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Model-selection-based approach for calculating cellular multiplicity of infection during virus colonization of multi-cellular hosts

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Model-selection-based approach for calculating cellular multiplicity of infection during virus colonization of multi-cellular hosts

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dc.contributor.author Zwart, Mark Peter es_ES
dc.contributor.author Tromas ., Nicolas es_ES
dc.contributor.author Elena Fito, Santiago Fco es_ES
dc.date.accessioned 2014-08-28T12:22:55Z
dc.date.available 2014-08-28T12:22:55Z
dc.date.issued 2013-05
dc.identifier.issn 1932-6203
dc.identifier.uri http://hdl.handle.net/10251/39278
dc.description.abstract The cellular multiplicity of infection (MOI) is a key parameter for describing the interactions between virions and cells, predicting the dynamics of mixed-genotype infections, and understanding virus evolution. Two recent studies have reported in vivo MOI estimates for Tobacco mosaic virus (TMV) and Cauliflower mosaic virus (CaMV), using sophisticated approaches to measure the distribution of two virus variants over host cells. Although the experimental approaches were similar, the studies employed different definitions of MOI and estimation methods. Here, new model-selection-based methods for calculating MOI were developed. Seven alternative models for predicting MOI were formulated that incorporate an increasing number of parameters. For both datasets the best-supported model included spatial segregation of virus variants over time, and to a lesser extent aggregation of virus-infected cells was also implicated. Three methods for MOI estimation were then compared: the two previously reported methods and the best-supported model. For CaMV data, all three methods gave comparable results. For TMV data, the previously reported methods both predicted low MOI values (range: 1.04-1.23) over time, whereas the best-supported model predicted a wider range of MOI values (range: 1.01-2.10) and an increase in MOI over time. Model selection can therefore identify suitable alternative MOI models and suggest key mechanisms affecting the frequency of coinfected cells. For the TMV data, this leads to appreciable differences in estimated MOI values. es_ES
dc.description.sponsorship This work was supported by grant BFU2012-30805 (SFE) and by 'Juan de la Cierva' postdoctoral contract JCI-2011-10379 (MPZ) from the Spanish Secretaria de Estado de Investigacion, Desarrollo e Innovacion. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. en_EN
dc.language Inglés es_ES
dc.publisher Public Library of Science es_ES
dc.relation 'Juan de la Cierva' postdoctoral contract from the Spanish Secretaria de Estado de Investigacion, Desarrollo e Innovacion JCI-2011-10379 es_ES
dc.relation BFU2012-30805 (SFE) es_ES
dc.relation.ispartof PLoS ONE es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Risoners-dilemma es_ES
dc.subject Mosaic-virus es_ES
dc.subject Nucleopolyhedrovirus es_ES
dc.subject Populations es_ES
dc.subject Movement es_ES
dc.title Model-selection-based approach for calculating cellular multiplicity of infection during virus colonization of multi-cellular hosts es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1371/journal.pone.0064657
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario Mixto de Biología Molecular y Celular de Plantas - Institut Universitari Mixt de Biologia Molecular i Cel·lular de Plantes es_ES
dc.description.bibliographicCitation Zwart, MP.; Tromas ., N.; Elena Fito, SF. (2013). Model-selection-based approach for calculating cellular multiplicity of infection during virus colonization of multi-cellular hosts. PLoS ONE. 8:64657-64657. doi:10.1371/journal.pone.0064657 es_ES
dc.description.accrualMethod Senia es_ES
dc.relation.publisherversion http://dx.doi.org/10.1371/journal.pone.0064657 es_ES
dc.description.upvformatpinicio 64657 es_ES
dc.description.upvformatpfin 64657 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 8 es_ES
dc.relation.senia 260385
dc.identifier.pmid 23724074 en_EN
dc.identifier.pmcid PMC3665715 en_EN


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