Adaptive modulation of antibiotic resistance through intragenomic coevolution

Abstract

Bacteria gain antibiotic resistance genes by horizontal acquisition of mobile genetic elements (MGEs) from other lineages. Newly acquired MGEs are often poorly adapted causing intragenomic conflicts; these are resolved by either compensatory adaptation—of the chromosome or the MGE—or reciprocal coadaptation. The footprints of such intragenomic coevolution are present in bacterial genomes, suggesting an important role promoting genomic integration of horizontally acquired genes, but direct experimental evidence of the process is limited. Here we show adaptive modulation of tetracycline resistance via intragenomic coevolution between Escherichia coli and the multidrug resistant plasmid RK2. Tetracycline treatments, including monotherapy or combination therapies with ampicillin, favoured de novo chromosomal resistance mutations coupled with mutations on RK2 impairing the plasmid-encoded tetracycline efflux pump. These mutations together provided increased tetracycline resistance at reduced cost. Additionally, the chromosomal resistance mutations conferred cross-resistance to chloramphenicol. Reciprocal coadaptation was not observed under ampicillin-only or no antibiotic selection. Intragenomic coevolution can create genomes comprising multiple replicons that together provide high-level, low-cost resistance, but the resulting co-dependence may limit the spread of coadapted MGEs to other lineages.

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Fig. 1: Resistance profiles of evolved plasmids and hosts.
Fig. 2: Mutations show treatment-specific parallelism.

References

  1. 1.

    Jain, R., Rivera, M. C., Moore, J. E. & Lake, J. A. Horizontal gene transfer accelerates genome innovation and evolution. Mol. Biol. Evol. 20, 1598–1602 (2003).

    Article  CAS  PubMed  Google Scholar 

  2. 2.

    Frost, L. S., Leplae, R., Summers, A. O. & Toussaint, A. Mobile genetic elements: the agents of open source evolution. Nat. Rev. Microbiol. 3, 722–732 (2005).

    Article  CAS  PubMed  Google Scholar 

  3. 3.

    Norman, A., Hansen, L. H. & Sørensen, S. J. Conjugative plasmids: vessels of the communal gene pool. Phil. Trans. R. Soc. B 364, 2275–2289 (2009).

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  4. 4.

    Svara, F. & Rankin, D. J. The evolution of plasmid-carried antibiotic resistance. BMC Evol. Biol. 11, 130 (2011).

    Article  PubMed Central  PubMed  Google Scholar 

  5. 5.

    Carattoli, A. Plasmids and the spread of resistance. Int. J. Med. Microbiol. 303, 298–304 (2013).

    Article  CAS  PubMed  Google Scholar 

  6. 6.

    Baltrus, D. A. Exploring the costs of horizontal gene transfer. Trends Ecol. Evol. 28, 489–495 (2013).

    Article  PubMed  Google Scholar 

  7. 7.

    Diaz Ricci, J. C. & Hernández, M. E. Plasmid effects on Escherichia coli metabolism. Crit. Rev. Biotechnol. 20, 79–108 (2000).

    Article  CAS  PubMed  Google Scholar 

  8. 8.

    Harrison, E., Guymer, D., Spiers, A. J., Paterson, S. & Brockhurst, M. A. Parallel compensatory evolution stabilizes plasmids across the parasitism–mutualism continuum. Curr. Biol. 25, 2034–2039 (2015).

    Article  CAS  PubMed  Google Scholar 

  9. 9.

    San Millan, A., Toll-Riera, M., Qi, Q. & MacLean, R. C. Interactions between horizontally acquired genes create a fitness cost in Pseudomonas aeruginosa. Nat. Commun. 6, 6845 (2015).

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  10. 10.

    Harrison, E. & Brockhurst, M. A. Plasmid-mediated horizontal gene transfer is a coevolutionary process. Trends Microbiol. 20, 262–267 (2012).

    Article  CAS  PubMed  Google Scholar 

  11. 11.

    Porse, A., Schønning, K., Munck, C. & Sommer, M. O. A. Survival and evolution of a large multidrug resistance plasmid in new clinical bacterial hosts. Mol. Biol. Evol. 33, 2860–2873 (2016).

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  12. 12.

    Loftie-Eaton, W. et al. Evolutionary paths that expand plasmid host-range: implications for spread of antibiotic resistance. Mol. Biol. Evol. 33, 885–897 (2016).

    Article  CAS  PubMed  Google Scholar 

  13. 13.

    McNally, A. et al. Combined analysis of variation in core, accessory and regulatory genome regions provides a super-resolution view into the evolution of bacterial populations. PLoS Genet. 12, e1006280 (2016).

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  14. 14.

    Pansegrau, W. et al. Complete nucleotide sequence of Birmingham IncPα plasmids: compilation and comparative analysis. J. Mol. Biol. 239, 623–663 (1994).

    Article  CAS  PubMed  Google Scholar 

  15. 15.

    Bottery, M. J., Wood, A. J. & Brockhurst, M. A. Selective conditions for a multidrug resistance plasmid depend on the sociality of antibiotic resistance. Antimicrob. Agents Chemother. 60, 2524–2527 (2016).

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  16. 16.

    Cowan, S. W. et al. Crystal structures explain functional properties of two E. coli porins. Nature 358, 727–733 (1992).

    Article  CAS  PubMed  Google Scholar 

  17. 17.

    Blair, J. M. A., Webber, M. A., Baylay, A. J., Ogbolu, D. O. & Piddock, L. J. V. Molecular mechanisms of antibiotic resistance. Nat. Rev. Microbiol. 13, 42–51 (2015).

    Article  CAS  PubMed  Google Scholar 

  18. 18.

    Cohen, S. P., McMurry, L. M., Hooper, D. C., Wolfson, J. S. & Levy, S. B. Cross-resistance to fluoroquinolones in multiple-antibiotic-resistant (Mar) Escherichia coli selected by tetracycline or chloramphenicol: decreased drug accumulation associated with membrane changes in addition to OmpF reduction. Antimicrob. Agents Chemother. 33, 1318–1325 (1989).

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  19. 19.

    Thanassi, D. G., Suh, G. S. & Nikaido, H. Role of outer membrane barrier in efflux-mediated tetracycline resistance of Escherichia coli. J. Bacteriol. 177, 998–1007 (1995).

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  20. 20.

    Baba, T. et al. Construction of Escherichia coli K-12 in-frame, single-gene knockout mutants: the Keio collection. Mol. Syst. Biol. 2, 2006.0008 (2006).

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  21. 21.

    Lee, J., Hiibel, S. R., Reardon, K. F. & Wood, T. K. Identification of stress-related proteins in Escherichia coli using the pollutant cis-dichloroethylene. J. Appl. Microbiol. 108, 2088–2102 (2010).

    Article  CAS  PubMed  Google Scholar 

  22. 22.

    Mendoza-Vargas, A. et al. Genome-wide identification of transcription start sites, promoters and transcription factor binding sites in E. coli. PLoS ONE 4, e7526 (2009).

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  23. 23.

    Membrillo-Hernández, J. et al. Evolution of the adhE gene product of Escherichia coli from a functional reductase to a dehydrogenase genetic and biochemical studies of the mutant proteins. J. Biol. Chem. 275, 33869–33875 (2000).

    Article  PubMed  Google Scholar 

  24. 24.

    Kessler, D., Leibrecht, I. & Knappe, J. Pyruvate-formate-lyase-deactivase and acetyl-CoA reductase activities of Escherichia coli reside on a polymeric protein particle encoded by adhE. FEBS Lett. 281, 59–63 (1991).

    Article  CAS  PubMed  Google Scholar 

  25. 25.

    Shasmal, M., Dey, S., Shaikh, T. R., Bhakta, S. & Sengupta, J. E. coli metabolic protein aldehyde-alcohol dehydrogenase-E binds to the ribosome: a unique moonlighting action revealed. Sci. Rep. 6, 19936 (2016).

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  26. 26.

    Ma, D., Alberti, M., Lynch, C., Nikaido, H. & Hearst, J. E. The local repressor AcrR plays a modulating role in the regulation of acrAB genes of Escherichia coli by global stress signals. Mol. Microbiol. 19, 101–112 (1996).

    Article  CAS  PubMed  Google Scholar 

  27. 27.

    Okusu, H., Ma, D. & Nikaido, H. AcrAB efflux pump plays a major role in the antibiotic resistance phenotype of Escherichia coli multiple-antibiotic-resistance (Mar) mutants. J. Bacteriol. 178, 306–308 (1996).

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  28. 28.

    Wang, H., Dzink-Fox, J. L., Chen, M. & Levy, S. B. Genetic characterization of highly fluoroquinolone-resistant clinical Escherichia coli strains from China: role of acrR mutations. Antimicrob. Agents Chemother. 45, 1515–1521 (2001).

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  29. 29.

    Cooper, T. F., Rozen, D. E. & Lenski, R. E. Parallel changes in gene expression after 20,000 generations of evolution in Escherichia coli. Proc. Natl Acad. Sci. USA 100, 1072–1077 (2003).

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  30. 30.

    Hale, L., Lazos, O., Haines, A. & Thomas, C. An efficient stress-free strategy to displace stable bacterial plasmids. BioTechniques 48, 223–228 (2010).

    Article  CAS  PubMed  Google Scholar 

  31. 31.

    Møller, T. S. B. et al. Relation between tetR and tetA expression in tetracycline resistant Escherichia coli. BMC Microbiol. 16, 39 (2016).

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  32. 32.

    Ramos, J. L. et al. The TetR family of transcriptional repressors. Microbiol. Mol. Biol. Rev. 69, 326–356 (2005).

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  33. 33.

    Allard, J. D. & Bertrand, K. P. Membrane topology of the pBR322 tetracycline resistance protein: TetA-PhoA gene fusions and implications for the mechanism of TetA membrane insertion. J. Biol. Chem. 267, 17809–17819 (1992).

    CAS  PubMed  Google Scholar 

  34. 34.

    Orth, P., Schnappinger, D., Hillen, W., Saenger, W. & Hinrichs, W. Structural basis of gene regulation by the tetracycline inducible Tet repressor–operator system. Nat. Struct. Mol. Biol. 7, 215–219 (2000).

    Article  CAS  Google Scholar 

  35. 35.

    Nguyen, T. N., Phan, Q. G., Duong, L. P., Bertrand, K. P. & Lenski, R. E. Effects of carriage and expression of the Tn10 tetracycline-resistance operon on the fitness of Escherichia coli K12. Mol. Biol. Evol. 6, 213–225 (1989).

    CAS  PubMed  Google Scholar 

  36. 36.

    Stoesser, N. et al. Evolutionary history of the global emergence of the Escherichia coli epidemic clone ST131. mBio 7, e02162-15 (2016).

    Article  PubMed Central  PubMed  Google Scholar 

  37. 37.

    Johnson, T. J. et al. Separate F-type plasmids have shaped the evolution of the H30 subclone of Escherichia coli sequence type 131. mSphere 1, e00121-16 (2016).

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  38. 38.

    Crozat, E., Philippe, N., Lenski, R. E., Geiselmann, J. & Schneider, D. Long-term experimental evolution in Escherichia coli. XII. DNA topology as a key target of selection. Genetics 169, 523–532 (2005).

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  39. 39.

    Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  40. 40.

    McKenna, A. et al. The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  41. 41.

    Cingolani, P. et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff. Fly (Austin) 6, 80–92 (2012).

    Article  CAS  Google Scholar 

  42. 42.

    Robinson, J. T. et al. Integrative genomics viewer. Nat. Biotechnol. 29, 24–26 (2011).

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  43. 43.

    Chen, K. et al. BreakDancer: an algorithm for high-resolution mapping of genomic structural variation. Nat. Methods 6, 677–681 (2009).

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  44. 44.

    Anderson, M. J. Distance-based tests for homogeneity of multivariate dispersions. Biometrics 62, 245–253 (2006).

    Article  PubMed  Google Scholar 

  45. 45.

    Anderson, M. J. A new method for non-parametric multivariate analysis of variance. Austral Ecol. 26, 32–46 (2001).

    Google Scholar 

  46. 46.

    Zapala, M. A. & Schork, N. J. Multivariate regression analysis of distance matrices for testing associations between gene expression patterns and related variables. Proc. Natl Acad. Sci. USA 103, 19430–19435 (2006).

    Article  PubMed Central  CAS  PubMed  Google Scholar 

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Acknowledgements

We thank J. P. W. Young, V. Friman, and members of the Friman and Brockhurst laboratories for discussion and comments on the manuscript. We thank C. M. Thomas for providing pCURE plasmids. This research was supported by the Wellcome Trust four-year PhD programme (WT095024MA) ‘Combating infectious disease: computational approaches in translation science’. This work was also supported by funding from the European Research Council under the European Union’s Seventh Framework Programme awarded to M.A.B. (FP7/2007-2013 ERC grant StG-2012-311490–COEVOCON).

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M.A.B. and A.J.W. supervised the project. M.J.B. performed the experiments and analysed the data. All authors contributed towards the design of the study and wrote the manuscript.

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Correspondence to Michael A. Brockhurst.

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Supplementary Figures 1–8

Supplementary Table 1

Genomic variations observed in response to experimental evolution

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Bottery, M.J., Wood, A.J. & Brockhurst, M.A. Adaptive modulation of antibiotic resistance through intragenomic coevolution. Nat Ecol Evol 1, 1364–1369 (2017). https://doi.org/10.1038/s41559-017-0242-3

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