Viral metagenomes of Lake Soyang, the largest freshwater lake in South Korea

Virus-prokaryote infection pairs associated with prokaryotic production in a freshwater lake

Viruses infect and kill prokaryotic populations in a density- or frequency-dependent manner and affect carbon cycling. However, the effects of the stratification transition, including the stratified and de-stratified periods, on the changes in prokaryotic and viral communities and their interactions remain unclear. We conducted a monthly survey of the surface and deep layers of a large and deep freshwater lake (Lake Biwa, Japan) for a year and analyzed the prokaryotic production and prokaryotic and viral community composition. Our analysis revealed that, in the surface layer, 19 prokaryotic species, accounting for approximately 40% of the total prokaryotic abundance, could potentially contribute to the majority of prokaryotic production, which is the highest during the summer and is suppressed by viruses. This suggests that a small fraction of prokaryotes and phages were the key infection pairs during the peak period of prokaryotic activity in the freshwater lake. We also found that approximately 50% of the dominant prokaryotic and viral species in the deep layer were present throughout the study period. This suggests that the "kill the winner" model could explain the viral impact on prokaryotes in the surface layer, but other dynamics may be at play in the deep layer. Furthermore, we found that annual vertical mixing could result in a similar rate of community change between the surface and deep layers. These findings may be valuable in understanding how communities and the interaction among them change when freshwater lake stratification is affected by global warming in the future.IMPORTANCEViral infection associated with prokaryotic production occurs in a density- or frequency-dependent manner and regulates the prokaryotic community. Stratification transition and annual vertical mixing in freshwater lakes are known to affect the prokaryotic community and the interaction between prokaryotes and viruses. By pairing measurements of virome analysis and prokaryotic production of a 1-year survey of the depths of surface and deep layers, we revealed (i) the prokaryotic infection pairs associated with prokaryotic production and (ii) the reset in prokaryotic and viral communities through annual vertical mixing in a freshwater lake. Our results provide a basis for future work into changes in stratification that may impact the biogeochemical cycling in freshwater lakes.

Metagenome sequencing and recovery of 444 metagenome-assembled genomes from the biofloc aquaculture system

Biofloc technology is increasingly recognised as a sustainable aquaculture method. In this technique, bioflocs are generated as microbial aggregates that play pivotal roles in assimilating toxic nitrogenous substances, thereby ensuring high water quality. Despite the crucial roles of the floc-associated bacterial (FAB) community in pathogen control and animal health, earlier microbiota studies have primarily relied on the metataxonomic approaches. Here, we employed shotgun sequencing on eight biofloc metagenomes from a commercial aquaculture system. This resulted in the generation of 106.6 Gbp, and the reconstruction of 444 metagenome-assembled genomes (MAGs). Among the recovered MAGs, 230 were high-quality (≥90% completeness, ≤5% contamination), and 214 were medium-quality (≥50% completeness, ≤10% contamination). Phylogenetic analysis unveiled Rhodobacteraceae as dominant members of the FAB community. The reported metagenomes and MAGs are crucial for elucidating the roles of diverse microorganisms and their functional genes in key processes such as nitrification, denitrification, and remineralization. This study will contribute to scientific understanding of phylogenetic diversity and metabolic capabilities of microbial taxa in aquaculture environments.

Genomic Analysis and Taxonomic Characterization of Seven Bacteriophage Genomes Metagenomic-Assembled from the Dishui Lake

Viruses in aquatic ecosystems exhibit remarkable abundance and diversity. However, scattered studies have been conducted to mine uncultured viruses and identify them taxonomically in lake water. Here, whole genomes (29-173 kbp) of seven uncultured dsDNA bacteriophages were discovered in Dishui Lake, the largest artificial lake in Shanghai. We analyzed their genomic signatures and found a series of viral auxiliary metabolic genes closely associated with protein synthesis and host metabolism. Dishui Lake phages shared more genes with uncultivated environmental viruses than with reference viruses based on the gene-sharing network classification. Phylogeny of proteomes and comparative genomics delineated three new genera within two known viral families of Kyanoviridae and Autographiviridae, and four new families in Caudoviricetes for these seven novel phages. Their potential hosts appeared to be from the dominant bacterial phyla in Dishui Lake. Altogether, our study provides initial insights into the composition and diversity of bacteriophage communities in Dishui Lake, contributing valuable knowledge to the ongoing research on the roles played by viruses in freshwater ecosystems.

The Viral Fraction Metatranscriptomes of Lake Baikal

This article characterises viral fraction metatranscriptomes (smaller than 0.2 µm) from the pelagic zone of oligotrophic Lake Baikal (Russia). The study revealed the dominance of transcripts of DNA viruses: bacteriophages and algal viruses. We identified transcripts similar to Pithovirus sibericum, a nucleocytoplasmic large DNA virus (NCLDV) isolated from the permafrost region of Eastern Siberia. Among the families detected were RNA viruses assigned to Retroviridae, Metaviridae, Potyviridae, Astroviridae, and Closteroviridae. Using the PHROG, SEED subsystems databases, and the VOGDB, we indicated that the bulk of transcripts belong to the functional replication of viruses. In a comparative unweighted pair group method with arithmetic mean (UPGMA) analysis, the transcripts from Lake Baikal formed a separate cluster included in the clade with transcripts from other freshwater lakes, as well as marine and oceanic waters, while there was no separation based on the trophic state of the water bodies, the size of the plankton fraction, or salinity.

Viral diversity and biogeochemical potential revealed in different prawn-culture sediments by virus-enriched metagenome analysis

As the most numerous biological entities on Earth, viruses affect the microbial dynamics, metabolism and biogeochemical cycles in the aquatic ecosystems. Viral diversity and functions in ocean have been relatively well studied, but our understanding of viruses in mariculture systems is limited. To fill this knowledge gap, we studied viral diversity and potential biogeochemical impacts of sediments from four different prawn-mariculture ecosystems (mono-culture of prawn and poly-culture of prawn with jellyfish, sea cucumber, and clam) using a metagenomic approach with prior virus-like particles (VLPs) separation. We found that the order Caudovirales was the predominant viral category and accounted for the most volume (78.39% of classified viruses). Sediment viruses were verified to have a high diversity by using the construct phylogenetic tree of terL gene, with three potential novel clades being identified. Meanwhile, compared with viruses inhabiting other ecosystems based on gene-sharing network, our results revealed that mariculture sediments harbored considerable unexplored viral diversity and that maricultural species were potentially important drivers of the viral community structure. Notably, viral auxiliary metabolic genes were identified and suggested that viruses influence carbon and sulfur cycling, as well as cofactors/vitamins and amino acid metabolism, which indirectly participate in biogeochemical cycling. Overall, our findings revealed the genomic diversity and ecological function of viral communities in prawn mariculture sediments, and suggested the role of viruses in microbial ecology and biogeochemistry.

Accurate identification of bacteriophages from metagenomic data using Transformer

Motivation

Bacteriophages are viruses infecting bacteria. Being key players in microbial communities, they can regulate the composition/function of microbiome by infecting their bacterial hosts and mediating gene transfer. Recently, metagenomic sequencing, which can sequence all genetic materials from various microbiome, has become a popular means for new phage discovery. However, accurate and comprehensive detection of phages from the metagenomic data remains difficult. High diversity/abundance, and limited reference genomes pose major challenges for recruiting phage fragments from metagenomic data. Existing alignment-based or learning-based models have either low recall or precision on metagenomic data.

Results

In this work, we adopt the state-of-the-art language model, Transformer, to conduct contextual embedding for phage contigs. By constructing a protein-cluster vocabulary, we can feed both the protein composition and the proteins’ positions from each contig into the Transformer. The Transformer can learn the protein organization and associations using the self-attention mechanism and predicts the label for test contigs. We rigorously tested our developed tool named PhaMer on multiple datasets with increasing difficulty, including quality RefSeq genomes, short contigs, simulated metagenomic data, mock metagenomic data and the public IMG/VR dataset. All the experimental results show that PhaMer outperforms the state-of-the-art tools. In the real metagenomic data experiment, PhaMer improves the F1-score of phage detection by 27%.

Bacteriophage classification for assembled contigs using graph convolutional network

Motivation

Bacteriophages (aka phages), which mainly infect bacteria, play key roles in the biology of microbes. As the most abundant biological entities on the planet, the number of discovered phages is only the tip of the iceberg. Recently, many new phages have been revealed using high-throughput sequencing, particularly metagenomic sequencing. Compared to the fast accumulation of phage-like sequences, there is a serious lag in taxonomic classification of phages. High diversity, abundance and limited known phages pose great challenges for taxonomic analysis. In particular, alignment-based tools have difficulty in classifying fast accumulating contigs assembled from metagenomic data.

Results

In this work, we present a novel semi-supervised learning model, named PhaGCN, to conduct taxonomic classification for phage contigs. In this learning model, we construct a knowledge graph by combining the DNA sequence features learned by convolutional neural network and protein sequence similarity gained from gene-sharing network. Then we apply graph convolutional network to utilize both the labeled and unlabeled samples in training to enhance the learning ability. We tested PhaGCN on both simulated and real sequencing data. The results clearly show that our method competes favorably against available phage classification tools.

Availability and implementation

The source code of PhaGCN is available via: https://github.com/KennthShang/PhaGCN.

Viral footprints across Gulfs of Kathiawar Peninsula and Arabian Sea: Unraveled from pelagic sediment metagenomic data

Marine biosphere is one of the largest, diverse and dynamic system hosting numerous of microorganisms. Viruses being the most abundant under explored lifeforms in ocean, represent a reservoir of great genetic diversity. We report the metagenomic insights on the viral communities in the deep sediments of the two Gulfs of Gujarat i.e. Gulf of Khambhat and Gulf of Kutch, with one sample from Arabian Sea, treated as open sea control. The viral reads were filtered from the whole dataset, assembled and studied for viral diversity, which was visualized by Pavian. The sequences were checked for the viral abundance, diversity and functionality. The resulting viral taxonomic classification contained 6 orders, 8 families and 47 genera. The results revealed that the phages infecting Cyanobacterium, Bacillus and Vibrio dominated the sediments. Further, it was observed that majority of viral sequences belonged to double-stranded DNA phages. The present study attempts to provide a primary insight of the viral signals and potential genetic content in the Gulfs of Kathiawar.

Comparison of ultrafiltration and iron chloride flocculation in the preparation of aquatic viromes from contrasting sample types

Viral metagenomes (viromes) are a valuable untargeted tool for studying viral diversity and the central roles viruses play in host disease, ecology, and evolution. Establishing effective methods to concentrate and purify viral genomes prior to sequencing is essential for high quality viromes. Using virus spike-and-recovery experiments, we stepwise compared two common approaches for virus concentration, ultrafiltration and iron chloride flocculation, across diverse matrices: wastewater influent, wastewater secondary effluent, river water, and seawater. Viral DNA was purified by removing cellular DNA via chloroform cell lysis, filtration, and enzymatic degradation of extra-viral DNA. We found that viral genomes were concentrated 1-2 orders of magnitude more with ultrafiltration than iron chloride flocculation for all matrices and resulted in higher quality DNA suitable for amplification-free and long-read sequencing. Given its widespread use and utility as an inexpensive field method for virome sampling, we nonetheless sought to optimize iron flocculation. We found viruses were best concentrated in seawater with five-fold higher iron concentrations than the standard used, inhibition of DNase activity reduced purification effectiveness, and five-fold more iron was needed to flocculate viruses from freshwater than seawater—critical knowledge for those seeking to apply this broadly used method to freshwater virome samples. Overall, our results demonstrated that ultrafiltration and purification performed better than iron chloride flocculation and purification in the tested matrices. Given that the method performance depended on the solids content and salinity of the samples, we suggest spike-and-recovery experiments be applied when concentrating and purifying sample types that diverge from those tested here.

Occurrence and diversity of viruses associated with cyanobacterial communities in a Brazilian freshwater reservoir

As part of the phytoplankton of marine and freshwater environments around the world, cyanobacteria interact with viruses (cyanophages) that affect their abundance and diversity. Investigations focusing on cyanophages co-occurring with freshwater cyanobacteria are scarce, particularly in Brazil. The aim of this study was to assess the diversity of cyanophages associated with a Microcystis-dominated cyanobacterial bloom in a tropical reservoir. Samples were processed as viral fractions of water and cellular fractions, and temporal fluctuations in the abundance of Ma-LMM01-type cyanophages and their Microcystis hosts were determined by qPCR. We applied shotgun metagenomics to obtain a wider characterization of the cyanophage community. During the study period, Microcystis gene copies were quantified in all cellular fractions, and the copy number of the Ma-LMM01 phage gene tended to increase with host abundance. Metagenomic analysis demonstrated that Caudovirales was the major viral order associated with the cyanophage families Myoviridae (34-88%), Podoviridae (3-42%), and Siphoviridae (6-23%). The metagenomic analysis results confirmed the presence of Microcystis cyanophages in both viral and cellular fractions and demonstrated a high relative abundance of picocyanobacteria-related viruses and Prochlorococcus (36-52%) and Synechococcus (37-50%) phages. For other main cyanobacterial genera, no related cyanophages were identified, which was probably due to the scarce representation of cyanophage sequences in databanks. Thus, the studied reservoir hosted a diverse cyanophage community with a remarkable contribution of phages related to picoplanktonic cyanobacteria. These results provide insights that motivate future sequencing efforts to assess cyanophage diversity and recover complete genomes.

Metaviromics coupled with phage-host identification to open the viral 'black box'

Viruses are found in almost all biomes on Earth, with bacteriophages (phages) accounting for the majority of viral particles in most ecosystems. Phages have been isolated from natural environments using the plaque assay and liquid medium-based dilution culturing. However, phage cultivation is restricted by the current limitations in the number of culturable bacterial strains. Unlike prokaryotes, which possess universally conserved 16S rRNA genes, phages lack universal marker genes for viral taxonomy, thus restricting cultureindependent analyses of viral diversity. To circumvent these limitations, shotgun viral metagenome sequencing (i.e., metaviromics) has been developed to enable the extensive sequencing of a variety of viral particles present in the environment and is now widely used. Using metaviromics, numerous studies on viral communities have been conducted in oceans, lakes, rivers, and soils, resulting in many novel phage sequences. Furthermore, auxiliary metabolic genes such as ammonic monooxygenase C and β-lactamase have been discovered in viral contigs assembled from viral metagenomes. Current attempts to identify putative bacterial hosts of viral metagenome sequences based on sequence homology have been limited due to viral sequence variations. Therefore, culture-independent approaches have been developed to predict bacterial hosts using single-cell genomics and fluorescentlabeling. This review focuses on recent viral metagenome studies conducted in natural environments, especially in aquatic ecosystems, and their contributions to phage ecology. Here, we concluded that although metaviromics is a key tool for the study of viral ecology, this approach must be supplemented with phage-host identification, which in turn requires the cultivation of phage-bacteria systems.