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Cited by 30Bacteriophages and microbial interactionsCRISPR and Genetic EngineeringBacterial Genetics and Biotechnology

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CRISPRi-ART enables functional genomics of diverse bacteriophages using RNA-binding dCas13d

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Adler, Benjamin A., Al-Shimary, Muntathar J., Patel, Jaymin R., Armbruster, Emily G., Colognori, David, Charles, Emeric J., Miller, Kate V., Lahiri, Arushi, Cui, Michael L., Oromí-Bosch, Agnès, Voelker, Angela, Trinidad, Marena, Lee, Jina, Beurnier, Sebastien, Boger, Ron, Nomburg, Jason, Barrangou, Rodolphe, Mutalik, Vivek K., Schoeniger, Joseph S., Pogliano, Joseph A., Savage, David F., Doudna, Jennifer A., Cress, Brady F.·2025·Nature Microbiology
DOI 10.1038/s41564-025-01935-7PMC PMC11879866
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Abstract

Bacteriophages constitute one of the largest reservoirs of genes of unknown function in the biosphere. Even in well-characterized phages, the functions of most genes remain unknown. Experimental approaches to study phage gene fitness and function at genome scale are lacking, partly because phages subvert many modern functional genomics tools. Here we leverage RNA-targeting dCas13d to selectively interfere with protein translation and to measure phage gene fitness at a transcriptome-wide scale. We find CRISPR Interference through Antisense RNA-Targeting (CRISPRi-ART) to be effective across phage phylogeny, from model ssRNA, ssDNA and dsDNA phages to nucleus-forming jumbo phages. Using CRISPRi-ART, we determine a conserved role of diverse rII homologues in subverting phage Lambda RexAB-mediated immunity to superinfection and identify genes critical for phage fitness. CRISPRi-ART establishes a broad-spectrum phage functional genomics platform, revealing more than 90 previously unknown genes important for phage fitness.

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  • Recent technologies for bacterial phenotyping and phage receptor identification enable predictive modeling.

    “Recent technologies for bacterial phenotyping and phage receptor identification enable predictive modeling [90,151–156]”

    From Phage therapy in oncology: opportunities for cancer prevention and treatment (2026) · cites this paper as [90]

    The Results section on targeting bacterial ribosome-binding sites (Fig. 1; page unavailable) shows that CRISPRi-ART measures E. coli growth effects when bacterial genes are repressed, supporting the bacterial-phenotyping part. The Discussion describes its primary use as phage functional genomics. Our copy does not show phage receptor identification or establish that these technologies enable predictive modeling. (LLM, conf=0.76)

    Experimental — accuracy not yet measured

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  1. Clokie, M. R., Millard, A. D., Letarov, A. V. & Heaphy, S. Phages in nature. Bacteriophage 1, 31–45 (2011). · DOI
  2. Cobián Güemes, A. G. et al. Viruses as winners in the game of life. Annu. Rev. Virol. 3, 197–214 (2016). · DOI
  3. Bernheim, A. & Sorek, R. The pan-immune system of bacteria: antiviral defence as a community resource. Nat. Rev. Microbiol. 18, 113–119 (2019). · DOI
  4. Youle, M., Haynes, M. & Rohwer, F. in Viruses: Essential Agents of Life (ed. Witzany, G.) 61–81 (Springer, 2012). · DOI
  5. Qi, L. S. et al. Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression. Cell 152, 1173–1183 (2013). · DOI · Paper page
  6. Peters, J. M. et al. A comprehensive, CRISPR-based functional analysis of essential genes in bacteria. Cell 165, 1493–1506 (2016). · DOI
  7. Liu, X. et al. High-throughput CRISPRi phenotyping identifies new essential genes in Streptococcus pneumoniae. Mol. Syst. Biol. 13, 931 (2017). · DOI
  8. Lee, H. H. et al. Functional genomics of the rapidly replicating bacterium Vibrio natriegens by CRISPRi. Nat. Microbiol. 4, 1105–1113 (2019). · DOI
  9. Peters, J. M. et al. Enabling genetic analysis of diverse bacteria with Mobile-CRISPRi. Nat. Microbiol. 4, 244–250 (2019). · DOI
  10. Huang, C. J., Adler, B. A. & Doudna, J. A. A naturally DNase-free CRISPR-Cas12c enzyme silences gene expression. Mol. Cell 82, 2148–2160.e4 (2022). · DOI
  11. Shin, J. et al. Genome-wide CRISPRi screen identifies enhanced autolithotrophic phenotypes in acetogenic bacterium. Proc. Natl Acad. Sci. USA 120, e2216244120 (2023). · DOI
  12. Baltimore, D. Expression of animal virus genomes. Bacteriol. Rev. 35, 235–241 (1971). · DOI
  13. Mayer, M. P. in Prokaryotic and Eukaryotic Heat Shock Proteins in Infectious Disease (eds Pockley, A. G. et al.) 85–105 (Springer, 2010). · DOI
  14. Weigele, P. & Raleigh, E. A. Biosynthesis and function of modified bases in bacteria and their viruses. Chem. Rev. 116, 12655–12687 (2016). · DOI
  15. Davison, J. Pre-early functions of bacteriophage T5 and its relatives. Bacteriophage 5, e1086500 (2015). · DOI
  16. Chaikeeratisak, V. et al. Assembly of a nucleus-like structure during viral replication in bacteria. Science 355, 194–197 (2017). · DOI
  17. Prichard, A. et al. Identifying the core genome of the nucleus-forming bacteriophage family and characterization of Erwinia phage RAY. Cell Rep. 42, 112432 (2023). · DOI
  18. Vlot, M. et al. Bacteriophage DNA glucosylation impairs target DNA binding by type I and II but not by type V CRISPR-Cas effector complexes. Nucleic Acids Res. 46, 873–885 (2018). · DOI
  19. Mendoza, S. D. et al. A bacteriophage nucleus-like compartment shields DNA from CRISPR nucleases. Nature 577, 244–248 (2020). · DOI
  20. Adler, B. A. et al. Broad-spectrum CRISPR-Cas13a enables efficient phage genome editing. Nat. Microbiol. 7, 1967–1979 (2022). · DOI
  21. Charles, E. J. et al. Engineering improved Cas13 effectors for targeted post-transcriptional regulation of gene expression. Preprint at bioRxiv https://doi.org/10.1101/2021.05.26.445687 (2021). · DOI
  22. 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). · DOI
  23. Konermann, S. et al. Transcriptome engineering with RNA-targeting type VI-D CRISPR effectors. Cell 173, 665–676.e14 (2018). · DOI · Paper page
  24. Miller, E. S. et al. Bacteriophage T4 genome. Microbiol. Mol. Biol. Rev. 67, 86–156 (2003). · DOI
  25. Calendar, R. The Bacteriophages Vol. 1 (Springer, 1988). · DOI
  26. Birkholz, E. A. et al. A cytoskeletal vortex drives phage nucleus rotation during jumbo phage replication in E. coli. Cell Rep. 40, 111179 (2022). · DOI
  27. Fiers, W. et al. Complete nucleotide sequence of bacteriophage MS2 RNA: primary and secondary structure of the replicase gene. Nature 260, 500–507 (1976). · DOI
  28. Benzer, S. Fine structure of a genetic region in bacteriophage. Proc. Natl Acad. Sci. USA 41, 344–354 (1955). · DOI
  29. Wong, S., Alattas, H. & Slavcev, R. A. A snapshot of the λ T4rII exclusion (Rex) phenotype in Escherichia coli. Curr. Genet. 67, 739–745 (2021). · DOI
  30. Adams, M. C. et al. The crystal structure of bacteriophage λ RexA provides novel insights into the DNA binding properties of Rex-like phage exclusion proteins. Nucleic Acids Res. 52, 4659–4675 (2024). · DOI
  31. Otsuka, Y. & Yonesaki, T. Dmd of bacteriophage T4 functions as an antitoxin against Escherichia coli LsoA and RnlA toxins. Mol. Microbiol. 83, 669–681 (2012). · DOI
  32. Hendrickson, H. E. & McCorquodale, D. J. Genetic and physiological studies of bacteriophage T5 I. An expanded genetic map of T5. J. Virol. 7, 612–618 (1971). · DOI
  33. Mozer, T. J., Thompson, R. B., Berget, S. M. & Warner, H. R. Isolation and characterization of a bacteriophage T5 mutant deficient in deoxynucleoside 5’-monophosphatase activity. J. Virol. 24, 642–650 (1977). · DOI
  34. Keen, E. C. et al. Novel ‘superspreader’ bacteriophages promote horizontal gene transfer by transformation. mBio 8, e02115-16 (2017). · DOI
  35. Korf, I. H. E. et al. Still something to discover: novel insights into Escherichia coli phage diversity and taxonomy. Viruses 11, 454 (2019). · DOI
  36. Iyer, L. M., Burroughs, A. M., Anand, S., de Souza, R. F. & Aravind, L. Polyvalent proteins, a pervasive theme in the intergenomic biological conflicts of bacteriophages and conjugative elements. J. Bacteriol. 199, e00245-17 (2017). · DOI
  37. Piya, D., Vara, L., Russell, W. K., Young, R. & Gill, J. J. The multicomponent antirestriction system of phage P1 is linked to capsid morphogenesis. Mol. Microbiol. 105, 399–412 (2017). · DOI
  38. Sobrero, P. M. & Valverde, C. Comparative genomics and evolutionary analysis of RNA-binding proteins of the CsrA family in the genus Pseudomonas. Front. Mol. Biosci. 7, 127 (2020). · DOI
  39. Campa, A. R. et al. The Rsm (Csr) post-transcriptional regulatory pathway coordinately controls multiple CRISPR-Cas immune systems. Nucleic Acids Res. 49, 9508–9525 (2021). · DOI
  40. Strathdee, S. A., Hatfull, G. F., Mutalik, V. K. & Schooley, R. T. Phage therapy: from biological mechanisms to future directions. Cell 186, 17–31 (2023). · DOI · Paper page
  41. Rubin, B. E. et al. Species- and site-specific genome editing in complex bacterial communities. Nat. Microbiol. 7, 34–47 (2022). · DOI
  42. Nethery, M. A., Hidalgo-Cantabrana, C., Roberts, A. & Barrangou, R. CRISPR-based engineering of phages for in situ bacterial base editing. Proc. Natl Acad. Sci. USA 119, e2206744119 (2022). · DOI
  43. Brödel, A. K. et al. In situ targeted base editing of bacteria in the mouse gut. Nature 632, 877–884 (2024). · DOI
  44. Duong, M. M., Carmody, C. M., Ma, Q., Peters, J. E. & Nugen, S. R. Optimization of T4 phage engineering via CRISPR/Cas9. Sci. Rep. 10, 18229 (2020). · DOI
  45. Wu, W. Y. et al. The miniature CRISPR-Cas12m effector binds DNA to block transcription. Mol. Cell 82, 4487–4502.e7 (2022). · DOI
  46. Gerovac, M. et al. Non-genetic messenger RNA silencing reveals essential genes in phage–host interplay. Preprint at bioRxiv https://doi.org/10.1101/2024.07.31.605949 (2024). · DOI
  47. Ojima, S. et al. Systematic discovery of phage genes that inactivate bacterial immune systems. Preprint at bioRxiv https://doi.org/10.1101/2024.04.14.589459 (2024). · DOI
  48. Armbruster, E. G. et al. Sequential membrane- and protein-bound organelles compartmentalize genomes during phage infection. Cell Rep. (in the press).
  49. Enustun, E. et al. A phage nucleus-associated RNA-binding protein is required for jumbo phage infection. Nucleic Acids Res. 52, 4440–4455 (2024). · DOI · Paper page
  50. Morgan, C. J. et al. An essential and highly selective protein import pathway encoded by nucleus-forming phage. Proc. Natl Acad. Sci. USA 121, e2321190121 (2024). · DOI · Paper page
  51. Nguyen, K. T. et al. Selective transport of fluorescent proteins into the phage nucleus. PLoS ONE 16, e0251429 (2021). · DOI
  52. Borges, A. L. et al. Widespread stop-codon recoding in bacteriophages may regulate translation of lytic genes. Nat. Microbiol. 7, 918–927 (2022). · DOI
  53. Luria, S. E. & Human, M. L. A nonhereditary, host-induced variation of bacterial viruses. J. Bacteriol. 64, 557–569 (1952). · DOI
  54. Arber, W. & Linn, S. DNA modification and restriction. Annu. Rev. Biochem. 38, 467–500 (1969). · DOI
  55. Barrangou, R. et al. CRISPR provides acquired resistance against viruses in prokaryotes. Science 315, 1709–1712 (2007). · DOI · Paper page
  56. Gibson, D. G. et al. Enzymatic assembly of DNA molecules up to several hundred kilobases. Nat. Methods 6, 343–345 (2009). · DOI
  57. Weber, E., Engler, C., Gruetzner, R., Werner, S. & Marillonnet, S. A modular cloning system for standardized assembly of multigene constructs. PLoS ONE 6, e16765 (2011). · DOI
  58. Jinek, M. et al. A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science 337, 816–821 (2012). · DOI · Paper page
  59. Ruegg, T. L. et al. Jungle Express is a versatile repressor system for tight transcriptional control. Nat. Commun. 9, 3617 (2018). · DOI
  60. Abedon, S. T. Lysis from without. Bacteriophage 1, 46–49 (2011). · DOI
  61. Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012). · DOI · Paper page
  62. Subramanian, S. K., Russ, W. P. & Ranganathan, R. A set of experimentally validated, mutually orthogonal primers for combinatorially specifying genetic components. Synth. Biol. 3, ysx008 (2018). · DOI
  63. Keseler, I. M. et al. EcoCyc: a comprehensive database resource for Escherichia coli. Nucleic Acids Res. 33, D334–D337 (2005). · DOI
  64. Li, G.-W., Burkhardt, D., Gross, C. & Weissman, J. S. Quantifying absolute protein synthesis rates reveals principles underlying allocation of cellular resources. Cell 157, 624–635 (2014). · DOI
  65. de Bakker, V., Liu, X., Bravo, A. M. & Veening, J.-W. CRISPRi-seq for genome-wide fitness quantification in bacteria. Nat. Protoc. 17, 252–281 (2022). · DOI
  66. Bravo, A. M., Typas, A. & Veening, J.-W. 2FAST2Q: a general-purpose sequence search and counting program for FASTQ files. PeerJ 10, e14041 (2022). · DOI
  67. Chen, S., Zhou, Y., Chen, Y. & Gu, J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34, i884–i890 (2018). · DOI · Paper page
  68. Lu, S. et al. CDD/SPARCLE: the conserved domain database in 2020. Nucleic Acids Res. 48, D265–D268 (2020). · DOI
  69. Terzian, P. et al. PHROG: families of prokaryotic virus proteins clustered using remote homology. NAR Genom. Bioinform. 3, lqab067 (2021). · DOI
  70. Zimmermann, L. et al. A completely reimplemented MPI bioinformatics toolkit with a new HHpred server at its core. J. Mol. Biol. 430, 2237–2243 (2018). · DOI · Paper page
  71. Holm, L. Dali server: structural unification of protein families. Nucleic Acids Res. 50, W210–W215 (2022). · DOI
  72. Boger, R. et al. TOPH (True Retrieval Of Proteins Homologs): adapting a contrastive question-answering framework for protein search. In Proc. 2023 ICML Workshop on Computational Biology (ICML, 2023); https://icml-compbio.github.io/2023/papers/WCBICML2023_paper138.pdf
  73. Wang, J. et al. Complete genome sequence of bacteriophage T5. Virology 332, 45–65 (2005). · DOI
  74. Whichard, J. M. et al. Complete genomic sequence of bacteriophage felix o1. Viruses 2, 710–730 (2010). · DOI
  75. Hobbs, S. J. et al. Phage anti-CBASS and anti-Pycsar nucleases subvert bacterial immunity. Nature 605, 522–526 (2022). · DOI
  76. Huiting, E. et al. Bacteriophages inhibit and evade cGAS-like immune function in bacteria. Cell 186, 864–876.e21 (2023). · DOI
  77. Jenson, J. M., Li, T., Du, F., Ea, C.-K. & Chen, Z. J. Ubiquitin-like conjugation by bacterial cGAS enhances anti-phage defence. Nature 616, 326–331 (2023). · DOI
  78. Azam, A. H. et al. Evasion of antiviral bacterial immunity by phage tRNAs. Nat. Commun. 15, 9586 (2024). · DOI
  79. Cook, R. et al. INfrastructure for a PHAge REference Database: identification of large-scale biases in the current collection of cultured phage genomes. Phage 2, 214–223 (2021). · DOI
  80. Steinegger, M. & Söding, J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nat. Biotechnol. 35, 1026–1028 (2017). · DOI · Paper page
  81. 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). · DOI · Paper page
  82. Katoh, K., Misawa, K., Kuma, K.-I. & Miyata, T. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res. 30, 3059–3066 (2002). · DOI · Paper page
  83. Capella-Gutiérrez, S., Silla-Martínez, J. M. & Gabaldón, T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 25, 1972–1973 (2009). · DOI
  84. Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree 2 – approximately maximum-likelihood trees for large alignments. PLoS ONE 5, e9490 (2010). · DOI · Paper page
  85. Letunic, I. & Bork, P. Interactive Tree of Life (iTOL) v6: recent updates to the phylogenetic tree display and annotation tool. Nucleic Acids Res. 52, W78–W82 (2024). · DOI
  86. Bin Jang, H. et al. Taxonomic assignment of uncultivated prokaryotic virus genomes is enabled by gene-sharing networks. Nat. Biotechnol. 37, 632–639 (2019). · DOI

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Metadata

Authors
Adler, B. A., Al-Shimary, M. J., Patel, J. R., Armbruster, E. G., Colognori, D., Charles, E. J., Miller, K. V., Lahiri, A., Cui, M. L., Oromí-Bosch, A., Voelker, A., Trinidad, M., Lee, J., Beurnier, S., Boger, R., Nomburg, J., Barrangou, R., Mutalik, V. K., Schoeniger, J. S., Pogliano, J. A., Savage, D. F., Doudna, J. A., & Cress, B. F.
Affiliations
  • QB3 (US)
  • Innovative Genomics Institute (US)
  • University of California San Diego (US)
  • University of California, Berkeley (US)
  • North Carolina State University (US)
  • Lawrence Berkeley National Laboratory (US)
  • Sandia National Laboratories California (US)
  • Howard Hughes Medical Institute (US)
Corresponding author
  • Doudna, Jennifer A.
  • Cress, Brady F.
ORCID
Venue
Nature Microbiology
Publisher
Springer Science and Business Media LLC
Published
2025-02-26
Volume
10
Issue
3
Pages
694-709
ISSN
2058-5276 (ISSN-L)
DOI
10.1038/s41564-025-01935-7
PMC
PMC11879866
OpenAlex
W4407978786
Cited by
30
References
4
Citations by year
2026: 14 · 2025: 16
FWCI
15.87
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Microbiology (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
  • eScholarship (California Digital Library) (submittedVersion, cc-by)
Funders
  • National Science Foundation (DEAC02-05CH11231)
  • U.S. Department of Energy (-AC02-05CH11231, 05CH11231, DE AC02 05CH11231, DE-AC02-)
  • Silicon Valley Community Foundation
  • Leona M. and Harry B. Helmsley Charitable Trust
  • Innovative Genomics Institute
  • Emerson Collective
  • Valhalla Foundation
  • Office of Science (DEAC02–05CH11231, AC02-05CH11231, DE-AC02)
  • Biological and Environmental Research (05CH11231, DE-AC02 − 05CH11231, AC02-05CH11231)
  • Lawrence Berkeley National Laboratory (AC02‐05CH11231, DE-AC02-05CH11231, 05CH11231)
Topics
  • Life Sciences › Immunology and Microbiology › Virology › Bacteriophages and microbial interactions
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › CRISPR and Genetic Engineering
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Bacterial Genetics and Biotechnology
Keywords
CRISPR interference, bacteriophages, RNA-targeting CRISPR, gene fitness, superinfection immunity, translation interference, phage gene function
MeSH terms
Bacteriophages, Bacteriophage lambda, Phylogeny, RNA, Antisense, RNA-Binding Proteins, Genome, Viral, Genomics, Genetic Fitness, Clustered Regularly Interspaced Short Palindromic Repeats, CRISPR-Cas Systems

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