Bioinformatics-based screening tool identifies a wide variety of human and zoonotic viruses in Trujillo-Peru wastewater.

Peru was one of the most affected countries during the COVID-19 pandemic. Moreover, multiple other viral diseases (enteric, respiratory, bloodborne, and vector-borne) are endemic and rising. According to Peru's Ministry of Health, various health facilities in the country were reallocated for the COVID-19 pandemic, thereby leading to reduced action to curb other diseases. Many viral diseases in the area are under-reported and not recognized. The One Health approach, in addition to clinical testing, incorporates environmental surveillance for detection of infectious disease outbreaks. The purpose of this work is to use a screening tool that is based on molecular methods, high throughput sequencing and bioinformatics analysis of wastewater samples to identify virus-related diseases circulating in Trujillo-Peru. To demonstrate the effectiveness of the tool, we collected nine untreated wastewater samples from the Covicorti wastewater utility in Trujillo-Peru on October 22, 2022. High throughput metagenomic sequencing followed by bioinformatic analysis was used to assess the viral diversity of the samples. Our results revealed the presence of sequences associated with multiple human and zoonotic viruses including Orthopoxvirus, Hepatovirus, Rhadinovirus, Parechovirus, Mamastrovirus, Enterovirus, Varicellovirus, Norovirus, Kobuvirus, Bocaparvovirus, Simplexvirus, Spumavirus, Orthohepevirus, Cardiovirus, Molliscipoxvirus, Salivirus, Parapoxvirus, Gammaretrovirus, Alphavirus, Lymphocryptovirus, Erythroparvovirus, Sapovirus, Cosavirus, Deltaretrovirus, Roseolovirus, Flavivirus, Betacoronavirus, Rubivirus, Lentivirus, Betapolyomavirus, Rotavirus, Hepacivirus, Alphacoronavirus, Mastadenovirus, Cytomegalovirus and Alphapapillomavirus. For confirmation purposes, we tested the samples for the presence of selective viruses belonging to the genera detected above. PCR based molecular methods confirmed the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), monkeypox virus (MPXV), noroviruses GI and GII (NoVGI and NoVGII), and rotavirus A (RoA) in our samples. Furthermore, publicly available clinical data for selected viruses confirm our findings. Wastewater or other environmental media surveillance, combined with bioinformatics methods, has the potential to serve as a systematic screening tool for the identification of human or zoonotic viruses that may cause disease. The results of this method can guide further clinical surveillance efforts and allocation of resources. Incorporation of this bioinformatic-based screening tool by public health officials in Peru and other Latin American countries will help manage endemic and emerging diseases that could save human lives and resources.

A broad wastewater screening and clinical data surveillance for virus-related diseases in the metropolitan Detroit area in Michigan.

BACKGROUND: Periodic bioinformatics-based screening of wastewater for assessing the diversity of potential human viral pathogens circulating in a given community may help to identify novel or potentially emerging infectious diseases. Any identified contigs related to novel or emerging viruses should be confirmed with targeted wastewater and clinical testing. RESULTS: During the COVID-19 pandemic, untreated wastewater samples were collected for a 1-year period from the Great Lakes Water Authority Wastewater Treatment Facility in Detroit, MI, USA, and viral population diversity from both centralized interceptor sites and localized neighborhood sewersheds was investigated. Clinical cases of the diseases caused by human viruses were tabulated and compared with data from viral wastewater monitoring. In addition to Betacoronavirus, comparison using assembled contigs against a custom Swiss-Prot human virus database indicated the potential prevalence of other pathogenic virus genera, including: Orthopoxvirus, Rhadinovirus, Parapoxvirus, Varicellovirus, Hepatovirus, Simplexvirus, Bocaparvovirus, Molluscipoxvirus, Parechovirus, Roseolovirus, Lymphocryptovirus, Alphavirus, Spumavirus, Lentivirus, Deltaretrovirus, Enterovirus, Kobuvirus, Gammaretrovirus, Cardiovirus, Erythroparvovirus, Salivirus, Rubivirus, Orthohepevirus, Cytomegalovirus, Norovirus, and Mamastrovirus. Four nearly complete genomes were recovered from the Astrovirus, Enterovirus, Norovirus and Betapolyomavirus genera and viral species were identified. CONCLUSIONS: The presented findings in wastewater samples are primarily at the genus level and can serve as a preliminary "screening" tool that may serve as indication to initiate further testing for the confirmation of the presence of species that may be associated with human disease. Integrating innovative environmental microbiology technologies like metagenomic sequencing with viral epidemiology offers a significant opportunity to improve the monitoring of, and predictive intelligence for, pathogenic viruses, using wastewater.

Targeting a free viral fraction enhances the early alert potential of wastewater surveillance for SARS-CoV-2: a methods comparison spanning the transition between delta and omicron variants in a large urban center.

Introduction: Wastewater surveillance has proven to be a valuable approach to monitoring the spread of SARS-CoV-2, the virus that causes Coronavirus disease 2019 (COVID-19). Recognizing the benefits of wastewater surveillance as a tool to support public health in tracking SARS-CoV-2 and other respiratory pathogens, numerous wastewater virus sampling and concentration methods have been tested for appropriate applications as well as their significance for actionability by public health practices. Methods: Here, we present a 34-week long wastewater surveillance study that covers nearly 4 million residents of the Detroit (MI, United States) metropolitan area. Three primary concentration methods were compared with respect to recovery of SARS-CoV-2 from wastewater: Virus Adsorption-Elution (VIRADEL), polyethylene glycol precipitation (PEG), and polysulfone (PES) filtration. Wastewater viral concentrations were normalized using various parameters (flow rate, population, total suspended solids) to account for variations in flow. Three analytical approaches were implemented to compare wastewater viral concentrations across the three primary concentration methods to COVID-19 clinical data for both normalized and non-normalized data: Pearson and Spearman correlations, Dynamic Time Warping (DTW), and Time Lagged Cross Correlation (TLCC) and peak synchrony. Results: It was found that VIRADEL, which captures free and suspended virus from supernatant wastewater, was a leading indicator of COVID-19 cases within the region, whereas PEG and PES filtration, which target particle-associated virus, each lagged behind the early alert potential of VIRADEL. PEG and PES methods may potentially capture previously shed and accumulated SARS-CoV-2 resuspended from sediments in the interceptors. Discussion: These results indicate that the VIRADEL method can be used to enhance the early-warning potential of wastewater surveillance applications although drawbacks include the need to process large volumes of wastewater to concentrate sufficiently free and suspended virus for detection. While lagging the VIRADEL method for early-alert potential, both PEG and PES filtration can be used for routine COVID-19 wastewater monitoring since they allow a large number of samples to be processed concurrently while being more cost-effective and with rapid turn-around yielding results same day as collection.

Wastewater surveillance beyond COVID-19: a ranking system for communicable disease testing in the tri-county Detroit area, Michigan, USA.

Introduction: Throughout the coronavirus disease 2019 (COVID-19) pandemic, wastewater surveillance has been utilized to monitor the disease in the United States through routine national, statewide, and regional monitoring projects. A significant canon of evidence was produced showing that wastewater surveillance is a credible and effective tool for disease monitoring. Hence, the application of wastewater surveillance can extend beyond monitoring SARS-CoV-2 to encompass a diverse range of emerging diseases. This article proposed a ranking system for prioritizing reportable communicable diseases (CDs) in the Tri-County Detroit Area (TCDA), Michigan, for future wastewater surveillance applications at the Great Lakes Water Authority's Water Reclamation Plant (GLWA's WRP). Methods: The comprehensive CD wastewater surveillance ranking system (CDWSRank) was developed based on 6 binary and 6 quantitative parameters. The final ranking scores of CDs were computed by summing the multiplication products of weighting factors for each parameter, and then were sorted based on decreasing priority. Disease incidence data from 2014 to 2021 were collected for the TCDA. Disease incidence trends in the TCDA were endowed with higher weights, prioritizing the TCDA over the state of Michigan. Results: Disparities in incidences of CDs were identified between the TCDA and state of Michigan, indicating epidemiological differences. Among 96 ranked CDs, some top ranked CDs did not present relatively high incidences but were prioritized, suggesting that such CDs require significant attention by wastewater surveillance practitioners, despite their relatively low incidences in the geographic area of interest. Appropriate wastewater sample concentration methods are summarized for the application of wastewater surveillance as per viral, bacterial, parasitic, and fungal pathogens. Discussion: The CDWSRank system is one of the first of its kind to provide an empirical approach to prioritize CDs for wastewater surveillance, specifically in geographies served by centralized wastewater collection in the area of interest. The CDWSRank system provides a methodological tool and critical information that can help public health officials and policymakers allocate resources. It can be used to prioritize disease surveillance efforts and ensure that public health interventions are targeted at the most potentially urgent threats. The CDWSRank system can be easily adopted to geographical locations beyond the TCDA.

Simple methods for early warnings of COVID-19 surges: Lessons learned from 21 months of wastewater and clinical data collection in Detroit, Michigan, United States.

Wastewater-based epidemiology (WBE) has drawn great attention since the Coronavirus disease 2019 (COVID-19) pandemic, not only due to its capability to circumvent the limitations of traditional clinical surveillance, but also due to its potential to forewarn fluctuations of disease incidences in communities. One critical application of WBE is to provide "early warnings" for upcoming fluctuations of disease incidences in communities which traditional clinical testing is incapable to achieve. While intricate models have been developed to determine early warnings based on wastewater surveillance data, there is an exigent need for straightforward, rapid, broadly applicable methods for health departments and partner agencies to implement. Our purpose in this study is to develop and evaluate such early-warning methods and clinical-case peak-detection methods based on WBE data to mount an informed public health response. Throughout an extended wastewater surveillance period across Detroit, MI metropolitan area (the entire study period is from September 2020 to May 2022) we designed eight early-warning methods (three real-time and five post-factum). Additionally, we designed three peak-detection methods based on clinical epidemiological data. We demonstrated the utility of these methods for providing early warnings for COVID-19 incidences, with their counterpart accuracies evaluated by hit rates. "Hit rates" were defined as the number of early warning dates (using wastewater surveillance data) that captured defined peaks (using clinical epidemiological data) divided by the total number of early warning dates. Hit rates demonstrated that the accuracy of both real-time and post-factum methods could reach 100 %. Furthermore, the results indicate that the accuracy was influenced by approaches to defining peaks of disease incidence. The proposed methods herein can assist health departments capitalizing on WBE data to assess trends and implement quick public health responses to future epidemics. Besides, this study elucidated critical factors affecting early warnings based on WBE amid the COVID-19 pandemic.

Surveillance of SARS-CoV-2 in nine neighborhood sewersheds in Detroit Tri-County area, United States: Assessing per capita SARS-CoV-2 estimations and COVID-19 incidence.

Wastewater-based epidemiology (WBE) has been suggested as a useful tool to predict the emergence and investigate the extent of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we screened appropriate population biomarkers for wastewater SARS-CoV-2 normalization and compared the normalized SARS-CoV-2 values across locations with different demographic characteristics in southeastern Michigan. Wastewater samples were collected between December 2020 and October 2021 from nine neighborhood sewersheds in the Detroit Tri-County area. Using reverse transcriptase droplet digital polymerase chain reaction (RT-ddPCR), concentrations of N1 and N2 genes in the studied sites were quantified, with N1 values ranging from 1.92 × 102 genomic copies/L to 6.87 × 103 gc/L and N2 values ranging from 1.91 × 102 gc/L to 6.45 × 103 gc/L. The strongest correlations were observed with between cumulative COVID-19 cases per capita (referred as COVID-19 incidences thereafter), and SARS-CoV-2 concentrations normalized by total Kjeldahl nitrogen (TKN), creatinine, 5-hydroxyindoleacetic acid (5-HIAA) and xanthine when correlating the per capita SARS-CoV-2 and COVID-19 incidences. When SARS-CoV-2 concentrations in wastewater were normalized and compared with COVID-19 incidences, the differences between neighborhoods of varying demographics were reduced as compared to differences observed when comparing non-normalized SARS-CoV-2 with COVID-19 cases. This indicates when studying the disease burden in communities of different demographics, accurate per capita estimation is of great importance. The study suggests that monitoring selected water quality parameters or biomarkers, along with RNA concentrations in wastewater, will allow adequate data normalization for spatial comparisons, especially in areas where detailed sanitary sewage flows and contributing populations in the catchment areas are not available. This opens the possibility of using WBE to assess community infections in rural areas or the developing world where the contributing population of a sample could be unknown.

Five-week warning of COVID-19 peaks prior to the Omicron surge in Detroit, Michigan using wastewater surveillance.

Wastewater-based epidemiology (WBE) is useful in predicting temporal fluctuations of COVID-19 incidence in communities and providing early warnings of pending outbreaks. To investigate the relationship between SARS-CoV-2 concentrations in wastewater and COVID-19 incidence in communities, a 12-month study between September 1, 2020, and August 31, 2021, prior to the Omicron surge, was conducted. 407 untreated wastewater samples were collected from the Great Lakes Water Authority (GLWA) in southeastern Michigan. N1 and N2 genes of SARS-CoV-2 were quantified using RT-ddPCR. Daily confirmed COVID-19 cases for the City of Detroit, and Wayne, Macomb, Oakland counties between September 1, 2020, and October 4, 2021, were collected from a public data source. The total concentrations of N1 and N2 genes ranged from 714.85 to 7145.98 gc/L and 820.47 to 6219.05 gc/L, respectively, which were strongly correlated with the 7-day moving average of total daily COVID-19 cases in the associated areas, after 5 weeks of the viral measurement. The results indicate a potential 5-week lag time of wastewater surveillance preceding COVID-19 incidence for the Detroit metropolitan area. Four statistical models were established to analyze the relationship between SARS-CoV-2 concentrations in wastewater and COVID-19 incidence in the study areas. Under a 5-week lag time scenario with both N1 and N2 genes, the autoregression model with seasonal patterns and vector autoregression model were more effective in predicting COVID-19 cases during the study period. To investigate the impact of flow parameters on the correlation, the original N1 and N2 gene concentrations were normalized by wastewater flow parameters. The statistical results indicated the optimum models were consistent for both normalized and non-normalized data. In addition, we discussed parameters that explain the observed lag time. Furthermore, we evaluated the impact of the omicron surge that followed, and the impact of different sampling methods on the estimation of lag time.

Identification of multiple potential viral diseases in a large urban center using wastewater surveillance.

Viruses are linked to a multitude of human illnesses and can disseminate widely in urbanized environments causing global adverse impacts on communities and healthcare infrastructures. Wastewater-based epidemiology was employed using metagenomics and quantitative polymerase chain reaction (qPCR) assays to identify enteric and non-enteric viruses collected from a large urban area for potential public health monitoring and outbreak analysis. Untreated wastewater samples were collected from November 2017 to February 2018 (n = 54) to evaluate the diversity of human viral pathogens in collected samples. Viruses were classified into virus types based on primary transmission routes and reviewed against viral associated diseases reported in the catchment area. Metagenomics detected the presence of viral pathogens that cause clinically significant diseases reported within the study area during the sampling year. Detected viruses belong to the Adenoviridae, Astroviridae, Caliciviridae, Coronaviridae, Flaviviridae, Hepeviridae, Herpesviridae, Matonaviridae, Papillomaviridae, Parvoviridae, Picornaviridae, Poxviridae, Retroviridae, and Togaviridae families. Furthermore, concentrations of adenovirus, norovirus GII, sapovirus, hepatitis A virus, human herpesvirus 6, and human herpesvirus 8 were measured in wastewater samples and compared to metagenomic findings to confirm detected viral genus. Hepatitis A virus obtained the greatest average viral load (1.86 × 107 genome copies/L) in wastewater samples compared to other viruses quantified using qPCR with a 100% detection rate in metagenomic samples. Average concentration of sapovirus (1.36 × 106 genome copies/L) was significantly greater than norovirus GII (2.94 × 104 genome copies/L) indicating a higher burden within the study area. Findings obtained from this study aid in evaluating the utility of wastewater-based epidemiology for identification and routine monitoring of various viruses in large communities. This methodology has the potential to improve public health responses to large scale outbreaks and viral pandemics.

Understanding temporal and spatial variations of viral disease in the US: The need for a one-health-based data collection and analysis approach.

Viral diseases exhibit spatial and temporal variation, and there are many factors that can affect their occurrence. The identification of these factors is critical in the efforts to predict and lessen viral disease burden. Because viral infection is able to spread to humans from the environment, animals, and other humans, the One-Health framework can be used to investigate the critical pathways through which viruses are transported and transmitted. A holistic approach, incorporating publicly available clinical data for human, livestock, and wildlife disease occurrence, together with environmental data reported in federal and state databases such as parameters related to land use, environmental quality, and weather, can enhance the understanding of variations in disease patterns, leading to the design and implementation of surveillance systems. An example analysis approach is presented for Michigan, United States, which is a state with large urban centers as well as a sizeable rural and agricultural population. Analysis of publicly available data from 2017 indicates that gastrointestinal (GI) and influenza-associated illnesses in Michigan may have been related with agricultural land use to a higher extent than with developed land use during that year. Meanwhile, hepatitis A virus appears to be most closely related with developed land use in dense population areas. GI illnesses may be related to precipitation, and this relationship is strongest in the springtime, although GI illnesses are most common in the winter months. Integration of human-related clinical data, animal disease data, and environmental data can ultimately be used for prioritization of the most critical locations and times for viral outbreaks in both urban and rural environments.

A water-focused one-health approach for early detection and prevention of viral outbreaks.

Despite consistent efforts to protect public health there is still a heavy burden of viral disease, both in the United States and abroad. In addition to conventional medical treatment, there is a need for a holistic approach for early detection and prevention of viral outbreaks at a population level. One-Health is a relatively new integrative approach to the solving of global health challenges. A key component to the One-Health approach is the notion that human health, animal health, and environmental health are all innately interrelated. One-Health interventions, initiated by veterinary doctors, have proven to be effective in controlling outbreaks, but thus far the applications focus on zoonotic viruses transmitted from animals to humans. Environmental engineers and environmental scientists hold a critical role in the further development of One-Health approaches that include water-related transport and transmission of human, animal, and zoonotic viruses. In addition to waterborne viruses, the proposed approach is applicable to a wide range of viruses that are found in human excrement since contaminated water-based surveillance systems may be used for early detection of viral disease. This paper proposes a greater One-Health based framework that involves water-related pathways. The first step in the proposed framework is the identification of critical exposure pathways of viruses in the water environment. Identification of critical pathways informs the second and third steps, which include water-based surveillance systems for early detection at a population level and implementation of intervention approaches to block the critical pathways of exposure.

Viral diversity and abundance in polluted waters in Kampala, Uganda.

Waterborne viruses are a significant cause of human disease, especially in developing countries such as Uganda. A total of 15 virus-selective samples were collected at five sites (Bugolobi Wastewater Treatment Plant (WWTP) influent and effluent, Nakivubo Channel upstream and downstream of the WWTP, and Nakivubo Swamp) in July and August 2016. Quantitative PCR and quantitative RT-PCR was performed to determine the concentrations of four human viruses (adenovirus, enterovirus, rotavirus, and hepatitis A virus) in the samples. Adenovirus (1.53*105-1.98*107 copies/L) and enterovirus (3.17*105-8.13*107 copies/L) were found to have the highest concentrations in the samples compared to rotavirus (5.79*101-3.77*103 copies/L) and hepatitis A virus (9.93*102-1.11*104 copies/L). In addition, next-generation sequencing and metagenomic analyses were performed to assess viral diversity, and several human and vertebrate viruses were detected, including Herpesvirales, Iridoviridae, Poxviridae, Circoviridae, Parvoviridae, Bunyaviridae and others. Effluent from the wastewater treatment plant appears to impact surface water, as samples taken from surface water downstream of the treatment plant had higher viral concentrations than samples taken upstream. Temporal fluctuations in viral abundance and diversity were also observed. Continuous monitoring of wastewater may contribute to assessing viral disease patterns at a population level and provide early warning of potential outbreaks using wastewater-based epidemiology methods.

Diversity of DNA viruses in effluents of membrane bioreactors in Traverse City, MI (USA) and La Grande Motte (France).

This study assesses diversity of DNA viruses in the effluents of two membrane bioreactor (MBR) wastewater treatment plants (WWTPs): an MBR in the United States and an MBR in France. Viral diversity of these effluents is compared to that of a conventional activated sludge WWTP in the U.S. Diversity analysis indicates Herpesvirales to be the most abundant order of potentially pathogenic human DNA viruses in wastewater treated effluent in all utilities. Other potentially pathogenic human viruses detected include Adenoviridae, Parvoviridae, and Polyomaviridae. Bacteriophage order Caudovirales comprises the majority of DNA virus sequences in the effluent of all utilities. The choice of treatment process (MBR versus activated sludge reactor) utilized had no impact on effluent DNA viral diversity. In contrast, the type of disinfection applied had an impact on the viral diversity present in the effluent.

Elution Is a Critical Step for Recovering Human Adenovirus 40 from Tap Water and Surface Water by Cross-Flow Ultrafiltration.

UNLABELLED: This paper examines the recovery of the enteric adenovirus human adenovirus 40 (HAdV 40) by cross-flow ultrafiltration and interprets recovery values in terms of physicochemical interactions of virions during sample concentration. Prior to ultrafiltration, membranes were either blocked by exposure to calf serum (CS) or coated with a polyelectrolyte multilayer (PEM). HAdV 40 is a hydrophobic virus with a point of zero charge between pH 4.0 and pH 4.3. In accordance with predictions from the extended Derjaguin-Landau-Verwey-Overbeek theory, the preelution recovery of HAdV (rpre) from deionized water was higher with PEM-coated membranes (rpre (PEM) = 74.8% ± 9.7%) than with CS-blocked membranes (rpre (CS) = 54.1% ± 6.2%). With either membrane type, the total virion recovery after elution (rpost) was high for both deionized water (rpost (PEM) = 99.5% ± 6.6% and rpost (CS) = 98.8% ± 7.7%) and tap water (rpost (PEM) = 89% ± 15% and rpost (CS) = 93.7% ± 6.9%). The nearly 100% recoveries suggest that the polyanion (sodium polyphosphate) and surfactant (Tween 80) in the eluent disrupt electrostatic and hydrophobic interactions between the virion and the membrane. Addition of EDTA to the eluent greatly improved the elution efficacy (rpost (CS) = 88.6% ± 4.3% and rpost (PEM) = 87.0% ± 6.9%) with surface water, even when the organic carbon concentration in the water was high (9.4 ± 0.1 mg/liter). EDTA likely disrupts cation bridging between virions and particles in the feed water matrix or the fouling layer on the membrane surface. For complex water matrices, the eluent composition is the most important factor for achieving high virion recovery. IMPORTANCE: Herein we present the results of a comprehensive physicochemical characterization of HAdV 40, an important human pathogen. The data on HAdV 40 surface properties enabled rigorous modeling to gain an understanding of the energetics of virion-virion and virion-filter interactions. Cross-flow filtration for concentration and recovery of HAdV 40 was evaluated, with postelution recoveries from ultrapure water (99%), tap water (∼91%), and high-carbon-content surface water (∼84%) being demonstrated. These results are significant because of the very low adenovirus recoveries that have been reported, to date, for other methods. The recovery data were interpreted in terms of specific interactions, and the eluent composition was designed accordingly to maximize HAdV 40 recovery.

Effect of pressure relaxation and membrane backwash on adenovirus removal in a membrane bioreactor.

Pressure relaxation and permeate backwash are two commonly used physical methods for membrane fouling mitigation in membrane bioreactor (MBR) systems. In order to assess the impact of these methods on virus removal by MBRs, experiments were conducted in a bench-scale submerged MBR treating synthetic wastewater. The membranes employed were hollow fibers with the nominal pore size of 0.45 µm. The experimental variables included durations of the filtration (tTMP>0), pressure relaxation (tTMP=0) and backwash (tTMP<0) steps. Both pressure relaxation and permeate backwash led to significant reductions in removal of human adenovirus (HAdV). For the same value of tTMP>0/tTMP=0, longer filtration/relaxation cycles (i.e. larger tTMP+tTMP=0) led to higher transmembrane pressure (TMP) but did not have a significant impact on HAdV removal. A shorter backwash (tTMP<0 = 10 min) at a higher flow rate (Q = 40 mL/min) resulted in more substantial decreases in TMP and HAdV removal than a longer backwash (tTMP<0 = 20 min) at a lower flow rate (Q = 20 mL/min) even though the backwash volume (QtTMP<0) was the same. HAdV removal returned to pre-cleaning levels within 16 h after backwash was applied. Moderate to strong correlations (R(2) = 0.63 to 0.94) were found between TMP and HAdV removal.

Effect of organic carbon on sorption of human adenovirus to soil particles and laboratory containers.

A key factor controlling the relationship between virus release and human exposure is how virus particles interact with soils, sediments and other solid particles in the environment and in engineered treatment systems. Finding no previous investigations of human adenovirus (HAdV) sorption, we performed a series of experiments to evaluate the role of soil organic carbon (SOC) and solution-phase dissolved organic carbon (DOC) on sorption capacity and reversibility. In preliminary methodological studies, we found that as much as 99% of HAdV was lost from inorganic buffer suspensions in polypropylene (PP) laboratory containers, but little loss occurred when using suspensions with substantial amounts of DOC or with glass containers from either type of suspension. It was confirmed that this loss was due to sorption rather than inactivation by using lysis-based recovery techniques and qPCR measurements that do not depend on virus viability. In isotherm experiments, soils with 2% OC had ≈ four-fold greater sorption capacity for HAdV than 8% OC soils; moreover, the sorption capacity of 2% OC soils was reduced ≈ seven-fold with an aqueous solution containing 150 mg/L of humic acid. After sequential extractions, higher fractions of sorbed HAdV were released from 8% OC soils. The amounts of HAdV and OC released remained relatively constant throughout each extraction step, indicating that desorbed HAdV could be caused primarily by the detachment of SOC from soils. Overall, results from this study suggest that OC plays a critical role in the sorption and desorption of HAdV, and as a result, on its environmental fate and transport.

Leaching and ponding of viral contaminants following land application of biosolids on sandy-loam soil.

Much of the land available for application of biosolids is cropland near urban areas. Biosolids are often applied on hay or grassland during the growing season or on corn ground before planting or after harvest in the fall. In this study, mesophilic anaerobic digested (MAD) biosolids were applied at 56,000 L/ha on a sandy-loam soil over large containment lysimeters seeded to perennial covers of orchardgrass (Dactylis glomerata L.), switchgrass (Panicum virgatum), or planted annually to maize (Zea mays L.). Portable rainfall simulators were to maintain the lysimeters under a nearly saturated (90%, volumetric basis) conditions. Lysimeter leachate and surface ponded water samples were collected and analyzed for somatic phage, adenoviruses, and anionic (chloride) and microbial (P-22 bacteriophage) tracers. Neither adenovirus nor somatic phage was recovered from the leachate samples. P-22 bacteriophage was found in the leachate of three lysimeters (removal rates ranged from 1.8 to 3.2 log(10)/m). Although the peak of the anionic tracer breakthrough occurred at a similar pore volume in each lysimeter (around 0.3 pore volume) the peak of P-22 breakthrough varied between lysimeters (<0.1, 0.3 and 0.7 pore volume). The early time to peak breakthrough of anionic and microbial tracers indicated preferential flow paths, presumably from soil cracks, root channels, worm holes or other natural phenomena. The concentration of viral contaminants collected in ponded surface water ranged from 1 to 10% of the initial concentration in the applied biosolids. The die off of somatic phage and P-22 in the surface water was fit to a first order decay model and somatic phage reached background level at about day ten. In conclusion, sandy-loam soils can effectively remove/adsorb the indigenous viruses leached from the land-applied biosolids, but there is a potential of viral pollution from runoff following significant rainfall events when biosolids remain on the soil surface.

Occurrence of pharmaceuticals in a municipal wastewater treatment plant: mass balance and removal processes.

Occurrence and removal efficiencies of fifteen pharmaceuticals were investigated in a conventional municipal wastewater treatment plant in Michigan. Concentrations of these pharmaceuticals were determined in both wastewater and sludge phases by a high-performance liquid chromatograph coupled to a tandem mass spectrometer. Detailed mass balance analysis was conducted during the whole treatment process to evaluate the contributing processes for pharmaceutical removal. Among the pharmaceuticals studied, demeclocycline, sulfamerazine, erythromycin and tylosin were not detected in the wastewater treatment plant influent. Other target pharmaceuticals detected in wastewater were also found in the corresponding sludge phase. The removal efficiencies of chlortetracycline, tetracycline, sulfamerazine, acetaminophen and caffeine were >99%, while doxycycline, oxytetracycline, sulfadiazine and lincomycin exhibited relatively lower removal efficiencies (e.g., <50%). For sulfamethoxazole, the removal efficiency was approximately 90%. Carbamazepine manifested a net increase of mass, i.e. 41% more than the input from the influent. Based on the mass balance analysis, biotransformation is believed to be the predominant process responsible for the removal of pharmaceuticals (22% to 99%), whereas contribution of sorption to sludge was relatively insignificant (7%) for the investigated pharmaceuticals.

Correlation of tetracycline and sulfonamide antibiotics with corresponding resistance genes and resistant bacteria in a conventional municipal wastewater treatment plant.

Antibiotics and corresponding resistance genes and resistant bacteria have been considered as emerging pollutants worldwide. Wastewater treatment plants (WWTPs) are potential reservoirs contributing to the evolution and spread of antibiotic resistance. In this study, total concentrations of tetracycline and sulfonamide antibiotics in final effluent were detected at 652.6 and 261.1ng/L, respectively, and in treated sludge, concentrations were at 1150.0 and 76.0µg/kg dry weight (dw), respectively. The quantities of antibiotic resistance genes and antibiotic resistant bacteria in final effluent were quantified in the range of 9.12×10(5)-1.05×10(6) gene abundances /100mL (genomic copies/100mL) and 1.05×10(1)-3.09×10(3)CFU/mL, respectively. In treated sludge, they were quantified at concentrations of 1.00×10(8)-1.78×10(9) gene abandances/100mL and 7.08×10(6)-1.91×10(8)CFU/100mL, respectively. Significant reductions (2-3 logs, p<0.05) of antibiotic resistance genes and antibiotic resistant bacteria were observed between raw influent and final effluent. The gene abundances of tetO and tetW normalized to that of 16S rRNA genes indicated an apparent decrease as compared to sulI genes, which remained stable along each treatment stage. Significant correlations (R(2)=0.75-0.83, p<0.05) between numbers of resistant bacteria and antibiotic concentrations were observed in raw influent and final effluent. No significance (R(2)=0.15, p>0.05) was found between tet genes (tetO and tetW) with concentration of tetracyclines identified in wastewater, while a significant correlation (R(2)=0.97, p<0.05) was observed for sulI gene and total concentration of sulfonamides. Correlations of the quantities of antibiotic resistance genes and antibiotic resistant bacteria with corresponding concentrations of antibiotics in sludge samples were found to be considerably weak (R(2)=0.003-0.07).

A perspective on the prevalence of DNA enteric virus genomes in anaerobic-digested biological wastes.

The major goal of this study is to gain a perspective on the prevalence of DNA enteric virus genomes in mesophilic anaerobic-digested (MAD) sewage sludge and manure by comparing their quantitative PCR (qPCR) concentrations and removals with traditional fecal indicators (Escherichia coli, enterococci, and Bacteroidetes). In addition, relationships between qPCR and culture measurements of fecal indicators (FIs) were determined. There was no significant difference between the qPCR concentrations of human adenovirus and E. coli/enterococci in MAD sewage sludge; however, the qPCR concentrations of bovine adenovirus were significantly lower than FIs and bovine polyomavirus (BPyV) in MAD manure. The qPCR concentrations of human polyomavirus were slightly lower than E. coli and enterococci (p ≤ 0.05), but no significant difference was observed between the qPCR concentrations of BPyV and FIs. The digestion treatment achieved higher genome removal of bovine DNA enteric viruses than FIs (p ≤ 0.05). Significant correlations were observed between qPCR and culture measurements of FIs, but the concentrations and removals of FIs determined by qPCR assays were still significantly different than those determined by culture assays. Overall, we determined that the prevalence of DNA enteric virus genomes in MAD biological wastes was high due to their comparable in qPCR concentrations to FIs, indicating that mesophilic anaerobic digestion treatment alone may not be effective enough to remove DNA viral pathogens in biological wastes.

Effect of detection methods on risk estimates of exposure to biosolids-associated human enteric viruses.

This study illustrates the effect of virus detection methods on estimates of risks of infection of biosolids-associated viruses for occupational workers and residential population during a hypothetical exposure of biosolids. Five gastroenteritis-associated human enteric viruses--enteroviruses (echovirus-12, enteroviruse types 68-71), adenoviruses, rotaviruses, and noroviruses genotype--I-were considered to represent human enteric viruses for risk estimation purposes. Ingested viral doses were calculated using literature-reported total infectious virus concentrations (based on BGM and A549 cell lines) and genome copies (GCs) in Michigan dewatered and class B biosolids. Cell-line-based infectivity parameters (i.e., ratio of total infectious virus concentration to GCs) were developed for different viruses in biosolids to use GCs for calculating ingested viral dose, addressing the issue of integration of molecular methods with biosolids-based virus risk assessment. Use of virus concentrations from molecular methods (with and without using cell-line-based infectivity parameter) resulted in higher risk estimates than culture methods, indicating the effect of the virus detection method on risk estimates. Further, use of virus concentrations from A549 cell lines resulted in higher risk estimates compared to those from BGM cell lines, suggesting the need for a proper choice of cell lines in determining infectious viral dose. The Monte Carlo uncertainty analyses of estimates for risk of infection due to enteroviruses showed that enteroviruses concentration was the most important parameter influencing risk estimates, indicating the need for reducing associated uncertainty. More work is required to develop cell-line-based infectivity parameters for different virus concentration levels and sample matrix types using a cut-off-based approach.