Next Article in Journal
Porcine Epidemic Diarrhea Virus Induces Autophagy to Benefit Its Replication
Next Article in Special Issue
Isolation and Characterization of a Shewanella Phage–Host System from the Gut of the Tunicate, Ciona intestinalis
Previous Article in Journal / Special Issue
Schrödinger’s Cheshire Cat: Are Haploid Emiliania huxleyi Cells Resistant to Viral Infection or Not?
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Viruses
Volume 9
Issue 3
10.3390/v9030052
viruses-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Coccolithoviruses: A Review of Cross-Kingdom Genomic Thievery and Metabolic Thuggery

by
Jozef I. Nissimov
1,2,
António Pagarete
3,
Fangrui Ma
4,
Sean Cody
4,
David D. Dunigan
4,
Susan A. Kimmance
1 and
Michael J. Allen
1,*
1
Plymouth Marine Laboratory, Prospect Place, The Hoe, Plymouth PL1 3DH, UK
2
Department of Marine and Coastal Sciences, Rutgers University, New Brunswick, NJ 08901, USA
3
Department of Biology, University of Bergen, Bergen, 7803, Norway
4
Nebraska Center for Virology, University of Nebraska, Lincoln, NE 68583, USA
*
Author to whom correspondence should be addressed.
Viruses 2017, 9(3), 52; https://doi.org/10.3390/v9030052
Submission received: 18 January 2017 / Revised: 13 March 2017 / Accepted: 14 March 2017 / Published: 18 March 2017
(This article belongs to the Special Issue Marine Viruses 2016)
Browse Figures
Versions Notes

Abstract

:
Coccolithoviruses (Phycodnaviridae) infect and lyse the most ubiquitous and successful coccolithophorid in modern oceans, Emiliania huxleyi. So far, the genomes of 13 of these giant lytic viruses (i.e., Emiliania huxleyi viruses—EhVs) have been sequenced, assembled, and annotated. Here, we performed an in-depth comparison of their genomes to try and contextualize the ecological and evolutionary traits of these viruses. The genomes of these EhVs have from 444 to 548 coding sequences (CDSs). Presence/absence analysis of CDSs identified putative genes with particular ecological significance, namely sialidase, phosphate permease, and sphingolipid biosynthesis. The viruses clustered into distinct clades, based on their DNA polymerase gene as well as full genome comparisons. We discuss the use of such clustering and suggest that a gene-by-gene investigation approach may be more useful when the goal is to reveal differences related to functionally important genes. A multi domain “Best BLAST hit” analysis revealed that 84% of the EhV genes have closer similarities to the domain Eukarya. However, 16% of the EhV CDSs were very similar to bacterial genes, contributing to the idea that a significant portion of the gene flow in the planktonic world inter-crosses the domains of life.

1. Introduction

It has been more than 10 years since the complete genome sequencing of a giant double-stranded DNA-containing virus infecting the ubiquitous bloom-forming coccolithophorid species Emiliania huxleyi [1]. Emiliania huxleyi virus strain number 86 (EhV-86) was isolated in 1999 from the English Channel, and a subsequent analysis of its major capsid protein (MCP) and DNA polymerase genes placed it in a new separate genus, Coccolithovirus, within the family Phycodnaviridae [2,3,4]. The Phycodnaviridae comprises other giant viruses that infect algae, such as Chlorella sp. (e.g., PBCV-1), Ectocarpus siliculousus (e.g., EsV-1), Micromonas pusilla (e.g., MpV-SP1), Chrysochromulina brevifilum (e.g., CbV-PW1), and Heterosigma akashiwo (e.g., HaV01) [5,6]. Because of E. huxleyi’s global impact on biogeochemical cycles, the study of this host-virus system is particularly relevant. Interactions between E. huxleyi and EhVs have been investigated both in vivo, through large-scale semi-natural mesocosm experiments and natural E. huxleyi blooms [7,8,9,10,11], and in vitro [12,13,14,15,16], in laboratory experiments designed to elucidate specific aspects of the infection cycle, the infection dynamics and the host cellular response to infection [17].
As a result of these studies, considerable insight has been gained regarding (1) the EhV intein [18] and the expression profile of EhV genes during infection [19,20,21]; (2) the EhV life cycle, including its utilization of lipid rafts for budding from the host cells [22,23]; (3) host cellular processes in response to infection such as autophagy and the induction of programmed cell death (PCD) pathways [17,24,25,26,27]; (4) the manipulation of fatty acid and lipid metabolism within infected cells, leading to the production of virus-induced lipids crucial for the progression of the infection [10,28,29,30,31]; (5) vector transmission of EhVs in the natural environment via aerosols and zooplankton faecal pellets [32,33]; and (6) the co-occurring diversity of EhVs and their viruses in a range of habitats, including the Atlantic Ocean, Norwegian Fjords and coastal regions of the Black Sea [8,34,35,36,37,38]. Perhaps the most astonishing finding to date was the identification of a de novo sphingolipid biosynthesis pathway in the EhV genome [1,9,39], encoding virus-derived glycosphingolipids (vGSLs) that are crucial regulators of infection [28]. Thus, important parts of the metabolic activity in the planktonic realm (in this case lipid production) are viral-driven [40]. It has been proposed that this pathway is a result of horizontal gene transfer (HGT) between E. huxleyi and their coccolithoviruses [1,9,39]. Similar HGT events with far-reaching ecological relevance and consequences have been reported between other marine viruses and their hosts. These include photosynthesis-related genes such as photosystem II core reaction center protein D1 and a high-light-inducible protein in Prochlorococcus phages [41], as well as phosphate transporter genes (e.g., pho4 and phoH) in viruses infecting Bathycoccus, Micromonas and Ostreococcus [42].
Since the sequencing of the EhV-86 genome, an additional 12 EhV strains have been isolated and their genomes sequenced [43,44,45,46,47,48,49]. This makes EhVs one of the largest collections of Phycodnaviridae viruses in culture with complete or near-complete genome sequences available. In this study, we conduct an in-depth comparison of these EhV genomes for the first time and consider the functional and ecological significance of variation observed between strains. Further, we investigate potential evolutionary links between these viruses and the other domains of life, in particular bacteria which co-occur with EhVs in the marine environment. Bacteria are important constituents of microbial food webs in marine habitats [50,51] and may themselves act as pathogens. As an example of the latter, certain bacteria have been found to induce caspase-like activity and cell death in E. huxleyi [52]. Diseases of macroalgae in coastal habitats have also been attributed to bacteria [53], which likely coexist with a diverse viral community [54]. Interestingly, bacterial-like genes have been reported in several Phycodnaviruses. For example, 48 to 57 bacterial-like genes were identified in three viruses of Chlorella, and 81% of the total bacterial-like genes identified in Mimivirus have no homologs in even distantly related eukaryotes [55,56]. The possibility that EhVs may also have acquired genes from marine microbes (other than their host) via HGT will be explored.

2. Methods

2.1. Coccolithoviruses and Their Phylogeny

The genomes of 13 EhV strains were retrieved from National Center for Biotechnology Information (NCBI) (Table 1). One genome (EhV-86) is complete. The remaining twelve are near-complete draft genomes which contain gaps between some of the contigs (see Section 3.3). A 14th genome (EhV-163) was not included in this analysis to avoid biases due to its incomplete sequence (80%) [43]. CLUSTALW multiple sequence alignment of two EhV genes, DNA polymerase and serine palmitoyltransferase (2921 and 2604 bp long, respectively), and subsequent phylogenetic analysis was conducted using MEGA6 [57]. The evolutionary history of these sequences was inferred using two independent methods: Neighbor-Joining and Maximum Likelihood [58].

2.2. Whole Genome Reconstruction, Alignment and Comparison

Annotated EhV genomes [1,44,45,46,47,48,49] were used to build genomic alignments. Prior to analysis, the gaps between the assembled annotated contigs of each draft genome were made the same length by adding a known length of ambiguous nucleotides (i.e., a series of 10 Ns). The Artemis Comparison Tool (ACT) was then used for BLASTn pairwise alignment and visualization of the draft genome sequences against the fully assembled non-gapped reference genome of EhV-86 [59]. This enabled identification of the most likely orientation and placement of contigs (note that inversions are common in virus genomes and it is possible that inversions represent a real difference between the genomes). Misplaced contigs were placed in their appropriate location and converted into the correct orientation manually. Subsequently, MAUVE 2.0, a program for the identification of conserved genomic DNA regions and rearrangements, was used to elucidate the variable regions of each genome [60] in relation to EhV-86. Additional gene prediction analysis and functional annotations were performed within the publically available online Integrated Microbial Genomes—Expert Review platform (IMG/ER; [61]). Pairwise average nucleotide identity between each pair of genomes was also performed in this platform using Average Nucleotide Identity (ANI) analysis [62,63]. Briefly, ANI was used to compare all protein coding genes within each EhV genome to the non-gapped reference genome of EhV-86 (Table 2). Only bidirectional best hits (BBHs) with >70% sequence identity over >70% of the length of the shorter sequence in each BBH pair were retained.

2.3. “Best BLAST Hit” Analysis of Genomes

A “Best BLAST hit” analysis was performed on the predicted CDSs of the EhV genomes using a BLASTp algorithm [64] with default parameters against the publically available NCBI non-redundant protein database, excluding viruses. The “Best BLAST hit” analyses used a comprehensive list of viral genes (in this case all the predicted CDSs of 13 EhV genomes) as a query against the NCBI non-redundant protein sequences and captured the top-hit taxonomic data if available (e.g., Domain, Phylum, Class, Order, Family, Genus, Species), associated with the subject homolog (Target), as well as sequence match scoring parameters. An initial search pulled all hits. These were clustered according to “Domain” and evaluated for alignment and Bit scores, which were normalized to the scoring system. While we recognize that there is no perfect cut-off, we have chosen to limit the dataset to Bit scores above 50 for “Domain”, and above 100 (E-value < 1 × 10−19) for the subsequent taxon categories. These analyses fall within the suggested boundaries [65].
Specific BLASTp analysis of each EhV genome against the pan genome of E. huxleyi CCMP1516 [66] and against other EhVs was conducted within the IMG/ER platform using a cut-off E-value of < 1 × 10−5 and identity of >50%. Additional BLASTp analysis of EhV genes highly similar to E. huxleyi CCMP1516 host genes and those similar to other putative genes in other taxa discovered during the “Best BLAST hit” analysis (see Section 3.5 and Section 3.6) were performed within NCBI against the non-redundant protein sequence database that includes viruses (Tables S1–S10).

3. Results and Discussion

3.1. Phylogenetic Relationships of Coccolithoviruses

Phylogenetic analysis of available DNA polymerase gene sequences, one of the commonly used phylogenetic markers for the dsDNA viral kingdom, indicated that the EhVs cluster into two major groups: A and B (Figure 1). The division into these groups was primarily due to a longer DNA polymerase gene present in EhV-18, EhV-156 and EhV-202 (caused by an insert of 12 bp, which results in the addition of glycine, threonine and two prolines at the end of the coding region). Group A was divided into three sub-clusters, where cluster A1 represents strains isolated primarily from the English Channel in 1999, A2 represents strains isolated primarily from the English Channel in 2001, and A3 represents a single strain isolated in 1999 from a Norwegian fjord. As such, these sub-clusters appear to be correlated with both year of isolation and location of origin. However, several exceptions were identified: EhV-145 and EhV-164 also clustered with A1 but were isolated after 1999. EhV-202, isolated in 2001 from the English Channel, clustered in B, with EhV-156 and EhV-18 (due to the 12 bp insertion mentioned previously), rather than A2. To further test these EhV groupings, phylogenetic analysis was also performed using the less conserved serine palmitoyltransferase (SPT) gene. This revealed similar groupings, with the exception of EhV-99B1 which clustered with A1.
The phylogenetic clades were also confirmed by the ANI analysis, in which the closest relative to EhV-86 based on the bidirectional pairwise alignment of the total number of genes was EhV-164 (placed in sub-clade A1), whereas those the furthest away were EhVs in clade B (Table 2).
Interestingly, significant differences have been observed in the infection dynamics of representative EhVs belonging to each phylogenetic clade identified in this study (Figure 1), both in respect to their lytic period [13] and their ability to utilize their host for the production of virally encoded glycosphingolipids, which are crucial for the successful demise of host cells [67].

3.2. Homology, Heterology and Genome Structure

Whole genome alignment revealed that the EhV genomes were syntenic with the exception of a ~80,000 bp section located in the middle of each genome (Figure 2) enriched with early transcription promoter elements [1,20,68]. As expected [37], this hyper-variable region was characterized by numerous inversions, rearrangements and base pair substitutions. One possibility is that the observed variation in this region is a result of the gaps in the draft genomes between the different contigs (Figure 2). Although this may be the case for some of the draft genomes (i.e., EhV-18, EhV-156, EhV-202, and EhV-208), where the highest number of gaps are in that region, it is not for others. For example, EhV-201 and EhV-99B1 sequences only have 2–3 gaps in that region, yet still exhibit variability. Further, many gaps are located in areas outside this region and show little variation; the draft genome of EhV-145 has 10 gaps in the section that ranges from ~300,000 bp to ~397,000 bp, yet variation in this section is minimal. It is therefore likely that the early transcriptional profile of these viruses can differ considerably.
The misalignment of different sections within the hyper-variable region (evident by numerous crossing lines between the co-linear blocks in Figure 2) becomes more prominent the further a genome is from those in cluster A1 (Figure 2). This is consistent with the DNA polymerase based phylogeny (Figure 1), in which viruses belonging to group B are more distant from those in group A1. Considered together, the genome alignments (Figure 2), and ANI analysis (Table 2) support the clustering of EhVs into the aforementioned groups and is consistent with DNA polymerase and SPT based phylogenies.

3.3. Genome Size and Putative Gene Differences

Previous pulsed-field gel electrophoresis (PFGE) of coccolithovirus genomes indicates that they have an average size of 410 kb [2]. In our study, the estimated length of the EhV genomes ranged from 376,759 to 421,891 bp (with a GC content of 39.94% to 40.49%), suggesting considerable variability in EhV genome size. For example, EhV-99B1 appears significantly shorter than the rest of the genomes (Figure 2). The genomes also differed in the number of predicted protein coding sequences (CDSs). They contained between 444 and 548 CDSs, from which an average of 90 had functional prediction, including three to six transfer RNA (tRNA) genes (Table 3). Due to the highly repetitive nature of the hyper-variable region, some of the variations observed could be attributed to sequencing errors, misalignments introduced during the original genome assembly, and the numerous gaps between the different contigs. However, these variations may also reflect real differences, as it is unlikely that regions as big as 45,132 bp long (the difference between the longest and shortest genome) were incorrectly sequenced or not included in the assemblies. These variations may have real consequences on the virus life cycle, affecting the time for viral genome synthesis within infected cells and, to an extent, the size of the capsid into which the DNA will be packed. As viruses exploit the resources of the host cell to synthesize new, infectious viral particles, these inherent differences may ultimately affect the number of viable viruses produced during infection.
Although strain-specific differences in the number and composition of transfer RNAs (tRNAs) encoded within the genomes were identified, the tRNAs for Arg, Asn and Gln were common to all (Table 4). Similarly, Pagarete et al. [44] report differences in the type of tRNAs encoded by EhV-86 and EhV-99B1. However, after an in-depth study of the different codon frequencies of the genomes of EhV-86 and EhV-99B1, they concluded that the difference in tRNAs does not correspond to the respective codon frequencies in each genome and that it is more likely that strain-specific tRNA differences represent adaptations to different host strains. If so, viruses with a larger number of tRNAs may have an advantage in terms of host range and translation within different host genotypes. Allen et al. [20] observe (in the absence of statistically robust data) that out of 23 different host strains tested, EhV-207 (which codes for six tRNAs) infects 10, whereas EhV-86 (which codes for five tRNAs) infects eight. Moreover, EhV-207 outcompetes EhV-86 when placed in direct competition over a single host genotype and has a higher rate of virus particle production [13]. The extent to which tRNAs are responsible for these observations has yet to be determined.
Most predicted CDSs were shared between all EhV genomes but a number of strain-specific CDSs were detected (Table 5). EhV-84 and EhV-202 contain the largest number of potentially “unique” genes (27 and 18, respectively). This is intriguing, as the other genomes in clade A1 and B (to which EhV-84 and EhV-202 belong respectively) do not exhibit a large number of “unique” genes (Table 5).
The observed strain-specific genomic differences within members of the same clade (Table 3, Table 4 and Table 5) highlight the limitations of virus taxonomy using a single gene such as DNA polymerase, when one tries to infer upon the evolutionary connections of these large viruses, the origin of certain genes, and potentially their functional implications. These limitations also become apparent in large-scale phylogenetic studies that include numerous taxa across the domains of life. Almost two decades ago, Villarreal and DeFilippis [69] suggested an alternative hypothesis for the flow of genetic material, with an emphasis on the virus DNA polymerase. Based on a large number of hits of virus DNA polymerases to other taxa, they suggest that algal viruses did not acquire replication genes from their eukaryotic hosts but vice versa [69]. We performed a similar analysis using the DNA polymerase gene of EhV-86 against the non-redundant protein sequence database in NCBI. The closest hit was to a DNA polymerase of the Yellowstone lake phycodnavirus 1 (reference sequence: YP_009174732.1), with a query cover of 81%, E-value of 9 × 10−137 and identity of 35% (Table S1), other Phycodnaviruses, and other organisms such as Klebsormidium laccidum (which belongs to a genus of filamentous charophyte green algae).

3.4. Coccolithovirus Gene Similarities to the Emiliania huxleyi Host

The prevailing dogma is that many EhV genes were acquired from Emiliania huxleyi through HGT. BLASTp analysis of EhV genomes revealed that, on average, ~25 EhV protein coding sequences were highly similar to counterparts in the host genome of E. huxleyi CCMP1516 (consistent with previous analysis of this host genome [66]). Unfortunately, most of these genes have no assigned function yet. Those with a predicted function include a group of genes that encode a de novo sphingolipid biosynthesis pathway (i.e., serine palmitoyltransferase [45%], sterol desaturase [42%], transmembrane fatty acid elongation protein [56%], and lipid phosphate phosphatase [29%]). BLASTp analysis of the EhV serine palmitoyltransferase gene (which encodes the rate-limiting enzyme in this pathway) showed that the most similar genes in the non-redundant protein sequence database of NCBI are putative serine palmitoyltransferases in E. huxleyi, Chrysochromulina sp. and Perkinsus marinus (Table S2). These genes are essential for the progression of infection through the production of virus-derived glycosphingolipids [28] and induction of PCD pathways within infected cells [17], and are present in all EhV genomes analysed. As previously reported [49], the two protein subunits of SPT (LCB1 and LCB2) are encoded by two separate genes in the genomes of EhV-18 and EhV-145. This separation over two genes may reflect the ancestral form prior to the fusion of the two subunits into a single gene (as seen in all other EhVs). The functional implications of this during infection are so far unknown. Nevertheless, the acquisition of this near complete pathway represents a classical example of HGT of a virus with its host, and illustrates a finely tuned co-evolutionary relationship between a host and its virus. In this case, it is manifested by a control for sphingolipid biosynthesis [29].
With the exception of EhV-99B1, EhV-202, EhV-18 and EhV-156, the CDS with the highest identity (i.e., 86.4%) to a similar gene in E. huxleyi CCMP1516 is a putative phosphate permease transporter (denoted as ehv117 in EhV-86). This transporter is encoded by all EhV isolates from the English Channel and the Scottish coast, but absent in the Norwegian isolate EhV-99B1 ([44]; and this study) and the partially sequenced genome of the Norwegian isolate EhV-163 (not included in this study) [43]. Instead, a 75-bp scar remnant of the transporter gene is still present at the 3′ end of this gene in both Norwegian isolates, and is replaced by a putative endonuclease [43]. This indicates that the Norwegian fjord EhVs once possessed the gene [44] and have since lost it. Such genes are common in E. huxleyi, which has six inorganic phosphate transporters and an alkaline phosphatase that enable it to thrive in low phosphorous conditions [66]. Phosphorus is also essential for successful viral replication in most host-virus systems [70,71,72]. However, we do not currently know if the ehv117 gene product is used to enhance phosphate acquisition from the external environment during infection. Its replacement with an endonuclease encoding gene in EhV-99B1 is intriguing, as this may function to provide additional phosphate via utilization of internal cellular resources, rather than acquisition of external phosphate via transporter activity. This could reflect the selective pressure imposed by particular geographic locations that are characterized by specific physicochemical conditions. For instance, the frequency of phosphate uptake genes in metagenomic datasets is higher in locations where the average phosphate concentration is lower (e.g., North Atlantic Gyre) [42,73]. Like SPT, it is most similar to a homologue in E. huxleyi (Table S3) and was likely acquired by HGT with its host. Other high hits in NCBI include similar genes in Ostreococcus lucimarinus and Ectocarpus siliculosus. Similarly, a phosphate transporter gene (i.e., pho4) was identified in the viruses infecting Ostreococcus and it was proposed that this was also a result of HGT [42].
For EhVs where the ehv117 transporter gene is absent, the CDS with the highest percentage similarity to a CDS in E. huxleyi CCMP1516 varies. In EhV-99B1, it is a predicted ribonucleoside-diphosphate reductase protein (RNR) (71.9% similar) whereas in EhV-202, EhV-18, and EhV-156 it is a predicted polyubiquitin protein (94.7% similar). While the former is an enzyme crucial for the conversion of ribonucleotides to deoxyribonucleotides for DNA synthesis, the latter is involved in protein degradation. We cannot confirm if these genes are also a result of HGT with their host, as there were many top hits in the NCBI non-redundant protein sequence database to other taxa, including the haptophyte Chrysochromulina, Chitinophaga niabensis bacteria, and the Gram-negative bacteria Cnuella takakiae, in the case of RNR (Table S4), and radiolarians such as Collozoum inerme, and protists such as Vitrella brassicaformis, in the case of polyubiquitin (Table S5).

3.5. Coccolithovirus Gene Similarities to Other Eukaryotes

As previously mentioned, the current consensus is that many EhV genes are a result of HGT between coccolithoviruses and their specific host [39]. If this is true, it demonstrates that these viruses are entwined within the molecular workings of their hosts and have managed to acquire genes that target and coerce core aspects of their cellular metabolism. Alternatively, many EhV genes (including some of those mentioned in Section 3.4) may have an alternative origin. Thirty-three percent of the total EhV gene hits in the “Best BLAST hit” analysis (which excluded viruses) matched Eukaryotes other than Isochrysidales (the order to which E. huxleyi belongs) (Figure 3). These genes included those involved in nucleotide transport and metabolism, replication, recombination and repair, and transcription (Table 6). Among these other Eukaryotes are phylogenetically distant organisms such as moulds, fungi, unicellular flagellated protozoa, centric diatoms, amoeba, and green algae. Most of these can be found in the planktonic realm where E. huxleyi also dwells, particularly diatoms whose development is often tightly linked to E. huxleyi growth in ecological successions [74]. In this study, some of the top EhV gene hits against other genera include DNA-directed RNA polymerase subunit-B (an enzyme that produces mainly RNA transcripts) and DNA ligase (an enzyme that facilitates the joining of DNA strands) (Table 6). The former had top hits against members of the genus Dictyostelium, a group of soil living amoeba, whereas the latter had top hits against Micromonas, a group of chlorophyte green algae (Tables S6 and S7).
It is also plausible that EhVs have, or have had in their evolutionary past, alternative hosts that have enabled them to facilitate HGT with other taxa. Some giant algal viruses have the capacity to alternate between hosts belonging to different genera. For example, viruses capable of infecting Haptolina hirta infect also Prymnesium kappa and vice versa; [75]). Alternatively, there may have been a retroviral stage during the evolution of the E. huxleyi-virus system. Several EhV genes thought to have originated via HGT with E. huxleyi (including those for the de novo sphingolipid biosynthesis) lack introns, unlike their counterparts in the host genome. This suggests the possible involvement of coccolithophore-infecting RNA viruses in mediating HGT, although such viruses have not been observed yet.

3.6. Coccolithovirus Gene Similarities to Bacteria

There are close ecological relationships between E. huxleyi and some bacterial groups. A previous study reports that E. huxleyi blooms in the North Atlantic are dominated by Roseobacter, SAR86, SAR11, and other Alpha and Gammaproteobacteria [76]. In their study, bacteria belonging to the Roseobacter genus and SAR86 and SAR11 clades account, together, for >50% of the bacterial rDNA in surface waters, whereas a cyanobacterium and members of the Alphaprotobacteria are associated with chlorophyll a-rich waters in the euphotic zone (0–50 m in depth), the typical niche at which coccolithophores are found [76]. A link between coccolithophores and bacteria is also found in cultures of E. huxleyi and Coccolithus pelagicus, which are enriched in hydrocarbon-degrading bacteria belonging to Marinobacter and Marivita [77]. These bacteria can colonize exopolymeric substances exuded by microalgae, but the ecological role of this phenomenon is unknown [78]. This tight evolutionary coexistence involving E. huxleyi, its viral community, and associated bacteria may have resulted in HGT across the domains.
In our more conservative “Best BLAST hit” analysis (using a bit-score of >100) we saw that 16% of the EhV genes also shared strong similarities to bacterial genes (Figure 3), involved in nucleotide, lipid, and carbohydrate transport and metabolism; and replication, recombination and repair (Table 6). Interestingly, almost half of the bacterial-like genes in the Chlorella virus NY2A, and a fifth of those in Mimivirus were proposed to be involved in DNA replication and repair [55,56]. In our analysis, top hits to bacteria include genes that code for sialidase, deoxycytidylate deaminase and fatty acid desaturase. These hits were against members of the genus Clostridium, Sphingobacterium and Niveispirillum respectively (Table 6, and Tables S8–S10). Bacteria from these genera are consistently found in all coccolithophore cultures studied by Green et al. [77]. The hits against the Sphingobacteriales are particularly intriguing as members of this order are characterized by the presence of cellular lipid components that are comprised of high concentrations of sphingophospholipids [79]. The rate limiting step in sphingolipid biosynthesis in S. multivorum is serine palmitoyltransferase (SPT) [80], as in the E. huxleyi—virus system [81]. Although the EhV SPT is more similar to the host gene (as indicated above), the closest crystal structure in the PDB database to the EhV SPT is Sphingobacterium multivorum [67]. This structure was used to model the EhV derived SPT enzyme and to infer its catalytic capabilities during infection [36,67].
Moreover, in S. multivorum, sialidase specifically hydrolyzes deaminated neuraminic acid linkages and is localized in the periplasm [82,83]. Viruses such as influenza, adenoviruses, and polyomaviruses [84,85], can use virus-derived sialidase to target host sialic acid glycosphingolipids located on the host membrane. A similar process could be fundamental for EhV host recognition and entry, notably because susceptible E. huxleyi strains are enriched in glycosphingolipids (GSLs) with a sialic acid-modified glycosyl head-group [12,14]. These GSLs are proposed as a target for hydrolysis by EhV-encoded sialidases or as a ligand for the attachment of EhV lectin proteins [23]. Indeed, virus-derived sialidase transcripts are detected during EhV-86 infection 6–24 h post infection [21].
Surprisingly, we observed that the putative sialidase gene is severely truncated (up to 95% of its extension) in some EhV strains. Its full form is present in 1999 isolates (as well as EhV-164 and EhV-145), whereas those isolated in 2001 (as well as in EhV-18 and EhV-156) have a truncated form. In the genomes with the truncated form, the reduction is from a full gene of 1122 bp to 180 bp. Further reduction is seen in EhV-18 and EhV-156 where only a 60 bp fragment of the original gene remains. To date, EhV infectivity data do not show an association between the lack of a full length sialidase gene and a reduced ability to infect E. huxleyi. Hence, the selection against this gene in many EhVs and the fact that infection still occurs (presumably alongside other viruses able to utilize the active gene), suggests that its presence is not essential. Previous studies of Influenza A viruses show that a lack of functional sialidase is not essential to all viruses and that some viruses can adapt and grow in its absence in tissue cultures, mice, and embryonic eggs [86].
The role of two other bacterial-like genes, fatty acid desaturase and deoxycytidylate deaminase (Table 6) identified in EhVs requires further investigation. Fatty acid desaturases catalyze the desaturation of fatty acids. During EhV infection, a significant remodeling of the fatty acid profile of E. huxleyi occurs and this gene most likely plays an important role [30,87]. Deoxycytidylate deaminase is an enzyme involved in the biosynthesis of deoxyribonucleoside triphosphates (dNTPs). Its role, however, during infection remains elusive, as its expression has not been confirmed [1].

3.7. Possible Mode for HGT with Bacteria

Bacterial homologues in the genomes of nucleocytoplasmic large DNA viruses (NCLDVs) have been previously reported [55,56]. To our knowledge, our study is the first time that this is specifically identified in coccolithoviruses. While it is possible that some of the aforementioned genes were incorporated in the EhV genomes before the evolutionary divergence of eukaryotes and prokaryotes (a detailed “Best BLAST hit” analysis against ancestors of E. huxleyi such as Tisochrysis lutea and Prymnesium parvum, as well as against other primitive lineages of bacteria should reveal that), other explanations are also plausible. HGT could have occurred in situations where the genetic material of EhVs and bacteria co-occurred during virus replication. It is possible that EhVs and bacteria share, at moments, the same intracellular environment within E. huxleyi, particularly in light of recent data highlighting the importance of mixotrophy in phytoplankton [88]. For instance, in another NCLDV (i.e., Cafeteria roenbergensis virus), a 38-kb genomic region was suggested to be bacterial in origin and possibly acquired during an infection of its microflagellated grazer host that often contains a phagocytosed bacteria in its cytoplasm [89]. While there is no direct evidence for the engulfment of bacteria by E. huxleyi, a recent study of the different life stages of this alga shows that both diploid calcifying and motile haploid cells can engulf microbeads as big as 0.5 µm in diameter [90]. Also, a high abundance of transcripts linked to the digestive apparatus and those related to endocytosis are detected in diploid E. huxleyi cells, suggestive of an inherent ability of coccolithophores to participate in mixotrophy [90]. Endocytotic vesicles may be an additional mechanism for EhV infection [22], and E. huxleyi feeding on cohabiting bacteria might sometimes be infected by lytic viruses. Such mixotrophic-viral infection events may facilitate HGT across the domains.
Whether these events have occurred multiple times during which individual bacterial genes from different co-habiting bacteria were acquired by EhVs throughout their evolutionary history, or there have been only a few events during which large “chunks” of bacterial DNA (comprising of several adjacent genes, possibly sharing a similar function) were incorporated into EhVs, is unknown. However, the EhV genes with the highest bit-scores to Bacteria in our study were not genomically-located near each other in the analyzed genomes and did not appear to hit the same bacterial taxa. This is therefore consistent with the occurrence of multiple independent gene transfer events.

4. Conclusions

In light of the increasing body of literature that focuses on high-throughput metagenomics data and direct sequencing of virus genomes from environmental samples, it is important to remember the utility of model host-virus systems and single genome analysis. Here, we provided a review of the genomic features of 13 coccolithovirus strains and highlighted the differences and similarities in their respective genomes. We showed that the classification of coccolithoviruses using whole genome analysis mimics that of conserved gene based phylogeny. However, this approach does not allow the elucidation of functionally important differences among closely related viruses, and a detailed gene-by-gene examination may sometimes be more suitable. In addition, although many coccolithovirus genes were most similar to their known host and other eukaryotes, we highlighted the close and often ignored relationships that microalgae and their viruses have with bacteria in the marine environment. We revealed that for EhVs, as for other NCLDVs, HGT does not necessarily follow the traditionally expected pattern of host association. This analysis, performed across the three domains of life, contributes to some central questions in current viral ecology and evolution: (1) what defines a viral gene? (2) Where do viral genes come from? (3) are viruses able to serve as gene transfer agents across the domains of life? The existence of clear links to both Eukarya and Bacteria in this giant virus genomic assembly enhances the idea that viruses play a central role in the transfer of genetic information among the different life domains. Unwinding the relationships within the viral “domain”, understanding how it came to be, and how it has and continues to shape the three modern domains that we can easily recognize today remains a challenge.

Supplementary Materials

The following are available online at https://www.mdpi.com/1999-4915/9/3/52/s1, Table S1: BLASTp analysis of the EhV DNA polymerase gene against the non-redundant protein database on NCBI, Table S2: BLASTp analysis of the EhV DNA serine palmitoyltranferase gene against the non-redundant protein database on NCBI, Table S3: BLASTp analysis of the EhV phosphate permease gene against the non-redundant protein database on NCBI, Table S4: BLASTp analysis of the EhV ribonucleoside-diphosphate reductase gene against the non-redundant protein database on NCBI, Table S5: BLASTp analysis of the EhV DNA polyubiquitin gene against the non-redundant protein database on NCBI, Table S6: BLASTp analysis of the EhV DNA-directed RNA polymerase subunit B gene against the non-redundant protein database on NCBI, Table S7: BLASTp analysis of the EhV DNA ligase gene against the non-redundant protein database on NCBI, Table S8: BLASTp analysis of the EhV deoxycytidylate deaminase gene against the non-redundant protein database on NCBI, Table S9: BLASTp analysis of the EhV sialidase gene against the non-redundant protein database on NCBI, Table S10: BLASTp analysis of the EhV fatty acid desaturase gene against the non-redundant protein database on NCBI.

Acknowledgments

This work was funded by the NERC Oceans 2025 program, Plymouth Marine Laboratory’s Research Program, and a NERC PhD grant awarded to J.I.N. supervised by M.J.A. and S.A.K. at Plymouth Marine Laboratory. We would also like to thank the reviewers in pointing us towards some crucial literature and suggesting significant improvements to this manuscript, as well as Maeve Eason Hubbard for proof-reading the final version of this manuscript.

Author Contributions

J.I.N. isolated originally some of the EhVs in this paper, prepared them for sequencing, analyzed the data, did the genome comparisons, and wrote the initial version of the manuscript; A.P. provided insight into the genomic characteristics of EhV-99B1 and advised on some of the evolutionary aspects of these viruses; F.M., S.C, and D.D.D. conceived the idea and conducted the “Best BLAST hit” analysis, as well as helped in writing the manuscript, S.A.K. provided insight on the ecological aspects of these viruses, and M.J.A. obtained the funding for the work as well as provided insight into the molecular biology and evolution of these viruses. All authors provided critical input into the design, writing, and editorial revisions of the final manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Wilson, W.H.; Schroeder, D.C.; Allen, M.J.; Holden, M.T.G.; Parkhill, J.; Barrell, B.G.; Churcher, C.; Hamlin, N.; Mungall, K.; Norbertczak, H.; et al. Complete genome sequence and lytic phase transcription profile of a Coccolithovirus. Science 2005, 309, 1090–1092. [Google Scholar] [CrossRef] [PubMed]
  2. Schroeder, D.C.; Oke, J.; Malin, G.; Wilson, W.H. Coccolithovirus (Phycodnaviridae): Characterisation of a new large dsDNA algal virus that infects Emiliana huxleyi. Arch. Virol. 2002, 147, 1685–1698. [Google Scholar] [CrossRef] [PubMed]
  3. Wilson, W.H.; Tarran, G.A.; Schroeder, D.; Cox, M.J.; Oke, J.; Malin, G. Isolation of viruses responsible for the demise of an Emiliania huxleyi bloom in the English Channel. J. Mar. Biol. Assoc. 2002, 82, 369–377. [Google Scholar] [CrossRef]
  4. Allen, M.J.; Schroeder, D.C.; Holden, M.T.G.; Wilson, W.H. Evolutionary history of the Coccolithoviridae. Mol. Biol. Evol. 2006, 23, 86–92. [Google Scholar] [CrossRef] [PubMed]
  5. Dunigan, D.D.; Fitzgerald, L.A.; Van Etten, J.L. Phycodnaviruses: A peek at genetic diversity. Virus Res. 2006, 117, 119–132. [Google Scholar] [CrossRef] [PubMed]
  6. Wilson, W.H.; Van Etten, J.L.; Allen, M.J. The Phycodnaviridae: The story of how tiny giants rule the world. Curr. Top. Microbiol. Immunol. 2009, 328, 1–42. [Google Scholar] [PubMed]
  7. Martínez, J.M.; Schroeder, D.C.; Larsen, A.; Bratbak, G.; Wilson, W.H. Molecular dynamics of Emiliania huxleyi and cooccurring viruses during two separate mesocosm studies. Appl. Environ. Microbiol. 2007, 73, 554–562. [Google Scholar] [CrossRef] [PubMed]
  8. Martínez, J.M.; Schroeder, D.C.; Wilson, W.H. Dynamics and genotypic composition of Emiliania huxleyi and their co-occurring viruses during a coccolithophore bloom in the North Sea. FEMS Microbiol. Ecol. 2012, 81, 315–323. [Google Scholar] [CrossRef] [PubMed]
  9. Pagarete, A.; Allen, M.J.; Wilson, W.H.; Kimmance, S.A.; de Vargas, C. Host-virus shift of the sphingolipid pathway along an Emiliania huxleyi bloom: Survival of the fattest. Environ. Microbiol. 2009, 11, 2840–2848. [Google Scholar] [CrossRef] [PubMed]
  10. Vardi, A.; Haramaty, L.; Van Mooy, B.A.S.; Fredricks, H.F.; Kimmance, S.A.; Larsen, A.; Bidle, K.D. Host-virus dynamics and subcellular controls of cell fate in a natural coccolithophore population. Proc. Natl. Acad. Sci. USA 2012, 109, 19327–19332. [Google Scholar] [CrossRef] [PubMed]
  11. Kimmance, S.A.; Allen, M.J.; Pagarete, A.; Martínez Martínez, J.; Wilson, W.H. Reduction in photosystem II efficiency during a virus-controlled Emiliania huxleyi bloom. Mar. Ecol. Prog. Ser. 2014, 495, 65–76. [Google Scholar] [CrossRef]
  12. Fulton, J.M.; Fredricks, H.F.; Bidle, K.D.; Vardi, A.; Kendrick, B.J.; DiTullio, G.R.; Van Mooy, B.A.S. Novel molecular determinants of viral susceptibility and resistance in the lipidome of Emiliania huxleyi. Environ. Microbiol. 2014, 16, 1137–1149. [Google Scholar] [CrossRef] [PubMed]
  13. Nissimov, J.I.; Napier, J.A.; Allen, M.J.; Kimmance, S.A. Intragenus competition between coccolithoviruses: An insight on how a select few can come to dominate many. Environ. Microbiol. 2015, 18, 133–145. [Google Scholar] [CrossRef] [PubMed]
  14. Hunter, J.E.; Frada, M.J.; Fredricks, H.F.; Vardi, A.; Van Mooy, B.A.S. Targeted and untargeted lipidomics of Emiliania huxleyi viral infection and life cycle phases highlights molecular biomarkers of infection, susceptibility, and ploidy. Front. Mar. Sci. 2015, 2. [Google Scholar] [CrossRef]
  15. Schroeder, D.C.; Oke, J.; Hall, M.; Malin, G.; Wilson, W.H. Virus succession observed during an Emiliania huxleyi bloom. Appl. Environ. Microbiol. 2003, 69, 2484–2490. [Google Scholar] [CrossRef] [PubMed]
  16. Lehahn, Y.; Koren, I.; Schatz, D.; Frada, M.; Sheyn, U.; Boss, E.; Efrati, S.; Rudich, Y.; Trainic, M.; Sharoni, S.; et al. Decoupling Physical from Biological Processes to Assess the Impact of Viruses on a Mesoscale Algal Bloom. Curr. Biol. 2014, 24, 2041–2046. [Google Scholar] [CrossRef] [PubMed]
  17. Bidle, K.D. The Molecular Ecophysiology of Programmed Cell Death in Marine Phytoplankton. Ann. Rev. Mar. Sci. 2015, 7, 341–375. [Google Scholar] [CrossRef] [PubMed]
  18. Allen, M.J.; Lanzén, A.; Bratbak, G. Characterisation of the coccolithovirus intein. Mar. Genomics 2011, 4, 1–7. [Google Scholar] [CrossRef] [PubMed]
  19. Allen, M.J.; Wilson, W.H. The coccolithovirus microarray: An array of uses. Brief. Funct. Genomic. Proteom. 2006, 5, 273–279. [Google Scholar] [CrossRef] [PubMed]
  20. Allen, M.J.; Martinez-Martinez, J.; Schroeder, D.C.; Somerfield, P.J.; Wilson, W.H. Use of microarrays to assess viral diversity: from genotype to phenotype. Environ. Microbiol. 2007, 9, 971–982. [Google Scholar] [CrossRef] [PubMed]
  21. Kegel, J.U.; Blaxter, M.; Allen, M.J.; Metfies, K.; Wilson, W.H.; Valentin, K. Transcriptional host–virus interaction of Emiliania huxleyi (Haptophyceae) and EhV-86 deduced from combined analysis of expressed sequence tags and microarrays. Eur. J. Phycol. 2010, 45, 1–12. [Google Scholar] [CrossRef]
  22. Mackinder, L.C.M.; Worthy, C.A.; Biggi, G.; Hall, M.; Ryan, K.P.; Varsani, A.; Harper, G.M.; Wilson, W.H.; Brownlee, C.; Schroeder, D.C. A unicellular algal virus, Emiliania huxleyi virus 86, exploits an animal-like infection strategy. J. Gen. Virol. 2009, 90, 2306–2316. [Google Scholar] [CrossRef] [PubMed]
  23. Rose, S.L.; Fulton, J.M.; Brown, C.M.; Natale, F.; Van Mooy, B.A.S.; Bidle, K.D. Isolation and characterization of lipid rafts in Emiliania huxleyi: A role for membrane microdomains in host-virus interactions. Environ. Microbiol. 2014, 16, 1150–1166. [Google Scholar] [CrossRef] [PubMed]
  24. Evans, C.; Malin, G.; Mills, G.P.; Wilson, W.H. Viral Infection of Emiliania huxleyi (Prymnesiophyceae) Leads to Elevated Production of Reactive Oxygen Species. J. Phycol. 2006, 42, 1040–1047. [Google Scholar] [CrossRef]
  25. Bidle, K.D.; Haramaty, L.; Barcelos, E.; Ramos, J.; Falkowski, P. Viral activation and recruitment of metacaspases in the unicellular coccolithophore, Emiliania huxleyi. Proc. Natl. Acad. Sci. USA 2007, 104, 6049–6054. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Bidle, K.D.; Kwityn, C.J. Assessing the Role of Caspase Activity and Metacaspase Expression on Viral Susceptibility of the Coccolithophore, Emiliania Huxleyi (Haptophyta). J. Phycol. 2012, 48, 1079–1089. [Google Scholar] [CrossRef] [PubMed]
  27. Schatz, D.; Shemi, A.; Rosenwasser, S.; Sabanay, H.; Wolf, S.G.; Ben-Dor, S.; Vardi, A. Hijacking of an autophagy-like process is critical for the life cycle of a DNA virus infecting oceanic algal blooms. New Phytol. 2014, 204, 854–863. [Google Scholar] [CrossRef] [PubMed]
  28. Vardi, A.; Van Mooy, B.A.S.; Fredricks, H.F.; Popendorf, K.J.; Ossolinski, J.E.; Haramaty, L.; Bidle, K.D. Viral glycosphingolipids induce lytic infection and cell death in marine phytoplankton. Science 2009, 326, 861–865. [Google Scholar] [CrossRef] [PubMed]
  29. Bidle, K.D.; Vardi, A. A chemical arms race at sea mediates algal host-virus interactions. Curr. Opin. Microbiol. 2011, 14, 449–457. [Google Scholar] [CrossRef] [PubMed]
  30. Rosenwasser, S.; Mausz, M.A.; Schatz, D.; Sheyn, U.; Malitsky, S.; Aharoni, A.; Weinstock, E.; Tzfadia, O.; Ben-Dor, S.; Feldmesser, E.; et al. Rewiring Host Lipid Metabolism by Large Viruses Determines the Fate of Emiliania huxleyi, a Bloom-Forming Alga in the Ocean. Plant Cell 2014, 26, 2689–2707. [Google Scholar] [CrossRef] [PubMed]
  31. Ziv, C.; Malitsky, S.; Othman, A.; Ben-Dor, S.; Wei, Y.; Zheng, S.; Aharoni, A.; Hornemann, T.; Vardi, A. Viral serine palmitoyltransferase induces metabolic switch in sphingolipid biosynthesis and is required for infection of a marine alga. Proc. Natl. Acad. Sci. USA 2016, 113, E1907–E1916. [Google Scholar] [CrossRef] [PubMed]
  32. Frada, M.J.; Schatz, D.; Farstey, V.; Ossolinski, J.E.; Sabanay, H.; Ben-Dor, S.; Koren, I.; Vardi, A. Zooplankton May Serve as Transmission Vectors for Viruses Infecting Algal Blooms in the Ocean. Curr. Biol. 2014, 24, 2592–2597. [Google Scholar] [CrossRef] [PubMed]
  33. Sharoni, S.; Trainic, M.; Schatz, D.; Lehahn, Y.; Flores, M.J.; Bidle, K.D.; Ben-Dor, S.; Rudich, Y.; Koren, I.; Vardi, A. Infection of phytoplankton by aerosolized marine viruses. Proc. Natl. Acad. Sci. USA 2015, 112, 6643–6647. [Google Scholar] [CrossRef] [PubMed]
  34. Coolen, M.J.L. 7000 years of Emiliania huxleyi viruses in the Black Sea. Science 2011, 333, 451–452. [Google Scholar] [CrossRef] [PubMed]
  35. Rowe, J.M.; Fabre, M.-F.; Gobena, D.; Wilson, W.H.; Wilhelm, S.W. Application of the major capsid protein as a marker of the phylogenetic diversity of Emiliania huxleyi viruses. FEMS Microbiol. Ecol. 2011, 76, 373–380. [Google Scholar] [CrossRef] [PubMed]
  36. Nissimov, J.I.; Jones, M.; Napier, J.A.; Munn, C.B.; Kimmance, S.A.; Allen, M.J. Functional inferences of environmental coccolithovirus biodiversity. Virol. Sin. 2013, 28, 291–302. [Google Scholar] [CrossRef] [PubMed]
  37. Pagarete, A.; Kusonmano, K.; Petersen, K.; Kimmance, S.A.; Martínez Martínez, J.; Wilson, W.H.; Hehemann, J.H.; Allen, M.J.; Sandaa, R.A. Dip in the gene pool: Metagenomic survey of natural coccolithovirus communities. Virology 2014, 466–467, 129–137. [Google Scholar] [CrossRef] [PubMed]
  38. Highfield, A.; Evans, C.; Walne, A.; Miller, P.I.; Schroeder, D.C. How many Coccolithovirus genotypes does it take to terminate an Emiliania huxleyi bloom? Virology 2014, 466-467, 138–145. [Google Scholar] [CrossRef] [PubMed]
  39. Monier, A.; Pagarete, A.; de Vargas, C.; Allen, M.J.; Read, B.; Claverie, J.; Ogata, H. Horizontal gene transfer of an entire metabolic pathway between a eukaryotic alga and its DNA virus. Genome Res. 2009, 19, 1441–1449. [Google Scholar] [CrossRef] [PubMed]
  40. Pagarete, A.; Le Corguillé, G.; Tiwari, B.; Ogata, H.; de Vargas, C.; Wilson, W.H.; Allen, M.J. Unveiling the transcriptional features associated with coccolithovirus infection of natural Emiliania huxleyi blooms. FEMS Microbiol. Ecol. 2011, 78, 555–564. [Google Scholar] [CrossRef] [PubMed]
  41. Lindell, D.; Sullivan, M.B.; Johnson, Z.I.; Tolonen, A.C.; Rohwer, F.; Chisholm, S.W. Transfer of photosynthesis genes to and from Prochlorococcus viruses. Proc. Natl. Acad. Sci. USA 2004, 101, 11013–11018. [Google Scholar] [CrossRef] [PubMed]
  42. Monier, A.; Welsh, R.M.; Gentemann, C.; Weinstock, G.; Sodergren, E.; Armbrust, E.V.; Eisen, J.A.; Worden, A.Z. Phosphate transporters in marine phytoplankton and their viruses: Cross-domain commonalities in viral-host gene exchanges. Environ. Microbiol. 2011, 14, 162–176. [Google Scholar] [CrossRef] [PubMed]
  43. Allen, M.J.; Schroeder, D.C.; Donkin, A.; Crawfurd, K.J.; Wilson, W.H. Genome comparison of two Coccolithoviruses. Virol. J. 2006, 3, 15. [Google Scholar] [CrossRef] [PubMed]
  44. Pagarete, A.; Lanzén, A.; Puntervoll, P.; Sandaa, R.A.; Larsen, A.; Larsen, J.B.; Allen, M.J.; Bratbak, G. Genomic sequence and analysis of EhV-99B1, a new coccolithovirus from the Norwegian fjords. Intervirology 2013, 56, 60–66. [Google Scholar] [CrossRef] [PubMed]
  45. Nissimov, J.I.; Worthy, C.A.; Rooks, P.; Napier, J.A.; Kimmance, S.A.; Henn, M.R.; Ogata, H.; Allen, M.J. Draft genome sequence of the coccolithovirus EhV-84. Stand. Genomic Sci. 2011, 5, 1–11. [Google Scholar] [CrossRef] [PubMed]
  46. Nissimov, J.I.; Worthy, C.A.; Rooks, P.; Napier, J.A.; Kimmance, S.A.; Henn, M.R.; Ogata, H.; Allen, M.J. Draft Genome Sequence of Four Coccolithoviruses: Emiliania huxleyi Virus EhV-88, EhV-201, EhV-207, and EhV-208. J. Virol. 2012, 86, 2896–2897. [Google Scholar] [CrossRef] [PubMed]
  47. Nissimov, J.I.; Worthy, C.A.; Rooks, P.; Napier, J.A.; Kimmance, S.A.; Henn, M.R.; Ogata, H.; Allen, M.J. Draft Genome Sequence of the Coccolithovirus Emiliania huxleyi Virus 202. J. Virol. 2012, 86, 2380–2381. [Google Scholar] [CrossRef] [PubMed]
  48. Nissimov, J.I.; Worthy, C.A.; Rooks, P.; Napier, J.A.; Kimmance, S.A.; Henn, M.R.; Ogata, H.; Allen, M.J. Draft genome sequence of the Coccolithovirus Emiliania huxleyi virus 203. J. Virol. 2011, 85, 13468–13469. [Google Scholar] [CrossRef] [PubMed]
  49. Nissimov, J.I.; Napier, J.A.; Kimmance, S.A.; Allen, M.J. Permanent draft genomes of four new coccolithoviruses: EhV-18, EhV-145, EhV-156 and EhV-164. Mar. Genomics 2014, 15, 7–8. [Google Scholar] [CrossRef] [PubMed]
  50. Azam, F.; Fenchel, T.; Field, J. The ecological role of water-column microbes in the sea. Mar. Ecol. Prog. Ser. 1983, 10, 257–263. [Google Scholar] [CrossRef]
  51. Azam, F.; Fandino, L.; Grossart, H.; Long, R. Microbial loop: Its significance in oceanic productivity and global change. Rapp. Comrn. inl. Mer Médit. 1998, 35, 1–3. [Google Scholar]
  52. Mayers, T.J.; Bramucci, A.R.; Yakimovich, K.M.; Case, R.J. A Bacterial Pathogen Displaying Temperature-Enhanced Virulence of the Microalga Emiliania huxleyi. Front. Microbiol. 2016, 7, 892. [Google Scholar] [CrossRef] [PubMed]
  53. Egan, S.; Fernandes, N.D.; Kumar, V.; Gardiner, M.; Thomas, T. Bacterial pathogens, virulence mechanism and host defence in marine macroalgae. Environ. Microbiol. 2014, 16, 925–938. [Google Scholar] [CrossRef] [PubMed]
  54. Lachnit, T.; Thomas, T.; Steinberg, P. Expanding our understanding of the seaweed holobiont: RNA Viruses of the Red Alga Delisea pulchra. Front. Microbiol. 2016, 6, 1–12. [Google Scholar] [CrossRef] [PubMed]
  55. Filée, J.; Siguier, P.; Chandler, M. I am what I eat and I eat what I am: acquisition of bacterial genes by giant viruses. Trends Genet. 2007, 23, 10–15. [Google Scholar] [CrossRef] [PubMed]
  56. Filée, J.; Pouget, N.; Chandler, M. Phylogenetic evidence for extensive lateral acquisition of cellular genes by Nucleocytoplasmic large DNA viruses. BMC Evol. Biol. 2008, 8, 320. [Google Scholar] [CrossRef] [PubMed]
  57. Tamura, K.; Stecher, G.; Peterson, D.; Filipski, A.; Kumar, S. MEGA6: Molecular Evolutionary Genetics Analysis version 6.0. Mol. Biol. Evol. 2013, 30, 2725–2729. [Google Scholar] [CrossRef] [PubMed]
  58. Saitou, N.; Nei, M. The Neighbor-joining Method : A New Method for Reconstructing Phylogenetic Trees. Mol. Biol. Evol. 1987, 4, 406–425. [Google Scholar] [PubMed]
  59. Carver, T.J.; Rutherford, K.M.; Berriman, M.; Rajandream, M.-A.; Barrell, B.G.; Parkhill, J. ACT: The Artemis Comparison Tool. Bioinformatics 2005, 21, 3422–3423. [Google Scholar] [CrossRef] [PubMed]
  60. Darling, A.E.; Mau, B.; Perna, N.T. progressiveMauve: Multiple genome alignment with gene gain, loss and rearrangement. PLoS ONE 2010, 5, e11147. [Google Scholar] [CrossRef] [PubMed]
  61. Markowitz, V.M.; Mavromatis, K.; Ivanova, N.N.; Chen, I.-M.A.; Chu, K.; Kyrpides, N.C. IMG ER: A system for microbial genome annotation expert review and curation. Bioinformatics 2009, 25, 2271–2278. [Google Scholar] [CrossRef] [PubMed]
  62. Konstantinidis, K.T.; Tiedje, J.M. Genomic insights that advance the species definition for prokaryotes. Proc. Natl. Acad. Sci. USA 2005, 102, 2567–2572. [Google Scholar] [CrossRef] [PubMed]
  63. Klappenbach, J.A.; Goris, J.; Vandamme, P.; Coenye, T.; Konstantinidis, K.T.; Tiedje, J.M. DNA–DNA hybridization values and their relationship to whole-genome sequence similarities. Int. J. Syst. Evol. Microbiol. 2007, 57, 81–91. [Google Scholar]
  64. Altschul, S.F.; Gish, W.; Miller, W.; Myers, E.W.; Lipman, D.J. Basic local alignment search tool. J. Mol. Biol. 1990, 215, 403–410. [Google Scholar] [CrossRef]
  65. Louie, B.; Higdon, R.; Kolker, E. A statistical model of protein sequence similarity and function similarity reveals overly-specific function predictions. PLoS ONE 2009, 4, e7546. [Google Scholar] [CrossRef] [PubMed]
  66. Read, B.A.; Kegel, J.; Klute, M.J.; Kuo, A.; Lefebvre, S.C.; Maumus, F.; Mayer, C.; Miller, J.; Monier, A.; Salamov, A.; et al. Pan genome of the phytoplankton Emiliania underpins its global distribution. Nature 2013, 499, 209–213. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  67. Nissimov, J.I. Competitive ecology of coccolithoviruses as revealed through biochemical diversity of serine palmitoyltransferase. 2017; unpublished, in review. [Google Scholar]
  68. Allen, M.J.; Schroeder, D.C.; Wilson, W.H. Preliminary characterisation of repeat families in the genome of EhV-86, a giant algal virus that infects the marine microalga Emiliania huxleyi. Arch. Virol. 2006, 151, 525–535. [Google Scholar] [CrossRef] [PubMed]
  69. Villarreal, L.P.; DeFilippis, V.R. A hypothesis for DNA viruses as the origin of eukaryotic replication proteins. J. Virol. 2000, 74, 7079–7084. [Google Scholar] [CrossRef] [PubMed]
  70. Maat, D.S.; Blok, R.; De Brussaard, C.P.D. Combined Phosphorus Limitation and Light Stress Prevent Viral Proliferation in the Phytoplankton Species Phaeocystis globosa, but Not in Micromonas pusilla. Front. Micr. 2016, 3. [Google Scholar] [CrossRef]
  71. Wilson, W.H.; Carr, N.G.; Mann, N.H. The effect of phosphate status on the kinetics of cyanophage infection in the oceanic cyanobacterium Synechococcus sp. wh7803. J. Phycol. 1996, 32, 506–516. [Google Scholar] [CrossRef]
  72. Bratbak, G.; Jacobsen, A.; Heldal, M.; Nagasaki, K.; Thingstad, F. Virus production in Phaeocystis pouchetii and its relation to host cell growth and nutrition. Aquat. Microb. Ecol. 1998, 16, 1–9. [Google Scholar] [CrossRef]
  73. Coleman, M.L.; Chisholm, S.W. Ecosystem-specific selection pressures revealed through comparative population genomics. Proc. Natl. Acad. Sci. USA 2010, 107, 18634–18639. [Google Scholar] [CrossRef] [PubMed]
  74. Balch, W.M. Re-evaluation of the physiological ecology of coccolithophores. In Coccolithophores; Springer: Berlin, Germany, 2004; pp. 165–190. [Google Scholar]
  75. Johannessen, T.V.; Bratbak, G.; Larsen, A.; Ogata, H.; Egge, E.S.; Edvardsen, B.; Eikrem, W.; Sandaa, R.-A. Characterisation of three novel giant viruses reveals huge diversity among viruses infecting Prymnesiales (Haptophyta). Virology 2015, 476, 180–188. [Google Scholar] [CrossRef] [PubMed]
  76. Gonza´lez, J.M.; Simo, R.; Massana, R.; Covert, J.S.; Casamayor, E.O.; Pedro, C.; Moran, M.A. Bacterial Community Structure Associated with a North Atlantic Algal Bloom. Appl. Environ. Microb. 2000, 66, 4237–4246. [Google Scholar] [CrossRef]
  77. Green, D.H.; Echavarri-Bravo, V.; Brennan, D.; Hart, M.C.; Green, D.H.; Echavarri-Bravo, V.; Brennan, D.; Hart, M.C. Bacterial Diversity Associated with the Coccolithophorid Algae Emiliania huxleyi and Coccolithus pelagicus f. braarudii. Biomed Res. Int. 2015, 1–15. [Google Scholar]
  78. Carrias, J.-F.; Serre, J.-P.; Sime-Ngando, T.; Amblard, C. Distribution, size, and bacterial colonization of pico- and nano-detrital organic particles (DOP) in two lakes of different trophic status. Limnol. Oceanogr. 2002, 47, 1202–1209. [Google Scholar] [CrossRef]
  79. Yabuuchi, E.; Kaneko, T.; Yano, I.; Moss, C.W.; Miyoshi, N. Sphingobacterium gen. nov., Sphingobacterium spiritivorum comb. nov., Sphingobacterium multivorum comb. nov., Sphingobacterium mizutae sp. nov., and Flavobacterium indologenes sp. nov.: Glucose-Nonfermenting Gram-Negative Rods in CDC Groups IIK-2 and IIb. Int. J. Syst. Bacteriol. 1983, 33, 580–598. [Google Scholar] [CrossRef]
  80. Ikushiro, H.; Islam, M.M.; Tojo, H.; Hayashi, H. Molecular characterization of membrane-associated soluble serine palmitoyltransferases from Sphingobacterium multivorum and Bdellovibrio stolpii. J. Bacteriol. 2007, 189, 5749–5761. [Google Scholar] [CrossRef] [PubMed]
  81. Han, G.; Gable, K.; Yan, L.; Allen, M.J.; Wilson, W.H.; Moitra, P.; Harmon, J.M.; Dunn, T.M. Expression of a novel marine viral single-chain serine palmitoyltransferase and construction of yeast and mammalian single-chain chimera. J. Biol. Chem. 2006, 281, 39935–39942. [Google Scholar] [CrossRef] [PubMed]
  82. Kitajima, K.; Kuroyanagi, H.; Inoue, S.; Ye, J.; Troy, F.A.; Inoue, Y. Discovery of a new type of sialidase, “KDNase,” which specifically hydrolyzes deaminoneuraminyl (3-deoxy-D-glycero-D-galacto-2-nonulosonic acid) but not N-acylneuraminyl linkages. J. Biol. Chem. 1994, 269, 21415–21419. [Google Scholar] [PubMed]
  83. Nishino, S.; Kuroyanagi, H.; Terada, T.; Inoue, S.; Inoue, Y.; Troy, F.A.; Kitajima, K. Induction, localization, and purification of a novel sialidase, deaminoneuraminidase (KDNase), from Sphingobacterium multivorum. J. Biol. Chem. 1996, 271, 2909–2913. [Google Scholar] [CrossRef] [PubMed]
  84. Stray, S.J.; Cummings, R.D.; Air, G.M. Influenza virus infection of desialylated cells. Glycobiology 2000, 10, 649–658. [Google Scholar] [CrossRef] [PubMed]
  85. Neu, U.; Bauer, J.; Stehle, T. Viruses and sialic acids: rules of engagement. Curr. Opin. Struct. Biol. 2011, 21, 610–618. [Google Scholar] [CrossRef] [PubMed]
  86. Hughes, M.T.; Matrosovich, M.; Rodgers, M.E.; McGregor, M.; Kawaoka, Y. Influenza A viruses lacking sialidase activity can undergo multiple cycles of replication in cell culture, eggs, or mice. J. Virol. 2000, 74, 5206–5212. [Google Scholar] [CrossRef] [PubMed]
  87. Evans, C.; Pond, D.; Wilson, W. Changes in Emiliania huxleyi fatty acid profiles during infection with E. huxleyi virus 86: physiological and ecological implications. Aquat. Microb. Ecol. 2009, 55, 219–228. [Google Scholar] [CrossRef]
  88. Stoecker, D.K.; Hansen, P.J.; Caron, D.A.; Mitra, A. Mixotrophy in the Marine Plankton. Ann. Rev. Mar. Sci. 2016, 9, 311–335. [Google Scholar] [CrossRef] [PubMed]
  89. Fischer, M.G.; Allen, M.J.; Wilson, W.H.; Suttle, C.A. Giant virus with a remarkable complement of genes infects marine zooplankton. Proc. Natl. Acad. Sci. USA 2010, 107, 19508–19513. [Google Scholar] [CrossRef] [PubMed]
  90. Rokitta, S.D.; de Nooijer, L.J.; Trimborn, S.; de Vargas, C.; Rost, B.; John, U. Transcriptome analyses reveal differential gene expression patterns between the life-cycle stages of Emiliania huxleyi (haptophyta) and reflect specialization to different ecological niches. J. Phycol. 2011, 47, 829–838. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Viruses 09 00052 g001 550
Figure 1. Phylogenetic analysis of coccolithoviruses based on their DNA polymerase and serine palmitoyltransferase (SPT) genes. The evolutionary history of 13 EhV strains was inferred based on the 2604 bp long SPT (I and II) and 2921 bp long DNA polymerase (III and IV) genes, using the Neighbor-Joining (I and III) and Maximum Likelihood (II and IV) methods. Note that EhV-18 and EhV-145 are absent from the serine palmitoyltransferase tree due to the full length SPT protein being split over two separate genes in their respective genomes. Based on the DNA polymerase phylogeny, the EhVs cluster into two main clades: A and B (green). Clade A is further divided into sub-clusters A1 (red), A2 (yellow), and A3 (purple). The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) are shown next to the branches. The evolutionary distances were computed using the Tamura-Nei method and are in the units of the number of base substitutions per site.
Figure 1. Phylogenetic analysis of coccolithoviruses based on their DNA polymerase and serine palmitoyltransferase (SPT) genes. The evolutionary history of 13 EhV strains was inferred based on the 2604 bp long SPT (I and II) and 2921 bp long DNA polymerase (III and IV) genes, using the Neighbor-Joining (I and III) and Maximum Likelihood (II and IV) methods. Note that EhV-18 and EhV-145 are absent from the serine palmitoyltransferase tree due to the full length SPT protein being split over two separate genes in their respective genomes. Based on the DNA polymerase phylogeny, the EhVs cluster into two main clades: A and B (green). Clade A is further divided into sub-clusters A1 (red), A2 (yellow), and A3 (purple). The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) are shown next to the branches. The evolutionary distances were computed using the Tamura-Nei method and are in the units of the number of base substitutions per site.
Viruses 09 00052 g001
Viruses 09 00052 g002 550
Figure 2. Whole genome alignment of sequenced coccolithovirus genomes. The genomes were aligned using MAUVE, in relation to the non-gapped backbone genome of EhV-86. Syntenous blocks are indicated in the same colours and the lines that connect them indicate the position of each block in relation to the same block of genes in the genome of EhV-86. The small red lines on each genome represent the exact positions of the gaps that separate the different contigs within each draft genome. The genomes are ordered based on their DNA polymerase phylogeny (Figure 1), based on the ANI analysis of this study (Table 2), and based on previously published microarray data that puts them into the aforementioned groups and sub-clades [20].
Figure 2. Whole genome alignment of sequenced coccolithovirus genomes. The genomes were aligned using MAUVE, in relation to the non-gapped backbone genome of EhV-86. Syntenous blocks are indicated in the same colours and the lines that connect them indicate the position of each block in relation to the same block of genes in the genome of EhV-86. The small red lines on each genome represent the exact positions of the gaps that separate the different contigs within each draft genome. The genomes are ordered based on their DNA polymerase phylogeny (Figure 1), based on the ANI analysis of this study (Table 2), and based on previously published microarray data that puts them into the aforementioned groups and sub-clades [20].
Viruses 09 00052 g002
Viruses 09 00052 g003 550
Figure 3. “Best BLAST hit” analysis of coccolithovirus CDSs in relation to the three domains of life: Eukarya, Bacteria and Archaea. Predicted genes within EhV genomes were BLASTp analyzed against possible hits in the three domains of life using a gene BitScore of >50 (A); and >100 (B). Further EhV gene hits analysis to the taxonomic level of “order” in Eukarya (C); and Bacteria (D) was performed using a BitScore of >100.
Figure 3. “Best BLAST hit” analysis of coccolithovirus CDSs in relation to the three domains of life: Eukarya, Bacteria and Archaea. Predicted genes within EhV genomes were BLASTp analyzed against possible hits in the three domains of life using a gene BitScore of >50 (A); and >100 (B). Further EhV gene hits analysis to the taxonomic level of “order” in Eukarya (C); and Bacteria (D) was performed using a BitScore of >100.
Viruses 09 00052 g003
Table
Table 1. A brief description of the coccolithoviruses used in this study, their geographical origin, year of isolation and sea water depth from which they were obtained.
Table 1. A brief description of the coccolithoviruses used in this study, their geographical origin, year of isolation and sea water depth from which they were obtained.
Strain #IsolateIsolationLat/LongDepth (m)DateNCBIReference *
LocationDateSequencedAccession #
EhV-84E.C.199950°15′ N, 04°13′ W152011JF974290Schroeder et al., 2002 [2]; Nissimov et al., 2011 [45]
EhV-86E.C.199950°30′ N, 04°20′ Wsurface2005AJ890364Schroeder et al., 2002 [2]; Wilson et al., 2005 [1]
EhV-88E.C.199950°15′ N, 04°13′ W52011JF974310Schroeder et al., 2002 [2]; Nissimov et al., 2012 [46]
EhV-201E.C.200149°56′ N, 04°19′ W22011JF974311Schroeder et al., 2002 [2]; Nissimov et al., 2012 [46]
EhV-202E.C.200150°00′ N, 04°18′ W152011HQ634145Schroeder et al., 2002 [2]; Nissimov et al., 2012 [47]
EhV-203E.C.200150°00′ N, 04°18′ W152011JF974291Schroeder et al., 2002 [2]; Nissimov et al., 2011 [48]
EhV-207E.C.200150°15′ N, 04°13′ W52011JF974317Schroeder et al., 2002 [2]; Nissimov et al., 2012 [46]
EhV-208E.C.200150°15′ N, 04°13′ W52011JF974318Schroeder et al., 2002 [2]; Nissimov et al., 2012 [46]
EhV-99B1N.F.199960°20′ N, 05°20′ Esurface2013FN429076Pagarete et al., 2013 [44]
EhV-18E.C.200850°15′ N, 04°13′ Wsurface2013KF481685Nissimov et al., 2014 [49]
EhV-145Loss.200857°72′ N, 03°29′Wsurface2013KF481686Nissimov et al., 2014 [49]
EhV-156E.C.200950°15′ N, 04°13′ Wsurface2013KF481687Nissimov et al., 2014 [49]
EhV-164SSF.200956°26′ N, 02°63′ Wsurface2013KF481688Nissimov et al., 2014 [49]
* The references refer to literature that first presented information on each isolate or its genome. E.C.: English Channel; N.F.: Norwegian Fjord; Loss: Lossiemouth (off the UK coast); SSF.: Scottish Shore of Fife (UK).
Table
Table 2. Average Nucleotide Identity (ANI) analysis of EhV genomes against EhV-86. The analysis included 12 draft EhV genomes, where a higher ANI score indicates greater genome similarity.
Table 2. Average Nucleotide Identity (ANI) analysis of EhV genomes against EhV-86. The analysis included 12 draft EhV genomes, where a higher ANI score indicates greater genome similarity.
Reference GenomeDraft GenomeANI ScoreTotal BBH *Clade
EhV-86EhV-16499.95443A1
EhV-14599.93456A1
EhV-8499.07434A1
EhV-8898.96442A1
EhV-99B198.23421A3
EhV-20896.78399A2
EhV-20796.67411A2
EhV-20196.6399A2
EhV-20396.6402A2
EhV-1879.52307B
EhV-20279.42312B
EhV-15679.4308B
* BBH: bidirectional best hit.
Table
Table 3. Predicted genomic characteristics of sequenced coccolithoviruses. The statistics for each genome were obtained from the annotated ordered genomes uploaded into the Integrated Microbial Genomes—Expert Review (IMG/ER) online genome analysis pipeline [66]. Note that the numbers of genes, bases, coding sequences (CDSs), coding bases and transfer RNAs (tRNAs) here are underestimates (except for EhV-86) due to incomplete genome sequences.
Table 3. Predicted genomic characteristics of sequenced coccolithoviruses. The statistics for each genome were obtained from the annotated ordered genomes uploaded into the Integrated Microbial Genomes—Expert Review (IMG/ER) online genome analysis pipeline [66]. Note that the numbers of genes, bases, coding sequences (CDSs), coding bases and transfer RNAs (tRNAs) here are underestimates (except for EhV-86) due to incomplete genome sequences.
Genome NameGenesTotal BasesCDSCoding BasesGenes with Function PredictiontRNAsGC (%)Number of Gaps in Genome
E. huxleyi virus 8448639662048233446385440.178
E. huxleyi virus 8647840733947236915790540.180
E. huxleyi virus 88 48039729847535780390540.187
E. huxleyi virus 20145740730145136371489640.466
E. huxleyi virus 202 48840751648535221593340.311
E. huxleyi virus 203 47040052046436417891640.125
E. huxleyi virus 20747942189147337131393640.4915
E. huxleyi virus 208 46141100345534838690640.4216
E. huxleyi virus 99B145137675944433340090640.0416
E. huxleyi virus 1850839965150334616191540.4921
E. huxleyi virus 145552397508548350414103439.9441
E. huxleyi virus 15649839934449335108388540.4719
E. huxleyi virus 16451440067551035429095440.1117
Table
Table 4. Genes predicted to encode tRNAs in the genomes of 13 coccolithoviruses. Their presence (+) in each genome is indicated, and in grey shaded cells are those tRNAs common to all genomes. The phylogenetic clade of each genome (based on their DNA polymerase gene) is indicated above the column headers (see Figure 1). It is important to note that some of these tRNAs may still be present in the genomes of some EhVs in the unsequenced parts between the different contigs.
Table 4. Genes predicted to encode tRNAs in the genomes of 13 coccolithoviruses. Their presence (+) in each genome is indicated, and in grey shaded cells are those tRNAs common to all genomes. The phylogenetic clade of each genome (based on their DNA polymerase gene) is indicated above the column headers (see Figure 1). It is important to note that some of these tRNAs may still be present in the genomes of some EhVs in the unsequenced parts between the different contigs.
Phylogenetic GroupAB
A1A2A3
tRNAGenomeEhV-84EhV-86EhV-88EhV-164EhV-145EhV-201EhV-203EhV-207EhV-208EhV-99B1EhV-18EhV-156EhV-202
Arg +++++++++++++
Asn +++++++++++++
Gln +++++++++++++
Glu ++++
Ile +++++ +
Leu + +++++++
Lys + +++++++
Table
Table 5. Coccolithovirus strain-specific CDSs that are not shared among the different viruses and are “unique” to each strain. Analysis was done using the “build in BLASTp” algorithm in IMG/ER [61] using a maximum E-value of 1 × 10−5 and a minimum % identity of 30. The phylogenetic clades regrouping genomes are shown above the column headers (see Figure 1).
Table 5. Coccolithovirus strain-specific CDSs that are not shared among the different viruses and are “unique” to each strain. Analysis was done using the “build in BLASTp” algorithm in IMG/ER [61] using a maximum E-value of 1 × 10−5 and a minimum % identity of 30. The phylogenetic clades regrouping genomes are shown above the column headers (see Figure 1).
Phylogenetic GroupAB
A1A2A3
Predicted CDSEhV-84EhV-86EhV-88EhV-145EhV-164EhV-201EhV-203EhV-207EhV-208EhV-99B1EhV-202EhV-18EhV-156
hypothetical protein273478449961896
putative endonuclease 2
putative membrane protein 2 11 4
putative transposase 1
putative DUF814 domain containing protein 1
zinc finger protein 1
putative ribonuclease 11
glycosyltransferase family 29 (sialyltransferase) 11
Total27548945991518118
Table
Table 6. “Best BLAST hit” analysis of EhVs against the Bacterial and Eukaryotic domains of life, as well as against the known host Emiliania huxleyi. The top EhV genes with function predictions are shown based on the “Best BLAST hit” analysis using a BitScore of >100 and are ordered based on their E-value. The COG (Clusters of Orthologous Groups of genes with similar functions across the domains of life) cluster for each gene was identified on IMG/ER, where the different letters represent metabolic pathways involved in nucleotide transport and metabolism [F]; carbohydrate transport and metabolism [G]; general function prediction only [R]; replication, recombination and repair [L]; lipid transport and metabolism [I]; transcription [K]; inorganic ion transport and metabolism [P]; intracellular trafficking, and secretion and vesicular transport [U].
Table 6. “Best BLAST hit” analysis of EhVs against the Bacterial and Eukaryotic domains of life, as well as against the known host Emiliania huxleyi. The top EhV genes with function predictions are shown based on the “Best BLAST hit” analysis using a BitScore of >100 and are ordered based on their E-value. The COG (Clusters of Orthologous Groups of genes with similar functions across the domains of life) cluster for each gene was identified on IMG/ER, where the different letters represent metabolic pathways involved in nucleotide transport and metabolism [F]; carbohydrate transport and metabolism [G]; general function prediction only [R]; replication, recombination and repair [L]; lipid transport and metabolism [I]; transcription [K]; inorganic ion transport and metabolism [P]; intracellular trafficking, and secretion and vesicular transport [U].
Major Hits against Eukarya
Ehv Predicted GeneCOG IDIdentity (%)E-ValueBit-ScorePhylumClassOrderGenus
DNA-directed RNA polymerase subunit BK40.390825NANADictyosteliidaDictyostelium
DNA ligaseL51.290612ChlorophytaMamiellophyceaeMamiellalesMicromonas
DNA topoisomeraseL330586MicrosporidiaNANANematocida
DNA-dependent RNA polymerase II largest subunitK34.097 × 10−171555AscomycotaSordariomycetesXylarialesEutypa
thymidylate synthaseF49.71 × 10−168497NANAPeronosporalesPhytophthora
DNA polymerase delta catalytic subunitL35.112 × 10−132436ArthropodaMalacostracaDecapodaProcambarus
DNA helicaseL49.33 × 10−137419BacillariophytaCoscinodiscophyceaeThalassiosiralesThalassiosira
Major Hits against Bacteria
deoxycytidylate deaminaseF62.968 × 10−64206FirmicutesClostridiaClostridialesClostridium
SialidaseG30.032 × 10−37148BacteroidetesSphingobacteriiaSphingobacterialesSphingobacterium
DNA-binding proteinR34.367 × 10−32129VerrucomicrobiaNANANA
endonucleaseL45.674 × 10−32121ProteobacteriaAlphaproteobacteriaRhizobialesPseudochrobactrum
fatty acid desaturaseI34.762 × 10−28121ProteobacteriaAlphaproteobacteriaRhodospirillalesNiveispirillum
NA: NCBI classification was not available for Phylum, Class, Order or Genus.

Share and Cite

MDPI and ACS Style

Nissimov, J.I.; Pagarete, A.; Ma, F.; Cody, S.; Dunigan, D.D.; Kimmance, S.A.; Allen, M.J. Coccolithoviruses: A Review of Cross-Kingdom Genomic Thievery and Metabolic Thuggery. Viruses 2017, 9, 52. https://doi.org/10.3390/v9030052

AMA Style

Nissimov JI, Pagarete A, Ma F, Cody S, Dunigan DD, Kimmance SA, Allen MJ. Coccolithoviruses: A Review of Cross-Kingdom Genomic Thievery and Metabolic Thuggery. Viruses. 2017; 9(3):52. https://doi.org/10.3390/v9030052

Chicago/Turabian Style

Nissimov, Jozef I., António Pagarete, Fangrui Ma, Sean Cody, David D. Dunigan, Susan A. Kimmance, and Michael J. Allen. 2017. "Coccolithoviruses: A Review of Cross-Kingdom Genomic Thievery and Metabolic Thuggery" Viruses 9, no. 3: 52. https://doi.org/10.3390/v9030052

APA Style

Nissimov, J. I., Pagarete, A., Ma, F., Cody, S., Dunigan, D. D., Kimmance, S. A., & Allen, M. J. (2017). Coccolithoviruses: A Review of Cross-Kingdom Genomic Thievery and Metabolic Thuggery. Viruses, 9(3), 52. https://doi.org/10.3390/v9030052

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop