Prediction of Influence of Environmental Factors on the Toxicity of Pentachlorophenol on E.coli-Based Bioassay

Evaluating the impact of pollutants on ecosystems and human health is crucial. To achieve this, a wide range of bioassays, using organisms representative of different trophic levels, are available. However, extrapolating the results of these bioassays to real environmental conditions remains a major challenge. Indeed, how can a toxicity value obtained under controlled laboratory conditions be transposed to an often very different environment? This study specifically addresses this challenge by aiming to develop an algorithm capable of predicting the effect of environmental conditions on the impact of a toxic compound, Pentachlorophenol (PCP). To achieve this, three abiotic factors were considered: pH, temperature, and conductivity. Firstly, the study highlighted the effect of these factors on the biological activity of Escherichia coli. In the absence of the toxicant, pH and temperature are the only factors that significantly influence the activity of this bioindicator. However, when exposed to PCP, the results showed that the sensitivity of the bacteria was affected by pH and conductivity, but not by temperature. From this data, a predictive model was established to assess the intensity of the toxic effect induced by PCP under conditions other than those used in the laboratory test. This model was validated using a dataset of 384 supplementary experiments and demonstrated a strong correlation between the experimental and predicted values (r²≈0.9). Thus, this approach enables the effective prediction of PCP's effects by accounting for environmental variations.