Physiological and molecular effect assessment versus physico-chemistry based mode of action schemes: Daphnia magna exposed to narcotics and polar narcotics
| Autor: | Dries Knapen, Tine Vandenbrouck, Ronny Blust, Lucia Vergauwen, Mieke Jansen, Nathalie Dom |
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| Rok vydání: | 2011 |
| Předmět: |
Narcotics
Chemical Phenomena Transcription Genetic Energy reserves Daphnia magna Classification scheme Computational biology Environmental Chemistry Animals Cluster Analysis RNA Messenger Least-Squares Analysis Mode of action Biology Environmental risk assessment Biological data biology Chemistry Gene Expression Profiling General Chemistry Chemical similarity Environmental Exposure biology.organism_classification Effect assessment Daphnia Environmental chemistry Energy Metabolism Engineering sciences. Technology |
| Zdroj: | Environmental science and technology |
| ISSN: | 1520-5851 0013-936X |
| Popis: | Structural analogues are assumed to elicit toxicity via similar predominant modes of action (MOAs). Currently, MOA categorization of chemicals in environmental risk assessment is mainly based on the physicochemical properties of potential toxicants. It is often not known whether such classification schemes are also supported by mechanistic biological data. In this study, the toxic effects of two groups of structural analogues (alcohols and anilines) with predefined MOA (narcotics and polar narcotics) were investigated at different levels of biological organization (gene transcription, energy reserves, and growth). Chemical similarity was not indicative of a comparable degree of toxicity and a similar biological response. Categorization of the test chemicals based on the different biological responses (growth, energy use, and gene transcription) did not result in a classification of the predefined narcotics versus the predefined polar narcotics. Moreover, gene transcription based clustering profiles were indicative of the observed effects at higher level of biological organization. Furthermore, a small set of classifier genes could be identified that was discriminative for the clustering pattern. These classifier genes covaried with the organismal and physiological responses. Compared to the physico-chemistry based MOA classification, integrated biological multilevel effect assessment can provide the necessary MOA information that is crucial in high-quality environmental risk assessment. Our findings support the view that transcriptomics tools hold considerable promise to be used in biological response based mechanistic profiling of potential (eco)toxicants. |
| Databáze: | OpenAIRE |
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