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dc.contributor.authorKehe, Jared Scott
dc.contributor.authorKulesa, Anthony Benjamin
dc.contributor.authorOrtiz, Anthony
dc.contributor.authorGore, Jeff
dc.contributor.authorBlainey, Paul C
dc.date.accessioned2020-03-30T19:22:13Z
dc.date.available2020-03-30T19:22:13Z
dc.date.issued2019-06-11
dc.identifier.issn0027-8424
dc.identifier.issn1091-6490
dc.identifier.urihttps://hdl.handle.net/1721.1/124422
dc.description.abstractMicrobial communities have numerous potential applications in biotechnology, agriculture, and medicine. Nevertheless, the limited accuracy with which we can predict interspecies interactions and environmental dependencies hinders efforts to rationally engineer beneficial consortia. Empirical screening is a complementary approach wherein synthetic communities are combinatorially constructed and assayed in high throughput. However, assembling many combinations of microbes is logistically complex and difficult to achieve on a timescale commensurate with microbial growth. Here, we introduce the kChip, a droplets-based platform that performs rapid, massively parallel, bottom-up construction and screening of synthetic microbial communities. We first show that the kChip enables phenotypic characterization of microbes across environmental conditions. Next, in a screen of ∼100,000 multispecies communities comprising up to 19 soil isolates, we identified sets that promote the growth of the model plant symbiont Herbaspirillum frisingense in a manner robust to carbon source variation and the presence of additional species. Broadly, kChip screening can identify multispecies consortia possessing any optically assayable function, including facilitation of biocontrol agents, suppression of pathogens, degradation of recalcitrant substrates, and robustness of these functions to perturbation, with many applications across basic and applied microbial ecology.en_US
dc.description.sponsorshipNational Science Foundation (U.S.). Graduate Research Fellowship (Fellow ID 2016220942)en_US
dc.description.sponsorshipNational Science Foundation (U.S.). Graduate Research Fellowship (Fellow ID 2013164251)en_US
dc.description.sponsorshipBurroughs Wellcome Fund (Career Award at the Scientific Interface Grant 1010240)en_US
dc.description.sponsorshipSimons Foundation (Grant 542385)en_US
dc.language.isoen
dc.publisherProceedings of the National Academy of Sciencesen_US
dc.relation.isversionof10.1073/pnas.1900102116en_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.subjectMultidisciplinaryen_US
dc.titleMassively parallel screening of synthetic microbial communitiesen_US
dc.typeArticleen_US
dc.identifier.citationKehe, Jared et al. "Massively parallel screening of synthetic microbial communities." Proceedings of the National Academy of Sciences of the United States of America 116 (2019):12804-12809 © 2019 The Author(s)en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biologyen_US
dc.relation.journalProceedings of the National Academy of Sciences of the United States of Americaen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2020-02-12T19:07:51Z
dspace.date.submission2020-02-12T19:07:52Z
mit.journal.volume116en_US
mit.journal.issue26en_US
mit.licensePUBLISHER_POLICY


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