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Human gut bacteria contain acquired interbacterial defence systems

Abstract

The human gastrointestinal tract consists of a dense and diverse microbial community, the composition of which is intimately linked to health. Extrinsic factors such as diet and host immunity are insufficient to explain the constituents of this community, and direct interactions between co-resident microorganisms have been implicated as important drivers of microbiome composition. The genomes of bacteria derived from the gut microbiome contain several pathways that mediate contact-dependent interbacterial antagonism1,2,3. Many members of the Gram-negative order Bacteroidales encode the type VI secretion system (T6SS), which facilitates the delivery of toxic effector proteins into adjacent cells4,5. Here we report the occurrence of acquired interbacterial defence (AID) gene clusters in Bacteroidales species that reside within the human gut microbiome. These clusters encode arrays of immunity genes that protect against T6SS-mediated intra- and inter-species bacterial antagonism. Moreover, the clusters reside on mobile elements, and we show that their transfer is sufficient to confer resistance to toxins in vitro and in gnotobiotic mice. Finally, we identify and validate the protective capability of a recombinase-associated AID subtype (rAID-1) that is present broadly in Bacteroidales genomes. These rAID-1 gene clusters have a structure suggestive of active gene acquisition and include predicted immunity factors of toxins derived from diverse organisms. Our data suggest that neutralization of contact-dependent interbacterial antagonism by AID systems helps to shape human gut microbiome ecology.

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Fig. 1: T6SS orphan immunity genes are found in human gut microbiomes.
Fig. 2: T6SS orphan immunity gene clusters are encoded by several species in the human gut microbiome.
Fig. 3: Orphan immunity genes are mobile and protect against T6S-delivered toxins.
Fig. 4: rAID systems encode toxin-neutralizing immunity genes and are prevalent in human gut microbiomes.

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Data availability

All data required to assess the conclusion of this research are available in the main text and Supplementary Information, have been deposited at the Sequence Read Archive (SRA) under BioProject accession PRJNA484981 or are available from https://github.com/borenstein-lab/T6SS).

Code availability

Python and R scripts used in this work are available for download (https://github.com/borenstein-lab/T6SS).

References

  1. Whitney, J. C. et al. A broadly distributed toxin family mediates contact-dependent antagonism between Gram-positive bacteria. eLife 6, e26938 (2017).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  2. Zhang, D., de Souza, R. F., Anantharaman, V., Iyer, L. M. & Aravind, L. Polymorphic toxin systems: comprehensive characterization of trafficking modes, processing, mechanisms of action, immunity and ecology using comparative genomics. Biol. Direct 7, 18 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Coyne, M. J., Roelofs, K. G. & Comstock, L. E. Type VI secretion systems of human gut Bacteroidales segregate into three genetic architectures, two of which are contained on mobile genetic elements. BMC Genomics 17, 58 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  4. Russell, A. B. et al. A type VI secretion-related pathway in Bacteroidetes mediates interbacterial antagonism. Cell Host Microbe 16, 227–236 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Cornforth, D. M. & Foster, K. R. Competition sensing: the social side of bacterial stress responses. Nat. Rev. Microbiol. 11, 285–293 (2013).

    Article  CAS  PubMed  Google Scholar 

  7. Hille, F. et al. The biology of CRISPR–Cas: backward and forward. Cell 172, 1239–1259 (2018).

    Article  CAS  PubMed  Google Scholar 

  8. 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 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Wexler, A. G. et al. Human symbionts inject and neutralize antibacterial toxins to persist in the gut. Proc. Natl Acad. Sci. USA 113, 3639–3644 (2016).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  10. Hecht, A. L. et al. Strain competition restricts colonization of an enteric pathogen and prevents colitis. EMBO Rep. 17, 1281–1291 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Kirchberger, P. C., Unterweger, D., Provenzano, D., Pukatzki, S. & Boucher, Y. Sequential displacement of type VI secretion system effector genes leads to evolution of diverse immunity gene arrays in Vibrio cholerae. Sci. Rep. 7, 45133 (2017).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  12. Steele, M. I., Kwong, W. K., Whiteley, M. & Moran, N. A. Diversification of type VI secretion system toxins reveals ancient antagonism among bee gut microbes. mBio 8, e26938 (2017).

    Article  Google Scholar 

  13. Ting, S. Y. et al. Bifunctional immunity proteins protect bacteria against Ftsz-targeting ADP-ribosylating toxins. Cell 175, 1380–1392 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Lloyd-Price, J. et al. Strains, functions and dynamics in the expanded Human Microbiome Project. Nature 550, 61–66 (2017).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  15. Qin, J. et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464, 59–65 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Manor, O. et al. Metagenomic evidence for taxonomic dysbiosis and functional imbalance in the gastrointestinal tracts of children with cystic fibrosis. Sci. Rep. 6, 22493 (2016).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  17. Siguier, P., Gourbeyre, E. & Chandler, M. Bacterial insertion sequences: their genomic impact and diversity. FEMS Microbiol. Rev. 38, 865–891 (2014).

    Article  CAS  PubMed  Google Scholar 

  18. Zhao, S. et al. Adaptive evolution within gut microbiomes of healthy people. Cell Host Microbe 25, 656–667.e8 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Wozniak, R. A. & Waldor, M. K. Integrative and conjugative elements: mosaic mobile genetic elements enabling dynamic lateral gene flow. Nat. Rev. Microbiol. 8, 552–563 (2010).

    Article  CAS  PubMed  Google Scholar 

  20. Stevens, A. M., Shoemaker, N. B. & Salyers, A. A. The region of a Bacteroides conjugal chromosomal tetracycline resistance element which is responsible for production of plasmidlike forms from unlinked chromosomal DNA might also be involved in transfer of the element. J. Bacteriol. 172, 4271–4279 (1990).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Castillo, F., Benmohamed, A. & Szatmari, G. Xer site specific recombination: double and single recombinase systems. Front. Microbiol. 8, 453 (2017).

    PubMed  PubMed Central  Google Scholar 

  22. Abu-Ali, G. S. et al. Metatranscriptome of human faecal microbial communities in a cohort of adult men. Nat. Microbiol. 3, 356–366 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Foster, K. R. & Bell, T. Competition, not cooperation, dominates interactions among culturable microbial species. Curr. Biol. 22, 1845–1850 (2012).

    Article  CAS  PubMed  Google Scholar 

  24. Poole, S. J. et al. Identification of functional toxin/immunity genes linked to contact-dependent growth inhibition (CDI) and rearrangement hotspot (Rhs) systems. PLoS Genet. 7, e1002217 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Drider, D., Fimland, G., Héchard, Y., McMullen, L. M. & Prévost, H. The continuing story of class IIa bacteriocins. Microbiol. Mol. Biol. Rev. 70, 564–582 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Coyte, K. Z., Schluter, J. & Foster, K. R. The ecology of the microbiome: networks, competition, and stability. Science 350, 663–666 (2015).

    Article  ADS  CAS  PubMed  Google Scholar 

  27. Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature 486, 207–214 (2012).

    Article  ADS  CAS  Google Scholar 

  28. Qin, J. et al. A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature 490, 55–60 (2012).

    Article  ADS  CAS  PubMed  Google Scholar 

  29. Li, J. et al. An integrated catalog of reference genes in the human gut microbiome. Nat. Biotechnol. 32, 834–841 (2014).

    Article  CAS  PubMed  Google Scholar 

  30. Truong, D. T. et al. MetaPhlAn2 for enhanced metagenomic taxonomic profiling. Nat. Methods 12, 902–903 (2015).

    Article  CAS  PubMed  Google Scholar 

  31. Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Luo, R. et al. SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. Gigascience 1, 18 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Besemer, J., Lomsadze, A. & Borodovsky, M. GeneMarkS: a self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions. Nucleic Acids Res. 29, 2607–2618 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Bacic, M. K. & Smith, C. J. Laboratory maintenance and cultivation of bacteroides species. Curr. Protoc. Microbiol. 9, 13C.1.1–13C.1.21 (2008).

    PubMed  Google Scholar 

  36. Koropatkin, N. M., Martens, E. C., Gordon, J. I. & Smith, T. J. Starch catabolism by a prominent human gut symbiont is directed by the recognition of amylose helices. Structure 16, 1105–1115 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Degnan, P. H., Barry, N. A., Mok, K. C., Taga, M. E. & Goodman, A. L. Human gut microbes use multiple transporters to distinguish vitamin B12 analogs and compete in the gut. Cell Host Microbe 15, 47–57 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Hoffman, L. R. et al. Escherichia coli dysbiosis correlates with gastrointestinal dysfunction in children with cystic fibrosis. Clin. Infect. Dis. 58, 396–399 (2014).

    Article  PubMed  Google Scholar 

  39. Wick, R. R., Judd, L. M., Gorrie, C. L. & Holt, K. E. Unicycler: resolving bacterial genome assemblies from short and long sequencing reads. PLOS Comput. Biol. 13, e1005595 (2017).

    Article  ADS  PubMed  PubMed Central  CAS  Google Scholar 

  40. Martens, E. C., Chiang, H. C. & Gordon, J. I. Mucosal glycan foraging enhances fitness and transmission of a saccharolytic human gut bacterial symbiont. Cell Host Microbe 4, 447–457 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. García-Bayona, L. & Comstock, L. E. Bacterial antagonism in host-associated microbial communities. Science 361, eaat2456 (2018).

    Article  PubMed  CAS  Google Scholar 

  42. Lim, B., Zimmermann, M., Barry, N. A. & Goodman, A. L. Engineered regulatory systems modulate gene expression of human commensals in the gut. Cell 169, 547–558 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Paik, J. et al. Potential for using a hermetically-sealed, positive-pressured isocage system for studies involving germ-free mice outside a flexible-film isolator. Gut Microbes 6, 255–265 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Bailey, T. L. et al. MEME SUITE: tools for motif discovery and searching. Nucleic Acids Res. 37, W202–W208 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Silverman, J. M. et al. Haemolysin coregulated protein is an exported receptor and chaperone of type VI secretion substrates. Mol. Cell 51, 584–593 (2013).

    Article  CAS  PubMed  Google Scholar 

  46. Cardona, S. T. & Valvano, M. A. An expression vector containing a rhamnose-inducible promoter provides tightly regulated gene expression in Burkholderia cenocepacia. Plasmid 54, 219–228 (2005).

    Article  CAS  PubMed  Google Scholar 

  47. Bookout, A. L., Cummins, C. L., Mangelsdorf, D. J., Pesola, J. M. & Kramer, M. F. High-throughput real-time quantitative reverse transcription PCR. Curr. Protoc. Mol. Biol. 73, 15.8.1–15.8.28 (2006).

    PubMed  Google Scholar 

  48. Caro-Quintero, A. & Ochman, H. Assessing the unseen bacterial diversity in microbial communities. Genome Biol. Evol. 7, 3416–3425 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank the UW GNAC for assistance with gnotobiotic experiments. We thank C. Sears, A. Goodman, T. Kuwahara and E. Martens for providing Bacteroides strains. This work was supported by National Institutes of Health (NIH) grants AI080609 (to J.D.M.), P30DK089507 (to L.R.H. as pilot study PI), R01DK095869 (to L.R.H.), K99GM129874 (to B.D.R.), R01GM124312 (to E.B.), and New Innovator Award DP2AT00780201 (to E.B.), and the Burroughs Wellcome Fund (to J.D.M.). A.J.V. was supported by a postdoctoral fellowship from the Natural Sciences and Engineering Research Council of Canada. B.D.R. was supported by a Simons Foundation-sponsored Life Sciences Research Foundation postdoctoral fellowship. E.B. is a Faculty Fellow of the Edmond J. Safra Center for Bioinformatics at Tel Aviv University. J.D.M. is an HHMI Investigator.

Author information

Authors and Affiliations

Authors

Contributions

B.D.R., A.J.V., A.M.H., S.B.P., E.B. and J.D.M. designed the study. B.D.R. and D.T.S. performed in vitro growth experiments; A.J.V., B.D.R. and M.C.R. performed bioinformatic analyses; B.D.R., C.E.P. and L.R.H. isolated and sequenced genomes of gut bacteria; B.D.R., D.T.S., A.M.H. and S.B.P. performed gnotobiotic mouse experiments; B.D.R., A.J.V., M.C.R., D.T.S., A.M.H., S.B.P., E.B. and J.D.M. analysed data; and B.D.R., A.J.V., S.B.P., E.B. and J.D.M. wrote the manuscript.

Corresponding authors

Correspondence to Elhanan Borenstein or Joseph D. Mougous.

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The authors declare no competing interests.

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Peer review information Nature thanks Melanie Blokesch, Kevin Foster and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Extended data figures and tables

Extended Data Fig. 1 Prevalence of B. fragilis-specific orphan immunity genes in adult and infant microbiomes.

a, Number of adult human gut microbiome samples in which the indicated immunity genes (1–14, GA3_i1–14 from ref. 8) can be detected at an 80% nucleotide identity threshold and an abundance more than tenfold that of B. fragilis marker genes. Bars coloured as in Fig. 1a, and asterisks indicate immunity genes without orphan representation. b, Comparison of abundance of B. fragilis-specific T6SS immunity genes with B. fragilis species-specific marker genes in infant microbiome samples16 (Supplementary Table 4). Abundances are calculated as in Fig. 1a. Samples in which immunity gene abundance exceeds that of Bacteroides by over tenfold (blue) are highlighted.

Extended Data Fig. 2 Diversity and genomic context of orphan immunity genes in human gut microbiomes and diverse Bacteroides species.

a, Representative AID-1 gene clusters containing homologues of the indicated B. fragilis T6S immunity genes from the indicated reference genomes. b, Data points indicate the amino acid identity of unique genes homologous to indicated B. fragilis-specific T6SS cognate immunity genes identified through BLAST analysis of the IGC29 (n = 88 genes, maximum E = 1 × 10−40; minimum percentage identity, 60%).

Extended Data Fig. 3 Orphan immunity genes specifically enhance the fitness of Bacteroides strains in vitro and in vivo.

a, b, T6SS-dependent competitiveness of parental strains of B. ovatus 3725 and the indicated mutant and complemented derivatives during in vitro growth competition experiments with B. fragilis 9343. Relative recipient fitness was determined by calculating the ratio of final to initial c.f.u. and normalizing to the corresponding experiment with B. fragilis 9343 lacking tssC (T6S-inactive). Data are mean ± s.d. of three independent biological replicates. *P < 0.01, unpaired two-tailed t-test. c, T6SS-dependent competitiveness of a parental strain of B. ovatus 3725 or a strain bearing in-frame deletions of indicated orphan immunity genes, during in vitro growth competition experiments with an orthogonal effector-bearing B. fragilis 638R parental strain or a derivative strain lacking tssC (T6S-inactive). Relative recipient fitness and statistics were calculated as in a and b. n = 3 independent biological replicates. d, e, Recovery of B. fragilis 9343 (d) or 638R (e) and the indicated orphan immunity mutant derivative from pairwise competitions of the strains in germ-free mice. Lines indicate the mean at each time point (n = 8 mice per group for each of two independent experiments). Alternating time points of these data are included in ratio form in Fig. 3c. f, Schematic depicting genomic loci for the B. fragilis ATCC 43859 parental strain, the B. fragilis 638R AID-1 donor strain, the AID-1 system, and the ATCC 43859 AID-1 recipient. Grey shading indicates homology; red arrows indicate the position of PCR primers used to infer insertion of the AID-1 element at the tRNALys insertion site. g, Abundance of B. ovatus in samples lacking detected orphan immunity genes (−) and samples in which the indicated orphan immunity genes were assigned to B. ovatus (+). Abundances are calculated as in Fig. 1a. *P < 0.001, Wilcoxon rank-sum test. n = 128 non-orphan samples, n = 24 samples containing orphan immunity. For box plots, the middle line denotes the median; the box denotes the interquartile range (IQR); and the whiskers denote 1.5× the IQR.

Source data

Extended Data Fig. 4 The GA2 system of Bacteroidales mediates interbacterial antagonism.

Recovery of Bacteroides dorei DSM 17855 cells lacking GA2_e14-i14 (BACDOR_RS22955-17020) from two-strain in vitro growth competition experiments with the indicated donor strains. n = 3 technical replicates representative of three biological replicates. **P < 0.01, unpaired two-tailed t-test.

Source data

Extended Data Fig. 5 rAID-1 systems include conserved and repetitive intergenic sequences and bear hallmarks of horizontal gene transfer.

a, Left, motif enrichment analysis from the intergenic sequences immediately 3′ of the recombinase stop codon to the start codon of the first downstream open reading frame within 16 randomly selected rAID-1 gene clusters. This region is highlighted in blue in three representative rAID-1 systems shown above. Right, motif enrichment analysis from all 86 intergenic sequences between the ORFs of six rAID-1 clusters (B. fragilis NCTC 9343, B. cellulosilyticus WH2, B. ovatus 3725, Paraprevotella clara YIT 11840, Parabacteroides goldsteinii dnLKV18, and Parabacteroides gordonii MS-1)44. This region is highlighted in red in three representative rAID-1 systems shown above. b, Average G + C nucleotide content of rAID-1-associated recombinase versus rAID-1 predicted ORFs (n = 226). ***P < 0.0001, unpaired two-tailed t-test. c, Schematic depicting the G + C and A + T nucleotide content across a representative rAID-1 system from B. fragilis 9343. d, Frequency distribution of gene number in rAID-1 clusters (n = 1,247 genes in 226 clusters). Bin width is five genes. e, Composition of genes in rAID-1 clusters (n = 226 clusters) as determined by profile HMM scans and BLAST analysis against a curated database of Bacteroidales T6SS immunity genes2,8. f, Comparison of the total abundances of rAID-1-associated predicted recombinases and the Bacteroides genus in adult microbiome samples derived from the HMP and MetaHIT studies (Supplementary Table 8). Abundance values are calculated as in Fig. 1; genus abundance corresponds to the sum of all Bacteroides spp. (calculated individually as the average of species-specific marker gene abundances). g, Results of qRT–PCR analyses for the indicated B. ovatus 3725 genes belonging to AID-1 (i6, M088_1971) or AID-1 clusters (Rec, recombinase, M088_1401; orf1, M088_1400) under conditions of growth in mono- or co-culture with B. fragilis 9343 for 2 h. Data are mean ± s.d. of three independent biological replicates. *P < 0.05, **P < 0.01, Wilcoxon two-tailed sign-rank test.

Source data

Supplementary information

Supplementary Figure 1

Source data (unedited gel images) associated with Fig. 3

Reporting Summary

Supplementary Table 1

Metagenomic results derived from the HMP and MetaHIT studies utilized in this study.

Supplementary Table 2

List of Bacteroidales T6SS cognate immunity genes.

Supplementary Table 3

Accession numbers and abbreviations of relevant Bacteroides strains.

Supplementary Table 4

Metagenomic results derived from infant stool samples utilized in this study.

Supplementary Table 5

Description of AID gene clusters in genomes depicted in Fig. 2.

Supplementary Table 6

Description of rAID-1 gene clusters depicted in Fig. 4.

Supplementary Table 7

Features associated with rAID-1 gene clusters in Bacteroidales genomes.

Supplementary Table 8

Metagenomic results of rAID-1 genes derived from the HMP and MetaHit studies utilized in this study.

Supplementary Table 9

Metagenomic and metatranscriptomic results from analysis of rAID-1 genes from ref. 19.

Supplementary Table 10

Strains, plasmids and primers used in this study.

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Ross, B.D., Verster, A.J., Radey, M.C. et al. Human gut bacteria contain acquired interbacterial defence systems. Nature 575, 224–228 (2019). https://doi.org/10.1038/s41586-019-1708-z

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