Genomic Approaches for Cross-Species Extrapolation in Toxicology: 1st Edition (Hardback) book cover

Genomic Approaches for Cross-Species Extrapolation in Toxicology

1st Edition

Edited by William H. Benson, Richard T. Di Giulio

CRC Press

216 pages | 16 B/W Illus.

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pub: 2006-12-13
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Description

The latest tools for investigating stress response in organisms, genomic technologies provide great insight into how different organisms respond to environmental conditions. However, their usefulness needs to be tested, verified, and codified. Genomic Approaches for Cross-Species Extrapolation in Toxicology provides a balanced discussion drawn from the experience of thirty-five scientists and professionals from diverse fields including environmental toxicology and chemistry, biomedical toxicology, molecular biology, genetics, physiology, bioinformatics, computer science, and statistics.

The book introduces genomic, transcriptomic, proteomic, and metabolomic technologies. It describes the advantages and challenges associated with these approaches compared to traditional methodologies, particularly from the perspective of cross-species extrapolation within human and environmental toxicology, and explores solutions that will facilitate the incorporation of these technologies into predictive toxicology. The book goes on to identify and prioritize species of animals that can serve as surrogates for environmental and human health in comparative toxicogenomic studies. The chapter authors elucidate similarities and differences among species, relate stressor-mediated responses to adverse outcomes, and extend this science into innovative approaches to risk assessment and regulatory decision-making.

Table of Contents

"OMIC" APPROACHES IN THE CONTEXT OF ENVIRONMENTAL TOXICOLOGY

Introduction

Overview of Omic Technologies

Discovery-Driven Versus Hypothesis-Driven Research: A Need for Balance

Advantages, Challenges, and Solutions of Omic Technologies

Pathway Mapping - The Future of Omic Technologies

An Example of Cross Species Extrapolation Using Transcriptomics

Recommendations

Future

References

SELECTION OF SURROGATE ANIMAL SPECIES FOR COMPARATIVE TOXICOGENOMICS

Introduction

Brief Review on Studies Using Comparative Genomics

Selection Criteria for Surrogate Species

Selection of Surrogate Species

Discussion

Conclusions

References

SPECIES DIFFERENCES IN RESPONSE TO TOXIC SUBSTANCES: SHARED PATHWAYS OF TOXICITY

What Omics Approaches Would be of Greatest Value in Predictive Toxicology that Utilizes Biologically Relevant Effects in Organisms or the Environment?

How Can Omics be Utilized to Understand Mechanism and/or Mode of Action?

How do we Integrate Responses Across Gene Expression, Proteomics, and Metabolomics and Apply this to Make a Science-Based Statement About the Health of an Organism?

How Does Development of Omic Technologies Impact the Interspecies Extrapolation Process?

What are the Key Limitations/Considerations in Using Omics Technologies to Inform Mechanism of Cross-Species Differences in Response to Xenobiotics?

Conclusions

Recommendations

BIOINFORMATIC APPROACHES AND COMPUTATIONAL MODELS FOR DATA INTEGRATION AND CROSS-SPECIES EXTRAPOLATION IN THE POST-GENOMIC ERA

Introduction

Mechanistic vs. Classification Studies

Computational Methods for Ortholog Identification

Interpreting Expression Data Across Species

Integrating Data Across Domains

Supervised and Unsupervised Analysis for Toxicogenomics

Networks

The Problem of Validation

Predictive Toxicology

Recommendations for Advancing the Field

Concluding Remarks

References

THE EXTENSION OF MOLECULAR AND COMPUTATIONAL INFORMATION TO RISK ASSESSMENT AND REGULATORY DECISION-MAKING

Introduction

Overview of Human and Ecological Risk Assessment

Potential of 'Omics to Improve Risk Assessment

The Path Forward?

Conclusions and Recommendations

Acknowledgements

References

Subject Categories

BISAC Subject Codes/Headings:
MAT029000
MATHEMATICS / Probability & Statistics / General
SCI026000
SCIENCE / Environmental Science
SCI029000
SCIENCE / Life Sciences / Genetics & Genomics