Sewage treatment plants (STPs) accumulate both antibiotic and nonantibiotic antimicrobial compounds that can select for antibiotic resistant bacteria. Herein, we aimed to identify the predominant antibacterial compounds impacting E. coli from Ontario sewage sludge consisting of thousands of unknown compounds. Among the 10 extracted sludge samples, 6 extracts exerted significant growth inhibition effects in E. coli. A total of 103 compounds were tentatively detected across the 10 sludge samples by suspect screening, among which the bacterial enoyl-ACP reductase (FabI) inhibitor triclocarban was detected at the highest abundance. A hypomorphic FabI knockdown E. coli strain was highly susceptible to the sludge extracts, confirming FabI inhibitors as the primary antibacterial compounds in the sludge. Protein affinity pulldown identified triclosan as the major ligand binding to a His-tagged FabI protein from the sludge, despite the higher abundance of triclocarban in the same samples. Effect-directed analysis was used to determine the contributions of triclosan to the observed antibacterial potencies. Antibacterial effects were only detected in F17 and F18 across 20 fractions, which was consistent with the elution of triclosan and triclocarban in the same two fractions. Further, potency mass balance analysis confirmed that triclosan explained the majority (58–113%) of inhibition effects from sludge extracts. This study highlighted triclosan as the predominant antibacterial compound in sewage sludge impacting E. coli despite the co-occurrence of numerous other antibiotics and nonantibiotics.

Surveillance of antibiotic resistance genes (ARGs) has been increasingly conducted in environmental sectors to complement the surveys in human and animal sectors under the “One-Health” framework. However, there are substantial challenges in comparing and synthesizing the results of multiple studies that employ different test methods and approaches in bioinformatic analysis. In this article, we consider the commonly used quantification units (ARG copy per cell, ARG copy per genome, ARG density, ARG copy per 16S rRNA gene, RPKM, coverage, PPM, etc.) for profiling ARGs and suggest a universal unit (ARG copy per cell) for reporting such biological measurements of samples and improving the comparability of different surveillance efforts.

This study aimed to provide a low-cost technique for virus detection in wastewater by improving an aluminum hydroxide adsorption–precipitation method. The releasing efficiency of viruses trapped by the aluminum hydroxide precipitates was improved by adding ethylenediaminetetraacetic acid disodium salt (EDTA-2Na) to dissolve the precipitates at a Na 2 EDTA·2H 2 O:AlCl 3 molar ratio of 1.8–3.6. The recovery rates of the improved method for seven viruses, including SARS-CoV-2-abEN pseudovirus and six animal viruses, were 5.9–22.3% in tap water and 4.9–35.1% in wastewater. Rotavirus A (9.0–4.5 × 10 3 copies/mL), porcine circovirus type 2 (5.8–6.4 × 10 5 copies/mL), and porcine parvovirus (5.6–2.7 × 10 4 copies/mL) were detected in China’s pig farm wastewater, while rotavirus A (2.0 × 10 3 copies/mL) was detected in hospital wastewater. SARS-CoV-2 was detected in hospital wastewater (8.4 × 10 2 to 1.4 × 10 4 copies/mL), sewage (6.4 × 10 to 2.3 × 10 3 copies/mL), and river water (6.6 × 10 to 9.3 × 10 copies/mL) in Nepal. The method was automized, with a rate of recovery of 4.8 ± 1.4% at a virus concentration of 10 2 copies/mL. Thus, the established method could be used for wastewater-based epidemiology with sufficient sensitivity in coping with the COVID-19 epidemic and other virus epidemics.