Metabolism, gene expression and the evolution of drug resistance
- When?
- Friday 9 October 2009, 16:00
- Where?
- Department of Mathematics, room 22AA04
- Open to:
- Staff, Students
- Speaker:
- Caroline Colijn, University of Bristol
- Refreshments:
- Error processing inline link Content is not allowed in prolog.
Original content:
Coffee and tea will be available in 40AA04 from 3.45 pm
Abstract: Tuberculosis is a respiratory infectious disease estimated to kill 1.7 million people annually worldwide. Recently, outbreaks of multi- and extensively-drug-resistant variants of this pathogen have occurred in numerous disparate locations. TB is a fully sequenced organism, so we understand something about its metabolism, and there is a wealth of gene expression data available. But despite the importance of linking genotype to phenotype in pathogens like TB, methods to integrate these datasets have been somewhat lacking. In the first part of the talk, I'll present a computational method based on linear optimisation, for interpreting gene expression data in the context of a metabolic model, and apply it to mycolic acid production in M. tuberculosis. The method uncovers known anti-tuberculosis drugs including isoniazid, one of the main drugs to which TB is now becoming resistant.
Very rare single point mutations confer resistance to these drugs, but somehow, simultaneous resistance to up to 10 agents has emerged in multiple locations worldwide. In the second part of the talk, I'll show that the distribution of singly-resistant mutants in high-grade TB infections is approximated by an infinite-variance alpha-stable distribution. This means that the probability of seeing dually-resistant TB bacteria is orders of magnitude higher than has been reported previously. Combined with transmission of low levels of resistance, this can in part account for the frequency of occurrence of highly resistant disease.
