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The release of a wide variety of persistent chemical contaminants into wastewater has become a growing concern due to their potential health and environmental risks. While the toxic effects of these pollutants on aquatic organisms have been extensively studied, their impact on microbial pathogens and their virulence mechanisms remains largely unexplored. This research paper focuses on the identification and prioritization of chemical pollutants that increase bacterial pathogenicity, which is a public health concern. In order to predict how chemical compounds, such as pesticides and pharmaceuticals, would affect the virulence mechanisms of three bacterial strains (Escherichia coli K12, Pseudomonas aeruginosa H103, and Salmonella enterica serovar. Typhimurium), this study has developed quantitative structure–activity relationship (QSAR) models. The use of analysis of variance (ANOVA) functions assists in developing QSAR models based on the chemical structure of the compounds, to predict their effect on the growth and swarming behavior of the bacterial strains. The results showed an uncertainty in the created model, and that increases in virulence factors, including growth and motility of bacteria, after exposure to the studied compounds are possible to be predicted. These results could be more accurate if the interactions between groups of functions are included. For that, to make an accurate and universal model, it is essential to incorporate a larger number of compounds of similar and different structures.

The ability of WWTP outflow bacteria at colonizing rock surfaces and contributing to the formation of river epilithic biofilms was investigated. Bacterial community structures of biofilms (b-) developing on rocks exposed to treated wastewaters (TWW) of a hospital (HTWW) and a domestic (DTWW) clarifier, and to surface waters of the stream located at 10 m, 500 m, and 8 km from the WWTP outlet, were compared. Biofilm bacterial contents were analyzed by cultural approaches and a tpm-based DNA metabarcoding analytical scheme. Co-occurrence distribution pattern analyses between bacterial datasets and eighteen monitored pharmaceuticals were performed. Higher concentrations of iohexol, ranitidine, levofloxacin, and roxithromycin were observed in the b-HTWW while atenolol, diclofenac, propranolol, and trimethoprim were higher in the b-DTWW. MPN growth assays showed recurrent occurrences of Pseudomonas aeruginosa and Aeromonas caviae among these biofilms. An enrichment of multi-resistant P. aeruginosa cells was observed in the hospital sewer line. P. aeruginosa MPN values were negatively correlated to roxithromycin concentrations. The tpm DNA metabarcoding analyses confirmed these trends and allowed an additional tracking of more than 90 species from 24 genera. Among the recorded 3082 tpm ASV (amplicon sequence variants), 41% were allocated to the Pseudomonas. Significant differences through ANOSIM and DESeq2 statistical tests were observed between ASV recovered from b-HTWW, b-DTWW, and epilithic river biofilms. More than 500 ASV were found restricted to a single sewer line such as those allocated to Aeromonas popoffii and Stenotrophomonas humi being strictly found in the b-HTWW file. Several significant correlations between tpm ASV counts per species and pharmaceutical concentrations in biofilms were recorded such as those of Lamprocystis purpurea being positively correlated with trimethoprim concentrations. A tpm source tracking analysis showed the b-DTWW and b-HTWW tpm ASV to have contributed, respectively, at up to 35% and 2.5% of the epilithic river biofilm tpm-taxa recovered downstream from the WWTP outlet. Higher contributions of TWW taxa among epilithic biofilms were recorded closer to the WWTP outlet. These analyses demonstrated a coalescence of WWTP sewer communities with river freshwater taxa among epilithic biofilms developing downstream of a WWTP outlet.