Abstract
The evolutionary arms race between bacteria and phages led to the emergence of bacterial immune systems whose diversity and dynamics remain poorly understood. Here we use comparative genomics to describe a widespread genetic element, defined by the presence of the Gamma-Mobile-Trio (GMT) proteins, that serves as a reservoir of offensive and defensive tools. We demonstrate, using Vibrio parahaemolyticus as a model, that GMT-containing genomic islands are active mobile elements. Furthermore, we show that GMT islands’ cargoes contain various anti-phage defence systems, antibacterial type VI secretion system (T6SS) effectors and antibiotic-resistance genes. We reveal four anti-phage defence systems encoded within GMT islands and further characterize one system, GAPS1, showing it is triggered by a phage capsid protein to induce cell dormancy. Our findings underscore the need to broaden the concept of ‘defence islands’ to include defensive and offensive tools, as both share the same mobile elements for dissemination.
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All data related to the manuscript are available in the main text, the supplementary material and the source data files. Source data for the figures are provided with this paper.
References
Pukatzki, S. et al. Identification of a conserved bacterial protein secretion system in Vibrio cholerae using the Dictyostelium host model system. Proc. Natl Acad. Sci. USA 103, 1528–1533 (2006).
Hood, R. D. et al. A type VI secretion system of Pseudomonas aeruginosa targets a toxin to bacteria. Cell Host Microbe 7, 25–37 (2010).
Jana, B. & Salomon, D. Type VI secretion system: a modular toolkit for bacterial dominance. Future Microbiol. 14, 1451–1463 (2019).
MacIntyre, D. L., Miyata, S. T., Kitaoka, M. & Pukatzki, S. The Vibrio cholerae type VI secretion system displays antimicrobial properties. Proc. Natl Acad. Sci. USA 107, 19520–19524 (2010).
Allsopp, L. P. & Bernal, P. Killing in the name of: T6SS structure and effector diversity. Microbiology 169, 001367 (2023).
Speare, L. et al. Bacterial symbionts use a type VI secretion system to eliminate competitors in their natural host. Proc. Natl Acad. Sci. USA 115, E8528–E8537 (2018).
Ma, L. S., Hachani, A., Lin, J. S., Filloux, A. & Lai, E. M. Agrobacterium tumefaciens deploys a superfamily of type VI secretion DNase effectors as weapons for interbacterial competition in planta. Cell Host Microbe 16, 94–104 (2014).
Borgeaud, S., Metzger, L. C., Scrignari, T. & Blokesch, M. The type VI secretion system of Vibrio cholerae fosters horizontal gene transfer. Science 347, 63–67 (2015).
Sana, T. G. et al. Salmonella Typhimurium utilizes a T6SS-mediated antibacterial weapon to establish in the host gut. Proc. Natl Acad. Sci. USA 113, E5044–E5051 (2016).
Verster, A. J. et al. The landscape of type VI secretion across human gut microbiomes reveals its role in community composition. Cell Host Microbe 22, 411–419.e4 (2017).
Unterweger, D. et al. The Vibrio cholerae type VI secretion system employs diverse effector modules for intraspecific competition. Nat. Commun. 5, 3549 (2014).
Pleška, M., Lang, M., Refardt, D., Levin, B. R. & Guet, C. C. Phage–host population dynamics promotes prophage acquisition in bacteria with innate immunity. Nat. Ecol. Evol. 2, 359–366 (2018).
Hussain, F. A. et al. Rapid evolutionary turnover of mobile genetic elements drives bacterial resistance to phages. Science 374, 488–492 (2021).
Piel, D. et al. Phage–host coevolution in natural populations. Nat. Microbiol. 7, 1075–1086 (2022).
Hampton, H. G., Watson, B. N. J. & Fineran, P. C. The arms race between bacteria and their phage foes. Nature 577, 327–336 (2020).
Doron, S. et al. Systematic discovery of antiphage defense systems in the microbial pangenome. Science 359, eaar4120 (2018).
Makarova, K. S., Wolf, Y. I., Snir, S. & Koonin, E. V. Defense islands in bacterial and archaeal genomes and prediction of novel defense systems. J. Bacteriol. 193, 6039–6056 (2011).
Bernheim, A. & Sorek, R. The pan-immune system of bacteria: antiviral defence as a community resource. Nat. Rev. Microbiol. 18, 113–119 (2020).
Millman, A. et al. An expanded arsenal of immune systems that protect bacteria from phages. Cell Host Microbe 30, 1556–1569.e5 (2022).
Le Roux, F. & Blokesch, M. Eco-evolutionary dynamics linked to horizontal gene transfer in vibrios. Annu. Rev. Microbiol. 72, 89–110 (2018).
Arnold, B. J., Huang, I. T. & Hanage, W. P. Horizontal gene transfer and adaptive evolution in bacteria. Nat. Rev. Microbiol. 20, 206–218 (2022).
Horne, T., Orr, V. T. & Hall, J. P. How do interactions between mobile genetic elements affect horizontal gene transfer? Curr. Opin. Microbiol. 73, 102282 (2023).
Bellanger, X., Payot, S., Leblond-Bourget, N. & Guédon, G. Conjugative and mobilizable genomic islands in bacteria: evolution and diversity. FEMS Microbiol. Rev. 38, 720–760 (2014).
Khedkar, S. et al. Landscape of mobile genetic elements and their antibiotic resistance cargo in prokaryotic genomes. Nucleic Acids Res. 50, 3155–3168 (2022).
Stephens, C. et al. F plasmids are the major carriers of antibiotic resistance genes in human-associated commensal Escherichia coli. mSphere 5, e00709–e00720 (2020).
Alekshun, M. N. & Levy, S. B. Molecular mechanisms of antibacterial multidrug resistance. Cell 128, 1037–1050 (2007).
Fillol-Salom, A. et al. Bacteriophages benefit from mobilizing pathogenicity islands encoding immune systems against competitors. Cell 185, 3248–3262.e20 (2022).
Vassallo, C. N., Doering, C. R., Littlehale, M. L., Teodoro, G. I. C. & Laub, M. T. A functional selection reveals previously undetected anti-phage defence systems in the E. coli pangenome. Nat. Microbiol. 7, 1568–1579 (2022).
Rousset, F. et al. Phages and their satellites encode hotspots of antiviral systems. Cell Host Microbe 30, 740–753.e5 (2022).
Salomon, D. et al. Type VI secretion system toxins horizontally shared between marine bacteria. PLoS Pathog. 11, e1005128 (2015).
Jana, B., Keppel, K., Fridman, C. M., Bosis, E. & Salomon, D. Multiple T6SSs, mobile auxiliary modules, and effectors revealed in a systematic analysis of the Vibrio parahaemolyticus pan-genome. mSystems 7, e00723-22 (2022).
Thomas, J., Watve, S. S., Ratcliff, W. C. & Hammer, B. K. Horizontal gene transfer of functional type VI killing genes by natural transformation. mBio 8, e00654-17 (2017).
Santoriello, F. J., Kirchberger, P. C., Boucher, Y. & Pukatzki, S. Pandemic Vibrio cholerae acquired competitive traits from an environmental Vibrio species. Life Sci. Alliance 6, e202201437 (2023).
Ruhe, Z. C., Low, D. A. & Hayes, C. S. Polymorphic toxins and their immunity proteins: diversity, evolution, and mechanisms of delivery. Annu. Rev. Microbiol. 74, 497–520 (2020).
Ellabaan, M. M. H., Munck, C., Porse, A., Imamovic, L. & Sommer, M. O. A. Forecasting the dissemination of antibiotic resistance genes across bacterial genomes. Nat. Commun. 12, 2435 (2021).
Baker-Austin, C. Vibrio spp. infections. Nat. Rev. Dis. Primers 4, 8 (2018).
Hurley, C. C., Quirke, A. M., Reen, F. J. & Boyd, E. F. Four genomic islands that mark post-1995 pandemic Vibrio parahaemolyticus isolates. BMC Genomics 7, 104 (2006).
Salomon, D. et al. Marker for type VI secretion system effectors. Proc. Natl Acad. Sci. USA 111, 9271–9276 (2014).
Fridman, C. M., Jana, B., Ben-Yaakov, R., Bosis, E. & Salomon, D. A DNase type VI secretion system effector requires its MIX domain for secretion. Microbiol. Spectr. 10, e0246522 (2022).
Marchler-Bauer, A. et al. CDD: a conserved domain database for interactive domain family analysis. Nucleic Acids Res. 35, D237–D240 (2007).
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).
Guerrero-Bustamante, C. A. & Hatfull, G. F. Bacteriophage tRNA-dependent lysogeny: requirement of phage-encoded tRNA genes for establishment of lysogeny. mBio 15, e0326023 (2024).
Banerjee, S., Petronella, N., Leung, C. C. & Farber, J. Draft genome sequences of four Vibrio parahaemolyticus isolates from clinical cases in Canada. Genome Announc. 3, e01482-14 (2015).
Pedelacq, J. D. & Cabantous, S. Development and applications of superfolder and split fluorescent protein detection systems in biology. Int. J. Mol. Sci. 20, 3479 (2019).
Davidov, E. & Kaufmann, G. RloC: a wobble nucleotide-excising and zinc-responsive bacterial tRNase. Mol. Microbiol. 69, 1560–1574 (2008).
Shneider, M. M. et al. PAAR-repeat proteins sharpen and diversify the type VI secretion system spike. Nature 500, 350–353 (2013).
Ray, A. et al. Type VI secretion system MIX-effectors carry both antibacterial and anti-eukaryotic activities. EMBO Rep. 18, 1978–1990 (2017).
Dar, Y., Salomon, D. & Bosis, E. The antibacterial and anti-eukaryotic type VI secretion system MIX-effector repertoire in Vibrionaceae. Mar. Drugs 16, 433 (2018).
Jana, B., Fridman, C. M., Bosis, E. & Salomon, D. A modular effector with a DNase domain and a marker for T6SS substrates. Nat. Commun. 10, 3595 (2019).
Koskiniemi, S. et al. Rhs proteins from diverse bacteria mediate intercellular competition. Proc. Natl Acad. Sci. USA 110, 7032–7037 (2013).
Payne, L. J. et al. Identification and classification of antiviral defence systems in bacteria and archaea with PADLOC reveals new system types. Nucleic Acids Res. 49, 10868–10878 (2021).
Tesson, F. et al. Systematic and quantitative view of the antiviral arsenal of prokaryotes. Nat. Commun. 13, 2561 (2022).
Botelho, J. Defense systems are pervasive across chromosomally integrated mobile genetic elements and are inversely correlated to virulence and antimicrobial resistance. Nucleic Acids Res. 51, 4385–4397 (2023).
Wozniak, R. A. F. et al. Comparative ICE genomics: insights into the evolution of the SXT/R391 family of ICEs. PLoS Genet. 5, e1000786 (2009).
Dobrindt, U., Hochhut, B., Hentschel, U. & Hacker, J. Genomic islands in pathogenic and environmental microorganisms. Nat. Rev. Microbiol. 2, 414–424 (2004).
LeGault, K. N. et al. Temporal shifts in antibiotic resistance elements govern phage-pathogen conflicts. Science 373, eabg2166 (2021).
Maffei, E. et al. Systematic exploration of Escherichia coli phage–host interactions with the BASEL phage collection. PLoS Biol. 19, e3001424 (2021).
Johnson, A. G. et al. Bacterial gasdermins reveal an ancient mechanism of cell death. Science 375, 221–225 (2022).
Ernits, K. et al. The structural basis of hyperpromiscuity in a core combinatorial network of type II toxin–antitoxin and related phage defense systems. Proc. Natl Acad. Sci. USA 120, e2305393120 (2023).
Hossain, A. A. et al. DNA glycosylases provide antiviral defence in prokaryotes. Nature 629, 410–416 (2024).
Knizewski, L., Kinch, L. N., Grishin, N. V., Rychlewski, L. & Ginalski, K. Realm of PD-(D/E)XK nuclease superfamily revisited: detection of novel families with modified transitive meta profile searches. BMC Struct. Biol. 7, 40 (2007).
Steczkiewicz, K., Muszewska, A., Knizewski, L., Rychlewski, L. & Ginalski, K. Sequence, structure and functional diversity of PD-(D/E)XK phosphodiesterase superfamily. Nucleic Acids Res. 40, 7016–7045 (2012).
Arcus, V. L., Mckenzie, J. L., Robson, J. & Cook, G. M. The PIN-domain ribonucleases and the prokaryotic VapBC toxin–antitoxin array. Protein Eng. Des. Sel. 24, 33–40 (2011).
Gabler, F. et al. Protein sequence analysis using the MPI bioinformatics toolkit. Curr. Protoc. Bioinformatics 72, e108 (2020).
Fernández-García, L. & Wood, T. K. Phage-defense systems are unlikely to cause cell suicide. Viruses 15, 1795 (2023).
Georjon, H. & Bernheim, A. The highly diverse antiphage defence systems of bacteria. Nat. Rev. Microbiol. 21, 686–700 (2023).
Aframian, N. & Eldar, A. Abortive infection antiphage defense systems: separating mechanism and phenotype. Trends Microbiol. 31, 1003–1012 (2023).
Fernández-García, L. et al. Toxin/antitoxin systems induce persistence and work in concert with restriction/modification systems to inhibit phage. Microbiol. Spectr. 12, e0338823 (2024).
Scherrer, R. & Moyed, H. S. Conditional impairment of cell division and altered lethality in hipA mutants of Escherichia coli K-12. J. Bacteriol. 170, 3321–3326 (1988).
Granato, E. T., Meiller-Legrand, T. A. & Foster, K. R. The evolution and ecology of bacterial warfare. Curr. Biol. 29, R521–R537 (2019).
Botelho, J. et al. Phylogroup-specific variation shapes the clustering of antimicrobial resistance genes and defence systems across regions of genome plasticity in Pseudomonas aeruginosa. eBioMedicine 90, 104532 (2023).
Salomon, D. MIX and match: mobile T6SS MIX-effectors enhance bacterial fitness. Mob. Genet. Elements 6, e1123796 (2016).
Kosek, D., Hickman, A. B., Ghirlando, R., He, S. & Dyda, F. Structures of ISCth4 transpososomes reveal the role of asymmetry in copy-out/paste-in DNA transposition. EMBO J. 40, e105666 (2021).
Chandler, M., Fayet, O., Rousseau, P., Hoang, B. T. & Duval-Valentin, G. in Mobile DNA III (eds Chandler, M. et al.) 591–607 (Wiley, 2015).
Patel, P. H. et al. Anti-phage defence through inhibition of virion assembly. Nat. Commun. 15, 1644 (2024).
Gibson, D. G. et al. Enzymatic assembly of DNA molecules up to several hundred kilobases. Nat. Methods 6, 343–345 (2009).
O’Toole, R., Milton, D. L. & Wolf-Watz, H. Chemotactic motility is required for invasion of the host by the fish pathogen Vibrio anguillarum. Mol. Microbiol. 19, 625–637 (1996).
Chung, H. S. & Raetz, C. R. H. Interchangeable domains in the Kdo transferases of Escherichia coli and Haemophilus influenzae. Biochemistry 49, 4126–4137 (2010).
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).
Dunn, A. K., Millikan, D. S., Adin, D. M., Bose, J. L. & Stabb, E. V. New rfp- and pES213-derived tools for analyzing symbiotic Vibrio fischeri reveal patterns of infection and lux expression in situ. Appl. Environ. Microbiol. 72, 802–810 (2006).
Cohen, D. et al. Cyclic GMP–AMP signalling protects bacteria against viral infection. Nature 574, 691–695 (2019).
Goren, M. G., Mahata, T. & Qimron, U. An efficient, scarless, selection-free technology for phage engineering. RNA Biol. 20, 830–835 (2023).
Wannier, T. M. et al. Improved bacterial recombineering by parallelized protein discovery. Proc. Natl Acad. Sci. USA 117, 13689–13698 (2020).
Nyerges, Á. et al. A highly precise and portable genome engineering method allows comparison of mutational effects across bacterial species. Proc. Natl Acad. Sci. USA 113, 2502–2507 (2016).
Sharan, S. K., Thomason, L. C., Kuznetsov, S. G. & Court, D. L. Recombineering: a homologous recombination-based method of genetic engineering. Nat. Protoc. 4, 206–223 (2009).
Yosef, I., Manor, M., Kiro, R. & Qimron, U. Temperate and lytic bacteriophages programmed to sensitize and kill antibiotic-resistant bacteria. Proc. Natl Acad. Sci. USA 112, 7267–7272 (2015).
Dar, Y., Jana, B., Bosis, E. & Salomon, D. A binary effector module secreted by a type VI secretion system. EMBO Rep. 23, e53981 (2022).
Fridman, C. M., Keppel, K., Gerlic, M., Bosis, E. & Salomon, D. A comparative genomics methodology reveals a widespread family of membrane-disrupting T6SS effectors. Nat. Commun. 11, 1085 (2020).
Brown, C. L. et al. mobileOG-db: a manually curated database of protein families mediating the life cycle of bacterial mobile genetic elements. Appl. Environ. Microbiol. 88, e0099122 (2022).
Liu, B., Zheng, D., Zhou, S., Chen, L. & Yang, J. VFDB 2022: a general classification scheme for bacterial virulence factors. Nucleic Acids Res. 50, D912–D917 (2022).
Wang, J. et al. BastionHub: a universal platform for integrating and analyzing substrates secreted by Gram-negative bacteria. Nucleic Acids Res. 49, D651–D659 (2021).
Katoh, K., Rozewicki, J. & Yamada, K. D. MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization. Brief. Bioinform. 20, 1160–1166 (2019).
Katoh, K., Misawa, K., Kuma, K. & Miyata, T. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res. 30, 3059–3066 (2002).
Saitou, N. & Nei, M. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 4, 406–425 (1987).
Madeira, F. et al. Search and sequence analysis tools services from EMBL-EBI in 2022. Nucleic Acids Res. 50, W276–W279 (2022).
Kumar, S., Stecher, G., Li, M., Knyaz, C. & Tamura, K. MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol. Biol. Evol. 35, 1547–1549 (2018).
Le, S. Q. & Gascuel, O. An improved general amino acid replacement matrix. Mol. Biol. Evol. 25, 1307–1320 (2008).
Letunic, I. & Bork, P. Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation. Nucleic Acids Res. 49, W293–W296 (2021).
Crooks, G. E., Hon, G., Chandonia, J.-M. & Brenner, S. E. WebLogo: a sequence logo generator. Genome Res. 14, 1188–1190 (2004).
Sievers, F. et al. Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol. Syst. Biol. 7, 539 (2011).
Robert, X. & Gouet, P. Deciphering key features in protein structures with the new ENDscript server. Nucleic Acids Res. 42, W320–W324 (2014).
Acknowledgements
We thank members of the Salomon, Qimron and Bosis laboratories for helpful discussions and suggestions; A. Endimiani (University of Bern) for gifting us the E. coli ZH142-A strain; and A. Harms (ETH Zurich) for generously sharing the BASEL phage collection. D.S. and E.B. received funding from the Israel Science Foundation (ISF grant number 1362/21). U.Q. was supported by the European Research Council – Horizon 2020 research and innovation programme, grant no. 818878. U.Q. also received funding from the Israeli Ministry of Health in the framework of the ERANET-JPI-AMR, grant no. 15370. K.K. was supported by a PhD scholarship from the Tel Aviv University Center for Combatting Pandemics.
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T.M., E.B., U.Q. and D.S. conceived the work; T.M., K.K., E.B., U.Q. and D.S. designed experiments; E.B. performed bioinformatic analysis and D.S. assisted in data interpretation; T.M. and K.K. carried out most of the experiments; M.G.G. generated mutant phages and identified escape phages; R.M.R. assisted in performing phage plaque assays; E.B., U.Q. and D.S. acquired the funding and supervised the work. E.B. and D.S. wrote the manuscript draft, and all authors edited and approved the paper.
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Extended data
Extended Data Fig. 1 Closely related GmtY proteins are found in diverse bacterial orders.
Phylogenetic distribution of GmtY proteins encoded within GMT islands for which an insertion site was identified. The bacterial order and the type of predicted GMT island insertion site are denoted. Blue bars denote the GMT island cargo length. The evolutionary history was inferred by using the Maximum Likelihood method and LG+G+I model. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. Evolutionary analyses were conducted in MEGA X.
Extended Data Fig. 2 GMT islands with a predicted intragenic insertion site contain a homolog of the disrupted gene.
Representative GMT islands (cyan rectangles) predicted to disrupt a gene upon insertion into the bacterial genome are shown above a predicted naïve insertion site in a closely related Vibrio strain. The disrupted and the homologous genes are denoted with the same color. Gray rectangles denote homologous regions. The amino acid identity percentage between the protein encoded by the gene in which the predicted naïve insertion site is found and the homolog within the GMT island are denoted in blue rectangles. The strain names and the RefSeq accession numbers are provided.
Extended Data Fig. 3. The insertion site spacer sequence is important to facilitate GMT island insertion.
(a) Agarose gel electrophoresis analysis of the indicated amplicons. The total DNA isolated from wild-type V. parahaemolyticus RIMD 2210633 cells conjugated with an empty plasmid (pEmpty), a plasmid containing a predicted 30 bp-long naïve insertion site for VPaI-6 (pNISVPaI-6), or a plasmid containing a mutated version of the insertion site in which the spacer between the inverted repeats was modified (pNISVPaI-6-Mut), was used as a template. Arrows denote the positions of primers used for each amplicon; the expected amplicon size is denoted in gray. cat, chloramphenicol resistance gene found on the plasmids. A representative result out of at least three independent experiments is shown. (b) The sequences of the natural VPaI-6 naïve insertion site (NISVPaI-6) and its mutated form (NISVPaI-6-Mut) used in (a).
Extended Data Fig. 4 The GMT island in V. parahaemolyticus 04.2548 is a functional mobile element.
(a) Schematic representation of the GMT island in V. parahaemolyticus 04.2548 (cyan rectangle). A predicted intragenic (tRNA-Gly), inverted repeat-containing (pink and purple-colored sequences) naïve insertion site identified in V. parahaemolyticus 20140829008-1 is shown below. Inverted repeat sequences flanking the GMT island are denoted. GenBank accession numbers are provided. (b) Agarose gel electrophoresis analysis of the indicated amplicons. The total DNA isolated from wild-type V. parahaemolyticus 04.2548 cells conjugated with an empty plasmid (pEmpty), a plasmid containing a predicted naïve insertion site for VPaI-6 (pNISVPaI-6), or a plasmid containing a predicted naïve insertion site for the 04.2548 GMT island (pNIS04.2548), was used as a template. Arrows denote the positions of primers used for each amplicon; the expected amplicon size is denoted in gray. cat, chloramphenicol resistance gene found on the plasmids. A representative result out of at least three independent experiments is shown.
Extended Data Fig. 5 GAPS1 homologues are widespread in bacteria.
Phylogenetic distribution of GAPS1 homologues. The bacterial order is denoted by color. Blue bars denote the number of genomes in which each protein accession was identified (Log10 scale). The evolutionary history was inferred by using the Maximum Likelihood method and LG+G+I+F model. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. Evolutionary analyses were conducted in MEGA X.
Extended Data Fig. 6 Closely positioned residues in the T7 phage capsid protein are mutated in GAPS1 escape mutants.
The position of glutamic acid 183 (yellow), isoleucine 217 (green), and valine 247 (magenta) in the solved structure of the T7 phage capsid protein Gp10 (PDB:3j7x chain G).
Extended Data Fig. 7 GAPS1 homologues in E. coli.
Multiple sequence alignment for the indicated protein sequences was performed with Clustal W using Mega X. Similarity (red letter) and identity (red background) shading were done in ESPript 3.0. The accession number of GAPS1 is WP_005477165.1.
Extended Data Fig. 8 A proposed model for GMT island replicative transfer.
A yet-unknown event or process leads to the excision and circularization of one of the GMT island strands without the flanking inverted repeat sequences; base pairing between the inverted repeat sequences may play a role in the process. A complementary strand is polymerized, resulting in a double-stranded circular form of the GMT island. The GMT system proteins, which are required for the excision and circularization, possibly remain bound to the junction between the ends of the GMT island and mediate recognition of a naïve insertion site containing a specific inverted repeat sequence. The naïve insertion site is cleaved within the spacer sequence found between the inverted repeats, and the GMT island is inserted into the recipient site. In parallel, the cell replaces the excised strand in the donor DNA using the remaining strand as a template. This process results in two identical GMT islands.
Extended Data Fig. 9 Identical GMT islands on the chromosome and on a plasmid have similar predicted insertion sites.
(a-b) The nucleotide sequences flanking identical GMT islands on the chromosome (a) and on a plasmid (b) in Vibrio alginolyticus, and their predicted naïve insertion sites (shown below). Inverted repeat sequences are denoted in blue and green; the conserved repeat core found in both predicted insertion sites is denoted in bold. Direct repeat sequences resulting from apparent spacer duplication upon GMT island insertion into the chromosomal site are denoted in pink and purple (a). Gray rectangles denote identical sequences. The strain names and the GenBank accession numbers are provided.
Extended Data Fig. 10 Identification of GMT islands.
(a) Criteria for the identification of genomic accessions in closely related genomes that are homologous to the sequences flanking the GMT system. Thick lines represent the alignments between query and subject accessions. (b) Sequences upstream and downstream of the GMT islands should contain sequence alignments to the subject accessions in at least 4 kbp out of 10 kbp upstream and downstream sequences. (c) Grouping of alignments meeting all the requirements to determine the 5′ and 3′ borders of GMT islands. (d) Intragenic and intergenic insertion sites. (e) Analysis of sequences surrounding a predicted insertion site to identify direct and inverted repeats. Bold letters denote an inverted repeat found within the sequence example.
Supplementary information
Supplementary Information
Supplementary Figs. 1 and 2 and references (for citations found in supplementary tables).
Supplementary Tables
Table 1: Mutations found in GAPS1 T7 phage escape mutants. Table 2: List of bacterial strains used in this study. Table 3: List of gene fragments that were commercially synthesized for this study. Table 4: List of plasmids used in this study. Table 5: List of primers used in this study. Table 6: List of bacteriophages used in this study.
Supplementary Data 1
List of GMT proteins and adjacently encoded proteins.
Supplementary Data 2
The borders of GMT islands found within complete genomes.
Supplementary Data 3
Anti-phage defence systems and antibacterial T6SS effectors identified in GMT island cargoes and the presence of a T6SS in these strains.
Supplementary Data 4
List of GAPS1 homologues.
Source data
Source Data Fig. 1
Unprocessed gels.
Source Data Fig. 2
Unprocessed gels.
Source Data Figs. 2–6
Graph and statistical source data for Figs. 2–6.
Source Data Extended Data Fig. 3
Unprocessed gels.
Source Data Extended Data Fig. 4
Unprocessed gels.
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Mahata, T., Kanarek, K., Goren, M.G. et al. Gamma-Mobile-Trio systems are mobile elements rich in bacterial defensive and offensive tools. Nat Microbiol 9, 3268–3283 (2024). https://doi.org/10.1038/s41564-024-01840-5
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DOI: https://doi.org/10.1038/s41564-024-01840-5
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