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dc.contributor.authorPardee, Keith
dc.contributor.authorGreen, Alexander A.
dc.contributor.authorLambert, Guillaume
dc.contributor.authorFerrante, Tom
dc.contributor.authorMa, Duo
dc.contributor.authorDonghia, Nina
dc.contributor.authorFan, Melina
dc.contributor.authorDudley, Dawn M.
dc.contributor.authorO’Connor, David H.
dc.contributor.authorTakahashi, Melissa Kimie
dc.contributor.authorBraff, Dana
dc.contributor.authorLee, Jeongwook
dc.contributor.authorDaringer, Nichole Marie
dc.contributor.authorBosch, Irene
dc.contributor.authorGehrke, Lee
dc.contributor.authorCollins, James J.
dc.date.accessioned2017-05-22T13:39:41Z
dc.date.available2017-05-22T13:39:41Z
dc.date.issued2016-05
dc.date.submitted2016-04
dc.identifier.issn0092-8674
dc.identifier.issn1097-4172
dc.identifier.urihttp://hdl.handle.net/1721.1/109241
dc.description.abstractThe recent Zika virus outbreak highlights the need for low-cost diagnostics that can be rapidly developed for distribution and use in pandemic regions. Here, we report a pipeline for the rapid design, assembly, and validation of cell-free, paper-based sensors for the detection of the Zika virus RNA genome. By linking isothermal RNA amplification to toehold switch RNA sensors, we detect clinically relevant concentrations of Zika virus sequences and demonstrate specificity against closely related Dengue virus sequences. When coupled with a novel CRISPR/Cas9-based module, our sensors can discriminate between viral strains with single-base resolution. We successfully demonstrate a simple, field-ready sample-processing workflow and detect Zika virus from the plasma of a viremic macaque. Our freeze-dried biomolecular platform resolves important practical limitations to the deployment of molecular diagnostics in the field and demonstrates how synthetic biology can be used to develop diagnostic tools for confronting global health crises.en_US
dc.description.sponsorshipDefense Threat Reduction Agency (DTRA) (HDTRA1-14-1-0006)en_US
dc.description.sponsorshipUnited States. National Institutes of Health (NIH AI100190)en_US
dc.language.isoen_US
dc.publisherElsevieren_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.cell.2016.04.059en_US
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs Licenseen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.sourceProf. Collins via Howard Silveren_US
dc.titleRapid, Low-Cost Detection of Zika Virus Using Programmable Biomolecular Componentsen_US
dc.typeArticleen_US
dc.identifier.citationPardee, Keith; Green, Alexander A.; Takahashi, Melissa K.; Braff, Dana; Lambert, Guillaume; Lee, Jeong Wook; Ferrante, Tom et al. “Rapid, Low-Cost Detection of Zika Virus Using Programmable Biomolecular Components.” Cell 165, no. 5 (May 2016): 1255–1266. © 2016 Elsevier Incen_US
dc.contributor.departmentInstitute for Medical Engineering and Scienceen_US
dc.contributor.departmentHarvard University--MIT Division of Health Sciences and Technologyen_US
dc.contributor.approverCollins, Jamesen_US
dc.contributor.mitauthorTakahashi, Melissa Kimie
dc.contributor.mitauthorBraff, Dana
dc.contributor.mitauthorLee, Jeongwook
dc.contributor.mitauthorDaringer, Nichole Marie
dc.contributor.mitauthorBosch, Irene
dc.contributor.mitauthorGehrke, Lee
dc.contributor.mitauthorCollins, James J.
dc.relation.journalCellen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsPardee, Keith; Green, Alexander A.; Takahashi, Melissa K.; Braff, Dana; Lambert, Guillaume; Lee, Jeong Wook; Ferrante, Tom; Ma, Duo; Donghia, Nina; Fan, Melina; Daringer, Nichole M.; Bosch, Irene; Dudley, Dawn M.; O’Connor, David H.; Gehrke, Lee; Collins, James J.en_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0003-0705-0177
dc.identifier.orcidhttps://orcid.org/0000-0002-2026-8130
dc.identifier.orcidhttps://orcid.org/0000-0002-9387-8212
dc.identifier.orcidhttps://orcid.org/0000-0002-5560-8246
mit.licensePUBLISHER_CCen_US
mit.metadata.statusComplete


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