The diversity-generating benefits of a prokaryotic adaptive immune system (original) (raw)

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Sequence data are available from the European Nucleotide Archive under accession number PRJEB12001 and analysis scripts are available from https://github.com/scottishwormboy/vanHoute.

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Acknowledgements

We thank D. Morley and S. Kay for experimental contributions and A. Gardner for comments on the manuscript. S.v.H. has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement number 660039. E.R.W. received funding from the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007-2013) under Research Executive Agency grant agreement number 327606. E.R.W., A.B. and M.B. also acknowledge the Natural Environment Research Council, the Biotechnology and Biological Sciences Research Council, the Royal Society, the Leverhulme Trust, the Wellcome Trust and the AXA research fund for funding. J.M.B.-D. was supported by the University of California San Francisco Program for Breakthrough in Biomedical Research, the Sandler Foundation, and a National Institutes of Health Director’s Early Independence Award (DP5-OD021344). H.C. was funded by the Erasmus+ programme (European Union), the Explora’Sup programme (Région Rhône-Alpes) and the Centre Régional des Œuvres Universitaires et Scolaires (CROUS; French State).

Author information

Authors and Affiliations

  1. ESI and CEC, Biosciences, University of Exeter, Cornwall Campus, Penryn, TR10 9EZ, UK
    Stineke van Houte, Alice K. E. Ekroth, Jenny M. Broniewski, Hélène Chabas, Angus Buckling & Edze R. Westra
  2. CEFE UMR 5175, CNRS-Université de Montpellier, Université Paul-Valéry Montpellier, EPHE, 1919, route de Mende, Montpellier, 34293, Cedex 5, France
    Hélène Chabas & Sylvain Gandon
  3. Department of Integrative Biology, University of California, Berkeley, 94720, California, USA
    Ben Ashby & Mike Boots
  4. CEC, Biosciences, University of Exeter, Cornwall Campus, Penryn, TR10 9EZ, UK
    Ben Ashby & Mike Boots
  5. Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, California 94158, USA,
    Joseph Bondy-Denomy
  6. Institute of Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK
    Steve Paterson

Authors

  1. Stineke van Houte
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  2. Alice K. E. Ekroth
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  3. Jenny M. Broniewski
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  4. Hélène Chabas
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  5. Ben Ashby
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  6. Joseph Bondy-Denomy
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  7. Sylvain Gandon
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  8. Mike Boots
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  9. Steve Paterson
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  10. Angus Buckling
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  11. Edze R. Westra
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Contributions

E.R.W., A.B. and S.v.H. conceived and designed the experiments. H.C. performed coevolution experiments. S.v.H., E.R.W., A.K.E.E. and J.M.B. performed all competition experiments and associated analysis of virus persistence and host and virus evolution. S.P. performed and analysed deep sequencing of virus genomes. J.B.-D. supplied virus with anti-CRISPR gene. B.A. and M.B. contributed to discussions and provided feedback throughout the project. S.G. and H.C. helped to set up the experiments with S. thermophilus. S.v.H., E.R.W. and A.B. wrote the manuscript.

Corresponding authors

Correspondence toStineke van Houte, Angus Buckling or Edze R. Westra.

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Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 CRISPR diversity drives virus extinct since virus cannot escape by point mutation.

a, Percentage bacteria (WT or CRISPR KO) from the experiment shown in Fig. 1 that have evolved CRISPR immunity (white bar), surface immunity (black bar) or remained sensitive (sensitive; grey bars) at 5 d.p.i. with virus DMS3vir (n = 6 for both treatments). b, Relative fitness of CRISPR immune monocultures (single spacer; low diversity, n = 48) and polycultures (48 spacers; high diversity, n = 6) at 3 d.p.i. when competing with a surface mutant (sm) in the absence of virus. c, d, Deep sequencing analysis of the frequency of mutations in the seed region and PAM of the target sequence of virus isolated at t = 1 d.p.i. from the experiment shown in Fig. 4. c, Frequency of point mutation in the target sequence of viral populations isolated from monoculture 1–3 × surface mutant competitions. d, Average frequency of point mutation across all target sites in the ancestral virus genome and in the genomes of virus from pooled samples of all biological replicates from a single diversity treatment (monocultures: n = 48; 6-clone: n = 8; 12-clone: n = 8; 24-clone: n = 6; 48-clone: n = 6). e, f, Virus that escapes a single spacer present in a diverse CRISPR population decreases in frequency, despite a fitness benefit over ancestral virus. e, Titres (in plaque-forming units per millilitre) over time upon infection of monocultures (dotted line) or polycultures of 48 clones (solid line) with approximately 108 p.f.u. ancestral (closed circles) or escape (open circles) virus. Escape virus was isolated from monocultures 1–6 × surface mutant competitions shown in Figs 2, 3, 4, at 24 h.p.i. n = 6 for all experiments. The limit of detection is 200 p.f.u. ml−1. f, Relative fitness of escape virus at t = 1 d.p.i. when competing with ancestral virus on CRISPR-resistant monocultures or polycultures consisting of 48 clones. n = 6 for both experiments. g, For each diversity treatment shown in Figs 2, 3, 4 we examined the spacer content of 192 randomly isolated clones at both t = 0 and t = 3 d.p.i. (384 clones in total per diversity treatment). The change in the total number of spacers between t = 0 and t = 3 d.p.i was calculated independently for each replicate experiment (number of biological replicates as indicated in legend of Fig. 2) and divided by the number of clones that were examined. The graph indicates the average across the replicates of the change in spacer content per clone. h, i, Titres (in plaque-forming units per millilitre) over time of virus carrying an anti-CRISPR gene (DMS3vir+acrF1) following infection of a bacterial population consisting of an equal mixture of a surface mutant and a monoculture with CRISPR-mediated immunity (h; n = 48) or a 48-clone polyculture with CRISPR-mediated immunity (i; n = 6). Each clone is equally represented in each treatment. Each line indicates a biological replicate experiment. The limit of detection is 200 p.f.u. ml−1. j, The number of replicate experiments in which the CRISPR immune population went extinct (no detectable white colonies) at 1 and 3 d.p.i. In all cases, n is the number of biological replicates and error bars represent 95% CI.

Extended Data Figure 2 Virus persistence inversely correlates with the level of CRISPR spacer diversity in CRISPR immune populations of S. thermophilus.

a, b, Virus titres (in plaque-forming units per millilitre) over time upon infection of a bacterial population consisting of a monoculture with CRISPR-mediated immunity (a; n = 44 biological replicates) or 44-clone polycultures with CRISPR-mediated immunity (b; n = 28 biological replicates). Each clone is equally represented in each treatment. Each line indicates a biological replicate experiment. The limit of detection is 200 p.f.u. ml−1. c, Absorbance at 600 nm of monocultures and polycultures at 16 and 40 h.p.i. Error bars, 95% CI. d, Emergence of virus mutants that overcome CRISPR-mediated immunity after 0, 16, 24, 40 and 48 h.p.i. Green indicates no escape virus. Red indicates emergence of escape virus. Escape virus emerged in none of the 28 biological replicates of the polyculture experiments.

Extended Data Figure 3 Sensitive bacteria are unable to invade bacterial populations with CRISPR-mediated immunity in the presence of virus.

a–e, Virus titres (in plaque-forming units per millilitre) over time upon infection of a bacterial population consisting of an equal mixture of a sensitive CRISPR KO clone and a monoculture with CRISPR-mediated immunity (a; n = 48), or polycultures with CRISPR-mediated immunity consisting of 6 clones (b; n = 8), 12 clones (c; n = 8), 24 clones (d; n = 6) and 48 clones (e; n = 6). The number of replicates is chosen such that all clones are equally represented in each treatment. Each line indicates a biological replicate experiment. The limit of detection is 200 p.f.u. ml−1. f, Relative fitness of CRISPR populations at 3 d.p.i. during the competitions with the sensitive CRISPR KO described in a–e. Relative fitness of CRISPR populations decreases with increasing spacer diversity due to the rapid virus extinction, which benefits sensitive bacteria, but is higher than 1 in all cases. Error bars, 95% CI. g, Relative fitness of monoculture (single spacer; low diversity, n = 48) and polyculture (48 spacers; high diversity, n = 6) at 3 d.p.i. when competing with the CRISPR KO strain in the absence of virus. Error bars, 95% CI. In all cases n is the number of biological replicates.

Extended Data Figure 4 Evolution of virus infectivity is constrained by CRISPR diversity when CRISPR immune populations compete with sensitive CRISPR KO bacteria.

Emergence of virus mutants that overcome CRISPR-mediated immunity during the experiment shown in Extended Data Fig. 3. Each column in a table represents a time point (0, 16, 24, 40, 48, 64 and 72 h.p.i., as indicated below the table (in days post-infection)) where virus was isolated. Green indicates no escape virus. Red indicates emergence of escape virus. Panels a–e correspond to each of the experiments shown in Extended Data Fig. 3a–e. Bold numbers indicate each of the individual biological replicates, as detailed in the legend of Extended Data Fig. 3. In b–e, individual replicates are separated by bold lines. Numbers between parentheses indicate the identity of clones that are present in a population with CRISPR-mediated immunity. Asterisks indicate replicate experiments where virus went extinct during the experiment.

Extended Data Table 1 Tukey’s honest significant difference test of all pairwise comparisons of the data in Fig. 3

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van Houte, S., Ekroth, A., Broniewski, J. et al. The diversity-generating benefits of a prokaryotic adaptive immune system.Nature 532, 385–388 (2016). https://doi.org/10.1038/nature17436

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