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Microorganisms
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Herpesvirus Diversity and Evolution
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Herpesvirus Diversity and Evolution

A special issue of Microorganisms (ISSN 2076-2607).

Deadline for manuscript submissions: closed (28 February 2021) | Viewed by 9609

Special Issue Editor

Dr. Diego Forni

E-Mail Website
Guest Editor
Bioinformatics, Scientific Institute, IRCCS E. MEDEA, 23842 Bosisio Parini, Lecco, Italy
Interests: virus evolution; natural selection; viral phylodynamics; molecular dating; host-pathogen interaction; viral genome variability; molecular evolution

Special Issue Information

Dear Colleagues,

Herpesviruses are a group of large DNA viruses that can infect a wide spectrum of species, spanning from mammals to birds and reptiles. These viruses not only infect a large range of hosts, but they are globally distributed and, in the case of human herpesviruses, infect the overwhelming majority of the population. Herpesviruses usually establish a lifelong latent infection but in some peculiar cases can result in different disease. They are largely host specific, and co-evolution with their hosts is well established, but distantly and closely related host switches are common. The investigation of viral genetic determinants and understanding the molecular evolution of these viruses can have an impact from a biomedical point of view.

This Special Issue will highlight all the evolutionary processes and mechanisms that characterize the evolutionary history and adaptation of all herpesviruses, infecting both humans and all other animals. This includes, but is not limited to, topics such as phylogenetic analyses, molecular dating estimation, and co-divergence studies.

Dr. Diego Forni
Guest Editor

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Published Papers (3 papers)

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26 pages, 5168 KiB  
Article
Genomes of Anguillid Herpesvirus 1 Strains Reveal Evolutionary Disparities and Low Genetic Diversity in the Genus Cyprinivirus
by Owen Donohoe, Haiyan Zhang, Natacha Delrez, Yuan Gao, Nicolás M. Suárez, Andrew J. Davison and Alain Vanderplasschen
Microorganisms 2021, 9(5), 998; https://doi.org/10.3390/microorganisms9050998 - 5 May 2021
Cited by 11 | Viewed by 3276
Abstract
Anguillid herpesvirus 1 (AngHV-1) is a pathogen of eels and a member of the genus Cyprinivirus in the family Alloherpesviridae. We have compared the biological and genomic features of different AngHV-1 strains, focusing on their growth kinetics in vitro and genetic content, [...] Read more.
Anguillid herpesvirus 1 (AngHV-1) is a pathogen of eels and a member of the genus Cyprinivirus in the family Alloherpesviridae. We have compared the biological and genomic features of different AngHV-1 strains, focusing on their growth kinetics in vitro and genetic content, diversity, and recombination. Comparisons based on three core genes conserved among alloherpesviruses revealed that AngHV-1 exhibits a slower rate of change and less positive selection than other cypriniviruses. We propose that this may be linked to major differences in host species and corresponding epidemiological circumstances. Efforts to derive evolutionary rate estimates for cypriniviruses under various theoretical models were ultimately unrewarding. We highlight the potential value of future collaborative efforts towards generating short-term evolutionary rate estimates based on known sequence sampling dates. Finally, we revealed that there is significantly less genetic diversity in core gene sequences within cyprinivirus species clades compared to species in the family Herpesviridae. This suggests that cyprinivirus species may have undergone much more vigorous purifying selection post species clade divergence. We discuss whether this may be linked to biological and anthropogenic factors or to sampling bias, and we propose that the comparison of short-term evolutionary rates between species may provide further insights into these differences. Full article
(This article belongs to the Special Issue Herpesvirus Diversity and Evolution)
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Figure 1

Figure 1
<p>Analysis of AngHV-1 genome sequences. (<b>a</b>) Phylogenetic analysis (UPGMA). Bootstrap values (1000 replicates) are indicated at the right of each node. These values are also illustrated by the colors of the branches leading to each node. Numbers above each branch represent substitutions per nucleotide observed along the branch. The geographical origin of each strain is indicated in brackets. (<b>b</b>) Recombination analysis. Five potential recombination events were identified using nine sequenced isolates as input. For each event, the left column illustrates the results of RDP analyses, including locations of recombination events and <span class="html-italic">p</span>-values. The middle and the right columns show phylogenetic analyses based on the genome excluding the region of recombination and the same tree based on the recombination region only, respectively. Numbers on internal branches indicate bootstrap values (1000 replicates); only values &gt;50% are shown. The scales illustrate the number of substitutions per nucleotide. The color code used is described at the top.</p> Full article ">Figure 2
<p>Comparisons of the growth of AngHV-1 strains in vitro. (<b>a</b>) Viral growth assay. EK-1 cells were infected with the strains indicated (see top for symbol codes) and the log<sub>10</sub> value of the titer (pfu/mL) in the cell supernatant was determined at the indicated dpi. Data are presented in <a href="#microorganisms-09-00998-t001" class="html-table">Table 1</a>. Cells were infected with the strains indicated, and plaque areas were measured over time. Data presented are the mean ± SEM for measurements of 20 randomly selected plaques. (<b>c</b>) Correlation between plaque area measured at 8 dpi (panel (<b>a</b>)) and viral titers measured at 4 dpi (panel (<b>b</b>)). Data presented are the mean ± SEM.</p> Full article ">Figure 3
<p>Phylogenetic analysis of concatenated cyprinivirus core gene sequences. Cladogram of bootstrap consensus tree (UPGMA) from phylogenetic analysis of concatenated AA sequences of three core genes (DNA polymerase, helicase and terminase) derived from sequenced cyprinivirus genomes. Bootstrap values (1000 replicates) are indicated at the right of each node. These values are also illustrated through the colors of the branches leading to each node, according to the scale on the top left. Branch lengths are arbitrary.</p> Full article ">Figure 4
<p>Relative rates of cyprinivirus evolution. ML trees were produced based on the same data used to generate the cladograms in <a href="#microorganisms-09-00998-f003" class="html-fig">Figure 3</a>. (<b>a</b>) ML tree based on concatenated core gene AA sequences. (<b>b</b>) ML tree based on concatenated core gene DNA sequences excluding the third codon position. In these trees, branch lengths represent the number of substitutions per site. The results of Tajima’s relative rate tests for pairwise comparison between species clades are presented in each panel. <span class="html-italic">p</span>-values highlighted in red indicate significant differences in the rate of evolution between species. The results for Tajima’s relative rate tests presented in panel (<b>b</b>) were obtained by considering transversions only. Equivalent tests, considering transitions only, are presented in <a href="#app1-microorganisms-09-00998" class="html-app">Table S4</a>.</p> Full article ">Figure 5
<p>AA changes in cyprinivirus core genes driven by positive selection. CodeML analysis was performed to identify AA changes between cyprinivirus species that were driven by positive selection. Positive selection was identified in the (<b>a</b>) DNA polymerase and (<b>b</b>) helicase genes. The ML trees based on DNA polymerase and helicase codon alignments are displayed. A summary of results and <span class="html-italic">p</span>-values are indicated above each branch of interest. Only changes supported by PP &gt; 0.95 are shown. Codon and AA changes are displayed to the right of each tree, with position in alignments and color-coded descriptions of codon changes indicated on top of each column. Boxes around codons in each column are colored corresponding to the color-coded codon changes on top of each column, with codons representing the changes driven by positive selection indicated by thicker lines. PP values and species-specific positions of AA sites are summarized in <a href="#microorganisms-09-00998-t003" class="html-table">Table 3</a>.</p> Full article ">Figure 6
<p>Comparison of species-specific nucleotide substitution rate estimates between HHV-1 and cypriniviruses. HHV-1 substitution rates were reported in the studies described in <a href="#app1-microorganisms-09-00998" class="html-app">Table S9</a>. Rate estimates for cypriniviruses were estimated based on two different calibration hypotheses. Corresponding time trees are available in <a href="#app1-microorganisms-09-00998" class="html-app">Figure S3</a>.</p> Full article ">Figure 7
<p>Comparison of nucleotide diversity in core genes between cypriniviruses and members of the family <span class="html-italic">Herpesviridae</span>. Comparisons were based on species-level nucleotide alignments and trees generated using DNA polymerase, helicase, and terminase sequences from each species. Sequences from a fourth core gene, uracil-DNA glycosylase, were also added, facilitating the comparison of diversity between highly conserved and less well conserved core genes. All species name acronyms are defined in <a href="#app1-microorganisms-09-00998" class="html-app">Table S1</a>. The comparison consisted of 492 sequences from 123 sequenced strains. The 48 phylogenetic trees corresponding to each species-level gene alignment are provided in <a href="#app1-microorganisms-09-00998" class="html-app">Figures S4 and S5</a>. (<b>a</b>) Diversity (π) from each species-level nucleotide sequence alignment. (<b>b</b>) Mean branch length for each species-level tree. Pairwise comparison: * = <span class="html-italic">p</span> &lt; 0.05, ** = <span class="html-italic">p</span> &lt; 0.01.</p> Full article ">
26 pages, 1654 KiB  
Article
Expanding the Geographic Characterisation of Epstein–Barr Virus Variation through Gene-Based Approaches
by Marco Telford, David A. Hughes, David Juan, Mark Stoneking, Arcadi Navarro and Gabriel Santpere
Microorganisms 2020, 8(11), 1686; https://doi.org/10.3390/microorganisms8111686 - 29 Oct 2020
Cited by 11 | Viewed by 4355 | Correction
Abstract
The Epstein–Barr Virus (EBV) infects the vast majority of human individuals worldwide (~90%) and is associated with several diseases, including different types of cancer and multiple sclerosis, which show wide variation in incidence among global geographical regions. Genetic variants in EBV genomic sequences [...] Read more.
The Epstein–Barr Virus (EBV) infects the vast majority of human individuals worldwide (~90%) and is associated with several diseases, including different types of cancer and multiple sclerosis, which show wide variation in incidence among global geographical regions. Genetic variants in EBV genomic sequences have been used to determine the geographical structure of EBV isolates, but our understanding of EBV diversity remains highly incomplete. We generated sequences for 13 pivotal EBV genes derived from 103 healthy individuals, expanding current EBV diversity datasets with respect to both geographic coverage and number of isolates per region. These newly generated sequences were integrated with the more than 250 published EBV genomes, generating the most geographically comprehensive data set of EBV strains to date. We report remarkable variation in single-gene phylogenies that, when analysed together, show robust signals of population structure. Our results not only confirm known major global patterns of geographic variation, such as the clear separation of Asian isolates from the rest, and the intermixed relationships among African, European and Australian isolates, but yield novel phylogenetic relationships with previously unreported populations. We provide a better understanding of EBV’s population structure in South America, Africa and, by the inclusion of Turkey and Georgia, we also gain insight into EBV diversity in Western Asia, a crossroads connecting Europe, Africa and Asia. In summary, our results provide a detailed world-wide characterisation of EBV genetic clusters, their enrichment in specific geographic regions, novel inter-population relationships, and a catalogue of geographically informative EBV genetic variants. Full article
(This article belongs to the Special Issue Herpesvirus Diversity and Evolution)
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Figure 1

Figure 1
<p>Major phylogenetic relationships. (<b>A</b>) Supertree generated by combining the phylogenies of all genes. The strain labels are coloured by country of origin. The countries of the same continent are coloured by different shades of the same colour. The new sequences produced in this study are identified by black asterisks. Nodes with bootstraps values higher than 0.5 are indicated with a red circle. (<b>B</b>,<b>C</b>) Heatmap representing the bootstrapped pairwise genetic distances between EBV populations weighted per all genes in the data set. Populations IDs correspond to the country of origin (<b>B</b>), or the continent of origin (<b>C</b>), and are coloured by continent. The colour of the heatmap cells is proportional to the genetic distance value (the closer the populations, the darker red the cell colour). Groups of isolates mentioned in the text are reported together with the proportion of the total number of isolates of the geographical origin.</p> Full article ">Figure 2
<p>Difference between genes phylogenies. Example of two genes with different genetic structure. (<b>A</b>) Cladograms of the maximum likelihood phylogenies are reported for two genes, with the leaves coloured per country of origin. The new sequences produced in this study are identified by black asterisks. Nodes with bootstraps values higher than 0.5 are indicated with a red circle. (<b>B</b>) Heatmaps representing the bootstrapped pairwise genetic distances between populations. The heatmap cells colour is proportional to the genetic distance value (the more similar the populations, the darker red the cell colour). Populations IDs correspond to the country of origin and are coloured by continent.</p> Full article ">Figure 3
<p>Clustering workflow. For each gene, (<b>①</b>) a maximum likelihood phylogenetic tree is generated. (<b>②</b>) Hierarchical clustering is used to generate groupings that separate the isolates in increasing number of clusters. (<b>③</b>) For each grouping a similarity value with the geographical origin of the isolates is calculated (see methods), as well as the number of valid clusters (i.e., clusters containing at least 3 isolates). The optimum clusterisation is determined as the one giving the highest similarity value for the maximum number of valid clusters. (<b>④</b>) The grouping with the optimum number of clusters is taken and for each cluster the odds ratios for the presence of isolates of each population is calculated. The polymorphic positions found in each clusters/origin pair with high odds ratios undergo analysis to calculate statistical significance of the presence of each allele.</p> Full article ">Figure 4
<p>Variation distribution examples. (<b>A</b>) characterization of genetic variation in a cluster: Indonesia in EBNA-3C type 1. EBNA-3C type 1 phylogenetic tree coloured by country of origin. The asterisks identify sequences added in this study. The variation of 14 polymorphisms highly enriched in the purely Indonesian cluster number 20 (optimal clustering against country of origin) is shown on the right of the tree. The variant positions relative to the reference sequence are: 86143, 86160, 86212, 86233, 86894, 86926, 86927, 86938, 87557, 88122, 88233, 88901. (<b>B</b>) Variation in EBNA-1. EBNA-1 maximum likelihood phylogenetic tree with labels coloured by (<b>1</b>) ebnotype (<b>2</b>) country of origin. Four isolates with poor alignment around the codons translating for the typing residues were excluded from the analysis. The asterisks identify sequences added in this study, and the red circles nodes with bootstrap values higher than 0.5.</p> Full article ">

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4 pages, 1811 KiB  
Correction
Correction: Telford et al. Expanding the Geographic Characterisation of Epstein–Barr Virus Variation through Gene-Based Approaches. Microorganisms 2020, 8, 1686
by Marco Telford, David A. Hughes, David Juan, Mark Stoneking, Arcadi Navarro and Gabriel Santpere
Microorganisms 2021, 9(11), 2328; https://doi.org/10.3390/microorganisms9112328 - 11 Nov 2021
Viewed by 1177
Abstract
The authors wish to make the following correction to this paper [...] Full article
(This article belongs to the Special Issue Herpesvirus Diversity and Evolution)
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Figure 1

Figure 1
<p>Major phylogenetic relationships. (<b>A</b>) Supertree generated by combining the phylogenies of all genes. The strain labels are coloured by country of origin. The countries of the same continent are coloured by different shades of the same colour. The new sequences produced in this study are identified by black asterisks. Nodes with bootstraps values higher than 0.5 are indicated with a red circle. (<b>B</b>,<b>C</b>) Heatmap representing the bootstrapped pairwise genetic distances between EBV populations weighted per all genes in the data set. Populations IDs correspond to the country of origin (<b>B</b>), or the continent of origin (<b>C</b>), and are coloured by continent. The colour of the heatmap cells is proportional to the genetic distance value (the closer the populations, the darker red the cell colour). Groups of isolates mentioned in the text are reported together with the proportion of the total number of isolates of the geographical origin.</p> Full article ">Figure 2
<p>Variation distribution examples. (<b>A</b>) characterization of genetic variation in a cluster: Indonesia in EBNA-3C type 1. EBNA-3C type 1 phylogenetic tree coloured by country of origin. The asterisks identify sequences added in this study. The variation of 14 polymorphisms highly enriched in the purely Indonesian cluster number 20 (optimal clustering against country of origin) is shown on the right of the tree. The variant positions relative to the reference sequence are: 86143, 86160, 86212, 86233, 86894, 86926, 86927, 86938, 87557, 88122, 88233, 88901. (<b>B</b>) Variation in EBNA-1. EBNA-1 maximum likelihood phylogenetic tree with labels coloured by (<b>1</b>) ebnotype (<b>2</b>) country of origin. Four isolates with poor alignment around the codons translating for the typing residues were excluded from the analysis. The asterisks identify sequences added in this study, and the red circles nodes with bootstrap values higher than 0.5.</p> Full article ">
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