of chemicals, their metabolites and mixtures
EPA Grant Number: R840032Title: Integrating tissue chips, rapid untargeted analytical methods and molecular modeling for toxicokinetic screening of chemicals, their metabolites and mixtures
Investigators: Rusyn, Ivan , Baker, Erin D. , Chiu, Weihsueh A
Institution: Texas A & M University , North Carolina State University
EPA Project Officer: Spatz, Kyle
Project Period: August 1, 2020 through July 30, 2023 (Extended to July 30, 2024)
Project Period Covered by this Report: August 1, 2021 through July 31,2022
Project Amount: $799,993
RFA: Advancing Toxicokinetics for Efficient and Robust Chemical Evaluations (2019) RFA Text | Recipients Lists
Research Category: Chemical Safety for Sustainability
Objective:
The long-term objective of this project is to support risk-based decisions with new approach methodologies (NAMs) data by demonstrating integration of new biological (i.e., tissue chips), analytical (i.e., IMS-MS), and modeling methods for high fidelity, data-driven IVIVE. Specifically, this project aims to use tissue chips that are already commercially available to generate physiologically relevant toxicokinetic data, as well as to demonstrate how high-throughput detection, identification, and quantification of multiple chemicals, their metabolites, and mixtures can be achieved through the use of Ion mobility spectrometry-mass spectrometry and a computational pipeline and database of thousands of environmental chemicals. We are extending traditional IVIVE approaches by incorporating both tissue chip-based toxicokinetic data and IMS-MS analytical data into high throughput PBPK modeling of both parent chemicals and metabolites. This work will enable a more comprehensive characterization of toxicokinetics and metabolite formation, thereby reducing the uncertainty of traditional IVIVE approaches and improving the basis for decision-making with NAMs data.
The main outcome of this project will be a novel approach and a framework to support risk-based decisions on environmental chemicals and mixtures by demonstrating how an integrated set of novel biological assays (i.e., tissue chips), analytical techniques (i.e., IMS-MS) and computational methods can be used to enable high-fidelity, data-driven toxicokinetic modeling. Overall, the project is pursuing the following specific aims.
Aim 1: To generate physiologically relevant toxicokinetic data for IVIVE by using tissue chips.
Aim 2: To integrate untargeted analytical methods and metabolite predictions into IVIVE.
Aim 3: To integrate tissue chip assays and IMS-MS into high throughput PBPK models for more efficient and robust IVIVE.
Progress Summary:
The practical aspects of using microphysiological systems (MPS) in the context of their applications in decision-making are largely under-reported because most publications focus on the development of MPS rather than their use to address regulatory science-related challenges. Therefore, the work of this project to demonstrate the use of MPS that are either commercially available (i.e., accessible to the wider community) or can be manufactured at low cost and high number without the need for specialized equipment, to generate physiologically-relevant toxicokinetic data for regulatory science applications and especially for IVIVE modeling. To this end, we focused our work in Year 2 on the number of projects as detailed below.
In Aim 1, most of our work this year was focused on characterizing the utility of human liver MPS for studies of toxicokinetics of drugs and environmental chemicals. In one study, we used human microfluidic four-cell liver acinus microphysiology system (LAMPS) tissue chip to predict hepatic clearance for seven drugs with human toxicokinetic data. We found that, compared to in vivo clinically derived values, the LAMPS model with iPSC-derived hepatocytes had higher precision as compared to primary cells in suspension or 2D culture, but, consistent with previous studies in other MPS, tended to underestimate in vivo clearance. Overall, these results suggest that use of LAMPS and iPSC-derived hepatocytes together with an empirical scaling factor warrants additional study with a larger set of compounds, as it has the potential to provide more accurate and precise estimates of hepatic clearance. In a second study, we conducted a comparative analysis of three in vitro liver models to evaluate their utility for studies of metabolism of pesticides in mixtures: suspension, 2D sandwich, and OrganoPlate® 2-lane 96 well plate. We determined clearance rate for each compound with traditional mass spectrometry methods and nontargeted analytical method (IMS-MS). The results of this study are informative for assessment of metabolic capacity between traditional in vitro metabolism models and a novel microphysiological system; the data show the limitations of the microphysiological systems with respect to their metabolic capacity.
In a third study under Aim 1, we focused on creating a robust and easy-to-use model for human small airway on a chip. We developed a device that can be easily manufactured while allowing for the production of a differentiated lung tissue on a chip. This multilayered device enabled coculture of primary human small airway epithelial cells and lung microvascular endothelial cells under physiological conditions for up to 18 days and recreates the parenchymal-vascular interface in the distal lung. To explore the potential of this airway on a chip for applications in inhalation toxicology, we also devised a system that allows for direct gas/aerosol exposures of the engineered airway epithelium to noxious stimuli known to cause adverse respiratory effects, including dry flowing air, lipopolysaccharide, particulate matter, and iodomethane. This study generated quantitative, high-content data that were indicative of aberrant changes in biochemical, barrier, functional, and molecular phenotypes of the small airway epithelium due to inhalational exposures. While we have not evaluated toxicokinetics in this study, it is significant because it established an in vitro model of human small airway on a chip that can be used in medium/high-throughput studies of subacute effects of inhalation toxicants.
In Aim 2, we continued research to tackle a number of key challenges in identification and quantification of chemicals, their metabolites, and constituents of mixtures in environmental and experimental samples. We used nontargeted analyses coupling ion mobility spectrometry and mass spectrometry (IMS-MS) separations and compared the results to traditional analytical data. Specifically, we published several papers that demonstrated the application of IMS-MS to the analysis of complex substances (such as products of petroleum refining), mixtures (per- and poly-fluorinated compounds, pesticides), and tissue samples. We also demonstrated how IMS-MS can be used to identify persistent organic pollutants (POPs) and their metabolites in complex samples, to increase knowledge about molecules changing based on specific exposures, and developed novel tools and workflows to evaluate the data. Because humans are exposed to mixtures of chemicals, the findings and products of these studies (methods, analysis techniques and databases) are significant as they demonstrate the importance of incorporating novel rapid nontargeted analytical methods in order to accurately evaluate potential exposures, prioritize risks and facilitate science-based decision-making.
The purpose of Aim 3 is to integrate tissue chip assays and IMS-MS into high-throughput PBPK models for IVIVE. In Year 2, we have focused model development on the Absorption portion of the PBPK model, in addition to supporting the other Aims. Specifically, we published an open-source version of the Advanced Compartmental and Transit (ACAT) model that shows good performance for pharmaceuticals (Hsieh et al., 2021). We also have adapted this model to environmental chemicals by “turning off” drug-related components related to the dissolution-precipitation processes, thus assuming that environmental chemical is ingested in dissolved form, as well as adding liver and kidney compartments, denoting this the Environmental Compartmental and Transit (ECAT) model. Using this model, we then made predictions as to the fraction absorbed (incorporating uncertainty) for environmental chemicals for which in vitro Caco-2 permeability data were available. While most of these chemicals were predicted to have nearly complete absorption, there were three out of 15 chemicals where the 95% confidence interval extended below 50% absorption. using these results, we proposed a probabilistic modeling framework to convert in vitro permeability measurements to predictions of fraction absorbed that can be readily incorporated into IVIVE predictions of Css. While currently calibrated for Caco-2 transwell experiments, the database can be readily used to calibrate to other types of in vitro or microphysiological models. In support of other parts of the project, we worked to derive hepatic clearance estimates using the data from experiments using various microphysiological or 2D models.
Future Activities:
In Specific Aim 1, we will continue experiments with the tissue chip models for kidney (both glomerulus and proximal tubule), gut (Caco-2 cells and human enteroids), and liver (two different commercial platforms for the liver). We will be testing a number of chemicals in each model and conduct both in vitro and analytical chemistry experiments to collect data for IVIVE analyses in Aim 3. We will be testing both individual chemicals, their metabolites, and mixtures.
In Specific Aim 2, we will continue to utilize IMS-MS and our new workflow based on molecular descriptors for the evaluation of both parent chemicals and their transformation products in complex biological samples and tissue chip models. The observed transformation products from these analyses will then be incorporated into computational models and workflows to assess and annotate the features and gain a better understanding of metabolism, degradation, and other transformation mechanisms.
In Specific Aim 3, will complete publication of the ECAT model for gut absorption, and then work with Aims 1 and 2 to incorporate data from both traditional Caco-2 experiments and “gut chips” into the model to make predictions as to gut absorption. For hepatic clearance, we will continue to support Aim 1 in make clearance calculations using data from various platforms. Additionally, when kidney chip data are available, we will apply the parallel tube model to derive renal excretion parameters. In all cases, we will continue to utilize the literature data we have collected on ADME for comparison and analyses of accuracy.
Journal Articles on this Report : 6 Displayed | Download in RIS Format
Other project views: | All 19 publications | 16 publications in selected types | All 16 journal articles |
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Aly N, Dodds J, Luo Y, Grimm F, Foster M, Rusyn I, Baker E. Utilizing ion mobility spectrometry-mass spectrometry for the characterization and detection of persistent organic pollutants and their metabolites. ANALYTICAL AND BIOANALYTICAL CHEMISTRY 2021;414(3):1245-1258 |
R840032 (2022) |
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Dodds J, Baker E. Improving the Speed and Selectivity of Newborn Screening Using Ion Mobility SpectrometryâMass Spectrometry. ANALYTICAL CHEMISTRY 2021;93(51):17094-17102 |
R840032 (2022) |
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Foley M, Walker M, Stewart A, O'Flaherty S, Gentry E, Patel S, Beaty V, Allen G, Pan M, Simpson J, Perkins C, Vanoy M, Doughtery M, McGill S, Gulati A, Dorrenstein P, Baker E, Redinbo M, Barrangou R, Theriot C. Bile salt hydrolases shape the bile acid landscape and restrict Clostridioides difficile growth in the murine gut. NATURE MICROBIOLOGY 2023;8(4):611-628 |
R840032 (2022) |
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Foster M, Rainey M, Watson C, Dodds J, Kirkwood K, Fernandez F, Baker E. Uncovering PFAS and Other Xenobiotics in the Dark Metabolome Using Ion Mobility Spectrometry, Mass Defect Analysis, and Machine Learning. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022;56(12):9133-9143 |
R840032 (2022) |
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Kirkwood K, Fleming J, Nguyn F, Reif D, Baker E, Belcher S. Utilizing Pine Needles to Temporally and Spatially Profile Per- and Polyfluoroalkyl Substances (PFAS). ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022;56(6):3441-3451 |
R840032 (2022) |
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Odenkirk MT, Reif DM, Baker ES. Multiomic Big Data Analysis Challenges:Increasing Confidence in the Interpretation of Artificial Intelligence Assessments. Analytical Chemistry 2021. |
R840032 (2021) R840032 (2022) |
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Supplemental Keywords:
in vitro-to-in vivo, tissue chips, rapid analytical methods, IMS-MS, NAMs.Relevant Websites:
GitHub Exit , NC State Collision Cross Section Database Exit
Progress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.