Spacer prioritization in CRISPR-Cas9 immunity is enabled by the leader RNA.
Journal
Nature microbiology
ISSN: 2058-5276
Titre abrégé: Nat Microbiol
Pays: England
ID NLM: 101674869
Informations de publication
Date de publication:
04 2022
04 2022
Historique:
received:
07
11
2021
accepted:
01
02
2022
pubmed:
23
3
2022
medline:
6
4
2022
entrez:
22
3
2022
Statut:
ppublish
Résumé
CRISPR-Cas systems store fragments of foreign DNA, called spacers, as immunological recordings used to combat future infections. Of the many spacers stored in a CRISPR array, the most recent are known to be prioritized for immune defence. However, the underlying mechanism remains unclear. Here we show that the leader region upstream of CRISPR arrays in CRISPR-Cas9 systems enhances CRISPR RNA (crRNA) processing from the newest spacer, prioritizing defence against the matching invader. Using the CRISPR-Cas9 system from Streptococcus pyogenes as a model, we found that the transcribed leader interacts with the conserved repeats bordering the newest spacer. The resulting interaction promotes transactivating crRNA (tracrRNA) hybridization with the second of the two repeats, accelerating crRNA processing. Accordingly, disruption of this structure reduces the abundance of the associated crRNA and immune defence against targeted plasmids and bacteriophages. Beyond the S. pyogenes system, bioinformatics analyses revealed that leader-repeat structures appear across CRISPR-Cas9 systems. CRISPR-Cas systems thus possess an RNA-based mechanism to prioritize defence against the most recently encountered invaders.
Identifiants
pubmed: 35314780
doi: 10.1038/s41564-022-01074-3
pii: 10.1038/s41564-022-01074-3
pmc: PMC7612570
mid: EMS141007
doi:
Substances chimiques
CRISPR-Associated Proteins
0
RNA
63231-63-0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
530-541Subventions
Organisme : European Research Council
ID : 865973
Pays : International
Informations de copyright
© 2022. The Author(s), under exclusive licence to Springer Nature Limited.
Références
Barrangou, R. et al. CRISPR provides acquired resistance against viruses in prokaryotes. Science 315, 1709–1712 (2007).
pubmed: 17379808
doi: 10.1126/science.1138140
van der Oost, J., Westra, E. R., Jackson, R. N. & Wiedenheft, B. Unravelling the structural and mechanistic basis of CRISPR-Cas systems. Nat. Rev. Microbiol. 12, 479–492 (2014).
pubmed: 24909109
pmcid: 4225775
doi: 10.1038/nrmicro3279
Jackson, S. A. et al. CRISPR-Cas: adapting to change. Science 356, eaal5056 (2017).
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).
pubmed: 16079334
doi: 10.1099/mic.0.28048-0
Mojica, F. J. M., Díez-Villaseñor, C., García-Martínez, J. & Soria, E. Intervening sequences of regularly spaced prokaryotic repeats derive from foreign genetic elements. J. Mol. Evol. 60, 174–182 (2005).
pubmed: 15791728
doi: 10.1007/s00239-004-0046-3
Sorek, R., Kunin, V. & Hugenholtz, P. CRISPR—a widespread system that provides acquired resistance against phages in bacteria and archaea. Nat. Rev. Microbiol. 6, 181–186 (2008).
pubmed: 18157154
doi: 10.1038/nrmicro1793
Arslan, Z., Hermanns, V., Wurm, R., Wagner, R. & Pul, Ü. Detection and characterization of spacer integration intermediates in type I-E CRISPR–Cas system. Nucleic Acids Res. 42, 7884–7893 (2014).
pubmed: 24920831
pmcid: 4081107
doi: 10.1093/nar/gku510
Xiao, Y., Ng, S., Nam, K. H. & Ke, A. How type II CRISPR-Cas establish immunity through Cas1-Cas2-mediated spacer integration. Nature 550, 137–141 (2017).
pubmed: 28869593
pmcid: 5832332
doi: 10.1038/nature24020
McGinn, J. & Marraffini, L. A. Molecular mechanisms of CRISPR-Cas spacer acquisition. Nat. Rev. Microbiol. 17, 7–12 (2019).
pubmed: 30171202
doi: 10.1038/s41579-018-0071-7
Brouns, S. J. J. et al. Small CRISPR RNAs guide antiviral defense in prokaryotes. Science 321, 960–964 (2008).
pubmed: 18703739
pmcid: 5898235
doi: 10.1126/science.1159689
Charpentier, E., Richter, H., van der Oost, J. & White, M. F. Biogenesis pathways of RNA guides in archaeal and bacterial CRISPR-Cas adaptive immunity. FEMS Microbiol. Rev. 39, 428–441 (2015).
pubmed: 25994611
pmcid: 5965381
doi: 10.1093/femsre/fuv023
Garneau, J. E. et al. The CRISPR/Cas bacterial immune system cleaves bacteriophage and plasmid DNA. Nature 468, 67–71 (2010).
pubmed: 21048762
doi: 10.1038/nature09523
Meeske, A. J., Nakandakari-Higa, S. & Marraffini, L. A. Cas13-induced cellular dormancy prevents the rise of CRISPR-resistant bacteriophage. Nature 570, 241–245 (2019).
pubmed: 31142834
pmcid: 6570424
doi: 10.1038/s41586-019-1257-5
Rostøl, J. T. et al. The Card1 nuclease provides defence during type III CRISPR immunity. Nature 590, 624–629 (2021).
pubmed: 33461211
pmcid: 7906951
doi: 10.1038/s41586-021-03206-x
Elmore, J. R. et al. Programmable plasmid interference by the CRISPR-Cas system in Thermococcus kodakarensis. RNA Biol. 10, 828–840 (2013).
pubmed: 23535213
pmcid: 3737340
doi: 10.4161/rna.24084
Carte, J. et al. The three major types of CRISPR-Cas systems function independently in CRISPR RNA biogenesis in Streptococcus thermophilus. Mol. Microbiol. 93, 98–112 (2014).
pubmed: 24811454
pmcid: 4095994
doi: 10.1111/mmi.12644
Crawley, A. B., Henriksen, E. D., Stout, E., Brandt, K. & Barrangou, R. Characterizing the activity of abundant, diverse and active CRISPR-Cas systems in lactobacilli. Sci. Rep. 8, 11544 (2018).
pubmed: 30068963
pmcid: 6070500
doi: 10.1038/s41598-018-29746-3
Deltcheva, E. et al. CRISPR RNA maturation by trans-encoded small RNA and host factor RNase III. Nature 471, 602–607 (2011).
pubmed: 21455174
pmcid: 3070239
doi: 10.1038/nature09886
McGinn, J. & Marraffini, L. A. CRISPR-Cas systems optimize their immune response by specifying the site of spacer integration. Mol. Cell 64, 616–623 (2016).
pubmed: 27618488
pmcid: 5096952
doi: 10.1016/j.molcel.2016.08.038
Martynov, A., Severinov, K. & Ispolatov, I. Optimal number of spacers in CRISPR arrays. PLoS Comput. Biol. 13, e1005891 (2017).
pubmed: 29253874
pmcid: 5749868
doi: 10.1371/journal.pcbi.1005891
Rao, C., Chin, D. & Ensminger, A. W. Priming in a permissive type I-C CRISPR-Cas system reveals distinct dynamics of spacer acquisition and loss. RNA 23, 1525–1538 (2017).
Liao, C. & Beisel, C. L. The tracrRNA in CRISPR biology and technologies. Annu. Rev. Genet. 55, 161–181 (2021).
pubmed: 34416117
doi: 10.1146/annurev-genet-071719-022559
Karvelis, T. et al. crRNA and tracrRNA guide Cas9-mediated DNA interference in Streptococcus thermophilus. RNA Biol. 10, 841–851 (2013).
pubmed: 23535272
pmcid: 3737341
doi: 10.4161/rna.24203
Jinek, M. et al. A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science 337, 816–821 (2012).
pubmed: 22745249
pmcid: 6286148
doi: 10.1126/science.1225829
Pickar-Oliver, A. & Gersbach, C. A. The next generation of CRISPR–Cas technologies and applications. Nat. Rev. Mol. Cell Biol. 20, 490–507 (2019).
pubmed: 31147612
pmcid: 7079207
doi: 10.1038/s41580-019-0131-5
Bikard, D. et al. Programmable repression and activation of bacterial gene expression using an engineered CRISPR-Cas system. Nucleic Acids Res. 41, 7429–7437 (2013).
pubmed: 23761437
pmcid: 3753641
doi: 10.1093/nar/gkt520
Jiang, W., Bikard, D., Cox, D., Zhang, F. & Marraffini, L. A. RNA-guided editing of bacterial genomes using CRISPR-Cas systems. Nat. Biotechnol. 31, 233–239 (2013).
pubmed: 23360965
pmcid: 3748948
doi: 10.1038/nbt.2508
Citorik, R. J., Mimee, M. & Lu, T. K. Sequence-specific antimicrobials using efficiently delivered RNA-guided nucleases. Nat. Biotechnol. 32, 1141–1145 (2014).
pubmed: 25240928
pmcid: 4237163
doi: 10.1038/nbt.3011
Leenay, R. T. & Beisel, C. L. Deciphering, communicating, and engineering the CRISPR PAM. J. Mol. Biol. 429, 177–191 (2017).
pubmed: 27916599
doi: 10.1016/j.jmb.2016.11.024
Dugar, G. et al. CRISPR RNA-dependent binding and cleavage of endogenous RNAs by the Campylobacter jejuni Cas9. Mol. Cell 69, 893–905 (2018).
pubmed: 29499139
pmcid: 5859949
doi: 10.1016/j.molcel.2018.01.032
Xue, C. et al. CRISPR interference and priming varies with individual spacer sequences. Nucleic Acids Res. 43, 10831–10847 (2015).
pubmed: 26586800
pmcid: 4678831
doi: 10.1093/nar/gkv1259
Collias, D. et al. A positive, growth-based PAM screen identifies noncanonical motifs recognized by the Cas9. Sci. Adv. 6, eabb4054 (2020).
pubmed: 32832642
pmcid: 7439565
doi: 10.1126/sciadv.abb4054
Altuvia, Y. et al. In vivo cleavage rules and target repertoire of RNase III in Escherichia coli. Nucleic Acids Res. 46, 10530–10531 (2018).
pubmed: 30184218
pmcid: 6212792
doi: 10.1093/nar/gky816
Wei, Y., Chesne, M. T., Terns, R. M. & Terns, M. P. Sequences spanning the leader-repeat junction mediate CRISPR adaptation to phage in Streptococcus thermophilus. Nucleic Acids Res. 43, 1749–1758 (2015).
pubmed: 25589547
pmcid: 4330368
doi: 10.1093/nar/gku1407
Pougach, K. et al. Transcription, processing and function of CRISPR cassettes in Escherichia coli. Mol. Microbiol. 77, 1367–1379 (2010).
pubmed: 20624226
pmcid: 2939963
doi: 10.1111/j.1365-2958.2010.07265.x
Yosef, I., Goren, M. G. & Qimron, U. Proteins and DNA elements essential for the CRISPR adaptation process in Escherichia coli. Nucleic Acids Res. 40, 5569–5576 (2012).
pubmed: 22402487
pmcid: 3384332
doi: 10.1093/nar/gks216
Jiao, C. et al. Noncanonical crRNAs derived from host transcripts enable multiplexable RNA detection by Cas9. Science 372, 941–948 (2021).
Jabbari, H., Wark, I. & Montemagno, C. RNA secondary structure prediction with pseudoknots: contribution of algorithm versus energy model. PLoS ONE 13, e0194583 (2018).
pubmed: 29621250
pmcid: 5886407
doi: 10.1371/journal.pone.0194583
Wei, Y., Terns, R. M. & Terns, M. P. Cas9 function and host genome sampling in Type II-A CRISPR-Cas adaptation. Genes Dev. 29, 356–361 (2015).
pubmed: 25691466
pmcid: 4335292
doi: 10.1101/gad.257550.114
Laanto, E., Hoikkala, V., Ravantti, J. & Sundberg, L.-R. Long-term genomic coevolution of host-parasite interaction in the natural environment. Nat. Commun. 8, 111 (2017).
pubmed: 28740072
pmcid: 5524643
doi: 10.1038/s41467-017-00158-7
Zhang, Y. et al. Processing-independent CRISPR RNAs limit natural transformation in Neisseria meningitidis. Mol. Cell 50, 488–503 (2013).
pubmed: 23706818
pmcid: 3694421
doi: 10.1016/j.molcel.2013.05.001
Dugar, G. et al. High-resolution transcriptome maps reveal strain-specific regulatory features of multiple Campylobacter jejuni isolates. PLoS Genet. 9, e1003495 (2013).
pubmed: 23696746
pmcid: 3656092
doi: 10.1371/journal.pgen.1003495
Haurwitz, R. E., Jinek, M., Wiedenheft, B., Zhou, K. & Doudna, J. A. Sequence- and structure-specific RNA processing by a CRISPR endonuclease. Science 329, 1355–1358 (2010).
pubmed: 20829488
pmcid: 3133607
doi: 10.1126/science.1192272
Li, R. & Bowerman, B. Symmetry breaking in biology. Cold Spring Harb. Perspect. Biol. 2, a003475 (2010).
pubmed: 20300216
pmcid: 2829966
doi: 10.1101/cshperspect.a003475
McCarty, N. S., Graham, A. E., Studená, L. & Ledesma-Amaro, R. Multiplexed CRISPR technologies for gene editing and transcriptional regulation. Nat. Commun. 11, 1281 (2020).
pubmed: 32152313
pmcid: 7062760
doi: 10.1038/s41467-020-15053-x
Al-Hashimi, H. M. & Walter, N. G. RNA dynamics: it is about time. Curr. Opin. Struct. Biol. 18, 321–329 (2008).
pubmed: 18547802
pmcid: 2580758
doi: 10.1016/j.sbi.2008.04.004
Watters, K. E., Strobel, E. J., Yu, A. M., Lis, J. T. & Lucks, J. B. Cotranscriptional folding of a riboswitch at nucleotide resolution. Nat. Struct. Mol. Biol. 23, 1124–1131 (2016).
pubmed: 27798597
pmcid: 5497173
doi: 10.1038/nsmb.3316
Liao, C. et al. Modular one-pot assembly of CRISPR arrays enables library generation and reveals factors influencing crRNA biogenesis. Nat. Commun. 10, 2948 (2019).
pubmed: 31270316
pmcid: 6610086
doi: 10.1038/s41467-019-10747-3
Wimmer, F. & Beisel, C. L. CRISPR-Cas systems and the paradox of self-targeting spacers. Front. Microbiol. 10, 3078 (2019).
pubmed: 32038537
doi: 10.3389/fmicb.2019.03078
Leenay, R. T. et al. Genome editing with CRISPR-Cas9 in Lactobacillus plantarum revealed that editing outcomes can vary across strains and between methods. Biotechnol. J. 14, e1700583 (2019).
pubmed: 30156038
doi: 10.1002/biot.201700583
Gruber, A. R., Lorenz, R., Bernhart, S. H., Neubock, R. & Hofacker, I. L. The Vienna RNA Websuite. Nucleic Acids Res. 36, W70–W74 (2008).
pubmed: 18424795
pmcid: 2447809
doi: 10.1093/nar/gkn188
Lorenz, R. et al. ViennaRNA Package 2.0. Algorithms Mol. Biol. 6, 26 (2011).
Sharma, C. M. et al. The primary transcriptome of the major human pathogen Helicobacter pylori. Nature 464, 250–255 (2010).
pubmed: 20164839
doi: 10.1038/nature08756
Papenfort, K. et al. σ
pubmed: 17427289
pmcid: 1804206
doi: 10.1111/j.1365-2958.2006.05524.x
Pernitzsch, S. R., Tirier, S. M., Beier, D. & Sharma, C. M. A variable homopolymeric G-repeat defines small RNA-mediated posttranscriptional regulation of a chemotaxis receptor in Helicobacter pylori. Proc. Natl Acad. Sci. USA 111, E501–E510 (2014).
pubmed: 24474799
pmcid: 3910625
doi: 10.1073/pnas.1315152111
Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 17, 1 (2011).
doi: 10.14806/ej.17.1.200
Förstner, K. U., Vogel, J. & Sharma, C. M. READemption-a tool for the computational analysis of deep-sequencing-based transcriptome data. Bioinformatics 30, 3421–3423 (2014).
pubmed: 25123900
doi: 10.1093/bioinformatics/btu533
Hoffmann, S. et al. Fast mapping of short sequences with mismatches, insertions and deletions using index structures. PLoS Comput. Biol. 5, e1000502 (2009).
pubmed: 19750212
pmcid: 2730575
doi: 10.1371/journal.pcbi.1000502
Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
pubmed: 19505943
pmcid: 2723002
doi: 10.1093/bioinformatics/btp352
Lopez-Delisle, L. et al. pyGenomeTracks: reproducible plots for multivariate genomic data sets. Bioinformatics 37, 422–423 (2020).
pmcid: 8058774
doi: 10.1093/bioinformatics/btaa692
Kent, W. J., Zweig, A. S., Barber, G., Hinrichs, A. S. & Karolchik, D. BigWig and BigBed: enabling browsing of large distributed datasets. Bioinformatics 26, 2204–2207 (2010).
pubmed: 20639541
pmcid: 2922891
doi: 10.1093/bioinformatics/btq351
Padilha, V. A., Alkhnbashi, O. S., Shah, S. A., de Carvalho, A. C. P. L. F. & Backofen, R. CRISPRcasIdentifier: machine learning for accurate identification and classification of CRISPR-Cas systems. Gigascience 9, giaa062 (2020).
Padilha, V. A. et al. Casboundary: automated definition of integral Cas cassettes. Bioinformatics 37, 1352–1359 (2020).
pmcid: 8208735
doi: 10.1093/bioinformatics/btaa984
Mitrofanov, A. et al. CRISPRidentify: identification of CRISPR arrays using machine learning approach. Nucleic Acids Res. 49, e20 (2021).
pubmed: 33290505
doi: 10.1093/nar/gkaa1158
Alkhnbashi, O. S. et al. CRISPRstrand: predicting repeat orientations to determine the crRNA-encoding strand at CRISPR loci. Bioinformatics 30, i489–i496 (2014).
pubmed: 25161238
pmcid: 4147912
doi: 10.1093/bioinformatics/btu459
Fu, L., Niu, B., Zhu, Z., Wu, S. & Li, W. CD-HIT: accelerated for clustering the next-generation sequencing data. Bioinformatics 28, 3150–3152 (2012).
pubmed: 23060610
pmcid: 3516142
doi: 10.1093/bioinformatics/bts565
Ding, Y. & Lawrence, C. E. A statistical sampling algorithm for RNA secondary structure prediction. Nucleic Acids Res. 31, 7280–7301 (2003).
pubmed: 14654704
pmcid: 297010
doi: 10.1093/nar/gkg938
Altschul, S. F. & Erickson, B. W. Significance of nucleotide sequence alignments: a method for random sequence permutation that preserves dinucleotide and codon usage. Mol. Biol. Evol. 2, 526–538 (1985).
pubmed: 3870875