Nothing Special   »   [go: up one dir, main page]

You seem to have javascript disabled. Please note that many of the page functionalities won't work as expected without javascript enabled.
 
 
Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

Article Types

Countries / Regions

Search Results (7)

Search Parameters:
Keywords = Prasinovirus

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
17 pages, 2550 KiB  
Article
Functional Profiling and Evolutionary Analysis of a Marine Microalgal Virus Pangenome
by Briallen Lobb, Anson Shapter, Andrew C. Doxey and Jozef I. Nissimov
Viruses 2023, 15(5), 1116; https://doi.org/10.3390/v15051116 - 5 May 2023
Cited by 2 | Viewed by 2686
Abstract
Phycodnaviridae are large double-stranded DNA viruses, which facilitate studies of host–virus interactions and co-evolution due to their prominence in algal infection and their role in the life cycle of algal blooms. However, the genomic interpretation of these viruses is hampered by a lack [...] Read more.
Phycodnaviridae are large double-stranded DNA viruses, which facilitate studies of host–virus interactions and co-evolution due to their prominence in algal infection and their role in the life cycle of algal blooms. However, the genomic interpretation of these viruses is hampered by a lack of functional information, stemming from the surprising number of hypothetical genes of unknown function. It is also unclear how many of these genes are widely shared within the clade. Using one of the most extensively characterized genera, Coccolithovirus, as a case study, we combined pangenome analysis, multiple functional annotation tools, AlphaFold structural modeling, and literature analysis to compare the core and accessory pangenome and assess support for novel functional predictions. We determined that the Coccolithovirus pangenome shares 30% of its genes with all 14 strains, making up the core. Notably, 34% of its genes were found in at most three strains. Core genes were enriched in early expression based on a transcriptomic dataset of Coccolithovirus EhV-201 algal infection, were more likely to be similar to host proteins than the non-core set, and were more likely to be involved in vital functions such as replication, recombination, and repair. In addition, we generated and collated annotations for the EhV representative EhV-86 from 12 different annotation sources, building up information for 142 previously hypothetical and putative membrane proteins. AlphaFold was further able to predict structures for 204 EhV-86 proteins with a modelling accuracy of good–high. These functional clues, combined with generated AlphaFold structures, provide a foundational framework for the future characterization of this model genus (and other giant viruses) and a further look into the evolution of the Coccolithovirus proteome. Full article
(This article belongs to the Section General Virology)
Show Figures

Figure 1

Figure 1
<p>Phylogeny, geographical origin, and pangenome density of available Coccolithovirus genomes: (<b>A</b>) The phylogeny displayed here is a midpoint-rooted cladogram created with RAxML (GTRGAMMA) from the panX alignment data. The phylogeny with branch lengths displayed is in <a href="#app1-viruses-15-01116" class="html-app">Figure S1</a>. CDS numbers are from NCBI GenBank files and are slightly different than previously reported numbers in Nissimov et al. [<a href="#B12-viruses-15-01116" class="html-bibr">12</a>] from an alternate pipeline. (<b>B</b>) Approximate sampling locations around the coast of Great Britain and Norway. For exact GPS coordinates and depth, see <a href="#app1-viruses-15-01116" class="html-app">Table S1</a>. (<b>C</b>) Gene distribution across the 14 Coccolithovirus genomes, with the number of genes found in each genome. An aligned relative density estimate of the histogram is displayed on the alternative <span class="html-italic">y</span>-axis (right). The darker column represents genes that were shared across every Coccolithovirus strain in the pangenome. Re-annotated Coccolithoviruses (using Prokka) were also used to create a pangenome (displayed in <a href="#app1-viruses-15-01116" class="html-app">Figure S2</a>) with a very similar distribution (core genes changing from 30.25% to 34.50% of the pangenome).</p>
Full article ">Figure 2
<p>Genome comparison of Coccolithoviruses using EhV-86 as a representative. NC_007346 was used as the query against all Coccolithovirus genomes. The percent alignment identity across regions of EhV-86 to other Coccolithovirus strains is indicated based on colour intensity. Rings (EhV strains) are coloured and grouped by subclade. The black bar indicates a long region of interest with predominantly core genes. Generated with BLAST Ring Image Generator (BRIG) v0.95 [<a href="#B41-viruses-15-01116" class="html-bibr">41</a>]. This alignment shows the genetic content in the pangenome in relation to EhV-86. The genomes have different lengths and different numbers of genes (see <a href="#app1-viruses-15-01116" class="html-app">Table S1</a>). For an overview of the pangenome gene presence/absence, see <a href="#app1-viruses-15-01116" class="html-app">Figure S2</a>.</p>
Full article ">Figure 3
<p>Annotation coverage and AlphaFold results for EhV-86: (<b>A</b>) All 12 annotation sources collected and/or generated for EhV-86. Any proteins called “hypothetical protein”, “putative membrane protein”, “uncharacterized protein”, or (in the case of EggNOG) not having any free text description were not included as “annotated”. Combined indicates all proteins with at least one annotation in any of the other categories. The Ku et al. [<a href="#B16-viruses-15-01116" class="html-bibr">16</a>] annotation set is a manual curation of EhV-201 annotations from other papers as well as BLAST searches against a variety of databases. The PDB (remote homology) annotations were retrieved from Mirzakhanyan and Gershon [<a href="#B28-viruses-15-01116" class="html-bibr">28</a>]. These data are included in <a href="#app1-viruses-15-01116" class="html-app">Table S4</a>. (<b>B</b>) Frequency of COG categories in Coccolithoviruses, divided into the core and accessory pangenome. Frequency here is the number of genes with the COG category in a genome. Counts less than 3 are not labelled. COG annotations derive from the EggNOG annotation database using emapper v2.0.1b. This method, likely due to genetic differences, does not always annotate every gene clustered together by panX in the same way (meaning that core genes do not always have equal counts of functorial categories across the figure). (<b>C</b>) The chain pLDDT scores for the best scoring model AlphaFold predicted for EhV-86 proteins. Chain pLDDT (predicted local distance difference test) scores closer to 100 show greater overall model confidence, being an average of the per-residue pLDDT values across the entire predicted structure.</p>
Full article ">Figure 4
<p>The majority taxonomy from EhV-86 BLASTP hits divided into different alignment percent identity ranges. The denominator for the percentages on the <span class="html-italic">x</span>-axis is indicated on the <span class="html-italic">y</span>-axis after the pangenome category (i.e., Core (240)). This is the number of EhV-86 proteins that had a majority taxonomy for that alignment percent identity range. The taxonomy in the legend is indented to indicate the taxonomic level. Only taxa present at greater than two percent within their category (<span class="html-italic">y</span>-axis) are displayed here. A full table of these data is available in <a href="#app1-viruses-15-01116" class="html-app">Table S7</a>.</p>
Full article ">Figure 5
<p>EhV-201 expression data from Ku et al. (2020) [<a href="#B16-viruses-15-01116" class="html-bibr">16</a>] broken up into core and accessory genes based on the pangenome analysis. The infection phase categories on the <span class="html-italic">x</span>-axis are from a hierarchical clustering analysis (MetaCell method using the k-nearest neighbor graph partitions) of the expression data performed by Ku et al. [<a href="#B16-viruses-15-01116" class="html-bibr">16</a>] looking at a 0–24 h post-infection time range of <span class="html-italic">E. huxleyi</span> CCMP2090 infected by EhV-201.</p>
Full article ">
15 pages, 2192 KiB  
Article
Sediments from Arctic Tide-Water Glaciers Remove Coastal Marine Viruses and Delay Host Infection
by Douwe S. Maat, Maarten A. Prins and Corina P. D. Brussaard
Viruses 2019, 11(2), 123; https://doi.org/10.3390/v11020123 - 30 Jan 2019
Cited by 19 | Viewed by 5719
Abstract
Over the past few decades, the Arctic region has been strongly affected by global warming, leading to increased sea surface temperatures and melting of land and sea ice. Marine terminating (tide-water) glaciers are expected to show higher melting and calving rates, with an [...] Read more.
Over the past few decades, the Arctic region has been strongly affected by global warming, leading to increased sea surface temperatures and melting of land and sea ice. Marine terminating (tide-water) glaciers are expected to show higher melting and calving rates, with an increase in the input of fine sediment particles in the coastal marine environment. We experimentally investigated whether marine viruses, which drive microbial interactions and biogeochemical cycling are removed from the water column through adsorption to glacier-delivered fine sediments. Ecologically relevant concentrations of 30, 100 and 200 mg·L−1 sediments were added to filtered lysates of 3 cultured algal viruses and to a natural marine bacterial virus community. Total virus removal increased with sediment concentration whereby the removal rate depended on the virus used (up to 88% for an Arctic algal virus), suggesting a different interaction strength with the sediment. Moreover, we observed that the adsorption of viruses to sediment is a reversible process, and that desorbed viruses are still able to infect their respective hosts. Nonetheless, the addition of sediment to infection experiments with the Arctic prasinovirus MpoV-45T substantially delayed host lysis and the production of progeny viruses. We demonstrate that glacier-derived fine sediments have the potency to alter virus availability and consequently, host population dynamics. Full article
(This article belongs to the Special Issue Viruses of Microbes V: Biodiversity and Future Applications)
Show Figures

Figure 1

Figure 1
<p>Size distribution of glacier-derived sediment that was used for the adsorption-removal experiments. The <span class="html-italic">y</span>-axis shows the relative abundance (vol%) of the particles of the different sediment size classes (µm), which are depicted on the <span class="html-italic">x</span>-axis.</p>
Full article ">Figure 2
<p>Relative loss of total viruses (%; mean ± s.d.) compared to the control (no sediment) at T0.15 h, T6 h and T36 h, for MpV-08T (<b>A</b>), MpoV-45T (<b>B</b>), PgV-07T (<b>C</b>) and NVC (<b>D</b>) and with final sediment concentrations of 30, 100 and 200 mg·L<sup>−1</sup>. Asterisks (*) above the bars show which treatments are significantly different (<span class="html-italic">p</span> &lt; 0.05) from the control.</p>
Full article ">Figure 3
<p>Mean (±s.d.) viral abundances over time, during the 200 mg·L<sup>−1</sup> adsorption-removal experiments of undiluted MpoV-45T, with clean sediment and sediment that was exposed to either untreated or sonicated PgV-07T lysate to test the influence of detritus on virus removal. The abundances right before sediment addition (T0 h) are depicted on the left side of the vertical dotted line. Further sampling was done at T0, T6 and T36 h. The letters in the graphs above the bars show a significant difference with the control (a) or the 200 mg·L<sup>−1</sup> treatment without detritus (lysate; b).</p>
Full article ">Figure 4
<p>Abundances over time of uninfected (<b>A</b>) and infected (<b>B</b>) <span class="html-italic">M. polaris</span> TX-01, and the virus MpoV-45T (<b>C</b>) with and without 200 mg·L<sup>−1</sup> sediment, during a one-step infection experiment (virus:host ratio = 10:1). The “no sediment” treatments are depicted with black symbols. Sediment was either added to the cultures at the same time as the lysate (“with lysate treatment”; white symbols) or mixed with the lysate first and then added to the host culture (“added to lysate first treatment”; grey symbols). Algae are depicted with circles and viruses with triangles. The inlay in panel C shows the viral abundances in the first 24 h in detail.</p>
Full article ">Figure 5
<p>Abundances over time of uninfected (<b>A</b>) and infected (<b>B</b>) <span class="html-italic">M. polaris</span> TX-01, and the virus MpoV-45T (<b>C</b>,<b>D</b>) with and without 30 or 200 mg·L<sup>−1</sup> sediment, during a two-step infection experiment (virus:host ratio = 0.5:1). Black, white and grey symbols represent 0, 30 and 100 mg·L<sup>−1</sup> sediment, with algae as circles and viruses as triangles. Panel D represents a detail of panel C, displaying the viral abundances during the first 75 h.</p>
Full article ">
11 pages, 3430 KiB  
Article
Rapidity of Genomic Adaptations to Prasinovirus Infection in a Marine Microalga
by Sheree Yau, Gaëtan Caravello, Nadège Fonvieille, Élodie Desgranges, Hervé Moreau and Nigel Grimsley
Viruses 2018, 10(8), 441; https://doi.org/10.3390/v10080441 - 19 Aug 2018
Cited by 5 | Viewed by 4772
Abstract
Prasinoviruses are large dsDNA viruses commonly found in aquatic systems worldwide, where they can infect and lyse unicellular prasinophyte algae such as Ostreococcus. Host susceptibility is virus strain-specific, but resistance of susceptible Ostreococcus tauri strains to a virulent virus arises frequently. In [...] Read more.
Prasinoviruses are large dsDNA viruses commonly found in aquatic systems worldwide, where they can infect and lyse unicellular prasinophyte algae such as Ostreococcus. Host susceptibility is virus strain-specific, but resistance of susceptible Ostreococcus tauri strains to a virulent virus arises frequently. In clonal resistant lines that re-grow, viruses are usually present for many generations, and genes clustered on chromosome 19 show physical rearrangements and differential expression. Here, we investigated changes occurring during the first two weeks after inoculation of the prasinovirus OtV5. By serial dilutions of cultures at the time of inoculation, we estimated the frequency of resistant cells arising in virus-challenged O. tauri cultures to be 10−3–10−4 of the inoculated population. Re-growing resistant cells were detectable by flow cytometry 3 days post-inoculation (dpi), visible re-greening of cultures occurred by 6 dpi, and karyotypic changes were visually detectable at 8 dpi. Resistant cell lines showed a modified spectrum of host-virus specificities and much lower levels of OtV5 adsorption. Full article
(This article belongs to the Special Issue Algae Virus)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Host cell dynamics during a lytic infection. Each point represents an average from five independent cultures of <span class="html-italic">O. tauri</span>. Lysis occurs over two days following OtV5 inoculation, but at 3 days post-inoculation (dpi) OtV5-resistant cells observed by flow cytometry were growing, visible re-greening of the cultures occurring by 5 to 6 dpi.</p>
Full article ">Figure 2
<p>Karyotypes of <span class="html-italic">O. tauri</span> cultures visualised by pulsed field gel electrophoresis (PFGE) separation of the chromosomes. The sizes and positions of <span class="html-italic">O. tauri</span> chromosomes are indicated on the left. Chromosome 19 (red numbers) was not visualised in freshly OtV5-resistant test cultures (gel tracks indicated with red annotations at the bottom). <b><span class="html-italic">w.t</span>.</b>: wild-type <span class="html-italic">O. tauri</span> RCC4221 from the original culture used before inoculation. <b>t<sub>0</sub></b>: wild-type <span class="html-italic">O. tauri</span> RCC4221 from the RCC4221 culture at the start of the experiment. <b>C1</b>, <b>C2</b> and <b>C3</b>: mock-inoculated Control cultures at 8 days post-inoculation (dpi). <b>T1–T5</b>: Test cultures inoculated with OtV5 at MOI 5 (colours correspond with those in <a href="#viruses-10-00441-f003" class="html-fig">Figure 3</a> below), 8 dpi. <b><span style="color:red">-</span></b>: absence of chromosome 19 at its expected mobility (312 kb) in test cultures. <b><span style="color:red">v</span></b>: presence of the OtV5 viral genome (184 kb long) in inoculated cultures. <b><span style="color:#0070C0">Blue dots</span></b>: wells with higher fluorescence.</p>
Full article ">Figure 3
<p>Karyotypes of clonal lines <span class="html-italic">O. tauri</span> visualised by PFGE separation of the chromosomes. The figure is a composite of two separate gels. <b>t<sub>0</sub></b>: wild-type <span class="html-italic">O. tauri</span> RCC4221 the start of the experiment. <b>C1</b>, <b>C2</b>, and <b>C3</b>: clonal lines established from mock-inoculated control cultures. <b>T1–T5</b>: Five independent clonal lines were established from each of the Test (T1–T5) OtV5-resistant cultures shown in <a href="#viruses-10-00441-f002" class="html-fig">Figure 2</a>, i.e., five lines from each of the five cultures (labelled and boxed with similar colours in both figures). Annotations underneath the gel tracks show which tracks have bands with altered mobilities. <b><span style="color:red">-</span></b>: absence of chromosome 19 at its expected mobility (0.3 Mb, indicated position in bold on the left) in test cultures. <b><span style="color:red">+</span></b>: presence of a chromosomal band not detected in Control cultures. <b><span style="color:red">v</span></b>: presence of the OtV5 viral genome (184 kb long) in inoculated cultures.</p>
Full article ">Figure 4
<p>(<b>Left</b>): uninfected cultures. (<b>Right</b>): cells inoculated with OtV5 at MOI 5, as shown in the table. Each of the 16 columns of wells is a separate culture, diluted as shown in the table in rows top (least dilute) to bottom (most dilute). Green dots indicate the most dilute step of the series in which host cell growth was visible in a proportion of the cultures.</p>
Full article ">Figure 5
<p>Altered spectrum of virus resistance in OtV5-resistant <span class="html-italic">O. tauri</span> lines. <b>+</b>: complete or almost complete host cell lysis <b>-</b>: no or little host cell lysis. <b>?</b>: not possible to determine. Orange background cell: result on susceptible <span class="html-italic">O. tauri</span> control differed from previous observation [<a href="#B22-viruses-10-00441" class="html-bibr">22</a>]. Blue background cell: result that differed to the null hypothesis that the susceptibility of this strain would be the same as that previously observed (S1a to S8a controls and those of a past paper [<a href="#B22-viruses-10-00441" class="html-bibr">22</a>]). Note that OtV5 is not highlighted since these lines were selected for their resistance to this virus. <b>S</b>: susceptible clonal line [<a href="#B19-viruses-10-00441" class="html-bibr">19</a>]. <b>R</b>: resistant clonal line [<a href="#B19-viruses-10-00441" class="html-bibr">19</a>]. <b>vir2012</b>: The number of independently isolated wild-type <span class="html-italic">O. tauri</span> strains on which the viral isolate shown was noted as virulent out of 12 tested previously [<a href="#B22-viruses-10-00441" class="html-bibr">22</a>] (excluding the strain on which the virus was isolated).</p>
Full article ">Figure 6
<p>Acquired resistance reduces adsorption of OtV5. Ten algal strains (abscissa) were each assayed six times (grey bars) for their ability to bind to OtV5. <b>Ot</b>: control susceptible wild-type <span class="html-italic">O. tauri</span> RCC4221, <b>Ps</b>: <span class="html-italic">Picochlorum</span> sp. RCC4223, <b>Bp</b>: <span class="html-italic">Bathycoccus</span> sp. RCC4222, <b>R</b>: OtV5-resistant line [<a href="#B19-viruses-10-00441" class="html-bibr">19</a>].</p>
Full article ">
4236 KiB  
Article
Characterization and Temperature Dependence of Arctic Micromonas polaris Viruses
by Douwe S. Maat, Tristan Biggs, Claire Evans, Judith D. L. Van Bleijswijk, Nicole N. Van der Wel, Bas E. Dutilh and Corina P. D. Brussaard
Viruses 2017, 9(6), 134; https://doi.org/10.3390/v9060134 - 2 Jun 2017
Cited by 40 | Viewed by 11419
Abstract
Global climate change-induced warming of the Artic seas is predicted to shift the phytoplankton community towards dominance of smaller-sized species due to global warming. Yet, little is known about their viral mortality agents despite the ecological importance of viruses regulating phytoplankton host dynamics [...] Read more.
Global climate change-induced warming of the Artic seas is predicted to shift the phytoplankton community towards dominance of smaller-sized species due to global warming. Yet, little is known about their viral mortality agents despite the ecological importance of viruses regulating phytoplankton host dynamics and diversity. Here we report the isolation and basic characterization of four prasinoviruses infectious to the common Arctic picophytoplankter Micromonas. We furthermore assessed how temperature influenced viral infectivity and production. Phylogenetic analysis indicated that the putative double-stranded DNA (dsDNA) Micromonas polaris viruses (MpoVs) are prasinoviruses (Phycodnaviridae) of approximately 120 nm in particle size. One MpoV showed intrinsic differences to the other three viruses, i.e., larger genome size (205 ± 2 vs. 191 ± 3 Kb), broader host range, and longer latent period (39 vs. 18 h). Temperature increase shortened the latent periods (up to 50%), increased the burst size (up to 40%), and affected viral infectivity. However, the variability in response to temperature was high for the different viruses and host strains assessed, likely affecting the Arctic picoeukaryote community structure both in the short term (seasonal cycles) and long term (global warming). Full article
(This article belongs to the Special Issue Marine Viruses 2016)
Show Figures

Figure 1

Figure 1
<p>Transmission electron micrographs of thin sections of the uninfected <span class="html-italic">Micromonas</span> strain TX-01 (<b>A</b>,<b>B</b>), and infected with virus MpoV-44T (<b>C</b>,<b>D</b>), 45T (<b>E</b>), 46T (<b>F</b>–<b>H</b>), and 47T (<b>I</b>,<b>J</b>). Scale bar represents 200 nm (<b>A</b>,<b>C</b>,<b>D</b>,<b>I</b>) or 500 nm (<b>B</b>,<b>E</b>–<b>H</b>,<b>J</b>).</p>
Full article ">Figure 2
<p>Position of the four <span class="html-italic">Micromonas polaris</span> viruses (MpoVs) (in bold) in a maximum likelihood dendrogram (100 bootstrap replicates), based on a multiple alignment of 178 amino acid positions of DNA polymerase B (<span class="html-italic">polB</span>). Only nodes with bootstrap values &gt;50% are displayed. Virus strains and accession numbers are indicated. “Contigs” are <span class="html-italic">polB</span> sequences extracted from an Arctic marine metagenome [<a href="#B22-viruses-09-00134" class="html-bibr">22</a>]. The tree was rooted using <span class="html-italic">polB</span> sequences of <span class="html-italic">Bathycoccus</span> viruses.</p>
Full article ">Figure 3
<p>Abundances of <span class="html-italic">Micromonas</span> cells (×10<sup>6</sup> mL<sup>−1</sup>) and viruses MpoV-44T, 45T, 46T, and 47T (×10<sup>8</sup> mL<sup>−1</sup>) infecting host strain TX-01. Panel (<b>A</b>) shows the algal abundances (mean ± standard deviation (S.D.) over time, with the filled circles depicting the non-infected control cultures, open circles depicting the cultures infected with MpoV-44T, filled triangles depicting the ones infected with MpoV-45T, closed triangles depicting the ones infected with MpoV-46T, and the filled squares depicting the ones infected with MpoV-47T. The inlay panel shows the growth of the non-infected controls in detail. Panel (<b>B</b>) shows the viral abundances (mean ± S.D.) over time, with the symbols corresponding to panel (<b>A</b>), i.e., each virus is depicted by the same symbol as the culture it infected.</p>
Full article ">Figure 4
<p>Effects of temperature exposure on the infectivity of MpoV-44T, 45T, 46T, and 47T (actual infection assay performed at 3 °C). The <span class="html-italic">x</span>-axis depicts the exposure temperature and the <span class="html-italic">y</span>-axis depicts the relative infectivity (normalized to highest infectivity) of the virus as determined by the most probable number (MPN) dilution assay. r.u. stands for relative units. Error bars show standard error (<span class="html-italic">n</span> = 5).</p>
Full article ">Figure 5
<p>Abundances of <span class="html-italic">Micromonas</span> strain TX-01 (×10<sup>5</sup> mL<sup>−1</sup>) and virus MpoV-45T <b>(</b>×10<sup>6</sup> mL<sup>−1</sup><b>)</b> tested at 0.5, 2.5, 3.5, and 7.0 °C. Panel (<b>A</b>) shows the algal abundances (mean ± S.D.) over time, with filled circles representing 0.5 °C, filled triangles representing 2.5 °C, open circles representing 3.5 °C, and open triangles representing 7.0 °C. The inlay panel shows the growth of the non-infected controls. Panel (<b>B</b>) shows the viral abundances (mean ± S.D.) over time, with the symbols corresponding to panel A, i.e., each virus is depicted by the same symbol as the culture it infected. Panel (<b>C</b>) depicts the median viral latent periods (black bars; determined with an 8 h sampling resolution) and viral burst sizes (grey bars; mean ± S.D.).</p>
Full article ">Figure 6
<p>Median latent periods (<b>A</b>) and mean burst sizes (<b>B</b>) of MpoV-45T (left panels) and MpoV-44T (right panels) infecting host TX-01, RCC2257, and RCC2258 at 3 °C (black bars) and 7 °C (grey bars). Note that the TX-01 data are from the same as in <a href="#viruses-09-00134-f005" class="html-fig">Figure 5</a>. The range bars in panel A depict the actual time interval on which the latent period is based. The error bars in panel B depict the standard deviation (S.D.). Statistical analysis of inter- and intra-strain differences are depicted in <a href="#app1-viruses-09-00134" class="html-app">Supplement Table S2</a>.</p>
Full article ">Figure 7
<p>Unrooted maximum likelihood phylogeny of MpoV-related sequences from various studies, and their abundance in environmental metagenomes. Abundance is expressed as the total number of aligned reads out of 2.5 billion reads in 26 Tara Oceans datasets.</p>
Full article ">
2246 KiB  
Article
Variation in the Genetic Repertoire of Viruses Infecting Micromonas pusilla Reflects Horizontal Gene Transfer and Links to Their Environmental Distribution
by Jan F. Finke, Danielle M. Winget, Amy M. Chan and Curtis A. Suttle
Viruses 2017, 9(5), 116; https://doi.org/10.3390/v9050116 - 19 May 2017
Cited by 16 | Viewed by 6731
Abstract
Prasinophytes, a group of eukaryotic phytoplankton, has a global distribution and is infected by large double-stranded DNA viruses (prasinoviruses) in the family Phycodnaviridae. This study examines the genetic repertoire, phylogeny, and environmental distribution of phycodnaviruses infecting Micromonas pusilla, other prasinophytes and [...] Read more.
Prasinophytes, a group of eukaryotic phytoplankton, has a global distribution and is infected by large double-stranded DNA viruses (prasinoviruses) in the family Phycodnaviridae. This study examines the genetic repertoire, phylogeny, and environmental distribution of phycodnaviruses infecting Micromonas pusilla, other prasinophytes and chlorophytes. Based on comparisons among the genomes of viruses infecting M. pusilla and other phycodnaviruses, as well as the genome from a host isolate of M. pusilla, viruses infecting M. pusilla (MpVs) share a limited set of core genes, but vary strongly in their flexible pan-genome that includes numerous metabolic genes, such as those associated with amino acid synthesis and sugar manipulation. Surprisingly, few of these presumably host-derived genes are shared with M. pusilla, but rather have their closest non-viral homologue in bacteria and other eukaryotes, indicating horizontal gene transfer. A comparative analysis of full-length DNA polymerase (DNApol) genes from prasinoviruses with their overall gene content, demonstrated that the phylogeny of DNApol gene fragments reflects the gene content of the viruses; hence, environmental DNApol gene sequences from prasinoviruses can be used to infer their overall genetic repertoire. Thus, the distribution of virus ecotypes across environmental samples based on DNApol sequences implies substantial underlying differences in gene content that reflect local environmental conditions. Moreover, the high diversity observed in the genetic repertoire of prasinoviruses has been driven by horizontal gene transfer throughout their evolutionary history, resulting in a broad suite of functional capabilities and a high diversity of prasinovirus ecotypes. Full article
(This article belongs to the Special Issue Viruses of Microbes)
Show Figures

Figure 1

Figure 1
<p>Venn diagram of shared coding sequences (CDS) of four MpVs and <span class="html-italic">M. pusilla</span> UTEX LB991, based on clusters by 0.5 amino acid identity. Dashed circles represent host genes shared with viruses.</p>
Full article ">Figure 2
<p>Presumed origin of 90 genes with a functional annotation in the four <span class="html-italic">M. pusilla</span> viruses examined in this study. Numbers indicate the number of genes assigned to putative origins. Origin is based on BLAST-P hits against the nr-database.</p>
Full article ">Figure 3
<p>Phylogeny of prasinoviruses infecting the genera <span class="html-italic">Ostreococcus</span> (OtV1, OtV2, OtV5, OtV6, OlV1), <span class="html-italic">Bathyococcus</span> (BpV1, BpV2), <span class="html-italic">Micromonas</span> (MpV1, MpV-12T, MpV-PL1, MpV-SP1), and <span class="html-italic">Chlorella</span> (PBCV1, AR158). The neighbor-joining tree is based on the presence and absence of shared putative genes. Bootstrap values are based on 1000 iterations of sub-sampling.</p>
Full article ">Figure 4
<p>Maximum likelihood tree of prasinoviruses and chloroviruses infecting the genera <span class="html-italic">Ostreococcus</span> (OtV1, OtV2, OtV5, OtV6, OlV1), <span class="html-italic">Bathyococcus</span> (BpV1, BpV2), <span class="html-italic">Micromonas</span> (MpV1, MpV-12T, MpV-PL1, MpV-SP1), and <span class="html-italic">Chlorella</span> (PBCV1, AR158). The phylogeny is based on full-length DNA polymerase B (DNApol) sequences, bootstrap values based on 1000 iterations; the scale bar represents the substitution rate.</p>
Full article ">Figure 5
<p>Variation in phylogenetic distance based on DNApol. The standard deviation (stdv) of the pairwise phylogenetic distances of full-length DNApol sequences of reference virus clusters are shown against their corresponding amplicon equivalents at different levels of % amino acid (aa) identity to demonstrate that amplicon sequences clustered at 97% identity are representative of the full-length sequences.</p>
Full article ">Figure 6
<p>Sampling locations (<b>A</b>) and corresponding environmental parameters, sea surface temperature ((<b>B</b>) SST, °C), photosynthetically-active radiation ((<b>C</b>) PAR, μmol photons m<sup>−2</sup> s<sup>−1</sup>) and Chlorophyll <span class="html-italic">a</span> concentration ((<b>D</b>) Chl, mg m<sup>−3</sup>), all based on 32-day composite data from the Aqua MODIS satellite. Sampling stations: Juan de Fuca Strait (JF), Jericho Pier (JP), Point Atkinson (PA), and Saanich Inlet (SI). lat: Degree latitude; long: Degree longitude.</p>
Full article ">Figure 7
<p>Maximum likelihood tree of 197 partial phycodnavirus DNApol sequences from five environmental samples clustered at 97% aa identity. Reference sequences are highlighted in purple, dominant OTUs and branches for the environmental samples are indicated in green for JP, PA, JF, SI. Black branches represent other operational taxonomic units (OTUs). Bootstrap values indicate branch support, values from 50 to 100% are shown as size-dependent circles.</p>
Full article ">
4697 KiB  
Review
Marine Prasinoviruses and Their Tiny Plankton Hosts: A Review
by Karen D. Weynberg, Michael J. Allen and William H. Wilson
Viruses 2017, 9(3), 43; https://doi.org/10.3390/v9030043 - 15 Mar 2017
Cited by 34 | Viewed by 10184
Abstract
Viruses play a crucial role in the marine environment, promoting nutrient recycling and biogeochemical cycling and driving evolutionary processes. Tiny marine phytoplankton called prasinophytes are ubiquitous and significant contributors to global primary production and biomass. A number of viruses (known as prasinoviruses) that [...] Read more.
Viruses play a crucial role in the marine environment, promoting nutrient recycling and biogeochemical cycling and driving evolutionary processes. Tiny marine phytoplankton called prasinophytes are ubiquitous and significant contributors to global primary production and biomass. A number of viruses (known as prasinoviruses) that infect these important primary producers have been isolated and characterised over the past decade. Here we review the current body of knowledge about prasinoviruses and their interactions with their algal hosts. Several genes, including those encoding for glycosyltransferases, methyltransferases and amino acid synthesis enzymes, which have never been identified in viruses of eukaryotes previously, have been detected in prasinovirus genomes. The host organisms are also intriguing; most recently, an immunity chromosome used by a prasinophyte in response to viral infection was discovered. In light of such recent, novel discoveries, we discuss why the cellular simplicity of prasinophytes makes for appealing model host organism–virus systems to facilitate focused and detailed investigations into the dynamics of marine viruses and their intimate associations with host species. We encourage the adoption of the prasinophyte Ostreococcus and its associated viruses as a model host–virus system for examination of cellular and molecular processes in the marine environment. Full article
(This article belongs to the Special Issue Marine Viruses 2016)
Show Figures

Figure 1

Figure 1
<p>Negatively stained transmission electron microscopy micrographs of (<b>A</b>,<b>B</b>) <span class="html-italic">Micromonas pusilla</span> viruses (MpVs); (<b>C</b>) ‘Spiderweb’-like plate from exterior of <span class="html-italic">Bathycoccus prasinos</span> cell; (<b>D</b>–<b>H</b>) <span class="html-italic">O. tauri</span> viruses (OtVs).</p>
Full article ">Figure 2
<p>Characterisation of the OtV-2 virally encoded cytochrome <span class="html-italic">b</span><sub>5</sub> protein. Absorbance spectra for oxidised and reduced forms of (<b>A</b>) human cytochrome <span class="html-italic">b</span><sub>5</sub> protein and (<b>B</b>) OtV-2 viral cytochrome <span class="html-italic">b</span><sub>5</sub> protein and (<b>C</b>) structural display of the OtV-2 protein as a ribbon diagram. Adapted from [<a href="#B37-viruses-09-00043" class="html-bibr">37</a>].</p>
Full article ">
1989 KiB  
Article
Virus Resistance Is Not Costly in a Marine Alga Evolving under Multiple Environmental Stressors
by Sarah E. Heath, Kirsten Knox, Pedro F. Vale and Sinead Collins
Viruses 2017, 9(3), 39; https://doi.org/10.3390/v9030039 - 8 Mar 2017
Cited by 10 | Viewed by 6462
Abstract
Viruses are important evolutionary drivers of host ecology and evolution. The marine picoplankton Ostreococcus tauri has three known resistance types that arise in response to infection with the Phycodnavirus OtV5: susceptible cells (S) that lyse following viral entry and replication; resistant cells (R) [...] Read more.
Viruses are important evolutionary drivers of host ecology and evolution. The marine picoplankton Ostreococcus tauri has three known resistance types that arise in response to infection with the Phycodnavirus OtV5: susceptible cells (S) that lyse following viral entry and replication; resistant cells (R) that are refractory to viral entry; and resistant producers (RP) that do not all lyse but maintain some viruses within the population. To test for evolutionary costs of maintaining antiviral resistance, we examined whether O. tauri populations composed of each resistance type differed in their evolutionary responses to several environmental drivers (lower light, lower salt, lower phosphate and a changing environment) in the absence of viruses for approximately 200 generations. We did not detect a cost of resistance as measured by life-history traits (population growth rate, cell size and cell chlorophyll content) and competitive ability. Specifically, all R and RP populations remained resistant to OtV5 lysis for the entire 200-generation experiment, whereas lysis occurred in all S populations, suggesting that resistance is not costly to maintain even when direct selection for resistance was removed, or that there could be a genetic constraint preventing return to a susceptible resistance type. Following evolution, all S population densities dropped when inoculated with OtV5, but not to zero, indicating that lysis was incomplete, and that some cells may have gained a resistance mutation over the evolution experiment. These findings suggest that maintaining resistance in the absence of viruses was not costly. Full article
(This article belongs to the Special Issue Marine Viruses 2016)
Show Figures

Figure 1

Figure 1
<p>Mean (± SE) cell density mL<sup>−1</sup> of resistant (R), resistant producer (RP) and susceptible (S) <span class="html-italic">O. tauri</span> lines three days after OtV5 inoculation in five environments. Points represent the average of the three assay replicates for each evolved population. Inoculated = populations inoculated with OtV5, Not inoculated = negative control populations that were grown for the same period without OtV5 inoculation. There were three evolved populations of each line. The dashed line represents the starting cell density at 100,000 cell mL<sup>−1</sup>.</p>
Full article ">Figure 2
<p>Change in cell density of the susceptible lines NG’2, NG’3 and NG’4 after OtV5 inoculation one week into the selection experiment (Start) and after 32 transfer cycles of evolution (End). The dashed line represents no change.</p>
Full article ">Figure 3
<p>Growth rates as measured by mean cell divisions per day for each evolving population over four time points (1, 14, 20 and 32 transfer cycles). The dashed line represents one cell division per day. T1 is the growth rate following acclimation at the beginning of the experiment. There are no growth measurements for the randomized environment at T1 because lines had only been growing for one transfer cycle.</p>
Full article ">Figure 4
<p>Mean cell divisions per day (±SEM). R = resistant, RP = resistant producer, S = susceptible. Each panel represents a growth assay, with cells evolved in the selection environment (top label) and growth rates measured in the assay environment (bottom label). The dashed line indicates, for reference, one cell division per day.</p>
Full article ">Figure 5
<p>Competitive ability, as measured by fold difference in growth relative to a roGFP-modified <span class="html-italic">O. tauri</span> line, of evolved populations and control populations assayed in the selection environments. R = resistant, RP= resistant producer, S = susceptible. Each panel represents one assay, with populations evolved in the selection environment (top label) and competitiveness measured in the assay environment (bottom label). The dashed line represents no change (i.e., equal proportions of roGFP and competitor populations).</p>
Full article ">
Back to TopTop