Clades of huge phages from across Earth's ecosystems.

Bacteriophages typically have small genomes1 and depend on their bacterial hosts for replication2. Here we sequenced DNA from diverse ecosystems and found hundreds of phage genomes with lengths of more than 200 kilobases (kb), including a genome of 735 kb, which is-to our knowledge-the largest phage genome to be described to date. Thirty-five genomes were manually curated to completion (circular and no gaps). Expanded genetic repertoires include diverse and previously undescribed CRISPR-Cas systems, transfer RNAs (tRNAs), tRNA synthetases, tRNA-modification enzymes, translation-initiation and elongation factors, and ribosomal proteins. The CRISPR-Cas systems of phages have the capacity to silence host transcription factors and translational genes, potentially as part of a larger interaction network that intercepts translation to redirect biosynthesis to phage-encoded functions. In addition, some phages may repurpose bacterial CRISPR-Cas systems to eliminate competing phages. We phylogenetically define the major clades of huge phages from human and other animal microbiomes, as well as from oceans, lakes, sediments, soils and the built environment. We conclude that the large gene inventories of huge phages reflect a conserved biological strategy, and that the phages are distributed across a broad bacterial host range and across Earth's ecosystems.

Genetic diversity and evolutionary convergence of cryptic SARS- CoV-2 lineages detected via wastewater sequencing.

Wastewater-based epidemiology (WBE) is an effective way of tracking the appearance and spread of SARS-COV-2 lineages through communities. Beginning in early 2021, we implemented a targeted approach to amplify and sequence the receptor binding domain (RBD) of SARS-COV-2 to characterize viral lineages present in sewersheds. Over the course of 2021, we reproducibly detected multiple SARS-COV-2 RBD lineages that have never been observed in patient samples in 9 sewersheds located in 3 states in the USA. These cryptic lineages contained between 4 to 24 amino acid substitutions in the RBD and were observed intermittently in the sewersheds in which they were found for as long as 14 months. Many of the amino acid substitutions in these lineages occurred at residues also mutated in the Omicron variant of concern (VOC), often with the same substitutions. One of the sewersheds contained a lineage that appeared to be derived from the Alpha VOC, but the majority of the lineages appeared to be derived from pre-VOC SARS-COV-2 lineages. Specifically, several of the cryptic lineages from New York City appeared to be derived from a common ancestor that most likely diverged in early 2020. While the source of these cryptic lineages has not been resolved, it seems increasingly likely that they were derived from long-term patient infections or animal reservoirs. Our findings demonstrate that SARS-COV-2 genetic diversity is greater than what is commonly observed through routine SARS-CoV-2 surveillance. Wastewater sampling may more fully capture SARS-CoV-2 genetic diversity than patient sampling and could reveal new VOCs before they emerge in the wider human population.

Considerations and Opportunities for Probe Capture Enrichment Sequencing of Emerging Viruses from Wastewater.

Until recently, wastewater-based monitoring for pathogens of public health concern primarily used PCR-based quantification methods and targeted sequencing for specific pathogens (e.g., SARS-CoV-2). In the past three years, researchers have expanded sequencing to monitor a broad range of pathogens, applying probe capture enrichment to wastewater. The goals of those studies included (1) monitoring and expanding fundamental knowledge of disease dynamics for known pathogens and (2) evaluating the potential for early detection of emerging diseases resulting from zoonotic spillover or novel viral variants. Several studies using off-the-shelf probe panels designed for clinical and environmental surveillance reported that enrichment increased virus relative abundance but did not recover complete genomes for most nonenteric viruses. Based on our experience and recent results reported by others using these panels for wastewater, clinical, and synthetic samples, we discuss challenges and technical factors that affect the rates of false positive and false negative results. We identify trade-offs and opportunities throughout the workflow, including in wastewater sample processing, probe panel design, and bioinformatic analysis. We suggest tailored methods of virus concentration and background removal, carefully designed probe panels, and multithresholded bioinformatics analysis.

Evaluation of the Impact of Concentration and Extraction Methods on the Targeted Sequencing of Human Viruses from Wastewater.

Sequencing human viruses in wastewater is challenging due to their low abundance compared to the total microbial background. This study compared the impact of four virus concentration/extraction methods (Innovaprep, Nanotrap, Promega, and Solids extraction) on probe-capture enrichment for human viruses followed by sequencing. Different concentration/extraction methods yielded distinct virus profiles. Innovaprep ultrafiltration (following solids removal) had the highest sequencing sensitivity and richness, resulting in the successful assembly of several near-complete human virus genomes. However, it was less sensitive in detecting SARS-CoV-2 by digital polymerase chain reaction (dPCR) compared to Promega and Nanotrap. Across all preparation methods, astroviruses and polyomaviruses were the most highly abundant human viruses, and SARS-CoV-2 was rare. These findings suggest that sequencing success can be increased using methods that reduce nontarget nucleic acids in the extract, though the absolute concentration of total extracted nucleic acid, as indicated by Qubit, and targeted viruses, as indicated by dPCR, may not be directly related to targeted sequencing performance. Further, using broadly targeted sequencing panels may capture viral diversity but risks losing signals for specific low-abundance viruses. Overall, this study highlights the importance of aligning wet lab and bioinformatic methods with specific goals when employing probe-capture enrichment for human virus sequencing from wastewater.

Correlation between wastewater and COVID-19 case incidence rates in major California sewersheds across three variant periods.

Monitoring for COVID-19 through wastewater has been used for adjunctive public health surveillance, with SARS-CoV-2 viral concentrations in wastewater correlating with incident cases in the same sewershed. However, the generalizability of these findings across sewersheds, laboratory methods, and time periods with changing variants and underlying population immunity has not been well described. The California Department of Public Health partnered with six wastewater treatment plants starting in January 2021 to monitor wastewater for SARS-CoV-2, with analyses performed at four laboratories. Using reported PCR-confirmed COVID-19 cases within each sewershed, the relationship between case incidence rates and wastewater concentrations collected over 14 months was evaluated using Spearman's correlation and linear regression. Strong correlations were observed when wastewater concentrations and incidence rates were averaged (10- and 7-day moving window for wastewater and cases, respectively, ρ = 0.73-0.98 for N1 gene target). Correlations remained strong across three time periods with distinct circulating variants and vaccination rates (winter 2020-2021/Alpha, summer 2021/Delta, and winter 2021-2022/Omicron). Linear regression revealed that slopes of associations varied by the dominant variant of concern, sewershed, and laboratory (ß = 0.45-1.94). These findings support wastewater surveillance as an adjunctive public health tool to monitor SARS-CoV-2 community trends.

Wastewater Surveillance to Inform Public Health Decision Making in Residential Institutions.

Testing sewage (wastewater-based surveillance, or WBS) for pathogens is an increasingly important tool for monitoring the health of populations. During the COVID-19 pandemic, some residential institutions including colleges, prisons, and skilled nursing facilities used facility-level wastewater data to inform their pandemic responses. To understand how these early adopters used WBS data in decision making, we conducted in-depth, semistructured interviews with multiple decision makers at 6 residential institutions in the United States (universities, prisons, and nursing homes) encompassing a total of more than 70 000 residents and staff about interpretation, uses, and limitations of these data. We found that WBS data were used in extremely diverse ways. WBS combined with clinical surveillance informed a wide range of public health actions at residential institutions, including transmission reduction measures, public health communications, and allocation of resources. WBS also served other institutional purposes, such as maintaining relationships with external stakeholders and helping alleviate decision makers' pervasive stress. Recognizing these diverse ways of using WBS data can inform expansion of this practice among institutions as well as development of community-scale systems.

Challenges in Measuring the Recovery of SARS-CoV-2 from Wastewater.

Wastewater-based epidemiology is an emerging tool for tracking the spread of SARS-CoV-2 through populations. However, many factors influence recovery and quantification of SARS-CoV-2 from wastewater, complicating data interpretation. Specifically, these factors may differentially affect the measured virus concentration, depending on the laboratory methods used to perform the test. Many laboratories add a proxy virus to wastewater samples to determine losses associated with concentration and extraction of viral RNA. While measuring recovery of a proxy virus is an important process control, in this piece, we describe the caveats and limitations to the interpretation of this control, including that it typically does not account for losses during RNA extraction. We recommend reporting the directly measured concentration data alongside the measured recovery efficiency, rather than attempting to correct the concentration for recovery efficiency. Even though the ability to directly compare SARS-CoV-2 concentrations from different sampling locations determined using different methods is limited, concentration data (uncorrected for recovery) can be useful for public health response.

Sewage, Salt, Silica, and SARS-CoV-2 (4S): An Economical Kit-Free Method for Direct Capture of SARS-CoV-2 RNA from Wastewater.

Wastewater-based epidemiology is an emerging tool to monitor COVID-19 infection levels by measuring the concentration of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater. There remains a need to improve wastewater RNA extraction methods' sensitivity, speed, and reduce reliance on often expensive commercial reagents to make wastewater-based epidemiology more accessible. We present a kit-free wastewater RNA extraction method, titled "Sewage, Salt, Silica and SARS-CoV-2" (4S), that employs the abundant and affordable reagents sodium chloride (NaCl), ethanol, and silica RNA capture matrices to recover sixfold more SARS-CoV-2 RNA from wastewater than an existing ultrafiltration-based method. The 4S method concurrently recovered pepper mild mottle virus (PMMoV) and human 18S ribosomal subunit rRNA, which have been proposed as fecal concentration controls. The SARS-CoV-2 RNA concentrations measured in three sewersheds corresponded to the relative prevalence of COVID-19 infection determined via clinical testing. Lastly, controlled experiments indicate that the 4S method prevented RNA degradation during storage of wastewater samples, was compatible with heat pasteurization, and in our experience, 20 samples can be processed by one lab technician in approximately 2 h. Overall, the 4S method is promising for effective, economical, and accessible wastewater-based epidemiology for SARS-CoV-2, providing another tool to fight the global pandemic.

Genome-Resolved Meta-Omics Ties Microbial Dynamics to Process Performance in Biotechnology for Thiocyanate Degradation.

Remediation of industrial wastewater is important for preventing environmental contamination and enabling water reuse. Biological treatment for one industrial contaminant, thiocyanate (SCN-), relies upon microbial hydrolysis, but this process is sensitive to high loadings. To examine the activity and stability of a microbial community over increasing SCN- loadings, we established and operated a continuous-flow bioreactor fed increasing loadings of SCN-. A second reactor was fed ammonium sulfate to mimic breakdown products of SCN-. Biomass was sampled from both reactors for metagenomics and metaproteomics, yielding a set of genomes for 144 bacteria and one rotifer that constituted the abundant community in both reactors. We analyzed the metabolic potential and temporal dynamics of these organisms across the increasing loadings. In the SCN- reactor, Thiobacillus strains capable of SCN- degradation were highly abundant, whereas the ammonium sulfate reactor contained nitrifiers and heterotrophs capable of nitrate reduction. Key organisms in the SCN- reactor expressed proteins involved in SCN- degradation, sulfur oxidation, carbon fixation, and nitrogen removal. Lower performance at higher loadings was linked to changes in microbial community composition. This work provides an example of how meta-omics can increase our understanding of industrial wastewater treatment and inform iterative process design and development.

Bioreactor microbial ecosystems for thiocyanate and cyanide degradation unravelled with genome-resolved metagenomics.

Gold ore processing uses cyanide (CN(-) ), which often results in large volumes of thiocyanate- (SCN(-) ) contaminated wastewater requiring treatment. Microbial communities can degrade SCN(-) and CN(-) , but little is known about their membership and metabolic potential. Microbial-based remediation strategies will benefit from an ecological understanding of organisms involved in the breakdown of SCN(-) and CN(-) into sulfur, carbon and nitrogen compounds. We performed metagenomic analysis of samples from two laboratory-scale bioreactors used to study SCN(-) and CN(-) degradation. Community analysis revealed the dominance of Thiobacillus spp., whose genomes harbour a previously unreported operon for SCN(-) degradation. Genome-based metabolic predictions suggest that a large portion of each bioreactor community is autotrophic, relying not on molasses in reactor feed but using energy gained from oxidation of sulfur compounds produced during SCN(-) degradation. Heterotrophs, including a bacterium from a previously uncharacterized phylum, compose a smaller portion of the reactor community. Predation by phage and eukaryotes is predicted to affect community dynamics. Genes for ammonium oxidation and denitrification were detected, indicating the potential for nitrogen removal, as required for complete remediation of wastewater. These findings suggest optimization strategies for reactor design, such as improved aerobic/anaerobic partitioning and elimination of organic carbon from reactor feed.

Disturbed subsurface microbial communities follow equivalent trajectories despite different structural starting points.

Microbial community structure, and niche and neutral processes can all influence response to disturbance. Here, we provide experimental evidence for niche versus neutral and founding community effects during a bioremediation-related organic carbon disturbance. Subsurface sediment, partitioned into 22 flow-through columns, was stimulated in situ by the addition of acetate as a carbon and electron donor source. This drove the system into a new transient biogeochemical state characterized by iron reduction and enriched Desulfuromonadales, Comamonadaceae and Bacteroidetes lineages. After approximately 1 month conditions favoured sulfate reduction, and were accompanied by a substantial increase in the relative abundance of Desulfobulbus, Desulfosporosinus, Desulfitobacterium and Desulfotomaculum. Two subsets of four to five columns each were switched from acetate to lactate amendment during either iron (earlier) or sulfate (later) reduction. Hence, subsets had significantly different founding communities. All lactate treatments exhibited lower relative abundances of Desulfotomaculum and Bacteroidetes, enrichments of Clostridiales and Psychrosinus species, and a temporal succession from highly abundant Clostridium sensu stricto to Psychrosinus. Regardless of starting point, lactate-switch communities followed comparable structural trajectories, whereby convergence was evident 9 to 16 days after each switch, and significant after 29 to 34 days of lactate addition. Results imply that neither the founding community nor neutral processes influenced succession following perturbation.

Responses of drinking water bulk and biofilm microbiota to elevated water age in bench-scale simulated distribution systems.

Reductions in nonresidential water demand during the COVID-19 pandemic highlighted the importance of understanding how water age impacts drinking water quality and microbiota in piped distribution systems. Using benchtop model distribution systems, we aimed to characterize the impacts of elevated water age on microbiota in bulk water and pipe wall biofilms. Five replicate constant-flow reactors were fed with municipal chloraminated tap water for 6 months prior to building closures and 7 months after. After building closures, chloramine levels entering the reactors dropped; in the reactor bulk water and biofilms the mean cell counts and ATP concentrations increased over an order of magnitude while the detection of opportunistic pathogens remained low. Water age, and the corresponding physicochemical changes, strongly influenced microbial abundance and community composition. Differential initial microbial colonization also had a lasting influence on microbial communities in each reactor (i.e., historical contingency).

The dynamic relationship between COVID-19 cases and SARS-CoV-2 wastewater concentrations across time and space: Considerations for model training data sets.

During the COVID-19 pandemic, wastewater-based surveillance has been used alongside diagnostic testing to monitor infection rates. With the decline in cases reported to public health departments due to at-home testing, wastewater data may serve as the primary input for epidemiological models, but training these models is not straightforward. We explored factors affecting noise and bias in the ratio between wastewater and case data collected in 26 sewersheds in California from October 2020 to March 2022. The strength of the relationship between wastewater and case data appeared dependent on sampling frequency and population size, but was not increased by wastewater normalization to flow rate or case count normalization to testing rates. Additionally, the lead and lag times between wastewater and case data varied over time and space, and the ratio of log-transformed individual cases to wastewater concentrations changed over time. This ratio decreased between the Epsilon/Alpha and Delta variant surges of COVID-19 and increased during the Omicron BA.1 variant surge, and was also related to the diagnostic testing rate. Based on this analysis, we present a framework of scenarios describing the dynamics of the case to wastewater ratio to aid in data handling decisions for ongoing modeling efforts.

O2 partitioning of sulfur oxidizing bacteria drives acidity and thiosulfate distributions in mining waters.

The acidification of water in mining areas is a global environmental issue primarily catalyzed by sulfur-oxidizing bacteria (SOB). Little is known about microbial sulfur cycling in circumneutral pH mine tailing impoundment waters. Here we investigate biological sulfur oxidation over four years in a mine tailings impoundment water cap, integrating aqueous sulfur geochemistry, genome-resolved metagenomics and metatranscriptomics. The microbial community is consistently dominated by neutrophilic, chemolithoautotrophic SOB (relative abundances of ~76% in 2015, ~55% in 2016/2017 and ~60% in 2018). Results reveal two SOB strategies alternately dominate across the four years, influencing acid generation and sulfur speciation. Under oxic conditions, novel Halothiobacillus drive lower pH conditions (as low as 4.3) and lower [S2O32-] via the complete Sox pathway coupled to O2. Under anoxic conditions, Thiobacillus spp. dominate in activity, via the incomplete Sox and rDSR pathways coupled to NO3-, resulting in higher [S2O32-] and no net significant acidity generation. This study provides genomic evidence explaining acidity generation and thiosulfate accumulation patterns in a circumneutral mine tailing impoundment and has significant environmental applications in preventing the discharge of sulfur compounds that can impact downstream environments. These insights illuminate opportunities for in situ biotreatment of reduced sulfur compounds and prediction of acidification events using gene-based monitoring and in situ RNA detection.

Microbial Water Quality through a Full-Scale Advanced Wastewater Treatment Demonstration Facility.

The fates of viruses, bacteria, and antibiotic resistance genes during advanced wastewater treatment are important to assess for implementation of potable reuse systems. Here, a full-scale advanced wastewater treatment demonstration facility (ozone, biological activated carbon filtration, micro/ultrafiltration, reverse osmosis, and advanced oxidation) was sampled over three months. Atypically, no disinfectant residual was applied before the microfiltration step. Microbial cell concentrations and viability were assessed via flow cytometry and adenosine triphosphate (ATP). Concentrations of bacteria (16S rRNA gene), viruses (human adenovirus and JC polyomavirus), and antibiotic resistance genes (sul1 and bla TEM ) were assessed via quantitative PCR following the concentration of large sample volumes by dead-end ultrafiltration. In all membrane filtration permeates, microbial concentrations were higher than previously reported for chloraminated membranes, and log10 reduction values were lower than expected. Concentrations of 16S rRNA and sul1 genes were reduced by treatment but remained quantifiable in reverse osmosis permeate. It is unclear whether sul1 in the RO permeate was from the passage of resistance genes or new growth of microorganisms, but the concentrations were on the low end of those reported for conventional drinking water distribution systems. Adenovirus, JC polyomavirus, and bla TEM genes were reduced below the limit of detection (∼10-2 gene copies per mL) by microfiltration. The results provide insights into how treatment train design and operation choices affect microbial water quality as well as the use of flow cytometry and ATP for online monitoring and process control.

SARS-CoV-2 RNA is enriched by orders of magnitude in primary settled solids relative to liquid wastewater at publicly owned treatment works.

Wastewater-based epidemiology has gained attention throughout the world for detection of SARS-CoV-2 RNA in wastewater to supplement clinical testing. Raw wastewater consists of small particles, or solids, suspended in liquid. Methods have been developed to measure SARS-CoV-2 RNA in the liquid and the solid fraction of wastewater, with some studies reporting higher concentrations in the solid fraction. To investigate this relationship further, six laboratories collaborated to conduct a study across five publicly owned treatment works (POTWs) where both primary settled solids obtained from primary clarifiers and raw wastewater influent samples were collected and quantified for SARS-CoV-2 RNA. Settled solids and influent samples were processed by participating laboratories using their respective methods and retrospectively paired based on date of collection. SARS-CoV-2 RNA concentrations, on a mass equivalent basis, were higher in settled solids than in influent by approximately three orders of magnitude. Concentrations in matched settled solids and influent were positively and significantly correlated at all five POTWs. RNA concentrations in both settled solids and influent were correlated to COVID-19 incidence rates in the sewersheds and thus representative of disease occurrence; the settled solids methods appeared to produce a comparable relationship between SARS-CoV-2 RNA concentration measurements and incidence rates across all POTWs. Settled solids and influent methods showed comparable sensitivity, N gene detection frequency, and calculated empirical incidence rate lower limits. Analysis of settled solids for SARS-CoV-2 RNA has the advantage of using less sample volume to achieve similar sensitivity to influent methods.

Genetic Diversity and Evolutionary Convergence of Cryptic SARS-CoV-2 Lineages Detected Via Wastewater Sequencing.

Wastewater-based epidemiology (WBE) is an effective way of tracking the appearance and spread of SARS-COV-2 lineages through communities. Beginning in early 2021, we implemented a targeted approach to amplify and sequence the receptor binding domain (RBD) of SARS-COV-2 to characterize viral lineages present in sewersheds. Over the course of 2021, we reproducibly detected multiple SARS-COV-2 RBD lineages that have never been observed in patient samples in 9 sewersheds located in 3 states in the USA. These cryptic lineages contained between 4 to 24 amino acid substitutions in the RBD and were observed intermittently in the sewersheds in which they were found for as long as 14 months. Many of the amino acid substitutions in these lineages occurred at residues also mutated in the Omicron variant of concern (VOC), often with the same substitution. One of the sewersheds contained a lineage that appeared to be derived from the Alpha VOC, but the majority of the lineages appeared to be derived from pre-VOC SARS-COV-2 lineages. Specifically, several of the cryptic lineages from New York City appeared to be derived from a common ancestor that most likely diverged in early 2020. While the source of these cryptic lineages has not been resolved, it seems increasingly likely that they were derived from immunocompromised patients or animal reservoirs. Our findings demonstrate that SARS-COV-2 genetic diversity is greater than what is commonly observed through routine SARS-CoV-2 surveillance. Wastewater sampling may more fully capture SARS-CoV-2 genetic diversity than patient sampling and could reveal new VOCs before they emerge in the wider human population. Author Summary: During the COVID-19 pandemic, wastewater-based epidemiology has become an effective public health tool. Because many infected individuals shed SARS-CoV-2 in feces, wastewater has been monitored to reveal infection trends in the sewersheds from which the samples were derived. Here we report novel SARS-CoV-2 lineages in wastewater samples obtained from 3 different states in the USA. These lineages appeared in specific sewersheds intermittently over periods of up to 14 months, but generally have not been detected beyond the sewersheds in which they were initially found. Many of these lineages may have diverged in early 2020. Although these lineages share considerable overlap with each other, they have never been observed in patients anywhere in the world. While the wastewater lineages have similarities with lineages observed in long-term infections of immunocompromised patients, animal reservoirs cannot be ruled out as a potential source.

Thiocyanate and Organic Carbon Inputs Drive Convergent Selection for Specific Autotrophic Afipia and Thiobacillus Strains Within Complex Microbiomes.

Thiocyanate (SCN-) contamination threatens aquatic ecosystems and pollutes vital freshwater supplies. SCN--degrading microbial consortia are commercially adapted for remediation, but the impact of organic amendments on selection within SCN--degrading microbial communities has not been investigated. Here, we tested whether specific strains capable of degrading SCN- could be reproducibly selected for based on SCN- loading and the presence or absence of added organic carbon. Complex microbial communities derived from those used to treat SCN--contaminated water were exposed to systematically increased input SCN concentrations in molasses-amended and -unamended reactors and in reactors switched to unamended conditions after establishing the active SCN--degrading consortium. Five experiments were conducted over 790 days, and genome-resolved metagenomics was used to resolve community composition at the strain level. A single Thiobacillus strain proliferated in all reactors at high loadings. Despite the presence of many Rhizobiales strains, a single Afipia variant dominated the molasses-free reactor at moderately high loadings. This strain is predicted to break down SCN- using a novel thiocyanate desulfurase, oxidize resulting reduced sulfur, degrade product cyanate to ammonia and CO2 via cyanate hydratase, and fix CO2 via the Calvin-Benson-Bassham cycle. Removal of molasses from input feed solutions reproducibly led to dominance of this strain. Although sustained by autotrophy, reactors without molasses did not stably degrade SCN- at high loading rates, perhaps due to loss of biofilm-associated niche diversity. Overall, convergence in environmental conditions led to convergence in the strain composition, although reactor history also impacted the trajectory of community compositional change.

Genome Sequencing of Sewage Detects Regionally Prevalent SARS-CoV-2 Variants.

Viral genome sequencing has guided our understanding of the spread and extent of genetic diversity of SARS-CoV-2 during the COVID-19 pandemic. SARS-CoV-2 viral genomes are usually sequenced from nasopharyngeal swabs of individual patients to track viral spread. Recently, RT-qPCR of municipal wastewater has been used to quantify the abundance of SARS-CoV-2 in several regions globally. However, metatranscriptomic sequencing of wastewater can be used to profile the viral genetic diversity across infected communities. Here, we sequenced RNA directly from sewage collected by municipal utility districts in the San Francisco Bay Area to generate complete and nearly complete SARS-CoV-2 genomes. The major consensus SARS-CoV-2 genotypes detected in the sewage were identical to clinical genomes from the region. Using a pipeline for single nucleotide variant calling in a metagenomic context, we characterized minor SARS-CoV-2 alleles in the wastewater and detected viral genotypes which were also found within clinical genomes throughout California. Observed wastewater variants were more similar to local California patient-derived genotypes than they were to those from other regions within the United States or globally. Additional variants detected in wastewater have only been identified in genomes from patients sampled outside California, indicating that wastewater sequencing can provide evidence for recent introductions of viral lineages before they are detected by local clinical sequencing. These results demonstrate that epidemiological surveillance through wastewater sequencing can aid in tracking exact viral strains in an epidemic context.

Tools for interpretation of wastewater SARS-CoV-2 temporal and spatial trends demonstrated with data collected in the San Francisco Bay Area.

Wastewater surveillance for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA can be integrated with COVID-19 case data to inform timely pandemic response. However, more research is needed to apply and develop systematic methods to interpret the true SARS-CoV-2 signal from noise introduced in wastewater samples (e.g., from sewer conditions, sampling and extraction methods, etc.). In this study, raw wastewater was collected weekly from five sewersheds and one residential facility. The concentrations of SARS-CoV-2 in wastewater samples were compared to geocoded COVID-19 clinical testing data. SARS-CoV-2 was reliably detected (95% positivity) in frozen wastewater samples when reported daily new COVID-19 cases were 2.4 or more per 100,000 people. To adjust for variation in sample fecal content, four normalization biomarkers were evaluated: crAssphage, pepper mild mottle virus, Bacteroides ribosomal RNA (rRNA), and human 18S rRNA. Of these, crAssphage displayed the least spatial and temporal variability. Both unnormalized SARS-CoV-2 RNA signal and signal normalized to crAssphage had positive and significant correlation with clinical testing data (Kendall's Tau-b (τ)=0.43 and 0.38, respectively), but no normalization biomarker strengthened the correlation with clinical testing data. Locational dependencies and the date associated with testing data impacted the lead time of wastewater for clinical trends, and no lead time was observed when the sample collection date (versus the result date) was used for both wastewater and clinical testing data. This study supports that trends in wastewater surveillance data reflect trends in COVID-19 disease occurrence and presents tools that could be applied to make wastewater signal more interpretable and comparable across studies.