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dc.contributor.authorByrd, Allyson Lindsayen_US
dc.date.accessioned2017-05-02T18:00:15Z
dc.date.issued2017
dc.identifier.urihttps://hdl.handle.net/2144/21963
dc.description.abstractMetagenomics, or genomic sequence of the community of microbiota (bacteria, fungi, virus), enables an investigation of the full complement of genetic material, including virulence, antibiotic resistance, and strain differentiating markers. The granularity to distinguish between closely related strains is important as within one species, these strains possess distinct functions and relationships to a host. To analyze metagenomic samples, I developed a reference-based approach that utilizes both single nucleotide variants and genetic content to assign species and strain-level designations. After refining this approach with complex simulated communities, I utilized it to analyze the microbial communities present in skin samples from healthy and diseased individuals. First, to investigate strain-level heterogeneity in healthy adults, I focused on the common skin commensals Propionibacterium acnes and Staphylococcus epidermidis with well-documented sequence variation. Results indicated that an individual’s strains of P. acnes are shared across multiple sites of his or her body, and that those strains are more similar within than between individuals. For S. epidermidis, in addition to individual site similarities, there were also site-specific strains. Overall these results emphasize that both individuality and site specificity shape our bodies’ microbial communities. Based on longitudinal data, an individual’s strain signatures remain stable for up to a year despite external, environmental perturbations. I then used metagenomic data to explore microbial temporal dynamics in atopic dermatitis (AD; eczema), an inflammatory skin disease commonly associated with Staphylococcal species. Species-level investigation of AD flares demonstrated a microbial dichotomy in which S. aureus predominated on more severely affected patients while S. epidermidis predominated on less severely affected patients. Strain-level analysis determined that S. aureus-predominant patients were monocolonized with distinct S. aureus strains, while all patients had heterogeneous S. epidermidis strain communities. To assess the host immunologic effects of these species, I topically applied patient-derived strains to mice. AD strains of S. aureus were sufficient to elicit a skin immune response, characteristic of AD patients. This suggests a model whereby staphylococcal strains contribute to AD progression through activation of the host immune system. Overall, this strain-level analysis of healthy and disease communities provides previously unexplored resolution of human skin microbiome.en_US
dc.language.isoen_US
dc.rightsAttribution-ShareAlike 4.0 Internationalen_US
dc.rights.urihttps://creativecommons.org/licenses/by-sa/4.0/
dc.subjectBioinformaticsen_US
dc.subjectAtopic dermatitisen_US
dc.subjectMetagenomicsen_US
dc.subjectMicrobiomeen_US
dc.subjectMicrobiotaen_US
dc.subjectSkinen_US
dc.subjectStaphylococcusen_US
dc.titleBacterial strain-tracking across the human skin landscape in health and diseaseen_US
dc.typeThesis/Dissertationen_US
dc.date.updated2017-03-24T22:08:04Z
dc.description.embargo2018-03-24T00:00:00Z
etd.degree.nameDoctor of Philosophyen_US
etd.degree.leveldoctoralen_US
etd.degree.disciplineBioinformatics GRSen_US
etd.degree.grantorBoston Universityen_US


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Except where otherwise noted, this item's license is described as Attribution-ShareAlike 4.0 International