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dc.contributor.authorWallach, T
dc.contributor.authorSchellenberg, K
dc.contributor.authorMaier, B
dc.contributor.authorKalathur, RKR
dc.contributor.authorPorras, P
dc.contributor.authorWanker, EE
dc.contributor.authorFutschik, Matthias
dc.contributor.authorKramer, A
dc.date.accessioned2017-02-07T19:52:42Z
dc.date.available2017-02-07T19:52:42Z
dc.date.issued2013-03
dc.identifier.issn1553-7404
dc.identifier.issn1553-7404
dc.identifier.otherARTN e1003398
dc.identifier.urihttp://hdl.handle.net/10026.1/8413
dc.description.abstract

Essentially all biological processes depend on protein-protein interactions (PPIs). Timing of such interactions is crucial for regulatory function. Although circadian (~24-hour) clocks constitute fundamental cellular timing mechanisms regulating important physiological processes, PPI dynamics on this timescale are largely unknown. Here, we identified 109 novel PPIs among circadian clock proteins via a yeast-two-hybrid approach. Among them, the interaction of protein phosphatase 1 and CLOCK/BMAL1 was found to result in BMAL1 destabilization. We constructed a dynamic circadian PPI network predicting the PPI timing using circadian expression data. Systematic circadian phenotyping (RNAi and overexpression) suggests a crucial role for components involved in dynamic interactions. Systems analysis of a global dynamic network in liver revealed that interacting proteins are expressed at similar times likely to restrict regulatory interactions to specific phases. Moreover, we predict that circadian PPIs dynamically connect many important cellular processes (signal transduction, cell cycle, etc.) contributing to temporal organization of cellular physiology in an unprecedented manner.

dc.format.extente1003398-e1003398
dc.format.mediumPrint-Electronic
dc.languageen
dc.language.isoeng
dc.publisherPublic Library of Science (PLoS)
dc.subjectARNTL Transcription Factors
dc.subjectCLOCK Proteins
dc.subjectCell Cycle
dc.subjectCircadian Clocks
dc.subjectCircadian Rhythm
dc.subjectErbB Receptors
dc.subjectHEK293 Cells
dc.subjectHumans
dc.subjectProtein Interaction Maps
dc.subjectProtein Phosphatase 1
dc.subjectSignal Transduction
dc.titleDynamic Circadian Protein–Protein Interaction Networks Predict Temporal Organization of Cellular Functions
dc.typejournal-article
dc.typeJournal Article
dc.typeResearch Support, Non-U.S. Gov't
plymouth.author-urlhttps://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000316866700069&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008
plymouth.issue3
plymouth.volume9
plymouth.publication-statusPublished online
plymouth.journalPLoS Genetics
dc.identifier.doi10.1371/journal.pgen.1003398
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Faculty of Health
plymouth.organisational-group/Plymouth/Users by role
dc.publisher.placeUnited States
dcterms.dateAccepted2013-02-05
dc.identifier.eissn1553-7404
dc.rights.embargoperiodNot known
rioxxterms.versionofrecord10.1371/journal.pgen.1003398
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2013-03
rioxxterms.typeJournal Article/Review


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