Letter

Interplay between microbial d-amino acids and host d-amino acid oxidase modifies murine mucosal defence and gut microbiota

  • Nature Microbiology 1, Article number: 16125 (2016)
  • doi:10.1038/nmicrobiol.2016.125
  • Download Citation
Received:
Accepted:
Published online:

Abstract

L-Amino acids are the building blocks for proteins synthesized in ribosomes in all kingdoms of life, but d-amino acids (d-aa) have important non-ribosome-based functions1. Mammals synthesize d-Ser and d-Asp, primarily in the central nervous system, where d-Ser is critical for neurotransmission2. Bacteria synthesize a largely distinct set of d-aa, which become integral components of the cell wall and are also released as free d-aa3,4. However, the impact of free microbial d-aa on host physiology at the host–microbial interface has not been explored. Here, we show that the mouse intestine is rich in free d-aa that are derived from the microbiota. Furthermore, the microbiota induces production of d-amino acid oxidase (DAO) by intestinal epithelial cells, including goblet cells, which secrete the enzyme into the lumen. Oxidative deamination of intestinal d-aa by DAO, which yields the antimicrobial product H2O2, protects the mucosal surface in the small intestine from the cholera pathogen. DAO also modifies the composition of the microbiota and is associated with microbial induction of intestinal sIgA. Collectively, these results identify d-aa and DAO as previously unrecognized mediators of microbe–host interplay and homeostasis on the epithelial surface of the small intestine.

  • Subscribe to Nature Microbiology for full access:

    $59

    Subscribe

Additional access options:

Already a subscriber?  Log in  now or  Register  for online access.

References

  1. 1.

    & Homochirality and life. Chem. Record 4, 267–278 (2004).

  2. 2.

    , , & D-amino acids in the brain: D-serine in neurotransmission and neurodegeneration. FEBS J. 275, 3514–3526 (2008).

  3. 3.

    et al. D-amino acids govern stationary phase cell wall remodeling in bacteria. Science 325, 1552–1555 (2009).

  4. 4.

    , , , & Distinct pathways for modification of the bacterial cell wall by non-canonical d-amino acids. EMBO J. 30, 3442–3453 (2011).

  5. 5.

    & Pattern recognition receptors and inflammation. Cell 140, 805–820 (2010).

  6. 6.

    & Innate immune recognition. Annu. Rev. Immunol. 20, 197–216 (2002).

  7. 7.

    , , , & Diversity, stability and resilience of the human gut microbiota. Nature 489, 220–230 (2012).

  8. 8.

    et al. Chiral amino acid analysis of Japanese traditional Kurozu and the developmental changes during earthenware jar fermentation processes. J. Chromatogr. B 966, 187–192 (2014).

  9. 9.

    , , , & D-amino acid metabolism in mammals: biosynthesis, degradation and analytical aspects of the metabolic study. J. Chromatogr. B 879, 3162–3168 (2011).

  10. 10.

    , , , & Physiological functions of d-amino acid oxidases: from yeast to humans. Cell. Mol. Life Sci. 64, 1373–1394 (2007).

  11. 11.

    et al. D-amino acid oxidase controls motoneuron degeneration through d-serine. Proc. Natl Acad. Sci. USA 109, 627–632 (2012).

  12. 12.

    , & Pathogen recognition and innate immunity. Cell 124, 783–801 (2006).

  13. 13.

    & Mouse mutant deficient in d-amino acid oxidase activity. Genetics 103, 277–285 (1983).

  14. 14.

    Role of oxygen gradients in shaping redox relationships between the human intestine and its microbiota. Free Rad. Biol. Med. 55, 130–140 (2013).

  15. 15.

    & Beyond oxidative stress: an immunologist's guide to reactive oxygen species. Nature Rev. Immunol. 13, 349–361 (2013).

  16. 16.

    et al. Structural basis for the broad specificity of a new family of amino-acid racemases. Acta Crystallogr. D 70, 79–90 (2014).

  17. 17.

    et al. Catalases promote resistance of oxidative stress in Vibrio cholerae. PLoS ONE 7, e53383 (2012).

  18. 18.

    , & Salmonella evades d-amino acid oxidase to promote infection in neutrophils. mBio 5, e01886-14 (2014).

  19. 19.

    , & Protective role of d-amino acid oxidase against Staphylococcus aureus infection. Infect. Immun. 80, 1546–1553 (2012).

  20. 20.

    , , & Roles of thioredoxin and thioredoxin reductase in the resistance to oxidative stress in Lactobacillus casei. Microbiology 158, 953–962 (2012).

  21. 21.

    et al. The genome sequence of the probiotic intestinal bacterium Lactobacillus johnsonii NCC 533. Proc. Natl Acad. Sci. USA 101, 2512–2517 (2004).

  22. 22.

    , , & L-alanine auxotrophy of Lactobacillus johnsonii as demonstrated by physiological, genomic, and gene complementation approaches. Appl. Environ. Microbiol. 70, 1869–1873 (2004).

  23. 23.

    et al. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nature Biotechnol. 31, 814–821 (2013).

  24. 24.

    et al. Metabolic reconstruction for metagenomic data and its application to the human microbiome. PLoS Comput. Biol. 8, e1002358 (2012).

  25. 25.

    Evolution, development, mechanism and function of IgA in the gut. Curr. Opin. Immunol. 20, 170–177 (2008).

  26. 26.

    et al. Immunoglobulin A coating identifies colitogenic bacteria in inflammatory bowel disease. Cell 158, 1000–1010 (2014).

  27. 27.

    et al. The antibacterial lectin RegIIIγ promotes the spatial segregation of microbiota and host in the intestine. Science 334, 255–258 (2011).

  28. 28.

    et al. Tryptophan catabolites from microbiota engage aryl hydrocarbon receptor and balance mucosal reactivity via interleukin-22. Immunity 39, 372–385 (2013).

  29. 29.

    et al. Metagenomic biomarker discovery and explanation. Genome Biol. 12, R60 (2011).

  30. 30.

    Isolation of a purified epithelial cell population from human colon. Methods Mol. Med. 50, 15–20 (2001).

  31. 31.

    et al. Simultaneous determination of hydrophilic amino acid enantiomers in mammalian tissues and physiological fluids applying a fully automated micro-two-dimensional high-performance liquid chromatographic concept. J. Chromatogr. A 1217, 1056–1062 (2010).

  32. 32.

    et al. DNA sequence of both chromosomes of the cholera pathogen Vibrio cholerae. Nature 406, 477–483 (2000).

  33. 33.

    & Construction of an eae deletion mutant of enteropathogenic Escherichia coli by using a positive-selection suicide vector. Infect. Immun. 59, 4310–4317 (1991).

  34. 34.

    et al. Extending the host range of Listeria monocytogenes by rational protein design. Cell 129, 891–902 (2007).

  35. 35.

    , , & Taxonomic study of the Lactobacillus acidophilus group, with recognition of Lactobacillus gallinarum sp. nov. and Lactobacillus johnsonii sp. nov. and synonymy of Lactobacillus acidophilus group A3 (Johnson et al. 1980) with the type strain of Lactobacillus amylovorus (Nakamura 1981). Int. J. System. Bacteriol. 42, 487–491 (1992).

  36. 36.

    et al. Genome sequence of enterohaemorrhagic Escherichia coli O157:H7. Nature 409, 529–533 (2001).

  37. 37.

    et al. Genome sequence of Vibrio parahaemolyticus: a pathogenic mechanism distinct from that of V. cholerae. Lancet 361, 743–749 (2003).

  38. 38.

    & Production of staphylococcal pyrogenic exotoxin type C: influence of physical and chemical factors. J. Infect. Dis. 147, 236–242 (1983).

  39. 39.

    , & Chromosomal genetics of Pseudomonas. Microbiol. Rev. 43, 73–102 (1979).

  40. 40.

    , , & Establishment of an adult mouse model for direct evaluation of the efficacy of vaccines against Vibrio cholerae. Infect. Immun. 77, 3475–3484 (2009).

  41. 41.

    , , & Vibrio cholerae intestinal population dynamics in the suckling mouse model of infection. Infect. Immun. 67, 3733–3739 (1999).

  42. 42.

    et al. Transitions in bacterial communities along the 2000 km salinity gradient of the Baltic Sea. ISME J. 5, 1571–1579 (2011).

  43. 43.

    et al. QIIME allows analysis of high-throughput community sequencing data. Nature Methods 7, 335–336 (2010).

  44. 44.

    et al. An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. ISME J. 6, 610–618 (2012).

  45. 45.

    et al. Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing. Nature Methods 10, 57–59 (2013).

Download references

Acknowledgements

The authors thank M. Nakane (Shiseido) for technical support with 2D-HPLC, L. Comstock for help with anaerobic cultures, R. Konno for providing DAOG181R mice, Waldor laboratory colleagues and M. Silverman for their comments on the manuscript, Q. Wang for help creating the ΔoxyR strain, L. Bry for germ-free mice, G. Abu-Ali/Huttenhower Group for assistance with LEfSe and 16S metagenomic analysis and S. Aiso for support. This work was supported by the Howard Hughes Medical Institute (M.K.W.), NIH grant no. R37 AI-042347 (M.K.W.) and the Moritani Scholarship Foundation (J.S.).

Author information

Affiliations

  1. Division of Infectious Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA

    • Jumpei Sasabe
    • , Ting Zhang
    • , Brigid M. Davis
    •  & Matthew K. Waldor
  2. Howard Hughes Medical Institute, Boston, Massachusetts 02115, USA

    • Jumpei Sasabe
    • , Ting Zhang
    • , Brigid M. Davis
    •  & Matthew K. Waldor
  3. Keio University School of Medicine, Shinjuku-ku, Tokyo 160-8582, Japan

    • Jumpei Sasabe
  4. Graduate School of Pharmaceutical Sciences, Kyushu University, Fukuoka 812-8582, Japan

    • Yurika Miyoshi
    •  & Kenji Hamase
  5. Division of Infectious Diseases, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA

    • Seth Rakoff-Nahoum
  6. Shiseido Co., Ltd, Minato-ku, Tokyo 105-0021, Japan

    • Masashi Mita

Authors

  1. Search for Jumpei Sasabe in:

  2. Search for Yurika Miyoshi in:

  3. Search for Seth Rakoff-Nahoum in:

  4. Search for Ting Zhang in:

  5. Search for Masashi Mita in:

  6. Search for Brigid M. Davis in:

  7. Search for Kenji Hamase in:

  8. Search for Matthew K. Waldor in:

Contributions

J.S. and M.K.W. conceived and designed the study. J.S. carried out histological experiments, biochemical analyses, microbiological studies, sequence analyses, animal experiments with T.Z., and figure preparation. Y.M. and K.H. performed HPLC quantifications of chiral amino acids with technical support by M.M. S.R.-N. and B.M.D. provided scientific advice. M.K.W. supervised the experiments and directed the analysis. J.S., S.R.-N., B.M.D. and M.K.W. wrote the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Matthew K. Waldor.

Supplementary information

PDF files

  1. 1.

    Supplementary information

    Supplementary Methods, Supplementary Figures 1–13, Supplementary References