A new study shows that differences in the vulnerability of animals to a virus are crucial to understanding patterns of infection, and that variation in susceptibility to two marginally different viruses increases the number of infections when the two virus variants are present in the same animal. This study, by researchers from the Netherlands and Spain, will be published on June 30th in the open-access journal PLoS Computational Biology.
Models of virus infection often fail to predict how many animals will become infected and which virus variants will be present in the infected animals, even under controlled laboratory conditions. To discover whether these models are fundamentally wrong or simply not detailed enough, the researchers created four mathematical models of virus infection. They subsequently tested the predictive ability of the models against data from laboratory experiments in which they exposed caterpillars, Lepidopteran larvae, to insect viruses.
"We were surprised to find that a relatively simple model could describe the data", says Mark Zwart, one of the study´s authors and currently a postdoctoral fellow at the Instituto de Biología Molecular y Celular de Plantas, Spain. "The only ingredient we needed to add to an infection model was differences in caterpillar vulnerability to the virus. Our work confirms that virus particles independently infect animals, even in situations where we thought they might be working together."
The study improves our understanding of how virus particles interact with each other and the host animal during infection, and concludes that "Most deviations from [model] predictions may be caused by variation in host susceptibility". The extent to which this conclusion applies to other viruses and pathogens is not yet clear and a follow-up study on a wide range of different pathogens is currently being carried out.
Funding: MPZ was supported in part by a Rubicon Grant from the Netherlands Organisation for Scientific Research (NWO, www.nwo.nl), and a grant from the C.T. de Wit Graduate School for 'Production Ecology and Resource Conservation'. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
Citation: van der Werf W, Hemerik L, Vlak JM, Zwart MP (2011) Heterogeneous Host Susceptibility Enhances Prevalence of Mixed-Genotype Micro-Parasite Infections. PLoS Comput Biol 7(6): e1002097. doi:10.1371/journal.pcbi.1002097
Mark P. Zwart, Ph.D.
Instituto de Biología Molecular y Celular de Plantas (CSIC-UPV),Valencia, Spain
Phone (Office): +34 608 584 345
This press release refers to an upcoming article in PLoS Computational Biology. The release is provided by journal staff, or by the article authors and/or their institutions. Any opinions expressed in this release or article are the personal views of the journal staff and/or article contributors, and do not necessarily represent the views or policies of PLoS. PLoS expressly disclaims any and all warranties and liability in connection with the information found in the releases and articles and your use of such information.
PLoS Journals publish under a Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.5/), which permits free reuse of all materials published with the article, so long as the work is cited (e.g., Kaltenbach LS et al. (2007) Huntingtin Interacting Proteins Are Genetic Modifiers of Neurodegeneration. PLoS Genet 3(5): e82. doi:10.1371/journal.pgen.0030082). No prior permission is required from the authors or publisher. For queries about the license, please contact the relative journal contact indicated here: http://www.plos.org/journals/embargopolicy.php
About PLoS Computational Biology
PLoS Computational Biology (www.ploscompbiol.org) features works of exceptional significance that further our understanding of living systems at all scales through the application of computational methods. All works published in PLoS Computational Biology are open access. Everything is immediately available subject only to the condition that the original authorship and source are properly attributed. Copyright is retained.
About the Public Library of Science
The Public Library of Science (PLoS) is a non-profit organization of scientists and physicians committed to making the world's scientific and medical literature a freely available public resource. For more information, visit http://www.plos.org.
AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert! system.