Stormwater loadings of antibiotic resistance genes in an urban stream.

Antibiotic resistance presents a critical public health challenge and the transmission of antibiotic resistance via environmental pathways continues to gain attention. Factors driving the spread of antibiotic resistance genes (ARGs) in surface water and sources of ARGs in urban stormwater have not been well-characterized. In this study, five ARGs (sul1, sul2, tet(O), tet(W), and erm(F)) were quantified throughout the duration of three storm runoff events in an urban inland stream. Storm loads of all five ARGs were significantly greater than during equivalent background periods. Neither fecal indicator bacteria measured (E. coli or enterococci) was significantly correlated with sul1, sul2, or erm(F), regardless of whether ARG concentration was absolute or normalized to 16S rRNA levels. Both E. coli and enterococci were correlated with the tetracycline resistance genes, tet(O) and tet(W). Next-generation shotgun metagenomic sequencing was conducted to more thoroughly characterize the resistome (i.e., full complement of ARGs) and profile the occurrence of all ARGs described in current databases in storm runoff in order to inform future watershed monitoring and management. Between 37 and 121 different ARGs were detected in each stream sample, though the ARG profiles differed among storms. This study establishes that storm-driven transport of ARGs comprises a considerable fraction of overall downstream loadings and broadly characterizes the urban stormwater resistome to identify potential marker ARGs indicative of impact.

Storm loads of culturable and molecular fecal indicators in an inland urban stream.

Elevated concentrations of fecal indicator bacteria in receiving waters during wet-weather flows are a considerable public health concern that is likely to be exacerbated by future climate change and urbanization. Knowledge of factors driving the fate and transport of fecal indicator bacteria in stormwater is limited, and even less is known about molecular fecal indicators, which may eventually supplant traditional culturable indicators. In this study, concentrations and loading rates of both culturable and molecular fecal indicators were quantified throughout six storm events in an instrumented inland urban stream. While both concentrations and loading rates of each fecal indicator increased rapidly during the rising limb of the storm hydrographs, it is the loading rates rather than instantaneous concentrations that provide a better estimate of transport through the stream during the entire storm. Concentrations of general fecal indicators (both culturable and molecular) correlated most highly with each other during storm events but not with the human-associated HF183 Bacteroides marker. Event loads of general fecal indicators most strongly correlated with total runoff volume, maximum discharge, and maximum turbidity, while event loads of HF183 most strongly correlated with the time to peak flow in a hydrograph. These observations suggest that collection of multiple samples during a storm event is critical for accurate predictions of fecal indicator loading rates and total loads during wet-weather flows, which are required for effective watershed management. In addition, existing predictive models based on general fecal indicators may not be sufficient to predict source-specific genetic markers of fecal contamination.