Oliver Adams successfully elucidated the structure of the M. tuberculosis MmpL3 membrane transporter using cryo-EM and this has recently been published online in Structure. This was the main aim of his PhD studies in Simon Newstead‘s group in the Department of Biochemistry here in Oxford. It is an important protein structure since although other MmpL3 […]
Through the CompBioMed2 EU Centre of Excellence project I have funding to appoint a postdoctoral researcher to develop machine-learning models to predict whether an infection is susceptible to an antibiotic. The need for predictive methods, such as these, will grow in the coming years as more of clinical microbiology transitions to using genetics to infer […]
In this preprint, the CRyPTIC project proposes the maximum value of minimum inhibitory concentration (MIC) for 13 different anti-TB drugs below which a sample can be considered to be ‘genotypically wild-type’. It is necessary to establish these values, called epidemiological cutoff values (ECOFFs or ECVs), so that the MICs measured can be converted into binary […]
Although the population structure M. tuberculosis is clonal, one must be careful when inferring the effect of individual mutations on the effect of an antibiotic. Purely because a mutation appears to define a phylogeny does not mean it has no effect on the minimum inhibitory concentration. Read more here (Open Access).
AMyGDA is a python module that analyses photographs of 96-well plates and, by examining each well for bacterial growth, is able to read a series of minimum inhibitory concentrations for the antibiotics present on a plate. Previously it was only available to download from this website (due to licensing) if you gave your email address […]
Having only recently having to write bioinformatics Python code that e.g. interrogate GenBank files to find out the sequence of specific genes I’ve learnt a bit of Biopython. I’ve always wondered why (and I could be wrong) the bioinformatics community doesn’t make more use of numpy? For example the Seq class in Biopython seems to be […]
I was very pleased to be invited to contribute to this “Voices” article organised by the journal Cell Host and Microbe. You can read it here.
Usually, the protein that an antibiotic binds is essential for bacterial survival, which is how the drug has its effect. In this case, relatively few protein mutations arise that confer resistance, they are often subtle in nature and one can try to predict the phenotype of a protein mutation by considering how it affects the […]
In this Microbiology paper we show how a Python package, called the Automated Mycobacterial Detection Growth Algorithm (AMyDGA for short), can be used to independently read a 96-well plate designed for determining the minimum inhibitory concentration of 14 different anti-tubercular drugs. AMyGDA is reproducible and shows promising levels of accuracy. Where it fails, it does in […]
BashTheBug, a citizen science project I run that is helping us measure how different clinical samples of M. tuberculosis grow in the presence of 14 different antibiotics, reached its first million classifications earlier this week. To read more head over to its blog. The photo mosaic on the left is made up of images […]