Similarities and differences in combined toxicity of sulfonamides and other antibiotics towards bacteria for environmental risk assessment.

Antibiotics as a type of environmental contaminants are typically exposed to chemical mixtures over long periods of time, so chronic combined toxicity is the best way to perform an environmental risk assessment. In this paper, the individual and combined toxicity of sulfonamides (SAs), sulfonamide potentiators (SAPs), and doxycycline hyclate (DH) were tested on gram-positive (Bacillus subtilis, B. subtilis) and gram-negative (Escherichia coli, E. coli) bacteria. The individual toxicity of antibiotics on the two bacteria could be ranked in the same order: SAs < SAPs < DH. But E. coli was more sensitive than B. subtilis to the antibiotics, which was likely due to both the different abilities of antibiotics to pass through the cell membrane and the varied capacities to bind target proteins between the two bacteria. In addition, the binary mixtures of SAs-SAPs, SAs-DH, and SAs-SAs exhibited synergistic, antagonistic, and additive effects on both of the bacteria but in different magnitudes as represented by the toxicity units (TU). And we found the different TU values were result from the different effective concentrations of antibiotic mixtures based on the approach of molecular docking and quantitative structure-activity relationships (QSARs). Moreover, from the results of risk assessment, it should be noted that the mixture of SAs and other antibiotics may pose a potential environmental risk assessment due to their combined action with the current environmentally realistic concentrations.

Novel approach for predicting the joint effects based on the enzyme-catalyzed kinetics.

Organisms are exposed to mixtures of multiple contaminants and it is necessary to build prediction models for the joint effects, considering the high expense and the complexity of the traditional toxicity testing and the flood occurrence of environmental chemical pollutants. In this study, a new method for predicting the joint effects was developed and corresponding prediction models were constructed based on the kinetic models of enzyme-catalyzed reactions. While, we utilized Vibrio fischeri, Escherichia coli and Bacillus subtilis as model organisms and determined the chronic toxicity of the binary mixtures of sulfonamides (SAs) and sulfonamide potentiators (SAPs) (SA+SAP), the mixtures of two kinds of sulfonamides (SA+SA) and the binary mixtures of sulfonamide potentiators (SAPs) and tetracyclines (TCs) (SAP+TC) respectively. Finally, corresponding mixture toxicity data was utilized to fit and verify the prediction models for different joint effects.