Catchment-scale export of antibiotic resistance genes and bacteria from an agricultural watershed in central Iowa

Simultaneous stream assessment of antibiotics, bacteria, antibiotic resistant bacteria, and antibiotic resistance genes in an agricultural region of the United States

Antimicrobial resistance (AMR) is now recognized as a leading global threat to human health. Nevertheless, there currently is a limited understanding of the environment's role in the spread of AMR and antibiotic resistance genes (ARGs). In 2019, the U.S. Geological Survey conducted the first statewide assessment of antibiotic resistant bacteria (ARB) and ARGs in surface water and bed sediment collected from 34 stream locations across Iowa. Environmental samples were analyzed for a suite of 29 antibiotics and plated on selective media for 15 types of bacteria growth; DNA was extracted from culture growth and used in downstream polymerase chain reaction (PCR) assays for the detection of 24 ARGs. ARGs encoding resistance to antibiotics of clinical importance to human health and disease prevention were prioritized as their presence in stream systems has the potential for environmental significance. Total coliforms, Escherichia coli (E. coli), and staphylococci were nearly ubiquitous in both stream water and stream bed sediment samples, with enterococci present in 97 % of water samples, and Salmonella spp. growth present in 94 % and 67 % of water and bed sediment samples. Bacteria enumerations indicate that high bacteria loads are common in Iowa's streams, with 23 (68 %) streams exceeding state guidelines for primary contact for E. coli in recreational waters and 6 (18 %) streams exceeding the secondary contact advisory level. Although antibiotic-resistant E. coli growth was detected from 40 % of water samples, vancomycin-resistant enterococci (VRE) and penicillinase-resistant Staphylococcus aureus (MRSA) colony growth was detected from nearly all water samples. A total of 14 different ARGs were detected from viable bacteria cells from 30 Iowa streams (88 %, n = 34). Study results provide the first baseline understanding of the prevalence of ARB and ARGs throughout Iowa's waterways and health risk potential for humans, wildlife, and livestock using these waterways for drinking, irrigating, or recreating.

A geospatial approach to identify patterns of antibiotic susceptibility at a neighborhood level in Wisconsin, United States

The global threat of antimicrobial resistance (AMR) varies regionally. This study explores whether geospatial analysis and data visualization methods detect both clinically and statistically significant variations in antibiotic susceptibility rates at a neighborhood level. This observational multicenter geospatial study collected 10 years of patient-level antibiotic susceptibility data and patient addresses from three regionally distinct Wisconsin health systems (UW Health, Fort HealthCare, Marshfield Clinic Health System [MCHS]). We included the initial Escherichia coli isolate per patient per year per sample source with a patient address in Wisconsin (N = 100,176). Isolates from U.S. Census Block Groups with less than 30 isolates were excluded (n = 13,709), resulting in 86,467 E. coli isolates. The primary study outcomes were the results of Moran's I spatial autocorrelation analyses to quantify antibiotic susceptibility as spatially dispersed, randomly distributed, or clustered by a range of - 1 to + 1, and the detection of statistically significant local hot (high susceptibility) and cold spots (low susceptibility) for variations in antibiotic susceptibility by U.S. Census Block Group. UW Health isolates collected represented greater isolate geographic density (n = 36,279 E. coli, 389 = blocks, 2009-2018), compared to Fort HealthCare (n = 5110 isolates, 48 = blocks, 2012-2018) and MCHS (45,078 isolates, 480 blocks, 2009-2018). Choropleth maps enabled a spatial AMR data visualization. A positive spatially-clustered pattern was identified from the UW Health data for ciprofloxacin (Moran's I = 0.096, p = 0.005) and trimethoprim/sulfamethoxazole susceptibility (Moran's I = 0.180, p < 0.001). Fort HealthCare and MCHS distributions were likely random. At the local level, we identified hot and cold spots at all three health systems (90%, 95%, and 99% CIs). AMR spatial clustering was observed in urban areas but not rural areas. Unique identification of AMR hot spots at the Block Group level provides a foundation for future analyses and hypotheses. Clinically meaningful differences in AMR could inform clinical decision support tools and warrants further investigation for informing therapy options.

Antimicrobial resistance in integrated agroecosystems: State of the science and future opportunities

As the Journal of Environmental Quality (JEQ) celebrates 50 years of publication, the division of environmental microbiology is one of the newest additions to the journal. During this time, significant advances in understanding of the interconnected microbial community and impact of the microbiome on natural and designed environmental systems have occurred. In this review, we highlight the intractable challenge of antimicrobial resistance (AMR) on humans, animals, and the environment, with particular emphasis on the role of integrated agroecosystems and by highlighting contributions published in JEQ. From early studies of phenotypic resistance of indicator organisms in waters systems to current calls for integrating AMR assessment across "One Health," publications in JEQ have advanced our understanding of AMR. As we reflect on the state of the science, we emphasize future opportunities. First, integration of phenotypic and molecular tools for assessing environmental spread of AMR and human health risk continues to be an urgent research need for a one health approach to AMR. Second, monitoring AMR levels in manure is recommended to understand inputs and potential spread through agroecosystems. Third, baseline knowledge of AMR levels is important to realize the impact of manure inputs on water quality and public health risk; this can be achieved through background monitoring or identifying the source-related genes or organisms. And finally, conservation practices designed to meet nutrient reduction goals should be explored for AMR reduction potential.

Twenty-first century molecular methods for analyzing antimicrobial resistance in surface waters to support One Health assessments

Antimicrobial resistance (AMR) in the environment is a growing global health concern, especially the dissemination of AMR into surface waters due to human and agricultural inputs. Within recent years, research has focused on trying to understand the impact of AMR in surface waters on human, agricultural and ecological health (One Health). While surface water quality assessments and surveillance of AMR have historically utilized culture-based methods, culturing bacteria has limitations due to difficulty in isolating environmental bacteria and the need for a priori information about the bacteria for selective isolation. The use of molecular techniques to analyze AMR at the genetic level has helped to overcome the difficulties with culture-based techniques since they do not require advance knowledge of the bacterial population and can analyze uncultivable environmental bacteria. The aim of this review is to provide an overview of common contemporary molecular methods available for analyzing AMR in surface waters, which include high throughput real-time polymerase chain reaction (HT-qPCR), metagenomics, and whole genome sequencing. This review will also feature how these methods may provide information on human and animal health risks. HT-qPCR works at the nanoliter scale, requires only a small amount of DNA, and can analyze numerous gene targets simultaneously, but may lack in analytical sensitivity and the ability to optimize individual assays compared to conventional qPCR. Metagenomics offers more detailed genomic information and taxonomic resolution than PCR by sequencing all the microbial genomes within a sample. Its open format allows for the discovery of new antibiotic resistance genes; however, the quantity of DNA necessary for this technique can be a limiting factor for surface water samples that typically have low numbers of bacteria per sample volume. Whole genome sequencing provides the complete genomic profile of a single environmental isolate and can identify all genetic elements that may confer AMR. However, a main disadvantage of this technique is that it only provides information about one bacterial isolate and is challenging to utilize for community analysis. While these contemporary techniques can quickly provide a vast array of information about AMR in surface waters, one technique does not fully characterize AMR nor its potential risks to human, animal, or ecological health. Rather, a combination of techniques (including both molecular- and culture-based) are necessary to fully understand AMR in surface waters from a One Health perspective.

Seasonal variations in export of antibiotic resistance genes and bacteria in runoff from an agricultural watershed in Iowa

Seasonal variations of antimicrobial resistance (AMR) indicators in runoff water can help improve our understanding of AMR sources and transport within an agricultural watershed. This study aimed to monitor multiple areas throughout the Black Hawk Lake (BHL) watershed (5324 ha) in central Iowa during 2017 and 2018 that consists of both swine and cattle feeding operations as well as known areas with manure application. The measured indicators included plate counts for fecal indicator bacteria (FIB) E. coli, Enterococcus, antibiotic resistant fecal indicator bacteria (ARBs) tylosin resistant Enterococcus, tetracycline resistant Enterococcus, and antibiotic resistance genes (ARGs): ermB, ermF (macrolide), tetA, tetM, tetO, tetW (tetracycline), sul1, sul2 (sulfonamide), aadA2 (aminoglycoside), vgaA, and vgaB (pleuromutilin). Both the plate count and the ARG analyses showed seasonal trends. Plate counts were significantly greater during the growing season, while the ARGs were greater in the pre-planting and post-harvest seasons (Wilcoxon Rank-Sum Test p < 0.05). The ermB gene concentration was significantly correlated (p < 0.05) with E. coli and Enterococcus concentrations in 2017, suggesting a potential use of this ARG as an indicator of environmental AMR and human health risk. Flow rate was not a significant contributor to annual variations in bacteria and AMR indicators. Based on observed seasonal patterns, we concluded that manure application was the likely contributor to elevated ARG indicators observed in the BHL watershed, while the driver of elevated ARB indictors in the growing season can only be speculated. Understanding AMR export patterns in agricultural watersheds provides public health officials knowledge of seasonal periods of higher AMR load to recreational waters.