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dc.contributor.authorMünch, Karin
dc.contributor.authorMünch, Richard
dc.contributor.authorBiedendieck, Rebekka
dc.contributor.authorJahn, Dieter
dc.contributor.authorMüller, Johannes
dc.date.accessioned2019-05-10T13:10:31Z
dc.date.available2019-05-10T13:10:31Z
dc.date.issued2019-01-01
dc.identifier.citationPLoS Comput Biol. 2019 Mar 5;15(3):e1006724. doi: 10.1371/journal.pcbi.1006724 eCollection 2019 Mar.en_US
dc.identifier.issn1553-7358
dc.identifier.pmid30835726
dc.identifier.doi10.1371/journal.pcbi.1006724
dc.identifier.urihttp://hdl.handle.net/10033/621769
dc.description.abstractPlasmids are extrachromosomal DNA elements of microorganisms encoding beneficial genetic information. They were thought to be equally distributed to daughter cells during cell division. Here we use mathematical modeling to investigate the evolutionary stability of plasmid segregation for high-copy plasmids—plasmids that are present in up to several hundred copies per cell—carrying antibiotic resistance genes. Evolutionary stable strategies (ESS) are determined by numerical analysis of a plasmid-load structured population model. The theory predicts that the evolutionary stable segregation strategy of a cell depends on the plasmid copy number: For low and medium plasmid load, both daughters receive in average an equal share of plasmids, while in case of high plasmid load, one daughter obtains distinctively and systematically more plasmids. These findings are in good agreement with recent experimental results. We discuss the interpretation and practical consequences.en_US
dc.language.isoenen_US
dc.publisherPLOSen_US
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.titleEvolutionary model for the unequal segregation of high copy plasmids.en_US
dc.typeArticleen_US
dc.contributor.departmentBRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.en_US
dc.identifier.journalPLoS computational biologyen_US
refterms.dateFOA2019-05-10T13:10:31Z
dc.source.journaltitlePLoS computational biology


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