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

## TL;DR

This study creates a model to predict how environmental factors affect the toxicity of pentachlorophenol on E. coli, improving bioassay accuracy in real-world conditions.

## Contribution

A novel predictive algorithm is developed to account for environmental variables in assessing PCP toxicity on E. coli.

## Key findings

- A predictive model was developed and validated with strong correlation (r2 ≈ 0.9) between experimental and predicted PCP toxicity.
- Environmental factors pH, temperature, and conductivity significantly influence PCP toxicity on E. coli.
- The model offers an alternative to conventional models by incorporating real-world environmental complexities.

## Abstract

Evaluating the impact of pollutants on ecosystems and human health is crucial. To achieve this, a wide range of bioassays, using organisms of different trophic levels, are available. Extrapolating the results of these bioassays to real environmental conditions remains a major challenge. This study addresses this challenge by aiming to develop an algorithm capable of predicting the effect of environmental conditions on the impact of a toxicant, pentachlorophenol (PCP). Three abiotic factors were considered: pH, temperature, and conductivity. In the absence of the toxicant, the activity of Escherichia coli is influenced only by pH and temperature. However, exposed to PCP, the sensitivity of the bacteria was affected by these three factors. From these data, a predictive model was established to assess the intensity of the toxic effect induced by PCP. This model was validated using a validation dataset 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. This proof of concept constitutes a potential alternative, complementary to conventional models like BLMs (focused on water chemistry for metals) and QSARs (linking structure to intrinsic toxicity), which often overlook the complexities of real-world environmental conditions.