Municipal Wastewater as a Microbial Surveillance Platform for Enteric Diseases: A Case Study for Salmonella and Salmonellosis

Integrating wastewater surveillance and meteorological data to monitor seasonal variability of enteric and respiratory pathogens for infectious disease control in Dhaka city

BACKGROUND

Seasonal meteorological variations influence the spread of infectious diseases. Wastewater surveillance helps understanding pathogen transmission dynamics, particularly in urban areas of climate-vulnerable countries like Bangladesh.

METHODS

We analysed 54 weeks of wastewater surveillance, clinical surveillance, and meteorological data from Dhaka, Bangladesh. Samples from 11 sites were tested for Vibrio cholerae (V. cholerae), SARS-CoV-2, Salmonella enterica subspecies enterica serovar Typhi (S. Typhi), and Group A rotavirus. Diarrhoeal Disease Surveillance data were sourced from icddr,b, and meteorological data from the Bangladesh Meteorological Department. Regression models adjusted for site and time variations were used for statistical analysis.

RESULTS

Proportion of confirmed cholera cases among the diarrhoeal disease surveillance recruits were highest during post-monsoon (coef: 2.53; 95 % CI: 0.41 to 4.67; p = 0.029). V. cholerae log10 concentrations in wastewater were positively associated with pre-monsoon (coef: 0.93; 95 % CI: 0.26 to 1.58; p = 0.010), while SARS-CoV-2 peaked during monsoon (coef: 1.85; 95 % CI: 0.96 to 2.73; p < 0.001). S. Typhi and rotavirus log10 concentrations showed negative associations with pre-monsoon (coef: -0.96; 95 % CI: -1.68 to -0.27; p = 0.011, and -0.84; 95 % CI: -1.17 to -0.50; p < 0.001, respectively). Temperature positively influenced log10 concentrations of V. cholerae (adj. coef: 0.09; 95 % CI: 0.02 to 0.15; p = 0.014) and SARS-CoV-2 (adj. coef: 0.19; 95 % CI: 0.10 to 0.27; p < 0.001), but negatively associated with rotavirus (adj. coef: -0.06; 95 % CI: -0.10 to -0.03; p < 0.001). Similar associations were found between pathogen-positive samples and temperature.

CONCLUSION

Our study shows that seasonal, and meteorological factors (particularly temperature) influence the patterns and abundance of pathogens in wastewater and help in understanding disease transmission across different weather patterns.

Bacterial Wastewater-Based Epidemiology Using Surface-Enhanced Raman Spectroscopy and Machine Learning

Although wastewater-based epidemiology has been used extensively for the surveillance of viral diseases, it has not been used to a similar extent for bacterial diseases. This is in part owing to difficulties in distinguishing pathogenic from nonpathogenic bacteria using PCR methods. Here, we show that surface-enhanced Raman spectroscopy (SERS) can be a scalable, label-free method for the detection of bacteria in wastewater. We enhance Raman signal from bacteria in wastewater using plasmonic gold nanorods (AuNRs) that electrostatically bind to the bacterial surface and confirm this binding using cryoelectron microscopy. We spike four clinically relevant bacterial species and AuNRs into filtered wastewater, varying the AuNR concentration to maximize the signal. We then collect 540 spectra from each species at 109 cells/mL and train a machine learning model to identify them with more than 87% accuracy. We also demonstrate an environmentally realistic limit of detection of 104 cells/mL. These results are a key step toward a SERS platform for bacterial WBE.

Can Wastewater Surveillance Enhance Genomic Tracking of Climate-Driven Pathogens?

Climate change heightens the threat of infectious diseases in Europe, necessitating innovative surveillance methods. Based on 390 scientific papers, for the first time, this review associates climate-related pathogens, data related to their presence in wastewater, and associated available genomic detection methods. This deep analysis reveals a wide range of pathogens that can be tracked through methods such as quantitative and digital PCR, as well as genomic pathogen enrichment in combination with sequencing and metagenomics. Nevertheless, significant gaps remain in the development of methods, particularly for vector-borne pathogens, and in their general harmonization relating to performance criteria. By offering an overview of recent advancements while identifying critical gaps, we advocate for collaborative research and validation to integrate detection techniques into surveillance frameworks. This will enhance public health resilience against emerging infectious diseases driven by climate change.

Monitoring and preventing foodborne outbreaks: are we missing wastewater as a key data source?

In 2022, the number of foodborne outbreaks in Europe increased by 43.9%, highlighting the need to improve surveillance systems and design outbreak predictive tools. This review aims to assess the scientific literature describing wastewater surveillance to monitor foodborne pathogens in association with clinical data. In the selected studies, the relationship between peaks of pathogen concentration in wastewater and reported clinical cases is described. Moreover, details on analytical methods to detect and quantify pathogens as well as wastewater sampling procedures are discussed. Few papers show a statistically significant correlation between high concentrations of foodborne pathogens in wastewater and the occurrence of clinical cases. However, monitoring pathogen concentration in wastewater looks like a promising and cost-effective strategy to improve foodborne outbreak surveillance. Such a strategy can be articulated in three steps, where the first one is testing wastewater with an untargeted method, like shotgun metagenomic, to detect microorganisms belonging to different domains. The second consists of testing wastewater with a targeted method, such as quantitative polymerase chain reaction, to quantify those specific pathogens that in the metagenomic dataset display an increasing trend or exceed baseline concentration thresholds. The third involves the integrated wastewater and clinical data analysis and modeling to find meaningful epidemiological correlations and make predictions.

Tracking Chlamydia and Syphilis in the Detroit Metro Area by Molecular Analysis of Environmental Samples

This paper describes one of the first studies applying wastewater surveillance to monitor Chlamydia and Syphilis and back-estimate infections in the community, based on bacterial shedding and wastewater surveillance data. Molecular biology laboratory methods were optimized, and a workflow was designed to implement wastewater surveillance tracking Chlamydia and Syphilis in the Detroit metro area (DMA), one of the most populous metropolitan areas in the U.S. Untreated composite wastewater samples were collected weekly from the three main interceptors that service DMA, which collect wastewater and discharge it to the Great Lakes Water Authority Water Resource Recovery Facility. Additionally, untreated wastewater was also collected from street manholes in three neighborhood sewersheds in Wayne, Macomb, and Oakland counties. Centrifugation, DNA extraction, and ddPCR methods were optimized and performed, targeting Chlamydia trachomatis and Treponema pallidum, the causative agents of Chlamydia and Syphilis, respectively. The limit of blank and limit of detection methods were determined experimentally for both targets. Both targets were detected and monitored in wastewater between December 25th, 2023, and April 22nd, 2024. The magnitudes of C. trachomatis and T. pallidum concentrations observed in neighborhood sewersheds were higher as compared to the concentrations observed in the interceptors. Infections of Chlamydia and Syphilis were back-estimated through an optimized formula based on shedding dynamics and wastewater surveillance data, which indicated potentially underreported conditions relative to publicly available clinical data.

Adjusting for dilution in wastewater using biomarkers: A practical approach

We developed a biomarker-based approach to quantify in-sewer dilution by measuring wastewater quality parameters (ammoniacal-N, orthophosphate, crAssphage). This approach can enhance the environmental management of wastewater treatment works (WWTW) by optimising their operation and providing cost-effective information on the health and behaviour of populations and their interactions with the environment through wastewater-based epidemiology (WBE). Our method relies on site specific baselines calculated for each biomarker. These baselines reflect the sewer conditions without the influence of rainfall-derived inflow and infiltration (RDII). Ammoniacal-N was the best candidate to use as proxy for dilution. We demonstrated that the dilution calculated using biomarkers correlates well with the dilution indicated by measured flow. In some instances, the biomarkers showed much higher dilution than measured flows. These differences were attributed to the loss of flow volume at wastewater treatment works due to the activation of combined sewer overflows (CSOs) and/or storm tanks. Using flow measured directly at the WWTW could therefore result in underestimation of target analyte loads.

Research Progress on Detection of Pathogens in Medical Wastewater by Electrochemical Biosensors

The detection of pathogens in medical wastewater is crucial due to the high content of pathogenic microorganisms that pose significant risks to public health and the environment. Medical wastewater, which includes waste from infectious disease and tuberculosis facilities, as well as comprehensive medical institutions, contains a variety of pathogens such as bacteria, viruses, fungi, and parasites. Traditional detection methods like nucleic acid detection and immunological assays, while effective, are often time-consuming, expensive, and not suitable for rapid detection in underdeveloped areas. Electrochemical biosensors offer a promising alternative with advantages including simplicity, rapid response, portability, and low cost. This paper reviews the sources of pathogens in medical wastewater, highlighting specific bacteria (e.g., E. coli, Salmonella, Staphylococcus aureus), viruses (e.g., enterovirus, respiratory viruses, hepatitis virus), parasites, and fungi. It also discusses various electrochemical biosensing techniques such as voltammetry, conductometry, impedance, photoelectrochemical, and electrochemiluminescent biosensors. These technologies facilitate the rapid, sensitive, and specific detection of pathogens, thereby supporting public health and environmental safety. Future research may should pay more attention on enhancing sensor sensitivity and specificity, developing portable and cost-effective devices, and innovating detection methods for diverse pathogens to improve public health protection and environmental monitoring.

Understanding Stimulation of Conjugal Gene Transfer by Nonantibiotic Compounds: How Far Are We?

A myriad of nonantibiotic compounds is released into the environment, some of which may contribute to the dissemination of antimicrobial resistance by stimulating conjugation. Here, we analyzed a collection of studies to (i) identify patterns of transfer stimulation across groups and concentrations of chemicals, (ii) evaluate the strength of evidence for the proposed mechanisms behind conjugal stimulation, and (iii) examine the plausibility of alternative mechanisms. We show that stimulatory nonantibiotic compounds act at concentrations from 1/1000 to 1/10 of the minimal inhibitory concentration for the donor strain but that stimulation is always modest (less than 8-fold). The main proposed mechanisms for stimulation via the reactive oxygen species/SOS cascade and/or an increase in cell membrane permeability are not unequivocally supported by the literature. However, we identify the reactive oxygen species/SOS cascade as the most likely mechanism. This remains to be confirmed by firm molecular evidence. Such evidence and more standardized and high-throughput conjugation assays are needed to create technologies and solutions to limit the stimulation of conjugal gene transfer and contribute to mitigating global antibiotic resistance.

Comparison of gene targets and sampling regimes for SARS-CoV-2 quantification for wastewater epidemiology in UK prisons

Prisons are high-risk settings for infectious disease transmission, due to their enclosed and semi-enclosed environments. The proximity between prisoners and staff, and the diversity of prisons reduces the effectiveness of non-pharmaceutical interventions, such as social distancing. Therefore, alternative health monitoring methods, such as wastewater-based epidemiology (WBE), are needed to track pathogens, including SARS-CoV-2. This pilot study assessed WBE to quantify SARS-CoV-2 prevalence in prison wastewater to determine its utility within a health protection system for residents. The study analysed 266 samples from six prisons in England over a 12-week period for nucleoprotein 1 (N1 gene) and envelope protein (E gene) using quantitative reverse transcriptase-polymerase chain reaction. Both gene assays successfully detected SARS-CoV-2 fragments in wastewater samples, with both genes significantly correlating with COVID-19 case numbers across the prisons (p < 0.01). However, in 25% of the SARS-positive samples, only one gene target was detected, suggesting that both genes be used to reduce false-negative results. No significant differences were observed between 14- and 2-h composite samples, although 2-h samples showed greater signal variance. Population normalisation did not improve correlations between the N1 and E genes and COVID-19 case data. Overall, WBE shows considerable promise for health protection in prison settings.

Temporal and spatial relationships of CrAssphage and enteric viral and bacterial pathogens in wastewater in North Carolina

Enteric disease remains one of the most common concerns for public health, particularly when it results from human exposure to surface and recreational waters contaminated with wastewater. Characterizing the temporal and spatial variation of enteric pathogens prevalent in wastewater is critical to develop approaches to mitigate their distribution in the environment. In this study, we aim to characterize pathogen variability and test the applicability of the human-associated wastewater indicator crAssphage as an indicator of enteric viral and bacterial pathogens. We conducted weekly samplings for 14 months from four wastewater treatment plants in North Carolina, USA. Untreated wastewater samples were processed using hollow fiber ultrafiltration, followed by secondary concentration methods. Adenovirus, norovirus, enterovirus, Salmonella, Shiga toxin 2 (stx2), Campylobacter, and crAssphage were measured by quantitative polymerase chain reaction (qPCR) and reverse transcriptase (rt)-qPCR. Our results revealed significant correlations between crAssphage and human adenovirus, enterovirus, norovirus, Salmonella, and Campylobacter (p<0.01). Pathogens and crAssphage concentrations in untreated wastewater showed distinct seasonal patterns, with peak concentrations of crAssphage and viral pathogens in fall and winter, while bacterial pathogens showed peaked concentrations in either winter (Campylobacter), fall (Salmonella), or summer (stx2). This study enhances the understanding of crAssphage as an alternative molecular indicator for both bacterial and viral pathogens. The findings of this study can also inform microbial modeling efforts for the prediction of the impact of wastewater pathogens on surface waters due to increased flooding events and wastewater overflows associated with climate change.

Sampling Considerations for Wastewater Surveillance of Antibiotic Resistance in Fecal Bacteria

Wastewaters can be analyzed to generate population-level data for public health surveillance, such as antibiotic resistance monitoring. To provide representative data for the contributing population, bacterial isolates collected from wastewater should originate from different individuals and not be distorted by a selection pressure in the wastewater. Here we use Escherichia coli diversity as a proxy for representativeness when comparing grab and composite sampling at a major municipal wastewater treatment plant influent and an untreated hospital effluent in Gothenburg, Sweden. All municipal samples showed high E. coli diversity irrespective of the sampling method. In contrast, a marked increase in diversity was seen for composite compared to grab samples from the hospital effluent. Virtual resampling also showed the value of collecting fewer isolates on multiple occasions rather than many isolates from a single sample. Time-kill tests where individual E. coli strains were exposed to sterile-filtered hospital wastewater showed rapid killing of antibiotic-susceptible strains and significant selection of multi-resistant strains when incubated at 20 °C, an effect which could be avoided at 4 °C. In conclusion, depending on the wastewater collection site, both sampling method and collection/storage temperature could significantly impact the representativeness of the wastewater sample.

Retrospective Analysis of Wastewater-Based Epidemiology of SARS-CoV-2 in Residences on a Large College Campus: Relationships between Wastewater Outcomes and COVID-19 Cases across Two Semesters with Different COVID-19 Mitigation Policies

Wastewater-based epidemiology (WBE) has been utilized for outbreak monitoring and response efforts in university settings during the coronavirus disease 2019 (COVID-19) pandemic. However, few studies examined the impact of university policies on the effectiveness of WBE to identify cases and mitigate transmission. The objective of this study was to retrospectively assess relationships between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) wastewater outcomes and COVID-19 cases in residential buildings of a large university campus across two academic semesters (August 2020-May 2021) under different COVID-19 mitigation policies. Clinical case surveillance data of student residents were obtained from the university COVID-19 response program. We collected and processed building-level wastewater for detection and quantification of SARS-CoV-2 RNA by RT-qPCR. The odds of obtaining a positive wastewater sample increased with COVID-19 clinical cases in the fall semester (OR = 1.50, P value = 0.02), with higher odds in the spring semester (OR = 2.63, P value < 0.0001). We observed linear associations between SARS-CoV-2 wastewater concentrations and COVID-19 clinical cases (parameter estimate = 1.2, P value = 0.006). Our study demonstrated the effectiveness of WBE in the university setting, though it may be limited under different COVID-19 mitigation policies. As a complementary surveillance tool, WBE should be accompanied by robust administrative and clinical testing efforts for the COVID-19 pandemic response.

Wastewater surveillance of antibiotic-resistant bacterial pathogens: A systematic review

Infectious diseases caused by antibiotic-resistant bacterial (ARB) pathogens are a serious threat to human and animal health. The active surveillance of ARB using an integrated one-health approach can help to reduce the emergence and spread of ARB, reduce the associated economic impact, and guide antimicrobial stewardship programs. Wastewater surveillance (WWS) of ARB provides composite samples for a total population, with easy access to the mixed community microbiome. This concept is emerging rapidly, but the clinical utility, sensitivity, and uniformity of WWS of ARB remain poorly understood especially in relation to clinical evidence in sewershed communities. Here, we systematically searched the literature to identify studies that have compared findings from WWS of ARB and antibiotic resistance genes (ARG) with clinical evidence in parallel, thereby evaluating how likely WWS of ARB and ARG can relate to the clinical cases in communities. Initially, 2,235 articles were obtained using the primary search keywords, and 1,219 articles remained after de-duplication. Among these, 35 articles fulfilled the search criteria, and an additional 13 relevant articles were included by searching references in the primary literature. Among the 48 included papers, 34 studies used a culture-based method, followed by 11 metagenomics, and three PCR-based methods. A total of 28 out of 48 included studies were conducted at the single sewershed level, eight studies involved several countries, seven studies were conducted at national or regional scales, and five at hospital levels. Our review revealed that the performance of WWS of ARB pathogens has been evaluated more frequently for Escherichia coli, Enterococcus spp., and other members of the family Enterobacteriaceae, but has not been uniformly tested for all ARB pathogens. Many wastewater-based ARB studies comparing the findings with clinical evidence were conducted to evaluate the public health risk but not to relate with clinical evidence and to evaluate the performance of WWS of ARB. Indeed, relating WWS of ARB with clinical evidence in a sewershed is not straightforward, as the source of ARB in wastewater cannot be only from symptomatic human individuals but can also be from asymptomatic carriers as well as from animal sources. Further, the varying fates of each bacterial species and ARG within the sewerage make the aim of connecting WWS of ARB with clinical evidence more complicated. Therefore, future studies evaluating the performance of many AMR pathogens and their genes for WWS one by one can make the process simpler and the interpretation of results easier.

Wastewater Surveillance for Infectious Disease: A Systematic Review

Wastewater surveillance for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been shown to be a valuable source of information regarding SARS-CoV-2 transmission and coronavirus disease 2019 (COVID-19) cases. Although the method has been used for several decades to track other infectious diseases, there has not been a comprehensive review outlining all of the pathogens that have been surveilled through wastewater. Herein we identify the infectious diseases that have been previously studied via wastewater surveillance prior to the COVID-19 pandemic. Infectious diseases and pathogens were identified in 100 studies of wastewater surveillance across 38 countries, as were themes of how wastewater surveillance and other measures of disease transmission were linked. Twenty-five separate pathogen families were identified in the included studies, with the majority of studies examining pathogens from the family Picornaviridae, including polio and nonpolio enteroviruses. Most studies of wastewater surveillance did not link what was found in the wastewater to other measures of disease transmission. Among those studies that did, the value reported varied by study. Wastewater surveillance should be considered as a potential public health tool for many infectious diseases. Wastewater surveillance studies can be improved by incorporating other measures of disease transmission at the population-level including disease incidence and hospitalizations.

Detection of SARS-CoV-2 RNA throughout wastewater treatment plants and a modeling approach to understand COVID-19 infection dynamics in Winnipeg, Canada

Although numerous studies have detected SARS-CoV-2 RNA in wastewater and attempted to find correlations between the concentration of SARS-CoV-2 RNA and the number of cases, no consensus has been reached on sample collection and processing, and data analysis. Moreover, the fate of SARS-CoV-2 in wastewater treatment plants is another issue, specifically regarding the discharge of the virus into environmental settings and the water cycle. The current study monitored SARS-CoV-2 RNA in influent and effluent wastewater samples with three different concentration methods and sludge samples over six months (July to December 2020) to compare different virus concentration methods, assess the fate of SARS-CoV-2 RNA in wastewater treatment plants, and describe the potential relationship between SARS-CoV-2 RNA concentrations in influent and infection dynamics. Skimmed milk flocculation (SMF) resulted in 15.27 ± 3.32% recovery of an internal positive control, Armored RNA, and a high positivity rate of SARS-CoV-2 RNA in stored wastewater samples compared to ultrafiltration methods employing a prefiltration step to eliminate solids in fresh wastewater samples. Our results suggested that SARS-CoV-2 RNA may predominate in solids, and therefore, concentration methods focusing on both supernatant and solid fractions may result in better recovery. SARS-CoV-2 RNA was detected in influent and primary sludge samples but not in secondary and final effluent samples, indicating a significant reduction during primary and secondary treatments. SARS-CoV-2 RNA was first detected in influent on September 30th, 2020. A decay-rate formula was applied to estimate initial concentrations of late-processed samples with SMF. A model based on shedding rate and new cases was applied to estimate SARS-CoV-2 RNA concentrations and the number of active shedders. Inferred sensitivity of observed and modeled concentrations to the fluctuations in new cases and test-positivity rates indicated a potential contribution of newly infected individuals to SARS-CoV-2 RNA loads in wastewater.

Heavy Rainfall, Sewer Overflows, and Salmonellosis in Black Skimmers (Rynchops niger)

Extreme weather events, particularly heavy rainfall, are occurring at greater frequency with climate change. Although adverse human health effects from heavy rainfall are often publicized, impacts to free-ranging wildlife populations are less well known. We first summarize documented associations of heavy rainfall on wildlife health. We then report a novel investigation of a salmonellosis outbreak in a colony of black skimmers (Rynchops niger) in Florida, USA. During June-September 2016, heavy rainfall resulted in the discharge of millions of gallons of untreated wastewater into the Tampa Bay system, contaminating the water body, where adult skimmers foraged. At least 48 fledglings died, comprising 39% of the colony's nesting season's offspring. Of eight examined deceased birds from the colony, six had a systemic salmonellosis infection. Isolates were identified as Salmonella enterica serotype Typhimurium. Their pulsed-field gel electrophoresis patterns were identical to each other and matched those from several human Salmonella sp. infections. Differences among whole-genome sequences were negligible. These findings and the outbreak's epidemic curve suggest propagated transmission occurred within the colony. A multidisciplinary and One Health approach is recommended to mitigate any adverse effects of climate change-driven stochastic events, especially when they place already imperiled wildlife at further risk.

Decay of four enteric pathogens and implications to wastewater-based epidemiology: Effects of temperature and wastewater dilutions

Measurement of pathogens in raw wastewater from a population within certain sewer catchments can provide quantitative information on public health status within the sampled urban area. This so-called wastewater-based epidemiology (WBE) approach has the potential of becoming a powerful tool to monitor pathogen circulation and support timely intervention during outbreaks. However, many WBE studies failed to account for the pathogen decay during wastewater transportation in back calculating the disease prevalence. Various sewer process factors, including water temperature and infiltration/inflow, can lead to the variation of pathogen decay rates. This paper firstly reviewed the effects of temperature and types of water, i.e., wastewater, freshwater, and saline water, on the decay of four selected enteric pathogens, i.e., Campylobacter, Salmonella, Norovirus, and Adenovirus. To elucidate the importance of the pathogen decay rates (measured by culture and molecular methods) to WBE, a sensitivity analysis was conducted on the back-calculation equation for infection prevalence with decay rates collected from published literature. It was found that WBE back-calculation is more sensitive to decay rates under the condition of high wastewater temperature (i.e., over 25 °C) or if wastewater is diluted by saline water (i.e., sewer infiltration or use of seawater as an alternative source of freshwater constituting around 1/3 household water demand in some cities). Stormwater dilution of domestic wastewater (i.e., sewer inflow might achieve 10 times volumetric dilution) was shown to play a role in increasing the sensitivity of WBE back-calculation to bacterial pathogens, but not viral pathogens. Hence, WBE back-calculation in real sewers should account for in-sewer decay of specific pathogen species under different wastewater temperatures and dilutions. Overall, this review contributes to a better understanding of pathogen decay in wastewater which can lead to improved accuracy of WBE back-calculation.

Environmental and Human Microbiome for Health

Microorganisms are an essential part of life on the earth and can exist in association with virtually any living thing. The environmental microbiome is much more diverse than the human microbiome. It is reported that most microbes existing in the environment are difficult to culture in the laboratory. Whereas both pathogenic and beneficial microbes may be prevailing in the environment, the human body can have three categories of microbes- beneficial, pathogenic, and opportunistic pathogenic. With at least 10-fold more cells than human cells, microbes as normal flora are critical for human survival. The microbes present in the human body play a crucial role in maintaining human health, and the environmental microbiome influences the human microbiome makeup. The interaction between the environmental and human microbiome highly influences human health, however it is poorly understood. In addition, as an established infection is associated with health-seeking behavior, a large number of studies have focused on the transmission and dynamics of infectious microorganisms than the noninfectious or beneficial ones. This review will summarize how the interaction between the environmental and human microbiome affects human health and identify approaches that might be beneficial for humans to improve health by being exposed to the natural environment.

Self-Driven Pretreatment and Room-Temperature Storage of Water Samples for Virus Detection Using Enhanced Porous Superabsorbent Polymer Beads

The continuous emergence of infectious viral diseases has become a major threat to public health. To quantify viruses, proper handling of water samples is required to ensure the accuracy and reliability of the testing results. In this study, we develop enhanced porous superabsorbent polymer (PSAP) beads to pretreat and store water samples for virus detection. By applying PSAP beads to collect water samples, the viruses are captured and encapsulated inside the beads while undesired components are excluded. We have successfully demonstrated that the shelf life of the model virus can be effectively extended at room temperature (22 °C) and an elevated temperature (35 °C). Both the infectivity level and genome abundance of the viruses are preserved even in a complex medium such as untreated wastewater. Under the tested conditions, the viral degradation rate constant can be reduced to more than 10 times using the PSAP beads. Therefore, the enhanced PSAP beads provide a low-cost and efficient sample pretreatment and storage method that is feasible and practical for large-scale surveillance of viral pathogens in water samples.

Implementing building-level SARS-CoV-2 wastewater surveillance on a university campus

The COVID-19 pandemic has been a source of ongoing challenges and presents an increased risk of illness in group environments, including jails, long-term care facilities, schools, and residential college campuses. Early reports that the SARS-CoV-2 virus was detectable in wastewater in advance of confirmed cases sparked widespread interest in wastewater-based epidemiology (WBE) as a tool for mitigation of COVID-19 outbreaks. One hypothesis was that wastewater surveillance might provide a cost-effective alternative to other more expensive approaches such as pooled and random testing of groups. In this paper, we report the outcomes of a wastewater surveillance pilot program at the University of North Carolina at Charlotte, a large urban university with a substantial population of students living in on-campus dormitories. Surveillance was conducted at the building level on a thrice-weekly schedule throughout the university's fall residential semester. In multiple cases, wastewater surveillance enabled the identification of asymptomatic COVID-19 cases that were not detected by other components of the campus monitoring program, which also included in-house contact tracing, symptomatic testing, scheduled testing of student athletes, and daily symptom reporting. In the context of all cluster events reported to the University community during the fall semester, wastewater-based testing events resulted in the identification of smaller clusters than were reported in other types of cluster events. Wastewater surveillance was able to detect single asymptomatic individuals in dorms with resident populations of 150-200. While the strategy described was developed for COVID-19, it is likely to be applicable to mitigation of future pandemics in universities and other group-living environments.

Implementing building-level SARS-CoV-2 wastewater surveillance on a university campus

The COVID-19 pandemic has been a source of ongoing challenges and presents an increased risk of illness in group environments, including jails, long-term care facilities, schools, and residential college campuses. Early reports that the SARS-CoV-2 virus was detectable in wastewater in advance of confirmed cases sparked widespread interest in wastewater-based epidemiology (WBE) as a tool for mitigation of COVID-19 outbreaks. One hypothesis was that wastewater surveillance might provide a cost-effective alternative to other more expensive approaches such as pooled and random testing of groups. In this paper, we report the outcomes of a wastewater surveillance pilot program at the University of North Carolina at Charlotte, a large urban university with a substantial population of students living in on-campus dormitories. Surveillance was conducted at the building level on a thrice-weekly schedule throughout the university's fall residential semester. In multiple cases, wastewater surveillance enabled the identification of asymptomatic COVID-19 cases that were not detected by other components of the campus monitoring program, which also included in-house contact tracing, symptomatic testing, scheduled testing of student athletes, and daily symptom reporting. In the context of all cluster events reported to the University community during the fall semester, wastewater-based testing events resulted in the identification of smaller clusters than were reported in other types of cluster events. Wastewater surveillance was able to detect single asymptomatic individuals in dorms with resident populations of 150-200. While the strategy described was developed for COVID-19, it is likely to be applicable to mitigation of future pandemics in universities and other group-living environments.

Fecal indicator bacteria, direct pathogen detection, and microbial community analysis provide different microbiological water quality assessment of a tropical urban marine estuary

Urban marine estuaries are often impacted by microbiological contamination that impairs use and affects human health acutely, while limited is known about microbiological water quality in urban marine estuaries in the absence of reported sewage spills. This study used a tropical urban marine estuary, the Ala Wai Canal in Honolulu, Hawaii, as the model system to compare fecal indicator bacteria (FIB) concentrations, bacterial pathogen profiles, and microbial community structures. The FIB Escherichia coli exhibited higher geometric mean 132 CFU/100mL (n=28) than those of enterococci (18 CFU/100mL) and Clostridium perfringens (21 CFU/100mL). Amongst the four pathogens targeted by cultivation methods (Salmonella, Campylobacter, Listeria monocytogenes and Vibrio parahaemolyticus), only was V. parahaemolyticus detected and was detected at high frequency. Microbial community analysis through 16S rRNA gene amplicon sequencing also indicated the high prevalence of Vibrio in the water. The pathogen detection patterns and microbial community structure showed no significant correlation with FIB concentration profiles. Together, the results highlight the limitation of using traditional FIB in assessing water microbiological quality in the tropical urban marine estuary environment, indicating the need for more comprehensive microbial risk assessment approaches such as direct detection of pathogens.

Municipal Wastewater Surveillance Revealed a High Community Disease Burden of a Rarely Reported and Possibly Subclinical Salmonella enterica Serovar Derby Strain

Clinical surveillance of enteric pathogens like Salmonella is integral to track outbreaks and endemic disease trends. However, clinic-centered disease monitoring biases toward detection of severe cases and underestimates the incidence of self-limiting gastroenteritis and asymptomatic strains. Monitoring pathogen loads and diversity in municipal wastewater (MW) can provide insight into asymptomatic or subclinical infections which are not reflected in clinical cases. Subclinical infection patterns may explain the unusual observation from a year-long sampling campaign in Hawaii: Salmonella enterica serovar Derby was the most abundant pulsotype in MW but was detected infrequently in clinics over the sampling period. Using whole-genome sequencing data of Salmonella isolates from MW and public databases, we demonstrate that the Derby serovar has lower virulence potential than other clinical serovars, particularly based on its reduced profile of genes linked with immune evasion and symptom production, suggesting its potential as a subclinical salmonellosis agent. Furthermore, MW had high abundance of a rare Derby sequence type (ST), ST-72 (rather than the more common ST-40). ST-72 isolates had higher frequencies of fimbrial adherence genes than ST-40 isolates; these are key virulence factors involved in colonization and persistence of infections. However, ST-72 isolates lack the Derby-specific Salmonella pathogenicity island 23 (SPI-23), which invokes host immune responses. In combination, ST-72's genetic features may lead to appreciable infection rates without obvious symptom production, allowing for subclinical persistence in the community. This study demonstrated wastewater's capability to provide community infectious disease information-such as background infection rates of subclinical enteric illness-which is otherwise inaccessible through clinical approaches.IMPORTANCE Wastewater-based epidemiology (WBE) has been conventionally used to analyze community health via the detection of chemicals, such as legal and illicit drugs; however, municipal wastewater contains microbiological determinants of health and disease as well, including enteric pathogens. Here, we demonstrate that WBE can be used to examine subclinical community salmonellosis patterns. Derby was the most abundant Salmonella serovar detected in Hawaii wastewater over a year-long sampling study, with few corresponding clinical cases. Comparative genomics analyses indicate that the normally rare strain of S Derby found in wastewater has a unique combination of genes which allow it to persist as a subclinical infection without producing symptoms of severe gastroenteritis. This study shows that WBE can be used to explore trends in community infectious disease patterns which may not be reflected in clinical monitoring, shedding light on overall enteric disease burden and rates of asymptomatic cases.

Population-level surveillance of antibiotic resistance in Escherichia coli through sewage analysis

IntroductionThe occurrence of antibiotic resistance in faecal bacteria in sewage is likely to reflect the current local clinical resistance situation.AimThis observational study investigated the relationship between Escherichia coli resistance rates in sewage and clinical samples representing the same human populations.MethodsE. coli were isolated from eight hospital (n = 721 isolates) and six municipal (n = 531 isolates) sewage samples, over 1 year in Gothenburg, Sweden. An inexpensive broth screening method was validated against disk diffusion and applied to determine resistance against 11 antibiotics in sewage isolates. Resistance data on E. coli isolated from clinical samples from corresponding local hospital and primary care patients were collected during the same year and compared with those of the sewage isolates by linear regression.ResultsE. coli resistance rates derived from hospital sewage and hospital patients strongly correlated (r2 = 0.95 for urine and 0.89 for blood samples), as did resistance rates in E. coli from municipal sewage and primary care urine samples (r2 = 0.82). Resistance rates in hospital sewage isolates were close to those in hospital clinical isolates while resistance rates in municipal sewage isolates were about half of those measured in primary care isolates. Resistance rates in municipal sewage isolates were more stable between sampling occasions than those from hospital sewage.ConclusionOur findings provide support for development of a low-cost, sewage-based surveillance system for antibiotic resistance in E. coli, which could complement current monitoring systems and provide clinically relevant antibiotic resistance data for countries and regions where surveillance is lacking.

Surveillance of antibiotic resistant Escherichia coli in human populations through urban wastewater in ten European countries

Antibiotic resistance surveillance data is lacking in many parts of the world, limiting effective therapy and management of resistance development. Analysis of urban wastewater, which contains bacteria from thousands of individuals, opens up possibilities to generate informative surveillance data in a standardized and resource-efficient way. Here, we evaluate the relationship between antibiotic resistance prevalence in E. coli from wastewater and clinical samples by studying countries with different resistance situations as assessed by traditional clinical surveillance. Composite, influent wastewater samples were collected over 24 h from treatment plants serving major cities in ten European countries. Using a broth screening method, resistance to six antibiotic classes was analyzed for 2507 E. coli isolates (n = 247-252 per country). Resistance prevalence in wastewater E. coli was compared to that in clinical E. coli reported by the European Antibiotic Resistance Surveillance Network. Resistance prevalence was lower in wastewater than clinical E. coli but followed similar geographic trends. Significant relationships were found for resistance to aminopenicillins (R² = 0.72, p = 0.0019) and fluoroquinolones (R² = 0.62, p = 0.0072), but not for aminoglycosides (R² = 0.13, p = 0.31) and third-generation cephalosporins (R² = 0.00, p = 0.99) where regression analyses were based on considerably fewer resistant isolates. When all four antibiotic classes were taken into account, the relationship was strong (R² = 0.85, p < 0.0001). Carbapenem resistance was rare in both wastewater and clinical isolates. Wastewater monitoring shows promise as method for generating surveillance data reflecting the clinical prevalence of antibiotic resistant bacteria. Such data may become especially valuable in regions where clinical surveillance is currently limited.

Size distribution, biological characteristics and emerging contaminants of aerosols emitted from an urban wastewater treatment plant

Air-liquid exchange process could spread pathogens and pharmaceutical emerging pollutants into the air as aerosol particles in an Urban wastewater treatment plants (UWTPs). These particles can later be transported to places where such pollution is unforeseen. In this study, measurements were conducted in the aeration area of a UWTP in northern Taiwan. According to this investigation, nanoparticles are major contributors to both the number and volume concentration of particles. Most fluorescent particles may be bacterial aggregates or fungal species. Moreover, nine common emerging contaminants were analyzed and found in both air and water samples. Among these contaminants, the most abundant chemicals in the air were erythromycin-H₂O (191.45 pg/m³) and methamphetamine (39.02 pg/m³). These results imply that UWTPs could be an emission source of emerging contaminants and bioaerosols, and the potential risk of inhalation exposure should be carefully evaluated.

Characterization of Salmonella Isolates from Wastewater Treatment Plant Influents to Estimate Unreported Cases and Infection Sources of Salmonellosis

Salmonella enterica is a major cause of gastroenteritis usually caused by animal-based contaminated foods. Since the current passive surveillance is not sufficient to detect all infections and infection sources, we determined the prevalence of Salmonella isolated from sewage influent of wastewater treatment plants (WWTPs) and compared the characteristics of human and food isolates to identify the infection sources. Sewage influent samples were collected monthly from two WWTPs located in the Yamanashi Prefecture, Japan, for three years. Serotypes, antimicrobial resistances, isolation periods, isolated areas, and pulsed-field gel electrophoresis patterns of six isolates belonging to five serotypes were consistent with those of the isolates from patients. Real-time PCR for Salmonella indicated that sewage influents reflect cases of patients infected with Salmonella, including unreported cases. Serovars Schwarzengrund and Anatum were predominant in sewage, but not in humans, and their characteristics were closely related or identical to those isolated from poultry heart and liver, respectively. These results suggest that sewage influent contains Salmonella isolates from humans and that some originated from unreported human cases infected by poultry-associated products. Therefore, it is necessary to take countermeasures against Salmonella infection based on the unreported cases, which would be disclosed by analysis of sewage influent.

Characterization and evolution of antibiotic resistance of Salmonella in municipal wastewater treatment plants

The objective of this study was to investigate the evolution of antibiotic resistance phenotypes, antibiotic resistance genes (ARGs) and Class 1 integron of Salmonella in municipal wastewater treatment plants (WWTPs). A total of 221 Salmonella strains were isolated from different stages of three WWTPs. After the susceptibility testing, high frequency of resistance was observed for tetracycline (TET, 47.5% of isolates) and sulfamethoxazole (SMZ, 38.5%), followed by ampicillin (AMP, 25.3%), streptomycin (STP, 17.6%), chloramphenicol (CHL, 15.4%), and gentamicin (GEN, 11.3%). Low prevalence of resistance was detected for norfloxacin (0.45%), ciprofloxacin (0.9%), and cefotaxime (0.9%). The tetA and sul3 genes were most frequently detected among the Salmonella isolates. Statistically significant correlations among AMP, CHL, GEN, and STP resistances were observed. High detection frequencies of Class 1 integron were observed in double antibiotic-resistant and multiple-antibiotic-resistant (MAR) Salmonella, which were 94.3% and 85.7%, respectively. The proliferation of MAR Salmonella and transfer of ARGs occurred in WWTPs. Class 1 integron plays a crucial role in the evolution of MAR Salmonella during WWTPs.

Repeated Isolation of Extended-Spectrum-β-Lactamase-Positive Escherichia coli Sequence Types 648 and 131 from Community Wastewater Indicates that Sewage Systems Are Important Sources of Emerging Clones of Antibiotic-Resistant Bacteria

Antibiotic resistance in bacteria is an emerging problem globally. Resistant bacteria are found in human and animal microbiota, as well as in the environment. Wastewater receives bacteria from all these sources and thus can provide a measurement of abundance and diversity of antibiotic-resistant bacteria circulating in communities. In this study, water samples were collected from a wastewater pump station in a Norwegian suburban community over a period of 15 months. A total of 45 daily samples were cultured and analyzed for the presence of Escherichia coli Eighty E. coli-like colonies were collected from each daily sample and then phenotyped and analyzed for antibiotic resistance using the PhenePlate-AREB system. During the sampling period, two unique E. coli phenotypes with resistance to cefotaxime and cefpodoxime indicating carriage of extended-spectrum β-lactamases (ESBL) were observed repeatedly. Whole-genome sequencing of 15 representative isolates from the two phenotypes identified these as two distinct clones belonging to the two globally spread E. coli multilocus sequence types (STs) ST131 and ST648 and carrying blaCTX-M-15 The number of ESBL-positive E. coli strains in the community wastewater pump station was 314 of 3,123 (10%) analyzed E. coli strains. Of the ESBL-positive isolates, 37% belonged to ST648, and 7% belonged to ST131. Repeated findings of CTX-M-15-positive ST648 and ST131 over time indicate that these STs are resident in the analyzed wastewater systems and/or circulate abundantly in the community.

Clinically Unreported Salmonellosis Outbreak Detected via Comparative Genomic Analysis of Municipal Wastewater Salmonella Isolates

Municipal wastewater includes human waste that contains both commensal and pathogenic enteric microorganisms, and this collective community microbiome can be monitored for community diseases. In a previous study, we assessed the salmonellosis disease burden using municipal wastewater from Honolulu, Hawaii, which was monitored over a 54-week period. During that time, a strain of Salmonella enterica serovar Paratyphi B variant L(+) tartrate(+) (also known as Salmonella enterica serovar Paratyphi B variant Java) was identified; this strain was detected simultaneously with a clinically reported outbreak, and pulsed-field gel electrophoresis patterns were identical for clinical and municipal wastewater isolates. Months after the outbreak subsided, the same pulsotype was detected as the dominant pulsotype in municipal wastewater samples, with no corresponding clinical cases reported. Using genomic characterization (including core single-nucleotide polymorphism alignment, core genome multilocus sequence typing, and screening for virulence and antibiotic resistance genes), all S Java municipal wastewater isolates were determined to be clonal, indicating a resurgence of the original outbreak strain. This demonstrates the feasibility and utility of municipal wastewater surveillance for determining enteric disease outbreaks that may be missed by traditional clinical surveillance methods.IMPORTANCE Underdetection of microbial infectious disease outbreaks in human communities carries enormous health costs and is an ongoing problem in public health monitoring (which relies almost exclusively on data from health clinics). Surveillance of municipal wastewater for community-level monitoring of infectious disease burdens has the potential to fill this information gap, due to its easy access to the mixed community microbiome. In the present study, the genomes of 21 S Java isolates (collected from municipal wastewater in Honolulu) were analyzed; results showed that the same Salmonella strain that caused a known salmonellosis clinical outbreak in spring 2010 remerged as the most dominant strain in municipal wastewater in spring 2011, indicating a new outbreak that was not detected by health clinics. Our results show that wastewater monitoring holds great promise to inform the field of public health regarding outbreak status within communities.

Wastewater microbial community structure and functional traits change over short timescales

Wastewater contains microorganisms coming from various sources, e.g. feces discharges, soil infiltrations and sewer biofilms and sediments. The primary objective of this work was to determine if end-of-pipe wastewater microbial community structures exhibits short-timescale variation, and assess possible microbial origins. To this end, we measured hourly physicochemical characteristics of wastewater influent for 2 days and analyzed the microbial community at 4-h intervals using 16S rRNA gene amplicon sequencing. Results showed large variations in the microbial community composition at phylum and genus levels, i.e. Proteobacteria ranged from 44 to 63% of the total relative abundance and Arcobacter ranged from 11 to 22%. Diurnal patterns were observed in the alpha-diversity, beta-diversity and the prevalence of several taxa. Wastewater physicochemical characteristics explained 61% of the total microbial community variance by Canonical Correspondence Analysis (CCA), with flow rate being the main explanatory variable exhibiting a clear diurnal profile. Comparison with public databases using closed reference OTUs revealed that only 7.3% of the sequences were shared with human gut microbiota and 21.7% with soil microbiota, the majority being from the sewer biofilms and sediments. The functional trait, weighted average ribosomal RNA operon (rrn) copy number per genome, was found to be relatively high in the wastewater microbiota (average 3.6, soil 2.1, and human gut 2.6) and significantly correlated with flow, inferring active microbial enrichments in the sewer. The prevalence of Methylophilaceae, methanol oxidation genes and denitrification genes were related to high influent methanol and NO₃^- concentration in the influent wastewater. These functional organisms and genes indicate important carbon and nutrient removal related functions in the sewer. Together, the observed temporal patterns of the microbial community and functional traits suggest that high wastewater flow causes greater transport of active sewer microorganisms which are functionally important.