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Parallel bacterial evolution within multiple patients identifies candidate pathogenicity genes

Nature Genetics volume 43, pages 1275–1280 (2011)Cite this article

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Abstract

Bacterial pathogens evolve during the infection of their human host1,2,3,4,5,6,7,8, but separating adaptive and neutral mutations remains challenging9,10,11. Here we identify bacterial genes under adaptive evolution by tracking recurrent patterns of mutations in the same pathogenic strain during the infection of multiple individuals. We conducted a retrospective study of a Burkholderia dolosa outbreak among subjects with cystic fibrosis, sequencing the genomes of 112 isolates collected from 14 individuals over 16 years. We find that 17 bacterial genes acquired nonsynonymous mutations in multiple individuals, which indicates parallel adaptive evolution. Mutations in these genes affect important pathogenic phenotypes, including antibiotic resistance and bacterial membrane composition and implicate oxygen-dependent regulation as paramount in lung infections. Several genes have not previously been implicated in pathogenesis and may represent new therapeutic targets. The identification of parallel molecular evolution as a pathogen spreads among multiple individuals points to the key selection forces it experiences within human hosts.

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Figure 1: Whole-genome sequencing of 112 epidemic B. dolosa isolates recovered from 14 subjects shows the steady accumulation of mutations over years.
Figure 2: Bacterial phylogeny reveals a likely network of transmission between individuals and between organs.
Figure 3: Pathogenic phenotypes are associated with point mutations in key genes.
Figure 4: Parallel evolution identifies a set of genes under strong selection during pathogenesis.

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Acknowledgements

We are grateful to M. Caimano, M. Cendron, P. Kokorowski, S. Lory, C. Marx, N. Delany, S. Walker, M. Waldor and R. Ward for insightful discussions and comments, to O. Iartchouk, A. Brown, M. Light and their team at Partners HealthCare Center for Personalized Genetic Medicine (PCPGM) for Illumina sequencing, to J. Deane and L. Williams for technical assistance, to S. Vargas for assistance with IRB protocols and to M. Baym, M. Ernebjerg, A. Palmer, E. Toprak, K. Vetsigian, Z. Yao and all of the Kishony lab members for helpful discussions and general support. J.B.M. was supported by the Foundational Questions in Evolutionary Biology Prize Fellowship and the Systems Biology PhD Program (Harvard Medical School). G.P.P. was supported in part by The Mannion Fund for Research of the Center for the Critically Ill Child of Children's Hospital Boston. J.J.L. was supported by the Cystic Fibrosis Foundation. This work was supported in part by US National Institutes of Health grants (GM080177 to the Systems Biology Department, Harvard Medical School and GM081617 to R.K.), by a grant from the New England Regional Center of Excellence for Biodefense and Emerging Infectious Diseases (NERCE; AI057159 to R.K.) and by a Harvard Catalyst grant (to R.K., A.J.M. and M. Cendron).

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Author notes

  1. Tami D Lieberman and Jean-Baptiste Michel: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA

    Tami D Lieberman, Jean-Baptiste Michel, Nicholas Leiby & Roy Kishony

  2. Program for Evolutionary Dynamics, Harvard University, Cambridge, Massachusetts, USA

    Jean-Baptiste Michel

  3. Department of Medicine, Division of Infectious Diseases, Children's Hospital Boston, Boston, Massachusetts, USA

    Mythili Aingaran & Gregory P Priebe

  4. Infection Prevention & Control, Children's Hospital Boston, Boston, Massachusetts, USA

    Gail Potter-Bynoe

  5. Department of Medicine, Channing Laboratory, Brigham and Women's Hospital, Boston, Massachusetts, USA

    Damien Roux, David Skurnik & Gregory P Priebe

  6. Department of Microbiology, University of Virginia Health System, Charlottesville, Virginia, USA

    Michael R Davis Jr & Joanna B Goldberg

  7. Department of Pediatrics, University of Michigan Medical School, Ann Arbor, Michigan, USA

    John J LiPuma

  8. Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA

    John J LiPuma

  9. Department of Laboratory Medicine, Children's Hospital Boston, Boston, Massachusetts, USA

    Alexander J McAdam

  10. Department of Anesthesia, Division of Critical Care Medicine, Children's Hospital Boston, Boston, Massachusetts, USA

    Gregory P Priebe

  11. School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA

    Roy Kishony

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Contributions

J.-B.M., A.J.M. and R.K. conceived of the study. J.J.L., A.J.M. and G.P.P. collected the clinical samples. T.D.L. and N.L. performed resistance phenotyping. J.B.G., D.R., M.R.D., D.S. and G.P.P. performed LPS phenotyping and complementation. M.A., G.P.-B., A.J.M. and G.P.P. conducted chart review and provided medical information. T.D.L., J.-B.M. and R.K. performed whole-genome sequencing and data analysis. T.D.L., J.-B.M., J.J.L., A.J.M., G.P.P. and R.K. interpreted the results and wrote the manuscript.

Corresponding authors

Correspondence to Alexander J McAdam, Gregory P Priebe or Roy Kishony.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–8, Supplementary Tables 1, 4 and 5 and Supplementary Note. (PDF 1715 kb)

Supplementary Table 2

Polymorphic loci among 113 B. dolosa isolates (XLSX 217 kb)

Supplementary Table 3

Genes mutated during an epidemic of B. dolosa (XLSX 26 kb)

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Lieberman, T., Michel, JB., Aingaran, M. et al. Parallel bacterial evolution within multiple patients identifies candidate pathogenicity genes. Nat Genet 43, 1275–1280 (2011). https://doi.org/10.1038/ng.997

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