Please use this identifier to cite or link to this item:
https://doi.org/10.1186/s12916-016-0575-9
Title: | Mycobacterium tuberculosis whole genome sequencing and protein structure modelling provides insights into anti-tuberculosis drug resistance | Authors: | Phelan, J Coll, F McNerney, R Ascher, D.B Pires, D.E Furnham, N Coeck, N Hill-Cawthorne, G.A Nair, M.B Mallard, K Ramsay, A Campino, S Hibberd, M.L Pain, A Rigouts, L Clark, T.G |
Keywords: | aminosalicylic acid capreomycin ethambutol ethionamide isoniazid ofloxacin rifampicin streptomycin tuberculostatic agent bacterial protein isoniazid tuberculostatic agent Article bacterial gene bacterial genome bacterium isolate binding site controlled study convergent evolution drug efficacy drug resistant tuberculosis gene mutation genetic association study genetic polymorphism minimum inhibitory concentration Mycobacterium tuberculosis nonhuman patient care protein stability protein structure tuberculosis control whole genome sequencing bacterial genome chemistry DNA sequence genetics genome-wide association study human isolation and purification metabolism microbial sensitivity test microbiology molecular model multidrug resistance mutation Mycobacterium tuberculosis protein conformation Tuberculosis, Multidrug-Resistant Antitubercular Agents Bacterial Proteins Drug Resistance, Multiple, Bacterial Genome, Bacterial Genome-Wide Association Study Humans Isoniazid Microbial Sensitivity Tests Models, Molecular Mutation Mycobacterium tuberculosis Protein Conformation Sequence Analysis, DNA Tuberculosis, Multidrug-Resistant |
Issue Date: | 2016 | Citation: | Phelan, J, Coll, F, McNerney, R, Ascher, D.B, Pires, D.E, Furnham, N, Coeck, N, Hill-Cawthorne, G.A, Nair, M.B, Mallard, K, Ramsay, A, Campino, S, Hibberd, M.L, Pain, A, Rigouts, L, Clark, T.G (2016). Mycobacterium tuberculosis whole genome sequencing and protein structure modelling provides insights into anti-tuberculosis drug resistance. BMC Medicine 14 (1) : 31. ScholarBank@NUS Repository. https://doi.org/10.1186/s12916-016-0575-9 | Rights: | Attribution 4.0 International | Abstract: | Background: Combating the spread of drug resistant tuberculosis is a global health priority. Whole genome association studies are being applied to identify genetic determinants of resistance to anti-tuberculosis drugs. Protein structure and interaction modelling are used to understand the functional effects of putative mutations and provide insight into the molecular mechanisms leading to resistance. Methods: To investigate the potential utility of these approaches, we analysed the genomes of 144 Mycobacterium tuberculosis clinical isolates from The Special Programme for Research and Training in Tropical Diseases (TDR) collection sourced from 20 countries in four continents. A genome-wide approach was applied to 127 isolates to identify polymorphisms associated with minimum inhibitory concentrations for first-line anti-tuberculosis drugs. In addition, the effect of identified candidate mutations on protein stability and interactions was assessed quantitatively with well-established computational methods. Results: The analysis revealed that mutations in the genes rpoB (rifampicin), katG (isoniazid), inhA-promoter (isoniazid), rpsL (streptomycin) and embB (ethambutol) were responsible for the majority of resistance observed. A subset of the mutations identified in rpoB and katG were predicted to affect protein stability. Further, a strong direct correlation was observed between the minimum inhibitory concentration values and the distance of the mutated residues in the three-dimensional structures of rpoB and katG to their respective drugs binding sites. Conclusions: Using the TDR resource, we demonstrate the usefulness of whole genome association and convergent evolution approaches to detect known and potentially novel mutations associated with drug resistance. Further, protein structural modelling could provide a means of predicting the impact of polymorphisms on drug efficacy in the absence of phenotypic data. These approaches could ultimately lead to novel resistance mutations to improve the design of tuberculosis control measures, such as diagnostics, and inform patient management. @ 2016 Phelan et al. | Source Title: | BMC Medicine | URI: | https://scholarbank.nus.edu.sg/handle/10635/179956 | ISSN: | 17417015 | DOI: | 10.1186/s12916-016-0575-9 | Rights: | Attribution 4.0 International |
Appears in Collections: | Staff Publications Elements |
Show full item record
Files in This Item:
File | Description | Size | Format | Access Settings | Version | |
---|---|---|---|---|---|---|
10_1186_s12916-016-0575-9.pdf | 1.77 MB | Adobe PDF | OPEN | None | View/Download |
This item is licensed under a Creative Commons License