Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Genome sequencing of 161 Mycobacterium tuberculosis isolates from China identifies genes and intergenic regions associated with drug resistance


The worldwide emergence of multidrug-resistant (MDR) and extensively drug-resistant (XDR) tuberculosis threatens to make this disease incurable1,2. Drug resistance mechanisms are only partially understood3,4,5, and whether the current understanding of the genetic basis of drug resistance in M. tuberculosis is sufficiently comprehensive remains unclear. Here we sequenced and analyzed 161 isolates with a range of drug resistance profiles, discovering 72 new genes, 28 intergenic regions (IGRs), 11 nonsynonymous SNPs and 10 IGR SNPs with strong, consistent associations with drug resistance. On the basis of our examination of the dN/dS ratios of nonsynonymous to synonymous SNPs among the isolates6,7,8, we suggest that the drug resistance–associated genes identified here likely contain essentially all the nonsynonymous SNPs that have arisen as a result of drug pressure in these isolates and should thus represent a near-complete set of drug resistance–associated genes for these isolates and antibiotics. Our work indicates that the genetic basis of drug resistance is more complex than previously anticipated and provides a strong foundation for elucidating unknown drug resistance mechanisms.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Figure 1: Phylogenetic analysis of M. tuberculosis isolates.
Figure 2: Genomic locations of the 85 drug resistance–associated genes.
Figure 3: IGR SNPs alter the expression level of downstream genes.
Figure 4: The 84 drug resistance–associated protein-encoding genes identified in this study contain essentially all the nonsynonymous SNPs that have arisen as a result of drug pressure in this set of isolates and antibiotics.

Accession codes

Primary accessions

Sequence Read Archive

Referenced accessions

NCBI Reference Sequence


  1. 1

    Gandhi, N.R. et al. Multidrug-resistant and extensively drug-resistant tuberculosis: a threat to global control of tuberculosis. Lancet 375, 1830–1843 (2010).

    Article  Google Scholar 

  2. 2

    Zumla, A. et al. Drug-resistant tuberculosis—current dilemmas, unanswered questions, challenges, and priority needs. J. Infect. Dis. 205 (suppl. 2), S228–S240 (2012).

    Article  Google Scholar 

  3. 3

    Goldberg, D.E., Siliciano, R.F. & Jacobs, W.R. Jr. Outwitting evolution: fighting drug-resistant TB, malaria, and HIV. Cell 148, 1271–1283 (2012).

    CAS  Article  Google Scholar 

  4. 4

    Laurenzo, D. & Mousa, S.A. Mechanisms of drug resistance in Mycobacterium tuberculosis and current status of rapid molecular diagnostic testing. Acta Trop. 119, 5–10 (2011).

    CAS  Article  Google Scholar 

  5. 5

    Zhang, Y. & Yew, W.W. Mechanisms of drug resistance in Mycobacterium tuberculosis. Int. J. Tuberc. Lung Dis. 13, 1320–1330 (2009).

    CAS  PubMed  Google Scholar 

  6. 6

    Elena, S.F. & Lenski, R.E. Evolution experiments with microorganisms: the dynamics and genetic bases of adaptation. Nat. Rev. Genet. 4, 457–469 (2003).

    CAS  Article  Google Scholar 

  7. 7

    Barrick, J.E. et al. Genome evolution and adaptation in a long-term experiment with Escherichia coli. Nature 461, 1243–1247 (2009).

    CAS  Article  Google Scholar 

  8. 8

    Woods, R., Schneider, D., Winkworth, C.L., Riley, M.A. & Lenski, R.E. Tests of parallel molecular evolution in a long-term experiment with Escherichia coli. Proc. Natl. Acad. Sci. USA 103, 9107–9112 (2006).

    CAS  Article  Google Scholar 

  9. 9

    World Health Organization. Global Tuberculosis Control 2011 (World Health Organization, Geneva, 2011).

  10. 10

    Zhao, Y. et al. National survey of drug-resistant tuberculosis in China. N. Engl. J. Med. 366, 2161–2170 (2012).

    CAS  Article  Google Scholar 

  11. 11

    Ford, C.B. et al. Mycobacterium tuberculosis mutation rate estimates from different lineages predict substantial differences in the emergence of drug-resistant tuberculosis. Nat. Genet. 45, 784–790 (2013).

    CAS  Article  Google Scholar 

  12. 12

    Casali, N. et al. Microevolution of extensively drug-resistant tuberculosis in Russia. Genome Res. 22, 735–745 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. 13

    Walker, T.M. et al. Whole-genome sequencing to delineate Mycobacterium tuberculosis outbreaks: a retrospective observational study. Lancet Infect. Dis. 13, 137–146 (2013).

    CAS  Article  Google Scholar 

  14. 14

    Ford, C.B. et al. Use of whole genome sequencing to estimate the mutation rate of Mycobacterium tuberculosis during latent infection. Nat. Genet. 43, 482–486 (2011).

    CAS  Article  Google Scholar 

  15. 15

    Ioerger, T.R. et al. Genome analysis of multi- and extensively-drug-resistant tuberculosis from KwaZulu-Natal, South Africa. PLoS ONE 4, e7778 (2009).

    Article  Google Scholar 

  16. 16

    Cole, S.T. et al. Deciphering the biology of Mycobacterium tuberculosis from the complete genome sequence. Nature 393, 537–544 (1998).

    CAS  Article  Google Scholar 

  17. 17

    Comas, I. et al. Human T cell epitopes of Mycobacterium tuberculosis are evolutionarily hyperconserved. Nat. Genet. 42, 498–503 (2010).

    CAS  Article  Google Scholar 

  18. 18

    Hershberg, R. et al. High functional diversity in Mycobacterium tuberculosis driven by genetic drift and human demography. PLoS Biol. 6, e311 (2008).

    PubMed  PubMed Central  Google Scholar 

  19. 19

    Gagneux, S. & Small, P.M. Global phylogeography of Mycobacterium tuberculosis and implications for tuberculosis product development. Lancet Infect. Dis. 7, 328–337 (2007).

    Article  Google Scholar 

  20. 20

    Müller, B., Borrell, S., Rose, G. & Gagneux, S. The heterogeneous evolution of multidrug-resistant Mycobacterium tuberculosis. Trends Genet. 29, 160–169 (2013).

    Article  Google Scholar 

  21. 21

    Ramaswamy, S. & Musser, J.M. Molecular genetic basis of antimicrobial agent resistance in Mycobacterium tuberculosis: 1998 update. Tuber. Lung Dis. 79, 3–29 (1998).

    CAS  Article  Google Scholar 

  22. 22

    Sandgren, A. et al. Tuberculosis drug resistance mutation database. PLoS Med. 6, e2 (2009).

    Article  Google Scholar 

  23. 23

    Sekiguchi, J. et al. Detection of multidrug resistance in Mycobacterium tuberculosis. J. Clin. Microbiol. 45, 179–192 (2007).

    CAS  Article  Google Scholar 

  24. 24

    Zaunbrecher, M.A., Sikes, R.D. Jr., Metchock, B., Shinnick, T.M. & Posey, J.E. Overexpression of the chromosomally encoded aminoglycoside acetyltransferase eis confers kanamycin resistance in Mycobacterium tuberculosis. Proc. Natl. Acad. Sci. USA 106, 20004–20009 (2009).

    CAS  Article  Google Scholar 

  25. 25

    World Health Organization. Guidelines for Surveillance of Drug Resistance in Tuberculosis (World Health Organization, Geneva, 2009).

  26. 26

    World Health Organization. Treatment of Tuberculosis: Guidelines for National Programmes 4th edn. (World Health Organization, Geneva, 2009).

  27. 27

    Huang, W., Sherman, B.T. & Lempicki, R.A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4, 44–57 (2009).

    CAS  Article  Google Scholar 

  28. 28

    Mohanty, D., Sankaranarayanan, R. & Gokhale, R.S. Fatty acyl-AMP ligases and polyketide synthases are unique enzymes of lipid biosynthetic machinery in Mycobacterium tuberculosis. Tuberculosis (Edinb.) 91, 448–455 (2011).

    CAS  Article  Google Scholar 

  29. 29

    Schroeder, E.K., de Souza, N., Santos, D.S., Blanchard, J.S. & Basso, L.A. Drugs that inhibit mycolic acid biosynthesis in Mycobacterium tuberculosis. Curr. Pharm. Biotechnol. 3, 197–225 (2002).

    CAS  Article  Google Scholar 

  30. 30

    Heath, R.J., White, S.W. & Rock, C.O. Lipid biosynthesis as a target for antibacterial agents. Prog. Lipid Res. 40, 467–497 (2001).

    CAS  Article  Google Scholar 

  31. 31

    Birch, H.L. et al. Biosynthesis of mycobacterial arabinogalactan: identification of a novel α(1→3) arabinofuranosyltransferase. Mol. Microbiol. 69, 1191–1206 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. 32

    Gavalda, S. et al. The Pks13/FadD32 crosstalk for the biosynthesis of mycolic acids in Mycobacterium tuberculosis. J. Biol. Chem. 284, 19255–19264 (2009).

    CAS  Article  Google Scholar 

  33. 33

    Domenech, P., Reed, M.B. & Barry, C.E. III. Contribution of the Mycobacterium tuberculosis MmpL protein family to virulence and drug resistance. Infect. Immun. 73, 3492–3501 (2005).

    CAS  Article  Google Scholar 

  34. 34

    La Rosa, V. et al. MmpL3 is the cellular target of the antitubercular pyrrole derivative BM212. Antimicrob. Agents Chemother. 56, 324–331 (2012).

    CAS  Article  Google Scholar 

  35. 35

    Tahlan, K. et al. SQ109 targets MmpL3, a membrane transporter of trehalose monomycolate involved in mycolic acid donation to the cell wall core of Mycobacterium tuberculosis. Antimicrob. Agents Chemother. 56, 1797–1809 (2012).

    CAS  Article  Google Scholar 

  36. 36

    Deidda, D. et al. Bactericidal activities of the pyrrole derivative BM212 against multidrug-resistant and intramacrophagic Mycobacterium tuberculosis strains. Antimicrob. Agents Chemother. 42, 3035–3037 (1998).

    CAS  Article  Google Scholar 

  37. 37

    Comas, I. et al. Whole-genome sequencing of rifampicin-resistant Mycobacterium tuberculosis strains identifies compensatory mutations in RNA polymerase genes. Nat. Genet. 44, 106–110 (2012).

    CAS  Article  Google Scholar 

  38. 38

    Ramaswamy, S.V. et al. Single nucleotide polymorphisms in genes associated with isoniazid resistance in Mycobacterium tuberculosis. Antimicrob. Agents Chemother. 47, 1241–1250 (2003).

    CAS  Article  Google Scholar 

  39. 39

    Rindi, L. et al. Mutations responsible for Mycobacterium tuberculosis isoniazid resistance in Italy. Int. J. Tuberc. Lung Dis. 9, 94–97 (2005).

    CAS  PubMed  Google Scholar 

  40. 40

    Gagneux, S. et al. Impact of bacterial genetics on the transmission of isoniazid-resistant Mycobacterium tuberculosis. PLoS Pathog. 2, e61 (2006).

    Article  Google Scholar 

  41. 41

    Fivian-Hughes, A.S., Houghton, J. & Davis, E.O. Mycobacterium tuberculosis thymidylate synthase gene thyX is essential and potentially bifunctional, while thyA deletion confers resistance to p-aminosalicylic acid. Microbiology 158, 308–318 (2012).

    CAS  Article  Google Scholar 

  42. 42

    Reese, M.G. Application of a time-delay neural network to promoter annotation in the Drosophila melanogaster genome. Comput. Chem. 26, 51–56 (2001).

    CAS  Article  Google Scholar 

  43. 43

    Nellen, W. & Hammann, C. Small RNAs: Analysis and Regulatory Functions (Springer, Heidelberg, Germany, 2005).

  44. 44

    Song, T. & Wai, S.N. A novel sRNA that modulates virulence and environmental fitness of Vibrio cholerae. RNA Biol. 6, 254–258 (2009).

    CAS  Article  Google Scholar 

  45. 45

    Arnvig, K.B. et al. Sequence-based analysis uncovers an abundance of non-coding RNA in the total transcriptome of Mycobacterium tuberculosis. PLoS Pathog. 7, e1002342 (2011).

    CAS  Article  Google Scholar 

  46. 46

    Miotto, P. et al. Genome-wide discovery of small RNAs in Mycobacterium tuberculosis. PLoS ONE 7, e51950 (2012).

    CAS  Article  Google Scholar 

  47. 47

    Griffin, J.E. et al. High-resolution phenotypic profiling defines genes essential for mycobacterial growth and cholesterol catabolism. PLoS Pathog. 7, e1002251 (2011).

    CAS  Article  Google Scholar 

  48. 48

    Telenti, A. et al. Detection of rifampicin-resistance mutations in Mycobacterium tuberculosis. Lancet 341, 647–650 (1993).

    CAS  Article  Google Scholar 

  49. 49

    Koenig, R. Few mutations divide some drug-resistant TB strains. Science 318, 901–902 (2007).

    CAS  Article  Google Scholar 

  50. 50

    Fleischmann, R.D. et al. Whole-genome comparison of Mycobacterium tuberculosis clinical and laboratory strains. J. Bacteriol. 184, 5479–5490 (2002).

    CAS  Article  Google Scholar 

  51. 51

    World Health Organization. Policy Guidance on TB Drug Susceptibility Testing (DST) of Second-Line Drugs (World Health Organization, Geneva, 2008).

  52. 52

    Kamerbeek, J. et al. Simultaneous detection and strain differentiation of Mycobacterium tuberculosis for diagnosis and epidemiology. J. Clin. Microbiol. 35, 907–914 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. 53

    Demay, C. et al. SITVITWEB—a publicly available international multimarker database for studying Mycobacterium tuberculosis genetic diversity and molecular epidemiology. Infect. Genet. Evol. 12, 755–766 (2012).

    CAS  Article  Google Scholar 

  54. 54

    van Soolingen, D., Hermans, P.W., de Haas, P.E., Soll, D.R. & van Embden, J.D. Occurrence and stability of insertion sequences in Mycobacterium tuberculosis complex strains: evaluation of an insertion sequence–dependent DNA polymorphism as a tool in the epidemiology of tuberculosis. J. Clin. Microbiol. 29, 2578–2586 (1991).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. 55

    Li, R. et al. SOAP2: an improved ultrafast tool for short read alignment. Bioinformatics 25, 1966–1967 (2009).

    CAS  Google Scholar 

  56. 56

    Benson, G. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res. 27, 573–580 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. 57

    Tarailo-Graovac, M. & Chen, N. Using RepeatMasker to identify repetitive elements in genomic sequences. Curr. Protoc. Bioinformatics Chapter 4, Unit 4.10 (2009).

  58. 58

    Zhang, Z. et al. KaKs_Calculator: calculating Ka and Ks through model selection and model averaging. Genomics Proteomics Bioinformatics 4, 259–263 (2006).

    CAS  Article  Google Scholar 

Download references


We would like to thank S.M. Wang for helpful discussions and input and the anonymous reviewers for their constructive comments. We thank D. Chatterji (Indian Institute of Science) for the pSD5B vector. L.B. was supported by the National Natural Science Foundation of China (grant 31170132), the National Basic Research Program of China (grants 2009CB825402 and 2012CB518703), the Chinese Academy of Sciences (grant KSZD-EW-Z-006) and the Key Project Specialized for Infectious Diseases of the Chinese Ministry of Health (grants 2012ZX10003002 and 2013ZX10003006).

Author information




H.Z. conducted the experiments. D.L., J.F., H.Z., N.L., Y.H., Z.L., Y. Zhu, S.W., M.W., Y. Zhou, J.D., J.W., R.Y., G.Z., N.G., H.H., L. Zhao, J. Zhou and J. Zhang contributed to data analysis. K.W., L. Zhao, C.L., Q.Z., L. Zhou, T.C. and F.L. collected the isolates. Y.G., H.Z., L. Zhao, N.L. and T.C. cultured the isolates and prepared DNA samples. Tong Wang performed genome sequencing and assembly. H.Z. and Ting Wang performed the IGR promoter experiments. J.F. and H.Z. wrote and revised the manuscript. X.-E.Z. directed part of the work, and L.B. conceived, designed and provided overall direction for the project.

Corresponding authors

Correspondence to Kanglin Wan or Jun Wang or Xian-En Zhang or Lijun Bi.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–6 and Supplementary Tables 1–19 (PDF 21834 kb)

Source data

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Zhang, H., Li, D., Zhao, L. et al. Genome sequencing of 161 Mycobacterium tuberculosis isolates from China identifies genes and intergenic regions associated with drug resistance. Nat Genet 45, 1255–1260 (2013).

Download citation

Further reading


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing