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Phylogenetic Analysis of Anti-CRISPR and Member Addition in the Families

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Abstract

CRISPR-Cas is a widespread anti-viral adaptive immune system in the microorganisms. Viruses living in bacteria or some phages carry anti-CRISPR proteins to evade immunity by CRISPR-Cas. The anti-CRISPR proteins are prevalent in phages capable of lying dormant in a CRISPR-carrying host, while their orthologs frequently found in virulent phages. Here, we propose a probabilistic strategy of ancestral sequence reconstruction (ASR) and Hidden Markov Model (HMM) profile search to fish out sequences of anti-CRISPR proteins from environmental metagenomic, human microbiome metagenomic, human microbiome reference genome, and NCBI’s non-redundant databases. Our results revealed that the metagenome database dark matter might contain anti-CRISPR encoding genes.

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References

  1. Seed, K. D. (2015). Battling phages: How bacteria defend against viral attack. PLoS Pathogens, 11(6), e1004847.

    Article  Google Scholar 

  2. Ishino, Y., Shinagawa, H., Makino, K., Amemura, M., & Nakata, A. (1987). Nucleotide sequence of the iap gene, responsible for alkaline phosphatase isozyme conversion in Escherichia coli, and identification of the gene product. Journal of Bacteriology, 169(12), 5429–5433.

    Article  CAS  Google Scholar 

  3. Grissa, I., Vergnaud, G., & Pourcel, C. (2007). The CRISPRdb database and tools to display CRISPRs and to generate dictionaries of spacers and repeats. BMC Bioinformatics, 23(8), 172.

    Article  Google Scholar 

  4. Labrie, S., Samson, J., & Moineau, S. (2010). Bacteriophage resistance mechanisms. Nature Reviews Microbiology, 8(5), 317–327.

    Article  CAS  Google Scholar 

  5. Samson, J., Magadán, A., Sabri, M., & Moineau, S. (2013). Revenge of the phages: Defeating bacterial defences. Nature Reviews Microbiology, 11(10), 675–687.

    Article  CAS  Google Scholar 

  6. Levasseur, A., Bekliz, M., Chabrière, E., Pontarotti, P., La Scola, B., & Raoult, D. (2016). MIMIVIRE is a defence system in mimivirus that confers resistance to virophage. Nature, 531(7593), 249–252.

    Article  CAS  Google Scholar 

  7. Makarova, K. S., Haft, D. H., Barrangou, R., Brouns, S. J. J., Charpentier, E., Horvath, P., Moineau, S., Mojica, F. J. M., Wolf, Y. I., Yakunin, A. F., Oost, J. V. D., & Koonin, E. V. (2011). Evolution and classification of the CRISPR-Cas systems. Nature Reviews Microbiology, 9(6), 467–477.

    Article  CAS  Google Scholar 

  8. Burstein, D., Harrington, L. B., Strutt, S. C., Probst, A. J., Anantharaman, K., Thomas, B. C., Doudna, J. A., & Banfield, J. F. (2017). New CRISPR-Cas systems from uncultivated microbes. Nature, 542(7640), 237–241.

    Article  CAS  Google Scholar 

  9. Makarova, K. S., Wolf, Y. I., Alkhnbashi, O. S., Costa, F., Shah, S. A., Saunders, S. J., Barrangou, R., Brouns, S. J. J., Charpentier, E., Haft, D. H., Horvath, P., Moineau, S., Mojica, F. J. M., Terns, R. M., Terns, M. P., White, M. F., Yakunin, A. F., Garrett, R. A., Oost, J. V. D., … Koonin, E. V. (2015). An updated evolutionary classification of CRISPR-Cas systems. Nature Reviews Microbiology, 13(11), 722–736.

    Article  CAS  Google Scholar 

  10. Jore, M., Brouns, S., & van der Oost, J. (2012). RNA in defense: CRISPRs protect prokaryotes against mobile genetic elements. Cold Spring Harbor Perspectives in Biology, 4(6), a003657.

    Article  Google Scholar 

  11. Bondy-Denomy, J., Pawluk, A., Maxwell, K. L., & Davidson, A. R. (2013). Bacteriophage genes that inactivate the CRISPR/Cas bacterial immune system. Nature, 493(7432), 429–432.

    Article  CAS  Google Scholar 

  12. Hynes, A. P., Rousseau, G. M., Lemay, M. L., Horvath, P., Romero, D. A., Fremaux, C., & Moineau, S. (2017). An anti-CRISPR from a virulent streptococcal phage inhibits Streptococcus pyogenes Cas9. Nature Microbiology, 2(10), 1374–1380.

    Article  CAS  Google Scholar 

  13. He, F., Bhoobalan-Chitty, Y., Van, L. B., Kjeldsen, A. L., Dedola, M., Makarova, K. S., Koonin, E. V., Brodersen, D. E., & Peng, X. (2018). Anti-CRISPR proteins encoded by archaeal lytic viruses inhibit subtype I-D immunity. Nature Microbiology, 3(4), 461–469.

    Article  CAS  Google Scholar 

  14. Pawluk, A., Davidson, A., & Maxwell, K. (2017). Anti-CRISPR: Discovery, mechanism and function. Nature Reviews Microbiology, 16(1), 12–17.

    Article  Google Scholar 

  15. Pawluk, A., Staals, R. H. J., Taylor, C., Watson, B. N. J., Saha, S., Fineran, P. C., Maxwell, K. L., & Davidson, A. R. (2016). Inactivation of CRISPR-Cas systems by anti-CRISPR proteins in diverse bacterial species. Nature Microbiology, 1, 16085.

    Article  CAS  Google Scholar 

  16. Pawluk, A., Amrani, N., Zhang, Y., Garcia, B., Reyes-Hidalgo, Y., Lee, J., Edraki, A., Shah, M., Sontheimer, E. J., Maxwell, K. L., & Davidson, A. R. (2016). Naturally occurring off-switches for CRISPR-Cas9. Cell, 167(7), 1829-1838.e9.

    Article  CAS  Google Scholar 

  17. Dong, C., Hao, G. F., Hua, H. L., Liu, S., Labena, A. A., Chai, G., Huang, J., Rao, N., & Guo, F. B. (2018). Anti-CRISPRdb: A comprehensive online resource for anti-CRISPR proteins. Nucleic Acids Research, 46(D1), D393–D398.

    Article  CAS  Google Scholar 

  18. Iqbal, H. A., Feng, Z., & Brady, S. F. (2012). Biocatalysts and small molecule products from metagenomic studies. Current Opinion in Chemical Biology, 16, 109–116.

    Article  CAS  Google Scholar 

  19. Rabausch, U., Juergensen, J., Ilmberger, N., Bohnke, S., Fischer, S., Schubach, B., Schulte, M., & Streit, W. R. (2013). Functional screening of metagenome and genome libraries for detection of novel flavonoid-modifying enzymes. Applied and Environmental Microbiology, 79, 4551–4563.

    Article  CAS  Google Scholar 

  20. Eddy, S. R. (2011). Accelerated profile HMM searches. PLoS Computational Biology, 7(10), e1002195.

    Article  CAS  Google Scholar 

  21. Collins, L. J., Poole, A. M., & Penny, D. (2003). Using ancestral sequences to uncover potential gene homologues. Applied Bioinformatics, 2(3 Suppl), S85-95.

    CAS  Google Scholar 

  22. Edgar, R. C. (2004). MUSCLE: A multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics, 5, 113.

    Article  Google Scholar 

  23. Capella-Gutiérrez, S., Silla-Martínez, J. M., & Gabaldón, T. (2009). trimAl: A tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics, 25(15), 1972–1973.

    Article  Google Scholar 

  24. Price, M. N., Dehal, P. S., & Arkin, A. P. (2010). FastTree 2—Approximately maximum-likelihood trees for large alignments. PLoS ONE, 5(3), e9490.

    Article  Google Scholar 

  25. Sullivan, M. J., Petty, N. K., & Beats-on, S. A. (2011). EasyFig: A genome comparison visualizer. Bioinformatics, 27(7), 1009–1010.

    Article  CAS  Google Scholar 

  26. Wang, J., Dai, W., Li, J., Xie, R., Dunstan, A. R., Stubenrauch, C., Zhang, Y., & Lithgow, T. (2020). PaCRISPR: A server for predicting and visualizing anti-CRISPR proteins. Nucleic Acids Research, 48(1), W348–W357.

    Article  CAS  Google Scholar 

  27. Meyer, H., & Foucault, M. (n.d.). L'archéologie du savoir. Books Abroad, 44(2), 263.

  28. Abat, C., Raoult, D., & Rolain, J. (2018). Are we living in an antibiotic resistance nightmare? Clinical Microbiology and Infection, 24(6), 568–569.

    Article  CAS  Google Scholar 

  29. Koonin, E., & Krupovic, M. (2015). Evolution of adaptive immunity from transposable elements combined with innate immune systems. Nature Reviews Genetics, 16(3), 184–192.

    Article  CAS  Google Scholar 

  30. Risso, V. A., Gavira, J. A., Mejia-Carmona, D. F., Gaucher, E. A., & Sanchez-Ruiz, J. M. (2013). Hyperstability and substrate promiscuity in laboratory resurrections of Precambrian β-lactamases. Journal of the American Chemical Society, 135, 2899–2902.

    Article  CAS  Google Scholar 

  31. Sharma, V., Colson, P., Giorgi, R., Pontarotti, P., & Raoult, D. (2014). DNA-dependent RNA polymerase detects hidden giant viruses in published databanks. Genome Biology and Evolution, 6, 1603–1610.

    Article  Google Scholar 

  32. Keshri, V., Panda, A., Levasseur, A., Rolain, J., Pontarotti, P., & Raoult, D. (2018). Phylogenomic analysis of β-lactamase in Archaea and bacteria enables the identification of putative new members. Genome Biology and Evolution, 10(4), 1106–1114.

    Article  CAS  Google Scholar 

  33. Bondy-Denomy, J., Davidson, A. R., Doudna, J. A., Fineran, P. C., Maxwell, K. L., Moineau, S., Peng, X., Sontheimer, E. J., & Wiedenheft, B. (2018). A unified resource for tracking anti-CRISPR names. CRISPR Journal, 1, 304–305.

    Article  Google Scholar 

  34. Zhang, F., Zhao, S., Ren, C., Zhu, Y., Zhou, H., Lai, Y., Zhou, F., Jia, Y., Zheng, K., & Huang, Z. (2018). CRISPRminer is a knowledge base for exploring CRISPR-Cas systems in microbe and phage interactions. Communications Biology, 1, 180.

    Article  Google Scholar 

  35. Yi, H., Huang, L., Yang, B., Gomez, J., Zhang, H., & Yin, Y. (2020). AcrFinder: Genome mining anti-CRISPR operons in prokaryotes and their viruses. Nucleic Acids Research, 48(W1), W358–W365.

    Article  CAS  Google Scholar 

  36. Wang, J., Dai, W., Li, J., Li, Q., Xie, R., Zhang, Y., Stubenrauch, C., & Lithgow, T. (2021). AcrHub: An integrative hub for investigating, predicting and mapping anti-CRISPR proteins. Nucleic Acids Research, 49(D1), D630–D638.

    Article  CAS  Google Scholar 

  37. Gussow, A. B., Park, A. E., Borges, A. L., et al. (2020). Machine-learning approach expands the repertoire of anti-CRISPR protein families. Nature Communications, 11, 3784.

    Article  CAS  Google Scholar 

  38. Eitzinger, S., Asif, A., Watters, K. E., Iavarone, A. T., Knott, G. J., Doudna, J. A., & Minhas, F. (2020). Machine learning predicts new anti-CRISPR proteins. Nucleic Acids Research, 48, 4698–4708.

    Article  CAS  Google Scholar 

  39. Dong, C., Pu, D.-K., Ma, C., Wang, X., Wen, Q.-F., Zeng, Z., & Guo F.-B. (2020). Precise detection of Acrs in prokaryotes using only six features. 2020. bioRxiv. preprint: not peer reviewed.

  40. Huang, L., Yang, B., Yi, H., Asif, A., Wang, J., Lithgow, T., Zhang, H., Minhas, F. U. A. A., & Yin, Y. (2021). AcrDB: A database of anti-CRISPR operons in prokaryotes and viruses. Nucleic Acids Research, 49(D1), D622–D629.

    Article  CAS  Google Scholar 

  41. Dong, C., Wang, X., Ma, C., Zeng, Z., Pu, D. K., Liu, S., Wu, C. S., Chen, S., Deng, Z., & Guo, F. B. (2022). Anti-CRISPRdb v2.2: An online repository of anti-CRISPR proteins including information on inhibitory mechanisms, activities and neighbors of curated anti-CRISPR proteins. Database (Oxford), 2022, baac010.

    Article  CAS  Google Scholar 

  42. Pearson, W. R. (2009). An introduction to sequence similarity (‘homology’) searching. Current Protocols in Bioinformatics. https://doi.org/10.1002/0471250953.bi0301s42

    Article  Google Scholar 

  43. Gophna, U., Kristensen, D. M., Wolf, Y. I., Pop-a, O., Drevet, C., & Koonin, E. V. (2015). No evidence of inhibition of horizontal gene transfer by CRISPR-Cas on evolutionary timescales. The ISME Journal, 9(9), 2021–2027.

    Article  Google Scholar 

  44. Touchon, M., Bernheim, A., & Rocha, E. P. C. (2016). Genetic and life-history traits associated with the distribution of prophages in bacteria. The ISME Journal, 10(11), 2744–2754.

    Article  CAS  Google Scholar 

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Acknowledgements

We would like to thank Dr. Feng-Biao Guo and Dr. Chris M. Brown, who kindly provided us with mirror site of the anti-CRISPR database containing the anti-CRISPR protein sequences.

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SN contributed to conceptualization and methodology; SN, PT, and VT contributed to formal analysis and investigation and writing—original draft of the preparation.

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Correspondence to Vijay Tripathi.

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Nidhi, S., Tripathi, P. & Tripathi, V. Phylogenetic Analysis of Anti-CRISPR and Member Addition in the Families. Mol Biotechnol 65, 273–281 (2023). https://doi.org/10.1007/s12033-022-00558-1

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