BioInformatic Resources at the Environmental Protection Agency: Tools and Webinars on Toxicity Prediction

Curator Stephen J. Williams Ph.D.

New GenRA Module in EPA’s CompTox Dashboard Will Help Predict Potential Chemical Toxicity

Published September 25, 2018

As part of its ongoing computational toxicology research, EPA is developing faster and improved approaches to evaluate chemicals for potential health effects.  One commonly applied approach is known as chemical read-across. Read-across uses information about how a chemical with known data behaves to make a prediction about the behavior of another chemical that is “similar” but does not have as much data. Current read-across, while cost-effective, relies on a subjective assessment, which leads to varying predictions and justifications depending on who undertakes and evaluates the assessment.

To reduce uncertainties and develop a more objective approach, EPA researchers have developed an automated read-across tool called Generalized Read-Across (GenRA), and added it to the newest version of the EPA Computational Toxicology Dashboard. The goal of GenRA is to encode as many expert considerations used within current read-across approaches as possible and combine these with data-driven approaches to transition read-across towards a more systematic and data-based method of making predictions.

EPA chemist Dr. Grace Patlewicz says it was this uncertainty that motivated the development of GenRA. “You don’t actually know if you’ve been successful at using read-across to help predict chemical toxicity because it’s a judgement call based on one person versus the next. That subjectivity is something we were trying to move away from.” Patlewicz says.

Since toxicologists and risk assessors are already familiar with read-across, EPA researchers saw value in creating a tool that that was aligned with the current read-across workflow but which addressed uncertainty using data analysis methods in what they call a “harmonized-hybrid workflow.”

In its current form, GenRA lets users find analogues, or chemicals that are similar to their target chemical, based on chemical structural similarity. The user can then select which analogues they want to carry forward into the GenRA prediction by exploring the consistency and concordance of the underlying experimental data for those analogues. Next, the tool predicts toxicity effects of specific repeated dose studies. Then, a plot with these outcomes is generated based on a similarity-weighted activity of the analogue chemicals the user selected. Finally, the user is presented with a data matrix view showing whether a chemical is predicted to be toxic (yes or no) for a chosen set of toxicity endpoints, with a quantitative measure of uncertainty.

The team is also comparing chemicals based on other similarity contexts, such as physicochemical characteristics or metabolic similarity, as well as extending the approach to make quantitative predictions of toxicity.

Patlewicz thinks incorporating other contexts and similarity measures will refine GenRA to make better toxicity predictions, fulfilling the goal of creating a read-across method capable of assessing thousands of chemicals that currently lack toxicity data.

“That’s the direction that we’re going in,” Patlewicz says. “Recognizing where we are and trying to move towards something a little bit more objective, showing how aspects of the current read-across workflow could be refined.”

Learn more at: https://comptox.epa.gov

A listing of EPA Tools for Air Quality Assessment

Tools

• Atmospheric Model Evaluation Tool (AMET)
  AMET helps in the evaluation of meteorological and air quality simulations.
• Benchmark Dose Software (BMDS)
  EPA developed the Benchmark Dose Software (BMDS) as a tool to help estimate dose or exposure of a chemical or chemical mixture associated with a given response level. The methodology is used by EPA risk assessors and is fast becoming the world’s standard for dose-response analysis for risk assessments, including air pollution risk assessments.
• BenMAP
  BenMAP is a Windows-based computer program that uses a Geographic Information System (GIS)-based to estimate the health impacts and economic benefits occurring when populations experience changes in air quality.
• Community-Focused Exposure and Risk Screening Tool (C-FERST)
  C-FERST is an online tool developed by EPA in collaboration with stakeholders to provide access to resources that can be used with communities to help identify and learn more about their environmental health issues and explore exposure and risk reduction options.
• Community Health Vulnerability Index
  EPA scientists developed a Community Health Vulnerability Index that can be used to help identify communities at higher health risk from wildfire smoke. Breathing smoke from a nearby wildfire is a health threat, especially for people with lung or heart disease, diabetes and high blood pressure as well as older adults, and those living in communities with poverty, unemployment and other indicators of social stress. Health officials can use the tool, in combination with air quality models, to focus public health strategies on vulnerable populations living in areas where air quality is impaired, either by wildfire smoke or other sources of pollution. The work was published in Environmental Science & Technology.
• Critical Loads Mapper Tool
  The Critical Loads Mapper Tool can be used to help protect terrestrial and aquatic ecosystems from atmospheric deposition of nitrogen and sulfur, two pollutants emitted from fossil fuel burning and agricultural emissions. The interactive tool provides easy access to information on deposition levels through time; critical loads, which identify thresholds when pollutants have reached harmful levels; and exceedances of these thresholds.
• EnviroAtlas
  EnviroAtlas provides interactive tools and resources for exploring the benefits people receive from nature or “ecosystem goods and services”. Ecosystem goods and services are critically important to human health and well-being, but they are often overlooked due to lack of information. Using EnviroAtlas, many types of users can access, view, and analyze diverse information to better understand the potential impacts of various decisions.
• EPA Air Sensor Toolbox for Citizen Scientists
  EPA’s Air Sensor Toolbox for Citizen Scientists provides information and guidance on new low-cost compact technologies for measuring air quality. Citizens are interested in learning more about local air quality where they live, work and play. EPA’s Toolbox includes information about: Sampling methodologies; Calibration and validation approaches; Measurement methods options; Data interpretation guidelines; Education and outreach; and Low cost sensor performance information.
• ExpoFIRST
  The Exposure Factors Interactive Resource for Scenarios Tool (ExpoFIRST) brings data from EPA’s Exposure Factors Handbook: 2011 Edition (EFH) to an interactive tool that maximizes flexibility and transparency for exposure assessors. ExpoFIRST represents a significant advance for regional, state, and local scientists in performing and documenting calculations for community and site-specific exposure assessments, including air pollution exposure assessments.
• EXPOsure toolbox (ExpoBox)
  This is a toolbox created to assist individuals from within government, industry, academia, and the general public with assessing exposure, including exposure to air contaminants, fate and transport processes of air pollutants and their potential exposure concentrations. It is a compendium of exposure assessment tools that links to guidance documents, databases, models, reference materials, and other related resources.
• Federal Reference & Federal Equivalency Methods
  EPA scientists develop and evaluate Federal Reference Methods and Federal Equivalency Methods for accurately and reliably measuring six primary air pollutants in outdoor air. These methods are used by states and other organizations to assess implementation actions needed to attain National Ambient Air Quality Standards.
• Fertilizer Emission Scenario Tool for CMAQ (FEST-C)
  FEST-C facilitates the definition and simulation of new cropland farm management system scenarios or editing of existing scenarios to drive Environmental Policy Integrated Climate model (EPIC) simulations.  For the standard 12km continental Community Multi-Scale Air Quality model (CMAQ) domain, this amounts to about 250,000 simulations for the U.S. alone. It also produces gridded daily EPIC weather input files from existing hourly Meteorology-Chemistry Interface Processor (MCIP) files, transforms EPIC output files to CMAQ-ready input files and links directly to Visual Environment for Rich Data Interpretation (VERDI) for spatial visualization of input and output files. The December 2012 release will perform all these functions for any CMAQ grid scale or domain.
• Instruction Guide and Macro Analysis Tool for Community-led Air Monitoring 
  EPA has developed two tools for evaluating the performance of low-cost sensors and interpreting the data they collect to help citizen scientists, communities, and professionals learn about local air quality.
• Integrated Climate and Land use Scenarios (ICLUS)
  Climate change and land-use change are global drivers of environmental change. Impact assessments frequently show that interactions between climate and land-use changes can create serious challenges for aquatic ecosystems, water quality, and air quality. Population projections to 2100 were used to model the distribution of new housing across the landscape. In addition, housing density was used to estimate changes in impervious surface cover.  A final report, datasets, the ICLUS+ Web Viewer and ArcGIS tools are available.
• Indoor Semi-Volatile Organic Compound (i-SVOC)
  i-SVOC Version 1.0 is a general-purpose software application for dynamic modeling of the emission, transport, sorption, and distribution of semi-volatile organic compounds (SVOCs) in indoor environments. i-SVOC supports a variety of uses, including exposure assessment and the evaluation of mitigation options. SVOCs are a diverse group of organic chemicals that can be found in: Many are also present in indoor air, where they tend to bind to interior surfaces and particulate matter (dust).
  • Pesticides;
  • Ingredients in cleaning agents and personal care products;
  • Additives to vinyl flooring, furniture, clothing, cookware, food packaging, and electronics.
• Municipal Solid Waste Decision Support Tool (MSW DST)EXIT
  This tool is designed to aid solid waste planners in evaluating the cost and environmental aspects of integrated municipal solid waste management strategies. The tool is the result of collaboration between EPA and RTI International and its partners.
• Optical Noise-Reduction Averaging (ONA) Program Improves Black Carbon Particle Measurements Using Aethalometers
  ONA is a program that reduces noise in real-time black carbon data obtained using Aethalometers. Aethalometers optically measure the concentration of light absorbing or “black” particles that accumulate on a filter as air flows through it. These particles are produced by incomplete fossil fuel, biofuel and biomass combustion. Under polluted conditions, they appear as smoke or haze.
• RETIGO tool
  Real Time Geospatial Data Viewer (RETIGO) is a free, web-based tool that shows air quality data that are collected while in motion (walking, biking or in a vehicle). The tool helps users overcome technical barriers to exploring air quality data. After collecting measurements, citizen scientists and other users can import their own data and explore the data on a map.
• Remote Sensing Information Gateway (RSIG)
  RSIG offers a new way for users to get the multi-terabyte, environmental datasets they want via an interactive, Web browser-based application. A file download and parsing process that now takes months will be reduced via RSIG to minutes.
• Simulation Tool Kit for Indoor Air Quality and Inhalation Exposure (IAQX)
  IAQX version 1.1 is an indoor air quality (IAQ) simulation software package that complements and supplements existing indoor air quality simulation (IAQ) programs. IAQX is for advanced users who have experience with exposure estimation, pollution control, risk assessment, and risk management. There are many sources of indoor air pollution, such as building materials, furnishings, and chemical cleaners. Since most people spend a large portion of their time indoors, it is important to be able to estimate exposure to these pollutants. IAQX helps users analyze the impact of pollutant sources and sinks, ventilation, and air cleaners. It performs conventional IAQ simulations to calculate the pollutant concentration and/or personal exposure as a function of time. It can also estimate adequate ventilation rates based on user-provided air quality criteria. This is a unique feature useful for product stewardship and risk management.
• Spatial Allocator
  The Spatial Allocator provides tools that could be used by the air quality modeling community to perform commonly needed spatial tasks without requiring the use of a commercial Geographic Information System (GIS).
• Traceability Protocol for Assay and Certification of Gaseous Calibration Standards
  This is used to certify calibration gases for ambient and continuous emission monitors. It specifies methods for assaying gases and establishing traceability to National Institute of Standards and Technology (NIST) reference standards. Traceability is required under EPA ambient and continuous emission monitoring regulations.
• Watershed Deposition Mapping Tool (WDT)
  WDT provides an easy to use tool for mapping the deposition estimates from CMAQ to watersheds to provide the linkage of air and water needed for TMDL (Total Maximum Daily Load) and related nonpoint-source watershed analyses.
• Visual Environment for Rich Data Interpretation (VERDI)
  VERDI is a flexible, modular, Java-based program for visualizing multivariate gridded meteorology, emissions, and air quality modeling data created by environmental modeling systems such as CMAQ and the Weather Research and Forecasting (WRF) model.

Databases

• Air Quality Data for the CDC National Environmental Public Health Tracking Network 
  EPA’s Exposure Research scientists are collaborating with the Centers for Disease Control and Prevention (CDC) on a CDC initiative to build a National Environmental Public Health Tracking (EPHT) network. Working with state, local and federal air pollution and health agencies, the EPHT program is facilitating the collection, integration, analysis, interpretation, and dissemination of data from environmental hazard monitoring, and from human exposure and health effects surveillance. These data provide scientific information to develop surveillance indicators, and to investigate possible relationships between environmental exposures, chronic disease, and other diseases, that can lead to interventions to reduce the burden of theses illnesses. An important part of the initiative is air quality modeling estimates and air quality monitoring data, combined through Bayesian modeling that can be linked with health outcome data.
• EPAUS9R – An Energy Systems Database for use with the Market Allocation (MARKAL) Model
  The EPAUS9r is a regional database representation of the United States energy system. The database uses the MARKAL model. MARKAL is an energy system optimization model used by local and federal governments, national and international communities and academia. EPAUS9r represents energy supply, technology, and demand throughout the major sectors of the U.S. energy system.
• Fused Air Quality Surfaces Using Downscaling
  This database provides access to the most recent O3 and PM2.5 surfaces datasets using downscaling.
• Health & Environmental Research Online (HERO)
  HERO provides access to scientific literature used to support EPA’s integrated science assessments, including the  Integrated Science Assessments (ISA) that feed into the National Ambient Air Quality (NAAQS) reviews.
• SPECIATE 4.5 Database
  SPECIATE is a repository of volatile organic gas and particulate matter (PM) speciation profiles of air pollution sources.

A listing of EPA Tools and Databases for Water Contaminant Exposure Assessment

Exposure and Toxicity

• EPA ExpoBox (A Toolbox for Exposure Assessors)
  This toolbox assists individuals from within government, industry, academia, and the general public with assessing exposure from multiple media, including water and sediment. It is a compendium of exposure assessment tools that links to guidance documents, databases, models, reference materials, and other related resources.

Chemical and Product Categories (CPCat) Database
CPCat is a database containing information mapping more than 43,000 chemicals to a set of terms categorizing their usage or function. The comprehensive list of chemicals with associated categories of chemical and product use was compiled from publically available sources. Unique use category taxonomies from each source are mapped onto a single common set of approximately 800 terms. Users can search for chemicals by chemical name, Chemical Abstracts Registry Number, or by CPCat terms associated with chemicals.

A listing of EPA Tools and Databases for Chemical Toxicity Prediction & Assessment

• Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS)
  SeqAPASS is a fast, online screening tool that allows researchers and regulators to extrapolate toxicity information across species. For some species, such as humans, mice, rats, and zebrafish, the EPA has a large amount of data regarding their toxicological susceptibility to various chemicals. However, the toxicity data for numerous other plants and animals is very limited. SeqAPASS extrapolates from these data rich model organisms to thousands of other non-target species to evaluate their specific potential chemical susceptibility.

• Aggregated Computational Toxicology Resource (ACToR)
  ACToR is an online warehouse of publicly available chemical toxicity data and can be used to find all publicly available data about potential chemical risks to human health and the environment. ACToR aggregates data from over 1000 public sources on over 500,000 environmental chemicals searchable by chemical name, other identifiers and by chemical structure.
• Chemical and Product Category Database
  Contains information on how chemicals are used in consumer products. It includes information mapping over 43,000 chemicals to a set of terms categorizing their usage in consumer products or function.
• Distributed Structure Searchable Toxicity Database (DSSTox)
  Publishes downloadable, structure-searchable, standardized chemical structure files associated with chemical inventories or toxicity data sets of environmental relevance.
• Downloadable Computational Toxicology Data
  All publicly available computational toxicology data.
• Ecotoxicology Database (EcoTox)
  Source for finding single chemical toxicity data for aquatic life, terrestrial plants and wildlife.
• Toxicity Reference Database (ToxRefDB)
  ToxRefDB contains thousands of animal toxicity studies on hundreds of chemicals from 30 years worth of animal toxicity studies.
• Toxicity Forecaster Data (ToxCast)
  ToxCast data includes high-throughput screening data on thousands of chemicals.

A listing of EPA Webinar and Literature on Bioinformatic Tools and Projects

Comparative Bioinformatics Applications for Developmental Toxicology

Discuss how the US EPA/NCCT is trying to solve the problem of too many chemicals, too high cost, and too much biological uncertainty Discuss the solution the ToxCast Program is proposing; a data-rich system to screen, classify and rank chemicals for further evaluation

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dirEntryId=186844

CHEMOINFORMATIC AND BIOINFORMATIC CHALLENGES AT THE US ENVIRONMENTAL PROTECTION AGENCY.

This presentation will provide an overview of both the scientific program and the regulatory activities related to computational toxicology. This presentation will provide an overview of both the scientific program and the regulatory activities related to computational toxicology.

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dirEntryId=154013

How Can We Use Bioinformatics to Predict Which Agents Will Cause Birth Defects?

The availability of genomic sequences from a growing number of human and model organisms has provided an explosion of data, information, and knowledge regarding biological systems and disease processes. High-throughput technologies such as DNA and protein microarray biochips are now standard tools for probing the cellular state and determining important cellular behaviors at the genomic/proteomic levels. While these newer technologies are beginning to provide important information on cellular reactions to toxicant exposure (toxicogenomics), a major challenge that remains is the formulation of a strategy to integrate transcript, protein, metabolite, and toxicity data. This integration will require new concepts and tools in bioinformatics. The U.S. National Library of Medicine’s Pubmed site includes 19 million citations and abstracts and continues to grow. The BDSM team is now working on assembling the literature’s unstructured data into a structured database and linking it to BDSM within a system that can then be used for testing and generating new hypotheses. This effort will generate data bases of entities (such as genes, proteins, metabolites, gene ontology processes) linked to PubMed identifiers/abstracts and providing information on the relationships between them. The end result will be an online/standalone tool that will help researchers to focus on the papers most relevant to their query and uncover hidden connections and obvious information gaps.

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dirEntryId=227345

ADVANCED PROTEOMICS AND BIOINFORMATICS TOOLS IN TOXICOLOGY RESEARCH: OVERCOMING CHALLENGES TO PROVIDE SIGNIFICANT RESULTS

This presentation specifically addresses the advantages and limitations of state of the art gel, protein arrays and peptide-based labeling proteomic approaches to assess the effects of a suite of model T4 inhibitors on the thyroid axis of Xenopus laevis.

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NHEERL&dirEntryId=152823

Bioinformatic Integration of in vivo Data and Literature-based Gene Associations for Prioritization of Adverse Outcome Pathway Development

Adverse outcome pathways (AOPs) describe a sequence of events, beginning with a molecular initiating event (MIE), proceeding via key events (KEs), and culminating in an adverse outcome (AO). A challenge for use of AOPs in a safety evaluation context has been identification of MIEs and KEs relevant for AOs observed in regulatory toxicity studies. In this work, we implemented a bioinformatic approach that leverages mechanistic information in the literature and the AOs measured in regulatory toxicity studies to prioritize putative MIEs and/or early KEs for AOP development relevant to chemical safety evaluation. The US Environmental Protection Agency Toxicity Reference Database (ToxRefDB, v2.0) contains effect information for >1000 chemicals curated from >5000 studies or summaries from sources including data evaluation records from the US EPA Office of Pesticide Programs, the National Toxicology Program (NTP), peer-reviewed literature, and pharmaceutical preclinical studies. To increase ToxRefDB interoperability, endpoint and effect information were cross-referenced with codes from the United Medical Language System, which enabled mapping of in vivo pathological effects from ToxRefDB to PubMed (via Medical Subject Headings or MeSH). This enabled linkage to any resource that is also connected to PubMed or indexed with MeSH. A publicly available bioinformatic tool, the Entity-MeSH Co-occurrence Network (EMCON), uses multiple data sources and a measure of mutual information to identify genes most related to a MeSH term. Using EMCON, gene sets were generated for endpoints of toxicological relevance in ToxRefDB linking putative KEs and/or MIEs. The Comparative Toxicogenomics Database was used to further filter important associations. As a proof of concept, thyroid-related effects and their highly associated genes were examined, and demonstrated relevant MIEs and early KEs for AOPs to describe thyroid-related AOs. The ToxRefDB to gene mapping for thyroid resulted in >50 unique gene to chemical relationships. Integrated use of EMCON and ToxRefDB data provides a basis for rapid and robust putative AOP development, as well as a novel means to generate mechanistic hypotheses for specific chemicals. This abstract does not necessarily reflect U.S. EPA policy. Abstract and Poster for 2019 Society of Toxicology annual meeting in March 2019

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dirEntryId=344452

Bioinformatic Integration of in vivo Data and Literature-based Gene Associations for Prioritization of Adverse Outcome Pathway Development

Adverse outcome pathways (AOPs) describe a sequence of events, beginning with a molecular initiating event (MIE), proceeding via key events (KEs), and culminating in an adverse outcome (AO). A challenge for use of AOPs in a safety evaluation context has been identification of MIEs and KEs relevant for AOs observed in regulatory toxicity studies. In this work, we implemented a bioinformatic approach that leverages mechanistic information in the literature and the AOs measured in regulatory toxicity studies to prioritize putative MIEs and/or early KEs for AOP development relevant to chemical safety evaluation. The US Environmental Protection Agency Toxicity Reference Database (ToxRefDB, v2.0) contains effect information for >1000 chemicals curated from >5000 studies or summaries from sources including data evaluation records from the US EPA Office of Pesticide Programs, the National Toxicology Program (NTP), peer-reviewed literature, and pharmaceutical preclinical studies. To increase ToxRefDB interoperability, endpoint and effect information were cross-referenced with codes from the United Medical Language System, which enabled mapping of in vivo pathological effects from ToxRefDB to PubMed (via Medical Subject Headings or MeSH). This enabled linkage to any resource that is also connected to PubMed or indexed with MeSH. A publicly available bioinformatic tool, the Entity-MeSH Co-occurrence Network (EMCON), uses multiple data sources and a measure of mutual information to identify genes most related to a MeSH term. Using EMCON, gene sets were generated for endpoints of toxicological relevance in ToxRefDB linking putative KEs and/or MIEs. The Comparative Toxicogenomics Database was used to further filter important associations. As a proof of concept, thyroid-related effects and their highly associated genes were examined, and demonstrated relevant MIEs and early KEs for AOPs to describe thyroid-related AOs. The ToxRefDB to gene mapping for thyroid resulted in >50 unique gene to chemical relationships. Integrated use of EMCON and ToxRefDB data provides a basis for rapid and robust putative AOP development, as well as a novel means to generate mechanistic hypotheses for specific chemicals. This abstract does not necessarily reflect U.S. EPA policy. Abstract and Poster for 2019 Society of Toxicology annual meeting in March 2019

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dateBeginPublishedPresented=03%2F26%2F2014&dateEndPublishedPresented=03%2F26%2F2019&dirEntryId=344452&keyword=Chemical+Safety&showCriteria=2&sortBy=pubDateYear&subject=Chemical+Safety+Research

Bioinformatic Integration of in vivo Data and Literature-based Gene Associations for Prioritization of Adverse Outcome Pathway Development

Adverse outcome pathways (AOPs) describe a sequence of events, beginning with a molecular initiating event (MIE), proceeding via key events (KEs), and culminating in an adverse outcome (AO). A challenge for use of AOPs in a safety evaluation context has been identification of MIEs and KEs relevant for AOs observed in regulatory toxicity studies. In this work, we implemented a bioinformatic approach that leverages mechanistic information in the literature and the AOs measured in regulatory toxicity studies to prioritize putative MIEs and/or early KEs for AOP development relevant to chemical safety evaluation. The US Environmental Protection Agency Toxicity Reference Database (ToxRefDB, v2.0) contains effect information for >1000 chemicals curated from >5000 studies or summaries from sources including data evaluation records from the US EPA Office of Pesticide Programs, the National Toxicology Program (NTP), peer-reviewed literature, and pharmaceutical preclinical studies. To increase ToxRefDB interoperability, endpoint and effect information were cross-referenced with codes from the United Medical Language System, which enabled mapping of in vivo pathological effects from ToxRefDB to PubMed (via Medical Subject Headings or MeSH). This enabled linkage to any resource that is also connected to PubMed or indexed with MeSH. A publicly available bioinformatic tool, the Entity-MeSH Co-occurrence Network (EMCON), uses multiple data sources and a measure of mutual information to identify genes most related to a MeSH term. Using EMCON, gene sets were generated for endpoints of toxicological relevance in ToxRefDB linking putative KEs and/or MIEs. The Comparative Toxicogenomics Database was used to further filter important associations. As a proof of concept, thyroid-related effects and their highly associated genes were examined, and demonstrated relevant MIEs and early KEs for AOPs to describe thyroid-related AOs. The ToxRefDB to gene mapping for thyroid resulted in >50 unique gene to chemical relationships. Integrated use of EMCON and ToxRefDB data provides a basis for rapid and robust putative AOP development, as well as a novel means to generate mechanistic hypotheses for specific chemicals. This abstract does not necessarily reflect U.S. EPA policy. Abstract and Poster for 2019 Society of Toxicology annual meeting in March 2019

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dateBeginPublishedPresented=04%2F02%2F2014&dateEndPublishedPresented=04%2F02%2F2019&dirEntryId=344452&keyword=Chemical+Safety&showCriteria=2&sortBy=pubDateYear&subject=Chemical+Safety+Research

Bioinformatic Integration of in vivo Data and Literature-based Gene Associations for Prioritization of Adverse Outcome Pathway Development

Adverse outcome pathways (AOPs) describe a sequence of events, beginning with a molecular initiating event (MIE), proceeding via key events (KEs), and culminating in an adverse outcome (AO). A challenge for use of AOPs in a safety evaluation context has been identification of MIEs and KEs relevant for AOs observed in regulatory toxicity studies. In this work, we implemented a bioinformatic approach that leverages mechanistic information in the literature and the AOs measured in regulatory toxicity studies to prioritize putative MIEs and/or early KEs for AOP development relevant to chemical safety evaluation. The US Environmental Protection Agency Toxicity Reference Database (ToxRefDB, v2.0) contains effect information for >1000 chemicals curated from >5000 studies or summaries from sources including data evaluation records from the US EPA Office of Pesticide Programs, the National Toxicology Program (NTP), peer-reviewed literature, and pharmaceutical preclinical studies. To increase ToxRefDB interoperability, endpoint and effect information were cross-referenced with codes from the United Medical Language System, which enabled mapping of in vivo pathological effects from ToxRefDB to PubMed (via Medical Subject Headings or MeSH). This enabled linkage to any resource that is also connected to PubMed or indexed with MeSH. A publicly available bioinformatic tool, the Entity-MeSH Co-occurrence Network (EMCON), uses multiple data sources and a measure of mutual information to identify genes most related to a MeSH term. Using EMCON, gene sets were generated for endpoints of toxicological relevance in ToxRefDB linking putative KEs and/or MIEs. The Comparative Toxicogenomics Database was used to further filter important associations. As a proof of concept, thyroid-related effects and their highly associated genes were examined, and demonstrated relevant MIEs and early KEs for AOPs to describe thyroid-related AOs. The ToxRefDB to gene mapping for thyroid resulted in >50 unique gene to chemical relationships. Integrated use of EMCON and ToxRefDB data provides a basis for rapid and robust putative AOP development, as well as a novel means to generate mechanistic hypotheses for specific chemicals. This abstract does not necessarily reflect U.S. EPA policy. Abstract and Poster for 2019 Society of Toxicology annual meeting in March 2019

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dateBeginPublishedPresented=04%2F02%2F2014&dateEndPublishedPresented=04%2F02%2F2019&dirEntryId=344452&fed_org_id=111&keyword=Chemical+Safety&showCriteria=2&sortBy=pubDateYear&subject=Chemical+Safety+Research

Bioinformatic Integration of in vivo Data and Literature-based Gene Associations for Prioritization of Adverse Outcome Pathway Development

Adverse outcome pathways (AOPs) describe a sequence of events, beginning with a molecular initiating event (MIE), proceeding via key events (KEs), and culminating in an adverse outcome (AO). A challenge for use of AOPs in a safety evaluation context has been identification of MIEs and KEs relevant for AOs observed in regulatory toxicity studies. In this work, we implemented a bioinformatic approach that leverages mechanistic information in the literature and the AOs measured in regulatory toxicity studies to prioritize putative MIEs and/or early KEs for AOP development relevant to chemical safety evaluation. The US Environmental Protection Agency Toxicity Reference Database (ToxRefDB, v2.0) contains effect information for >1000 chemicals curated from >5000 studies or summaries from sources including data evaluation records from the US EPA Office of Pesticide Programs, the National Toxicology Program (NTP), peer-reviewed literature, and pharmaceutical preclinical studies. To increase ToxRefDB interoperability, endpoint and effect information were cross-referenced with codes from the United Medical Language System, which enabled mapping of in vivo pathological effects from ToxRefDB to PubMed (via Medical Subject Headings or MeSH). This enabled linkage to any resource that is also connected to PubMed or indexed with MeSH. A publicly available bioinformatic tool, the Entity-MeSH Co-occurrence Network (EMCON), uses multiple data sources and a measure of mutual information to identify genes most related to a MeSH term. Using EMCON, gene sets were generated for endpoints of toxicological relevance in ToxRefDB linking putative KEs and/or MIEs. The Comparative Toxicogenomics Database was used to further filter important associations. As a proof of concept, thyroid-related effects and their highly associated genes were examined, and demonstrated relevant MIEs and early KEs for AOPs to describe thyroid-related AOs. The ToxRefDB to gene mapping for thyroid resulted in >50 unique gene to chemical relationships. Integrated use of EMCON and ToxRefDB data provides a basis for rapid and robust putative AOP development, as well as a novel means to generate mechanistic hypotheses for specific chemicals. This abstract does not necessarily reflect U.S. EPA policy. Abstract and Poster for 2019 Society of Toxicology annual meeting in March 2019

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dirEntryId=344452&fed_org_id=111&keyword=Chemical+Safety&showCriteria=2&sortBy=pubDateYear&subject=Chemical+Safety+Research

Bioinformatic Integration of in vivo Data and Literature-based Gene Associations for Prioritization of Adverse Outcome Pathway Development

Adverse outcome pathways (AOPs) describe a sequence of events, beginning with a molecular initiating event (MIE), proceeding via key events (KEs), and culminating in an adverse outcome (AO). A challenge for use of AOPs in a safety evaluation context has been identification of MIEs and KEs relevant for AOs observed in regulatory toxicity studies. In this work, we implemented a bioinformatic approach that leverages mechanistic information in the literature and the AOs measured in regulatory toxicity studies to prioritize putative MIEs and/or early KEs for AOP development relevant to chemical safety evaluation. The US Environmental Protection Agency Toxicity Reference Database (ToxRefDB, v2.0) contains effect information for >1000 chemicals curated from >5000 studies or summaries from sources including data evaluation records from the US EPA Office of Pesticide Programs, the National Toxicology Program (NTP), peer-reviewed literature, and pharmaceutical preclinical studies. To increase ToxRefDB interoperability, endpoint and effect information were cross-referenced with codes from the United Medical Language System, which enabled mapping of in vivo pathological effects from ToxRefDB to PubMed (via Medical Subject Headings or MeSH). This enabled linkage to any resource that is also connected to PubMed or indexed with MeSH. A publicly available bioinformatic tool, the Entity-MeSH Co-occurrence Network (EMCON), uses multiple data sources and a measure of mutual information to identify genes most related to a MeSH term. Using EMCON, gene sets were generated for endpoints of toxicological relevance in ToxRefDB linking putative KEs and/or MIEs. The Comparative Toxicogenomics Database was used to further filter important associations. As a proof of concept, thyroid-related effects and their highly associated genes were examined, and demonstrated relevant MIEs and early KEs for AOPs to describe thyroid-related AOs. The ToxRefDB to gene mapping for thyroid resulted in >50 unique gene to chemical relationships. Integrated use of EMCON and ToxRefDB data provides a basis for rapid and robust putative AOP development, as well as a novel means to generate mechanistic hypotheses for specific chemicals. This abstract does not necessarily reflect U.S. EPA policy. Abstract and Poster for 2019 Society of Toxicology annual meeting in March 2019

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dateBeginPublishedPresented=03%2F26%2F2014&dateEndPublishedPresented=03%2F26%2F2019&dirEntryId=344452&fed_org_id=111&keyword=Chemical+Safety&showCriteria=2&sortBy=pubDateYear&subject=Chemical+Safety+Research

Bioinformatic Integration of in vivo Data and Literature-based Gene Associations for Prioritization of Adverse Outcome Pathway Development

Adverse outcome pathways (AOPs) describe a sequence of events, beginning with a molecular initiating event (MIE), proceeding via key events (KEs), and culminating in an adverse outcome (AO). A challenge for use of AOPs in a safety evaluation context has been identification of MIEs and KEs relevant for AOs observed in regulatory toxicity studies. In this work, we implemented a bioinformatic approach that leverages mechanistic information in the literature and the AOs measured in regulatory toxicity studies to prioritize putative MIEs and/or early KEs for AOP development relevant to chemical safety evaluation. The US Environmental Protection Agency Toxicity Reference Database (ToxRefDB, v2.0) contains effect information for >1000 chemicals curated from >5000 studies or summaries from sources including data evaluation records from the US EPA Office of Pesticide Programs, the National Toxicology Program (NTP), peer-reviewed literature, and pharmaceutical preclinical studies. To increase ToxRefDB interoperability, endpoint and effect information were cross-referenced with codes from the United Medical Language System, which enabled mapping of in vivo pathological effects from ToxRefDB to PubMed (via Medical Subject Headings or MeSH). This enabled linkage to any resource that is also connected to PubMed or indexed with MeSH. A publicly available bioinformatic tool, the Entity-MeSH Co-occurrence Network (EMCON), uses multiple data sources and a measure of mutual information to identify genes most related to a MeSH term. Using EMCON, gene sets were generated for endpoints of toxicological relevance in ToxRefDB linking putative KEs and/or MIEs. The Comparative Toxicogenomics Database was used to further filter important associations. As a proof of concept, thyroid-related effects and their highly associated genes were examined, and demonstrated relevant MIEs and early KEs for AOPs to describe thyroid-related AOs. The ToxRefDB to gene mapping for thyroid resulted in >50 unique gene to chemical relationships. Integrated use of EMCON and ToxRefDB data provides a basis for rapid and robust putative AOP development, as well as a novel means to generate mechanistic hypotheses for specific chemicals. This abstract does not necessarily reflect U.S. EPA policy. Abstract and Poster for 2019 Society of Toxicology annual meeting in March 2019

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dirEntryId=344452&fed_org_id=111&keyword=Chemical+Safety&showCriteria=2&sortBy=pubDateYear&subject=Chemical+Safety+Research

Bioinformatic Integration of in vivo Data and Literature-based Gene Associations for Prioritization of Adverse Outcome Pathway Development

Adverse outcome pathways (AOPs) describe a sequence of events, beginning with a molecular initiating event (MIE), proceeding via key events (KEs), and culminating in an adverse outcome (AO). A challenge for use of AOPs in a safety evaluation context has been identification of MIEs and KEs relevant for AOs observed in regulatory toxicity studies. In this work, we implemented a bioinformatic approach that leverages mechanistic information in the literature and the AOs measured in regulatory toxicity studies to prioritize putative MIEs and/or early KEs for AOP development relevant to chemical safety evaluation. The US Environmental Protection Agency Toxicity Reference Database (ToxRefDB, v2.0) contains effect information for >1000 chemicals curated from >5000 studies or summaries from sources including data evaluation records from the US EPA Office of Pesticide Programs, the National Toxicology Program (NTP), peer-reviewed literature, and pharmaceutical preclinical studies. To increase ToxRefDB interoperability, endpoint and effect information were cross-referenced with codes from the United Medical Language System, which enabled mapping of in vivo pathological effects from ToxRefDB to PubMed (via Medical Subject Headings or MeSH). This enabled linkage to any resource that is also connected to PubMed or indexed with MeSH. A publicly available bioinformatic tool, the Entity-MeSH Co-occurrence Network (EMCON), uses multiple data sources and a measure of mutual information to identify genes most related to a MeSH term. Using EMCON, gene sets were generated for endpoints of toxicological relevance in ToxRefDB linking putative KEs and/or MIEs. The Comparative Toxicogenomics Database was used to further filter important associations. As a proof of concept, thyroid-related effects and their highly associated genes were examined, and demonstrated relevant MIEs and early KEs for AOPs to describe thyroid-related AOs. The ToxRefDB to gene mapping for thyroid resulted in >50 unique gene to chemical relationships. Integrated use of EMCON and ToxRefDB data provides a basis for rapid and robust putative AOP development, as well as a novel means to generate mechanistic hypotheses for specific chemicals. This abstract does not necessarily reflect U.S. EPA policy. Abstract and Poster for 2019 Society of Toxicology annual meeting in March 2019

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dateBeginPublishedPresented=04%2F11%2F2014&dateEndPublishedPresented=04%2F11%2F2019&dirEntryId=344452&fed_org_id=111&keyword=Chemical+Safety&showCriteria=2&sortBy=pubDateYear&subject=Chemical+Safety+Research

Bioinformatic Integration of in vivo Data and Literature-based Gene Associations for Prioritization of Adverse Outcome Pathway Development

Adverse outcome pathways (AOPs) describe a sequence of events, beginning with a molecular initiating event (MIE), proceeding via key events (KEs), and culminating in an adverse outcome (AO). A challenge for use of AOPs in a safety evaluation context has been identification of MIEs and KEs relevant for AOs observed in regulatory toxicity studies. In this work, we implemented a bioinformatic approach that leverages mechanistic information in the literature and the AOs measured in regulatory toxicity studies to prioritize putative MIEs and/or early KEs for AOP development relevant to chemical safety evaluation. The US Environmental Protection Agency Toxicity Reference Database (ToxRefDB, v2.0) contains effect information for >1000 chemicals curated from >5000 studies or summaries from sources including data evaluation records from the US EPA Office of Pesticide Programs, the National Toxicology Program (NTP), peer-reviewed literature, and pharmaceutical preclinical studies. To increase ToxRefDB interoperability, endpoint and effect information were cross-referenced with codes from the United Medical Language System, which enabled mapping of in vivo pathological effects from ToxRefDB to PubMed (via Medical Subject Headings or MeSH). This enabled linkage to any resource that is also connected to PubMed or indexed with MeSH. A publicly available bioinformatic tool, the Entity-MeSH Co-occurrence Network (EMCON), uses multiple data sources and a measure of mutual information to identify genes most related to a MeSH term. Using EMCON, gene sets were generated for endpoints of toxicological relevance in ToxRefDB linking putative KEs and/or MIEs. The Comparative Toxicogenomics Database was used to further filter important associations. As a proof of concept, thyroid-related effects and their highly associated genes were examined, and demonstrated relevant MIEs and early KEs for AOPs to describe thyroid-related AOs. The ToxRefDB to gene mapping for thyroid resulted in >50 unique gene to chemical relationships. Integrated use of EMCON and ToxRefDB data provides a basis for rapid and robust putative AOP development, as well as a novel means to generate mechanistic hypotheses for specific chemicals. This abstract does not necessarily reflect U.S. EPA policy. Abstract and Poster for 2019 Society of Toxicology annual meeting in March 2019

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dateBeginPublishedPresented=04%2F11%2F2014&dateEndPublishedPresented=04%2F11%2F2019&dirEntryId=344452&keyword=Chemical+Safety&showCriteria=2&sortBy=pubDateYear&subject=Chemical+Safety+Research

A Web-Hosted R Workflow to Simplify and Automate the Analysis of 16S NGS Data

Next-Generation Sequencing (NGS) produces large data sets that include tens-of-thousands of sequence reads per sample. For analysis of bacterial diversity, 16S NGS sequences are typically analyzed in a workflow that containing best-of-breed bioinformatics packages that may leverage multiple programming languages (e.g., Python, R, Java, etc.). The process totransform raw NGS data to usable operational taxonomic units (OTUs) can be tedious due tothe number of quality control (QC) steps used in QIIME and other software packages forsample processing. Therefore, the purpose of this work was to simplify the analysis of 16SNGS data from a large number of samples by integrating QC, demultiplexing, and QIIME(Quantitative Insights Into Microbial Ecology) analysis in an accessible R project. User command line operations for each of the pipeline steps were automated into a workflow. In addition, the R server allows multi-user access to the automated pipeline via separate useraccounts while providing access to the same large set of underlying data. We demonstratethe applicability of this pipeline automation using 16S NGS data from approximately 100 stormwater runoff samples collected in a mixed-land use watershed in northeast Georgia. OTU tables were generated for each sample and the relative taxonomic abundances were compared for different periods over storm hydrographs to determine how the microbial ecology of a stream changes with rise and fall of stream stage. Our approach simplifies the pipeline analysis of multiple 16S NGS samples by automating multiple preprocessing, QC, analysis and post-processing command line steps that are called by a sequence of R scripts. Presented at ASM 2015 Rapid NGS Bioinformatic Pipelines for Enhanced Molecular Epidemiologic Investigation of Pathogens

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NERL&dirEntryId=309890

DEVELOPING COMPUTATIONAL TOOLS NECESSARY FOR APPLYING TOXICOGENOMICS TO RISK ASSESSMENT AND REGULATORY DECISION MAKING.

GENOMICS, PROTEOMICS & METABOLOMICS CAN PROVIDE USEFUL WEIGHT-OF-EVIDENCE DATA ALONG THE SOURCE-TO-OUTCOME CONTINUUM, WHEN APPROPRIATE BIOINFORMATIC AND COMPUTATIONAL METHODS ARE APPLIED TOWARDS INTEGRATING MOLECULAR, CHEMICAL AND TOXICOGICAL INFORMATION. GENOMICS, PROTEOMICS & METABOLOMICS CAN PROVIDE USEFUL WEIGHT-OF-EVIDENCE DATA ALONG THE SOURCE-TO-OUTCOME CONTINUUM, WHEN APPROPRIATE BIOINFORMATIC AND COMPUTATIONAL METHODS ARE APPLIED TOWARDS INTEGRATING MOLECULAR, CHEMICAL AND TOXICOGICAL INFORMATION.

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dirEntryId=156264

The Human Toxome Project

The Human Toxome project, funded as an NIH Transformative Research grant 2011–‐ 2016, is focused on developing the concepts and the means for deducing, validating, and sharing molecular Pathways of Toxicity (PoT). Using the test case of estrogenic endocrine disruption, the responses of MCF–‐7 human breast cancer cells are being phenotyped by transcriptomics and mass–‐spectroscopy–‐based metabolomics. The bioinformatics tools for PoT deduction represent a core deliverable. A number of challenges for quality and standardization of cell systems, omics technologies, and bioinformatics are being addressed. In parallel, concepts for annotation, validation, and sharing of PoT information, as well as their link to adverse outcomes, are being developed. A reasonably comprehensive public database of PoT, the Human Toxome Knowledge–‐base, could become a point of reference for toxicological research and regulatory tests strategies. A reasonably comprehensive public database of PoT, the Human Toxome Knowledge–‐base, could become a point of reference for toxicological research and regulatory tests strategies.

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dirEntryId=309453

High-Resolution Metabolomics for Environmental Chemical Surveillance and Bioeffect Monitoring

High-Resolution Metabolomics for Environmental Chemical Surveillance and Bioeffect Monitoring (Presented by: Dean Jones, PhD, Department of Medicine, Emory University) (2/28/2013)

https://www.epa.gov/chemical-research/high-resolution-metabolomics-environmental-chemical-surveillance-and-bioeffect

Identification of Absorption, Distribution, Metabolism, and Excretion (ADME) Genes Relevant to Steatosis Using a Gene Expression Approach

Absorption, distribution, metabolism, and excretion (ADME) impact chemical concentration and activation of molecular initiating events of Adverse Outcome Pathways (AOPs) in cellular, tissue, and organ level targets. In order to better describe ADME parameters and how they modulate potential hazards posed by chemical exposure, our goal is to investigate the relationship between AOPs and ADME related genes and functional information. Given the scope of this task, we began using hepatic steatosis as a case study. To identify ADME genes related to steatosis, we used the publicly available toxicogenomics database, Open TG-GATEsTM. This database contains standardized rodent chemical exposure data from 170 chemicals (mostly drugs), along with differential gene expression data and corresponding associated pathological changes. We examined the chemical exposure microarray data set gathered from 9 chemical exposure treatments resulting in pathologically confirmed (minimal, moderate and severe) incidences of hepatic steatosis. From this differential gene expression data set, we utilized differential expression analyses to identify gene changes resulting from the chemical exposures leading to hepatic steatosis. We then selected differentially expressed genes (DEGs) related to ADME by filtering all genes based on their ADME functional identities. These DEGs include enzymes such as cytochrome p450, UDP glucuronosyltransferase, flavin-containing monooxygenase and transporter genes such as solute carriers and ATP-binding cassette transporter families. The up and downregulated genes were identified across these treatments. Total of 61 genes were upregulated and 68 genes were down regulated in all treatments. Meanwhile, 25 genes were both up regulated and downregulated across all the treatments. This work highlights the application of bioinformatics in linking AOPs with gene modulations specifically in relationships to ADME and exposures to chemicals. This abstract does not necessarily reflect U.S. EPA policy. This work highlights the application of bioinformatics tools to identify genes that are modulated by adverse outcomes. Specifically, we delineate a method to identify genes that are related to ADME and can impact target tissue dose in response to chemical exposures. The computational method outlined in this work is applicable to any adverse outcome pathway, and provide a linkage between chemical exposure, target tissue dose, and adverse outcomes. Application of this method will allow for the rapid screening of chemicals for their impact on ADME-related genes using available gene data bases in literature.

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NHEERL&dirEntryId=341273

Development of Environmental Fate and Metabolic Simulators

Presented at Bioinformatics Open Source Conference (BOSC), Detroit, MI, June 23-24, 2005. see description

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NERL&dirEntryId=257172

Useful Webinars on EPA Computational Tools and Informatics

Computational Toxicology Communities of Practice

Computational Toxicology Research

EPA’s Computational Toxicology Communities of Practice is composed of hundreds of stakeholders from over 50 public and private sector organizations (ranging from EPA, other federal agencies, industry, academic institutions, professional societies, nongovernmental organizations, environmental non-profit groups, state environmental agencies and more) who have an interest in using advances in computational toxicology and exposure science to evaluate the safety of chemicals.

The Communities of Practice is open to the public. Monthly webinars are held at EPA’s RTP campus, on the fourth Thursday of the month (occasionally rescheduled in November and December to accommodate holiday schedules), from 11am-Noon EST/EDT. Remote participation is available. For more information or to be added to the meeting email list, contact: Monica Linnenbrink (linnenbrink.monica@epa.gov).

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