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dc.contributor.advisorMartin Polz.en_US
dc.contributor.authorYang, Joy,Ph.D.(Joy Yu)Massachusetts Institute of Technology.en_US
dc.contributor.otherMassachusetts Institute of Technology. Computational and Systems Biology Program.en_US
dc.date.accessioned2019-12-13T18:57:39Z
dc.date.available2019-12-13T18:57:39Z
dc.date.copyright2019en_US
dc.date.issued2019en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/123250
dc.descriptionThesis: Ph. D., Massachusetts Institute of Technology, Computational and Systems Biology Program, 2019en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 113-121).en_US
dc.description.abstractBacteriophage and their hosts are locked in an age-old arms race. Successful bacteria are subject to predation, forcing the population to diversify, and phage are also quick to adapt tactics for infecting these potential hosts. Sampling of closely related bacterial strains that differ in phage infection profiles can further elucidate the mechanisms of infection. The Polz Lab maintains the Nahant Collection - 243 Vibrio strains challenged by 241 unique phage, all with sequenced genomes. This is the largest phylogenetically resolved host-range cross test available to date. Genetically mapping out the depths of this dataset requires carefully designed analysis techniques as well as further experimental exploration. First, we narrow in on a specific phage in the Nahant Collection, 2.275.0, to characterize the pressures that may select for phage that shuttle their own translational machinery.en_US
dc.description.abstractWhile translation is generally considered a hallmark of cellular life, some phage carry abundant tRNA. 2.275.0 carries 18 tRNA spanning 13 amino acids. We find that while encoding translation-related components requires shuttling a larger phage genome, it also reduces dependence on host translational machinery, allowing the phage to be more aggressive in degrading and recycling the host genome and other resources required for replication. Next we develop a systematic approach for uncovering genomic features that underlie phage-host interactions. We find that correcting for phylogenetic relationships allows us to pick out relevant signals that would otherwise be drowned out by spurious correlations resulting from statistically oversampled blooms of microbes. Using these results, we wrote an interative javascript visualization to facilitate the process of developing testable hypotheses concerning the mechanisms of phage infection and host response.en_US
dc.description.abstractFrom the visualization, we are able to identify, in the hosts, mobile genetic elements containing restriction modification systems that may defend against infection, as well as membrane protein modifications that may serve as phage attachment sites.en_US
dc.description.statementofresponsibilityby Joy Yang.en_US
dc.format.extent121 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectComputational and Systems Biology Program.en_US
dc.titleStatistically inferring the mechanisms of phage-host interactionsen_US
dc.typeThesisen_US
dc.description.degreePh. D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computational and Systems Biology Programen_US
dc.identifier.oclc1130060258en_US
dc.description.collectionPh.D. Massachusetts Institute of Technology, Computational and Systems Biology Programen_US
dspace.imported2019-12-13T18:57:38Zen_US
mit.thesis.degreeDoctoralen_US
mit.thesis.departmentCSBen_US


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