Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Targeting of temperate phages drives loss of type I CRISPR–Cas systems

A Publisher Correction to this article was published on 03 March 2020

This article has been updated

Abstract

On infection of their host, temperate viruses that infect bacteria (bacteriophages; hereafter referred to as phages) enter either a lytic or a lysogenic cycle. The former results in lysis of bacterial cells and phage release (resulting in horizontal transmission), whereas lysogeny is characterized by the integration of the phage into the host genome, and dormancy (resulting in vertical transmission)1. Previous co-culture experiments using bacteria and mutants of temperate phages that are locked in the lytic cycle have shown that CRISPR–Cas systems can efficiently eliminate the invading phages2,3. Here we show that, when challenged with wild-type temperate phages (which can become lysogenic), type I CRISPR–Cas immune systems cannot eliminate the phages from the bacterial population. Furthermore, our data suggest that, in this context, CRISPR–Cas immune systems are maladaptive to the host, owing to the severe immunopathological effects that are brought about by imperfect matching of spacers to the integrated phage sequences (prophages). These fitness costs drive the loss of CRISPR–Cas from bacterial populations, unless the phage carries anti-CRISPR (acr) genes that suppress the immune system of the host. Using bioinformatics, we show that this imperfect targeting is likely to occur frequently in nature. These findings help to explain the patchy distribution of CRISPR–Cas immune systems within and between bacterial species, and highlight the strong selective benefits of phage-encoded acr genes for both the phage and the host under these circumstances.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Phage persistence and evolution of resistance in the host upon infection with virulent or temperate phages.
Fig. 2: The effect of CRISPR adaptation and interference on lysogeny and phage persistence.
Fig. 3: Fitness of lysogens with an active CRISPR–Cas system is reduced unless they encode acr genes.
Fig. 4: Lysogens evolve to mitigate fitness costs.

Similar content being viewed by others

Data availability

Source Data associated with Figs. 14 and Extended Data Figs. 13, 5, 79 are provided with the paper. Sequencing data have been deposited in the European Nucleotide Archive under the study accession number PRJEB34503. The datasets analysed for the bioinformatic study are available on GitHub at https://github.com/davidchyou/Rollie-Chevallereau.

Code availability

Mathematical algorithms generated during this study are available in the Supplementary Information. Scripts generated for the bioinformatics analyses are available on GitHub at https://github.com/davidchyou/Rollie-Chevallereau.

Change history

References

  1. Stewart, F. M. & Levin, B. R. The population biology of bacterial viruses: why be temperate. Theor. Popul. Biol. 26, 93–117 (1984).

    Article  MathSciNet  CAS  PubMed  Google Scholar 

  2. Westra, E. R. et al. Parasite exposure drives selective evolution of constitutive versus inducible defense. Curr. Biol. 25, 1043–1049 (2015).

    Article  CAS  PubMed  Google Scholar 

  3. van Houte, S. et al. The diversity-generating benefits of a prokaryotic adaptive immune system. Nature 532, 385–388 (2016).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  4. Barrangou, R. et al. CRISPR provides acquired resistance against viruses in prokaryotes. Science 315, 1709–1712 (2007).

    Article  ADS  CAS  PubMed  Google Scholar 

  5. Garneau, J. E. et al. The CRISPR/Cas bacterial immune system cleaves bacteriophage and plasmid DNA. Nature 468, 67–71 (2010).

    Article  ADS  CAS  PubMed  Google Scholar 

  6. Datsenko, K. A. et al. Molecular memory of prior infections activates the CRISPR/Cas adaptive bacterial immunity system. Nat. Commun. 3, 945 (2012).

    Article  ADS  PubMed  Google Scholar 

  7. Fineran, P. C. et al. Degenerate target sites mediate rapid primed CRISPR adaptation. Proc. Natl Acad. Sci. USA 111, E1629–E1638 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Howard-Varona, C., Hargreaves, K. R., Abedon, S. T. & Sullivan, M. B. Lysogeny in nature: mechanisms, impact and ecology of temperate phages. ISME J. 11, 1511–1520 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Heussler, G. E. et al. Clustered regularly interspaced short palindromic repeat-dependent, biofilm-specific death of Pseudomonas aeruginosa mediated by increased expression of phage-related genes. mBio 6, e00129-15 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Zegans, M. E. et al. Interaction between bacteriophage DMS3 and host CRISPR region inhibits group behaviors of Pseudomonas aeruginosa. J. Bacteriol. 191, 210–219 (2009).

    Article  CAS  PubMed  Google Scholar 

  11. Berngruber, T. W., Froissart, R., Choisy, M. & Gandon, S. Evolution of virulence in emerging epidemics. PLoS Pathog. 9, e1003209 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Trasanidou, D. et al. Keeping CRISPR in check: diverse mechanisms of phage-encoded anti-CRISPRS. FEMS Microbiol. Lett. 366, fnz098 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Bondy-Denomy, J. et al. Multiple mechanisms for CRISPR–Cas inhibition by anti-CRISPR proteins. Nature 526, 136–139 (2015).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  14. Little, J. W. & Michalowski, C. B. Stability and instability in the lysogenic state of phage lambda. J. Bacteriol. 192, 6064–6076 (2010).

  15. Goldberg, G. W., Jiang, W., Bikard, D. & Marraffini, L. A. Conditional tolerance of temperate phages via transcription-dependent CRISPR–Cas targeting. Nature 514, 633–637 (2014).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  16. Samai, P. et al. Co-transcriptional DNA and RNA cleavage during type III CRISPR–Cas immunity. Cell 161, 1164–1174 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Landsberger, M. et al. Anti-CRISPR phages cooperate to overcome CRISPR–Cas immunity. Cell 174, 908–916 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Borges, A. L. et al. Bacteriophage cooperation suppresses CRISPR–Cas3 and Cas9 immunity. Cell 174, 917–925 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Poulsen, B. E. et al. Defining the core essential genome of Pseudomonas aeruginosa. Proc. Natl Acad. Sci. USA 116, 10072–10080 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Mooij, M. J. et al. Characterization of the integrated filamentous phage Pf5 and its involvement in small-colony formation. Microbiology 153, 1790–1798 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Zhou, Y., Liang, Y., Lynch, K. H., Dennis, J. J. & Wishart, D. S. PHAST: a fast phage search tool. Nucleic Acids Res. 39, W347–W52 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Makarova, K. S. et al. An updated evolutionary classification of CRISPR–Cas systems. Nat. Rev. Microbiol. 13, 722–736 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Levy, A. et al. CRISPR adaptation biases explain preference for acquisition of foreign DNA. Nature 520, 505–510 (2015).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  24. Stern, A., Keren, L., Wurtzel, O., Amitai, G. & Sorek, R. Self-targeting by CRISPR: gene regulation or autoimmunity? Trends Genet. 26, 335–340 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Vercoe, R. B. et al. Cytotoxic chromosomal targeting by CRISPR/Cas systems can reshape bacterial genomes and expel or remodel pathogenicity islands. PLoS Genet. 9, e1003454 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Jiang, W. et al. Dealing with the evolutionary downside of CRISPR immunity: bacteria and beneficial plasmids. PLoS Genet. 9, e1003844 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Goldberg, G. W. et al. Incomplete prophage tolerance by type III-A CRISPR–Cas systems reduces the fitness of lysogenic hosts. Nat. Commun. 9, 61 (2018).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  28. Cady, K. C. & O’Toole, G. A. Non-identity-mediated CRISPR-bacteriophage interaction mediated via the Csy and Cas3 proteins. J. Bacteriol. 193, 3433–3445 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Liberati, N. T. et al. An ordered, nonredundant library of Pseudomonas aeruginosa strain PA14 transposon insertion mutants. Proc. Natl Acad. Sci. USA 103, 2833–2838 (2006).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  30. Cady, K. C., Bondy-Denomy, J., Heussler, G. E., Davidson, A. R. & O’Toole, G. A. The CRISPR/Cas adaptive immune system of Pseudomonas aeruginosa mediates resistance to naturally occurring and engineered phages. J. Bacteriol. 194, 5728–5738 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Ceyssens, P.-J. et al. Comparative analysis of the widespread and conserved PB1-like viruses infecting Pseudomonas aeruginosa. Environ. Microbiol. 11, 2874–2883 (2009).

    Article  CAS  PubMed  Google Scholar 

  32. Chevallereau, A. et al. Exploitation of the cooperative behaviors of anti-CRISPR phages. Cell Host Microbe 27, 1–10 (2019).

    Google Scholar 

  33. Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Arndt, D. et al. PHASTER: a better, faster version of the PHAST phage search tool. Nucleic Acids Res. 44, W16– W21 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank A. R. Davidson for providing the mutant strains of PA14 ∆cas3, ∆cas7, ∆cas1 and ∆CRISPR2, G. A. O’Toole for the strain CRISPR2 ∆sp1–2 and J. Bondy-Denomy for the Tn::pilA (∆pilA) PA14 surface mutant. Genome sequencing was provided by MicrobesNG (http://www.microbesng.uk), which is supported by the BBSRC (grant number BB/L024209/1). This work was funded by a grant from the European Research Council (https://erc.europa.eu) (ERC-STG-2016-714478 - EVOIMMECH) and NERC Independent Research Fellowship (NE/M018350/1) awarded to E.R.W. A.C. has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 834052. P.C.F. was supported by the Marsden Fund from the Royal Society of New Zealand.

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization of the study was done by C.R., A.C. and E.R.W. Experimental design was carried out by C.R., A.C., B.N.J.W and E.R.W. Bacterial evolution, competition and growth experiments were done by C.R. and A.C. with assistance from O.F. and I.M. Virulent versus temperate phage competitions and prophage induction-rate experiments were performed by C.R. All experiments with acr phages and CRISPR 2 spacer 1 were done by A.C. B.N.J.W. and A.C. carried out Pf5 experiments. The experiment with superinfecting virulent phage was done by E.R.W. C.R., A.C., B.N.J.W., T.-y.C., C.M.B., P.C.F. and E.R.W. analysed the data. S.G. generated theoretical mathematical models. T.-y.C. conducted bioinformatic analyses supervised by C.M.B. and P.C.F. A.C. performed whole-genome sequencing analyses. C.R. wrote the original draft of the manuscript; A.C. wrote the revised version of the manuscript with contributions from C.R., B.N.J.W., T.-y.C., S.G., C.M.B. and P.C.F. E.R.W. supervised the project and provided comments on all versions of the manuscript.

Corresponding authors

Correspondence to Clare Rollie, Anne Chevallereau or Edze R. Westra.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature thanks Eugene Koonin and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Infection with a 50:50 mix of temperate:virulent phages.

a, b, Bacterial (a) and phage (b) titres during a co-culture experiment of wild-type PA14 (red) or ∆cas7 mutant (blue), and a 50:50 mix of DMS3 and DMS3vir. c, d, Resistance phenotypes at day 3 (c) or day 7 (d) of the co-culture experiment, based on 24 random clones per replicate experiment. Data are the mean of six biological replicates per treatment. Error bars represent 95% confidence intervals.

Source data

Extended Data Fig. 2 The suppression of lysogeny and immunopathological effects are due to spacer 1 of CRISPR array 2.

a, b, Phage (a) and bacterial (b) titres during co-culture of phage DMS3 and P. aeruginosa PA14 ΔCRISPR2, expressing a non-targeting spacer from a plasmid (ΔCRISPR2-NT) or the original CRISPR2 spacer 1 (ΔCRISPR2-sp1). c, d,The proportion of lysogens (c) and the frequency of loss of CRISPR–Cas immune systems (d) at 1 and 3 days post-infection, based on PCR analyses of 24 random clones per replicate experiment. ad, Data are the mean of three biological replicates. Error bars represent 95% confidence intervals. eg, Growth of three independent lysogen clones isolated at three days post-infection, as determined by OD600 nm measurements. ΔCRISPR2-NT (e) and ΔCRISPR2-sp1 (f) lysogen clones carry the ancestral ΔCRISPR2 CRISPR–Cas immune system, whereas the ΔCRISPR2-sp1 (g) lysogen clones have evolved to lose CRISPR–Cas.

Source data

Extended Data Fig. 3 Prophage induction rates are increased in hosts with active CRISPR–Cas.

a, The percentage of lysogens formed upon infection of wild-type host with DMS3 phages engineered to produce AcrIF1 or AcrIF4 anti-CRISPR proteins. b, c, Optical density (b) and phage titres (c) during growth of lysogens of DMS3, DMS3 acrIFI or DMS3 acrIF4 phages in a wild-type PA14 or ∆cas7 genetic background. d, Relative fitness of the DMS3 phage during competition with the virulent mutant DMS3vir in the presence of varying fractions of sensitive (∆cas7) host and resistant hosts with CRISPR-based immunity (BIM) or surface-based immunity (sm2) against these phages. Data show mean fitness at 8 h after infection. All panels show the mean of six biological replicates and error bars represent 95% confidence intervals.

Source data

Extended Data Fig. 4 Lysogens lose their CRISPR–Cas immune systems.

a, PCR amplification of the c-repressor gene of the prophage (c-rep, 611 bp), the fimV gene (located about 1 Mb from the CRISPR loci and used as a positive control for the PCR, 116 bp) and CRISPR loci 1 (349 bp) and 2 (206 bp) on the host genome. PCRs were performed on 6 independent DMS3 lysogens in wild-type, Δcas1 and Δcas7 backgrounds isolated at 1 or 7 days post-infection, as well as on 6 independent lysogens of DMS3, DMS3 acrIF1 or DMS3 acrIF4 (wild-type background) isolated at 6 or 120 h after infection. Red frames indicate a failure to amplify a product. PCR amplifications were performed on clones isolated from three biological replicate experiments and produced similar results. For gel source data, see Supplementary Fig. 1. b, Schematic of the CRISPR–Cas locus of wild-type PA14, which spans a region of around 11 kb. Primers used to amplify regions of CRISPR arrays 1 or 2 are shown as red arrows. ce, Whole-genome sequencing of DMS3 lysogens that lost their CRISPR–Cas system (red frames in a) in wild-type PA14 (c), ∆cas1 (d) or ∆cas7 (e) backgrounds. Graphs show the read coverage of the region encompassing positions 2.70–2.97 Mb of the wild-type PA14 genome. The CRISPR–Cas locus is indicated by a green box on the x axis. A genome map depicting coding sequences (yellow arrows) is shown above the graphs. The region comprising 2.84–2.88 Mb includes sequences that are repeated elsewhere on the PA14 genome, explaining why reads that map to these positions are still detected in some of the deletion mutants. The high peak at the 3′ end of the CRISPR locus corresponds to the coverage of spacer 20 of CRISPR2 by reads that derive from DMS3 prophage (5′ and 3′ extremities of these reads map to the phage genome). Spacer 20 of CRISPR2 has 100% identity to DMS3 but is not immunogenic because there is no consensus protospacer-adjacent motif.

Extended Data Fig. 5 Expression of Pf5 priming spacer in P. aeruginosa PA14.

a, Growth of ∆cas7 (dashed line) or wild-type (solid line) clones carrying an expression plasmid encoding a non-targeting spacer (pNT) or a spacer targeting the PA14 natural prophage Pf5 with one mismatch (pPf5-MS), as determined by OD600 nm measurements. Graphs show mean curves from 6 biological replicates, and shaded areas correspond to 95% confidence intervals. b, Relative fitness of wild-type pNT or wild-type pPf5-MS during competition with ∆cas7 pNT. Data are the mean of six biological replicates per treatment. Error bars represent 95% confidence intervals.

Source data

Extended Data Fig. 6 Simulations of population and evolutionary dynamics of bacteria–phage interactions, when virulent and temperate phages compete on bacteria with a CRISPR–Cas system.

ac, eg, Graphs show densities of susceptible hosts, CRISPR-resistant bacteria and lysogens (a, e) or free viruses over time (b, f), as well as the proportion of temperate phages in a population composed of both temperate and virulent types (c, g). Temperate phages can transmit both horizontally and vertically, whereas virulent phages can transmit only horizontally and cannot superinfect lysogens. d, h, Frequency of evolutionary loss of CRISPR–Cas system in the lysogen population over time. The simulations shown in ad reflect a situation in which both virulent and temperate phages lack acr genes, whereas those in eh reflect a scenario in which the temperate type carries an acr gene.

Extended Data Fig. 7 Matches between spacers and temperate phages are widespread.

a, Total matches between non-redundant spacers (n = 1,239,973) from 171,361 RefSeq and GenBank complete genomes and a non-redundant set of temperate phages (n = 19,996)21. The counts of perfect (0) or mismatched (1–5) targets are shown. As a control, the temperate phages were shuffled ten times, while retaining the hexanucleotide content (control). b, Counts of spacers matching temperate phages from all genera with over 500 spacer–prophage matches. The total number (n) of spacer–prophage matches is shown for each genus in parentheses. Counts of matches are shown (0, green; 1–5 mismatches, red). The number of temperate phages analysed is plotted (prophages in purple) as are the matches to shuffled prophages. The control is shown in blue, but is not visible because it had only 0 to 10 counts. c, The percentage of prophages within each genus that were targeted by self-priming spacers (1–5 mismatches). d, Heat map of the distribution of mismatches (0–5). Genera are as in b and data are shown as log(count) for each genus, as the number of matches varied widely between genera.

Source data

Extended Data Fig. 8 Self-targeting genomes are enriched for acr gene(s).

a, b, The number of P. aeruginosa genomes with complete CRISPR–Cas systems that contain (+) or lack (−) genes encoding known Acr proteins. For these strains, the total number of strains with perfect (0) or mismatched (1–5) self-targeting (ST) spacers to anywhere in the genome (a) or to prophages (b) are shown. For complete P. aeruginosa genomes, all self-targeting events were analysed for matches to prophages using PHASTER34. The number of genomes with acr genes (acr +) and self-targeting (ST +) spacers is significantly greater than the number of genomes with acr genes and without self-targeting spacers (P = 8.14 × 10−5, two-sided Fisher’s exact test, n = 71).

Source data

Extended Data Fig. 9 Presence of a superinfecting virulent phage does not alter immunopathological effects.

ac, Bacterial (a) and phage titres upon individual (b) or mixed (c) infection of wild-type PA14 with phage DMS3 and virulent phage LMA2. d, e, Resistance phenotypes evolved by bacteria against DMS3 upon individual (d) or mixed (e) infection. f, Frequency of loss of CRISPR–Cas immune systems upon infection with phage DMS3 or with both the phages DMS3 and LMA2, based on 24 random clones per replicate experiment. g, Relative fitness of wild-type PA14 during competition with PA14 Δcas7 in the presence or absence of phages DMS3 and LMA2. ag, Data are the means of six biological replicates. Error bars indicate 95% confidence intervals. ho, Simulations of population and evolutionary dynamics during infection of bacteria carrying CRISPR–Cas systems with a mixed population of unrelated virulent and temperate phages. Graphs show densities of susceptible hosts, CRISPR-resistant bacteria and lysogens (h, i) and free viruses over time (j, k), as well as the frequencies of temperate phages in a population composed of both temperate and virulent types (l, m). Temperate phage can transmit both horizontally and vertically, whereas virulent phage can transmit only horizontally and can superinfect the lysogens (because temperate and virulent phages are unrelated). n, o, Frequencies of evolutionary loss of CRISPR–Cas system in the lysogen population over time. The simulations shown in h, j, l, n reflect a scenario in which bacteria can evolve CRISPR-based resistance against both phages, whereas those shown in i, k, m, o reflect a situation in which CRISPR-based resistance does not evolve against the virulent phage, and bacteria instead evolve costly surface-based resistance (as it is the case in our experiments). A detailed description of the simulations is provided in the Supplementary Information.

Source data

Extended Data Table 1 Genomic deletions and prophage insertion sites in DMS3 late lysogen clones

Supplementary information

Supplementary Information

These files contain Supplementary Methods: Description of epidemiological modelling of phage dynamics (mathematical algorithms) and of bioinformatic analysis of widespread priming off temperate phages. Supplementary Table 1: Parameters of the mathematical model with default values. Supplementary Figure 1: Source data images for PCR amplification.

Reporting Summary

Source data

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rollie, C., Chevallereau, A., Watson, B.N.J. et al. Targeting of temperate phages drives loss of type I CRISPR–Cas systems. Nature 578, 149–153 (2020). https://doi.org/10.1038/s41586-020-1936-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41586-020-1936-2

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing