Contrasting Life Strategies of Viruses that Infect Photo- and Heterotrophic Bacteria, as Revealed by Viral Tagging
Open Access
- 31 December 2012
- journal article
- Published by American Society for Microbiology in mBio
- Vol. 3 (6)
- https://doi.org/10.1128/mbio.00373-12
Abstract
Ocean viruses are ubiquitous and abundant and play important roles in global biogeochemical cycles by means of their mortality, horizontal gene transfer, and manipulation of host metabolism. However, the obstacles involved in linking viruses to their hosts in a high-throughput manner bottlenecks our ability to understand virus-host interactions in complex communities. We have developed a method called viral tagging (VT), which combines mixtures of host cells and fluorescent viruses with flow cytometry. We investigated multiple viruses which infect each of two model marine bacteria that represent the slow-growing, photoautotrophic genus Synechococcus (Cyanobacteria) and the fast-growing, heterotrophic genus Pseudoalteromonas (Gammaproteobacteria). Overall, viral tagging results for viral infection were consistent with plaque and liquid infection assays for cyanobacterial myo-, podo- and siphoviruses and some (myo- and podoviruses) but not all (four siphoviruses) heterotrophic bacterial viruses. Virus-tagged Pseudoalteromonas organisms were proportional to the added viruses under varied infection conditions (virus-bacterium ratios), while no more than 50% of the Synechococcus organisms were virus tagged even at viral abundances that exceeded (5 to 10×) that of their hosts. Further, we found that host growth phase minimally impacts the fraction of virus-tagged Synechococcus organisms while greatly affecting phage adsorption to Pseudoalteromonas. Together these findings suggest that at least two contrasting viral life strategies exist in the oceans and that they likely reflect adaptation to their host microbes. Looking forward to the point at which the virus-tagging signature is well understood (e.g., for Synechococcus), application to natural communities should begin to provide population genomic data at the proper scale for predictively modeling two of the most abundant biological entities on Earth.This publication has 90 references indexed in Scilit:
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