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Use of whole genome sequencing to estimate the mutation rate of Mycobacterium tuberculosis during latent infection

Nature Genetics volume 43, pages 482–486 (2011)Cite this article

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Abstract

Tuberculosis poses a global health emergency, which has been compounded by the emergence of drug-resistant Mycobacterium tuberculosis (Mtb) strains. We used whole-genome sequencing to compare the accumulation of mutations in Mtb isolated from cynomolgus macaques with active, latent or reactivated disease. We sequenced 33 Mtb isolates from nine macaques with an average genome coverage of 93% and an average read depth of 117×. Based on the distribution of SNPs observed, we calculated the mutation rates for these disease states. We found a similar mutation rate during latency as during active disease or in a logarithmically growing culture over the same period of time. The pattern of polymorphisms suggests that the mutational burden in vivo is because of oxidative DNA damage. We show that Mtb continues to acquire mutations during disease latency, which may explain why isoniazid monotherapy for latent tuberculosis is a risk factor for the emergence of isoniazid resistance1,2.

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Figure 1: Experimental protocol for assessing mutational capacity in different disease states.
Figure 2: WGS identifies SNPs in strains isolated from animals with active, latent, and reactivated latent infection.
Figure 3: The mutational capacity of strains from latency and reactivated disease is similar to that of strains from active disease or in vitro growth.
Figure 4: Mutations in Mtb isolated from macaques with latent infection and related human isolates are putative products of oxidative damage.

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Acknowledgements

This work was supported by a New Innovator's Award, DP2 0D001378 from the Director's Office of the National Institute of Health to S.M.F., by a subcontract from National Institute for Allergy and Infectious Diseases (NIAID) U19 AI076217 to S.M.F., by the US National Institutes of Health (NIH) RO1 HL075845 to J.L.F. and by the Bill and Melinda Gates Foundation (J.L.F.). The genome sequencing has been funded in part with federal funds from the National Institute of Allergy and Infectious Disease, US NIH, US Department of Health and Human Services, under contract no. HHSN266200400001C. The project described was supported in part by Award Number U54GM088558 to M.L. from the National Institute of General Medical Sciences. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of General Medical Sciences or the National Institutes of Health. We thank D. Gurgil and J. Xu of the Enterprise Research IS group at Partners Healthcare for their support and for provision of the HPC facilities and E. Klein for necropsy and pathology of the infected monkeys, as well as the veterinary technical staff for care of the animals. We also thank E. Rubin, C. Sassetti, B. Bloom, T. Rosebrock and B. Aldridge for helpful feedback.

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Author notes

  1. Christopher B Ford and Philana Ling Lin: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Immunology and Infectious Diseases, Harvard School of Public Health, Boston, Massachusetts, USA

    Christopher B Ford, Michael R Chase, Rupal R Shah, Marc Lipsitch & Sarah M Fortune

  2. Department of Pediatrics, Children's Hospital of Pittsburgh of the University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA

    Philana Ling Lin

  3. Partners Healthcare Center for Personalized Genetic Medicine, Harvard Medical School, Cambridge, Massachusetts, USA

    Oleg Iartchouk

  4. Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA

    James Galagan

  5. Department of Microbiology, Boston University, Boston, Massachusetts, USA

    James Galagan

  6. The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA

    James Galagan

  7. Department of Biochemistry and Biophysics, Texas A&M University, College Station, Texas, USA

    Nilofar Mohaideen & James C Sacchettini

  8. Department of Computer Science and Engineering, Texas A&M University, College Station, Texas, USA

    Thomas R Ioerger

  9. Department of Epidemiology, Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, Massachusetts, USA

    Marc Lipsitch

  10. Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA

    JoAnne L Flynn

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Contributions

C.B.F. performed molecular studies, conducted the data analyses, prepared the figures and drafted the manuscript; P.L.L. and J.L.F. conducted the infection of the cynomolgus macaques, determined clinical state and acquired bacterial strains on necropsy; M.R.C. analyzed sequence data and directed validation of SNPs; R.R.S. performed molecular and fluctuation analyses; O.I. oversaw sequencing of isolates sent to Partners Healthcare Center for Personalized Genetic Medicine (PHCPGM); J.G. oversaw sequencing of isolates sent to the Broad Institute; N.M., T.R.I. and J.C.S. oversaw sequencing and analysis of isolates sent to Texas A&M University; M.L. supervised and advised statistical analyses; S.M.F. initiated the project, performed molecular studies, supervised preparation and analysis of the data and drafted the manuscript.

Corresponding author

Correspondence to Sarah M Fortune.

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The authors declare no competing financial interests.

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Supplementary Figure 1 and Supplementary Tables 1 and 2. (PDF 190 kb)

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Ford, C., Lin, P., Chase, M. et al. Use of whole genome sequencing to estimate the mutation rate of Mycobacterium tuberculosis during latent infection. Nat Genet 43, 482–486 (2011). https://doi.org/10.1038/ng.811

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