- Research article
- Open Access
Giant viruses, giant chimeras: The multiple evolutionary histories of Mimivirus genes
© Moreira and Brochier-Armanet; licensee BioMed Central Ltd. 2008
- Received: 06 June 2007
- Accepted: 18 January 2008
- Published: 18 January 2008
Although capable to evolve, viruses are generally considered non-living entities because they are acellular and devoid of metabolism. However, the recent publication of the genome sequence of the Mimivirus, a giant virus that parasitises amoebas, strengthened the idea that viruses should be included in the tree of life. In fact, the first phylogenetic analyses of a few Mimivirus genes that are also present in cellular lineages suggested that it could define an independent branch in the tree of life in addition to the three domains, Bacteria, Archaea and Eucarya.
We tested this hypothesis by carrying out detailed phylogenetic analyses for all the conserved Mimivirus genes that have homologues in cellular organisms. We found no evidence supporting Mimivirus as a new branch in the tree of life. On the contrary, our phylogenetic trees strongly suggest that Mimivirus acquired most of these genes by horizontal gene transfer (HGT) either from its amoebal hosts or from bacteria that parasitise the same hosts. The detection of HGT events involving different eukaryotic donors suggests that the spectrum of hosts of Mimivirus may be larger than currently known.
The large number of genes acquired by Mimivirus from eukaryotic and bacterial sources suggests that HGT has been an important process in the evolution of its genome and the adaptation to parasitism.
- Horizontal Gene Transfer
- Additional Data File
- Horizontal Gene Transfer Event
- Giant Virus
- Eukaryotic Origin
Since their discovery in the last years of the XIX century up to our days, viruses have never ceased to puzzle biologists, especially those studying their evolution. Because of their nature as entities at the border between the living and the non-living, their origin has been the matter of passionate debate. Opinions range between the two extreme "virus-early" and "virus-late" hypotheses. The first postulates that viruses originated before modern cells [1–5]. On the contrary, the second hypothesis proposes that viruses originated either by the escape of genetic material and proteins from cells, or by a dramatic reductive evolution from cellular forms that lost all the "cellular paraphernalia" unnecessary for the parasitic lifestyle [6–8]. As a consequence, the position of viruses within the tree of life is also a subject of disagreement. Whereas some scientists fervently advocate that viruses should have a place in the tree of life , many other consider that, being acellular and lacking any kind of carbon and energy metabolism, viruses cannot be properly compared with true living beings (i.e. cellular) and, therefore, do not belong to the tree of life [7, 10]. Moreover, there is compelling evidence for the polyphyletic origin of viruses, which further complicates the issue .
These debates have recently gained an unprecedented impetus when Raoult and co-workers published the description of the genome of Mimivirus, a giant virus first detected as a parasite of amoeba of the genus Acanthamoeba, which is endowed with the biggest viral genome known to date: 1.2 Mbp containing 911 genes . A number of genomic signatures strongly support that Mimivirus belongs to the NCLDV (Nucleo-Cytoplasmic Large ds-DNA Virus) virus family. The mimiviral genome contains genes frequently found in viruses, as those involved in genome replication, but also, and for the first time in a virus, a number of genes coding for proteins involved in transcription and translation. Therefore, at least from the point of view of gene content, Mimivirus appears somehow closer to a typical cell than any other described virus. Moreover, Raoult et al. identified seven mimiviral proteins that have closely related eukaryotic homologues. Their phylogenetic analysis in a multi-protein concatenation supported the emergence of Mimivirus as a sister-group of eukaryotes in a tree including representatives from the three domains of life . Therefore, it was hypothesised that this virus would define a new branch distinct from the three domains of life: Bacteria, Archaea and Eukaryotes . Such an unexpected result had the potential to revolutionise our conceptions on the diversity and evolution of life, up to now based on the tripartite scheme of the three domains . Raoult et al. further suggested that the NCLDV family may have played a role in the origin of eukaryotes . This would agree with previous hypotheses stating that viruses could be at the origin of many eukaryotic genes [3, 14] or even the eukaryotic nucleus [15, 16].
The study of viral evolution using phylogenetic analysis is most often a difficult task due to several peculiarities of viruses related to their parasitic lifestyle, such as rapid evolutionary rates and the propensity to be involved in horizontal gene transfer (HGT) events . As recently shown , the emergence of Mimivirus at the base of the eukaryotic branch in the seven-protein study by Raoult et al. was the result of an accumulation of artefacts due to the simultaneous analysis of several markers that had been profusely exchanged between distant species by HGT . That was the case for two aminoacyl-tRNA synthetases: methyonyl-tRNA (Met-RS) and tyrosyl-tRNA (Tyr-RS) synthetases, which are known to have been intensely affected by HGT . For example, the proteobacterium Escherichia coli has a Met-RS of archaeal origin and a Tyr-RS transferred from Gram-positive Firmicutes [18, 19]. Therefore, a single species can have aminoacyl-tRNA synthetases with at least two very different evolutionary histories and, consequently, their simultaneous analysis in a multi-protein concatenation will inevitably lead to a wrong phylogenetic tree, especially when a restricted taxonomic sampling is used (i.e., a very small number of species).
When coping with datasets affected by HGT, the most reliable way to avoid artefacts is to carry out independent analyses for each marker. In fact, when independent phylogenetic trees of the proteins used by Raoult et al. were carried out with a rich taxonomic sampling, the results were completely different . Not only HGT events were detected, but Mimivirus did no longer form an independent branch at the base of the eukaryotes, but emerged well nested within them. Moreover, for certain markers such as the Tyr-RS, it branched as a close relative of several species of amoeba . This result showed that, instead of being the ancestral source of eukaryotic genes, Mimivirus has incorporated these genes from its eukaryotic host, the amoeba, into its own genome. While these studies were based on only a handful of genes, we sought here to understand how extensive was the role of HGT in shaping the whole Mimivirus genome, and which were the sources of the transferred genes. These questions were recently addressed using surrogate methods, those that do not require inference of phylogenetic trees, such as the analysis of BLAST scores. Using this approach, Ogata et al.  studied the distribution of BLAST scores for 87 Mimivirus ORFs, searched against a database containing homologous sequences from the amoeba Entamoeba histolytica, metazoa, fungi and plants. Their analysis showed that only five Mimivirus ORFs (MIMI_L124, MIMI_L469, MIMI_L619, MIMI_R665, and MIMI_L780) are more similar to their E. histolytica homologues than to the sequences from other eukaryotic groups. A similar analysis for the entire set of Mimivirus ORFs showed that about 40 of them have eukaryotic or bacterial sequences as best matches [21–23]. However, BLAST searches, as also other surrogate methods, offer only a very rough estimate of the phylogenetic affinity of a gene. Indeed, very often the best BLAST hit does not correspond to the closest evolutionary relative. For example, a BLAST search of the ORF MIMI_R299 (ribonucleotide reductase HI) retrieves several fungi as best hits, whereas phylogenetic analysis supports its relationship with bacterial homologues (Supplementary Figure 28 in Additional data file 2). This can be explained by several factors that can reduce the accuracy of BLAST searches, in particular the heterogeneity of evolutionary rates among species . In that sense, several studies have shown that surrogate methods are clearly inferior to phylogenetic analysis in inferring the evolutionary origin of genes [25, 26]. In addition, phylogenetic analyses can provide a very precise identification of the donors of genes acquired by HGT, especially in the case of recent transfer events, and they can also provide statistical measures of the support of the inferred phylogenetic relationships (e.g., bootstrap proportions or Bayesian posterior probabilities). Therefore, we carried out a detailed phylogenetic analysis of all the Mimivirus genome ORFs with well-identified cellular homologues in order to determine whether these genes have a viral or a cellular origin. In the latter case, phylogenetic analyses can be helpful to identify cell-to-Mimivirus HGT events and the corresponding gene donors.
Accurate phylogenetic reconstruction requires a correct degree of conservation among the sequences analysed. Therefore, we focused only on the set of 198 mimiviral proteins ascribed to COG families .
Mimivirus ORF homologues have an extremely patchy taxonomic distribution
Interestingly, we found that only a very small fraction of the 198 mimiviral ORFs has homologues in other members of the NCLDV family of viruses, even in those with relatively big genomes. For example, the phycodnaviruses Emiliania huxleyi virus 86 (407 kbp, 478 protein coding genes) and Paramecium bursaria Chlorella virus 1 (330 kbp, 701 genes) contain only 27 and 28 homologues of the 198 mimiviral ORFs (detected by BLASTP with an E-value threshold of 1e-03), respectively. This represents less than 15% of these 198 ORFs, and could be partially explained by the smaller genome size of those phycodnaviruses. However, the values are significantly smaller than those expected just by the difference in genome size: ~100–150 homologues should be retrieved in these phycodnaviruses. In addition, these data show a very disparate taxonomic distribution of genes among the different viruses of the NCLDV family, a situation that is frequently a clear symptom of HGT . Moreover, our phylogenetic analyses support a viral origin for only 4 ORFs among the 198 mimiviral ORFs studied (the helicase MIMI_L206, the NAD-dependent DNA ligase MIMI_R303, and the two thiol-oxidoreductases MIMI_R368 and MIMI_R596, Additional data file 2). This observation, together with the fact that the mimiviral ORFs that have homologues in the three domains of life are not the dominant class of ORFs in Mimivirus (see above), is extremely difficult to reconcile with the hypothesis that NCLDV viruses may define a fourth major lineage of life (a "fourth domain"). In fact, genomes among the smallest ones found in archaea (e.g. Nanoarchaeum equitans, 490 kbp ) and bacteria (e.g. Mycoplasma genitalium, 580 kbp ), which are significantly smaller than the Mimivirus genome, share many more genes with their archaeal and bacterial relatives than the Mimivirus does with the other NCLDV. Moreover, these archaeal and bacterial species with highly reduced genomes have a much larger repertoire of typical cellular genes than the Mimivirus [31, 32].
If the "fourth domain" hypothesis  was correct, the actual taxonomic distribution shown by the mimiviral ORFs could only be explained by an extremely massive loss of ancestral genes in the different NCLDV viruses but, even in that case, the majority of gene phylogenies should support a clear separation of the mimiviral sequences from those of the other domains. On the contrary, if the "gene acquisition by HGT" hypothesis  was correct, the majority of gene phylogenies should support an emergence of the Mimivirus ORFs that have cellular homologues within one of the three domains (according to the specific donor involved in each HGT event). We have explored these two possibilities by detailed phylogenetic analyses, applying Maximum Likelihood (ML) and Bayesian Inference (BI) methods, of all the 126 mimiviral ORFs with cellular homologues and with an adequate degree of sequence conservation.
Phylogenetic analysis: Mimiviral ORFs of prokaryotic origin
Mimiviral ORFs of eukaryotic origin: amoebas and evidence for unknown hosts
The amoebas as complex ecosystems promoting HGT
The number of bacterial species that have been characterised as stable inhabitants of diverse amoebas seems to be far from being completely known [33, 46]. As commented above, the promiscuity of these bacterial species within amoebas may have facilitated HGT and the adaptation to parasitic lifestyles . Several eukaryotic parasites, such as the kinetoplastid Perkinsiella, can also be found in amoebas . Moreover, there is increasing evidence that the use of amoebas as a reservoir can be a key factor in the selection of virulent strains of eukaryotic parasites of mammals, in particular several pathogenic dimorphic fungi [47, 48]. Mimiviruses infecting amoebas can thus coexist in a confined environment with a variety of other parasites. In addition to the DNA from the amoebal host, the sporadic cell lysis of these parasites provides DNA that can be a source of new genes for the virus. The acquisition of genes from the host and from its bacterial and eukaryotic parasites may be significant in the development of virulence traits of the virus, but also in its opportunistic pre-adaptation to alternative hosts, including humans. This has been shown to be an important process in other pathogens. For example, the parasitic bacterium L. pneumophila has acquired by HGT several eukaryotic genes involved in a variety of cell functions, in particular two serine/threonine protein kinases . It has been shown in several pathogens that these protein kinases are responsible of inhibiting phagosome-lysosome fusion, allowing intracellular survival, but also of disrupting the host defence by interfering with the eukaryotic signal transduction pathways [50, 51]. Interestingly, Mimivirus possesses three serine/threonine protein kinases (MIMI_R818, MIMI_R826 and MIMI_R831) that have been acquired from its amoebal hosts (see above and Figure 3). This is also the case for the RAS GTPase MIMI_R214. The presence of these proteins suggests that Mimivirus can regulate the host cell cycle to its benefit. This is an example of the crucial role that HGT may have had in the evolution of the virulence strategy of Mimivirus.
Most of the genes in Mimivirus with homologues in cellular organisms appear to have been acquired by HGT to the virus. This strongly supports that Mimivirus does not define a new domain of life. Mimivirus certainly acquired most of these genes either from its eukaryotic hosts or from other parasites coexisting in the same host. In that sense, this virus appears to have followed a similar strategy as other parasites to interfere with host cellular processes through the modification and expression of genes acquired from the host by HGT. Our data also suggest that the primary hosts for Mimivirus are the Amoebozoa, as most of the mimiviral ORFs of eukaryotic origin with a well resolved phylogeny are closely related to homologues from this group. Nevertheless, we detect HGT from putative alternative hosts, such as heterolobosea (e.g., Naegleria) and kinetoplastids. Despite the fact that Mimivirus appears to have the capacity to infect also humans [46, 52, 53], we identified only a single case of a probable gene acquisition from animals, the glycosyltransferases MIMI_L230 and MIMI_R699 (Supplementary Figure 15 in Additional data file 2). This small number suggests that the recently reported human infection by this virus may be a relatively rare or very recent event.
Phylogenetic reconstruction methods
Homologues for each Mimivirus ORF were retrieved from the NCBI protein non-redundant data base after identification by BLAST . The sequences were aligned with CLUSTALW  and the alignment was manually refined with the program ED of the MUST package . Regions where homology between sites was doubtful were removed before the phylogenetic analysis.
Data sets were analysed by Maximum likelihood (ML) using the JTT model with a Γ law (4 rate categories) and a proportion of invariant sites using the program PHYML . To asses the topologies found by ML, several data sets were also analysed with Bayesian methods using the program MrBAYES 3 with a mixed substitution model and a Γ law (6 rate categories) and a proportion of invariant sites to take among-site rate variation into account . The Markov chain Monte Carlo search was run with 4 chains for 1,000,000 generations, with trees being sampled every 100 generations (the first 2,500 trees were discarded as "burnin").
We thank the French "Agence Nationale de la Recherche" ANR for support (JCJC Program) and Purificación López-García and Simonetta Gribaldo for critical reading of the manuscript.
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