RNA viral community in human feces: prevalence of plant pathogenic viruses

Pasteurization, storage conditions and viral concentration methods influence RT-qPCR detection of SARS-CoV-2 RNA in wastewater

The COVID-19 pandemic presents many public health challenges including the tracking of infected individuals from local to regional scales. Wastewater surveillance of viral RNA has emerged as a complementary approach to track and monitor the presence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus in a variety of communities of different land use and population size. In the present study, we investigate how five different parameters (pasteurization, storage temperature, storage time, polyethylene glycol (PEG) concentration, and pellet mass) affect the detection of the SARS-CoV-2 N gene and fecal abundance indicator pepper mild mottle virus (PMMoV) gene. Pre-treatment of 24-h composite wastewater samples (n = 14) by pasteurization at 60 °C resulted in a significant reduction of total RNA concentration and copies of the SARS-CoV-2 N gene copies/L (paired Student's t-test, P < 0.05). Comparing the wastewater samples collected from 6 wastewater treatment plants (WWTPs) for a storage period of 7 and 14 days at 4 °C, -20 °C and -80 °C, demonstrated a decrease in SARS-CoV-2 N gene copies/L when samples were stored for 14 days at -20 °C. Polyethylene glycol-NaCl for purification and concentration of viral particles from the wastewater samples demonstrated that a short PEG incubation of 2 h during centrifugation at 4 °C was sufficient for the consistent detection of the SARS-CoV-2 N gene from a 30 mL sample volume. Combined, this paper presents method recommendations for developing a reliable, accurate, sensitive, and reproducible estimation of the SARS-CoV-2 virus in diverse domestic wastewater samples.

Reduction and discharge of SARS-CoV-2 RNA in Chicago-area water reclamation plants

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA is commonly excreted in the feces and urine of infected individuals and is, therefore, detected in wastewaters where infection is present in the surrounding population. Water reclamation plants (WRPs) that treat these wastewaters commonly discharge treated effluents into the surrounding environment, yet little is known about the removal or persistence of SARS-CoV-2 RNA through wastewater treatment systems and potential for eventual release into the environment. We collected 361 24-hour composite influent and effluent samples from seven WRPs in the Greater Chicago Area in Illinois. Samples were collected over a period of 21 weeks for three large WRPs (with design max flows of 1.89-2.32 billion gallons per day and serving a combined population of 4.62 million people) and 11 weeks for four smaller WRPs (with design max flows of 96.3-186 million gallons per day and serving a combined population of >0.5 million people). A total of two of the larger WRPs implemented seasonal disinfection (using UV light or chlorination/dechlorination) for 8 weeks of this sampling period. SARS-CoV-2 RNA was quantified in the influent and effluent samples by reverse-transcription quantitative PCR (RT-qPCR) of the N1 and N2 targets of the nucleocapsid (N) gene. Although SARS-CoV-2 RNA was regularly detected in influent and effluent from all WRPs, viral RNA concentrations in the effluent samples were considerably lower, with mean effluent: influent gene copy concentration ratios ranging from 1:160 to 1:2.95 between WRPs. Samples collected while disinfection was active vs. inactive did not show any significant difference in the portion of RNA persisting through the treatment process (P > .05).

Wastewater-Based Estimation of the Effective Reproductive Number of SARS-CoV-2

BACKGROUND

The effective reproductive number, R e , is a critical indicator to monitor disease dynamics, inform regional and national policies, and estimate the effectiveness of interventions. It describes the average number of new infections caused by a single infectious person through time. To date, R e estimates are based on clinical data such as observed cases, hospitalizations, and/or deaths. These estimates are temporarily biased when clinical testing or reporting strategies change.

OBJECTIVES

We show that the dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater can be used to estimate R e in near real time, independent of clinical data and without the associated biases.

METHODS

We collected longitudinal measurements of SARS-CoV-2 RNA in wastewater in Zurich, Switzerland, and San Jose, California, USA. We combined this data with information on the temporal dynamics of shedding (the shedding load distribution) to estimate a time series proportional to the daily COVID-19 infection incidence. We estimated a wastewater-based R e from this incidence.

RESULTS

The method to estimate R e from wastewater worked robustly on data from two different countries and two wastewater matrices. The resulting estimates were as similar to the R e estimates from case report data as R e estimates based on observed cases, hospitalizations, and deaths are among each other. We further provide details on the effect of sampling frequency and the shedding load distribution on the ability to infer R e .

DISCUSSION

To our knowledge, this is the first time R e has been estimated from wastewater. This method provides a low-cost, rapid, and independent way to inform SARS-CoV-2 monitoring during the ongoing pandemic and is applicable to future wastewater-based epidemiology targeting other pathogens. https://doi.org/10.1289/EHP10050.

Wastewater-Based Estimation of the Effective Reproductive Number of SARS-CoV-2

BACKGROUND

The effective reproductive number, Re, is a critical indicator to monitor disease dynamics, inform regional and national policies, and estimate the effectiveness of interventions. It describes the average number of new infections caused by a single infectious person through time. To date, Re estimates are based on clinical data such as observed cases, hospitalizations, and/or deaths. These estimates are temporarily biased when clinical testing or reporting strategies change.

OBJECTIVES

We show that the dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater can be used to estimate Re in near real time, independent of clinical data and without the associated biases.

METHODS

We collected longitudinal measurements of SARS-CoV-2 RNA in wastewater in Zurich, Switzerland, and San Jose, California, USA. We combined this data with information on the temporal dynamics of shedding (the shedding load distribution) to estimate a time series proportional to the daily COVID-19 infection incidence. We estimated a wastewater-based Re from this incidence.

RESULTS

The method to estimate Re from wastewater worked robustly on data from two different countries and two wastewater matrices. The resulting estimates were as similar to the Re estimates from case report data as Re estimates based on observed cases, hospitalizations, and deaths are among each other. We further provide details on the effect of sampling frequency and the shedding load distribution on the ability to infer Re.

DISCUSSION

To our knowledge, this is the first time Re has been estimated from wastewater. This method provides a low-cost, rapid, and independent way to inform SARS-CoV-2 monitoring during the ongoing pandemic and is applicable to future wastewater-based epidemiology targeting other pathogens. https://doi.org/10.1289/EHP10050.

Effect of Time and Temperature on SARS-CoV-2 in Municipal Wastewater Conveyance Systems

Wastewater surveillance for SARS-CoV-2 is becoming a widespread public health metric, but little is known about pre-analytical influences on these measurements. We examined SARS-CoV-2 loads from two sewer service areas with different travel times that were within the same metropolitan area. Throughout the one-year study, case rates were nearly identical between the two service areas allowing us to compare differences in empirical concentrations relative to conveyance system characteristics and wastewater treatment plant parameters. We found time did not have a significant effect on degradation of SARS-CoV-2 when using average transit times (22 vs. 7.5 h) (p = 0.08), or under low flow conditions when transit times are greater (p = 0.14). Flow increased rather than decreased SARS-CoV-2 case-adjusted concentrations, but this increase was only significant in one service area. Warmer temperatures (16.8–19.8 °C) compared with colder (8.4–12.3 °C) reduced SARS-CoV-2 case-adjusted loads by ~50% in both plants (p < 0.05). Decreased concentrations in warmer temperatures may be an important factor to consider when comparing seasonal dynamics. Oxygen demand and suspended solids had no significant effect on SARS-CoV-2 case-adjusted loads overall. Understanding wastewater conveyance system influences prior to sample collection will improve comparisons of regional or national data for SARS-CoV-2 community infections.

Rehabilitation of a misbehaving microbiome: phages for the remodeling of bacterial composition and function

The human gut microbiota is considered an adjunct metabolic organ owing to its health impact. Recent studies have shown correlations between gut phage composition and host health. Whereas phage therapy has popularized virulent phages as antimicrobials, both virulent and temperate phages have a natural ecological relationship with their cognate bacteria. Characterization of this evolutionary coadaptation has led to other emergent therapeutic phage applications that do not necessarily rely on bacterial eradication or target pathogens. Here, we present an overview of the tripartite relationship between phages, bacteria, and the mammalian host, and highlight applications of the wildtype and genetically engineered phage for gut microbiome remodeling. In light of new and varied strategies, we propose to categorize phage applications aiming to modulate bacterial composition or function as "phage rehabilitation." By delineating phage rehab from phage therapy, we believe it will enable greater nuance and understanding of these new phage-based technologies.

Cryptic and abundant marine viruses at the evolutionary origins of Earth's RNA virome

Whereas DNA viruses are known to be abundant, diverse, and commonly key ecosystem players, RNA viruses are insufficiently studied outside disease settings. In this study, we analyzed ≈28 terabases of Global Ocean RNA sequences to expand Earth's RNA virus catalogs and their taxonomy, investigate their evolutionary origins, and assess their marine biogeography from pole to pole. Using new approaches to optimize discovery and classification, we identified RNA viruses that necessitate substantive revisions of taxonomy (doubling phyla and adding >50% new classes) and evolutionary understanding. "Species"-rank abundance determination revealed that viruses of the new phyla "Taraviricota," a missing link in early RNA virus evolution, and "Arctiviricota" are widespread and dominant in the oceans. These efforts provide foundational knowledge critical to integrating RNA viruses into ecological and epidemiological models.

Integrating Virus Monitoring Strategies for Safe Non-potable Water Reuse

Wastewater reclamation and reuse have the potential to supplement water supplies, offering resiliency in times of drought and helping meet increased water demands associated with population growth. Non-potable water reuse represents the largest potential reuse market. Yet economic constraints for new water reuse infrastructure and safety concerns due to microbial water quality, and especially viral pathogen exposure, limit widespread implementation of water reuse. Cost-effective, real-time methods to measure or indicate viral quality of recycled water would do much to instill greater confidence in the practice. This manuscript discusses advancements in monitoring and modeling of viral health risks in the context of water reuse. First, we describe the current wastewater reclamation processes and treatment technologies with an emphasis on virus removal. Second, we review technologies for the measurement of viruses, both culture- and molecular-based, along with their advantages and disadvantages. We introduce promising viral surrogates and specific pathogenic viruses that can serve as indicators of viral risk for water reuse. We suggest metagenomic analyses for viral screening and flow cytometry for quantification of virus-like particles as new approaches to complement more traditional methods. Third, we describe modeling to assess health risks through quantitative microbial risk assessments (QMRAs), the most common strategy to couple data on virus concentrations with human exposure scenarios. We then explore the potential of artificial neural networks (ANNs) to incorporate suites of data from wastewater treatment processes, water quality parameters, and viral surrogates. We recommend ANNs as a means to utilize existing water quality data, alongside new complementary measures of viral quality, to achieve cost-effective strategies to assess risks associated with infectious human viruses in recycled water. Given the review, we conclude that technologies are ready for identifying and implementing viral surrogates for health risk reduction in the next decade. Incorporating modeling with monitoring data would likely result in more robust assessment of water reuse risk.

Improving correlation of wastewater SARS-CoV-2 gene copy numbers with COVID-19 public health cases using readily available biomarkers

The COVID-19 pandemic has highlighted the potential role that wastewater-based epidemiology can play in assessing aggregate community health. However, efforts to translate SARS-CoV-2 gene copy numbers obtained from wastewater samples into meaningful community health indicators are nascent. In this study, SARS-CoV-2 nucleocapsid (N) genes (N1 and N2) were quantified weekly using reverse transcriptase droplet digital PCR from two municipal wastewater treatment plants for seven months. Four biomarkers (ammonium, biological oxygen demand (BOD), creatinine, and human mitochondrial gene NADH dehydrogenase subunit 5) were quantified and used to normalize SARS-CoV-2 gene copy numbers. These were correlated to daily new case data and one-, two-, and three-week cumulative case data. Over the course of the study, the strongest correlations were observed with a one-day case data lag. However, early measurements were strongly correlated with a five-day case data lag. This indicates that in the early stages of the pandemic, the wastewater samples may have indicated active COVID-19 cases before clinical indications. Mitochondrial and creatinine normalization methods showed the strongest correlations throughout the study, indicating that human-specific biomarkers were better at normalizing wastewater data than ammonium or BOD. Granger causality tests supported this observation and showed that gene copies in wastewater could be predictive of new cases in a sewershed.

Evaluating the Use of Alternative Normalization Approaches on SARS-CoV-2 Concentrations in Wastewater: Experiences from Two Catchments in Northern Sweden

The detection of SARS-CoV-2 RNA fragments in feces has paved the way for wastewater-based epidemiology to contribute to COVID-19 mitigation measures, with its use in a public health context still under development. As a way to facilitate data comparison, this paper explores the impact of using alternative normalization approaches (wastewater treatment plant (WWTP) flow, population size estimates (derived using total nitrogen (TN), total phosphorus (TP) and census data) and pepper mild mottle virus (PMMoV)) on the relationship between viral wastewater data and clinical case numbers. Influent wastewater samples were collected at two WWTPs in Luleå, northern Sweden, between January and March 2021. TN and TP were determined upon sample collection, with RNA analysis undertaken on samples after one freeze–thaw cycle. The strength of the correlation between normalization approaches and clinical cases differed between WWTPs (r ≤ 0.73 or r ≥ 0.78 at the larger WWTP and r ≤ 0.23 or r ≥ 0.43 at the smaller WWTP), indicating that the use of wastewater as an epidemiological tool is context-dependent. Depending on the normalization approach utilized, time-shifted analyses imply that wastewater data on SARS-CoV-2 RNA pre-dated a rise in clinical cases by 0–2 and 5–8 days, for the lager and smaller WWTPs, respectively. SARS-CoV-2 viral loads normalized to the population or PMMoV better reflect the number of clinical cases when comparing wastewater data between sewer catchments.

Biomarkers Selection for Population Normalization in SARS-CoV-2 Wastewater-based Epidemiology

Wastewater-based epidemiology (WBE) has been one of the most cost-effective approaches to track the SARS-CoV-2 levels in the communities since the COVID-19 outbreak in 2020. Normalizing SARS-CoV-2 concentrations by the population biomarkers in wastewater can be critical for interpreting the viral loads, comparing the epidemiological trends among the sewersheds, and identifying the vulnerable communities. In this study, five population biomarkers, pepper mild mottle virus (pMMoV), creatinine (CRE), 5-hydroxyindoleacetic acid (5-HIAA), caffeine (CAF) and its metabolite paraxanthine (PARA) were investigated for their utility in normalizing the SARS-CoV-2 loads through developed direct and indirect approaches. Their utility in assessing the real-time population contributing to the wastewater was also evaluated. The best performed candidate was further tested for its capacity for improving correlation between normalized SARS-CoV-2 loads and the clinical cases reported in the City of Columbia, Missouri, a university town with a constantly fluctuated population. Our results showed that, except CRE, the direct and indirect normalization approaches using biomarkers allow accounting for the changes in wastewater dilution and differences in relative human waste input over time regardless flow volume and population at any given WWTP. Among selected biomarkers, PARA is the most reliable population biomarker in determining the SARS-CoV-2 load per capita due to its high accuracy, low variability, and high temporal consistency to reflect the change in population dynamics and dilution in wastewater. It also demonstrated its excellent utility for real-time assessment of the population contributing to the wastewater. In addition, the viral loads normalized by the PARA-estimated population significantly improved the correlation ( rho =0.5878, p <0.05) between SARS-CoV-2 load per capita and case numbers per capita. This chemical biomarker offers an excellent alternative to the currently CDC-recommended pMMoV genetic biomarker to help us understand the size, distribution, and dynamics of local populations for forecasting the prevalence of SARS-CoV2 within each sewershed.

HIGHLIGHT bullet points

The paraxanthine (PARA), the metabolite of the caffeine, is a more reliable population biomarker in SARS-CoV-2 wastewater-based epidemiology studies than the currently recommended pMMoV genetic marker.SARS-CoV-2 load per capita could be directly normalized using the regression functions derived from correlation between paraxanthine and population without flowrate and population data.Normalizing SARS-CoV-2 levels with the chemical marker PARA significantly improved the correlation between viral loads per capita and case numbers per capita.The chemical marker PARA demonstrated its excellent utility for real-time assessment of the population contributing to the wastewater.

Gut Virome: Role and Distribution in Health and Gastrointestinal Diseases

The study of the intestinal microbiome is an evolving field of research that includes comprehensive analysis of the vast array of microbes – bacterial, archaeal, fungal, and viral. Various gastrointestinal (GI) diseases, such as Crohn’s disease and ulcerative colitis, have been associated with instability of the gut microbiota. Many studies have focused on importance of bacterial communities with relation to health and disease in humans. The role of viruses, specifically bacteriophages, have recently begin to emerge and have profound impact on the host. Here, we comprehensively review the importance of viruses in GI diseases and summarize their influence in the complex intestinal environment, including their biochemical and genetic activities. We also discuss the distribution of the gut virome as it relates with treatment and immunological advantages. In conclusion, we suggest the need for further studies on this critical component of the intestinal microbiome to decipher the role of the gut virome in human health and disease.

The small intestine: barrier, permeability and microbiota

In recent years, there has been growing interest in the comprehension of the physiology of intestinal permeability and microbiota; and how these elements could influence the pathogenesis of diseases. The term intestinal permeability describes all the processes that allow the passage of molecules as water, electrolytes and nutrients through the intestinal barrier by the paracellular or the transcellular transport systems with several implications for self-tolerance and not-self immunity. An increased permeability might induce a more significant interaction of the immune system with unknown external antigens. This might favor the onset of several immune-related extra-intestinal diseases including coeliac disease, diabetes mellitus type 1, bronchial asthma and inflammatory bowel diseases. Furthermore, the intestinal permeability interacts every day with microbiota, the complex system of mutualistic inhabitants and commensal microorganisms living in the healthy gut. Microbiota is implicated in physiological functions by actively participating in digestion, absorption, synthesis of vitamins and protection from external aggressions. The critical site where these processes occur is the small intestine to which this updated review is dedicated. Understanding its anatomy, its barrier structure and permeability modulation and its microbiota composition is the essential skill to comprehend the complex pathogenesis of several - not only gastroenterological - diseases.

Quantification of human enteric viruses as alternative indicators of fecal pollution to evaluate wastewater treatment processes

We investigated the potential use and quantification of human enteric viruses in municipal wastewater samples of Winnipeg (Manitoba, Canada) as alternative indicators of contamination and evaluated the processing stages of the wastewater treatment plant. During the fall 2019 and winter 2020 seasons, samples of raw sewage, activated sludge, effluents, and biosolids (sludge cake) were collected from the North End Sewage Treatment Plant (NESTP), which is the largest wastewater treatment plant in the City of Winnipeg. DNA (Adenovirus and crAssphage) and RNA enteric viruses (Pepper mild mottle virus, Norovirus genogroups GI and GII, Rotavirus Astrovirus, and Sapovirus) as well as the uidA gene found in Escherichia coli were targeted in the samples collected from the NESTP. Total nucleic acids from each wastewater treatment sample were extracted using a commercial spin-column kit. Enteric viruses were quantified in the extracted samples via quantitative PCR using TaqMan assays. Overall, the average gene copies assessed in the raw sewage were not significantly different (p-values ranged between 0.1023 and 0.9921) than the average gene copies assessed in the effluents for DNA and RNA viruses and uidA in terms of both volume and biomass. A significant reduction (p-value ≤ 0.0438) of Adenovirus and Noroviruses genogroups GI and GII was observed in activated sludge samples compared with those for raw sewage per volume. Higher GCNs of enteric viruses were observed in dewatered sludge samples compared to liquid samples in terms of volume (g of sample) and biomass (ng of nucleic acids). Enteric viruses found in gene copy numbers were at least one order of magnitude higher than the E. coli marker uidA, indicating that enteric viruses may survive the wastewater treatment process and viral-like particles are being released into the aquatic environment. Viruses such as Noroviruses genogroups GI and GII, and Rotavirus were detected during colder months. Our results suggest that Adenovirus, crAssphage, and Pepper mild mottle virus can be used confidently as complementary viral indicators of human fecal pollution.

Comparison of five polyethylene glycol precipitation procedures for the RT-qPCR based recovery of murine hepatitis virus, bacteriophage phi6, and pepper mild mottle virus as a surrogate for SARS-CoV-2 from wastewater

Polyethylene glycol (PEG) precipitation is one of the conventional methods for virus concentration. This technique has been used to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater. The procedures and seeded surrogate viruses were different among implementers; thus, the reported whole process recovery efficiencies considerably varied among studies. The present study compared five PEG precipitation procedures, with different operational parameters, for the RT-qPCR-based whole process recovery efficiency of murine hepatitis virus (MHV), bacteriophage phi6, and pepper mild mottle virus (PMMoV), and molecular process recovery efficiency of murine norovirus using 34 raw wastewater samples collected in Japan. The five procedures yielded significantly different whole process recovery efficiency of MHV (0.070%-2.6%) and phi6 (0.071%-0.51%). The observed concentration of indigenous PMMoV ranged from 8.9 to 9.7 log (8.2 × 108 to 5.6 × 109) copies/L. Interestingly, PEG precipitation with 2-h incubation outperformed that with overnight incubation partially due to the difference in molecular process recovery efficiency. The recovery load of MHV exhibited a positive correlation (r = 0.70) with that of PMMoV, suggesting that PMMoV is the potential indicator of the recovery efficiency of SARS-CoV-2. In addition, we reviewed 13 published studies and found considerable variability between different studies in the whole process recovery efficiency of enveloped viruses by PEG precipitation. This was due to the differences in operational parameters and surrogate viruses as well as the differences in wastewater quality and bias in the measurement of the seeded load of surrogate viruses, resulting from the use of different analytes and RNA extraction methods. Overall, the operational parameters (e.g., incubation time and pretreatment) should be optimized for PEG precipitation. Co-quantification of PMMoV may allow for the normalization of SARS-CoV-2 RNA concentration by correcting for the differences in whole process recovery efficiency and fecal load among samples.

Surveillance of RNase P, PMMoV, and CrAssphage in wastewater as indicators of human fecal concentration across urban sewer neighborhoods, Kentucky

Wastewater surveillance has been widely used as a supplemental method to track the community infection levels of severe acute respiratory syndrome coronavirus 2. A gap exists in standardized reporting for fecal indicator concentrations, which can be used to calibrate the primary outcome concentrations from wastewater monitoring for use in epidemiological models. To address this, measurements of fecal indicator concentration among wastewater samples collected from sewers and treatment centers in four counties of Kentucky (N = 650) were examined. Results from the untransformed wastewater data over 4 months of sampling indicated that the fecal indicator concentration of human ribonuclease P (RNase P) ranged from 5.1 × 101 to 1.15 × 106 copies/ml, pepper mild mottle virus (PMMoV) ranged from 7.23 × 103 to 3.53 × 107 copies/ml, and cross-assembly phage (CrAssphage) ranged from 9.69 × 103 to 1.85 × 108 copies/ml. The results showed both regional and temporal variability. If fecal indicators are used as normalization factors, knowing the daily sewer system flow of the sample location may matter more than rainfall. RNase P, while it may be suitable as an internal amplification and sample adequacy control, has less utility than PMMoV and CrAssphage as a fecal indicator in wastewater samples when working at different sizes of catchment area. The choice of fecal indicator will impact the results of surveillance studies using this indicator to represent fecal load. Our results contribute broadly to an applicable standard normalization factor and assist in interpreting wastewater data in epidemiological modeling and monitoring.

SARS-CoV-2 RNA concentrations in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases

Current estimates of COVID-19 prevalence are largely based on symptomatic, clinically diagnosed cases. The existence of a large number of undiagnosed infections hampers population-wide investigation of viral circulation. Here, we quantify the SARS-CoV-2 concentration and track its dynamics in wastewater at a major urban wastewater treatment facility in Massachusetts, between early January and May 2020. SARS-CoV-2 was first detected in wastewater on March 3. SARS-CoV-2 RNA concentrations in wastewater correlated with clinically diagnosed new COVID-19 cases, with the trends appearing 4-10 days earlier in wastewater than in clinical data. We inferred viral shedding dynamics by modeling wastewater viral load as a convolution of back-dated new clinical cases with the average population-level viral shedding function. The inferred viral shedding function showed an early peak, likely before symptom onset and clinical diagnosis, consistent with emerging clinical and experimental evidence. This finding suggests that SARS-CoV-2 concentrations in wastewater may be primarily driven by viral shedding early in infection. This work shows that longitudinal wastewater analysis can be used to identify trends in disease transmission in advance of clinical case reporting, and infer early viral shedding dynamics for newly infected individuals, which are difficult to capture in clinical investigations.

Coprostanol as a Population Biomarker for SARS-CoV-2 Wastewater Surveillance Studies

Wastewater surveillance is a cost-effective tool for monitoring SARS-CoV-2 transmission in a community. However, challenges remain with regard to interpretating such studies, not least in how to compare SARS-CoV-2 levels between different-sized wastewater treatment plants. Viral faecal indicators, including crAssphage and pepper mild mottle virus, have been proposed as population biomarkers to normalise SARS-CoV-2 levels in wastewater. However, as these indicators exhibit variability between individuals and may not be excreted by everyone, their utility as population biomarkers may be limited. Coprostanol, meanwhile, is a bacterial metabolite of cholesterol which is excreted by all individuals. In this study, composite influent samples were collected from a large- and medium-sized wastewater treatment plant in Dublin, Ireland and SARS-CoV-2 N1, crAssphage, pepper mild mottle virus, HF183 and coprostanol levels were determined. SARS-CoV-2 N1 RNA was detected and quantified in all samples from both treatment plants. Regardless of treatment plant size, coprostanol levels exhibited the lowest variation in composite influent samples, while crAssphage exhibited the greatest variation. Moreover, the strongest correlations were observed between SARS-CoV-2 levels and national and Dublin COVID-19 cases when levels were normalised to coprostanol. This work demonstrates the usefulness of coprostanol as a population biomarker for wastewater surveillance studies.

Computational Prediction of Bacteriophage Host Ranges

Increased antibiotic resistance has prompted the development of bacteriophage agents for a multitude of applications in agriculture, biotechnology, and medicine. A key factor in the choice of agents for these applications is the host range of a bacteriophage, i.e., the bacterial genera, species, and strains a bacteriophage is able to infect. Although experimental explorations of host ranges remain the gold standard, such investigations are inherently limited to a small number of viruses and bacteria amendable to cultivation. Here, we review recently developed bioinformatic tools that offer a promising and high-throughput alternative by computationally predicting the putative host ranges of bacteriophages, including those challenging to grow in laboratory environments.

Phages in the Gut Ecosystem

Phages, short for bacteriophages, are viruses that specifically infect bacteria and are the most abundant biological entities on earth found in every explored environment, from the deep sea to the Sahara Desert. Phages are abundant within the human biome and are gaining increasing recognition as potential modulators of the gut ecosystem. For example, they have been connected to gastrointestinal diseases and the treatment efficacy of Fecal Microbiota Transplant. The ability of phages to modulate the human gut microbiome has been attributed to the predation of bacteria or the promotion of bacterial survival by the transfer of genes that enhance bacterial fitness upon infection. In addition, phages have been shown to interact with the human immune system with variable outcomes. Despite the increasing evidence supporting the importance of phages in the gut ecosystem, the extent of their influence on the shape of the gut ecosystem is yet to be fully understood. Here, we discuss evidence for phage modulation of the gut microbiome, postulating that phages are pivotal contributors to the gut ecosystem dynamics. We therefore propose novel research questions to further elucidate the role(s) that they have within the human ecosystem and its impact on our health and well-being.

Intestinal virome and therapeutic potential of bacteriophages in liver disease

Humans harbour a large quantity of microbes in the intestinal tract and have evolved symbiotic relationships with many of them. However, several specific bacterial pathobionts are associated with liver disease pathogenesis. Although bacteriophages (phages) and eukaryotic viruses (collectively known as "the virome") outnumber bacteria and fungi in the intestine, little is known about the intestinal virome in patients with liver disease. As natural predators of bacteria, phages can precisely edit the bacterial microbiota. Hence, there is interest in using them to target bacterial pathobionts in several diseases, including those of the liver. Herein, we will summarise changes in the faecal virome associated with fatty liver diseases and cirrhosis, and describe the therapeutic potential of phages and potential challenges to their clinical application.

Composition of Eukaryotic Viruses and Bacteriophages in Individuals with Acute Gastroenteritis

Metagenomics based on the next-generation sequencing (NGS) technique is a target-independent assay that enables the simultaneous detection and genomic characterization of all viruses present in a sample. There is a limited amount of data about the virome of individuals with gastroenteritis (GI). In this study, the enteric virome of 250 individuals (92% were children under 5 years old) with GI living in the northeastern and northern regions of Brazil was characterized. Fecal samples were subjected to NGS, and the metagenomic analysis of virus-like particles (VLPs) identified 11 viral DNA families and 12 viral RNA families. As expected, the highest percentage of viral sequences detected were those commonly associated with GI, including rotavirus, adenovirus, norovirus (94.8%, 82% and 71.2%, respectively). The most common co-occurrences, in a single individual, were the combinations of rotavirus-adenovirus, rotavirus-norovirus, and norovirus-adenovirus (78%, 69%, and 62%, respectively). In the same way, common fecal-emerging human viruses were also detected, such as parechovirus, bocaporvirus, cosavirus, picobirnavirus, cardiovirus, salivirus, and Aichivirus. In addition, viruses that infect plants, nematodes, fungi, protists, animals, and arthropods could be identified. A large number of unclassified viral contigs were also identified. We show that the metagenomics approach is a powerful and promising tool for the detection and characterization of different viruses in clinical GI samples.

Monitoring SARS-CoV-2 variants alterations in Nice neighborhoods by wastewater nanopore sequencing

BACKGROUND

Wastewater surveillance was proposed as an epidemiological tool to define the prevalence and evolution of the SARS-CoV-2 epidemics. However, most implemented SARS-CoV-2 wastewater surveillance projects were based on qPCR measurement of virus titers and did not address the mutational spectrum of SARS-CoV-2 circulating in the population.

METHODS

We have implemented a nanopore RNA sequencing monitoring system in the city of Nice (France, 550,000 inhabitants). Between October 2020 and March 2021, we monthly analyzed the SARS-CoV-2 variants in 113 wastewater samples collected in the main wastewater treatment plant and 20 neighborhoods.

FINDINGS

We initially detected the lineages predominant in Europe at the end of 2020 (B.1.160, B.1.177, B.1.367, B.1.474, and B.1.221). In January, a localized emergence of a variant (Spike:A522S) of the B.1.1.7 lineage occurred in one neighborhood. It rapidly spread and became dominant all over the city. Other variants of concern (B.1.351, P.1) were also detected in some neighborhoods, but at low frequency. Comparison with individual clinical samples collected during the same week showed that wastewater sequencing correctly identified the same lineages as those found in COVID-19 patients.

INTERPRETATION

Wastewater sequencing allowed to document the diversity of SARS-CoV-2 sequences within the different neighborhoods of the city of Nice. Our results illustrate how sequencing of sewage samples can be used to track pathogen sequence diversity in the current pandemics and in future infectious disease outbreaks.

TRANSLATION

For the French translation of the abstract see Supplementary Materials section.

Leviviricetes: expanding and restructuring the taxonomy of bacteria-infecting single-stranded RNA viruses

The vast majority of described prokaryotic viruses have double-stranded or single-stranded DNA or double-stranded RNA genomes. Until 2020, a mere four prokaryotic single-stranded, positive-sense RNA viruses have been classified in two genera (Riboviria; Lenarviricota; Allassoviricetes; Leviviridae). Several recent metagenomic and metatranscriptomic studies revealed a vastly greater diversity of these viruses in prokaryotic soil communities than ever anticipated. Phylogenetic analysis of these newly discovered viruses prompted the reorganization of class Allassoviricetes, now renamed Leviviricetes, to include two orders, Norzivirales and Timlovirales, and a total of six families, 428 genera and 882 species. Here we outline the new taxonomy of Leviviricetes, approved and ratified in 2021 by the International Committee on Taxonomy of Viruses, and describe open-access hidden Markov models to accommodate the anticipated identification and future classification of hundreds, if not thousands, of additional class members into this new taxonomic framework.

Technical framework for wastewater-based epidemiology of SARS-CoV-2

Wastewater-based epidemiology (WBE) is expected to become a powerful tool to monitor the dissemination of SARS-CoV-2 at the community level, which has attracted the attention of scholars all over the world. However, there is not yet a standard protocol to guide its implementation. In this paper, we proposed a comprehensive technical and theoretical framework of relative quantification via qPCR for determining the virus abundance in wastewater and estimating the infection ratio in corresponding communities, which is expected to achieve horizontal and vertical comparability of the data using a human-specific biomarker as the internal reference. Critical factors affecting the virus detectability and the estimation of infection ratio include virus concentration methods, lag-period, per capita virus shedding amount, sewage generation rate, temperature-related decay kinetics of virus/biomarker in wastewater, and hydraulic retention time (HRT), etc. Theoretical simulation shows that the main factors affecting the detectability of virus in sewage are per capita virus shedding amount and sewage generation rate. While the decay of SARS-CoV-2 RNA in sewage is a relatively slow process, which may have limited impact on its detection. Under the ideal condition of high per capita virus shedding amount and low sewage generation rate, it is expected to detect a single infected person within 400,000 people.

Zero-Valent Iron Filtration Reduces Microbial Contaminants in Irrigation Water and Transfer to Raw Agricultural Commodities

Groundwater depletion is a critical agricultural irrigation issue, which can be mitigated by supplementation with water of higher microbiological risk, including surface and reclaimed waters, to support irrigation needs in the United States. Zero-valent iron (ZVI) filtration may be an affordable and effective treatment for reducing pathogen contamination during crop irrigation. This study was performed to determine the effects of ZVI filtration on the removal and persistence of Escherichia coli, and pepper mild mottle virus (PMMoV) in irrigation water. Water was inoculated with E. coli TVS 353, filtered through a ZVI filtration unit, and used to irrigate cucurbit and cruciferous crops. Water (n = 168), leaf (n = 40), and soil (n = 24) samples were collected, the E. coli were enumerated, and die-off intervals were calculated for bacteria in irrigation water. Variable reduction of PMMoV was observed, however E. coli levels were consistently and significantly (p < 0.05) reduced in the filtered (9.59 lnMPN/mL), compared to unfiltered (13.13 lnMPN/mL) water. The die-off intervals of the remaining bacteria were significantly shorter in the filtered (−1.50 lnMPN/day), as compared to the unfiltered (−0.48 lnMPN/day) water. E. coli transfer to crop leaves and soils was significantly reduced (p < 0.05), as expected. The reduction of E. coli in irrigation water and its transfer to crops, by ZVI filtration is indicative of its potential to reduce pathogens in produce pre-harvest environments.

Wastewater Surveillance during Mass COVID-19 Vaccination on a College Campus

The suitability of wastewater monitoring following widespread vaccination against COVID-19 remains uncertain. SARS-CoV-2 RNA levels were monitored in wastewater solids during a university mass vaccination campaign in which >90% of the 12280 students were fully vaccinated (Pfizer-BioNTech, BNT162b2). SARS-CoV-2 RNA levels in wastewater solids correlated with the 7-day average of COVID-19 cases when lagged by 1-3 days (ρ = 0.51-0.55; p = 0.023-0.039). During and after the second vaccine dose, SARS-CoV-2 RNA was not detected in wastewater solids on 19 of 21 days (12 consecutive days of nondetection at the end of the semester), a significant decrease (p = 0.027) in positivity rate. A large influx of outside visitors (move out and commencement) led to an immediate increase in wastewater SARS-CoV-2 RNA positivity (seven detections over seven days). Wastewater solids offer a sensitive matrix for environmental surveillance of COVID-19 at the subsewershed level (50% probability of RNA detection with two cases) both during and after mass vaccination. Mass vaccination was coincident with decreased shedding of SARS-CoV-2 RNA into wastewater. This suggests the absence of a large population of shedding infections, symptomatic or not, following mass vaccination among a university campus population.

Non-intrusive wastewater surveillance for monitoring of a residential building for COVID-19 cases

Wastewater-based surveillance for SARS-CoV-2 has been used for the early warning of transmission or objective trending of the population-level disease prevalence. Here, we describe a new use-case of conducting targeted wastewater surveillance to complement clinical testing for case identification in a small community at risk of COVID-19 transmission. On 2 July 2020, a cluster of COVID-19 cases in two unrelated households residing on different floors in the same stack of an apartment building was reported in Singapore. After cases were conveyed to healthcare facilities and six healthy household contacts were quarantined in their respective apartments, wastewater surveillance was implemented for the entire residential block. SARS-CoV-2 was subsequently detected in wastewaters in an increasing frequency and concentration, despite the absence of confirmed COVID-19 cases, suggesting the presence of fresh case/s in the building. Phone interviews of six residents in quarantine revealed that no one was symptomatic (fever/respiratory illness). However, when nasopharyngeal swabs from six quarantined residents were tested by PCR tests, one was positive for SARS-CoV-2. The positive case reported episodes of diarrhea and the case's stool sample was also positive for SARS-CoV-2, explaining the SARS-CoV-2 spikes observed in wastewaters. After the case was conveyed to a healthcare facility, wastewaters continued to yield positive signals for five days, though with a decreasing intensity. This was attributed to the return of recovered cases, who had continued to shed the virus. Our findings demonstrate the utility of wastewater surveillance as a non-intrusive tool to monitor high-risk COVID-19 premises, which is able to trigger individual tests for case detection, highlighting a new use-case for wastewater testing.

Integrative Survey of 68 Non-overlapping Upstate New York Watersheds Reveals Stream Features Associated With Aquatic Fecal Contamination

Aquatic fecal contamination poses human health risks by introducing pathogens in water that may be used for recreation, consumption, or agriculture. Identifying fecal contaminant sources, as well as the factors that affect their transport, storage, and decay, is essential for protecting human health. However, identifying these factors is often difficult when using fecal indicator bacteria (FIB) because FIB levels in surface water are often the product of multiple contaminant sources. In contrast, microbial source-tracking (MST) techniques allow not only the identification of predominant contaminant sources but also the quantification of factors affecting the transport, storage, and decay of fecal contaminants from specific hosts. We visited 68 streams in the Finger Lakes region of Upstate New York, United States, between April and October 2018 and collected water quality data (i.e., Escherichia coli, MST markers, and physical–chemical parameters) and weather and land-use data, as well as data on other stream features (e.g., stream bed composition), to identify factors that were associated with fecal contamination at a regional scale. We then applied both generalized linear mixed models and conditional inference trees to identify factors and combinations of factors that were significantly associated with human and ruminant fecal contamination. We found that human contaminants were more likely to be identified when the developed area within the 60 m stream buffer exceeded 3.4%, the total developed area in the watershed exceeded 41%, or if stormwater outfalls were present immediately upstream of the sampling site. When these features were not present, human MST markers were more likely to be found when rainfall during the preceding day exceeded 1.5 cm. The presence of upstream campgrounds was also significantly associated with human MST marker detection. In addition to rainfall and water quality parameters associated with rainfall (e.g., turbidity), the minimum distance to upstream cattle operations, the proportion of the 60 m buffer used for cropland, and the presence of submerged aquatic vegetation at the sampling site were all associated based on univariable regression with elevated levels of ruminant markers. The identification of specific features associated with host-specific fecal contaminants may support the development of broader recommendations or policies aimed at reducing levels of aquatic fecal contamination.

Targeted wastewater surveillance of SARS-CoV-2 on a university campus for COVID-19 outbreak detection and mitigation

Targeted wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been proposed by the United States Centers for Disease Control and Prevention's National Wastewater Surveillance System as a complementary approach to clinical surveillance to detect the presence of Coronavirus Disease 2019 (COVID-19) at high-density facilities and institutions such as university campuses, nursing homes, and correctional facilities. In this study we evaluated the efficacy of targeted wastewater surveillance of SARS-CoV-2 RNA together with individual-level testing for outbreak mitigation on a university campus during Fall 2020 semester. Wastewater samples (n = 117) were collected weekly from manholes or sewer cleanouts that receive wastewater inputs from dormitories, community-use buildings, and a COVID-19 isolation dormitory. Quantitative RT-PCR N1 and N2 assays were used to measure SARS-CoV-2 nucleocapsid genes in wastewater. Due to varying human waste input in different buildings, pepper mild mottle virus (PMMV) RNA was also measured in all samples and used to normalize SARS-CoV-2 N1 and N2 RNA wastewater concentrations. In this study, temporal trends of SARS-CoV-2 in wastewater samples mirrored trends in COVID-19 cases detected on campus. Normalizing SARS-CoV-2 RNA concentrations using human fecal indicator, PMMV enhanced the correlation between N1 and N2 gene abundances in wastewater with COVID-19 cases. N1 and N2 genes were significant predictors of COVID-19 cases in dormitories, and the N2 gene was significantly correlated with the number of detected COVID-19 cases in dormitories. By implementing several public health surveillance programs include targeted wastewater surveillance, individual-level testing, contact tracing, and quarantine/isolation facilities, university health administrators could act decisively during an outbreak on campus, resulting in rapid decline of newly detected COVID-19 cases. Wastewater surveillance of SARS-CoV-2 is a proactive outbreak monitoring tool for university campuses seeking to continue higher education practices in person during the COVID-19 pandemic.

The virome in early life and childhood and development of islet autoimmunity and type 1 diabetes: A systematic review and meta-analysis of observational studies

Viruses are postulated as primary candidate triggers of islet autoimmunity (IA) and type 1 diabetes (T1D), based on considerable epidemiological and experimental evidence. Recent studies have investigated the association between all viruses (the 'virome') and IA/T1D using metagenomic next-generation sequencing (mNGS). Current associations between the early life virome and the development of IA/T1D were analysed in a systematic review and meta-analysis of human observational studies from Medline and EMBASE (published 2000-June 2020), without language restriction. Inclusion criteria were as follows: cohort and case-control studies examining the virome using mNGS in clinical specimens of children ≤18 years who developed IA/T1D. The National Health and Medical Research Council level of evidence scale and Newcastle-Ottawa scale were used for study appraisal. Meta-analysis for exposure to specific viruses was performed using random-effects models, and the strength of association was measured using odds ratios (ORs) and 95% confidence intervals (CIs). Eligible studies (one case-control, nine nested case-control) included 1,425 participants (695 cases, 730 controls) and examined IA (n = 1,023) or T1D (n = 402). Meta-analysis identified small but significant associations between IA and number of stool samples positive for all enteroviruses (OR 1.14, 95% CI 1.00-1.29, p = 0.05; heterogeneity χ2  = 1.51, p = 0.68, I2  = 0%), consecutive positivity for enteroviruses (1.55, 1.09-2.20, p = 0.01; χ2  = 0.19, p = 0.91, I2  = 0%) and number of stool samples positive specifically for enterovirus B (1.20, 1.01-1.42, p = 0.04; χ2  = 0.03, p = 0.86, I2  = 0%). Virome analyses to date have demonstrated associations between enteroviruses and IA that may be clinically significant. However, larger prospective mNGS studies with more frequent sampling and follow-up from pregnancy are required to further elucidate associations between early virus exposure and IA/T1D.

Recovery of Nucleic Acids of Enteric Viruses and Host-Specific Bacteroidales from Groundwater by Using an Adsorption-Direct Extraction Method

In this study, the adsorption-elution method was modified to concentrate viral particles in water samples and investigate the contamination of groundwater with norovirus genogroup II (NoV GII), rotavirus A (RVA), and Pepper mild mottle virus (PMMoV). The mean recovery rate of a murine norovirus strain, which was inoculated into groundwater samples collected from a deep well, was the highest (39%) when the viral RNA was directly extracted from the membrane instead of eluting the adsorbed viral particles. This adsorption-direct extraction method was applied to groundwater samples (20 liters) collected from deep wells used for the public drinking water supply (n = 22) and private wells (n = 9). RVA (85 copies/liter) and NoV GII (35 copies/liter) were detected in water samples from a deep well and a private well, respectively. PMMoV was detected in 95% and 89% of water samples from deep wells and private wells, respectively, at concentrations of up to 990 copies/liter. The modified method was also used to extract bacterial DNA from the membrane (recovery rate of inoculated Escherichia coli K-12 was 22%). The Bacteroidales genetic markers specific to ruminants (BacR) and pigs (Pig2Bac) were detected in samples from a deep well and a private well, respectively. The modified virus concentration method has important implications for the management of microbiological safety in the groundwater supply. IMPORTANCE We investigated the presence of enteric viruses and bacterial genetic markers to determine fecal contamination in groundwater samples from deep wells used for the public drinking water supply and private wells in Japan. Groundwater is often subjected to chlorination; malfunctions in chlorine treatment result in waterborne disease outbreaks. The modified method successfully concentrated both viruses and bacteria in 20-liter groundwater samples. Norovirus genogroup II (GII), rotavirus A, Pepper mild mottle virus, and Bacteroidales genetic markers specific to ruminants and pigs were detected. Frequent flooding caused by increased incidences of extreme rainfall events promotes the infiltration of surface runoff containing livestock wastes and untreated wastewater into wells, possibly increasing groundwater contamination risk. The practical and efficient method developed in this study will enable waterworks and the environmental health departments of municipal/prefectural governments to monitor water quality. Additionally, the modified method will contribute to improving the microbiological safety of groundwater.

Monitoring SARS-CoV-2 variants alterations in Nice neighborhoods by wastewater nanopore sequencing

Background

Wastewater surveillance was proposed as an epidemiological tool to define the prevalence and evolution of the SARS-CoV-2 epidemics. However, most implemented SARS-CoV-2 wastewater surveillance projects were based on qPCR measurement of virus titers and did not address the mutational spectrum of SARS-CoV-2 circulating in the population.

Methods

We have implemented a nanopore RNA sequencing monitoring system in the city of Nice (France, 550,000 inhabitants). Between October 2020 and March 2021, we monthly analyzed the SARS-CoV-2 variants in 113 wastewater samples collected in the main wastewater treatment plant and 20 neighborhoods.

Findings

We initially detected the lineages predominant in Europe at the end of 2020 (B.1.160, B.1.177, B.1.367, B.1.474, and B.1.221). In January, a localized emergence of a variant (Spike:A522S) of the B.1.1.7 lineage occurred in one neighborhood. It rapidly spread and became dominant all over the city. Other variants of concern (B.1.351, P.1) were also detected in some neighborhoods, but at low frequency. Comparison with individual clinical samples collected during the same week showed that wastewater sequencing correctly identified the same lineages as those found in COVID-19 patients.

Interpretation

Wastewater sequencing allowed to document the diversity of SARS-CoV-2 sequences within the different neighborhoods of the city of Nice. Our results illustrate how sequencing of sewage samples can be used to track pathogen sequence diversity in the current pandemics and in future infectious disease outbreaks.

Translation

For the French translation of the abstract see Supplementary Materials section.

Comparison of Detecting and Quantitating SARS-CoV-2 in Wastewater Using Moderate-Speed Centrifuged Solids versus an Ultrafiltration Method

Mounting evidence suggests that solids are a reliable matrix for SARS-CoV-2 detection in wastewater, yet studies comparing solids-based methods and common concentration methods using the liquid fraction remain limited. In this study, we developed and optimized a method for SARS-CoV-2 detection in wastewater using moderate-speed centrifuged solids and evaluated it against an ultrafiltration reference method. SARS-CoV-2 was quantified in samples from 12 wastewater treatment plants from Alberta, Canada, using RT-qPCR targeting the N2 and E genes. PCR inhibition was examined by spiking salmon DNA. The effects of using different amounts of solids, adjusting the sample pH to 9.6–10, and modifying the elution volume at the final step of RNA extraction were evaluated. SARS-CoV-2 detection rate in solids from 20 mL of wastewater showed no statistically significant difference compared to the ultrafiltration method (97/139 versus 90/139, p = 0.26, McNemar’s mid-p test). The optimized wastewater solids-based method had a significantly lower rate of samples with PCR inhibition versus ultrafiltration (3% versus 9.5%, p = 0.014, Chi-square test). Our optimized moderate-speed centrifuged solids-based method had similar sensitivity when compared to the ultrafiltration reference method but had the added advantages of lower costs, fewer processing steps, and a shorter turnaround time.

Decay of infectious SARS-CoV-2 and surrogates in aquatic environments

The introduction of SARS-CoV-2 containing human stool and sewage into water bodies may raise public health concerns. However, assessment of public health risks by faecally contaminated water is limited by a lack of knowledge regarding the persistence of infectious SARS-CoV-2 in water. In the present study the decay rates of viable infectious SARS-CoV-2 and SARS-CoV-2 RNA were determined in river and seawater at 4 and 20°C. These decay rates were compared to S. typhimurium bacteriophage MS2 and pepper mild mottle virus (PMMoV). Persistence of viable SARS-CoV-2 was temperature dependent, remaining infectious for significantly longer periods of time in both freshwater and seawater at 4°C than at 20°C. T90 for infectious SARS-CoV-2 in river water was 2.3 days and 3.8 days at 20°C and 4°C, respectively. The T90 values were 1.1 days and 2.2 days in seawater at 20°C and 4°C, respectively. In contrast to the rapid inactivation of infectious SARS-CoV-2 in river and sea water, viral RNA was relatively stable. The RNA decay rates were increased in non-sterilised river and seawater, presumably due to the presence of microbiota. The decay rates of infectious MS2, MS2 RNA and PMMoV RNA differed significantly from the decay rate of SARS-CoV-2 RNA, suggesting that their use as surrogate markers for the persistence of SARS-CoV-2 in the environment is limited.

Metatranscriptomics for the Human Microbiome and Microbial Community Functional Profiling

Shotgun metatranscriptomics (MTX) is an increasingly practical way to survey microbial community gene function and regulation at scale. This review begins by summarizing the motivations for community transcriptomics and the history of the field. We then explore the principles, best practices, and challenges of contemporary MTX workflows: beginning with laboratory methods for isolation and sequencing of community RNA, followed by informatics methods for quantifying RNA features, and finally statistical methods for detecting differential expression in a community context. In thesecond half of the review, we survey important biological findings from the MTX literature, drawing examples from the human microbiome, other (nonhuman) host-associated microbiomes, and the environment. Across these examples, MTX methods prove invaluable for probing microbe-microbe and host-microbe interactions, the dynamics of energy harvest and chemical cycling, and responses to environmental stresses. We conclude with a review of open challenges in the MTX field, including making assays and analyses more robust, accessible, and adaptable to new technologies; deciphering roles for millions of uncharacterized microbial transcripts; and solving applied problems such as biomarker discovery and development of microbial therapeutics.

Wastewater monitoring outperforms case numbers as a tool to track COVID-19 incidence dynamics when test positivity rates are high

Wastewater-based epidemiology (WBE) has been shown to coincide with, or anticipate, confirmed COVID-19 case numbers. During periods with high test positivity rates, however, case numbers may be underreported, whereas wastewater does not suffer from this limitation. Here we investigated how the dynamics of new COVID-19 infections estimated based on wastewater monitoring or confirmed cases compare to true COVID-19 incidence dynamics. We focused on the first pandemic wave in Switzerland (February to April, 2020), when test positivity ranged up to 26%. SARS-CoV-2 RNA loads were determined 2-4 times per week in three Swiss wastewater treatment plants (Lugano, Lausanne and Zurich). Wastewater and case data were combined with a shedding load distribution and an infection-to-case confirmation delay distribution, respectively, to estimate infection incidence dynamics. Finally, the estimates were compared to reference incidence dynamics determined by a validated compartmental model. Incidence dynamics estimated based on wastewater data were found to better track the timing and shape of the reference infection peak compared to estimates based on confirmed cases. In contrast, case confirmations provided a better estimate of the subsequent decline in infections. Under a regime of high-test positivity rates, WBE thus provides critical information that is complementary to clinical data to monitor the pandemic trajectory.

Wastewater monitoring outperforms case numbers as a tool to track COVID-19 incidence dynamics when test positivity rates are high

Wastewater-based epidemiology (WBE) has been shown to coincide with, or anticipate, confirmed COVID-19 case numbers. During periods with high test positivity rates, however, case numbers may be underreported, whereas wastewater does not suffer from this limitation. Here we investigated how the dynamics of new COVID-19 infections estimated based on wastewater monitoring or confirmed cases compare to true COVID-19 incidence dynamics. We focused on the first pandemic wave in Switzerland (February to April, 2020), when test positivity ranged up to 26%. SARS-CoV-2 RNA loads were determined 2-4 times per week in three Swiss wastewater treatment plants (Lugano, Lausanne and Zurich). Wastewater and case data were combined with a shedding load distribution and an infection-to-case confirmation delay distribution, respectively, to estimate infection incidence dynamics. Finally, the estimates were compared to reference incidence dynamics determined by a validated compartmental model. Incidence dynamics estimated based on wastewater data were found to better track the timing and shape of the reference infection peak compared to estimates based on confirmed cases. In contrast, case confirmations provided a better estimate of the subsequent decline in infections. Under a regime of high-test positivity rates, WBE thus provides critical information that is complementary to clinical data to monitor the pandemic trajectory.

The Gombe Ecosystem Health Project: 16 years of program evolution and lessons learned

Infectious disease outbreaks pose a significant threat to the conservation of chimpanzees (Pan troglodytes) and all threatened nonhuman primates. Characterizing and mitigating these threats to support the sustainability and welfare of wild populations is of the highest priority. In an attempt to understand and mitigate the risk of disease for the chimpanzees of Gombe National Park, Tanzania, we initiated a long-term health-monitoring program in 2004. While the initial focus was to expand the ongoing behavioral research on chimpanzees to include standardized data on clinical signs of health, it soon became evident that the scope of the project would ideally include diagnostic surveillance of pathogens for all primates (including people) and domestic animals, both within and surrounding the National Park. Integration of these data, along with in-depth post-mortem examinations, have allowed us to establish baseline health indicators to inform outbreak response. Here, we describe the development and expansion of the Gombe Ecosystem Health project, review major findings from the research and summarize the challenges and lessons learned over the past 16 years. We also highlight future directions and present the opportunities and challenges that remain when implementing studies of ecosystem health in a complex, multispecies environment.

Enteric Viruses and Pepper Mild Mottle Virus Show Significant Correlation in Select Mid-Atlantic Agricultural Waters

Enteric viruses (EVs) are the largest contributors to foodborne illnesses and outbreaks globally. Their ability to persist in the environment, coupled with the challenges experienced in environmental monitoring, creates a critical aperture through which agricultural crops may become contaminated. This study involved a 17-month investigation of select human EVs and viral indicators in nontraditional irrigation water sources (surface and reclaimed waters) in the Mid-Atlantic region of the United States. Real-time quantitative PCR was used for detection of Aichi virus, hepatitis A virus, and norovirus genotypes I and II (GI and GII, respectively). Pepper mild mottle virus (PMMoV), a common viral indicator of human fecal contamination, was also evaluated, along with atmospheric (air and water temperature, cloud cover, and precipitation 24 h, 7 days, and 14 days prior to sample collection) and physicochemical (dissolved oxygen, pH, salinity, and turbidity) data, to determine whether there were any associations between EVs and measured parameters. EVs were detected more frequently in reclaimed waters (32% [n = 22]) than in surface waters (4% [n = 49]), similar to PMMoV detection frequency in surface (33% [n = 42]) and reclaimed (67% [n = 21]) waters. Our data show a significant correlation between EV and PMMoV (R² = 0.628, P < 0.05) detection levels in reclaimed water samples but not in surface water samples (R² = 0.476, P = 0.78). Water salinity significantly affected the detection of both EVs and PMMoV (P < 0.05), as demonstrated by logistic regression analyses. These results provide relevant insights into the extent and degree of association between human (pathogenic) EVs and water quality data in Mid-Atlantic surface and reclaimed waters, as potential sources for agricultural irrigation. IMPORTANCE Microbiological analysis of agricultural waters is fundamental to ensure microbial food safety. The highly variable nature of nontraditional sources of irrigation water makes them particularly difficult to test for the presence of viruses. Multiple characteristics influence viral persistence in a water source, as well as affecting the recovery and detection methods that are employed. Testing for a suite of viruses in water samples is often too costly and labor-intensive, making identification of suitable indicators for viral pathogen contamination necessary. The results from this study address two critical data gaps, namely, EV prevalence in surface and reclaimed waters of the Mid-Atlantic region of the United States and subsequent evaluation of physicochemical and atmospheric parameters used to inform the potential for the use of indicators of viral contamination.

The Human Gut Phageome: Origins and Roles in the Human Gut Microbiome

The investigation of the microbial populations of the human body, known as the microbiome, has led to a revolutionary field of science, and understanding of its impacts on human development and health. The majority of microbiome research to date has focussed on bacteria and other kingdoms of life, such as fungi. Trailing behind these is the interrogation of the gut viruses, specifically the phageome. Bacteriophages, viruses that infect bacterial hosts, are known to dictate the dynamics and diversity of bacterial populations in a number of ecosystems. However, the phageome of the human gut, while of apparent importance, remains an area of many unknowns. In this paper we discuss the role of bacteriophages within the human gut microbiome. We examine the methods used to study bacteriophage populations, how this evolved over time and what we now understand about the phageome. We review the phageome development in infancy, and factors that may influence phage populations in adult life. The role and action of the phageome is then discussed at both a biological-level, and in the broader context of human health and disease.

Detection of Human Sapoviruses in Sewage in China by Next Generation Sequencing

Human sapovirus (SaV) is an important causative agent of nonbacterial gastroenteritis in humans. However, little is known about its circulation in China. To study the prevalence and diversity of human SaV genotypes circulating in eastern China, a 3-year environmental surveillance combined with next generation sequencing (NGS) technology was conducted. A total of 36 raw sewage samples were collected from January 2017 to December 2019 in Jinan and processed. Thirty-five (97.22%) samples were positive for human SaV genome in quantitative RT-PCR assay; 33 (91.67%) samples were positive in nested RT-PCR assay on partial capsid VP1 sequence and all amplicons were further analyzed separately by NGS. Among those, ten genotypes belonging to the genogroups of GI, GII, GIV, and GV were identified by NGS, including 4 major genotypes (GI.2, GI.1, GV.1 and GI.3) and 6 uncommon genotypes (GII.5, GII.1, GII.NA1, GII.3, GI.6 and GIV.1). A temporal switch of predominant genotype was observed from GI.2 to GI.1 around June 2019. Local and foreign sequences clustered together in some branches according to phylogenetic analysis, indicating frequent transmission of various lineages in different regions of the world. Environmental surveillance provides a comprehensive picture of human SaV in China. NGS-based environmental surveillance improves our knowledge on human SaV circulating in communities greatly and should be encouraged as a sensitive surveillance tool.

Assembly of the virome in newborn human infants

Healthy human infants are typically born without high concentrations of viral particles in their intestines, but after a few weeks of life particle counts typically reach a billion per gram of stool. Where do these vast populations come from? Recent studies support the idea that colonization is stepwise. First pioneer bacteria seed the infant gut. Bacteria commonly harbor prophage sequences integrated in their genomes, which periodically induce to make particles, providing a first wave of viral particles. Later more viruses infecting human cells are detected. Analysis showed that lower accumulation of viruses that grow in human cells is associated with breastfeeding. Thus these studies emphasize the environmental influences on formation of the early life virome, and begin to point the way toward modulating viral colonization to optimize health.

Bacteriophages and the Immune System

Bacteriophages-viruses that infect bacteria-are abundant within our bodies, but their significance to human health is only beginning to be explored. Here, we synthesize what is currently known about our phageome and its interactions with the immune system. We first review how phages indirectly affect immunity via bacterial expression of phage-encoded proteins. We next review how phages directly influence innate immunity and bacterial clearance. Finally, we discuss adaptive immunity against phages and its implications for phage/bacterial interactions. In light of these data, we propose that our microbiome can be understood as an interconnected network of bacteria, bacteriophages, and human cells and that the stability of these tri-kingdom interactions may be important for maintaining our immunologic and metabolic health. Conversely, the disruption of this balance, through exposure to exogenous phages, microbial dysbiosis, or immune dysregulation, may contribute to disease. Expected final online publication date for the Annual Review of Virology, Volume 8 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Scaling of SARS-CoV-2 RNA in Settled Solids from Multiple Wastewater Treatment Plants to Compare Incidence Rates of Laboratory-Confirmed COVID-19 in Their Sewersheds

Published and unpublished reports show that SARS-CoV-2 RNA in publicly owned treatment work (POTW) wastewater influent and solids is associated with new COVID-19 cases or incidence in associated sewersheds, but methods for comparing data collected from diverse POTWs to infer information about the relative incidence of laboratory-confirmed COVID-19 cases, and scaling to allow such comparisons, have not been previously established. Here, we show that SARS-CoV-2 N1 and N2 concentrations in solids normalized by concentrations of PMMoV RNA in solids can be used to compare incidence of laboratory confirmed new COVID-19 cases across POTWs. Using data collected at seven POTWs along the United States West Coast, Midwest, and East Coast serving ∼3% of the U.S. population (9 million people), we show that a 1 log change in N gene/PMMoV is associated with a 0.24 (range 0.19 to 0.29) log10 change in incidence of laboratory confirmed COVID-19. Scaling of N1 and N2 by PMMoV is consistent, conceptually, with a mass balance model relating SARS-CoV-2 RNA to the number of infected individuals shedding virus in their stool. This information should support the application of wastewater-based epidemiology to inform the response to the COVID-19 pandemic and potentially future viral pandemics.

The dark side of the gut: Virome-host interactions in intestinal homeostasis and disease

The diverse enteric viral communities that infect microbes and the animal host collectively constitute the gut virome. Although recent advances in sequencing and analysis of metaviromes have revealed the complexity of the virome and facilitated discovery of new viruses, our understanding of the enteric virome is still incomplete. Recent studies have uncovered how virome-host interactions can contribute to beneficial or detrimental outcomes for the host. Understanding the complex interactions between enteric viruses and the intestinal immune system is a prerequisite for elucidating their role in intestinal diseases. In this review, we provide an overview of the enteric virome composition and summarize recent findings about how enteric viruses are sensed by and, in turn, modulate host immune responses during homeostasis and disease.

Stability of the human gut virome and effect of gluten-free diet

The human gut microbiome consists of bacteria, archaea, eukaryotes, and viruses. The gut viruses are relatively underexplored. Here, we longitudinally analyzed the gut virome composition in 11 healthy adults: its stability, variation, and the effect of a gluten-free diet. Using viral enrichment and a de novo assembly-based approach, we demonstrate the quantitative dynamics of the gut virome, including dsDNA, ssDNA, dsRNA, and ssRNA viruses. We observe highly divergent individual viral communities, carrying on an average 2,143 viral genomes, 13.1% of which were present at all 3 time points. In contrast to previous reports, the Siphoviridae family dominates over Microviridae in studied individual viromes. We also show individual viromes to be stable at the family level but to vary substantially at the genera and species levels. Finally, we demonstrate that lower initial diversity of the human gut virome leads to a more pronounced effect of the dietary intervention on its composition.

Emerging Roles of Gut Virome in Pediatric Diseases

In the last decade, the widespread application of shotgun metagenomics provided extensive characterization of the bacterial "dark matter" of the gut microbiome, propelling the development of dedicated, standardized bioinformatic pipelines and the systematic collection of metagenomic data into comprehensive databases. The advent of next-generation sequencing also unravels a previously underestimated viral population (virome) present in the human gut. Despite extensive efforts to characterize the human gut virome, to date, little is known about the childhood gut virome. However, alterations of the gut virome in children have been linked to pathological conditions such as inflammatory bowel disease, type 1 diabetes, malnutrition, diarrhea and celiac disease.