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Journal of Advanced Research logoLink to Journal of Advanced Research
. 2023 Apr 17;57:107–117. doi: 10.1016/j.jare.2023.04.009

Environmental viromes reveal the global distribution signatures of deep-sea DNA viruses

Tianliang He a,b, Min Jin c, Pei Cui a, Xumei Sun a, Xuebao He c, Yaqin Huang c, Xi Xiao d, Tingting Zhang d, Xiaobo Zhang a,⁎
PMCID: PMC10918349  PMID: 37075861

Graphical abstract

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Keywords: Deep-sea sediment, Viral community, Ecosystem, Virus-encoded gene

Highlights

  • •

    The environmental virome dataset of global deep-sea sediments identified 347,737 viruses.

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    Most deep-sea viruses were unclassified, indicating that deep sea was a reservoir of novel viruses.

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    A total of 98,581 complete viral genomes were obtained, expanding our understanding of viruses.

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    Environment drove the differentiation of viral communities in deep-sea ecosystems.

Abstract

Introduction

Viruses are abundant and ecologically significant in marine ecosystems. However, the virome of deep-sea sediments is not extensively investigated.

Objectives

To explore the distribution pattern of deep-sea viruses on a global scale, the viromes of DNA viruses isolated from 138 sediments of 5 deep-sea ecosystems were characterized.

Methods

The viral particles were purified from each sediment sample. Then the viral DNAs were extracted and subjected to viral metagenomic analysis.

Results

Here, we constructed a global deep-sea environmental virome dataset by analyzing the viral DNA of 138 sediment samples. A total of 347,737 viral operational taxonomic units (vOTUs) were identified, of which 84.94% were hitherto unknown, indicating that deep sea was a reservoir of novel DNA viruses. Furthermore, circular viral genome analysis revealed 98,581 complete genomes. The classified vOTUs included eukaryotic (44.55%) and prokaryotic (25.75%) viruses, and were taxonomically assigned to 63 viral families. The composition and abundance of the deep-sea sediment viromes were dependent on the deep-sea ecosystem as opposed to geographical region. Further analysis revealed that the viral community differentiation in different deep-sea ecosystems was driven by the virus-mediated energy metabolism.

Conclusion

Our findings showed that deep-sea ecosystems are a reservoir of novel DNA viruses and the viral community is shaped by the environmental characteristics of deep-sea ecosystems, thus presenting critical information for determining the ecological significance of viruses in global deep-sea ecosystems.

Introduction

The deep-sea region is the largest extreme ecosystem on the earth, and occupies around 65 % of the surface area [1]. The first benthic organism was discovered in 1864 in the Baffin Bay at a depth of 1800 m, and numerous explorations since then have revealed an extremely diverse benthic ecosystem [1]. The deep-sea ecosystem is a major part of global biomass and biogeochemical cycles. However, the challenges in deep-sea exploration, especially deep-sea sediments, make it one of the least understood ecological regions on the earth [2]. Viruses are the most abundant marine biological entities, and exhibit considerable diversity and ecological functions [3]. However, the marine viral community structure has not been analyzed in detail [4] due to the technical challenges in culturing marine viruses and the absence of a universally conserved marker gene [5]. In recent years, several sea and ocean viromes have been identified and characterized via high-throughput sequencing [5], [6], [7]. As early as 2006, a viral metagenomic analysis of four major oceanic regions showed that more than 90 % of the viral sequences lacked homology with the previously identified virus sequences, indicating a highly diverse viruses in oceans [8]. Furthermore, the Tara Oceans Viromes (TOV) dataset has identified 5,476 viral populations in surface ocean, of which only 39 were previously identified [9]. Roux et al further augmented the TOV dataset to generate the Global Oceans Viromes (GOV) dataset, which included 15,222 epipelagic and mesopelagic viral populations [10]. Recently, the GOV 2.0 dataset has been expanded to 195,728 viral populations, which not only confirms the higher diversity of marine viruses, but also reveals that the patterns and drivers of viral diversity are positively correlated to geographical factors [11]. Although these metagenomic studies have considerably expanded the current knowledge of marine viral community and ecological functions, the deep-sea virome is largely unexplored.

Electron microscopic analyses of deep-sea sediment samples have revealed virus-like particles with considerable variation in shape and size [12]. The viral particles in the sediments are active, and Inoviridae is the dominant viral population [13]. The most abundant viral populations in the Black Sea, Mediterranean Sea, Arctic Ocean and Northeast Atlantic Ocean are Siphoviridae, Myoviridae and Podoviridae and the virus-associated sequences account for 2 %-54 % of the annotated reads [14], indicating substantial diversity among deep-sea viruses. The viral abundance in deep-sea waters is high at 0.6–60 × 108 viral particles/L, although it is at least one order of magnitude less than that in surface waters [15], [16], [17]. In the deep-sea sediment of the Western Mediterranean, the viral abundance ranges from 7.51 × 108 to 1.08 × 109 viruses/g sediment, which is 3 to 6.1 times higher than that of prokaryotes abundance [18]. The abundant deep-sea viruses can regulate the microbial host metabolism and community structures [6], [10], indicating their ecological significance. The viral genes function as “metabolic compensation genes” by inducing formation of branched metabolic pathways in the host cells, which enable their hosts to adapt to the environmental fluctuations [6]. Although some deep-sea viruses have been characterized, the viral communities across global deep-sea environments have not been explored so far. In addition, since the viral communities in ocean waters are affected by currents, they are not accurately representative of their deep-sea counterparts.

To explore the diversity and distribution signature of deep-sea viruses on a global scale, the viromes of DNA viruses of 138 deep-sea sediment samples collected from 5 deep-sea ecosystems were characterized in this study. The results indicated that the deep sea was a reservoir of novel DNA viruses and that the differentiation of viral communities depended on deep-sea ecosystems. Our study provided the critical information for exploring the functions of viruses in the global deep-sea ecosystems for the first time.

Materials and methods

Sample collection

The deep-sea sediment samples were collected during the cruises of Dayang No. 1 survey of China from 2010 to 2018. The sampling stations were located in five deep-sea environments including cold seeps, hadal trenches, hydrothermal vents, mid-ocean ridges and ocean basins from the Pacific Ocean, the Atlantic Ocean and the Indian Ocean. The detailed information on sampling stations is listed in Supplementary Table 1. The sampling methods were described in our previous study [19]. All samples were kept at −20 °C until further treatments in the laboratory.

Isolation of virions and viral DNA extraction

The isolation of viruses and viral DNA extraction were performed as described previously [6]. Each (20 g) of sediment samples was resuspended with 20 mL ultra-pure water to isolate the free viral particles and viruses adhering to sediment particles. After incubation for 30 min, the sample was centrifuged at 500 × g for 20 min at 4 °C to collect the supernatants. The precipitate was resuspended using 20 ml ultra-pure water, incubated and then centrifuged to collect the supernatants. These steps for each sample were replicated three times. All collected supernatants were filtered through 0.22-μm-pore-sized filters, followed by PEG6000 flocculation and ultracentrifugation at 50,000 × g for 2 h to concentrate viral particles. The virus pellet was further treated with DNase. The treatment of DNase is effective for purifying marine viral particles [20]. The purified virions from some sediments, selected at random, were observed using transmission electron microscopy (TEM). Subsequently the viral DNAs were extracted according to our previous protocol [6]. In brief, 100 μL of purified viral suspension was added with 900 μL TE buffer (10 mM Tris-HCl, 1 mM EDTA, pH 8.0), followed by incubation at 37 °C for 30 min. Subsequently, 40 μL of 10 % SDS and 8 μL of 10 mg/mL proteinase K were added to the mixture and incubated at 55 °C for 1 h. The mixture was added with 100 μL of 5 M NaCl and 100 μL of a CTAB solution (100 g/L CTAB, 2.4 M NaCl), followed by incubation at 65 °C for 10 min. The mixture was then chilled on ice and subjected to phenol–chloroform-isoamyl alcohol (25:24:1, pH 7.8) extraction. The aqueous layer was mixed with an equal volume of isopropyl alcohol to precipitate viral DNA. The precipitated DNA was washed with 70 % ethanol, vacuum dried, and dissolved in 10 μL of nuclease-free water.

Sequencing of viral metagenome

To facilitate the sequencing of viral metagenome, the extracted viral DNA was isothermally amplified using the GenomiPhi V2 DNA amplification kit according to the manufacturer’s instructions (GE Healthcare Life Science, Buckinghamshire, UK). This method has been widely used for the whole genome amplification of viral metagenomes [5], [6], [21], [22]. To avoid bias, the whole genome amplification of viral DNA of each sample was repeated three times and then pooled together. Our previous study demonstrated that the viral genome amplification didn’t cause bias of the viral metagenome sequencing [6]. To exclude the microbial contamination, the isothermally amplified products were subjected to the detection of bacterial 16S rDNA using PCR with the universal bacterial primer [6].

After purification and quantification, the viral DNA was used to construct a paired-end library with an insert size of 400 bp. The library construction was performed according to our previous methods [6]. The paired-end sequencing (2 × 250 bp) was carried out on an Illumina HiSeq 2500 system (Illumina Inc., SanDiego, CA, USA). All sequencing work was conducted in collaboration with Mingke Biotechnology Co., ltd. (Hangzhou, China).

Contig assembly and identification of viral contigs

The reads were trimmed using Trimmomatic v0.33 [23], and individually assembled using metaSPAdes 3.12.0 [24]. All the assembled contigs with a length more than 1500 bp were subjected to the identification of viral contigs using VirSorter [25], VirFinder [26] and VIBRANT [27], respectively. The viral contigs were matched the reported standards [11]. The remaining contigs were further identified using CAT [28] to screen for the viral contigs matched the reported standards [11]. Finally, all the viral contigs identified by four methods were pooled together and the duplications were removed. CheckV v7.0 pipeline was used to estimate the genome completeness of viral contigs [29].

Classification of viral operational taxonomic units

The viral contigs were piped through the nucmer pipeline of MUMmer 4.0 to identify viral operational taxonomic units (vOTUs) [30]. The viral contigs were classified into vOTUs if they shared ≥ 95 % mummer-based average nucleotide identity across ≥ 80 % of the length of the shortest sequence [11].

Viral taxonomy identification and host assignment

The open reading frames (ORFs) of each vOTU were predicted by Prodigal [31]. The amino acid sequences of ORFs were used to identify viral taxonomy of vOTUs using vConTACT2 [32] and blastp [33]. For the vConTACT2 analysis, the vOTU greater than 15 kb were clustered against viral genomes of viral RefSeq database (release 201) [34]. The remaining vOTUs and the vOUTs that could not be assigned into viral taxonomy by vConTACT2 were subjected to blastp [11]. If the blastp bit score of a vOTU was ≥ 50 to a known virus at a single hit and greater than 50 % ORFs were aligned to that kind of virus, the vOTU was assigned to the viral family of the known virus.

The hosts of the vOTUs with known taxonomy were collected from the host annotation of viral Refseq database.

Circle vOTUs identification

The circle vOTUs were identified by Cenote-Taker (https://github.com/mtisza1/ Cenote-Taker) [35]. This method was based on the overlapping ends of vOTU to identify the circular vOTUs.

Calculation of the relative abundance of vOTUs based on reads

The reads from each sample were mapped to vOTUs using bowtie2 v2.4.4 [36]. The reads that mapped less than 95 % nucleotide identity to the vOTU were removed using BamM v1.7.3 (https://github.com/ecogenomics/BamM). Subsequently the RPKM (reads per kilobase per million mapped reads) values were calculated by CoverM v0.3.1 (https:// github.com/wwood/ CoverM)[37].

Analysis of viral diversity

Based on the relative abundance of each vOTU, the Shannon index, Simpson index, Chao index and Ace index were calculated using vegan in R [38]. GraphPad Prism 7.0 was used to generate the boxplots of the four indices.

Principal coordinate analysis (PCoA) was used to reveal viral β diversity by vegan package in R [38]. The sample ordination was conducted using the Bray-Curtis dissimilarity matrices which generated from total reads of global deep-sea sediment viromes by the function vegdist (method = bray) after a cube root transformation by function nthroot (n = 3) [11].

Protein clustering and comparison of deep-sea vOTUs

The ORFs predicted from deep-sea vOTUs were annotated by the KEGG [39], UniProt [40], InterPro [41] and Pfams [42] protein databases, respectively. The e-value threshold was less than 10−5. All the annotated viral proteins were pooled together and the duplications were removed. The viral proteins with ≥ 60 % identity and ≥ 80 % coverage were clustered into a protein cluster using CD-HIT [43]. The protein clusters were compared against the IMG/VR v3 and NCBI Refseq Virus databases using DIAMOND (e-value ≤ 10-5, identity ≥ 30 % and coverage ≥ 50 %) [34].

Phylogenetic analysis of circular viral genomes

To perform the phylogenetic analysis of circular viral genomes (CVGs), the amino acid sequences of the predicted replication protein (Rep) of deep-sea CVGs were aligned with those of the homologous genes in NCBI nr database using the MUSCLE algorithm (v3.8) [44]. FastTree [45] was used to construct the maximum-likelihood phylogenetic tree with JTT matrix-based model and 1,000 bootstrap replicates.

Results

The global deep-sea sediment viromes

A total of 138 deep-sea sediment samples were collected during the 7 cruises of Dayang No. 1 survey of China from 2010 to 2018, the cruises that traveled more than 3.2 million km [46] (Fig. 1A and Table S1). The sampling depth ranged from 451 to 6,796 m with an average of 3,413 m (Table S1). Sediment samples were collected from hydrothermal vents (n = 83), cold seeps (n = 8), ocean basins (n = 21), hadal trenches (n = 14) and mid-ocean ridges (n = 12) in the Pacific Ocean, Atlantic Ocean and Indian Ocean, which encompass the typical deep-sea environments. The highest number of samples was retrieved from hydrothermal vents due to their ubiquitous presence in the deep seas.

Fig. 1.

Fig. 1

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The global deep-sea sediment viromes. (A) The geographical location of sampling stations. Red dotted circles show the regional distribution of the 138 sediment samples, and the number of samples in each regional cluster is indicated. (B) Transmission electron microscope observation of the viruses purified from 138 deep-sea sediments. The representative images are indicated. Scale bar, 100 nm. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

To characterize the global deep-sea viromes of DNA viruses, the viral particles were purified from each of 138 sediment samples and treated with nuclease, followed by the extraction of viral genomic DNAs and sequencing as reported in our previous study [6]. The TEM results showed that the purified particles shared the typical morphology of virions, indicating that the viruses were successfully purified from the deep-sea sediments (Fig. 1B) and the extracted DNAs were not contaminated with bacteria (Fig S1). To minimize sequencing errors, we performed a 2 × 250 bp pair-end sequencing for the viral metagenomic DNA. Each sample generated more than 5.79 Gb of clean data (Table S1), and the total sequencing data of the 138 samples amounted to 800.08 Gb, which included 3,680,671,980 completely sequenced reads.

Viral community structure of global deep-sea sediment virome

The deep-sea virome of DNA viruses was obtained by assembling the sequence reads of all samples, which yielded 2,614,763 contigs. At present, the known smallest viral genome is 1.7 kb of human hepatitis D virus [47]. After removal of short sequences, 786,207 contigs (≥1.5 kb) were identified (Fig. 2A and Table S2), and further classified using VirSorter, VirFinder, VIBRANT and CAT into 375,996 viral contigs across 138 samples (Fig. 2A and Table S2) (The National Omics Data Encyclopedia database accession number OEP002479). Based on CheckV analysis, 5.89 % of the viral contigs were complete genomes, 1.97 % high-quality genomes, 6.54 % medium-quality genomes and 12.39 % low-quality genomes, and the remaining 73.21 % were undetermined (Fig. 2A), suggesting that our data did not contain potential host’s genomic contamination. The 375,996 viral contigs were assigned into 347,737 vOTUs (Fig. 2A and Table S2), which represent more than 347,000 viruses compared to only 10,423 known viruses in the NCBI RefSeq database. Furthermore, 7 vOTUs were identified as known viruses at the family level by vConTACT2 using the RefSeq database, while 52,355 vOTUs were identified as known viruses by blastp (Fig. 2B and Table S3). Overall, 15.06 % (52,362) of all vOTUs matched with the reference viral genome sequences (Fig. 2B and Table S3), indicating that the deep-sea sediment is a reservoir of novel viruses. The known vOTUs were classified into 63 families (Fig. 2C and Table S3), which is 6.3-fold higher than the known viral families in GOV 2.0 [11], indicating higher virus diversity in deep-sea sediments compared to ocean water.

Fig. 2.

Fig. 2

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Viral community structure of global deep-sea sediment virome. (A) The identification workflow of viral operational taxonomic units (vOTUs). A total of 3,461,346,355 sequencing reads from the 138 deep-sea sediments were assembled into 786,207 contigs (≥1.5 kb), which were further classified into 375,996 viral contigs by four methods. The viral contigs were clustered into 347,737 vOTUs based on nucmer analysis. (B) The relative proportion of unknown or known vOTU in the entire dataset. (C) The abundance of the assigned viral families for the classified vOTUs. The “Others” included 42 viral families with relative abundance less than 0.1 % of all known vOTUs. (D) The number of host affiliations for the classified vOTUs at the domain level.

The unclassified group “norank” accounted for 23.74 % of all known vOTUs. Circoviridae, Siphoviridae, Microviridae, Myoviridae, Phycodnaviridae, Podoviridae and Fuselloviridae were the most abundant viral families that respectively accounted for 37.32 %, 10.73 %, 9.80 %, 7.47 %, 3.16 %, 1.68 % and 1.06 % of all known vOTUs (Fig. 2C). The remaining 55 viral families with less than 1 % abundance accounted for 5.04 % of all known vOTUs (Fig. 2C).

In addition, 25.75 % of the classified vOTUs were prokaryotic and 44.55 % were eukaryotic (Fig. 2D and Table S3). There were 9.02 % environmental viruses. However, the hosts of 20.68 % of the classified vOTUs were not identified. Among the known prokaryotic viruses, bacterial and archaeal viruses accounted for 1.9 % and 23.85 %, respectively (Fig. 2D and Table S3).

Taken together, the viral diversity and abundance in deep-sea sediments are higher than that in seawater, and the former harbors novel viruses.

Viruses with complete circular genomes in the global deep-sea sediment virome

To further characterize the composition of viral community in deep sea, the Cenote-Taker2 Pipeline [35] was used to identify the circular viral genomes (CVGs) which could represent the viruses with complete genomes. A total of 98,581 CVGs longer than 1.5 kb were obtained, which represented 98,581 complete viral genomes. Of these, 754 CVGs were longer than 10 kb (Fig. 3A and Table S4). The largest CVG was 309,885 bp and the smallest was 1,500 bp. Only 22,490 CVGs matched with the genomic sequences of known viruses, suggesting that most CVGs were unidentified viruses (Fig. 3B and Table S4) that could significantly expand the global database of 10,423 documented viruses with complete genomes. The classified CVGs were assigned into 35 families (Fig. 3C and Table S4). Circoviridae was the most dominant family with 13,014 known CVGs, followed by Phycodnaviridae (593 CVGs) and Microviridae (525 CVGs) (Fig. 3C and Table S4).

Fig. 3.

Fig. 3

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Viruses with complete circular genomes in the global deep-sea sediment virome. (A) The size and number of viruses with circular viral genomes (CVGs). (B) The proportion of the known and unidentified CVGs in the entire dataset. (C) The abundance of the known viruses with complete CVGs at family level. “Others” represented the viral family with less than 10 CVGs. (D-F) The phylogenetic tree of viral Rep sequences of CVGs classified into Circoviridae, Microviridae and Phycodnaviridae.

To further explore the variations in the deep-sea sediment viral communities, the conserved viral replication protein (Rep) genes was selected to analyze viral phylogenetic evolution of CVGs classified into the top 3 abundant viral families (Circoviridae, Microviridae and Phycodnaviridae). Phylogenetic analysis showed that 680 viral Rep (vRep) sequences of Circoviridae were classified into three clades (I, II and III), of which 676 vRep sequences were clustered with the reference sequences (rRep) in NCBI nr database into Clade III, and 4 vRep sequences with two clades without any rRep sequences (Clade I and II) (Fig. 3D). 8 vRep sequences of Microviridae were independently clustered into Clade I (Fig. 3E), and 179 vRep sequences of Phycodnaviridae into Clade I and II (Fig. 3F). These data indicated that the viral Rep proteins might be encoded by many novel viruses in deep-sea sediments, showing that deep sea is a reservoir of novel viruses.

Influence of deep-sea ecosystems on the differentiation of deep-sea viruses

To further characterize the relationship between deep-sea sediment viral communities and the environmental conditions, we compared the viromes of DNA viruses of oceanic regions and deep-sea ecosystems at the vOTU level. As shown in Fig. 4A, the viral communities in the sediments from three oceanic regions (Pacific Ocean, Atlantic Ocean and Indian Ocean) and five ecosystems (cold seep, hadal trench, hydrothermal vent, mid-ocean ridge and ocean basin) had low similarity. Most vOTUs were unique to each oceanic region and ecosystem (Fig. 4A). A total of 14,132 vOTUs were shared by the three oceanic regions and formed part of the respective core viromes (Fig. 4A and Table S5). However, only 281 core vOTUs were observed in five ecosystems (Fig. 4A and Table S6). Furthermore, 27 of 64 known viral families were present in the sediments from all five deep-sea ecosystems, while 47 were shared by three oceanic regions (Fig. 4B and Table S7). These data indicated that the environmental characteristics of deep-sea regions influence the structure of the sediment viral communities, suggesting the driving role of deep-sea ecosystems in the differentiation of deep-sea DNA viruses.

Fig. 4.

Fig. 4

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Influence of deep-sea ecosystems on the differentiation of deep-sea viruses. (A) The distribution of deep-sea sediment viromes in three oceanic regions or five deep-sea ecosystems. The number indicated the viral operational taxonomic units (vOTUs). (B) The distribution of the known viral families in five ecosystems or three oceanic regions. The number represented the known viral families. (C) The relative abundance of viral families in three oceanic regions and five ecosystems. The viral families with less than 1 % relative abundance were grouped into “Others”. (D) Boxplots showing the diversity index of viral communities of deep-sea sediments in three oceanic regions. The top, medium and bottom part of each box respectively correspond to the highest, average, and lowest diversity index of single viral community. The letter “n” indicates the number of samples in each oceanic region. (E) Virus diversity in the sediments from five deep-sea ecosystems. The letter “n” represents the number of samples in each ecosystem. (F) Principal coordinate analysis (PCoA) of the vOTUs from three oceanic regions. (G) PCoA of the vOTUs from five distinct deep-sea ecosystems.

There were viral families common to the three oceanic regions or five deep-sea ecosystems. Circoviridae, Genomoviridae, Myoviridae and Siphoviridae were the dominant viral families in global deep-sea sediments. However, their relative abundances in the three oceanic regions or five deep-sea ecosystems were significantly different (Fig. 4C). In cold seeps, hydrothermal vents and ocean basins, the most dominant viral family was Circoviridae, accounting for 49.76 %, 34.63 % and 54.03 % of known vOTUs, respectively. In hadal trenches and mid-ocean ridges, the most dominant viral family was Siphoviridae, accounting for 47.93 % and 75.12 %, respectively. These results indicated high internal diversity of viral community (vOTU level) and low external diversity of viral community (viral family level) of global deep-sea viromes, which in turn revealed that the viral communities in deep-sea sediments were dependent on deep-sea ecosystems. The α-diversity index analysis essentially generated the similar results (Fig. 4D, 4E and Table S8). The highest viral diversity was observed in cold seeps (Fig. 4E and Table S8). Consequently, the viral communities in global deep-sea sediments are extremely varied and exhibit environmental variances.

To further evaluate the impact of deep-sea ecosystems on the differentiation of deep-sea viruses, PCoA (principal coordinate analysis) was used to characterize the distribution and diversity of deep-sea viruses in global ocean. The results showed that the vOTUs of all sediment samples were clustered into 3 groups (Fig. 4F and 4G). All vOTUs in the Atlantic Ocean were grouped together, while the vOTUs in the Pacific Ocean and the Indian Ocean were distributed in at least two groups (Fig. 4F). These results suggested that the deep-sea viral community structures had a lower diversity between the three oceanic regions. However, the vOTUs of ocean basins and the partial vOTUs of hydrothermal vents and hadal trenches were grouped together, the vOTUs of cold seeps and mid-ocean ridges were clustered into one group, and the remaining vOTUs of hydrothermal vents comprised a distinct group (Fig. 4G). The differences between the deep-sea sediment viral communities of the three oceanic regions were lower than that of the five deep-sea ecosystems, revealing that the distinctive characteristics of these ecosystems rather than the geographical location influence the viral communities.

Collectively, the deep-sea ecosystems could drive the differentiation of DNA viruses in deep sea.

Roles of viral metabolic genes in the differentiation of deep-sea viruses

To further explore the relationship between viral community differentiation and deep-sea ecosystems, we analyzed the virus-encoded genes from the global deep-sea sediment virome (GDSV). A total of 1,108,370 ORFs were predicted from the vOTUs of GDSV and then annotated with KEGG, Pfam, UniProt and InterProScan databases. A total of 372,823 putative viral proteins were obtained that were clustered into 184,799 protein clusters (Fig. 5A). Compared to the public databases, only 15.6 % (n = 28,832) of the protein clusters in GDSV matched those in NCBI Viral RefSeq database (Fig. 5B). Moreover, 34.2 % (n = 63,195) of the GDSV protein clusters had homologous counterparts in the IMG/VR v3 database (Fig. 5B). Thus, the global deep-sea sediments are enriched with novel viruses.

Fig. 5.

Fig. 5

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Roles of virus-encoded metabolic genes in the differentiation of deep-sea viruses. (A) Flow diagram showing the bioinformatic workflow for protein clustering. (B) Comparison of protein clusters in the global deep-sea sediment virome with those in public virus databases. (C) The distribution of viral protein clusters in three oceanic regions or five deep-sea environments. The number indicated the viral protein clusters. (D) The metabolic pathways involving the putative virus-encoded metabolic genes according to KEGG pathway database. (E) The number of virus-encoded sulfur metabolism genes in five deep-sea ecosystems. A total of 18 virus-encoded sulfur metabolism genes, including sulfate/thiosulfate transport system ATP-binding protein (cysA), adenylylsulfate kinase (cysC), sulfate adenylyltransferase (cysE), serine O-acetyltransferase (cysE), phosphoadenosine phosphosulfate reductase (cysH), sulfite reductase hemoprotein beta-component (cysI), cysteine synthase (cysK), S-sulfo-l-cysteine synthase (cysM), sulfate adenylyltransferase subunit 1 (cysN), bifunctional enzyme (cysNC), sulfate/thiosulfate transport system substrate-binding protein (cysP), 3′(2′), 5′-bisphosphate nucleotidase (cysQ), sulfate/thiosulfate transport system permease protein (cysU and cysW), cystathionine gamma-synthase (metB), O-succinylhomoserine sulfhydrylase (metZ), sulfate adenylyltransferase (sat) and thiosulfate/3-mercaptopyruvate sulfurtransferase (TST), were expressed in deep-sea hydrothermal vents. (F) The relative abundance of virus-encoded sulfur metabolic genes in five deep-sea ecosystems.

Similar to the distribution pattern of vOTUs, the viral community similarity at the protein cluster level was lower between the three oceanic regions or five ecosystems. Only 3,517 core protein clusters were shared by three oceanic regions, while 117 core protein clusters were shared by the different ecosystems (Fig. 5C). These data further underscore the role of deep-sea environmental factors in shaping the viral communities.

To further evaluate the metabolic effect of these viruses on viral community differentiation, we identified the virus-encoded genes that potentially regulate host metabolism during infection. A total of 9,999 putative viral metabolic genes were classified into the “Metabolism” category in the KEGG pathway database and further divided into 12 subgroups, of which “Amino acid metabolism” was most enriched (2,882), followed by “Carbohydrate metabolism” (2,216) and “Nucleotide metabolism” (8 8 3) (Fig. 5D). Therefore, virus-encoded genes may influence the metabolic pathways in their hosts.

Given that sulfur metabolism is crucial for deep-sea ecological stability [11], we further analyzed virus-encoded genes participating in sulfur metabolic pathways. As shown in Fig. 5E, 18 of the 19 sulfur metabolism-associated genes encoded by deep-sea viruses were expressed in deep-sea hydrothermal vents. Moreover, the relative abundance of these sulfur metabolizing genes in the hydrothermal vents was the highest among all 5 deep-sea environments (Fig. 5F). These data were consistent with the high concentration of sulfur in deep-sea hydrothermal vents, indicating that sulfur metabolism is the cornerstone of this ecosystem. Thus, the differentiation of deep-sea viral community is significantly affected by the deep-sea ecosystems, which might be driven by the virus-mediated energy metabolism.

Discussion

The total number of viruses in oceans is estimated to be 1030, which accounts for 90 % of all marine organisms [3], [48]. Viruses participate in matter circulation and energy transfer in marine ecosystems, and therefore may play a key role in climate change [3], [49]. The deep-sea ecosystem has garnered considerable attention in recent years since it is the largest reservoir of organic carbon on earth [50]. Deep-sea viruses not only control prokaryotic mortality, release labile organic matter and compensate for host metabolic pathways, but also contribute substantially to nutrient cycling in the benthic environment [6], [51], [52], [53]. However, the viruses in global deep-sea ecosystems have not been extensively characterized so far. In addition, although many viruses in deep-sea waters have been identified [11], [54], [55], they may not be representative of the deep-sea viral communities due to the influence of ocean currents. Deep-sea sediments harbor more than 2.9 × 1029 active prokaryotic cells, which is nearly half of all prokaryotes in global oceans [50], [56]. Given that viral abundance in deep-sea sediments is positively correlated to that of prokaryotes [57], it is estimated to be at least 10 times higher than that in marine waters [58], [59]. Therefore, the viruses isolated from deep-sea sediments can better reflect the deep-sea viral community. We identified 347,737 vOTUs in the global deep-sea sediment samples, which is nearly 2-fold higher than the 195,728 viruses included in the Global Ocean Virome (GOV) 2.0 dataset [11]. In addition, 98,581 complete circular viral genomes were also identified from these vOTUs. However, 84.94 % of the deep-sea vOTUs did not match with the known viral genomes, indicating that the deep-sea sediment is a reservoir of novel viruses. This finding is further supported by the fact that 90 % of the functional genes of global deep-sea sediment virome cannot be annotated within public databases, including IMG/VR v3 which is by far the largest marine virus database [60].

The relationship between biodiversity and environmental characteristics has been the hotspot of ecological research [11]. Marine bacteria and eukaryotes correlate positively with variations in the niche [61], [62]. The biogeography of viral communities in upper-ocean and mesopelagic ocean are also dependent on the environmental conditions [9], [11]. Our findings demonstrate for the first time that the deep-sea viruses are heterogeneously distributed across five deep-sea ecosystems including cold seeps, hadal trenches, hydrothermal vents, mid-ocean ridges and ocean basins. Only less than 2 % of all vOTUs (281 of 14,132) were widely spread in global deep-sea sediments. The abundance of Circoviridae and Siphoviridae also differed greatly between the different ecosystems. The environmental specificity of viral composition and abundance has also been observed in the sediment samples of deep-sea hydrothermal vents, cold seeps, Black Sea, Atlantic Ocean, Arctic Ocean, Mediterranean Sea and Southwest Indian Ocean [14], [37], [63], [64], suggesting that the viral communities in deep-sea sediments are closely related to environmental characteristics. The specific viral adaptations in each ecological zone are likely the result of environmental selection pressures [9]. Among the 43 viromes currently identified in global oceans, only 24 core viral protein clusters are shared by surface, epipelagic and mesopelagic viromes [9]. The analysis of viral function genes in Arctic, Antarctic, bathypelagic, temperate and tropical epipelagic and mesopelagic zones also revealed that about 10 % of the viral protein clusters appear under positive selection in the specific zone [11]. Consistent with these findings, we also observed the environmental impact on the distribution and abundance of viral genes. Our results showed that only 117 core protein clusters (∼0.06 % of 184,799 viral protein clusters) were shared by the five deep-sea ecosystems, further demonstrating that the deep-sea environmental factors modulate viral communities. The environmental variations between deep-sea cold seep, hadal trench, hydrothermal vent, ocean basin and mid-ocean ridge could profoundly influence the composition, abundance and virus-encoded metabolic genes of viral communities in deep-sea sediments. These findings strongly indicate that deep-sea ecosystems drive the differentiation of viral community in global deep-sea sediments.

Conclusions

In this study, a global deep-sea environmental virome dataset of DNA viruses was constructed, which derived from 138 sediment samples of 5 deep-sea ecosystems of the Pacific Ocean, Atlantic Ocean and Indian Ocean. A total of 347,737 vOTUs were identified, representing more than 347,000 DNA viruses, which was much more than 10,423 known viruses in the viral RefSeq database [34]. Among these vOTUs, 84.94 % vOTUs were unclassified, indicating that deep sea is a reservoir of novel viruses. Furthermore, 98,581 vOTUs with circular complete viral genomes were obtained. The classified vOTUs were taxonomically assigned to 63 viral families, including eukaryotic (44.55 %) and prokaryotic (25.75 %) viruses. Circoviridae, Siphoviridae and Microviridae were the most abundant viral families of all classified vOTUs. The composition and abundance of the deep-sea viromes depended on the deep-sea ecosystems. The deep-sea ecosystems drove the differentiation of deep-sea viral communities. Therefore, our study characterized the global deep-sea virosphere for the first time, extremely expanding our understanding of the viruses in deep-sea ecosystems.

Compliance with Ethics Requirements

This article does not contain any studies with human or animal subjects

CRediT authorship contribution statement

Tianliang He: Conceptualization, Methodology, Data curation, Writing – original draft. Min Jin: Methodology, Investigation. Pei Cui: Methodology, Investigation, Data curation. Xumei Sun: Methodology, Investigation, Validation. Xuebao He: Methodology, Investigation. Yaqin Huang: Methodology, Investigation. Xi Xiao: Methodology, Investigation. Tingting Zhang: Methodology, Investigation. Xiaobo Zhang: Conceptualization, Methodology, Project administration, Writing – review & editing, Funding acquisition.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

Acknowledgements

This work was supported by China Ocean Mineral Resources R & D Association (DY135-B-04) and the National Key Research and Development Program of China (2018YFC0310703).

Availability of data and materials.

The data of viral contigs have been deposited in the National Omics Data Encyclopedia database under accession number OEP002479.

Footnotes

Peer review under responsibility of Cairo University.

Appendix A

Supplementary data to this article can be found online at https://doi.org/10.1016/j.jare.2023.04.009.

Appendix A. Supplementary material

The following are the Supplementary data to this article:

Supplementary data 1
mmc1.docx (199.4KB, docx)
Supplementary data 2
mmc2.xls (43.5KB, xls)
Supplementary data 3
mmc3.xls (33KB, xls)
Supplementary data 4
mmc4.xls (8MB, xls)
Supplementary data 5
mmc5.xlsx (5MB, xlsx)
Supplementary data 6
mmc6.xls (1.4MB, xls)
Supplementary data 7
mmc7.xls (46.5KB, xls)
Supplementary data 8
mmc8.xls (21.5KB, xls)
Supplementary data 9
mmc9.xls (66.5KB, xls)

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary data 1
mmc1.docx (199.4KB, docx)
Supplementary data 2
mmc2.xls (43.5KB, xls)
Supplementary data 3
mmc3.xls (33KB, xls)
Supplementary data 4
mmc4.xls (8MB, xls)
Supplementary data 5
mmc5.xlsx (5MB, xlsx)
Supplementary data 6
mmc6.xls (1.4MB, xls)
Supplementary data 7
mmc7.xls (46.5KB, xls)
Supplementary data 8
mmc8.xls (21.5KB, xls)
Supplementary data 9
mmc9.xls (66.5KB, xls)

Data Availability Statement

The data of viral contigs have been deposited in the National Omics Data Encyclopedia database under accession number OEP002479.

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