Abstract

The application of next generation sequencing technologies has opened the door to a new molecular epidemiology of tuberculosis, in which we can now look at transmission at a resolution not possible before. At the same time, new technical and analytical challenges have appeared, and we are still exploring the wider potential of this new technology. Whole genome sequencing in tuberculosis still requires bacterial cultures. Thus, although whole genome sequencing has revolutionized the interpretation of transmission patterns, it is not yet ready to be applied at the point-of-care. In this chapter, I will review the promises and challenges of genomic epidemiology, as well as some of the new questions that have arisen from the use of this new technology. In addition, I will examine the role of molecular epidemiology within the general frame of global tuberculosis control and how genomic epidemiology can contribute towards the elimination of the disease.

Keywords

Transmission, genome sequencing, outbreak, mutation rate 

Notes

Acknowledgements

I thank the members of my group for stimulating discussions. Work in my laboratory is supported by the Spanish National Foundation (MINECO SAF2013-43521-R) and the European Research Council (638553-TB-ACCELERATE).

References

  1. Andries K, Villellas C, Coeck N et al (2014) Acquired resistance of Mycobacterium tuberculosis to bedaquiline. PLoS One 9:e102135CrossRefPubMedPubMedCentralGoogle Scholar
  2. Biek R, Pybus OG, Lloyd-Smith JO, Didelot X (2015) Measurably evolving pathogens in the genomic era. Trends Ecol Evol 30:306–313CrossRefPubMedPubMedCentralGoogle Scholar
  3. Black PA, de Vos M, Louw GE et al (2015) Whole genome sequencing reveals genomic heterogeneity and antibiotic purification in Mycobacterium tuberculosis isolates. BMC Genomics 16:857CrossRefPubMedPubMedCentralGoogle Scholar
  4. Bloemberg GV, Keller PM, Stucki D et al (2015) Acquired resistance to bedaquiline and delamanid int for tuberculosis. N Engl J Med 373:1986–1988CrossRefPubMedPubMedCentralGoogle Scholar
  5. Bradley P, Gordon NC, Walker TM et al (2015) Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis. Nat Commun 6:10063CrossRefPubMedPubMedCentralGoogle Scholar
  6. Brown AC, Bryant JM, Einer-Jensen K et al (2015) Rapid whole-genome sequencing of Mycobacterium tuberculosis isolates directly from clinical samples. J Clin Microbiol 53:2230–2237CrossRefPubMedPubMedCentralGoogle Scholar
  7. Bryant JM, Harris SR, Parkhill J et al (2013a) Whole-genome sequencing to establish relapse or re-infection with Mycobacterium tuberculosis: a retrospective observational study. Lancet Respir Med 1:786–792CrossRefPubMedPubMedCentralGoogle Scholar
  8. Bryant JM, Schürch AC, van Deutekom H et al (2013b) Inferring patient to patient transmission of Mycobacterium tuberculosis from whole genome sequencing data. BMC Infect Dis 13:110CrossRefPubMedPubMedCentralGoogle Scholar
  9. Casali N, Nikolayevskyy V, Balabanova Y et al (2014) Evolution and transmission of drug-resistant tuberculosis in a Russian population. Nat Genet 46:279–286CrossRefPubMedPubMedCentralGoogle Scholar
  10. Cohen K, Abeel T, Manson McGuire A et al (2015) Evolution of extensively drug-resistant tuberculosis over four decades: whole genome sequencing and dating analysis of Mycobacterium tuberculosis isolates from KwaZulu-Natal. PLoS Med 12:1–22CrossRefGoogle Scholar
  11. Colangeli R, Arcus VL, Cursons RT et al (2014) Whole genome sequencing of Mycobacterium tuberculosis reveals slow growth and low mutation rates during latent infections in humans. PLoS One 9:e91024CrossRefPubMedPubMedCentralGoogle Scholar
  12. Cole ST, Brosch R, Parkhill J et al (1998) Deciphering the biology of Mycobacterium tuberculosis from the complete genome sequence. Nature 393:537–544CrossRefPubMedGoogle Scholar
  13. Colman RE, Schupp JM, Hicks ND et al (2015) Detection of low-level mixed-population drug resistance in Mycobacterium tuberculosis using high fidelity amplicon sequencing. PLoS One 10:e0126626CrossRefPubMedPubMedCentralGoogle Scholar
  14. Comas I, Gagneux S (2009) The past and future of tuberculosis research. PLoS Pathog 5:e1000600CrossRefPubMedPubMedCentralGoogle Scholar
  15. Comas I, Chakravartti J, Small PM et al (2010) Human T cell epitopes of Mycobacterium tuberculosis are evolutionarily hyperconserved. Nat Genet 42:498–503CrossRefPubMedPubMedCentralGoogle Scholar
  16. Comas I, Borrell S, Roetzer A et al (2012) Whole-genome sequencing of rifampicin-resistant Mycobacterium tuberculosis strains identifies compensatory mutations in RNA polymerase genes. Nat Genet 44:106–110CrossRefGoogle Scholar
  17. Copin R, Coscolla M, Seiffert SN et al (2014) Sequence diversity in the pe_pgrs genes of Mycobacterium tuberculosis is independent of human T cell recognition. MBio 5:e00960–e00913CrossRefPubMedPubMedCentralGoogle Scholar
  18. Coscolla M, Barry PM, Oeltmann JE et al (2015) Genomic epidemiology of multidrug-resistant Mycobacterium tuberculosis during transcontinental spread. J Infect Dis 15:383–388Google Scholar
  19. Didelot X, Gardy J, Colijn C (2013) Bayesian inference of infectious disease transmission from whole genome sequence data. Mol Biol Evol 31:1869–1879CrossRefGoogle Scholar
  20. Didelot X, Walker AS, Peto TE et al (2016) Within-host evolution of bacterial pathogens. Nat Rev Microbiol 14:150–162CrossRefPubMedPubMedCentralGoogle Scholar
  21. Doughty EL, Sergeant MJ, Adetifa I et al (2014) Culture-independent detection and characterisation of Mycobacterium tuberculosis and M. africanum in sputum samples using shotgun metagenomics on a benchtop sequencer. PeerJ 2:e585CrossRefPubMedPubMedCentralGoogle Scholar
  22. du Plessis L, Stadler T (2015) Getting to the root of epidemic spread with phylodynamic analysis of genomic data. Trends Microbiol 23:383–386CrossRefPubMedGoogle Scholar
  23. Dye C, Glaziou P, Floyd K, Raviglione M (2013) Prospects for tuberculosis elimination. Annu Rev Public Health 34:271–286CrossRefPubMedGoogle Scholar
  24. Eldholm V, Norheim G, von der Lippe B et al (2014) Evolution of extensively drug-resistant Mycobacterium tuberculosis from a susceptible ancestor in a single patient. Genome Biol 15:490CrossRefPubMedPubMedCentralGoogle Scholar
  25. Eldholm V, Monteserin J, Rieux A et al (2015) Four decades of transmission of a multidrug-resistant Mycobacterium tuberculosis outbreak strain. Nat Commun 6:7119CrossRefPubMedPubMedCentralGoogle Scholar
  26. Ford CB, Lin PL, Chase MR et al (2011) Use of whole genome sequencing to estimate the mutation rate of Mycobacterium tuberculosis during latent infection. Nat Genet 43:482–486CrossRefPubMedPubMedCentralGoogle Scholar
  27. Ford CB, Shah RR, Maeda MK et al (2013) Mycobacterium tuberculosis mutation rate estimates from different lineages predict substantial differences in the emergence of drug-resistant tuberculosis. Nat Genet 45:784–790CrossRefPubMedPubMedCentralGoogle Scholar
  28. Gardy JL, Johnston JC, Sui SJH et al (2011) Whole-genome sequencing and social-network analysis of a tuberculosis outbreak. N Engl J Med 364:730–739CrossRefPubMedGoogle Scholar
  29. Gillespie SH, Crook AM, McHugh TD et al (2014) Four-month moxifloxacin-based regimens for drug-sensitive tuberculosis. N Engl J Med 371:1577–1587CrossRefPubMedPubMedCentralGoogle Scholar
  30. Gordienko EN, Kazanov MD, Gelfand MS (2013) Evolution of pan-genomes of Escherichia coli, Shigella spp., and Salmonella enterica. J Bacteriol 195:2786–2792CrossRefPubMedPubMedCentralGoogle Scholar
  31. Grenfell BT, Pybus OG, Gog JR et al (2004) Unifying the epidemiological and evolutionary dynamics of pathogens. Science 303(80):327–332CrossRefPubMedGoogle Scholar
  32. Guerra-Assunção JA, Crampin AC, Houben RMGJ et al (2015a) Large-scale whole genome sequencing of M. tuberculosis provides insights into transmission in a high prevalence area. elife 4:1–17CrossRefGoogle Scholar
  33. Guerra-Assunção JA, Houben RMGJ, Crampin AC et al (2015b) Recurrence due to relapse or reinfection with Mycobacterium tuberculosis: a whole-genome sequencing approach in a large, population-based cohort with a high HIV infection prevalence and active follow-up. J Infect Dis 211:1154–1163CrossRefPubMedGoogle Scholar
  34. Hatherell H-A, Colijn C, Stagg HR et al (2016) Interpreting whole genome sequencing for investigating tuberculosis transmission: a systematic review. BMC Med 14:21CrossRefPubMedPubMedCentralGoogle Scholar
  35. Johnston JC, Khan FA, Dowdy DW (2015) Reducing relapse in tuberculosis treatment: is it time to reassess WHO treatment guidelines? Int J Tuberc Lung Dis 19:624CrossRefPubMedGoogle Scholar
  36. Jombart T, Cori A, Didelot X et al (2014) Bayesian eeconstruction of disease outbreaks by combining epidemiologic and genomic data. PLoS Comput Biol 10:e1003457CrossRefPubMedPubMedCentralGoogle Scholar
  37. Kay GL, Sergeant MJ, Zhou Z et al (2015) Eighteenth-century genomes show that mixed infections were common at time of peak tuberculosis in Europe. Nat Commun 6:6717CrossRefPubMedPubMedCentralGoogle Scholar
  38. Kühnert D, Stadler T, Vaughan TG, Drummond AJ (2014) Simultaneous reconstruction of evolutionary history and epidemiological dynamics from viral sequences with the birth-death SIR model. J R Soc Interface 11:20131106CrossRefPubMedPubMedCentralGoogle Scholar
  39. Liu Q, Via LE, Luo T et al (2015) Within patient microevolution of Mycobacterium tuberculosis correlates with heterogeneous responses to treatment. Sci Rep 5:17507CrossRefPubMedPubMedCentralGoogle Scholar
  40. Loman NJ, Pallen MJ (2015) Twenty years of bacterial genome sequencing. Nat Rev Microbiol:1–9Google Scholar
  41. Niemann S, Köser CU, Gagneux S et al (2009) Genomic diversity among drug sensitive and multidrug resistant isolates of Mycobacterium tuberculosis with identical DNA fingerprints. PLoS One 4:e7407CrossRefPubMedPubMedCentralGoogle Scholar
  42. O’Rawe J, Jiang T, Sun G et al (2013) Low concordance of multiple variant-calling pipelines: practical implications for exome and genome sequencing. Genome Med 5:28CrossRefPubMedPubMedCentralGoogle Scholar
  43. Pai M, Schito M (2015) Tuberculosis diagnostics in 2015: landscape, priorities, needs, and prospects. J Infect Dis 211(Suppl):S21–S28CrossRefPubMedPubMedCentralGoogle Scholar
  44. Pérez-Lago L, Comas I, Navarro Y et al (2013) Whole genome sequencing analysis of intrapatient microevolution in Mycobacterium tuberculosis: potential impact on the inference of tuberculosis transmission. J Infect Dis:1–11Google Scholar
  45. Perez-Lago L, Martinez Lirola M, Herranz M et al (2015) Fast and low-cost decentralized surveillance of transmission of tuberculosis based on strain-specific PCRs tailored from whole genome sequencing data: a pilot study. Clin Microbiol Infect 21:249.e1–249.e9CrossRefGoogle Scholar
  46. Pérez-Lago L, Navarro Y, Montilla P et al (2015) Persistent infection by a Mycobacterium tuberculosis strain that was theorized to have advantageous properties, as it was responsible for a massive outbreak. J Clin Microbiol 53:3423–3429CrossRefPubMedPubMedCentralGoogle Scholar
  47. Phelan JE, Coll F, Bergval I et al (2016) Recombination in pe/ppe genes contributes to genetic variation in Mycobacterium tuberculosis lineages. BMC Genomics 17:151CrossRefPubMedPubMedCentralGoogle Scholar
  48. Quail M, Smith ME, Coupland P et al (2012) A tale of three next generation sequencing platforms: comparison of Ion torrent, pacific biosciences and illumina MiSeq sequencers. BMC Genomics 13:1CrossRefPubMedPubMedCentralGoogle Scholar
  49. Quick J, Loman NJ, Duraffour S et al (2016) Real-time, portable genome sequencing for Ebola surveillance. Nature 530:228–232CrossRefPubMedPubMedCentralGoogle Scholar
  50. Rasmussen DA, Ratmann O, Koelle K (2011) Inference for nonlinear epidemiological models using genealogies and time series. PLoS Comput Biol 7:e1002136CrossRefPubMedPubMedCentralGoogle Scholar
  51. Rocha EPC, Smith JM, Hurst LD et al (2006) Comparisons of dN/dS are time dependent for closely related bacterial genomes. J Theor Biol 239:226–235CrossRefPubMedGoogle Scholar
  52. Roetzer A, Diel R, Kohl TA et al (2013) Whole genome sequencing versus traditional genotyping for investigation of a Mycobacterium tuberculosis outbreak: a longitudinal molecular epidemiological study. PLoS Med 10:e1001387CrossRefPubMedPubMedCentralGoogle Scholar
  53. Schurch AC, Kremer K, Daviena O et al (2010) High resolution typing by integration of genome sequencing data in a large tuberculosis cluster. J Clin Microbiol 48:3403–3406CrossRefPubMedPubMedCentralGoogle Scholar
  54. Stadler T, Kühnert D, Bonhoeffer S, Drummond AJ (2012) Birth – death skyline plot reveals temporal changes of epidemic spread in HIV and hepatitis C virus (HCV). Proc Natl Acad Sci U S A 110:228–233CrossRefPubMedPubMedCentralGoogle Scholar
  55. Sterling TR, Lehmann HP, Frieden TR (2003) Impact of DOTS compared with DOTS-plus on multidrug resistant tuberculosis and tuberculosis deaths: decision analysis. BMJ 326:574CrossRefPubMedPubMedCentralGoogle Scholar
  56. Stucki D, Ballif M, Bodmer T et al (2015a) Tracking a tuberculosis outbreak over 21 years: strain-specific single-nucleotide polymorphism typing combined with targeted whole-genome sequencing. J Infect Dis 211:1306–1316CrossRefPubMedGoogle Scholar
  57. Stucki D, Ballif M, Egger M et al (2015b) Standard genotyping overestimates transmission of Mycobacterium tuberculosis among immigrants in a low-incidence country. J Clin Microbiol 7:1862–1870Google Scholar
  58. Sun G, Luo T, Yang C et al (2012) Dynamic population changes in Mycobacterium tuberculosis during acquisition and fixation of drug resistance in patients. J Infect Dis 206:1724–1733CrossRefPubMedPubMedCentralGoogle Scholar
  59. Tameris MD, Hatherill M, Landry BS et al (2013) Safety and efficacy of MVA85A, a new tuberculosis vaccine, in infants previously vaccinated with BCG: a randomised, placebo-controlled phase 2b trial. Lancet 6736:1–8Google Scholar
  60. Van Rie A, Victor TC, Richardson M et al (2005) Reinfection and mixed infection cause changing Mycobacterium tuberculosis drug-resistance patterns. Am J Respir Crit Care Med 172:636–642CrossRefPubMedPubMedCentralGoogle Scholar
  61. Van Soolingen D (2014) Whole-genome sequencing of Mycobacterium tuberculosis as an epidemiological marker. Lancet Respir Med 4:251–252CrossRefGoogle Scholar
  62. Votintseva AA, Bradley P, Pankhurst L, Del Ojo Elias C, Loose M, Nilgiriwala K, Chatterjee A, Smith EG, Sanderson N, Walker TM, Morgan MR, Wyllie DH, Walker AS, Peto TEA, Crook DW, Iqbal Z (2017) Same-day diagnostic and surveillance data for tuberculosis via whole-genome sequencing of direct respiratory samples. J Clin Microbiol 55(5):1285–1298Google Scholar
  63. Walker TM, Ip CL, Harrell RH et al (2013a) Whole-genome sequencing to delineate Mycobacterium tuberculosis outbreaks: a retrospective observational study. Lancet Infect Dis 13:137–146CrossRefPubMedPubMedCentralGoogle Scholar
  64. Walker TM, Monk P, Smith EG, Peto TE a (2013b) Contact investigations for outbreaks of Mycobacterium tuberculosis: advances through whole genome sequencing. Clin Microbiol Infect 19:796–802CrossRefPubMedGoogle Scholar
  65. World Health Organization (2015). Global tuberculosis reportGoogle Scholar
  66. Yates TA, Khan PY, Knight GM et al (2016) The transmission of Mycobacterium tuberculosis in high burden settings. Lancet Infect Dis 16:227–238CrossRefPubMedGoogle Scholar
  67. Yozwiak NL, Schaffner SF, Sabeti PC (2015) Data sharing: make outbreak research open access. Nature 518:477–479CrossRefPubMedGoogle Scholar
  68. Zumla A, Memish ZA, Maeurer M et al (2014) Emerging novel and antimicrobial-resistant respiratory tract infections: new drug development and therapeutic options. Lancet Infect Dis 14:1136–1149CrossRefPubMedGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Institute of Biomedicine of Valencia (IBV-CSIC) and CIBER in Epidemiology and Public HealthValenciaSpain

Personalised recommendations