Fine-scale spatial patterns of antibiotic resistance gene concentrations in irrigation pond water

Antimicrobial resistance (AMR) in irrigation waters is a major worldwide health issue. Crops irrigated with waters containing antibiotic resistant bacteria (ARB) or related genes (ARG) can serve as a vector for AMR throughout food supply systems. The current extent of AMR in irrigation waters is poorly understood and even less so for small lentic waters such as farm ponds. The objectives of this work were to characterize the variability of ARG concentrations in an actively used irrigation pond and to determine if stable spatial patterns in the concentration data exist which can be used to inform monitoring designs. Water sampling was conducted on 9 dates between June and September 2023 at 20 locations within an actively used irrigation pond in Maryland, USA. The ARG tetracycline gene tetA was enumerated using dQPCR in all collected samples. Due to the presence of non-detects, the robust regression on ordered statistics (ROS) method was applied to the dataset to impute non-detectable concentrations on each date. Spatial variation of tetA concentrations was date-dependent with coefficients of variation ranging from 97 % to 377 % with an average of 181 %. Concentrations steadily declined throughout the observation period which significantly correlated with increases in water temperature (r_s = - 0.738; p = 0.023). Rainfall events throughout the observation period did not result in higher concentrations of tetA in the pond. On a majority of dates, significant outliers in the data were identified according to the extreme studentized deviate test.  The mean relative difference analysis revealed that samples collected at the pond banks contained higher tetA concentrations than those collected in the pond interior. Elevated concentrations of the ARG at bank sites were attributed to on-land activities as well as hydrological conditions within the waterbody. Sampling sites were identified that best represented the spatiotemporal average of the concentration data which is useful if large sample sets cannot be collected. This work is the first to evaluate fine-scale spatial variation of ARG in lentic waters used for irrigation and the results show that the choice of where to sample for ARG enumeration in ponds or lakes should not be made arbitrarily.