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dc.contributor.authorPourhasanzade, Fateme
dc.contributor.authorIyer, Swami
dc.contributor.authorTjendra, Jesslyn
dc.contributor.authorLandor, Lotta Anni Ingeborg
dc.contributor.authorVåge, Selina
dc.date.accessioned2022-12-22T08:35:03Z
dc.date.available2022-12-22T08:35:03Z
dc.date.created2022-09-21T09:27:30Z
dc.date.issued2022
dc.identifier.issn1553-734X
dc.identifier.urihttps://hdl.handle.net/11250/3039169
dc.description.abstractViruses play diverse and important roles in ecosystems. In recent years, trade-offs between host and virus traits have gained increasing attention in viral ecology and evolution. However, microbial organism traits, and viral population parameters in particular, are challenging to monitor. Mathematical and individual-based models are useful tools for predicting virus-host dynamics. We have developed an individual-based evolutionary model to study ecological interactions and evolution between bacteria and viruses, with emphasis on the impacts of trade-offs between competitive and defensive host traits on bacteria-phage population dynamics and trait diversification. Host dynamics are validated with lab results for different initial virus to host ratios (VHR). We show that trade-off based, as opposed to random bacteria-virus interactions, result in biologically plausible evolutionary outcomes, thus highlighting the importance of trade-offs in shaping biodiversity. The effects of nutrient concentration and other environmental and organismal parameters on the virus-host dynamics are also investigated. Despite its simplicity, our model serves as a powerful tool to study bacteria-phage interactions and mechanisms for evolutionary diversification under various environmental conditions.en_US
dc.language.isoengen_US
dc.publisherPublic Library of Scienceen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleIndividual-based model highlights the importance of trade-offs for virus-host population dynamics and long-term coexistenceen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersionen_US
dc.rights.holderCopyright 2022 Pourhasanzade et al.en_US
dc.source.articlenumbere1010228en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2
dc.identifier.doi10.1371/journal.pcbi.1010228
dc.identifier.cristin2053759
dc.source.journalPLoS Computational Biologyen_US
dc.identifier.citationPLoS Computational Biology. 2022, 18 (6), e1010228.en_US
dc.source.volume18en_US
dc.source.issue6en_US


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