Computational Toxicology: New Approaches for the 21st Century September 9 th , 2009 Session IV: ToxCast and the Comparative Toxicogenomics Database (CTD) David Dix, Acting Deputy Director of EPA/ORD’s National Center for Computational Toxicology Carolyn Mattingly, Mount Desert Island Biological Laboratory 1 September 9, 2009 1
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Computational Toxicology: New Approaches for the 21st Century
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Computational Toxicology: New Approaches for the 21st Century
September 9th, 2009 Session IV: ToxCast and the Comparative ToxicogenomicsDatabase (CTD)
David Dix, Acting Deputy Director of EPA/ORD’s National Center for Computational Toxicology
Carolyn Mattingly, Mount Desert Island Biological Laboratory
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September 9, 2009
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David DixActing Deputy Director, EPAs National Center for Computational Toxicology
ToxCast- Screening and Prioritization of Environmental Chemicals Based on Bioactivity Profiling and Predictions of Toxicity
NIEHS Risk e Learning Sept 9, 2009
Office of Research and DevelopmentNational Center for Computational Toxicology
This work was reviewed by EPA and approved for presentation but does not necessarily reflect official Agency policy.
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Office of Research and DevelopmentNational Center for Computational Toxicology
Predicting Toxicity Will Not Be Easy
Chemical
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Office of Research and DevelopmentNational Center for Computational Toxicology
Key Challenges Of Pathway Profiling
•Find the Toxicity Pathways•Hepato vs developmental nuerotoxicity
•Obtain HTS Assays for Them• Including metabolic capability
•Screen Chemical Libraries• Coverage of p-chem properties
•Link Results to in vivo Effects• Gold standard and dosimetry
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Office of Research and DevelopmentNational Center for Computational Toxicology
ToxCastTM Background
• Research program of EPA’s National Center for Computational Toxicology
• Addresses chemical screening and prioritization needs for pesticidal inerts, anti-microbials, CCLs, HPVs and MPVs
• Comprehensive use of HTS technologies
• Coordinated with NTP and NHGRI/NCGC via Tox21
• Committed to stakeholder involvement and public release of data
• Chemical Prioritization Community of Practice
• NCCT website- http://www.epa.gov/ncct/
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Office of Research and DevelopmentNational Center for Computational Toxicology
Office of Research and DevelopmentNational Center for Computational Toxicology
ToxRefDB
• Relational phenotypic/toxicity database
• Provides in vivo anchor for ToxCast predictions
• Three study types• Chronic/Cancer Rat and Mouse (Martin, et al, EHP 2008)
• Rat multigenerational Reproduction (Martin, et al, 2009)
• Rat & Rabbit Developmental Toxicity (Knudsen, et al, 2009)
• Two types of synthesis• Supervised (common individual phenotypes)
• Unsupervised (machine based clustering of phenotype patterns)
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Office of Research and DevelopmentNational Center for Computational Toxicology SOURCE: Matt Martin, NCCT, 2009
A = Rat B = Mouse C = Rabbit
CHRONIC/CANCER (CHR)Martin et al. (2008) Environ Hlth Perspdoi:10.1289/ehp.0800074
PRENATAL DEVELOPMENTAL (DEV)Knudsen et al. (2009) Reprod Toxicoldoi: 10.1016/j.reprotox.2009.03.016
MULTIGENERATION REPRODUCTIVE (MGR)Martin et al. (2009) Toxicol Scidoi: 10.1093/toxsci/kfp080
ToxRefDB Endpoint Coveragedata evaluation records ToxRefDB
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Rat Chronic Bioassay Results
Martin, et al EHP, 2009September 9, 2009 9
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Office of Research and DevelopmentNational Center for Computational Toxicology
Digitizing Legacy in Vivo Data in ToxRefDB
Chronic/CancerMultigenationDevelopmental
Che
mic
als
30 years and more than $2B worth of data
Martin et al 2009a,bKnudsen et al 2009
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Office of Research and DevelopmentNational Center for Computational Toxicology
ToxRefDB in Predictive Modeling
STRENGTHS– Source data from >2,000 guideline studies– Puts >$2B worth of legacy data into a computable form– in vivo database anchoring HTS in vitro assays– Enables comparison of endpoint incidence between species– Searchable database will be public (www.epa.gov/ncct/toxrefdb/)
LIMITATIONS– Endpoints aggregated as independent features– Data largely qualitative (LELs, LOAELS)– Not all ToxCast™ chemicals represented in ToxRefDB– Not all ToxRefDB chemicals represented in ToxCast™– Species dimorphism may link to biology or study design–Limited mode of action information available in source DERs
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Office of Research and DevelopmentNational Center for Computational Toxicology
ToxCast Assays
• Cell lines– HepG2 human hepatoblastoma– A549 human lung carcinoma– HEK 293 human embryonic kidney
• Primary cells– Human endothelial cells– Human monocytes– Human keratinocytes– Human fibroblasts– Human proximal tubule kidney cells– Human small airway epithelial cells
• Biotransformation competent cells– Primary rat hepatocytes– Primary human hepatocytes
Office of Research and DevelopmentNational Center for Computational Toxicology
Phase II Plans• Done in conjunction with Tox21 10k Library
–Subset of 700 will seed Phase II• Chemical Diversity
–More food use pesticides –Failed pharmaceuticals (preclinical and clinical)– “Green” chemicals–HPV Categories–Liver toxicants –OECD Molecular Screening Group nominations
• Evaluation of Phase I Assays• Addition of new assays via competitive procurements• Timing
–Chemical procurement completed 4thQ FY09–Launch of Assays, 1st Q FY10–Results Available early FY11
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Carolyn J. MattinglyThe Mount Desert Island Biological Laboratory
Salisbury Cove, Maine
The Comparative Toxicogenomics Database (CTD)
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Helping scientists explore the etiologies of environmental diseases
• What diseases are associated with arsenic?
• Arsenic affects which genes and proteins?
• What biological processes are affected by arsenic?
• Which molecular pathways are affected by arsenic?
• Which other chemicals affect the same molecular pathways?
• Which diseases are implicated with other chemicals?
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DiseasesGenes
Chemicals
Curated Data
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DiseasesGenes
Chemicals
chemical-diseaserelationships
chemical-diseaserelationships
chemical-geneinteractions
chemical-geneinteractions
gene-diseaserelationships
gene-diseaserelationships
Curated Data
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DiseasesGenes
Chemicals
Curated Data
MeSH (modified)
Entrez-Gene MeSH/OMIM
CTD interactions
chemical-diseaserelationships
chemical-diseaserelationships
chemical-geneinteractions
chemical-geneinteractions
gene-diseaserelationships
gene-diseaserelationships
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DiseasesGenes
Chemicals
chemical-diseaserelationships
chemical-diseaserelationships
chemical-geneinteractions
chemical-geneinteractions
gene-diseaserelationships
gene-diseaserelationships
181,150
9,179
5,757
Curated Data
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Arsenates
HMOX1 AlzheimerDisease
HMOX1
Inferred chemical-disease relationships
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Arsenates
HMOX1 AlzheimerDisease
HMOX1
Inferred chemical-disease relationships
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Chem/Gene Comps
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Tools
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Tools
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Tools
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Tools: VennViewer
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Tools: VennViewerInteracting Genes/Proteins
Pathways
127 1357118
Folic acid Arsenicals
4 7621
Folic acid Arsenicals
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Tools
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Tools: MyGeneVenn
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0 10 100
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0 10 100
64 168920
Array data CTD data
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0 10 100
64 168920
Array data CTD data
Mattingly, C. J., T. Hampton, K. Brothers, N. E. Griffin and A. J. Planchart (2009). Perturbation of defense pathways by low-dose arsenic exposure in zebrafish embryos. Environ Health Perspect doi:10.1289/ehp.0900555.
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Gohlke, J., R. Thomas, Y. Zhang, M. D. Rosenstein, A. P. Davis, C. Murphy, C. J. Mattingly, K. G. Becker and C. J. Portier (2009). The Genetic And Environmental Pathways to Complex Diseases. BMC Syst Biol.May 5 3:46.
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2096Chemicals
213Genes
213Genes Autism
Environmental etiology of autistic disorders
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2096Chemicals
213Genes
213Genes Autism
Environmental etiology of autistic disorders
• What do these chemicals have in common?
– Structure
– Regulatory features(e.g., High production, Carcinogen)
– Function(e.g., Associated pathways)
– Other associated diseases(e.g., Neurological)
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Next
• Analysis tools and visualization capabilities
• Integration of additional data sets
• Text mining
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• Gohlke, J., R. Thomas, Y. Zhang, M. D. Rosenstein, A. P. Davis, C. Murphy, C. J. Mattingly, K. G. Becker and C. J. Portier (2009). The Genetic And Environmental Pathways to Complex Diseases. BMC Syst Biol.May 5 3:46.
• Mattingly, C. J., T. Hampton, K. Brothers, N. E. Griffin and A. J. Planchart (2009). Perturbation of defense pathways by low-dose arsenic exposure in zebrafish embryos. Environ Health Perspect doi:10.1289/ehp.0900555.
• Davis, A. P., C. G. Murphy, C. A. Saraceni-Richards, M. C. Rosenstein, T. C. Wiegersand C. J. Mattingly (2009). Comparative Toxicogenomics Database: a knowledgebase and discovery tool for chemical-gene-disease networks. Nucleic Acids Res 37(Database issue): D786-92.
• Mattingly, C. J. (2009). Chemical databases for environmental health and clinical research. Toxicol Lett. 186(1):62-5.
• Davis, A. P., C. G. Murphy, M. C. Rosenstein, T. C. Wiegers and C. J. Mattingly (2008). The Comparative Toxicogenomics Database facilitates identification and understanding of chemical-gene-disease associations: arsenic as a case study. BMC Med Genomics 1: 48.
Recent CTD references
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AcknowledgementsScientific Curators
Allan Peter Davis, PhDCindy Murphy, PhDCynthia Richards, PhD
Scientific Software Engineers
Michael C Rosenstein, JDThomas Wiegers
System Administrator
Roy McMorran
James L. Boyer, MD (Yale)
Thomas Hampton (Dartmouth)
http://ctd.mdibl.org/
Zebrafish workAntonio Planchart, PhD
Funding
NIEHS and NLM (ES014065 and ES003828)NCRR (RR016463)Contact Us!