Quantifying and predicting antimicrobials and antimicrobial resistance genes in waterbodies through a holistic approach: a study in Minnesota, United States

Abstract

The environment plays a key role in the spread and persistence of antimicrobial resistance (AMR). Antimicrobials and antimicrobial resistance genes (ARG) are released into the environment from sources such as wastewater treatment plants, and animal farms. This study describes an approach guided by spatial mapping to quantify and predict antimicrobials and ARG in Minnesota’s waterbodies in water and sediment at two spatial scales: macro, throughout the state, and micro, in specific waterbodies. At the macroscale, the highest concentrations across all antimicrobial classes were found near populated areas. Kernel interpolation provided an approximation of antimicrobial concentrations and ARG abundance at unsampled locations. However, there was high uncertainty in these predictions, due in part to low study power and large distances between sites. At the microscale, wastewater treatment plants had an effect on ARG abundance (sul1 and sul2 in water; blaSHV, intl1, mexB, and sul2 in sediment), but not on antimicrobial concentrations. Results from sediment reflected a long-term history, while water reflected a more transient record of antimicrobials and ARG. This study highlights the value of using spatial analyses, different spatial scales, and sampling matrices, to design an environmental monitoring approach to advance our understanding of AMR persistence and dissemination.

Determination of the Antibiotic and Antibiotic Resistance Footprint in Surface Water Environments of a Metropolitan Area: Effects of Anthropogenic Activities

“…29,63 Missing environmental parameters at certain sampling sites were imputed using the mean value of each parameter across the samples. 31 Spearman correlation analysis was performed to assess the association of antibiotic concentrations, ARG concentrations/relative abundances, or the number of detected antibiotic/ARG types with environmental (water physicochemical properties and sediment LOI information) and anthropogenic factors. Nonmetric multidimensional scaling (NMDS) analysis was performed on antibiotic concentration data (prior to log 10 transformation) to determine dissimilarity (Bray−Curtis) among the sampling locations; and for the S11.…”

“…Water samples had to be taken from docks or piers rather than small watercraft, which would have required two people. The methodology previously developed to collect biomass for ARG quantification required ultrafiltration of water using a generator-powered peristaltic pump system in the field . This was not possible under the social distancing and travel limitations that were in place, and we deemed it unsafe for a single person to carry the generator to the field or volume of water needed back to the lab.…”

“…Detailed procedures of DNA extraction and qPCR assays are provided in Text S5. The targeted genes were selected based on prior observations for various aquatic compartments in MN, ,, which include (i) a total of 20 ARGs encoding resistance to sulfonamides, erythromycin and other macrolides, tetracyclines, ampicillin and broad-spectrum β-lactams, quinolones, streptomycin, vancomycin, quaternary ammonia compounds, and multidrugs via efflux pumps; (ii) integron-integrase genes associated with horizontal gene transfer; and (iii) the 16S ribosomal RNA (rRNA) gene for assessment of total biomass levels in the sediments. A full list of the target genes and primer sequences for qPCR amplicons (obtained from previous studies ,− ) are presented in Table S5.…”

“…Antibiotic concentrations, ARG concentrations, and ARG relative abundances were log 10 transformed with the nondetects (defined as no signal or below MDLs) replaced with 1/2 of MDLs to allow statistical analysis of left-censored data . To avoid biasing the analysis results due to substitution, the target compounds or genes with frequencies <60% were excluded to ensure low degree of censoring (≤40%) unless otherwise specified. , Missing environmental parameters at certain sampling sites were imputed using the mean value of each parameter across the samples . Spearman correlation analysis was performed to assess the association of antibiotic concentrations, ARG concentrations/relative abundances, or the number of detected antibiotic/ARG types with environmental (water physicochemical properties and sediment LOI information) and anthropogenic factors.…”

“…To test the above research questions, multiple statistical approaches were used to investigate associations of antibiotic and ARG occurrences and concentrations with the selected anthropogenic factors. These factors were extracted from Geographic Information System (GIS) databases using watershed boundaries 30 or a buffer zone with defined radius 31 to evaluate which provided more useful information. Parameters characterizing water and sediment properties were also evaluated for their relation to the antibiotic/ARG results.…”