Grantee Research Project Results
2013 Progress Report: Carolina Center for Computational Toxicology: Assays, models and tools for NextGen safety assessments
EPA Grant Number: R835166Title: 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 , North Carolina State University
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, 2012 through September 30,2013
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 have been following up on the success of our collaboration with NCATS and NIEHS/NTP in which we successfully screened 1,086 human lymphoblast cell lines, representing 9 populations from 5 continents, in a cell viability assay with 179 diverse environmental chemicals at 8 concentrations (Abdo, et al. 2012; Abdo, et al. 2013). A follow-up study (Abdo, et al. 2014) was designed to address two limitations of a lymphoblast-based in vitro screening model: restricted metabolic capacity of lymphoblasts and the potential to screen complex mixtures. We screened two environmental pesticide mixtures (organochlorine pesticide environmental mixture extracted from a passive surface water sampling device, or a mixture of 36 currently used pesticides) and drug/metabolite pairs (Carbamazepine, Sulfamethoxazole, or two major metabolites of each drug). These data provide the opportunity to establish population-based confidence intervals in cytotoxicity, as well as probe candidate susceptibility pathways. In addition, as an alternative way of addressing the limitations of lymphoblast cells with regards to metabolism and target-specific toxicity, we collaborated with Molecular Devices and Cellular Dynamics, companies that are world leaders in high-content/high throughput cellular imaging and induced pluripotent stem cell (iPSC)-based in vitro models, respectively. In these studies (Sirenko, et al. 2013a; Sirenko, et al. 2013b; Sirenko, et al. 2013c), we used iPSC-derived hepatocytes and cardiomyocytes to screen large (100+) libraries of chemicals and determined how the multi-parametric assessment of concentration response toxicity phenotypes can be used to make hazard-based rankings.
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 by utilizing the power of the 1000 Genomes Toxicity Screening data (Abdo, et al. 2012; Abdo, et al. 2013). Specifically, we partnered with Sage Bionetworks (Seattle, WA) to use this data for one of DREAM (Dialogue for Reverse Engineering Assessments & Methods) Challenges. In sub-challenge 1, the participants were asked to predict inter-individual variability in in vitro cytotoxicity based on genomic profiles of individual cell lines. For each compound, participants were challenged to predict the absolute values and relative ranks of cytotoxicity across a set of unknown cell lines for which genomic data is available. For sub-challenge 2, the task was for each compound, predict the concentration at which median cytotoxicity would occur, as well as inter-individual variation in cytotoxicity, described by the 5-95th percentile range, across the population. Each prediction was scored based on the participant’s ability to predict these two parameters within a set of compounds excluded from the training set. 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. Final announcement of the winners of the challenges will be made at the 2013 DREAM conference that will held on November 8-12 in Toronto, Canada, in conjunction with the RECOMB/ISCB Conference on Regulatory and Systems Genomics.
Future Activities:
In Specific Objective 1, we will finalize the analysis of the 1000 Genomes Project screening; finalize the analysis of the population-wide experiment with mixtures and drug/metabolite pairs; 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.
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 : 6 Displayed | Download in RIS Format
Other project views: | All 54 publications | 40 publications in selected types | All 40 journal articles |
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Low Y, Sedykh A, Fourches D, Golbraikh A, Whelan M, Rusyn I, Tropsha A. Integrative chemical-biological read-across approach for chemical hazard classification. Chemical Research in Toxicology 2013;26(8):1199-1208. |
R835166 (2013) R835166 (2016) R835166 (Final) |
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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) |
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Sirenko O, Crittenden C, Callamaras N, Hesley J, Chen YW, Funes C, Rusyn I, Anson B, Cromwell EF. Multiparameter in vitro assessment of compound effects on cardiomyocyte physiology using iPSC cells. Journal of Biomolecular Screening 2013;18(1):39-53. |
R835166 (2013) R835166 (2016) R835166 (Final) |
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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) |
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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) |
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Zhang L, Sedykh A, Tripathi A, Zhu H, Afantitis A, Mouchlis VD, Melagraki G, Rusyn I, Tropsha A. Identification of putative estrogen receptor-mediated endocrine disrupting chemicals using QSAR- and structure-based virtual screening approaches. Toxicology and Applied Pharmacology 2013;272(1):67-76. |
R835166 (2013) R835166 (Final) R833825 (Final) |
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Supplemental Keywords:
Bioinformatics, biostatistics, computational toxicology, QSAR, ToxCast, high throughput screeningProgress 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.