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Viruses 2018, 10(9), 468; https://doi.org/10.3390/v10090468

Quantitative Infection Dynamics of Cafeteria Roenbergensis Virus

1
Program for Computational Biology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
2
School of Biological Sciences and School of Physics, Georgia Institute of Technology, Atlanta, GA 30332, USA
3
Department of Marine Microbiology and Biogeochemistry, NIOZ Royal Netherlands Institute of Sea Research, and University of Utrecht, P.O. Box 59, 1790 AB Den Burg, Texel, The Netherlands
4
Aquatic Microbiology, Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, P.O. Box 94248, 1090 GE Amsterdam, The Netherlands
5
Department of Biomolecular Mechanisms, Max Planck Institute for Medical Research, 69120 Heidelberg, Germany
*
Author to whom correspondence should be addressed.
Received: 3 August 2018 / Revised: 24 August 2018 / Accepted: 26 August 2018 / Published: 31 August 2018
(This article belongs to the Special Issue Algae Virus)
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Abstract

The discovery of giant viruses in unicellular eukaryotic hosts has raised new questions on the nature of viral life. Although many steps in the infection cycle of giant viruses have been identified, the quantitative life history traits associated with giant virus infection remain unknown or poorly constrained. In this study, we provide the first estimates of quantitative infection traits of a giant virus by tracking the infection dynamics of the bacterivorous protist Cafeteria roenbergensis and its lytic virus CroV. Leveraging mathematical models of infection, we quantitatively estimate the adsorption rate, onset of DNA replication, latency time, and burst size from time-series data. Additionally, by modulating the initial ratio of viruses to hosts, we also provide evidence of a potential MOI-dependence on adsorption and burst size. Our work provides a baseline characterization of giant virus infection dynamics relevant to ongoing efforts to understand the ecological role of giant viruses. View Full-Text
Keywords: giant viruses; multiple infections; virus factories; infection modeling; CroV giant viruses; multiple infections; virus factories; infection modeling; CroV
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Taylor, B.P.; Weitz, J.S.; Brussaard, C.P.D.; Fischer, M.G. Quantitative Infection Dynamics of Cafeteria Roenbergensis Virus. Viruses 2018, 10, 468.

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