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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/26073
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dc.contributor.advisorWright, Gerard-
dc.contributor.authorCulp, Elizabeth-
dc.date.accessioned2020-12-09T20:49:51Z-
dc.date.available2020-12-09T20:49:51Z-
dc.date.issued2020-
dc.identifier.urihttp://hdl.handle.net/11375/26073-
dc.description.abstractAs the spread of antibiotic resistance threatens our ability to treat infections, avoiding the return of a pre-antibiotic era urgently requires the discovery of novel antibiotics. Actinomycetes, a family of bacteria commonly isolated from soil, are a proven source of clinically useful antibiotics. However, easily identifiable metabolites have been exhausted and the rediscovery of common antibiotics thwarts searches for rarer molecules. Sequencing of actinomycete genomes reveals that they contain far more biosynthetic gene clusters with the potential to encode antibiotics than whose products can be readily observed in the laboratory. The work presented in this thesis revolves around developing approaches to mine these previously inaccessible metabolites as a source of new antibiotics. First, I describe how inactivation of biosynthetic gene clusters for common antibiotics can uncover rare antibiotics otherwise masked in these strains. By applying CRISPR-Cas9 to knockout genes encoding nuisance antibiotics, I develop a simple strategy to reveal the hidden biosynthetic potential of actinomycete strains that can be used to discover rare or novel antibiotics. Second, I describe the use of the evolutionary history of biosynthetic gene clusters to prioritize divergent members of an antibiotic family, the glycopeptide antibiotics, that are likely to possess new biological activities. Using these predictions, I uncover a novel functional class of glycopeptide antibiotics that blocks the action of autolysins, essential peptidoglycan hydrolases required for remodelling the cell wall during growth. Finally, I apply target-directed genome mining, which makes use of target duplication as a predicted resistance mechanism within an antibiotic’s biosynthetic gene cluster. Using this approach, I discover the association of a family of gene clusters with the housekeeping protease ClpP and characterize the produced metabolite’s effect on ClpP function. These three research projects mine previously inaccessible chemical matter from a proven source of antibiotics, actinomycetes. The techniques and antibiotics described are required now more than ever to develop life-saving antibiotics capable of combatting multidrug-resistant pathogens.en_US
dc.language.isoenen_US
dc.subjectAntibioticsen_US
dc.subjectInfectious Diseaseen_US
dc.subjectActinomycetesen_US
dc.subjectNatural Productsen_US
dc.subjectBiosynthetic gene clusteren_US
dc.subjectGenome miningen_US
dc.subjectAutolysinen_US
dc.subjectClpPen_US
dc.titleBiosynthetic gene clusters guide rational antibiotic discovery from Actinomycetesen_US
dc.typeThesisen_US
dc.contributor.departmentBiochemistry and Biomedical Sciencesen_US
dc.description.degreetypeDissertationen_US
dc.description.degreeDoctor of Philosophy (PhD)en_US
dc.description.layabstractAntibiotics are essential for treating life-threatening infections, but the rise of antibiotic resistance renders them ineffective. To treat these drug-resistant infections, new antibiotics that work in new ways are required. A family of bacteria commonly isolated from soil called Actinomycetes produce most antibiotics we use today, but it has become increasingly difficult to find new antibiotics from this source. My work describes three techniques that can be applied to actinomycetes to help overcome the challenges associated with antibiotic discovery. Specifically, these techniques guide discovery efforts by making use of regions in actinomycete genomes called biosynthetic gene clusters that often encode antibiotics. In doing so, I describe ways to uncover rare antibiotics from actinomycete strains that produce common and uninteresting antibiotics, use antibiotic family trees to discover antibiotics that work in new ways, and apply antibiotic resistance to identify biosynthetic gene clusters likely to act on a certain bacterial target.en_US
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