Research Uncovered—Accelerating the Diagnosis of Drug-Resistant Tuberculosis: using a Combined Genetic and Computational Approach

 stjo_0130cm-bwWhat: Accelerating the Diagnosis of Drug-Resistant Tuberculosis: using a Combined Genetic and Computational Approach

Who: Philip Fowler

When: 13.00—14.00, Tuesday 22 November 2016

Where: Weston Library Lecture Theatre (map)

Access: all are welcome

Admission: free

Booking: registration is required

The discovery of antibiotics in the middle of the 20th century helped reduce the number of deaths from infectious diseases globally. Unfortunately, the use of antibiotics has inevitably led to bacteria developing resistance. It is vital, therefore, that doctors know which antibiotics can (and which cannot) be used to treat a patient with a bacterial infection, such as Tuberculosis (TB).

At present, a sample taken from the patient is sent to a laboratory, usually in a hospital, where the bacteria are grown and then different antibiotics administered to see which ones are effective. For a slow-growing bacterium like TB this process can take around a month. The incredible rate at which gene sequencing has got faster and cheaper now means that researchers, including the world-leading Modernising Medical Microbiology (MMM) group here at the University of Oxford, are beginning to replace the lab-based method with a genetics-based method.

This talk will describe this shift from lab-based to genetics-based microbiology that is happening in our hospitals and look at new methods that aim to predict the effect of individual mutations in TB genes.

Philip Fowler is a Senior Researcher working in the Modernising Medical Microbiology group at the John Radcliffe Hospital which is part of the Nuffield Department of Medicine at the University of Oxford. He is a computational biophysicist and his research focusses on using computer simulation to understand and predict how proteins and small molecules, like antibiotics, move and interact with one another. Philip blogs and is active on Twitter, @philipwfowler.

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