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dc.contributor.authorPhelan, Jody
dc.contributor.authorColl, Francesc
dc.contributor.authorMcNerney, Ruth
dc.contributor.authorAscher, David B.
dc.contributor.authorPires, Douglas E. V.
dc.contributor.authorFurnham, Nick
dc.contributor.authorCoeck, Nele
dc.contributor.authorHill-Cawthorne, Grant A.
dc.contributor.authorNair, Mridul
dc.contributor.authorMallard, Kim
dc.contributor.authorRamsay, Andrew
dc.contributor.authorCampino, Susana
dc.contributor.authorHibberd, Martin L.
dc.contributor.authorPain, Arnab
dc.contributor.authorRigouts, Leen
dc.contributor.authorClark, Taane G.
dc.date.accessioned2016-03-24T13:16:51Z
dc.date.available2016-03-24T13:16:51Z
dc.date.issued2016-03-23
dc.identifier.citationMycobacterium tuberculosis whole genome sequencing and protein structure modelling provides insights into anti-tuberculosis drug resistance 2016, 14 (1) BMC Medicine
dc.identifier.issn1741-7015
dc.identifier.pmid27005572
dc.identifier.doi10.1186/s12916-016-0575-9
dc.identifier.urihttp://hdl.handle.net/10754/603611
dc.description.abstractBackground 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.
dc.description.sponsorshipJP is supported by a BBSRC PhD studentship. The project was supported by the KAUST faculty baseline research fund (KAUST-BRF) to AP. The authors wish to thank members of KAUST Bioscience Core laboratory who sequenced the isolate DNA. DBA is supported by an NHMRC CJ Martin Fellowship (APP1072476). DEVP is supported by René Rachou Research Center (CPqRR/FIOCRUZ Minas). DBA and DEVP are funded by a Newton Fund RCUK-CONFAP Grant awarded by The Medical Research Council (MRC) and Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG). NF is funded by a Medical Research Council Methodology Research Fellowship (MR//K020420). TGC is funded by the Medical Research Council UK (Grant no. MR/K000551/1, MR/M01360X/1, MR/N010469/1). There are no conflicts of interests.
dc.language.isoen
dc.publisherSpringer Nature
dc.relation.urlhttp://www.biomedcentral.com/1741-7015/14/31
dc.rightsThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://​creativecommons.​org/​licenses/​by/​4.​0/​), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated.
dc.subjectTuberculosis
dc.subjectDrug resistance
dc.subjectGenomics
dc.subjectProtein structural modelling
dc.subjectAssociation study
dc.subjectConvergent evolution
dc.titleMycobacterium tuberculosis whole genome sequencing and protein structure modelling provides insights into anti-tuberculosis drug resistance
dc.typeArticle
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Division
dc.contributor.departmentBioscience Program
dc.contributor.departmentComputational Bioscience Research Center (CBRC)
dc.contributor.departmentPathogen Genomics Laboratory
dc.identifier.journalBMC Medicine
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionFaculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT, UK
dc.contributor.institutionUniversity of Cape Town Lung Institute, Lung Infection & Immunity Unit, Old Main Building, Groote Schuur Hospital, Observatory, Cape Town 7925, South Africa
dc.contributor.institutionDepartment of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge CB2 1GA, UK
dc.contributor.institutionCentro de Pesquisas René Rachou, Fundação Oswaldo Cruz, Avenida Augusto de Lima 1715, Belo Horizonte 30190-002, Brazil
dc.contributor.institutionMycobacteriology Unit, Institute of Tropical Medicine, Antwerp, Belgium
dc.contributor.institutionSydney Emerging Infections and Biosecurity Institute and School of Public Health, Sydney Medical School, University of Sydney, Sydney, NSW 2006, Australia
dc.contributor.institutionSpecial Programme for Research and Training in Tropical Diseases (TDR), World Health Organisation, Geneva, Switzerland
dc.contributor.institutionDepartment of Biomedical Sciences, Antwerp University, Antwerp, Belgium
dc.contributor.institutionFaculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT, UK
dc.contributor.institutionDepartment of Pathogen Molecular Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, UK
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)
kaust.personHill-Cawthorne, Grant A.
kaust.personNair, Mridul
kaust.personPain, Arnab
dc.relation.issupplementedbyDOI:10.6084/m9.figshare.c.3633278
refterms.dateFOA2018-06-13T13:08:22Z
display.relations<b> Is Supplemented By:</b> <br/> <ul><li><i>[Dataset]</i> <br/> Phelan, J., Coll, F., McNerney, R., Ascher, D., Pires, D., Furnham, N., … Taane Clark. (2016). Mycobacterium tuberculosis whole genome sequencing and protein structure modelling provides insights into anti-tuberculosis drug resistance. Figshare. https://doi.org/10.6084/m9.figshare.c.3633278. DOI: <a href="https://doi.org/10.6084/m9.figshare.c.3633278">10.6084/m9.figshare.c.3633278</a> HANDLE: <a href="http://hdl.handle.net/10754/624138">10754/624138</a></li></ul>
kaust.acknowledged.supportUnitBioscience Core Laboratory
dc.date.published-online2016-03-23
dc.date.published-print2016-12


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