Virus movement maintains local virus population diversity - PubMed (original) (raw)
Comparative Study
. 2007 Nov 27;104(48):19102-7.
doi: 10.1073/pnas.0709445104. Epub 2007 Nov 19.
Affiliations
- PMID: 18025457
- PMCID: PMC2141915
- DOI: 10.1073/pnas.0709445104
Comparative Study
Virus movement maintains local virus population diversity
Jamie C Snyder et al. Proc Natl Acad Sci U S A. 2007.
Abstract
Viruses are the largest reservoir of genetic material on the planet, yet little is known about the population dynamics of any virus within its natural environment. Over a 2-year period, we monitored the diversity of two archaeal viruses found in hot springs within Yellowstone National Park (YNP). Both temporal phylogeny and neutral biodiversity models reveal that virus diversity in these local environments is not being maintained by mutation but rather by high rates of immigration from a globally distributed metacommunity. These results indicate that geographically isolated hot springs are readily able to exchange viruses. The importance of virus movement is supported by the detection of virus particles in air samples collected over YNP hot springs and by their detection in metacommunity sequencing projects conducted in the Sargasso Sea. Rapid rates of virus movement are not expected to be unique to these archaeal viruses but rather a common feature among virus metacommunities. The finding that virus immigration rather than mutation can dominate community structure has significant implications for understanding virus circulation and the role that viruses play in ecology and evolution by providing a reservoir of mobile genetic material.
Conflict of interest statement
The authors declare no conflict of interest.
Figures
Fig. 1.
General water chemistry of each hot spring monitor site. Although not entirely static, the overall geochemical signature of each spring was distinct and relatively stable over the 2-year sampling course. Pie charts illustrate the distinct geochemical signature of each hot spring. (A) CHMS. (B) RCMS. (C) RHMS. Average values are reported in the table.
Fig. 2.
Comparison of the archaeal community detected at each of the hot springs. (A) CHMS. (B) RHMS. (C) RCMS. Pie charts illustrate the average relative abundance of each genus detected by using 16S rRNA gene analysis. The community composition was relatively stable over the 2-year time course, with Sulfolobus being the only common, but not the dominant, resident in each of the three hot springs. A, Acidianus; C, Caldococcus; D, Desulfurococcus; M, Metallosphaera; P, Pyrodictium; T, Thermocladium; V, Vulcanisaeta; S, Stygiolobus; O, other.
Fig. 3.
Phylogenetic relationships of clades of SIRV and their detection through time. (A) SIRV phylogenetic tree composed of 2,165 clones from three hot springs over all sampling times. Twelve well supported clades (A–L) with both maximum parsimony bootstrap values (10,000 resampling) and maximum likelihood clade credibility values are indicated. (B) Dominant SIRV clades detected over time within CHMS, RHMS, and RCMS. The size of the oval represents the relative number of sequences belonging to a particular clade detected at each sampling time. Asterisks indicate sampling times in which SIRV sequences were not detected.
Fig. 4.
A diverse SSV community transiently visits geochemically distinct hot spring environments. (A) SSV phylogenetic tree composed of 779 clones from three hot springs from all sampling times shows six well supported clades (A–F), with both maximum parsimony bootstrap values (10,000 resamplings) and maximum likelihood clade credibility values indicated. Globally distributed SSV isolates (indicated by isolate abbreviation) cluster within YNP clades. (B) Dominant SSV clades detected over time within the three hot springs, where the size of the oval represents the relative number of sequences for each clade. Asterisks indicate sampling times in which SSV sequences were not detected.
Fig. 5.
Rank abundance distribution of 2,944 sequences in 1,042 sequence types for SIRV and SSV sampled at all three hot springs during the ≈2-year study. Distributions and their AIC values are shown, with EtSF being the best fit. The abundances of the five most abundant genotypes are reported next to the corresponding point.
Fig. 6.
Community composition of SIRV and SSV as a function of time. Pairwise comparisons of community composition (Jaccard's distance) for SIRV (open circles) and SSV (bullets) are shown. The models including within-hot-springs (black lower lines) and among-hot-springs (upper red lines) comparisons along with days between sampling are illustrated for SIRV and SSV. The center lines depict the model, including only days between sampling. The 95% confidence intervals for the mantel correlation of each of the two models were essentially identical.
Fig. 7.
Phylogenetic relatedness of SIRV and SSV as a function of time. The phylogenetic distance (net-relatedness index) between samples compared with days between sampling are shown for both SIRV (open circles) and SSV (filled circles). The upper (red) and lower (black) lines represent the models, including both days between sampling events and among-hot-springs or within-hot-springs comparisons. The model including only days between sampling events is shown by the center line. The 95% confidence intervals for the mantel correlation of each of the two models were essentially identical.
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