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dc.contributor.authorKosuri, Sriram
dc.contributor.authorGoodman, Daniel Bryan
dc.contributor.authorCambray, Guillaume
dc.contributor.authorMutalik, Vivek K.
dc.contributor.authorGao, Yuan
dc.contributor.authorArkin, Adam P.
dc.contributor.authorEndy, Drew
dc.contributor.authorChurch, George M.
dc.date.accessioned2014-08-28T17:31:22Z
dc.date.available2014-08-28T17:31:22Z
dc.date.issued2013-08
dc.date.submitted2013-02
dc.identifier.issn0027-8424
dc.identifier.issn1091-6490
dc.identifier.urihttp://hdl.handle.net/1721.1/89095
dc.description.abstractThe inability to predict heterologous gene expression levels precisely hinders our ability to engineer biological systems. Using well-characterized regulatory elements offers a potential solution only if such elements behave predictably when combined. We synthesized 12,563 combinations of common promoters and ribosome binding sites and simultaneously measured DNA, RNA, and protein levels from the entire library. Using a simple model, we found that RNA and protein expression were within twofold of expected levels 80% and 64% of the time, respectively. The large dataset allowed quantitation of global effects, such as translation rate on mRNA stability and mRNA secondary structure on translation rate. However, the worst 5% of constructs deviated from prediction by 13-fold on average, which could hinder large-scale genetic engineering projects. The ease and scale this of approach indicates that rather than relying on prediction or standardization, we can screen synthetic libraries for desired behavior.en_US
dc.description.sponsorshipAgilent Technologiesen_US
dc.description.sponsorshipWyss Institute for Biologically Inspired Engineeringen_US
dc.description.sponsorshipNational Science Foundation (U.S.). Graduate Research Fellowshipen_US
dc.language.isoen_US
dc.publisherNational Academy of Sciences (U.S.)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1073/pnas.1301301110en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourcePNASen_US
dc.titleComposability of regulatory sequences controlling transcription and translation in Escherichia colien_US
dc.typeArticleen_US
dc.identifier.citationKosuri, S., D. B. Goodman, G. Cambray, V. K. Mutalik, Y. Gao, A. P. Arkin, D. Endy, and G. M. Church. “Composability of Regulatory Sequences Controlling Transcription and Translation in Escherichia Coli.” Proceedings of the National Academy of Sciences 110, no. 34 (August 7, 2013): 14024–14029.en_US
dc.contributor.departmentHarvard University--MIT Division of Health Sciences and Technologyen_US
dc.contributor.mitauthorGoodman, Daniel Bryanen_US
dc.relation.journalProceedings of the National Academy of Sciencesen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsKosuri, S.; Goodman, D. B.; Cambray, G.; Mutalik, V. K.; Gao, Y.; Arkin, A. P.; Endy, D.; Church, G. M.en_US
dc.identifier.orcidhttps://orcid.org/0000-0003-3759-6883
mit.licensePUBLISHER_POLICYen_US
mit.metadata.statusComplete


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