Download Whole genome sequence analysis of Mycobacteria tuberculosis

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