1738 Gene Expression Profile Analysis and Environmental Contaminant Exposure

Saturday, February 20, 2010: 9:10 AM
Room 6D (San Diego Convention Center)
Kevin Chipman , University of Birmingham, Birmingham, United Kingdom
Carson’s “Silent Spring” almost 50 years ago was a turning point in awareness of the need to protect the environment from chemicals that have the potential to cause ecological and human harm. However for many subsequent years the methods for assessing the impact of pollutants on organisms was limited to rather crude, insensitive end points. Over the last decade, the rapid expansion of knowledge about gene sequence and function, coupled with “omic” and associated mathematical modeling technologies has provided an unprecedented opportunity to transform environmental monitoring into mechanism-based and sensitive early-warning alerts that can be prognostic and diagnostic of adverse effects. It is the simultaneous monitoring of many of the activities of cells that will provide a more complete “systems” approach to toxicology and to help in understnading modes of toxic action. The focus is thus moving away from measurement of severe acute lethal effects which might leave uncovered detrimental effects on populations,  to protecting against more subtle chronic disturbance  of organismal function.Since many pollutants enter aquatic environments (see Halpern BS et. al. 2008, Science, 319, 948-952) much work has focussed on fish. Transcriptomic analyses and associated bioinformatic interogation can reveal the complex responses (in addition to e.g. the expected oxidative stress) in fish exposed to metals. Copper exposure in fish, for example, can produce a gene expression profile that simulates Wilson’s disease in humans indicating the relationship between pollutant exposure and known disease mechanisms. Fish from different environments clearly have different gene expression profiles for many reasons. However,  we have found that a sub-group of stress-related genes (identified from gene expression analyses following treatment of fish with pollutants under laboratory conditions) can be predictive of the environmental source of fish depending upon their levels of pollution exposure in their environments (Falciani et. al. 2008, Aquatic Toxicology, 90, 92-101). Interrogation of gene expression networks can reveal associations between key nodes of the network with  health-related parameters.  Thus expression profiles have potential utilisation as complex monitoring biomarkers, more informative  than conventional single gene product biomarkers which lack specificity. Collaboration between academia, government regulatory bodies and industry is now extensive internationally to ensure a coordinated development of these novel strategies to contribute to environmental safety.