Conspectus Antimicrobial resistance (AMR) is one of the greatest threats faced by humankind. The development of resistance in clinical and hospital settings has been well documented ever since the initial discovery of penicillin and the subsequent introduction of sulfonamides as clinical antibiotics. In contrast, the environmental (i.e., community-acquired) dimensions of resistance dissemination have been only more recently delineated. The global spread of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) between air, water, soil, and food is now well documented, while the factors that affect ARB and ARG dissemination (e.g., water and air quality, antibiotic fluxes, urbanization, sanitation practices) in these and other environmental matrices are just now beginning to be more fully appreciated. In this Account, we discuss how the global perpetuation of resistance is dictated by highly interconnected socioeconomic risk factors and illustrate that development status should be more fully considered when developing global strategies to address AMR. We first differentiate low to middle income countries (LMICs) and high-income countries (HICs), then we summarize the modes of action of commercially available antibiotics, and then discuss the four primary mechanisms by which bacteria develop resistance to those antibiotics. Resistance is disseminated via both vertical gene transfer (VGT; parent to offspring) as well as by horizontal gene transfer (HGT; cell to cell transference of genetic material). A key challenge hindering attempts to control resistance dissemination is the presence of native, environmental bacteria that can harbor ARGs. Such environmental “resistomes” have potential to transfer resistance to pathogens via HGT. Of particular concern is the development of resistance to antibiotics of last-resort such as the cephalosporins, carbapenems, and polymyxins. We then illustrate how antibiotic use differs in LMICs relative to HICs in terms of the volumes of antibiotics used and their fate within local environments. Antibiotic use in HICs has remained flat over the past 15 years, while in LMICs use over the same period has increased substantially as a result of economic improvements and changes in diet. These use and fate differences impact local citizens and thus the local dissemination of AMR. Various physical, social, and economic circumstances within LMICs potentially favor AMR dissemination. We focus on three physical factors: changing population density, sanitation infrastructure, and solid-waste disposal. We show that high population densities in cities within LMICs that suffer from poor sanitation and solid-waste disposal can potentially impact the dissemination of resistance. In the final section, we discuss potential monitoring approaches to quantify the spread of resistance both within LMICs as well as in HICs. We posit that culture-based approaches, molecular approaches, and cutting-edge nanotechnology-based methods for monitoring ARB and ARGs should be considered both within ...

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Inland freshwater salinity is rising worldwide, a phenomenon called the freshwater salinization 32 syndrome (FSS). We investigate a potential conflict between managing the FSS and indirect potable reuse, the practice of augmenting water supplies through the addition of reclaimed wastewater to surface waters and groundwaters. From time-series data collected over 25 years, we quantify the contributions of three salinity sources-a wastewater reclamation facility and two rapidly urbanizing watersheds-to the rising concentration of sodium (a major ion associated with the FSS) in a regionally important drinking water reservoir in the Mid-Atlantic United States. Sodium mass loading to the reservoir is primarily from watershed runoff during wet weather and reclaimed wastewater during dry weather. Across all timescales evaluated, sodium concentration in the reclaimed wastewater is higher than in outflow from the two watersheds. Sodium in reclaimed wastewater originates from chemicals added during wastewater treatment, industrial and commercial discharges, human excretion, and down-drain disposal of drinking water and sodium-rich household products. Thus, numerous opportunities exist to reduce the contribution of indirect potable reuse to sodium pollution at this site, and the FSS more generally. These efforts will require deliberative engagement with a diverse community of watershed stakeholders and careful consideration of the local political, social, and environmental context.

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Wastewater-based surveillance (WBS) for disease monitoring is highly promising but requires consistent methodologies that incorporate predetermined objectives, targets, and metrics. Herein, we describe a comprehensive metagenomics-based approach for global surveillance of antibiotic resistance in sewage that enables assessment of 1) which antibiotic resistance genes (ARGs) are shared across regions/communities; 2) which ARGs are discriminatory; and 3) factors associated with overall trends in ARGs, such as antibiotic concentrations. Across an internationally sourced transect of sewage samples collected using a centralized, standardized protocol, ARG relative abundances (16S rRNA genenormalized) were highest in Hong Kong and India and lowest in Sweden and Switzerland, reflecting national policy, measured antibiotic concentrations, and metal resistance genes. Asian versus European/US resistomes were distinct, with macrolidelincosamide-streptogramin, phenicol, quinolone, and tetracycline versus multidrug resistance ARGs being discriminatory, respectively. Regional trends in measured antibiotic concentrations differed from trends expected from public sales data. This could reflect unaccounted uses, captured only by the WBS approach. If properly benchmarked, antibiotic WBS might complement public sales and consumption statistics in the future. The WBS approach defined herein demonstrates multisite comparability and sensitivity to local/regional factors.

To evaluate the use of wastewater-based surveillance and epidemiology to monitor and predict SARS-CoV-2 virus trends, over the 2020–2021 academic year we collected wastewater samples twice weekly from 17 manholes across Virginia Tech’s main campus. We used data from external door swipe card readers and student isolation/quarantine status to estimate building-specific occupancy and COVID-19 case counts at a daily resolution. After analyzing 673 wastewater samples using reverse transcription quantitative polymerase chain reaction (RT-qPCR), we reanalyzed 329 samples from isolation and nonisolation dormitories and the campus sewage outflow using reverse transcription digital droplet polymerase chain reaction (RT-ddPCR). Population-adjusted viral copy means from isolation dormitory wastewater were 48% and 66% higher than unadjusted viral copy means for N and E genes (1846/100 mL to 2733/100 mL/100 people and 2312/100 mL to 3828/100 mL/100 people, respectively; n = 46). Prespecified analyses with random-effects Poisson regression and dormitory/cluster-robust standard errors showed that the detection of N and E genes were associated with increases of 85% and 99% in the likelihood of COVID-19 cases 8 days later (incident–rate ratio (IRR) = 1.845, p = 0.013 and IRR = 1.994, p = 0.007, respectively; n = 215), and one-log increases in swipe card normalized viral copies (copies/100 mL/100 people) for N and E were associated with increases of 21% and 27% in the likelihood of observing COVID-19 cases 8 days following sample collection (IRR = 1.206, p < 0.001, n = 211 for N ; IRR = 1.265, p < 0.001, n = 211 for E ). One-log increases in swipe normalized copies were also associated with 40% and 43% increases in the likelihood of observing COVID-19 cases 5 days after sample collection (IRR = 1.403, p = 0.002, n = 212 for N ; IRR = 1.426, p < 0.001, n = 212 for E ). Our findings highlight the use of building-specific occupancy data and add to the evidence for the potential of wastewater-based epidemiology to predict COVID-19 trends at subsewershed scales.