Abstract
The determination of the chronic toxicity is time-consumed and costly, so it’s of great interest to predict the chronic toxicity based on acute data. Current methods include the acute to chronic ratios (ACRs) and the QSTR models, both of which have some usage limitations. In this paper, the acute and chronic mixture toxicity of three types of antibiotics, namely sulfonamides, sulfonamide potentiators and tetracyclines, were determined by a bioluminescence inhibition test. A novel QSTR model was developed for predicting the chronic mixture toxicity using the acute data and docking-based descriptors. This model revealed a complex relationship between the acute and chronic toxicity, i.e. a linear correlation between the acute and chronic lg(−lgEC50)s, rather than the simple EC50s or −lgEC50s. In particular, the interaction energies (Ebind) of the chemicals with luciferase and LitR in the bacterial quorum sensing systems were introduced to represent their acute and chronic actions, respectively, regardless of their defined toxic mechanisms. Therefore, the present QSTR model can apply to the chemicals with distinct toxic mechanisms, as well as those with undefined mechanism. This study provides a novel idea for the acute to chronic toxicity extrapolation, which may benefit the environmental risk assessment on the pollutants.
Highlights
At present, the acute to chronic toxicity ratios (ACRs) are commonly used for acute to chronic toxicity extrapolation
The chronic −lgEC50s were greater than the acute ones, indicating a greater action of the antibiotics on the bacteria during the chronic test
The acute and chronic toxicity of the chemicals were determined based on a bioluminescence inhibition test, the detailed procedure was as follows: first, the chemicals were prepared into a series of solutions and added into the diluted bacteria suspension that has been cultured to exponential growth phase
Summary
The acute to chronic toxicity ratios (ACRs) are commonly used for acute to chronic toxicity extrapolation. It is assumed that the ACR of a certain chemical is a constant for different species, which is calculated using the observed acute and chronic toxicity data with one species and used to predict the chronic toxicity for another that is exposed to the same chemical[4]. This method is easy to perform and has been used in deriving US National Ambient Water Quality Criteria (NAWQC)[5] as well as in risk assessments in many countries[6]. Few of the researches consider the chronic effects at the population level from the chemical ecology perspective, e.g. the potential effects of the chemicals on the bacterial quorum sensing (QS) systems
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