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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.

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.

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.

The original version of this Article contained errors in Fig. 4. In panel a, the labels 'F420-reducing NiFe hydrogenase (group 3a)' and 'Group 2 NiFe hydrogenase' were misplaced. These errors have been corrected in both the PDF and HTML versions of the Article.

The evolution of aerobic respiration was likely linked to the origins of oxygenic Cyanobacteria. Close phylogenetic neighbors to Cyanobacteria, such as Margulisbacteria (RBX-1 and ZB3), Saganbacteria (WOR-1), Melainabacteria and Sericytochromatia, may constrain the metabolic platform in which aerobic respiration arose. Here, we analyze genomic sequences and predict that sediment-associated Margulisbacteria have a fermentation-based metabolism featuring a variety of hydrogenases, a streamlined nitrogenase, and electron bifurcating complexes involved in cycling of reducing equivalents. The genomes of ocean-associated Margulisbacteria encode an electron transport chain that may support aerobic growth. Some Saganbacteria genomes encode various hydrogenases, and others may be able to use O2 under certain conditions via a putative novel type of heme copper O2 reductase. Similarly, Melainabacteria have diverse energy metabolisms and are capable of fermentation and aerobic or anaerobic respiration. The ancestor of all these groups may have been an anaerobe in which fermentation and H2 metabolism were central metabolic features. The ability to use O2 as a terminal electron acceptor must have been subsequently acquired by these lineages.

A critical step in the biogeochemical cycle of sulfur on Earth is microbial sulfate reduction, yet organisms from relatively few lineages have been implicated in this process. Previous studies using functional marker genes have detected abundant, novel dissimilatory sulfite reductases (DsrAB) that could confer the capacity for microbial sulfite/sulfate reduction but were not affiliated with known organisms. Thus, the identity of a significant fraction of sulfate/sulfite-reducing microbes has remained elusive. Here we report the discovery of the capacity for sulfate/sulfite reduction in the genomes of organisms from 13 bacterial and archaeal phyla, thereby more than doubling the number of microbial phyla associated with this process. Eight of the 13 newly identified groups are candidate phyla that lack isolated representatives, a finding only possible given genomes from metagenomes. Organisms from Verrucomicrobia and two candidate phyla, Candidatus Rokubacteria and Candidatus Hydrothermarchaeota, contain some of the earliest evolved dsrAB genes. The capacity for sulfite reduction has been laterally transferred in multiple events within some phyla, and a key gene potentially capable of modulating sulfur metabolism in associated cells has been acquired by putatively symbiotic bacteria. We conclude that current functional predictions based on phylogeny significantly underestimate the extent of sulfate/sulfite reduction across Earth's ecosystems. Understanding the prevalence of this capacity is integral to interpreting the carbon cycle because sulfate reduction is often coupled to turnover of buried organic carbon. Our findings expand the diversity of microbial groups associated with sulfur transformations in the environment and motivate revision of biogeochemical process models based on microbial community composition.

The vast majority of bacterial diversity lies within phylum-level lineages called "candidate phyla," which lack isolated representatives and are poorly understood. These bacteria are surprisingly abundant in the oral cavity of marine mammals. We employed a genome-resolved metagenomic approach to recover and characterize genomes and functional potential from microbes in the oral gingival sulcus of two bottlenose dolphins (Tursiops truncatus). We detected organisms from 24 known bacterial phyla and one archaeal phylum. We also recovered genomes from two deep-branching, previously uncharacterized phylum-level lineages (here named "Candidatus Delphibacteria" and "Candidatus Fertabacteria"). The Delphibacteria lineage is found in both managed and wild dolphins; its metabolic profile suggests a capacity for denitrification and a possible role in dolphin health. We uncovered a rich diversity of predicted Cas9 proteins, including the two longest predicted Cas9 proteins to date. Notably, we identified the first type II CRISPR-Cas systems encoded by members of the Candidate Phyla Radiation. Using their spacer sequences, we subsequently identified and assembled a complete Saccharibacteria phage genome. These findings underscore the immense microbial diversity and functional potential that await discovery in previously unexplored environments.

Thiocyanate (SCN- ) is a toxic compound that forms when cyanide (CN- ), used to recover gold, reacts with sulfur species. SCN- -degrading microbial communities have been studied, using bioreactors fed synthetic wastewater. The inclusion of suspended solids in the form of mineral tailings, during the development of the acclimatized microbial consortium, led to the selection of an active planktonic microbial community. Preliminary analysis of the community composition revealed reduced microbial diversity relative to the laboratory-based reactors operated without suspended solids. Despite minor upsets during the acclimation period, the SCN- degradation performance was largely unchanged under stable operating conditions. Here, we characterized the microbial community in the SCN- degrading bioreactor that included solid particulate tailings and determined how it differed from the biofilm-based communities in solids-free reactor systems inoculated from the same source. Genome-based analysis revealed that the presence of solids decreased microbial diversity, selected for different strains, suppressed growth of thiobacilli inferred to be primarily responsible for SCN- degradation, and promoted growth of Trupera, an organism not detected in the reactors without solids. In the solids reactor community, heterotrophy and aerobic respiration represent the dominant metabolisms. Many organisms have genes for denitrification and sulfur oxidation, but only one Thiobacillus sp. in the solids reactor has SCN- degradation genes. The presence of the solids prevented floc and biofilm formation, leading to the observed reduced microbial diversity. Collectively the presence of the solids and lack of biofilm community may result in a process with reduced resilience to process perturbations, including fluctuations in the influent composition and pH. The results from this investigation have provided novel insights into the community composition of this industrially relevant community, giving potential for improved process control and operation through ongoing process monitoring.

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.

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.

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.

UnlabelledCultivation-independent surveys of microbial diversity have revealed many bacterial phyla that lack cultured representatives. These lineages, referred to as candidate phyla, have been detected across many environments. Here, we deeply sequenced microbial communities from acetate-stimulated aquifer sediment to recover the complete and essentially complete genomes of single representatives of the candidate phyla SR1, WWE3, TM7, and OD1. All four of these genomes are very small, 0.7 to 1.2 Mbp, and have large inventories of novel proteins. Additionally, all lack identifiable biosynthetic pathways for several key metabolites. The SR1 genome uses the UGA codon to encode glycine, and the same codon is very rare in the OD1 genome, suggesting that the OD1 organism could also transition to alternate coding. Interestingly, the relative abundance of the members of SR1 increased with the appearance of sulfide in groundwater, a pattern mirrored by a member of the phylum Tenericutes. All four genomes encode type IV pili, which may be involved in interorganism interaction. On the basis of these results and other recently published research, metabolic dependence on other organisms may be widely distributed across multiple bacterial candidate phyla.ImportanceFew or no genomic sequences exist for members of the numerous bacterial phyla lacking cultivated representatives, making it difficult to assess their roles in the environment. This paper presents three complete and one essentially complete genomes of members of four candidate phyla, documents consistently small genome size, and predicts metabolic capabilities on the basis of gene content. These metagenomic analyses expand our view of a lifestyle apparently common across these candidate phyla.

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., Competing Interests: Bradley J. White, Aaron Topol, and Dorothea H. Duong are employees of Verily Life Sciences., (This journal is © The Royal Society of Chemistry.)

SARS-CoV-2 RNA detection in wastewater is being rapidly developed and adopted as a public health monitoring tool worldwide. With wastewater surveillance programs being implemented across many different scales and by many different stakeholders, it is critical that data collected and shared are accompanied by an appropriate minimal amount of metainformation to enable meaningful interpretation and use of this new information source and intercomparison across datasets. While some databases are being developed for specific surveillance programs locally, regionally, nationally, and internationally, common globally-adopted data standards have not yet been established within the research community. Establishing such standards will require national and international consensus on what metainformation should accompany SARS-CoV-2 wastewater measurements. To establish a recommendation on minimum information to accompany reporting of SARS-CoV-2 occurrence in wastewater for the research community, the United States National Science Foundation (NSF) Research Coordination Network on Wastewater Surveillance for SARS-CoV-2 hosted a workshop in February 2021 with participants from academia, government agencies, private companies, wastewater utilities, public health laboratories, and research institutes. This report presents the primary two outcomes of the workshop: (i) a recommendation on the set of minimum meta-information that is needed to confidently interpret wastewater SARS-CoV-2 data, and (ii) insights from workshop discussions on how to improve standardization of data reporting., Competing Interests: Conflicts of interest C. D. is an employee of Biobot Analytics, Inc. P. K. is the founder of Venthic Technologies. B. M. S. is an employee of IDEXX Laboratories, Inc. R. U. H. is a cofounder of AquaVitas, LLC and the nonprofit project OneWaterOneHealth of the Arizona State University Foundation.