Effect assessment of the herbicide paraquat on a green alga using differential gene expression and biochemical biomarkersEffect assessment of the herbicide paraquat on a green alga using differential gene expression and biochemical biomarkers
Faculty of Sciences. Biology
Systemic Physiological and Ecotoxicological Research (SPHERE)
2010New York, N.Y., 2010
Environmental toxicology and chemistry. - New York, N.Y.
29(2010):4, p. 893-901
University of Antwerp
Effects of the herbicide paraquat were assessed on the green freshwater alga Chlamydomonas reinhardtii using different endpoints of toxicity. Cell concentration and growth rate were monitored, whereas flow cytometry was applied to determine changes in chlorophyll content, viability and presence of reactive oxygen species. Furthermore, a transcriptomics approach using microarray hybridizations was applied to elucidate the mechanisms of toxicity. The results reveal that paraquat concentrations above 0.25 µM induce toxic effects in C. reinhardtii, reflected in a significantly reduced growth rate and cell concentration with a corresponding median effective concentration (EC50) value of 0.26 µM. With increasing paraquat concentrations, an increase in cell volume was registered with a particle counter as well as in the forward scattering signal of flow cytometric measurements, which is a measure of cell size. Flow cytometry, moreover, showed an increase in reactive oxygen species with increasing exposure concentration, corroborating the general knowledge that this herbicide exerts its toxicity through the generation of oxidative stress. At the same time, several genes involved in oxidative stress defense mechanisms, such as L-ascorbate peroxidase, glutaredoxin, and a possible glutathione-S-transferase were differentially expressed, demonstrating the value of microarrays for elucidating possible mechanisms of toxicity. The fact that several genes were differentially expressed at paraquat concentrations that caused no adverse effects on higher levels of biological organization indicates that a transcriptomics approach allows for the detection of early effects, even before they become manifest at higher levels.