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Comparative genomics analysis of Klebsiella oxytoca: an emerging cause of multi-drug resistant hospital infections

Description 
Klebsiella oxytoca is a Gram-negative bacterium that is increasingly recognised as an important cause of hospital-associated infections, including pneumonia, blood, urinary and wound infections. A subset of K. oxytoca are categorised as an urgent threat by public health organisations all over the world, and of particular concern are multi-drug resistant strains displaying resistance to the drugs-of-last resort. Yet in spite of this, little is known about the underlying diversity, epidemiology and evolution of this species. Comparative genomic analyses represent a powerful approach for understanding how bacterial pathogens evolve and spread to cause public health threats. In this project the student will apply the latest genomics analysis approaches to investigate the underlying genetic diversity of K. oxytoca strains collected in Australia and overseas. The student will explore the ancestral relationships among these strains, identify and compare antibiotic resistance and virulence genes, and genes defining the key surface antigens. The outcomes of this project will vastly improve our knowledge of K. oxyotoca biology. Importantly, it will provide an essential framework with which we can investigate and understand emerging pathogenic and drug-resistant variants. The scope of the work can be refined to accommodate projects of varying length and is best suited for students interested in the application of computational biology approaches (including command-line programs) to analyse and interpret large datasets. Specific analysis approaches will include de novo genome assembly and annotation, reference-based variant detection, BLAST search and phylogenetics. Prior experience using the Unix operating system and the Python programming language is preferred but not essential.
Essential criteria: 
Minimum entry requirements can be found here: https://www.monash.edu/admissions/entry-requirements/minimum
Keywords 
infectious disease, Klebsiella, antibiotic resistance, genomics, computational biology, microbiology
Available options 
PhD/Doctorate
Masters by research
Honours
BMedSc(Hons)
Time commitment 
Full-time
Top-up scholarship funding available 
No
Physical location 
Burnet Institute
Co-supervisors 
Dr 
Kelly Wyres
Dr 
Jane Hawkey

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