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Background: A very large and rapidly growing collection of transcriptomic profiles in public repositories is potentially of great value to developing data-driven bioinformatics applications for toxicology/ecotoxicology. Modeled on human connectivity mapping (Cmap) in biomedical research, this study was undertaken to investigate the utility of an analogous Cmap approach in ecotoxicology. Over 3500 zebrafish (Danio rerio) and fathead minnow (Pimephales promelas) transcriptomic profiles, each associated with one of several dozen chemical treatment conditions, were compiled into three distinct collections of rank-ordered gene lists (ROGLs) by species and microarray platforms. Individual query signatures, each consisting of multiple gene probes differentially expressed in a chemical condition, were used to interrogate the reference ROGLs.

Results: Informative connections were established at high success rates within species when, as defined by their mechanisms of action (MOAs), both query signatures and ROGLs were associated with the same or similar chemicals. Thus, a simple query signature functioned effectively as an exposure biomarker without need for a time-consuming process of development and validation. More importantly, a large reference database of ROGLs also enabled a query signature to cross-interrogate other chemical conditions with overlapping MOAs, leading to novel groupings and subgroupings of seemingly unrelated chemicals at a finer resolution. This approach confirmed the identities of several estrogenic chemicals, as well as a polycyclic aromatic hydrocarbon and a neuro-toxin, in the largely uncharacterized water samples near several waste water treatment plants, and thus demonstrates its future potential utility in real world applications.

Conclusions: The power of Cmap should grow as chemical coverages of ROGLs increase, making it a framework easily scalable in the future. The feasibility of toxicity extrapolation across fish species using Cmap needs more study, however, as more gene expression profiles linked to chemical conditions common to multiple fish species are needed.