Multidrug-resistant tuberculosis (MDR-TB), caused by drug-resistant strains of Mycobacterium tuberculosis, is an increasingly serious problem worldwide. Here we examined a data set of whole-genome sequences from 5,310 M. tuberculosis isolates from five continents. Despite the great diversity of these isolates with respect to geographical point of isolation, genetic background and drug resistance, the patterns for the emergence of drug resistance were conserved globally. We have identified harbinger mutations that often precede multidrug resistance. In particular, the katG mutation encoding p.Ser315Thr, which confers resistance to isoniazid, overwhelmingly arose before mutations that conferred rifampicin resistance across all of the lineages, geographical regions and time periods. Therefore, molecular diagnostics that include markers for rifampicin resistance alone will be insufficient to identify pre-MDR strains. Incorporating knowledge of polymorphisms that occur before the emergence of multidrug resistance, particularly katG p.Ser315Thr, into molecular diagnostics should enable targeted treatment of patients with pre-MDR-TB to prevent further development of MDR-TB.
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We would like to thank the Broad Institute's Genome Sequencing Platform and Assembly and Annotation teams, including S.K. Young, M.E. Priest, T.P. Shea, B.J. Walker, L. Alvarado, M.G. Fitzgerald, S. Gujja, S. Hamilton, C. Howarth, J.D. Larimer, M.D. Pearson, Q. Zeng and J. Wortman. We would like to thank J. Romano and A. Keo for help with lineage detection, and M. Zambrano, B. Ferro and J.C. Rozo for isolation and phenotypic characterization of strains. We are also grateful to members of the TBResist Consortium for contribution of their strains, phenotypic data and expertise, and their help in forging collaborations, and to V. Dartois, D. Thomas, D. Hung and D. Plachetzki for helpful conversations. We also thank three anonymous reviewers of our manuscript for their insights and helpful suggestions. This project has been funded in whole or in part with federal funds from the National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health, Department of Health and Human Services (grant U19AI110818 to the Broad Institute (B.W.B. and A.M.E.)), contract HHSN272200900018C to the Broad Institute (B.W.B.) and contract HHSN2722000900050C to the TB Clinical Diagnostics Research Consortium, the Intramural Research Program of NIAID (C.E.B. and L.E.V.) and the Korean CDC, Korean Ministry of Health and Welfare. This work was also funded (in part) by the intramural research program of the NIAID, NIH (C.E.B.). Funding was also provided by NIH grant 5U01AI069924-07 for IeDEA (A.S.P.), the Howard Hughes Medical Institute (W.R.B.) and NIH grant R01 AI110386 for 'Host–pathogen interactions in a failing global lineage of MTBC: M. africanum' (W.R.B.). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the NIH.
The authors declare no competing financial interests.
Integrated supplementary information
(a) Geographic distribution of M. tuberculosis isolates by lineage. This plot shows the sampling frequency within our data set of 5,310 strains and is not necessarily indicative of overall global incidence. The pie charts illustrate the relative proportions of M. tuberculosis lineages isolated within each of 11 UN subregions (http://unstats.un.org/unsd/methods/m49/m49regin.htm). The map is colored by UN geographic subregion. There were no strains in our data set from geographic regions colored gray. UN geographic subregions with fewer than 30 strains were excluded from this figure. This map was modified from a blank map of UN geographical subregions (Pusch, T.; licensed under CC BY-SA 3.0 via Wikimedia Commons; https://commons.wikimedia.org/wiki/File:Geografiaj_subregionoj_la%C5%AD_Unui%C4%9Dintaj_Nacioj_malplene.svg). (b) Global prevalence for each of six WHO global subregions as a percentage of total global TB burden (black bars), side by side with the percentage of our data set from each of these regions. We used different geographic subdivisions (WHO rather than UN) for this panel to present our data side by side with WHO data. Note that our data set is under-represented in strains from Southeast Asia (which includes India) and over-represented in strains from Africa and Europe (which includes Russia). WHO global subregions are defined as follows. AFR (Africa): Algeria, Angola, Benin, Burkina Faso, Cameroon, Cape Verde, Chad, Comoros, Equatorial Guinea, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Madagascar, Mali, Mauritania, Mauritius, Niger, Nigeria, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone, Togo, Botswana, Burundi, Central African Republic, Congo, Côte d'Ivoire, Democratic Republic of the Congo, Eritrea, Ethiopia, Kenya, Lesotho, Malawi, Mozambique, Namibia, Rwanda, South Africa, Swaziland, Uganda, United Republic of Tanzania, Zambia, Zimbabwe; AMR (Americas): Canada, Cuba, United States of America, Antigua and Barbuda, Argentina, Bahamas, Barbados, Belize, Brazil, Chile, Colombia, Costa Rica, Dominica, Dominican Republic, El Salvador, Grenada, Guyana, Honduras, Jamaica, Mexico, Panama, Paraguay, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, Uruguay, Venezuela, Bolivia, Ecuador, Guatemala, Haiti, Nicaragua, Peru; EMR (Eastern Mediterranean): Bahrain, Cyprus, Iran (Islamic Republic of), Jordan, Kuwait, Lebanon, Libyan Arab Jamahiriya, Oman, Qatar, Saudi Arabia, Syrian Arab Republic, Tunisia, United Arab Emirates, Afghanistan, Djibouti, Egypt, Iraq, Morocco, Pakistan, Somalia, Sudan, Yemen; EUR (Europe): Andorra, Austria, Belgium, Croatia, Czech Republic, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Israel, Italy, Luxembourg, Malta, Monaco, Netherlands, Norway, Portugal, San Marino, Slovenia, Spain, Sweden, Switzerland, United Kingdom, Albania, Armenia, Azerbaijan, Bosnia and Herzegovina, Bulgaria, Georgia, Kyrgyzstan, Poland, Romania, Slovakia, Tajikistan, The Former Yugoslav Republic of Macedonia, Turkey, Turkmenistan, Uzbekistan, Yugoslavia, Belarus, Estonia, Hungary, Kazakhstan, Latvia, Lithuania, Republic of Moldova, Russian Federation, Ukraine; SEAR (Southeast Asia): Indonesia, Sri Lanka, Thailand, Bangladesh, Bhutan, Democratic People's Republic of Korea, India, Maldives, Myanmar, Nepal, Timor Leste; WPR (Western Pacific): Cambodia, China, Cook Islands, Fiji, Kiribati, Lao People's Democratic Republic, Malaysia, Marshall Islands, Micronesia (Federated States of), Mongolia, Nauru, Niue, Palau, Papua New Guinea, Philippines, Republic of Korea, Samoa, Solomon Islands, Tonga, Tuvalu, Vanuatu, Viet Nam, Australia, Brunei Darussalam, Japan, New Zealand, Singapore.
Supplementary Figure 2 Phylogenetic tree of all 5,310 M. tuberculosis isolates indicating data set of origin.
Phylogenetic tree of all 5,310 M. tuberculosis isolates (Online Methods). Colors in the outer circle indicate the data set of origin for each strain. In the central radial phylogeny, lineages are labeled and color-coded as follows: pink, lineage 1; blue, lineage 2; purple, lineage 3; red, lineage 4; brown, lineage 5 (M. africanum); dark green, lineage 6 (M. africanum); orange, lineage 7; light green, M. bovis.
Supplementary Figure 3 Phylogenetic tree of all 5,310 M. tuberculosis isolates indicating geographic region of isolation.
Phylogenetic tree of all 5,310 M. tuberculosis isolates (Online Methods). Colors in the outer circle indicate the geographic region of isolation. In the central radial phylogeny, lineages are labeled and color-coded as follows: pink, lineage 1; blue, lineage 2; purple, lineage 3; red, lineage 4; brown, lineage 5 (M. africanum); dark green, lineage 6 (M. africanum); orange, lineage 7; light green, M. bovis.
Supplementary Figure 4 Phylogenetic tree of all 5,310 M. tuberculosis isolates indicating genotypic drug resistance pattern.
Phylogenetic tree of all 5,310 M. tuberculosis isolates (Online Methods). Colors in the outer circle indicate the genotypic drug resistance pattern of the corresponding strain. In the central radial phylogeny, lineages are labeled and color-coded as follows: pink, lineage 1; blue, lineage 2; purple, lineage 3; red, lineage 4; brown, lineage 5 (M. africanum); dark green, lineage 6 (M. africanum); orange, lineage 7; light green, M. bovis.
Supplementary Figure 5 Rates of genotypic resistance to individual drugs across our entire data set of 5,310 strains.
The greatest numbers of strains were resistant to isoniazid, rifampicin and streptomycin.
The number of arisals and number of strains for each of the 392 drug resistance mutations detected in our data set.
Data are shown for each lineage with greater than 100 strains in our data set.
Supplementary Figure 8 Breakdown of genotypic resistance to individual antituberculous drugs by predicted lineage.
M. tuberculosis strains from lineages 5, 6 and 7 were excluded because of low numbers of isolates, and lineage B was excluded as all 44 strains were fully drug susceptible.
Supplementary Figure 9 Breakdown of resistance to individual antituberculous drugs by UN geographic region.
Geographic distribution of strains in 11 UN geographic regions having greater than 30 representative isolates in this data set (45 strains that derived from 6 UN geographic regions were excluded from this figure).
(a) Breakdown of monoresistance by geographic region and by lineage. (b) Breakdown of poly-drug resistance (excluding MDR, pre-XDR and MDR) by geographic region and by lineage.
Supplementary Figure 11 Percentage of nodes where resistance to other drugs arose prior or coincident with an Xpert MTB/RIF-detectable mutation.
(a) Resistance to single drugs. (b) Resistance to multiple drugs. This figure shows results for cases where all nodes between the first and last drug acquisition event leading up to the Xpert MTB/RIF-detectable mutation fit our filtering criteria (>90% bootstrap in the more ancestral node of a pair; maximal branch lengths between pairs <1 × 10–4).
Supplementary Figures 1–11, Supplementary Tables 1, 3, 4, 6 and 8–13, and Supplementary Note (PDF 3734 kb)
List of 5,310 strains included in our final data set of sequenced M. tuberculosis clinical isolates. (XLSX 414 kb)
List of all 392 mutations in our data set and their frequencies, as well as their frequencies of occurring first. (XLSX 122 kb)
The number of arisals and the number of strains with each mutation, for each of the 11 geographical regions with >30 strains. (XLSX 127 kb)
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Manson, A., Cohen, K., Abeel, T. et al. Genomic analysis of globally diverse Mycobacterium tuberculosis strains provides insights into the emergence and spread of multidrug resistance. Nat Genet 49, 395–402 (2017). https://doi.org/10.1038/ng.3767
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