Superbugs, antibiotics and genome-wide association

CIME & CEES Extra seminar by Timothy D. Read from Emory University School of Medicine


My research interests center around the application of genomics technologies to understanding infectious diseases. In particular, I am interested in trying to frame the questions that only become possible to answer as new and even better instruments for generating DNA sequence information come online. 

Genomics for infectious disease detection and clinical diagnosis.
The rapidly decreasing cost of sequencing offers the opportunity in the near future to rapidly acquire large portions of the genome sequence of pathogens, either from DNA extracted from pure cultures or directly from clinical samples (metagenomics). I am interested in applying new technologies to determine their limits of sensitivity and to develop software to extract clinically useful information from the sequence data. 

Bacterial Pathogen Genome Evolution.
The availability of multiple high quality genomes of pathogens such as Bacillus anthracis (etiologic agent of anthrax) and its less pathogenic close relatives affords the opportunity to ask questions about the evolution of virulence in these lineages. My particular interest is the extrachromosomal elements such as plasmids and bacteriophage, and intergenic repeat sequences. These extraneous genetic entities often carry vital virulence genes (like the anthrax toxin and plague virulence genes). They are also potent factors for short term genome change, through insertion, expansion and movement in the genomes and through the selec​tion pressure they presumably exert on the genome for resistance. I am interested to find out how (and why) pathogens evolve to infect humans. What are the species that recent ancestors of B. anthracis were infecting before they developed virulence for mammals? What are the danger signs to look for in predicting the source of new emerging diseases? A genome based understanding of pathogen evolution will be vital for interpreting genetic variation in clinical sequence data (see above). The same knowledge can also be applied to vaccine and drug target selection.

Timothy D. Read
Emory University School of Medicine

Organised by Centre for Integrative Microbial Evolution (CIME) and Centre for Ecological and Evolutionary Synthesis (CEES), UiO

Published June 3, 2014 9:04 AM - Last modified June 3, 2014 9:29 AM