A snapshot of the global drinking water virome: Diversity and metabolic potential vary with residual disinfectant use

New Drinking Water Genome Catalog Identifies a Globally Distributed Bacterial Genus Adapted to Disinfected Drinking Water Systems

Genome-resolved insights into the structure and function of the drinking water microbiome can advance the effective management of drinking water quality. To enable this, we constructed and curated thousands of metagenome-assembled and isolate genomes from drinking water distribution systems globally to develop a Drinking Water Genome Catalog (DWGC). The current DWGC disproportionately represents disinfected drinking water systems due to a paucity of metagenomes from nondisinfected systems. Using the DWGC, we identify core genera of the drinking water microbiome including a genus (UBA4765) within the order Rhizobiales that is frequently detected and highly abundant in disinfected drinking water systems. We demonstrate that this genus has been widely detected but incorrectly classified in previous amplicon sequencing-based investigations of the drinking water microbiome. Further, we show that a single genome variant (genomovar) within this genus is detected in 75% of drinking water systems included in this study. We propose a name for this uncultured bacterium as "Raskinella chloraquaticus" and describe the genus as "Raskinella" (endorsed by SeqCode). Metabolic annotation and modeling-based predictions indicate that this bacterium is capable of necrotrophic growth, is able to metabolize halogenated compounds, proliferates in a biofilm-based environment, and shows clear indications of disinfection-mediated selection.

Phage phylogeny, molecular signaling, and auxiliary antimicrobial resistance in aerobic and anaerobic membrane bioreactors

Phage emit communication signals that inform their lytic and lysogenic life cycles. However, little is known regarding the abundance and diversity of the genes associated with phage communication systems in wastewater treatment microbial communities. This study focused on phage communities within two distinct biochemical wastewater environments, specifically aerobic membrane bioreactors (AeMBRs) and anaerobic membrane bioreactors (AnMBRs) exposed to varying antibiotic concentrations. Metagenomic data from the bench-scale systems were analyzed to explore phage phylogeny, life cycles, and genetic capacity for antimicrobial resistance and quorum sensing. Two dominant phage families, Schitoviridae and Peduoviridae, exhibited redox-dependent dynamics. Schitoviridae prevailed in anaerobic conditions, while Peduoviridae dominated in aerobic conditions. Notably, the abundance of lytic and lysogenic proteins varied across conditions, suggesting the coexistence of both life cycles. Furthermore, the presence of antibiotic resistance genes (ARGs) within viral contigs highlighted the potential for phage to transfer ARGs in AeMBRs. Finally, quorum sensing genes in the virome of AeMBRs indicated possible molecular signaling between phage and bacteria. Overall, this study provides insights into the dynamics of viral communities across varied redox conditions in MBRs. These findings shed light on phage life cycles, and auxiliary genetic capacity such as antibiotic resistance and bacterial quorum sensing within wastewater treatment microbial communities.

Benchmarking informatics approaches for virus discovery: caution is needed when combining in silico identification methods

Understanding the ecological impacts of viruses on natural and engineered ecosystems relies on the accurate identification of viral sequences from community sequencing data. To maximize viral recovery from metagenomes, researchers frequently combine viral identification tools. However, the effectiveness of this strategy is unknown. Here, we benchmarked combinations of six widely used informatics tools for viral identification and analysis (VirSorter, VirSorter2, VIBRANT, DeepVirFinder, CheckV, and Kaiju), called "rulesets." Rulesets were tested against mock metagenomes composed of taxonomically diverse sequence types and diverse aquatic metagenomes to assess the effects of the degree of viral enrichment and habitat on tool performance. We found that six rulesets achieved equivalent accuracy [Matthews Correlation Coefficient (MCC) = 0.77, Padj ≥ 0.05]. Each contained VirSorter2, and five used our "tuning removal" rule designed to remove non-viral contamination. While DeepVirFinder, VIBRANT, and VirSorter were each found once in these high-accuracy rulesets, they were not found in combination with each other: combining tools does not lead to optimal performance. Our validation suggests that the MCC plateau at 0.77 is partly caused by inaccurate labeling within reference sequence databases. In aquatic metagenomes, our highest MCC ruleset identified more viral sequences in virus-enriched (44%-46%) than in cellular metagenomes (7%-19%). While improved algorithms may lead to more accurate viral identification tools, this should be done in tandem with careful curation of sequence databases. We recommend using the VirSorter2 ruleset and our empirically derived tuning removal rule. Our analysis provides insight into methods for in silico viral identification and will enable more robust viral identification from metagenomic data sets.

IMPORTANCE

The identification of viruses from environmental metagenomes using informatics tools has offered critical insights in microbial ecology. However, it remains difficult for researchers to know which tools optimize viral recovery for their specific study. In an attempt to recover more viruses, studies are increasingly combining the outputs from multiple tools without validating this approach. After benchmarking combinations of six viral identification tools against mock metagenomes and environmental samples, we found that these tools should only be combined cautiously. Two to four tool combinations maximized viral recovery and minimized non-viral contamination compared with either the single-tool or the five- to six-tool ones. By providing a rigorous overview of the behavior of in silico viral identification strategies and a pipeline to replicate our process, our findings guide the use of existing viral identification tools and offer a blueprint for feature engineering of new tools that will lead to higher-confidence viral discovery in microbiome studies.

Microbial ecology of drinking water from source to tap

As drinking water travels from its source, through various treatment processes, hundreds to thousands of kilometres of distribution network pipes, to the taps in private homes and public buildings, it is exposed to numerous environmental changes, as well as other microbes living in both water and on surfaces. This review aims to identify the key locations and factors that are associated with changes in the drinking water microbiome throughout conventional urban drinking water systems from the source to the tap water. Over the past 15 years, improvements in cultivation-independent methods have enabled studies that allow us to answer such questions. As a result, we are beginning to move towards predicting the impacts of disturbances and interventions resulting ultimately in management of drinking water systems and microbial communities rather than mere observation. Many challenges still exist to achieve effective management, particularly within the premise plumbing environment, which exhibits diverse and inconsistent conditions that may lead to alterations in the microbiota, potentially presenting public health risks. Finally, we recommend the establishment of global collaborative projects on the drinking water microbiome that will enhance our current knowledge and lead to tools for operators and researchers alike to improve global access to high-quality drinking water.

Bacteriophages: Vectors of or weapons against the transmission of antibiotic resistance genes in hospital wastewater systems?

Antimicrobial resistance poses a serious threat to human health and is responsible for the death of millions of people annually. Hospital wastewater is an important hotspot for antibiotic-resistance genes (ARGs) and antibiotic-resistant bacteria (ARB). However, little is known about the relationship between phages and ARGs in hospital wastewater systems (HWS). In the present study, the viral diversity of 12 HWSs using data from public metagenomic databases was investigated. Viruses were widely found in both the influent and effluent of each HWS. A total of 45 unique ARGs were carried by 85 viral contigs, which accounted for only 0.14% of the total viral populations, implying that ARGs were not commonly present in phages. Three efflux pump genes were identified as shared between phages and bacterial genomes. However, the predominant types of ARGs in HWS such as aminoglycoside- and beta-lactam-resistance genes were rarely found in phages. Based on CRISPR spacer and tRNA matches, interactions between 171 viral contigs and 60 antibiotic-resistant genomes were predicted, including interactions involving phages and vancomycin-resistant Enterococcus_B faecium or beta-lactam-resistant Klebsiella pneumoniae. More than half (56.1%) of these viral contigs indicated lytic and none of them carried ARGs. As the vOTUs in this study had few ARGs and were primarily lytic, HWS may be a valuable source for phage discovery. Future studies will be able to experimentally validate these sequence-based results to confirm the suitability of HWS phages for pathogen control measures in wastewater.

Global diversity and biogeography of DNA viral communities in activated sludge systems

BACKGROUND

Activated sludge (AS) systems in wastewater treatment plants (WWTPs) harbor enormous viruses that regulate microbial metabolism and nutrient cycling, significantly influencing the stability of AS systems. However, our knowledge about the diversity of viral taxonomic groups and functional traits in global AS systems is still limited. To address this gap, we investigated the global diversity and biogeography of DNA viral communities in AS systems using 85,114 viral operational taxonomic units (vOTUs) recovered from 144 AS samples collected across 54 WWTPs from 13 different countries.

RESULTS

AS viral communities and their functional traits exhibited distance-decay relationship (DDR) at the global scale and latitudinal diversity gradient (LDG) from equator to mid-latitude. Furthermore, it was observed that AS viral community and functional gene structures were largely driven by the geographic factors and wastewater types, of which the geographic factors were more important. Carrying and disseminating auxiliary metabolic genes (AMGs) associated with the degradation of polysaccharides, sulfate reduction, denitrification, and organic phosphoester hydrolysis, as well as the lysis of crucial functional microbes that govern biogeochemical cycles were two major ways by which viruses could regulate AS functions. It was worth noting that our study revealed a high abundance of antibiotic resistance genes (ARGs) in viral genomes, suggesting that viruses were key reservoirs of ARGs in AS systems.

CONCLUSIONS

Our results demonstrated the highly diverse taxonomic groups and functional traits of viruses in AS systems. Viral lysis of host microbes and virus-mediated HGT can regulate the biogeochemical and nutrient cycles, thus affecting the performance of AS systems. These findings provide important insights into the viral diversity, function, and ecology in AS systems on a global scale. Video Abstract.

Gut Phageome-An Insight into the Role and Impact of Gut Microbiome and Their Correlation with Mammal Health and Diseases

The gut microbiota, including bacteria, archaea, fungi, and viruses, compose a diverse mammalian gut environment and are highly associated with host health. Bacteriophages, the viruses that infect bacteria, are the primary members of the gastrointestinal virome, known as the phageome. However, our knowledge regarding the gut phageome remains poorly understood. In this review, the critical role of the gut phageome and its correlation with mammalian health were summarized. First, an overall profile of phages across the gastrointestinal tract and their dynamic roles in shaping the surrounding microorganisms was elucidated. Further, the impacts of the gut phageome on gastrointestinal fitness and the bacterial community were highlighted, together with the influence of diets on the gut phageome composition. Additionally, new reports on the role of the gut phageome in the association of mammalian health and diseases were reviewed. Finally, a comprehensive update regarding the advanced phage benchwork and contributions of phage-based therapy to prevent/treat mammalian diseases was provided. This study provides insights into the role and impact of the gut phagenome in gut environments closely related to mammal health and diseases. The findings provoke the potential applications of phage-based diagnosis and therapy in clinical and agricultural fields. Future research is needed to uncover the underlying mechanism of phage-bacterial interactions in gut environments and explore the maintenance of mammalian health via phage-regulated gut microbiota.

The association of prokaryotic antiviral systems and symbiotic phage communities in drinking water microbiomes

Prokaryotic antiviral systems are important mediators for prokaryote-phage interactions, which have significant implications for the survival of prokaryotic community. However, the prokaryotic antiviral systems under environmental stress are poorly understood, limiting the understanding of microbial adaptability. Here, we systematically investigated the profile of the prokaryotic antiviral systems at the community level and prokaryote-phage interactions in the drinking water microbiome. Chlorine disinfectant was revealed as the main ecological driver for the difference in prokaryotic antiviral systems and prokaryote-phage interactions. Specifically, the prokaryotic antiviral systems in the microbiome exhibited a higher abundance, broader antiviral spectrum, and lower metabolic burden under disinfectant stress. Moreover, significant positive correlations were observed between phage lysogenicity and enrichment of antiviral systems (e.g., Type IIG and IV restriction-modification (RM) systems, and Type II CRISPR-Cas system) in the presence of disinfection, indicating these antiviral systems might be more compatible with lysogenic phages and prophages. Accordingly, there was a stronger prokaryote-phage symbiosis in disinfected microbiome, and the symbiotic phages carried more auxiliary metabolic genes (AMGs) related to prokaryotic adaptability as well as antiviral systems, which might further enhance prokaryote survival in drinking water distribution systems. Overall, this study demonstrates that the prokaryotic antiviral systems had a close association with their symbiotic phages, which provides novel insights into prokaryote-phage interactions and microbial environmental adaptation.

Identifying Eukaryotes and Factors Influencing Their Biogeography in Drinking Water Metagenomes

The biogeography of eukaryotes in drinking water systems is poorly understood relative to that of prokaryotes or viruses, limiting the understanding of their role and management. A challenge with studying complex eukaryotic communities is that metagenomic analysis workflows are currently not as mature as those that focus on prokaryotes or viruses. In this study, we benchmarked different strategies to recover eukaryotic sequences and genomes from metagenomic data and applied the best-performing workflow to explore the factors affecting the relative abundance and diversity of eukaryotic communities in drinking water distribution systems (DWDSs). We developed an ensemble approach exploiting k-mer- and reference-based strategies to improve eukaryotic sequence identification and identified MetaBAT2 as the best-performing binning approach for their clustering. Applying this workflow to the DWDS metagenomes showed that eukaryotic sequences typically constituted small proportions (i.e., <1%) of the overall metagenomic data with higher relative abundances in surface water-fed or chlorinated systems with high residuals. The α and β diversities of eukaryotes were correlated with those of prokaryotic and viral communities, highlighting the common role of environmental/management factors. Finally, a co-occurrence analysis highlighted clusters of eukaryotes whose members' presence and abundance in DWDSs were affected by disinfection strategies, climate conditions, and source water types.

Evaluation of computational phage detection tools for metagenomic datasets

Introduction

As new computational tools for detecting phage in metagenomes are being rapidly developed, a critical need has emerged to develop systematic benchmarks.

Methods

In this study, we surveyed 19 metagenomic phage detection tools, 9 of which could be installed and run at scale. Those 9 tools were assessed on several benchmark challenges. Fragmented reference genomes are used to assess the effects of fragment length, low viral content, phage taxonomy, robustness to eukaryotic contamination, and computational resource usage. Simulated metagenomes are used to assess the effects of sequencing and assembly quality on the tool performances. Finally, real human gut metagenomes and viromes are used to assess the differences and similarities in the phage communities predicted by the tools.

Results

We find that the various tools yield strikingly different results. Generally, tools that use a homology approach (VirSorter, MARVEL, viralVerify, VIBRANT, and VirSorter2) demonstrate low false positive rates and robustness to eukaryotic contamination. Conversely, tools that use a sequence composition approach (VirFinder, DeepVirFinder, Seeker), and MetaPhinder, have higher sensitivity, including to phages with less representation in reference databases. These differences led to widely differing predicted phage communities in human gut metagenomes, with nearly 80% of contigs being marked as phage by at least one tool and a maximum overlap of 38.8% between any two tools. While the results were more consistent among the tools on viromes, the differences in results were still significant, with a maximum overlap of 60.65%. Discussion: Importantly, the benchmark datasets developed in this study are publicly available and reusable to enable the future comparability of new tools developed.