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A multivariate biomarker-based model predicting population-level responses of Daphnia magna
De Coen, W.M.; Janssen, C.R. (2003). A multivariate biomarker-based model predicting population-level responses of Daphnia magna. Environ. Toxicol. Chem. 22(9): 2195-2201
In: Environmental Toxicology and Chemistry. Setac Press: New York. ISSN 0730-7268, more
Peer reviewed article  

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Keywords
    Animal populations; Biomarkers; DNA; Energy metabolism; Pollutants; Prediction; Toxicity; Water pollution; Arthropoda [WoRMS]; Branchiopoda [WoRMS]; Cladocera [WoRMS]; Crustacea [WoRMS]; Daphnia magna Straus, 1820 [WoRMS]; Invertebrata; Fresh water

Authors  Top 
  • De Coen, W.M., more
  • Janssen, C.R., more

Abstract
    A multivariate model is proposed relating short-term biomarker measurements in Daphnia magna to chronic effects (21-d exposure) occurring at the population level (time to death, mean brood size, mean total young per female, intrinsic rate of natural increase, net reproductive rate, and growth). The results of the short-term exposure (48h-96 h) to eight model toxicants (cadmium, chromium, mercury, tributyl tin, linear alkylsulfonic acid, sodium pentachlorophenolate, lindane, and 2,4-dichlorophenoxyacetic acid) on the following biomarkers were used for the multivariate model: digestive enzymes (amylase, cellulase, βgalactosidase, trypsin, and esterase), enzymes of the intermediary metabolism (glycogen phosphorylase, glucose-6-phosphate dehydrogenase, pyruvate kinase, lactate dehydrogenase, and isocitrate dehydrogenase), cellular energy allocation (CEA) (protein, carbohydrate, and lipid content and electron transport activity), and DNA damage and antioxidative stress activity. Using partial least squares to latent structures (PLS), a two-component model was obtained with R2 of 0.68 and a Q2 value of 0.60 based on the combined analysis of a limited number of the 48- and 96-h biomarker responses. For the individual population-level responses, the R2 values varied from 0.66 to 0.77 and the Q2 values from 0.52 to 0.69. Energy-related biomarkers (cellular energy allocation, lipid contents, anaerobic metabolic activity-pyruvate kinase, and lactate dehydrogenase), combined with parameters related to oxidative stress (catalase) and DNA damage measured after 48 and 96 h of exposure, were able to predict long-term effects at higher levels of biological organization.

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