Model Construction and Prediction of Combined Toxicity of Arsenic(V) and Lead(II) on Chlamydomonas reinhardtii.

With the acceleration of industrialization, the impact of the toxic metalloid arsenic (As) and metal lead (Pb) on aquatic ecosystems has garnered widespread concern. However, the specific toxic effects of how these two metals jointly impact aquatic organisms are not yet fully understood. This study aims to investigate the toxic effects of As and Pb individually and in combination of the mixture on the growth of Chlamydomonas reinhardtii (C. reinhardtii) in a lab setup using the Concentration Addition (CA) model and the Independent Action (IA) model to predict the toxic effects at different concentrations. The results indicated that As and Pb had significant inhibitory effects on the growth of algae, and the toxicity of As was greater than that of Pb (As EC50 = 374.87 μg/L, Pb EC50 = 19,988.75 μg/L), measured by Spectrophotometer. As the metal concentrations increased, both metals demonstrated classic sigmoidal concentration-effect curves. Furthermore, we discovered that in mixtures of As and Pb at varying concentration ratios, the combined toxic effect shifted from additive to synergistic with increasing As concentration, exhibiting a pronounced concentration ratio dependency. Utilizing nonlinear least squares regression, we successfully constructed concentration-response models for both As and Pb, employing Observation-based Confidence Intervals (OCIs) to reflect the uncertainty of the data. By comparing experimental data with model predictions, the EC50 was used as an index to compare the toxicity magnitude of As/Pb mixtures. The toxicity of As and Pb mixtures gradually increases with the increase in their concentration ratios. Scanning and transmission electron microscopic observations revealed that the combination of 200 μg/L As and 2000 μg/L Pb resulted in the greatest synergistic toxic effect, with severe breakage and indentation to C. reinhardtii cells. This study not only provided new insights into the environmental behavior and ecological risks of As and Pb but also held significant implications for effective water pollution management strategies by offering a validated model-based framework for predicting mixture toxicity across different concentration regimes.