CoChat
Sign Up
Cited by 12CRISPR and Genetic EngineeringBacteriophages and microbial interactionsBacterial Genetics and Biotechnology

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Cas1 mediates the interference stage in a phage-encoded CRISPR–Cas system

Open access
Zhang, Laixing, Wang, Hao, Zeng, Jianwei, Cao, Xueli, Gao, Zhengyu, Liu, Zihe, Li, Feixue, Wang, Jiawei, Zhang, Yi, Yang, Maojun, Feng, Yue·2024·Nature Chemical Biology
DOI 10.1038/s41589-024-01659-5

Published version of a preprint

Open this paper in CoChat — free accountOpen PDF

Abstract

Clustered regularly interspaced short palindromic repeats (CRISPR)-Cas systems are prokaryotic adaptive immune systems against invading phages and other mobile genetic elements. Notably, some phages, including the Vibrio cholerae-infecting ICP1 (International Center for Diarrheal Disease Research, Bangladesh cholera phage 1), harbor CRISPR-Cas systems to counteract host defenses. Nevertheless, ICP1 Cas8f lacks the helical bundle domain essential for recruitment of helicase-nuclease Cas2/3 during target DNA cleavage and how this system accomplishes the interference stage remains unknown. Here, we found that Cas1, a highly conserved component known to exclusively work in the adaptation stage, also mediates the interference stage through connecting Cas2/3 to the DNA-bound CRISPR-associated complex for antiviral defense (Cascade; CRISPR system yersinia, Csy) of the ICP1 CRISPR-Cas system. A series of structures of Csy, Csy-dsDNA (double-stranded DNA), Cas1-Cas2/3 and Csy-dsDNA-Cas1-Cas2/3 complexes reveal the whole process of Cas1-mediated target DNA cleavage by the ICP1 CRISPR-Cas system. Together, these data support an unprecedented model in which Cas1 mediates the interference stage in a phage-encoded CRISPR-Cas system and the study also sheds light on a unique model of primed adaptation.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41589-024-01659-5

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Show all 3 references

Research works printed but not linked: 59

  1. Barrangou, R. et al. CRISPR provides acquired resistance against viruses in prokaryotes. Science 315, 1709–1712 (2007). · DOI · Paper page
  2. Bolotin, A., Quinquis, B., Sorokin, A. & Ehrlich, S. D. Clustered regularly interspaced short palindrome repeats (CRISPRs) have spacers of extrachromosomal origin. Microbiology 151, 2551–2561 (2005). · DOI · Paper page
  3. Marraffini, L. A. & Sontheimer, E. J. CRISPR interference limits horizontal gene transfer in staphylococci by targeting DNA. Science 322, 1843–1845 (2008). · DOI · Paper page
  4. Makarova, K. S. et al. Evolutionary classification of CRISPR–Cas systems: a burst of class 2 and derived variants. Nat. Rev. Microbiol. 18, 67–83 (2020). · DOI · Paper page
  5. Hille, F. et al. The biology of CRISPR–Cas: backward and forward. Cell 172, 1239–1259 (2018). · DOI
  6. Hu, C. Y. et al. Mechanism for Cas4-assisted directional spacer acquisition in CRISPR–Cas. Nature 598, 515–520 (2021). · DOI
  7. Wang, J. Y. et al. Genome expansion by a CRISPR trimmer-integrase. Nature 618, 855–861 (2023). · DOI · Paper page
  8. Ofir, G. & Sorek, R. Contemporary phage biology: from classic models to new insights. Cell 172, 1260–1270 (2018). · DOI
  9. Samson, J. E., Magadan, A. H., Sabri, M. & Moineau, S. Revenge of the phages: defeating bacterial defences. Nat. Rev. Microbiol. 11, 675–687 (2013). · DOI
  10. Hampton, H. G., Watson, B. N. J. & Fineran, P. C. The arms race between bacteria and their phage foes. Nature 577, 327–336 (2020). · DOI
  11. Seed, K. D., Lazinski, D. W., Calderwood, S. B. & Camilli, A. A bacteriophage encodes its own CRISPR/Cas adaptive response to evade host innate immunity. Nature 494, 489–491 (2013). · DOI
  12. Pausch, P. et al. CRISPR–CasΦ from huge phages is a hypercompact genome editor. Science 369, 333–337 (2020). · DOI
  13. Al-Shayeb, B. et al. Diverse virus-encoded CRISPR–Cas systems include streamlined genome editors. Cell 185, 4574–4586 (2022). · DOI
  14. Bellas, C. M., Anesio, A. M. & Barker, G. Analysis of virus genomes from glacial environments reveals novel virus groups with unusual host interactions. Front. Microbiol. 6, 656 (2015). · DOI
  15. Chenard, C., Wirth, J. F. & Suttle, C. A. Viruses infecting a freshwater filamentous cyanobacterium (Nostoc sp.) encode a functional CRISPR array and a proteobacterial DNA polymerase B. MBio 7, e00667-16 (2016). · DOI
  16. Al-Shayeb, B. et al. Clades of huge phages from across Earth’s ecosystems. Nature 578, 425–431 (2020). · DOI
  17. Naser, I. B. et al. Analysis of the CRISPR–Cas system in bacteriophages active on epidemic strains of Vibrio cholerae in Bangladesh. Sci. Rep. 7, 14880 (2017). · DOI
  18. Villion, M. & Moineau, S. Virology: phages hijack a host’s defence. Nature 494, 433–434 (2013). · DOI
  19. Penades, J. R. & Christie, G. E. The phage-inducible chromosomal islands: a family of highly evolved molecular parasites. Annu. Rev. Virol. 2, 181–201 (2015). · DOI
  20. Fillol-Salom, A. et al. Phage-inducible chromosomal islands are ubiquitous within the bacterial universe. ISME J. 12, 2114–2128 (2018). · DOI
  21. McKitterick, A. C., LeGault, K. N., Angermeyer, A., Alam, M. & Seed, K. D. Competition between mobile genetic elements drives optimization of a phage-encoded CRISPR-Cas system: insights from a natural arms race. Philos. Trans. R. Soc. Lond. B Biol. Sci. 374, 20180089 (2019). · DOI
  22. Mojica, F. J., Diez-Villasenor, C., Garcia-Martinez, J. & Almendros, C. Short motif sequences determine the targets of the prokaryotic CRISPR defence system. Microbiology 155, 733–740 (2009). · DOI · Paper page
  23. Rollins, M. F. et al. Structure reveals a mechanism of CRISPR-RNA-guided nuclease recruitment and anti-CRISPR viral mimicry. Mol. Cell 74, 132–142 (2019). · DOI
  24. Guo, T. W. et al. Cryo-EM structures reveal mechanism and inhibition of DNA targeting by a CRISPR–Cas surveillance complex. Cell 171, 414–426 (2017). · DOI
  25. Chowdhury, S. et al. Structure reveals mechanisms of viral suppressors that intercept a CRISPR RNA-guided surveillance complex. Cell 169, 47–57 (2017). · DOI
  26. Gao, Z. et al. Anti-CRISPR protein AcrIF4 inhibits the type I-F CRISPR–Cas surveillance complex by blocking nuclease recruitment and DNA cleavage. J. Biol. Chem. 298, 102575 (2022). · DOI
  27. Xie, Y. et al. AcrIF5 specifically targets DNA-bound CRISPR–Cas surveillance complex for inhibition. Nat. Chem. Biol. 18, 670–677 (2022). · DOI
  28. Xiao, Y., Luo, M., Dolan, A. E., Liao, M. & Ke, A. Structure basis for RNA-guided DNA degradation by Cascade and Cas3. Science 361, eaat0839 (2018). · DOI
  29. O’Brien, R. E. et al. Structural snapshots of R-loop formation by a type I-C CRISPR Cascade. Mol. Cell 83, 746–758 (2023). · DOI
  30. Schwartz, E. A. et al. Structural rearrangements allow nucleic acid discrimination by type I-D Cascade. Nat. Commun. 13, 2829 (2022). · DOI
  31. Wu, C. et al. Mechanisms of spacer acquisition by sequential assembly of the adaptation module in Synechocystis. Nucleic Acids Res. 49, 2973–2984 (2021). · DOI
  32. Wright, A. V. et al. Structures of the CRISPR genome integration complex. Science 357, 1113–1118 (2017). · DOI
  33. Rollins, M. F. et al. Cas1 and the Csy complex are opposing regulators of Cas2/3 nuclease activity. Proc. Natl Acad. Sci. USA 114, E5113–E5121 (2017). · DOI
  34. Zhang, M. et al. Mechanistic insights into DNA binding and cleavage by a compact type I-F CRISPR–Cas system in bacteriophage. Proc. Natl Acad. Sci. USA 120, e2215098120 (2023). · DOI
  35. Fagerlund, R. D. et al. Spacer capture and integration by a type I-F Cas1–Cas2-3 CRISPR adaptation complex. Proc. Natl Acad. Sci. USA 114, E5122–E5128 (2017). · DOI
  36. Xiao, Y. B., Ng, S., Nam, K. H. & Ke, A. L. How type II CRISPR–Cas establish immunity through Cas1–Cas2-mediated spacer integration. Nature 550, 137–141 (2017). · DOI
  37. Wang, J. et al. Structural and mechanistic basis of PAM-dependent spacer acquisition in CRISPR–Cas systems. Cell 163, 840–853 (2015). · DOI · Paper page
  38. Huo, Y. W. et al. Structures of CRISPR Cas3 offer mechanistic insights into Cascade-activated DNA unwinding and degradation. Nat. Struct. Mol. Biol. 21, 771–777 (2014). · DOI
  39. Santiago-Frangos, A. et al. Structure reveals why genome folding is necessary for site-specific integration of foreign DNA into CRISPR arrays. Nat. Struct. Mol. Biol. 30, 1675–1685 (2023). · DOI
  40. Sternberg, S. H., Richter, H., Charpentier, E. & Qimron, U. Adaptation in CRISPR–Cas systems. Mol. Cell 61, 797–808 (2016). · DOI
  41. Künne, T. et al. Cas3-derived target DNA degradation fragments fuel primed CRISPR adaptation. Mol. Cell 63, 852–864 (2016). · DOI
  42. McGinn, J. & Marraffini, L. A. Molecular mechanisms of CRISPR–Cas spacer acquisition. Nat. Rev. Microbiol. 17, 7–12 (2019). · DOI
  43. Staals, R. H. J. et al. Interference-driven spacer acquisition is dominant over naive and primed adaptation in a native CRISPR–Cas system. Nat. Commun. 7, 12853 (2016). · DOI
  44. Otwinowski, Z. & Minor, W.Processing of X-ray diffraction data collected in oscillation mode. Methods Enzymol. 276, 307–326 (1997). · DOI · Paper page
  45. Adams, P. D. et al. PHENIX: building new software for automated crystallographic structure determination. Acta Crystallogr. D Biol. Crystallogr. 58, 1948–1954 (2002). · DOI · Paper page
  46. Emsley, P. & Cowtan, K. Coot: model-building tools for molecular graphics. Acta Crystallogr. D Biol. Crystallogr. 60, 2126–2132 (2004). · DOI · Paper page
  47. Mastronarde, D. N. Automated electron microscope tomography using robust prediction of specimen movements. J. Struct. Biol. 152, 36–51 (2005). · DOI
  48. Li, J., & Frank, J.Automated acquisition of cryo-electron micrographs for single particle reconstruction on an FEI Tecnai electron microscope. J. Struct. Biol. 150, 69–80 (2005). · DOI
  49. Zheng, S. Q. et al. MotionCor2: anisotropic correction of beam-induced motion for improved cryo-electron microscopy. Nat. Methods 14, 331–332 (2017). · DOI
  50. Zhang, K. Gctf: real-time CTF determination and correction. J. Struct. Biol. 193, 1–12 (2016). · DOI
  51. Punjani, A., Rubinstein, J. L., Fleet, D. J. & Brubaker, M. A. cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination. Nat. Methods 14, 290–296 (2017). · DOI · Paper page
  52. Zivanov, J. et al. New tools for automated high-resolution cryo-EM structure determination in RELION-3. eLife 7, e42166 (2018). · DOI
  53. Sanchez-Garcia, R. et al. DeepEMhancer: a deep learning solution for cryo-EM volume post-processing. Commun. Biol. 4, 874 (2021). · DOI
  54. Pettersen, E. F. et al. UCSF Chimera—a visualization system for exploratory research and analysis. J. Comput. Chem. 25, 1605–1612 (2004). · DOI
  55. Swint-Kruse, L. & Brown, C. S. Resmap: automated representation of macromolecular interfaces as two-dimensional networks. Bioinformatics 21, 3327–3328 (2005). · DOI
  56. Afonine, P. V. et al. Real-space refinement in PHENIX for cryo-EM and crystallography. Acta Crystallogr. D Struct. Biol. 74, 531–544 (2018). · DOI
  57. Williams, C. J. et al. MolProbity: more and better reference data for improved all-atom structure validation. Protein Sci. 27, 293–315 (2018). · DOI · Paper page
  58. Pettersen, E. F. et al. UCSF ChimeraX: structure visualization for researchers, educators, and developers. Protein Sci. 30, 70–82 (2021). · DOI
  59. Zhang, Q. & Ye, Y. Not all predicted CRISPR–Cas systems are equal: isolated cas genes and classes of CRISPR like elements. BMC Bioinf. 18, 1–12 (2017). · DOI

Metadata

Authors
Zhang, L., Wang, H., Zeng, J., Cao, X., Gao, Z., Liu, Z., Li, F., Wang, J., Zhang, Y., Yang, M., & Feng, Y.
Affiliations
  • Center for Life Sciences (CN)
  • State Key Laboratory of Chemical Resource Engineering (CN)
  • Southern University of Science and Technology (CN)
Corresponding author
  • Zhang, Yi
  • Yang, Maojun
  • Feng, Yue
ORCID
Venue
Nature Chemical Biology
Publisher
Springer Science and Business Media LLC
Published
2024-07-08
Volume
20
Issue
11
Pages
1471-1481
ISSN
  • 1552-4450 (ISSN-L)
  • 1552-4469
DOI
10.1038/s41589-024-01659-5
OpenAlex
W4400422905
Cited by
12
References
3
Citations by year
2026: 5 · 2025: 7
FWCI
1.64
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Chemical Biology (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
Funders
  • Tsinghua University
  • Southern University of Science and Technology
  • National Key Research and Development Program of China
  • Institute of Microbiology, Chinese Academy of Sciences
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › CRISPR and Genetic Engineering
  • Life Sciences › Immunology and Microbiology › Virology › Bacteriophages and microbial interactions
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Bacterial Genetics and Biotechnology
Keywords
CRISPR-Cas, Cas1, Vibrio cholerae, cascades, phage defense, adaptive immunity
MeSH terms
Bacteriophages, DNA, Vibrio cholerae, CRISPR-Cas Systems, CRISPR-Associated Proteins

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review