Metagenomic Profiling of Internationally Sourced Sewage Influents and Effluents Yields Insight into Selecting Targets for Antibiotic Resistance Monitoring.

It has been debated whether wastewater treatment plants (WWTPs) primarily act to attenuate or amplify antibiotic resistance genes (ARGs). However, ARGs are highly diverse with respect to their resistance mechanisms, mobilities, and taxonomic hosts and therefore their behavior in WWTPs should not be expected to be universally conserved. We applied metagenomic sequencing to wastewater influent and effluent samples from 12 international WWTPs to classify the behavior of specific ARGs entering and exiting WWTPs. In total, 1079 different ARGs originating from a variety of bacteria were detected. This included ARGs that could be mapped to assembled scaffolds corresponding to nine human pathogens. While the relative abundance (per 16S rRNA gene) of ARGs decreased during treatment at 11 of the 12 WWTPs sampled and absolute abundance (per mL) decreased at all 12 WWTPs, increases in relative abundance were observed for 40% of the ARGs detected at the 12th WWTP. Also, the relative abundance of mobile genetic elements (MGE) increased during treatment, but the fraction of ARGs known to be transmissible between species decreased, thus demonstrating that increased MGE prevalence may not be generally indicative of an increase in ARGs. A distinct conserved resistome was documented in both influent and effluent across samples, suggesting that well-functioning WWTPs generally attenuate influent antibiotic resistance loads. This work helps inform strategies for wastewater surveillance of antibiotic resistance, highlighting the utility of tracking ARGs as indicators of treatment performance and relative risk reduction.

Selection and horizontal gene transfer underlie microdiversity-level heterogeneity in resistance gene fate during wastewater treatment.

Activated sludge is the centerpiece of biological wastewater treatment, as it facilitates removal of sewage-associated pollutants, fecal bacteria, and pathogens from wastewater through semi-controlled microbial ecology. It has been hypothesized that horizontal gene transfer facilitates the spread of antibiotic resistance genes within the wastewater treatment plant, in part because of the presence of residual antibiotics in sewage. However, there has been surprisingly little evidence to suggest that sewage-associated antibiotics select for resistance at wastewater treatment plants via horizontal gene transfer or otherwise. We addressed the role of sewage-associated antibiotics in promoting antibiotic resistance using lab-scale sequencing batch reactors fed field-collected wastewater, metagenomic sequencing, and our recently developed bioinformatic tool Kairos. Here, we found confirmatory evidence that fluctuating levels of antibiotics in sewage are associated with horizontal gene transfer of antibiotic resistance genes, microbial ecology, and microdiversity-level differences in resistance gene fate in activated sludge.

Highly Multiplexed Reverse-Transcription Loop-Mediated Isothermal Amplification and Nanopore Sequencing (LAMPore) for Wastewater-Based Surveillance.

Wastewater-based surveillance (WBS) has gained attention as a strategy to monitor and provide an early warning for disease outbreaks. Here, we applied an isothermal gene amplification technique, reverse-transcription loop-mediated isothermal amplification (RT-LAMP), coupled with nanopore sequencing (LAMPore) as a means to detect SARS-CoV-2. Specifically, we combined barcoding using both an RT-LAMP primer and the nanopore rapid barcoding kit to achieve highly multiplexed detection of SARS-CoV-2 in wastewater. RT-LAMP targeting the SARS-CoV-2 N region was conducted on 96 reactions including wastewater RNA extracts and positive and no-target controls. The resulting amplicons were pooled and subjected to nanopore sequencing, followed by demultiplexing based on barcodes that differentiate the source of each SARS-CoV-2 N amplicon derived from the 96 RT-LAMP products. The criteria developed and applied to establish whether SARS-CoV-2 was detected by the LAMPore assay indicated high consistency with polymerase chain reaction-based detection of the SARS-CoV-2 N gene, with a sensitivity of 89% and a specificity of 83%. We further profiled sequence variations on the SARS-CoV-2 N amplicons, revealing a number of mutations on a sample collected after viral variants had emerged. The results demonstrate the potential of the LAMPore assay to facilitate WBS for SARS-CoV-2 and the emergence of viral variants in wastewater.

Demonstrating a Comprehensive Wastewater-Based Surveillance Approach That Differentiates Globally Sourced Resistomes.

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 gene-normalized) 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 macrolide-lincosamide-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.

Subsewershed SARS-CoV-2 Wastewater Surveillance and COVID-19 Epidemiology Using Building-Specific Occupancy and Case Data.

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.

Nanobiotechnology enabled approaches for wastewater based epidemiology.

The impacts of the ongoing coronavirus pandemic highlight the importance of environmental monitoring to inform public health safety. Wastewater based epidemiology (WBE) has drawn interest as a tool for analysis of biomarkers in wastewater networks. Wide scale implementation of WBE requires a variety of field deployable analytical tools for real-time monitoring. Nanobiotechnology enabled sensing platforms offer potential as biosensors capable of highly efficient and sensitive detection of target analytes. This review provides an overview of the design and working principles of nanobiotechnology enabled biosensors and recent progress on the use of biosensors in detection of biomarkers. In addition, applications of biosensors for analysis of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus are highlighted as they relate to the potential expanded use of biosensors for WBE-based monitoring. Finally, we discuss the opportunities and challenges in future applications of biosensors in WBE for effective monitoring and investigation of public health threats.

Unraveling the riverine antibiotic resistome: The downstream fate of anthropogenic inputs.

River networks are one of the main routes by which the public could be exposed to environmental sources of antibiotic resistance, that may be introduced e.g. via treated wastewater. In this study, we applied a comprehensive integrated analysis encompassing mass-flow concepts, chemistry, bacterial plate counts, resistance gene quantification and shotgun metagenomics to track the fate of the resistome (collective antibiotic resistance genes (ARGs) in a microbial community) of treated wastewater in two Swiss rivers at the kilometer scale. The levels of certain ARGs and the class 1 integron integrase gene (intI1) commonly associated with anthropogenic sources of ARGs decreased quickly over short distances (2-2.5 km) downstream of wastewater discharge points. Mass-flow analysis based on conservative tracers suggested this decrease was attributable mainly to dilution but ARG loadings frequently also decreased (e.g., 55.0-98.5 % for ermB and tetW) over the longest studied distances (6.8 and 13.7 km downstream). Metagenomic analysis confirmed that ARG of wastewater-origin did not persist in rivers after 5 ~ 6.8 km downstream distance. sul1 and intI1 levels and loadings were more variable and even increased sharply at 5 ~ 6.8 km downstream distance on one occasion. While input from agriculture and in-situ positive selection pressure for organisms carrying ARGs cannot be excluded, in-system growth of biomass is a more probable explanation. The potential for direct human exposure to the resistome of wastewater-origin thus appeared to typically abate rapidly in the studied rivers. However, the riverine aquatic resistome was also dynamic, as evidenced by the increase of certain gene markers downstream, without obvious sources of anthropogenic contamination. This study provides new insight into drivers of riverine resistomes and pinpoints key monitoring targets indicative of where human sources and exposures are likely to be most acute.

Next generation sequencing approaches to evaluate water and wastewater quality.

The emergence of next generation sequencing (NGS) is revolutionizing the potential to address complex microbiological challenges in the water industry. NGS technologies can provide holistic insight into microbial communities and their functional capacities in water and wastewater systems, thus eliminating the need to develop a new assay for each target organism or gene. However, several barriers have hampered wide-scale adoption of NGS by the water industry, including cost, need for specialized expertise and equipment, challenges with data analysis and interpretation, lack of standardized methods, and the rapid pace of development of new technologies. In this critical review, we provide an overview of the current state of the science of NGS technologies as they apply to water, wastewater, and recycled water. In addition, a systematic literature review was conducted in which we identified over 600 peer-reviewed journal articles on this topic and summarized their contributions to six key areas relevant to the water and wastewater fields: taxonomic classification and pathogen detection, functional and catabolic gene characterization, antimicrobial resistance (AMR) profiling, bacterial toxicity characterization, Cyanobacteria and harmful algal bloom identification, and virus characterization. For each application, we have presented key trends, noteworthy advancements, and proposed future directions. Finally, key needs to advance NGS technologies for broader application in water and wastewater fields are assessed.

Differential Drivers of Antimicrobial Resistance across the World.

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 HICs and, as appropriate, within LMICs.

Waste treatment and energy production from small-scale wastewater digesters.

Three tubular anaerobic digestion (AD) systems were installed in Haiti to treat black water (toilet-based wastewater), including a three cell 36m3 clinic digester (CD), a two cell 2m3 hotel digester (HD), and a three-cell 3m3 farm digester (FD) for worker use. During digestion, total coliforms were reduced by 99.1%, E. coli by 98.5%, and chemical oxygen demand (COD) by 93.6%. Nutrients in the effluent averaged 99.4mg/L NH4+ and 10.6mg/L PO42-, producing an effective organic fertilizer. Average biogas production in CD was 108L/d, with 65.4% CH4. Survey participants (n=573) were willing to pay $0.10-0.30 per use for sanitation facilities. Seventy-two percent of the rural population surveyed in Cange, Haiti lacked access to improved sanitation due to financial constraints. The economic analysis calculated an investment cost for a shared toilet AD systems of $16-$47 (USD) per person based on daily use at design capacity.