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Mycobacterium tuberculosis lineage 4 comprises globally distributed and geographically restricted sublineages

Nature Genetics volume 48, pages 1535–1543 (2016)Cite this article

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Abstract

Generalist and specialist species differ in the breadth of their ecological niches. Little is known about the niche width of obligate human pathogens. Here we analyzed a global collection of Mycobacterium tuberculosis lineage 4 clinical isolates, the most geographically widespread cause of human tuberculosis. We show that lineage 4 comprises globally distributed and geographically restricted sublineages, suggesting a distinction between generalists and specialists. Population genomic analyses showed that, whereas the majority of human T cell epitopes were conserved in all sublineages, the proportion of variable epitopes was higher in generalists. Our data further support a European origin for the most common generalist sublineage. Hence, the global success of lineage 4 reflects distinct strategies adopted by different sublineages and the influence of human migration.

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Figure 1: Definition and global frequency of lineage 4 sublineages.
Figure 2: Global distribution of lineage 4 sublineages.
Figure 3: Country-specific proportions of sublineages identify generalists and specialists.
Figure 4: Pairwise ratios of rates of nonsynonymous to synonymous substitutions (dN/dS) in generalist and specialist sublineages for different gene categories.
Figure 5: Frequency distribution of the number of epitopes with nonsynonymous variants in generalist and specialist sublineages.
Figure 6: Genome-based phylogeny and diversity by continent of 293 strains of the L4.3/LAM sublineage.

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Acknowledgements

We thank S. Lecher, S. Li and J. Zallet for technical support. Calculations were performed at the sciCORE scientific computing core facility at the University of Basel. This work was supported by the Swiss National Science Foundation (grants 310030_166687 (S.G.) and 320030_153442 (M.E.) and Swiss HIV Cohort Study grant 740 to L.F.), the European Research Council (309540-EVODRTB to S.G.), TB-PAN-NET (FP7-223681 to S.N.), PathoNgenTrace projects (FP7-278864-2 to S.N.), SystemsX.ch (S.G.), the German Center for Infection Research (DZIF; S.N.), the Novartis Foundation (S.G.), the Natural Science Foundation of China (91631301 to Q.G.), and the National Institute of Allergy and Infectious Diseases (5U01-AI069924-05) of the US National Institutes of Health (M.E.).

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Author notes

  1. David Stucki, Daniela Brites and Leïla Jeljeli: These authors contributed equally to this work.

Authors and Affiliations

  1. Swiss Tropical and Public Health Institute, Basel, Switzerland

    David Stucki, Daniela Brites, Mireia Coscolla, Andrej Trauner, Lukas Fenner, Liliana Rutaihwa, Sonia Borrell, Marie Ballif, Bijaya Malla, Serej D Ley, Hans-Peter Beck & Sebastien Gagneux

  2. University of Basel, Basel, Switzerland

    David Stucki, Daniela Brites, Mireia Coscolla, Andrej Trauner, Lukas Fenner, Liliana Rutaihwa, Sonia Borrell, Marie Ballif, Bijaya Malla, Serej D Ley, Hans-Peter Beck & Sebastien Gagneux

  3. Forschungszentrum Borstel, Borstel, Germany

    Leïla Jeljeli & Stefan Niemann

  4. Institut Pasteur de Tunis, Université de Tunis El Manar, Tunis, Tunisia

    Leïla Jeljeli & Helmi Mardassi

  5. Key Laboratory of Medical Molecular Virology of the Ministries of Education and Health, Institutes of Biomedical Sciences and Institute of Medical Microbiology, School of Basic Medical Sciences, Fudan University, Shanghai, China

    Qingyun Liu & Qian Gao

  6. Institute for Social and Preventive Medicine, University of Bern, Bern, Switzerland

    Lukas Fenner, Marie Ballif & Matthias Egger

  7. Laboratory of Infection and Immunity, School of Basic Medical Science, West China Center of Medical Sciences, Sichuan University, Chengdu, China

    Tao Luo

  8. School of Medicine, University of California at San Francisco, San Francisco, California, USA

    Midori Kato-Maeda

  9. Laboratório de Saúde Pública, Lisbon, Portugal

    Rita Macedo

  10. Hospital Nossa Senhora da Paz, Cubal, Angola

    Milagros Moreno

  11. Servei de Microbiologia, Hospital Clínic–ISGlobal, Barcelona, Spain

    Griselda Tudo Vilanova

  12. Victorian Infectious Diseases Reference Laboratory, Victoria, Australia

    Janet Fyfe & Maria Globan

  13. Ifakara Health Institute, Bagamoyo, Tanzania

    Jackson Thomas

  14. Public Health Ontario, Toronto, Ontario, Canada

    Frances Jamieson & Jennifer L Guthrie

  15. Noguchi Memorial Institute for Medical Research, University of Ghana, Accra, Ghana

    Adwoa Asante-Poku & Dorothy Yeboah-Manu

  16. Department of Medical Microbiology, Makerere University, Kampala, Uganda

    Eddie Wampande, Willy Ssengooba & Moses Joloba

  17. Department of Global Health, University of Amsterdam, Amsterdam, the Netherlands

    Willy Ssengooba

  18. Department of Molecular Biology and Microbiology, Case Western Reserve University, Cleveland, Ohio, USA

    W Henry Boom

  19. LabPlus, Auckland City Hospital, Auckland, New Zealand

    Indira Basu & James Bower

  20. Life and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, Braga, Portugal

    Margarida Saraiva

  21. ICVS/3B's—PT Government Associate Laboratory, Braga/Guimarães, Portugal

    Margarida Saraiva

  22. Oswaldo Cruz Institute, Rio de Janeiro, Brazil

    Sidra E G Vasconcellos & Philip Suffys

  23. and Department of Clinical Laboratory Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa

    Anastasia Koch, Robert Wilkinson & Linda Gail-Bekker

  24. Department of Medicine, Imperial College London, London, UK

    Robert Wilkinson

  25. Francis Crick Institute Mill Hill Laboratory, London, UK

    Robert Wilkinson

  26. Papua New Guinea Institute of Medical Research, Goroka, Papua New Guinea

    Serej D Ley

  27. Insitute of Tropical Medicine, Antwerp, Belgium

    Bouke C de Jong, Florian Gehre & Suriya Akter

  28. Tartu University Hospital United Laboratories, Mycobacteriology, Tartu, Estonia

    Kadri Toit

  29. Clinical Research Department, Epicentre, Paris, France

    Elisabeth Sanchez-Padilla & Maryline Bonnet

  30. Department of Microbiology, University Hospital La Fe, Valencia, Spain

    Ana Gil-Brusola

  31. Institute of Tropical Medicine, University of Tübingen, Tübingen, Germany

    Matthias Frank & Francine Ntoumi

  32. Institute Laboratory for Tuberculosis Research (LTR), Biotechnology Center (BTC), University of Yaoundé I, Yaoundé, Cameroon

    Veronique N Penlap Beng

  33. Department of Pathology, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA

    Kathleen Eisenach

  34. Department of Medical Laboratory Technology, Faculty of Medical Technology, Baghdad, Iraq

    Issam Alani

  35. Institute of Tropical Medicine and Infectious Diseases (ITROMID), Jomo Kenyatta University of Agriculture and Technology (JKUAT), Nairobi, Kenya

    Perpetual Wangui Ndung'u

  36. Department of Pathology, Aga Khan University Hospital (AKUH), Nairobi, Kenya

    Gunturu Revathi

  37. Medical Research Council, Fajara, The Gambia

    Florian Gehre

  38. Fondation Congolaise pour la Recherche Médicale, Université Marien Gouabi, Brazzaville, Republic of the Congo

    Francine Ntoumi

  39. Right to Care and the Clinical HIV Research Unit, University of the Witwatersrand, Johannesburg, South Africa

    Lynsey Stewart-Isherwood

  40. National Institute of Medical Research, Mbeya Medical Research Centre (NIMR-MMRC), Mbeya, Tanzania

    Nyanda E Ntinginya

  41. Division of Infectious Diseases and Tropical Medicine, Medical Centre of the University of Munich, and German Centre for Infection Research (DZIF), partner site Munich, Munich, Germany

    Andrea Rachow & Michael Hoelscher

  42. Emerging Bacterial Pathogens Unit, IRCCS, San Raffaele Scientific Institute, Milan, Italy

    Daniela Maria Cirillo

  43. Riga East University Hospital, Centre of Tuberculosis and Lung Diseases, Riga, Latvia

    Girts Skenders

  44. Department of Microbiology, WHO Supranational TB Reference Laboratory, Public Health Agency of Sweden, Solna, Sweden

    Sven Hoffner

  45. Department of Immunology and Cell Biology, Institute of Biotechnology, Vilnius University, Vilnius, Lithuania

    Daiva Bakonyte & Petras Stakenas

  46. Institute for Epidemiology, Schleswig-Holstein University Hospital, Kiel, Germany

    Roland Diel

  47. National Tuberculosis Reference Laboratory, Phthysiopneumology Institute, Chisinau, Moldova

    Valeriu Crudu

  48. 'Marius Nasta' Pneumophtisiology Institute, Bucharest, Romania

    Olga Moldovan

  49. Department of Infection and Immunity, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia

    Sahal Al-Hajoj

  50. Instituto de Medicina Tropical Alexander von Humboldt, Molecular Epidemiology Unit–Tuberculosis, Universidad Peruana Cayetano Heredia, Lima, Peru

    Larissa Otero & Francesca Barletta

  51. Warren Alpert School of Medicine at Brown University, Miriam Hospital, Providence, Rhode Island, USA

    E Jane Carter

  52. Moi University School of Medicine, Eldoret, Kenya

    E Jane Carter & Lameck Diero

  53. Université Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019, UMR 8204, CIIL, Centre d'Infection et d'Immunité de Lille, Lille, France

    Philip Supply

  54. Institute of Biomedicine of Valencia (IBV-CSIC), Valencia, Spain

    Iñaki Comas

  55. CIBER Epidemiology and Public Health, Madrid, Spain

    Iñaki Comas

  56. German Center for Infection Research, Borstel Site, Borstel, Germany

    Stefan Niemann

Authors
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Contributions

D.S., D. Brites, L.J., S.N. and S.G. planned the experiments. D.S., L.J., D. Brites, A.T., L.F., L.R., S.B., M. Ballif, Q.L., T.L., Q.G., M.K.-M., M. Bonnet, M.E., R.M., H.M., M.M., G.T.V., J.F., M.G., J.T., F.J., J.L.G., A.A.-P., D.Y.-M., E.W., W.S., M.J., W.H.B., I.B., J.B., M.S., S.E.G.V., P. Suffys, A.K., R.W., L.G.-B., B.M., S.D.L., H.-P.B., B.C.d.J., K.T., E.S.-P., M. Bonnet, A.G.-B., M.F., V.N.P.B., K.E., I.A., P.W.N., G.R., F.G., S. Akter, F.N., L.S.-I., N.E.N., A.R., M.H., D.M.C., G.S., S.H., D. Bakonyte, P. Stakenas, R.D., V.C., O.M., S. Al-Hajoj, L.O., F.B., E.J.C., L.D., P. Supply and I.C. contributed reagents and performed the experiments. D.S., L.J., D. Brites, M.C., S.N. and S.G. analyzed the data. D.S., L.J., D. Brites, S.N. and S.G. wrote the manuscript. All authors critically reviewed the manuscript.

Corresponding author

Correspondence to Sebastien Gagneux.

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Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Maximum-likelihood phylogeny of 72 MTBC lineage 4 isolates and 9,455 variable single-nucleotide positions.

Sublineage names were adapted from Coll et al. Newly identified or newly named sublineages are labeled in red. Sublineage-specific markers are indicated in black boxes on the branches. Gray boxes on branches indicate large sequence polymorphisms (LSP/RD) described previously. Black circles indicate clade-specific SNPs published previously.

Supplementary Figure 2 Principal component analysis of 9,455 variable single-nucleotide positions in 72 lineage 4 strains.

Each dot represents one of 72 MTBC lineage 4 strains. Colors correspond to those in Figure 1.

Supplementary Figure 3 Mean pairwise SNP distances within and between isolates of the ten sublineages of lineage 4.

Purple circles represent mean pairwise numbers of SNPs for isolates within sublineages, and blue squares represent mean pairwise numbers of SNPs between isolates of the corresponding sublineage and all other lineage 4 isolates. Error bars are single standard deviation. Total mean pairwise distances between sublineages were significantly higher than total pairwise distances within sublineages (Wilcoxon rank-sum test, P < 0.0001).

Supplementary Figure 4 Isolates of three sublineages of MTBC lineage 4 (L4.1.2/Haarlem, L4.3/LAM and L4.10/PGG3) were observed in more than 40 countries each.

L4.3/LAM was found at a proportion of 30–100% in more than 50% of the countries of its occurrence. The differences in proportions among sublineages were statistically significant (χ2 test, P = 0.001).

Supplementary Figure 5 Additional heat maps of the proportions of three sublineages that were intermediate in distribution and numbers of countries of occurrence.

Intensity of red corresponds to the proportion of each sublineage among all lineage 4 isolates. Scale is identical to that in Figure 3. Countries with fewer than three isolates in total are filled white. Gray fill means the sublineage is not found in the country. A total of 3,366 isolates were used.

Supplementary Figure 6 World maps showing the proportions of all sublineages, normalized by TB prevalence (WHO, 2013) and area of the country.

Intensity of red corresponds to the proportion of each sublineage among all lineage 4 isolates. Countries with fewer than three isolates in total are filled white. Gray fill means that the sublineage is not found in the country. A total of 3,366 isolates were used. (A) Specialist sublineages. (B) Generalist sublineages. (C) Intermediate sublineages.

Supplementary Figure 7 Minimum spanning tree (MST) based on 24 MIRU-VNTR typing data for a worldwide collection of 2,132 L4.3/LAM strains.

The length of the branches (continuous, dashed and dotted lines) denotes the number of allele changes between two patterns: solid lines represent 1, 2 or 3 changes; gray dashed lines represent 4 changes; and gray dotted lines represent 5 or more changes. Strains selected for genome sequencing are colored in red.

Supplementary Figure 8 Geographical distribution of the 293 L4.3/LAM isolates from 57 countries.

The 293 L4.3/LAM strains selected for genome sequencing covered all continents and included 129 strains from Africa (22 countries), 42 strains from the Americas (9 countries), 36 strains from Asia (12 countries), 83 strains from Europe (12 countries) and 3 strains from Oceania (2 countries).

Supplementary Figure 9 Maximum-likelihood phylogeny of 293 L4.3/LAM strains.

Label colors indicate continent of strain origin (blue, Europe/Mediterranean; red, sub-Saharan Africa; yellow, Americas; pink, Asia). Numbers on nodes show branch support from bootstrapping (500 pseudoreplicates). Circles indicate clades with deleted regions of difference (RD). H37Rv was used as the outgroup.

Supplementary Figure 10 Genome-based Bayesian phylogeny of 203 strains of the L4.6.1/Uganda sublineage.

H37Rv was used as the outgroup. Numbers on the nodes indicate posterior probabilities. Continent colors correspond to those in Supplementary Figure 9.

Supplementary Figure 11 Genome-based maximum-likelihood phylogeny of 203 strains of the L4.6.1/Uganda sublineage.

H37Rv was used as the outgroup. Number on the nodes indicate bootstrap support. Continent colors correspond to those in Supplementary Figure 9.

Supplementary Figure 12 Maximum-likelihood phylogeny of 228 strains of the L4.2/Haarlem sublineage based on an alignment of 15,567 variable positions.

H37Rv was used as the outgroup. Numbers on the nodes indicate posterior probabilities. Continent colors correspond to those in Supplementary Figure 9.

Supplementary Figure 13 Maximum-likelihood phylogeny of 301 strains of the L4.10/PGG3 sublineage based on an alignment of 25,678 variable positions.

train of L4.2/Haarlem sublineage was used as the outgroup. Number on the node indicate bootstrap support.

Supplementary Figure 14 Genome-based phylogeny of 293 strains of the L4.3/LAM sublineage.

As in Figure 6 but with reconstructed ancestral geographical regions using a maximum-parsimony method (S-DIVA). Bayesian phylogeny with label colors indicating continent of strain origin (blue, Europe/Mediterranean; red, sub-Saharan Africa; yellow, Americas; pink, Asia). Numbers on nodes indicate posterior probabilities from MrBayes. Pie charts show the reconstructed ancestral geographical regions of the internal nodes using a maximum-parsimony method (S-DIVA in RASP software). The hypothetical L4.3/LAM ancestor is indicated, and a European origin for this ancestor was supported. The colors correspond to continents.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–14 and Supplementary Tables 1–4, 6 and 8. (PDF 2896 kb)

Supplementary Table 5

Distribution of MTBC lineage 4 clinical isolates per country and per sublineage. (XLSX 24 kb)

Supplementary Table 7

Whole-genome sequence data accession codes. (XLSX 72 kb)

Supplementary Table 9

Description of epitopes containing non-singleton nonsynonymous mutations in the four sublineages analyzed. (XLSX 16 kb)

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Stucki, D., Brites, D., Jeljeli, L. et al. Mycobacterium tuberculosis lineage 4 comprises globally distributed and geographically restricted sublineages. Nat Genet 48, 1535–1543 (2016). https://doi.org/10.1038/ng.3704

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