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dc.contributor.authorChen, Pin-Yi
dc.contributor.authorQian, Yili
dc.contributor.authorDel Vecchio, Domitilla
dc.date.accessioned2021-11-09T18:55:10Z
dc.date.available2021-11-09T18:55:10Z
dc.date.issued2018-12
dc.identifier.urihttps://hdl.handle.net/1721.1/138033
dc.description.abstract© 2018 IEEE. CRISPR-mediated gene regulation is known for its ability to control multiple targets simultaneously due to its modular nature: the same dCas9 effector can target different genes simply by changing the associated gRNA. However, multiplexing requires the sharing of limited amounts of dCas9 protein among multiple gRNAs, leading to resource competition. In turn, competition between gRNAs for the same resource may hamper network function. In this work, we develop a general model that takes into account the sharing of limited amounts of dCas9 protein for arbitrary CRISPR-mediated gene repression networks. We demonstrate that, as a result of resource competition, hidden interactions appear, which modifies the intended network regulations. As a case study, we analyze the effects of these hidden interactions on repression cascades. In particular, we illustrate that perfect adaptation to resource fluctuations can be achieved in cascades with an even number of repressors. In contrast, cascades with an odd number of repressors are substantially impacted by resource competition.en_US
dc.language.isoen
dc.publisherIEEEen_US
dc.relation.isversionof10.1109/cdc.2018.8619016en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcebioRxiven_US
dc.titleA Model for Resource Competition in CRISPR-Mediated Gene Repressionen_US
dc.typeArticleen_US
dc.identifier.citationChen, Pin-Yi, Qian, Yili and Del Vecchio, Domitilla. 2018. "A Model for Resource Competition in CRISPR-Mediated Gene Repression." Proceedings of the IEEE Conference on Decision and Control, 2018-December.
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering
dc.relation.journalProceedings of the IEEE Conference on Decision and Controlen_US
dc.eprint.versionOriginal manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2020-07-08T14:00:45Z
dspace.date.submission2020-07-08T14:00:49Z
mit.journal.volume2018-Decemberen_US
mit.licenseOPEN_ACCESS_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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