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Environ Sci Technol. 2007 Feb 15;41(4):1085-96.

Microevolution and ecotoxicology of metals in invertebrates.

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1
Cardiff School of Biosciences, Cardiff University, Cardiff, UK. MorganAJ1@cardiff.ac.uk

Abstract

Risk assessment of metal-contaminated habitats based on responses in the field is complicated by the evolution of local, metal-resistant ecotypes. The unpredictability of occurrence of genetically determined adaptive traits, in terms of site-specific geochemistry, a population's inferred exposure history, and in the physiology of resistance, exacerbates the problem. Micro-evolutionary events warrant the attention of ecotoxicologists because they undermine the application of the bedrock of toxicology, the dose-response curve, to in situ field assessments. Here we survey the evidence for the existence of genetically differentiated, metal-resistant, invertebrate populations; we also describe some of the molecular mechanisms underpinning the adaptations. Quantitative changes in tissue-metal partitioning, and in the molecular and cellular responses (biomarkers)to alterations in internal bioreactive metal pools, are widely accepted as indicators of toxicity and/or exposure in free-living organisms. Both can be modulated by resistance. The understanding that all genomes are intrinsicallyflexible, with subtle sequence changes in promoter regions or epigenetic adjustments conferring significant phenotypic consequences, is deemed highly relevant. Equally relevant is the systems biology insight that genes and proteins are woven into networks. We advocate that biomarker studies should work toward assimilating and exploiting these biological realities through monitoring the activities of suites of genes (transcriptomics) and their expressed products (proteomics), as well as profiling the metabolite signatures of individuals (metabolomics) and by using neutral genetic markers to genotype populations. Ecotoxicology requires robust tools that recognize the imprint of evolution on the constitution of field populations, as well as sufficient mechanistic understanding of the molecular-genetic observations to interpret them in meaningful environmental diagnostic ways.

PMID:
17593704
[Indexed for MEDLINE]
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