Grantee Research Project Results

2014 Progress Report: Carolina Center for Computational Toxicology: Assays, models and tools for NextGen safety assessments

EPA Grant Number: R835166
Title: Carolina Center for Computational Toxicology: Assays, models and tools for NextGen safety assessments
Investigators: Rusyn, Ivan , Wright, Fred A. , Yeatts, Karin B. , Tropsha, Alex
Current Investigators: Rusyn, Ivan , Wright, Fred A. , Tropsha, Alexander , Chiu, Weihsueh
Institution: University of North Carolina at Chapel Hill
Current Institution: University of North Carolina at Chapel Hill , North Carolina State University , Texas A & M University
EPA Project Officer: Aja, Hayley
Project Period: July 1, 2012 through June 30, 2016 (Extended to June 30, 2017)
Project Period Covered by this Report: July 1, 2013 through June 30,2014
Project Amount: $1,200,000
RFA: Developing High-Throughput Assays for Predictive Modeling of Reproductive and Developmental Toxicity Modulated Through the Endocrine System or Pertinent Pathways in Humans and Species Relevant to Ecological Risk Assessment (2011) RFA Text | Recipients Lists
Research Category: Chemical Safety for Sustainability

Objective:

The objective of the Carolina Center for Computational Toxicology is to advance the science and practice of toxicology by (i) filling critical gaps in our knowledge of the toxicity mechanisms, (ii) incorporating the population-based screening methods into the practice of toxicity testing, (iii) developing reliable computational models and tools that address specific existing challenges in hazard identification, and (iv) engaging with the stakeholders to increase the impact of our work.

Progress Summary:

In Specific Objective 1, our goal is to develop a quantitative high-throughput screening (qHTS) approach to probe differential chemical effects in a population-based in vitro system. To this end, we collaborated with NCATS and NIEHS/NTP that used 1,086 lymphoblastoid cell lines from the 1000 Genomes Project, representing 9 populations from 5 continents, to assess variation in cytotoxic response to 179 chemicals (Abdo, et al. 2015). This study demonstrated how a large-scale systems biology experiment (toxicity phenotyping and genetic mapping) can aid translation to public health protection. It provided novel information about global inter-individual variability. The availability of the genetically-diverse, genetically-defined renewable human cell lines opens an opportunity for in vitro toxicity testing at the population scale. Our heritability estimates show that variation may have a profound effect on differences between cell lines, and can be quantified and used to generate testable hypotheses about mechanisms of toxicity.

As a followup to these experiments, we also began exploring the potential and efficiency of our population in vitro model in assessing new challenges such as the evaluation of environmental chemical mixtures, and the extrapolation of the in vitro hazard to an oral equivalent dose (Abdo et al. 2014). We used 146 lymphoblast cell lines from 4 ancestrally and geographically diverse populations and exposed them to two pesticide mixtures at 8 concentrations to evaluate cytotoxicity. Multivariate genome-wide association mapping revealed an association between the current use-pesticide mixture and several polymorphism. Moreover, genetic pathway analysis showed a significant association between metabolism pathways and the cytotoxicity of the chlorinated pesticide mixture. By combining this data with reverse toxicokinetics information on the pesticides in the mixture, we demonstrated how an efficient in vitro experimental design may incorporate population variability and comparative population genomics to enable the quantification of human health hazard in the most sensitive individuals to environmental mixtures.

We also are collaborating on a highly multiplexed targeted sequencing assay, which is a highly cost-effective means for collecting gene expression data through next-generation sequencing. In addition, we continued our collaboration with Molecular Devices and Cellular Dynamics who are world leaders in high-content/high-throughput cellular imaging and induced pluripotent stem cell (iPSC)-based in vitro models, respectively. In addition to our previous studies in human iPSC-derived hepatocytes and cardiomyocytes, we conducted experiments in iPSC-derived neuronal cultures with model neurotoxic compounds, and in iPSC-derived cardiomyocytes with complex composition petroleum substances.

In Specific Objective 2, our goal is to provide the computational toxicology solutions for risk characterization in NexGen assessments with a focus on point-of-departure and population variability. First, we are developing computational solutions for estimation of the population variability in toxicity. Our cytotoxicity data in a population model enabled NIEHS-NCATS-UNC Toxicogenetics Challenge (http://dx.doi.org/10.7303/syn1761567) aimed to predict: (1) inter-individual variability of cytotoxicity from genomic profiles, and (2) population-level cytotoxicity from structural attributes of compounds. The NIEHS-NCATS-UNC Toxicogenetics Challenge attracted a “crowd” of ~250 researchers who used these data to elucidate the extent to which adverse effects of compounds can be inferred from genomic and/or chemical structure data. There were 99 models submitted by 35 teams for sub-challenge 1, and 85 models by 23 teams for sub-challenge 2.

Second, we are developing computational solutions for organ-specific toxicity using iPSCs. We continued our work on data integration across various in vitro and in vivo parameters through the use of ToxPi software developed in collaboration with U.S. EPA/NCCT with funding from STAR RD83382501 (Reif, et al. 2013). We sought to utilize ToxPi software and graphical user interface to aggregate and visualize a diverse database of information that was assembled in support of a category read across submission under REACH (Wilson, et al. 2015). We chose a case study of P-series glycol ethers which are typically formed by combining propylene oxide (PO) with a C1- C4 primary alcohol (ex. methanol, ethanol, n-propanol, n-butanol) and a base catalyst to produce a mixture of mono-, di-, tri-, and higher propylene glycol ethers. We found overall that the glycol ethers group together within their structure-based category. ToxPi allows for data incorporation, differential weighing, relative ranking based on the input, and step retention to maximize working transparency. This is accomplished while encouraging a multidisciplinary framework, criteria and guidance to maximize flexibility of the application and further facilitate effective communication of complex data into relevant presentation.

Third, we are developing computational solutions for estimation of the point-of-departure. In response to the need to develop default approaches to support risk estimation for chemicals lacking chemical-specific information, we are developing the Conditional Toxicity Value (CTV) Predictor in collaboration with EPA/NCEA (Wignall, et al. 2013). This project aims to address the challenge of creating an approach to support risk estimation for chemicals lacking chemical-specific information. CTV tool uses chemical properties and limited experimental data to predict toxicity values (such as the oral slope factor, inhalation unit risk, reference dose and concentration), as well as points of departure. The approach combines QSAR and regression modeling, and incorporates OECD principles for model building and external cross-validation. In the past year, we have focused our attention on developing a web-based CTV predictor that would enable easy interface to use our models.

Finally, we are developing computational solutions for cloud-based development of human health assessments of chemicals. We actively continued developing HAWC (Health Assessment Workspace Collaborative, https://hawcproject.org/), a modular, cloud-ready, informatics-based system to synthesize multiple data and information. By including both a web-based workspace for assessment teams who can collaborate on the same assessment rather than share files and edits, and a complementary web-based portal for reviewers and stakeholders, all interested parties have dynamic access to completed and ongoing assessments.

In Specific Objective 3, we develop cheminformatics-based, as well as enhanced chemical-biological, models of in vivo reproductive and developmental toxicity that rely on concomitant exploration of chemical descriptors and population-based screening data. Studies on the thyroid hormone receptor (THR) have been completed and published (Politi, et al. 2014). Models developed in this study can be employed either to identify environmental chemicals interacting with the THR or, conversely, to eliminate the THR-mediated mechanism of action for chemicals of concern. In addition, we were actively participating in the EPA/NCCT-driven effort to build a computational predictor of ER activity through EPA/NCCT-led CERAPP-Collaborative Estrogen Receptor Activity Prediction Project. CERAPP is a demonstration project for how predictive computational models and HTS data can be combined to prioritize a large chemical universe for one specific molecular target – the estrogen receptor. The models are developed in collaboration with 16 groups in the United States and Europe using common set of chemical structures divided into training set and a prediction set of ~32k compounds.

Future Activities:

In Specific Objective 1, we will finalize the analysis of the lymphoblast screening with pesticide mixtures and incorporate high-throughput genomics data into the analyses, and further explore the utility of iPSC models for population-based high-content/high-throughput screening by developing additional collaborations with Cellular Dynamics who are establishing iPSCs from hundreds of individuals with sequenced genomes. In Specific Objective 2, we will finish development of chemical structure- and biological data-based CTV, and continue development of HAWC in collaboration with end users. In Specific Objective 3, we will finalize our work with CERAPP collaborative.

References:

Abdo N, Marlot P, Pirmohamed M, Shea D, Wright FA, Rusyn I. 2014. Utilizing human population based in vitro model to investigate pesticide mixtures and drug/metabolite pairs. In: Society of Toxicology Annual Meeting. Phoenix, AZ.

Abdo N, Xia M, Brown CC, Kosyk O, Huang R, Sakamuru S, et al. 2015. Population-based in vitro hazard and concentration-response assessment of chemicals: The 1000 genomes high throughput screening study. Environ Health Perspect:(in press).

Grimm FA, Iwata Y, Sirenko O, Crittenden C, Roy T, Boogaard PJ, et al. 2015. Toxicological categorization of petroleum substances through high-content screening of induced pluripotent stem cell (ipsc) derived cardiomyocytes and hepatocytes In: Annual Meeting of the Society of Toxicology. San Diego, CA.

Politi R, Rusyn I, Tropsha A. 2014. Prediction of binding affinity and efficacy of thyroid hormone receptor ligands using qsar and structure-based modeling methods. Toxicol Appl Pharmacol 280:177-189.

Reif DM, Sypa M, Lock EF, Wright FA, Wilson A, Cathey T, et al. 2013. Toxpi gui: An interactive visualization tool for transparent integration of data from diverse sources of evidence. Bioinformatics 29:402-403.

Shapiro AJ, Cook N, Ross PK, Fox J, Cogliano V, Chiu WA, et al. 2013. Web-based benchmark dose modeling module as a prototype component of an informatics-based system for human health assessments of chemicals. In: Society of Toxicology Annual Meeting. San Antonio, TX.

Sirenko O, Crittenden C, Callamaras N, Hesley J, Chen YW, Funes C, et al. 2013a. Multiparameter in vitro assessment of compound effects on cardiomyocyte physiology using ipsc cells. J Biomol Screen 18:39-53.

Sirenko O, Cromwell EF, Crittenden C, Wignall JA, Wright FA, Rusyn I. 2013b. Assessment of beating parameters in human induced pluripotent stem cells enables quantitative in vitro screening for cardiotoxicity. Toxicol Appl Pharmacol 273:500-507.

Sirenko O, Hesley J, Rusyn I, Cromwell EF. 2014. High-content assays for hepatotoxicity using induced pluripotent stem cell-derived cells. Assay Drug Dev Technol 12:43-54.

Sirenko O, Hesley J, Rusyn I, Cromwell EF. 2015. High-content high-throughput assays for characterizing the viability and morphology of human ipsc-derived neuronal cultures. Assay Drug Dev Technol:in press.

Wignall JA, Muratov E, Fourches D, Tropsha A, Woodruff T, Zeise L, et al. 2013. Conditional toxicity value (ctv) predictor for generating toxicity values for data-sparse chemicals. In: Society of Toxicology Annual Meeting. San Antonio, TX.

Wilson MR, Ball N, Carney EW, Rowlands JC, Rusyn I. 2015. Data integration and visualization for transparent communication of the category read across using toxpi (toxicological priority index) tool: P-series glycol ethers case study. In: Annual Meeting of the Society of Toxicology. San Diego, CA.

World Health Organization. 2014. Guidance document on evaluating and expressing uncertainty in hazard characterization. Harmonization document no. 11. Geneva, Switzerland.

Yeakley J, Abdo N, Chappell G, Shepard P, Rusyn I, Seligmann B. 2015. A cost effective targeted sequencing method for monitoring gene expression. In: Annual Meeting of the Society of Toxicology. San Diego, CA.

Journal Articles on this Report : 8 Displayed | Download in RIS Format

Publications Views
Other project views:	All 55 publications	41 publications in selected types	All 41 journal articles

Publications
Type	Citation	Project	Document Sources
Journal Article	Abdo N, Xia M, Brown CC, Kosyk O, Huang R, Sakamuru S, Zhou YH, Jack JR, Gallins P, Xia K, Li Y, Chiu WA, Motsinger-Reif AA, Austin CP, Tice RR, Rusyn I, Wright FA. Population-based in vitro hazard and concentration-response assessment of chemicals: the 1000 genomes high-throughput screening study. Environmental Health Perspectives 2015;123(5):458-466.	R835166 (2014) R835166 (2015) R835166 (2016) R835166 (Final)	Full-text from PubMed Abstract from PubMed Associated PubMed link Full-text: EHP-Full Text PDF Abstract: EHP-Abstract and Full Text HTML
Journal Article	Low YS, Sedykh AY, Rusyn I, Tropsha A. Integrative approaches for predicting in vivo effects of chemicals from their structural descriptors and the results of short-term biological assays. Current Topics in Medicinal Chemistry 2014;14(11):1356-1364.	R835166 (2014) R835166 (2016) R835166 (Final) R832720 (2009) R833825 (Final) R834999 (Final)	Full-text from PubMed Abstract from PubMed Associated PubMed link Abstract: Bentham Science-Abstract Exit
Journal Article	Politi R, Rusyn I, Tropsha A. Prediction of binding affinity and efficacy of thyroid hormone receptor ligands using QSAR and structure-based modeling methods. Toxicology and Applied Pharmacology 2014;280(1):177-189.	R835166 (2014) R835166 (2016) R835166 (Final) R833825 (Final)	Full-text from PubMed Abstract from PubMed Associated PubMed link Full-text: ScienceDirect-Full Text HTML Exit Abstract: ScienceDirect-Abstract Exit Other: ScienceDirect-Full Text PDF Exit
Journal Article	Rusyn I, Lemon SM. Mechanisms of HCV-induced liver cancer: what did we learn from in vitro and animal studies? Cancer Letters 2014;345(2):210-215.	R835166 (2014) R835166 (2016)	Full-text from PubMed Abstract from PubMed Associated PubMed link Full-text: Cancer Letters-Full Text PDF Exit Abstract: Cancer Letters-Abstract and Full Text HTML Exit
Journal Article	Sirenko O, Cromwell EF, Crittenden C, Wignall JA, Wright FA, Rusyn I. Assessment of beating parameters in human induced pluripotent stem cells enables quantitative in vitro screening for cardiotoxicity. Toxicology and Applied Pharmacology 2013;273(3):500-507.	R835166 (2013) R835166 (2014) R835166 (2016) R835166 (Final)	Full-text from PubMed Abstract from PubMed Associated PubMed link Full-text: ScienceDirect-Full Text HTML Exit Abstract: ScienceDirect-Abstract Exit Other: ScienceDirect-Full Text PDF Exit
Journal Article	Sirenko O, Hesley J, Rusyn I, Cromwell EF. High-content assays for hepatotoxicity using induced pluripotent stem cell-derived cells. Assay and Drug Development Technologies 2014;12(1):43-54.	R835166 (2013) R835166 (2014) R835166 (2016) R835166 (Final)	Full-text from PubMed Abstract from PubMed Associated PubMed link Abstract: Liebert-Abstract Exit
Journal Article	Sirenko O, Hesley J, Rusyn I, Cromwell E. High-content high-throughput assays for characterizing the viability and morphology of human iPSC-derived neuronal cultures. Assay and Drug Development Technologies 2014;12(9-10):536-547.	R835166 (2014) R835166 (2016) R835166 (Final)	Full-text from PubMed Abstract from PubMed Associated PubMed link Full-text: Mary Ann Liebert-Full Text HTML Exit Abstract: Mary Ann Liebert-Abstract Exit Other: Mary Ann Liebert-Full Text PDF Exit
Journal Article	Wignall JA, Shapiro AJ, Wright FA, Woodruff TJ, Chiu WA, Guyton KZ, Rusyn I. Standardizing benchmark dose calculations to improve science-based decisions in human health assessments. Environmental Health Perspectives 2014;122(5):499-505.	R835166 (2013) R835166 (2014) R835166 (2016) R835166 (Final)	Full-text from PubMed Abstract from PubMed Associated PubMed link Full-text: EHP-Full Text PDF Abstract: EHP-Abstract and Full Text HTML

Supplemental Keywords:

Bioinformatics, biostatistics, computational toxicology, QSAR, ToxCast, high throughput screening

Progress and Final Reports:

Original Abstract

The 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.