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SGUL/LSHTM MRC London Intercollegiate Doctoral Training Partnership – 2017/18 Potential PhD Projects Title of PhD project Whole genome sequence analysis of Mycobacteria tuberculosis bacteria to identify the genetic determinants and mechanisms of anti-tuberculosis drug resistance Supervisor Prof Taane Clark LSHTM Co-Supervisor Prof Philip Butcher SGUL Brief description of project The emergence of strains of Mycobacterium tuberculosis resistant to the drugs used to treat the disease threatens to derail efforts to control tuberculosis, which remains a major global public health problem. Whole-genome sequencing of M. tuberculosis clinical isolates is facilitating the characterisation of mutations associated with drug resistance. Their detection offers a means of rapidly assessing susceptibility to anti tuberculosis drugs to improve patient management [1,2,3]. Whilst, mutations conferring resistance to some first-line treatments (e.g. rifampicin or isoniazid) have been well characterised, there are substantial gaps in knowledge for other drugs [4]. Genome-wide and phylogenetic-based association approaches have been proposed to identify novel genetic determinants of resistance to anti-tuberculosis drugs [4]. However, these approaches may be compromised by markers that barcode for strain-type, transmission and virulence [5] and the step-wise nature of treatments and potential cross-resistance. Applying a complementary protein structure and interaction modelling approach could elucidate the functional effects of putative mutations and provide insight into the molecular mechanisms leading to resistance [4]. In this project, we propose to use quantitative methods to: (1) disentangle markers associated with strain-types from those involving resistance to first- and second-line therapies; (2) use protein structure models to characterise the effects of mutations on protein stability and drug docking; (3) rapidly predict drug resistance from whole genome sequence data, and “learn” as more data becomes available. Genome sequence and drug susceptibility data is available immediately for over 8,000 M. tuberculosis samples sourced from 20 countries. We wish to identify novel resistance mutations and mechanisms, which ultimately could improve 1 SGUL/LSHTM MRC London Intercollegiate Doctoral Training Partnership – 2017/18 Potential PhD Projects the design of tuberculosis control measures, such as diagnostics, and inform patient management. References 1. Coll F, McNerney R, …, Clark TG. Rapid determination of anti-tuberculosis drug resistance from whole-genome sequences. Genome Med 2015, Genome Med. 2015; 7:51 2. Witney AA, Gould KA, …., Butcher PD. Clinical application of whole-genome sequencing to inform treatment for multidrug-resistant tuberculosis cases. J Clin Microbiol 2015, 53:1473–83. 3. Phelan J, O’Sullivan D, …. Clark TG. The variability and reproducibility of whole genome sequencing technology for detecting resistance to anti-tuberculous drugs. Genome Medicine. In press. 4. Phelan J, Coll F, …., Clark TG. Mycobacterium tuberculosis whole genome sequencing and protein structure modelling can provide insights into antituberculosis drug resistance. BMC Medicine 2016; 14:31 5. Coll F, McNerney R, ,..., Clark TG. A robust SNP barcode for typing Mycobacterium tuberculosis complex strains. Nat Commun 2014, 5:4812. Particular prior educational requirements for a student undertaking this project Standard School research degree entry requirements Skills we expect a student to develop/acquire whilst pursuing this project Bioinformatics, pathogen genomics, tuberculosis genetics, statistical and population genetics, mycobacterial biology, molecular biology, epidemiology 2