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PubMed2005

Toxicogenomic analysis of gene expression changes in rat liver after a 28-day oral benzene exposure.

Benzene is an industrial chemical, component of automobile exhaust and cigarette smoke. After hepatic bioactivation benzene induces bone marrow, blood and hepatic toxicity. Using a toxicogenomics approach this study analysed the effects of benzene at three dose levels on gene expression in the liver after 28 daily doses. NMR based metabolomics was used to assess benzene exposure by identification of characteristic benzene metabolite profiles in urine. The 28-day oral exposure to 200 and 800 mg/kg/day but not 10 mg/kg/day benzene-induced hematotoxicity in male Fisher rats. Additionally these upper dose levels slightly reduced body weight and increased relative liver weights. Changes in hepatic gene expression were identified with oligonucleotide microarrays at all dose levels including the 10 mg/kg/day dose level where no toxicity was detected by other methods. The benzene-induced gene expression changes were related to pathways of biotransformation, glutathione synthesis, fatty acid and cholesterol metabolism and others. Some of the effects on gene expression observed here have previously been observed after induction of acute hepatic necrosis with bromobenzene and acetaminophen. In conclusion, changes in hepatic gene expression were found after treatment with benzene both at the toxic and non-toxic doses. The results from this study show that toxicogenomics identified hepatic effects of benzene exposure possibly related to toxicity. The findings aid to interpret the relevance of hepatic gene expression changes in response to exposure to xenobiotics. In addition, the results have the potential to inform on the mechanisms of response to benzene exposure.

Animals↗

PubMed2005

In pursuit of effective toxicogenomics.

Biological systems exhibit complex responses to xenobiotics varying from generic stress responses to very specific changes closely associated with the mechanism of toxicity. Until recently our view of this complexity was obscured by the simplicity of available analysis tools which allowed determination of only a few genes in any one study. Then genome sequencing and high throughput library screening projects delivered data on the genome sequence of many organisms, and clones were collected and made available to researchers in a previously unparalleled quantity. To exploit this new resource the microarray was developed from its predecessor the dot blot. Further development has expanded the number of clones contained on any one microarray to a point where the expression of many tens of thousands of genes in a biological system can be determined in a short period of time. What these data are revealing is the full complexity of the gene expression response to stimuli such as xenobiotic exposure. Toxicogenomics seeks to use the complexity of this response as a fingerprint or signature characteristic of that xenobiotic exposure. There are though two major experimental challenges that need to be dealt with for toxicogenomics to be successful. The first is technical and relates to the intrinsic difficulties associated with the accurate measurement of gene expression. For microarrays, this problem is multiplied by the number of genes on the microarray itself. To overcome this technical variability correct experimental design is critical. The second challenge concerns the biological system used. What genetic background, time point and dose of xenobiotic should be chosen? For in vitro systems should cell lines or primary cells be used? These factors, and more, could affect the gene expression profile obtained in response to the same xenobiotic exposure. Using both our data and data from public databases these issues are explored in this paper.

Animals↗

PubMed2003

Toxicogenomic approach for assessing toxicant-related disease.

The problems of identifying environmental factors involved in the etiology of human disease and performing safety and risk assessments of drugs and chemicals have long been formidable issues. Three principal components for predicting potential human health risks are: (1) the diverse structure and properties of thousands of chemicals and other stressors in the environment; (2) the time and dose parameters that define the relationship between exposure and disease; and (3) the genetic diversity of organisms used as surrogates to determine adverse chemical effects. The global techniques evolving from successful genomics efforts are providing new exciting tools with which to address these intractable problems of environmental health and toxicology. In order to exploit the scientific opportunities, the National Institute of Environmental Health Sciences has created the National Center for Toxicogenomics (NCT). The primary mission of the NCT is to use gene expression technology, proteomics and metabolite profiling to create a reference knowledge base that will allow scientists to understand mechanisms of toxicity and to be able to predict the potential toxicity of new chemical entities and drugs. A principal scientific objective underpinning the use of microarray analysis of chemical exposures is to demonstrate the utility of signature profiling of the action of drugs or chemicals and to utilize microarray methodologies to determine biomarkers of exposure and potential adverse effects. The initial approach of the NCT is to utilize proof-of-principle experiments in an effort to "phenotypically anchor" the altered patterns of gene expression to conventional parameters of toxicity and to define dose and time relationships in which the expression of such signature genes may precede the development of overt toxicity. The microarray approach is used in conjunction with proteomic techniques to identify specific proteins that may serve as signature biomarkers. The longer-range goal of these efforts is to develop a reference relational database of chemical effects in biological systems (CEBS) that can be used to define common mechanisms of toxicity, chemical and drug actions, to define cellular pathways of response, injury and, ultimately, disease. In order to implement this strategy, the NCT has created a consortium of research organizations and private sector companies to actively collaborative in populating the database with high quality primary data. The evolution of discrete databases to a knowledge base of toxicogenomics will be accomplished through establishing relational interfaces with other sources of information on the structure and activity of chemicals such as that of the National Toxicology Program (NTP) and with databases annotating gene identity, sequence, and function.

Animals↗

PubMedDate not supplied

A database for tracking toxicogenomic samples and procedures.

Reproductive toxicogenomic studies generate large amounts of toxicological and genomic data. On the toxicology side, a substantial quantity of data accumulates from conventional endpoints such as histology, reproductive physiology and biochemistry. The largest source of genomics data is DNA microarrays, which generate enormous amounts of information in the course of profiling gene expression. Thus, data storage and management become essential and require a more sophisticated system than lab notebooks and electronic spreadsheets. We developed a database for tracking toxicogenomic samples and procedures (TSP 1.0) for our reproductive studies based on the MIAME-Tox guidelines and relational database theory. This database stores the various types of data from both toxicological and genomic assays in a hierarchical fashion. The user-friendly interface provides easy procedures for researchers to add, edit, save, delete, and navigate different records. Finally, TSP facilitates exporting microarray data into public databases.

Database Management Systems↗

PubMed2005

How can toxicogenomics inform risk assessment?

Technologies that generate information about the genome are being used to explore changes in gene expression and related proteins following exposure to chemicals. Conceptually, this information allows a greater understanding of genomic level mRNA expression (transcriptomics), cell and tissue protein expression (proteomics) and information about metabolite profiles (metabonomics). Having a greater understanding of this information alongside, empirical toxicological reference data provide for the continued evolution in our ability to understand toxicological modes of action, thereby providing a more scientific basis for extrapolation of toxicological information from animals to humans. Toxicogenomics also provides specific opportunities for improvements at different stages of the risk assessment process such as the development of new predictive models for identifying human health hazards and the identification of more precise molecular biomarkers of exposure. One possibility is that molecular fingerprinting in vivo or in vitro can be used to categorize chemicals and mixtures of chemicals into different mode of action groups. As there is indication that molecular signals differ at dose levels, it is hoped that toxicogenomic information can also contribute to the understanding and interpretation of effects seen with low dose exposure. Several gene polymorphisms have already been identified which play a role in the differing intra-species response to chemicals thus providing explanation for the observed differences in effects. It is therefore likely that a better understanding of genomic expression will enable a greater insight into the factors behind the observed variability in susceptibility to chemical exposure that can be seen in human populations.

Genomics↗

PubMed2005

Design issues in toxicogenomics using DNA microarray experiment.

The methods of toxicogenomics might be classified into omics study (e.g., genomics, proteomics, and metabolomics) and population study focusing on risk assessment and gene-environment interaction. In omics study, microarray is the most popular approach. Genes falling into several categories (e.g., xenobiotics metabolism, cell cycle control, DNA repair etc.) can be selected up to 20,000 according to a priori hypothesis. The appropriate type of samples and species should be selected in advance. Multiple doses and varied exposure durations are suggested to identify those genes clearly linked to toxic response. Microarray experiments can be affected by numerous nuisance variables including experimental designs, sample extraction, type of scanners, etc. The number of slides might be determined from the magnitude and variance of expression change, false-positive rate, and desired power. Instead, pooling samples is an alternative. Online databases on chemicals with known exposure-disease outcomes and genetic information can aid the interpretation of the normalized results. Gene function can be inferred from microarray data analyzed by bioinformatics methods such as cluster analysis. The population study often adopts hospital-based or nested case-control design. Biases in subject selection and exposure assessment should be minimized, and confounding bias should also be controlled for in stratified or multiple regression analysis. Optimal sample sizes are dependent on the statistical test for gene-to-environment or gene-to-gene interaction. The design issues addressed in this mini-review are crucial in conducting toxicogenomics study. In addition, integrative approach of exposure assessment, epidemiology, and clinical trial is required.

Computational Biology↗

PubMed2006

Toxicogenomics of endoplasmic reticulum stress inducer tunicamycin in the small intestine and liver of Nrf2 knockout and C57BL/6J mice.

This objective of this study was to investigate the toxicogenomics and the spatial regulation of global gene expression profiles elicited by endoplasmic reticulum (ER) stress inducer tunicamycin (TM) in mouse small intestine and liver as well as to identify TM-modulated nuclear factor-E2-related factor 2 (Nrf2)-dependent genes. Gene expression profiles were analyzed using 45,000 Affymetrix mouse genome 430 2.0 array and GeneSpring 7.2 software. Microarray results were validated by quantitative real-time reverse transcription-PCR analyses. Clusters of genes that were either induced or suppressed more than two-fold by TM treatment compared with vehicle in C57BL/6J/Nrf2 (-/-; knockout) and C57BL/6J Nrf2 (+/+; wildtype) mice genotypes were identified. Amongst these, in small intestine and liver, 1291 and 750 genes, respectively, were identified as Nrf2-dependent and upregulated, and 1370 and 943 genes, respectively, as Nrf2-dependent and downregulated. Based on their biological functions, these genes can be categorized into molecular chaperones and heat shock proteins, ubiquitination/proteolysis, apoptosis/cell cycle, electron transport, detoxification, cell growth/differentiation, signaling molecules/interacting partners, kinases and phosphatases, transport, biosynthesis/metabolism, nuclear assembly and processing, and genes related to calcium and glucose homeostasis. Phase II detoxification/antioxidant genes as well as putative interacting partners of Nrf2 such as nuclear corepressors and coactivators, were also identified as Nrf2-dependent genes. The identification of TM-regulated and Nrf2-dependent genes in the unfolded protein response to ER stress not only provides potential novel insights into the gestalt biological effects of TM on the toxicogenomics and spatial regulation of global gene expression profiles in cancer pharmacology and toxicology, but also points to the pivotal role of Nrf2 in these biological processes.

Animals↗

PubMed2002

Toxicology and genetic toxicology in the new era of "toxicogenomics": impact of "-omics" technologies.

The unprecedented advances in molecular biology during the last two decades have resulted in a dramatic increase in knowledge about gene structure and function, an immense database of genetic sequence information, and an impressive set of efficient new technologies for monitoring genetic sequences, genetic variation, and global functional gene expression. These advances have led to a new sub-discipline of toxicology: "toxicogenomics". We define toxicogenomics as "the study of the relationship between the structure and activity of the genome (the cellular complement of genes) and the adverse biological effects of exogenous agents". This broad definition encompasses most of the variations in the current usage of this term, and in its broadest sense includes studies of the cellular products controlled by the genome (messenger RNAs, proteins, metabolites, etc.). The new "global" methods of measuring families of cellular molecules, such as RNA, proteins, and intermediary metabolites have been termed "-omic" technologies, based on their ability to characterize all, or most, members of a family of molecules in a single analysis. With these new tools, we can now obtain complete assessments of the functional activity of biochemical pathways, and of the structural genetic (sequence) differences among individuals and species, that were previously unattainable. These powerful new methods of high-throughput and multi-endpoint analysis include gene expression arrays that will soon permit the simultaneous measurement of the expression of all human genes on a single "chip". Likewise, there are powerful new methods for protein analysis (proteomics: the study of the complement of proteins in the cell) and for analysis of cellular small molecules (metabonomics: the study of the cellular metabolites formed and degraded under genetic control). This will likely be extended in the near future to other important classes of biomolecules such as lipids, carbohydrates, etc. These assays provide a general capability for global assessment of many classes of cellular molecules, providing new approaches to assessing functional cellular alterations. These new methods have already facilitated significant advances in our understanding of the molecular responses to cell and tissue damage, and of perturbations in functional cellular systems. As a result of this rapidly changing scientific environment, regulatory and industrial toxicology practice is poised to undergo dramatic change during the next decade. These advances present exciting opportunities for improved methods of identifying and evaluating potential human and environmental toxicants, and of monitoring the effects of exposures to these toxicants. These advances also present distinct challenges. For example, the significance of specific changes and the performance characteristics of new methods must be fully understood to avoid misinterpretation of data that could lead to inappropriate conclusions about the toxicity of a chemical or a mechanism of action. We discuss the likely impact of these advances on the fields of general and genetic toxicology, and risk assessment. We anticipate that these new technologies will (1) lead to new families of biomarkers that permit characterization and efficient monitoring of cellular perturbations, (2) provide an increased understanding of the influence of genetic variation on toxicological outcomes, and (3) allow definition of environmental causes of genetic alterations and their relationship to human disease. The broad application of these new approaches will likely erase the current distinctions among the fields of toxicology, pathology, genetic toxicology, and molecular genetics. Instead, a new integrated approach will likely emerge that involves a comprehensive understanding of genetic control of cellular functions, and of cellular responses to alterations in normal molecular structure and function.

Animals↗

PubMed2002

Toxicogenomics and toxic torts.

One of the first practical applications of toxicogenomics will probably be in the context of toxic tort personal injury litigation. Gene expression changes that'fingerprint' exposure to particular classes of toxic substances can potentially be used to demonstrate exposure, prove causation and support novel damage claims in lawsuits brought by citizens injured by toxic exposures. Although the potential use of toxicogenomic data in toxic tort litigation is immense, there is a danger of premature use of such data before they have been adequately validated and characterized.

Causality↗

PubMed2003

Toxicogenomics: challenges and opportunities.

Toxicogenomics describes the measurement of global gene expression changes in biological samples exposed to toxicants. This new technology promises to greatly facilitate research into toxicant mechanisms, with the possibility of assisting in the detection of compounds with the potential to cause adverse health effects earlier in the development of pharmaceutical and chemical products. In this short review, I discuss the opportunities presented by toxicogenomics, the challenges we face in the application of these tools, and the progress we have made in realising the potential of these new genomic approaches.

Humans↗

PubMed2002

Toxicogenomics; transcript profiling and potential application to chemical allergy.

Novel transcript profiling technologies allow simultaneous measurement of the changes in expression of many hundreds or many thousands of genes. The availability of these methods has brought about revolutionary changes in many areas of investigative biology, where analyses of patterns of gene expression, rather than of individual genes, are being employed. The application of these technologies to toxicology (toxicogenomics) offers new opportunities for both mechanistic toxicity research and predictive toxicology. Here we provide an overview of the basic approaches used in this field. The development of a series of toxicology-specific microarrays in our own laboratory is discussed, together with an example of one area of mechanistic research, chemical allergy, where we believe judicious application of toxicogenomics will make an important contribution.

Animals↗

PubMed2003

The toxicogenomics of nuclear receptor agonists.

Toxicogenomics is the study of the structure and output of the genome as it responds to adverse xenobiotic exposure. Large-scale transcriptional analysis, made possible through microarray technologies, enables us to study and understand the complexity of the biological effects of drugs and chemicals, with the ultimate goal of separating wanted effects from adverse effects. Nuclear receptors are attractive targets for drug discovery because, as ligand-activated transcription factors, they coordinately regulate the expression of at least hundreds of genes that, in turn, control much of cellular metabolism. Through toxicogenomics, it is becoming possible to understand the therapeutic effects of agonists within the context of toxic effects, classify new chemicals as to their complete effects on biological systems, and identify environmental factors that may influence safety or efficacy of new and existing drugs.

Animals↗

PubMed2006

Rat toxicogenomic study reveals analytical consistency across microarray platforms.

To validate and extend the findings of the MicroArray Quality Control (MAQC) project, a biologically relevant toxicogenomics data set was generated using 36 RNA samples from rats treated with three chemicals (aristolochic acid, riddelliine and comfrey) and each sample was hybridized to four microarray platforms. The MAQC project assessed concordance in intersite and cross-platform comparisons and the impact of gene selection methods on the reproducibility of profiling data in terms of differentially expressed genes using distinct reference RNA samples. The real-world toxicogenomic data set reported here showed high concordance in intersite and cross-platform comparisons. Further, gene lists generated by fold-change ranking were more reproducible than those obtained by t-test P value or Significance Analysis of Microarrays. Finally, gene lists generated by fold-change ranking with a nonstringent P-value cutoff showed increased consistency in Gene Ontology terms and pathways, and hence the biological impact of chemical exposure could be reliably deduced from all platforms analyzed.

Animals↗

PubMed2004

Toxicogenomics and systems toxicology: aims and prospects.

Toxicogenomics combines transcript, protein and metabolite profiling with conventional toxicology to investigate the interaction between genes and environmental stress in disease causation. The patterns of altered molecular expression that are caused by specific exposures or disease outcomes have revealed how several toxicants act and cause disease. Despite these success stories, the field faces noteworthy challenges in discriminating the molecular basis of toxicity. We argue that toxicology is gradually evolving into a systems toxicology that will eventually allow us to describe all the toxicological interactions that occur within a living system under stress and use our knowledge of toxicogenomic responses in one species to predict the modes-of-action of similar agents in other species.

Animals↗

PubMedDate not supplied

Application of toxicogenomics to toxicology: basic concepts in the analysis of microarray data.

Toxicology and the practice of pathology are rapidly evolving in the postgenomic era. Observable treatment related changes have been the hallmark of toxicology studies. Toxicogenomics is a powerful new tool that may show gene and protein changes earlier and at treatment levels below the limits of detection of traditional measures of toxicity. It may also aid in the understanding of toxic mechanisms. It is important to remember that it is only a tool and will provide meaningful results only when properly applied. As is often the case with new experimental tools, the initial utilization is driven more by the technology than application to problem solving. Toxicogenomics is interdisciplinary in nature including at a minimum, pathology, toxicology, and genomics. Most studies will require the input from the disciplines of toxicology, pathology, molecular biology, bioinformatics, biochemistry, and others depending on the types of questions being asked.

Acetaminophen↗

PubMed2005

Class prediction in toxicogenomics.

The intent of this article is to discuss some of the complexities of toxicogenomics data and the statistical design and analysis issues that arise in the course of conducting a toxicogenomics study. We also describe a procedure for classifying compounds into various hepatotoxicity classes based on gene expression data. The methodology involves first classifying a compound as toxic or nontoxic and subsequently classifying the toxic compounds into the hepatotoxicity classes, based on votes by binary classifiers. The binary classifiers are constructed by using genes selected to best elicit differences between the two classes. We show that the gene selection strategy improves the misclassification error rates and also delivers gene pathways that exhibit biological relevance.

Algorithms↗

PubMed2005

Toxicogenomics in risk assessment: applications and needs.

Since its inception, there have been high expectations for the science of toxicogenomics to decrease the uncertainties associated with the risk assessment process by providing valuable insights into toxic mechanisms of action. However, the application of these data into risk assessment practices is still in the early stages of development, and proof of principle experiments have yet to emerge. The following discusses some potential applications as well as impediments that warrant a concerted investigation from all stakeholders in order to facilitate the acceptance and subsequent incorporation of toxicogenomics into regulatory decision making.

Animals↗

PubMed2006

dbZach: A MIAME-compliant toxicogenomic supportive relational database.

Quantitative risk assessment and the elucidation of mechanisms of toxicity requires computational infrastructure and innovative analysis approaches that systematically consider available data at all levels of biological organization. dbZach (http://dbzach.fst.msu.edu) is a modular relational database with associated data insertion, retrieval, and mining tools that manages traditional toxicology and complementary toxicogenomic data to facilitate comprehensive data integration, analysis, and sharing. It consists of four Core Subsystems (i.e., Clones, Genes, Sample Annotation, and Protocols), four Experimental Subsystems (i.e., Microarray, Affymetrix, Real-Time PCR, and Toxicology), and three Computational Subsystems (i.e., Gene Regulation, Pathways, Orthology) that comply with the Minimum Information About a Microarray Experiment (MIAME) standard. It is capable of including emerging technologies and other model systems, including ecologically relevant species. dbZach represents an enterprise toxicogenomic data management system which facilitates data integration and analysis, and reduces uncertainties in the continuum from initial exposure to toxicity while facilitating more comprehensive elucidations of mechanisms of toxicity and supporting mechanistically-based quantitative risk assessment.

Animals↗