DNA Microarray‐based ecotoxicological biomarker discovery in a small fish model species

Abstract

As potential biomarkers, gene classifiers are gene expression signatures or patterns capable of distinguishing biological samples belonging to different classes or conditions. This is the second of two papers on profiling gene expression in zebrafish (Danio rerio) treated with endocrine-disrupting chemicals of different modes of action, with a focus on comparative analysis of microarray data for gene classifier discovery. Various combinations of gene feature selection/class prediction algorithms were evaluated, with the use of microarray data organized by a chemical stressor or tissue type, for their accuracy in determining the class memberships of independent test samples. Two-way clustering of gene classifiers and treatment conditions offered another alternative to assess the performance of these potential biomarkers. Both gene feature selection methods and class prediction algorithms were shown to be important in identifying successful gene classifiers. The genetic algorithm and support vector machine yielded classifiers with the best prediction accuracy, regardless of sample size, nature of class prediction, and data complexity. A chemical stressor significantly altering the expression of a greater number of genes tended to generate gene classifiers with better performance. All combinations of gene feature selection/class prediction algorithms performed similarly well with data of high signal to noise ratio. Gene classifier discovery and application on the basis of individual sampling and sample data pooling, respectively, were found to enhance class predictions. Gene expression profiles of the top gene classifiers, identified from both microarray and quantitative polymerase chain reaction assays, displayed greater similarity between fadrozole and 17beta-trenbolone than either one to 17alpha-ethinylestradiol. These gene classifiers could serve as potential biomarkers of exposure to specific classes of endocrine disruptors.

Discovery and validation of gene classifiers for endocrine-disrupting chemicals in zebrafish (danio rerio)

“…While there are a great number of algorithms available for microarray-based gene classifier discovery, a choice was made to employ a combination of either GA-SVM (genetic algorithm-support vector machines) or GA-KNN (K-nearest neighbors) based on their previous evaluations as being the best and second best performer respectively [20]. GA is a computational approach modeled on biological evolution, incorporating concepts and processes such as genes, chromosomes, selection, recombination, mutation, and fitness [21].…”

Zebrafish: An In Vivo Model for Nano EHS Studies

“…For instance, the transparency of zebrafish embryos makes examination of gene expression level in the whole embryo by RNA in situ hybridization (ISH) possible. Multiple zebrafish microarrays have also been developed to facilitate the rapid and simultaneous assessment of the expression profiles of thousands of genes 33–35. Furthermore, the availability of many zebrafish transgenic lines with fluorescent reporter genes expressed in specific cells/tissues/organs allows direct observation and real‐time monitoring of biological changes in response to nanomaterial exposure in live animals.…”

Adaptation of a Bioinformatics Microarray Analysis Workflow for a Toxicogenomic Study in Rainbow Trout

“…High throughput technologies and molecular biology offer reliable techniques for the detection of these physiological perturbations. Over the past decade, microarrays have been proven as efficient tools to determine the molecular mode of action (MOA) of environmental pollutants and to identify biomarkers as indicators of exposure for ecological risk assessments [ 10 , 11 ].…”

“…Since the establishement of molecular biomarkers, especially transcriptomic alterations, as early-warning signals of contaminants exposure, is needed in environmental monitoring programs, this approach is increasingly used in ecotoxicological studies, and named « (eco)toxicogenomic » [ 12 ]. Despite the gap between genomic knowledge regarding fish and mammals, several studies have used microarrays on fish (including orphan species) as model organisms, especially to monitor the impact of EDCs on gene expression patterns [ 11 , 13 – 16 ]. Microarrays are very powerful tools that can be used to measure the expression of thousands of genes or the whole transcriptome of an organism, in one single experiment, and the resulting expression profile can be compared under many experimental conditions.…”