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Gut-inhabiting Clostridia build human GPCR ligands by conjugating neurotransmitters with diet- and human-derived fatty acids

Nature Microbiology volume 6, pages 792–805 (2021)Cite this article

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A Publisher Correction to this article was published on 22 April 2021

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Abstract

Human physiology is regulated by endogenous signalling compounds, including fatty acid amides (FAAs), chemical mimics of which are made by bacteria. The molecules produced by human-associated microbes are difficult to identify because they may only be made in a local niche or they require a substrate sourced from the host, diet or other microbes. We identified a set of uncharacterized gene clusters in metagenomics data from the human gut microbiome. These clusters were discovered to make FAAs by fusing exogenous fatty acids with amines. Using an in vitro assay, we tested their ability to incorporate 25 fatty acids and 53 amines known to be present in the human gut, from which the production of six FAAs was deduced (oleoyl dopamine, oleoyl tyramine, lauroyl tryptamine, oleoyl aminovaleric acid, α-linolenoyl phenylethylamine and caproyl tryptamine). These molecules were screened against panels of human G-protein-coupled receptors to deduce their putative human targets. Lauroyl tryptamine is found to be an antagonist to the immunomodulatory receptor EBI2 against its native oxysterol ligand (0.98 μM half-maximal inhibitory concentration), is produced in culture by Eubacterium rectale and is present in human faecal samples. FAAs produced by Clostridia may serve as a mechanism to modulate their host by mimicking human signalling molecules.

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Fig. 1: Mining Clostridia pathways from the human gut metagenome.
Fig. 2: The pathways from Clostridia produce FAAs.
Fig. 3: Enzyme activity against fatty acids and amines present in the human gut.
Fig. 4: Lauroyl tryptamine is an EBI2 antagonist that is present in human faecal material.

Data availability

Genomic data used in this study are available in JGI (https://gold.jgi.doe.gov/) and NCBI (https://www.ncbi.nlm.nih.gov/) with identifiers listed in Supplementary Data 1. The FAA pathways found in this study are available in NCBI with identifiers listed in Supplementary Table 2. HMP faecal metagenomic data used in this study are available in NCBI with identifiers listed in Supplementary Table 7. HMP faecal metatranscriptomic data used in this study are available in NCBI with identifiers listed in Supplementary Table 8. BIO-ML OpenBiome Project untargeted metabolomics data used in this study are available in the Metabolomics Workbench (https://www.metabolomicsworkbench.org) under Project ID PR000804. Data supporting the findings of this study are available within the paper, supplementary materials and Source data are provided with this paper. Additional data are available from the corresponding author upon reasonable request. All strains and plasmids are available upon request.

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References

  1. Wilson, M. R., Zha, L. & Balskus, E. P. Natural product discovery from the human microbiome. J. Biol. Chem. 292, 8546–8552 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Lee, W. J. & Hase, K. Gut microbiota-generated metabolites in animal health and disease. Nat. Chem. Biol. 10, 416–424 (2014).

    Article  CAS  PubMed  Google Scholar 

  3. Donia, M. S. & Fischbach, M. A. Small molecules from the human microbiota. Science 349, 1254766 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Sharon, G. et al. Specialized metabolites from the microbiome in health and disease. Cell Metab. 20, 719–730 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Chen, H. et al. A forward chemical genetic screen reveals gut microbiota metabolites that modulate host physiology. Cell https://doi.org/10.1016/j.cell.2019.03.036 (2019)

  6. Wang, Z. et al. Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease. Nature 472, 57–63 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Ridlon, J. M., Kang, D. J. & Hylemon, P. B. Bile salt biotransformations by human intestinal bacteria. J. Lipid Res. 47, 241–259 (2006).

    Article  CAS  PubMed  Google Scholar 

  8. Guo, C. J. et al. Discovery of reactive microbiota-derived metabolites that inhibit host proteases. Cell 168, 517–526 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Wieland Brown, L. C. et al. Production of ɑ-galactosylceramide by a prominent member of the human gut microbiota. PLoS Biol. 11, e1001610 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Ozaki, H. et al. Molecular structure of the toxin domain of heat-stable enterotoxin produced by a pathogenic strain of Escherichia coli. A putative binding site for a binding protein on rat intestinal epithelial cell membranes. J. Biol. Chem. 266, 5934–5941 (1991).

    Article  CAS  PubMed  Google Scholar 

  11. Round, J. L. et al. The Toll-like receptor 2 pathway establishes colonization by a commensal of the human microbiota. Science 332, 974–977 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Cohen, L. J. et al. Functional metagenomic discovery of bacterial effectors in the human microbiome and isolation of commendamide, a GPCR G2A/132 agonist. Proc. Natl Acad. Sci. USA 112, E4825–E4834 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Cohen, L. J. et al. Commensal bacteria make GPCR ligands that mimic human signalling molecules. Nature 549, 48–53 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Donia, M. S. et al. A systematic analysis of biosynthetic gene clusters in the human microbiome reveals a common family of antibiotics. Cell 158, 1402–1414 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Blin, K. et al. antiSMASH 4.0—improvements in chemistry prediction and gene cluster boundary identification. Nucleic Acids Res. 45, W36–W41 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Magnusdottir, S. & Thiele, I. Modeling metabolism of the human gut microbiome. Curr. Opin. Biotechnol. 51, 90–96 (2018).

    Article  CAS  PubMed  Google Scholar 

  17. Sonnenburg, J. L. & Backhed, F. Diet–microbiota interactions as moderators of human metabolism. Nature 535, 56–64 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Brotherton, C. A. & Balskus, E. P. A prodrug resistance mechanism is involved in colibactin biosynthesis and cytotoxicity. J. Am. Chem. Soc. 135, 3359–3362 (2013).

    Article  CAS  PubMed  Google Scholar 

  19. Arafat, E. S., Trimble, J. W., Andersen, R. N., Dass, C. & Desiderio, D. M. Identification of fatty acid amides in human plasma. Life Sci. 45, 1679–1687 (1989).

    Article  CAS  PubMed  Google Scholar 

  20. Ezzili, C., Otrubova, K. & Boger, D. L. Fatty acid amide signaling molecules. Bioorg. Med. Chem. Lett. 20, 5959–5968 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Devane, W. A. et al. Isolation and structure of a brain constituent that binds to the cannabinoid receptor. Science 258, 1946–1949 (1992).

    Article  CAS  PubMed  Google Scholar 

  22. Eisenstein, T. K., Meissler, J. J., Wilson, Q., Gaughan, J. P. & Adler, M. W. Anandamide and δ9-tetrahydrocannabinol directly inhibit cells of the immune system via CB2 receptors. J. Neuroimmunol. 189, 17–22 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Osei-Hyiaman, D. et al. Endocannabinoid activation at hepatic CB1 receptors stimulates fatty acid synthesis and contributes to diet-induced obesity. J. Clin. Investig. 115, 1298–1305 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Caterina, M. J. et al. The capsaicin receptor: a heat-activated ion channel in the pain pathway. Nature 389, 816–824 (1997).

    Article  CAS  PubMed  Google Scholar 

  25. Chu, C. J. et al. N-oleoyldopamine, a novel endogenous capsaicin-like lipid that produces hyperalgesia. J. Biol. Chem. 278, 13633–13639 (2003).

    Article  CAS  PubMed  Google Scholar 

  26. Przegalinski, E., Filip, M., Zajac, D. & Pokorski, M. N-oleoyl-dopamine increases locomotor activity in the rat. Int. J. Immunopathol. Pharmacol. 19, 897–904 (2006).

    Article  CAS  PubMed  Google Scholar 

  27. Chu, Z. L. et al. N-oleoyldopamine enhances glucose homeostasis through the activation of GPR119. Mol. Endocrinol. 24, 161–170 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Ross, H. R., Gilmore, A. J. & Connor, M. Inhibition of human recombinant T-type calcium channels by the endocannabinoid N-arachidonoyl dopamine. Br. J. Pharmacol. 156, 740–750 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Sergeeva, O. A. et al. N-oleoyldopamine modulates activity of midbrain dopaminergic neurons through multiple mechanisms. Neuropharmacology 119, 111–122 (2017).

    Article  CAS  PubMed  Google Scholar 

  30. Raboune, S. et al. Novel endogenous N-acyl amides activate TRPV1-4 receptors, BV-2 microglia, and are regulated in brain in an acute model of inflammation. Front. Cell. Neurosci. 8, 195 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Huang, S. M. et al. Identification of a new class of molecules, the arachidonyl amino acids, and characterization of one member that inhibits pain. J. Biol. Chem. 276, 42639–42644 (2001).

    Article  CAS  PubMed  Google Scholar 

  32. Oh, D. Y. et al. Identification of farnesyl pyrophosphate and N-arachidonylglycine as endogenous ligands for GPR92. J. Biol. Chem. 283, 21054–21064 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Sasso, O. et al. Endogenous N-acyl taurines regulate skin wound healing. Proc. Natl Acad. Sci. USA 113, E4397–E4406 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Hannedouche, S. & Roy, M. Ligand for G-protein coupled receptor GPR72 and uses thereof. US patent US7824866B2 (2008).

  35. Milman, G. et al. N-arachidonoyl l-serine, an endocannabinoid-like brain constituent with vasodilatory properties. Proc. Natl Acad. Sci. USA 103, 2428–2433 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Zhang, X., Maor, Y., Wang, J. F., Kunos, G. & Groopman, J. E. Endocannabinoid-like N-arachidonoyl serine is a novel pro-angiogenic mediator. Br. J. Pharmacol. 160, 1583–1594 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Camilleri, M. Review article: tegaserod. Aliment. Pharmacol. Ther. 15, 277–289 (2001).

    Article  CAS  PubMed  Google Scholar 

  38. Farrell, E. K. & Merkler, D. J. Biosynthesis, degradation and pharmacological importance of the fatty acid amides. Drug Discov. Today 13, 558–568 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Sussmuth, R. D. & Mainz, A. Nonribosomal peptide synthesis—principles and prospects. Angew. Chem. 56, 3770–3821 (2017).

    Article  Google Scholar 

  40. Raymond, K. N., Dertz, E. A. & Kim, S. S. Enterobactin: an archetype for microbial iron transport. Proc. Natl Acad. Sci. USA 100, 3584–3588 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Schneditz, G. et al. Enterotoxicity of a nonribosomal peptide causes antibiotic-associated colitis. Proc. Natl Acad. Sci. USA 111, 13181–13186 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Fischbach, M. A. & Walsh, C. T. Assembly-line enzymology for polyketide and nonribosomal peptide antibiotics: logic, machinery, and mechanisms. Chem. Rev. 106, 3468–3496 (2006).

    Article  CAS  PubMed  Google Scholar 

  43. Roche, E. D. & Walsh, C. T. Dissection of the EntF condensation domain boundary and active site residues in nonribosomal peptide synthesis. Biochemistry 42, 1334–1344 (2003).

    Article  CAS  PubMed  Google Scholar 

  44. Mori, S. et al. Activation and loading of the starter unit during thiocoraline biosynthesis. Biochemistry 56, 4457–4467 (2017).

    Article  CAS  PubMed  Google Scholar 

  45. Sun, S. & Liu, C. 7ɑ,25-dihydroxycholesterol-mediated activation of EBI2 in immune regulation and diseases. Front. Pharmacol. 6, 60 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Willinger, T. Oxysterols in intestinal immunity and inflammation. J. Intern. Med. 285, 367–380 (2019).

    Article  CAS  PubMed  Google Scholar 

  47. Weber, T. et al. antiSMASH 3.0—a comprehensive resource for the genome mining of biosynthetic gene clusters. Nucleic Acids Res. 43, W237–W243 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

  49. Franzosa, E. A. et al. Relating the metatranscriptome and metagenome of the human gut. Proc. Natl Acad. Sci. USA 111, E2329–E2338 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Navarro-Muñoz, J. et al. A computational framework to explore large-scale biosynthetic diversity. Nat. Chem. Biol. 16, 60–68 (2020).

    Article  PubMed  Google Scholar 

  51. Mazmanian, S. K., Round, J. L. & Kasper, D. L. A microbial symbiosis factor prevents intestinal inflammatory disease. Nature 453, 620–625 (2008).

    Article  CAS  PubMed  Google Scholar 

  52. Almeida, A. et al. A new genomic blueprint of the human gut microbiota. Nature 568, 499–504 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Nayfach, S., Fischbach, M. A. & Pollard, K. S. MetaQuery: a web server for rapid annotation and quantitative analysis of specific genes in the human gut microbiome. Bioinformatics 31, 3368–3370 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Rausch, C., Hoof, I., Weber, T., Wohlleben, W. & Huson, D. H. Phylogenetic analysis of condensation domains in NRPS sheds light on their functional evolution. BMC Evol. Biol. 7, 78 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  55. Keating, T. A., Marshall, C. G. & Walsh, C. T. Vibriobactin biosynthesis in Vibrio cholerae: VibH is an amide synthase homologous to nonribosomal peptide synthetase condensation domains. Biochemistry 39, 15513–15521 (2000).

    Article  CAS  PubMed  Google Scholar 

  56. Pfeifer, B. A., Admiraal, S. J., Gramajo, H., Cane, D. E. & Khosla, C. Biosynthesis of complex polyketides in a metabolically engineered strain of E. coli. Science 291, 1790–1792 (2001).

    Article  CAS  PubMed  Google Scholar 

  57. Pugin, B. et al. A wide diversity of bacteria from the human gut produces and degrades biogenic amines. Microb. Ecol. Health Dis. 28, 1353881 (2017).

    PubMed  PubMed Central  Google Scholar 

  58. Hansen, D. B., Bumpus, S. B., Aron, Z. D., Kelleher, N. L. & Walsh, C. T. The loading module of mycosubtilin: an adenylation domain with fatty acid selectivity. J. Am. Chem. Soc. 129, 6366–6367 (2007).

    Article  CAS  PubMed  Google Scholar 

  59. Stachelhaus, T., Mootz, H. D. & Marahiel, M. A. The specificity-conferring code of adenylation domains in nonribosomal peptide synthetases. Chem. Biol. 6, 493–505 (1999).

    Article  CAS  PubMed  Google Scholar 

  60. Stachelhaus, T., Mootz, H. D., Bergendahl, V. & Marahiel, M. A. Peptide bond formation in nonribosomal peptide biosynthesis. Catalytic role of the condensation domain. J. Biol. Chem. 273, 22773–22781 (1998).

    Article  CAS  PubMed  Google Scholar 

  61. Brady, S. F. & Clardy, J. Palmitoylputrescine, an antibiotic isolated from the heterologous expression of DNA extracted from bromeliad tank water. J. Nat. Prod. 67, 1283–1286 (2004).

    Article  CAS  PubMed  Google Scholar 

  62. Frolov, A., Cho, T. H., Billheimer, J. T. & Schroeder, F. Sterol carrier protein-2, a new fatty acyl coenzyme A-binding protein. J. Biol. Chem. 271, 31878–31884 (1996).

    Article  CAS  PubMed  Google Scholar 

  63. McKinney, M. K. & Cravatt, B. F. Structure and function of fatty acid amide hydrolase. Annu. Rev. Biochem. 74, 411–432 (2005).

    Article  CAS  PubMed  Google Scholar 

  64. Quadri, L. E. et al. Characterization of Sfp, a Bacillus subtilis phosphopantetheinyl transferase for peptidyl carrier protein domains in peptide synthetases. Biochemistry 37, 1585–1595 (1998).

    Article  CAS  PubMed  Google Scholar 

  65. Hill, M. J. Microbial Metabolism in the Digestive Tract (CRC Press, 2018).

  66. Abdelmagid, S. A. et al. Comprehensive profiling of plasma fatty acid concentrations in young healthy Canadian adults. PLoS ONE 10, e0116195 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  67. Chan, M., Himes, R. H. & Akagi, J. M. Fatty acid composition of thermophilic, mesophilic, and psychrophilic clostridia. J. Bacteriol. 106, 876–881 (1971).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Vernocchi, P., Del Chierico, F. & Putignani, L. Gut microbiota profiling: metabolomics based approach to unravel compounds affecting human health. Front. Microbiol. 7, 1144 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  69. Lyte, M. & Freestone, P. P. E. Microbial Endocrinology: Interkingdom Signaling in Infectious Disease and Health (Springer, 2010).

  70. Lucke, C., Zhang, F., Ruterjans, H., Hamilton, J. A. & Sacchettini, J. C. Flexibility is a likely determinant of binding specificity in the case of ileal lipid binding protein. Structure 4, 785–800 (1996).

    Article  CAS  PubMed  Google Scholar 

  71. Rademacher, M., Zimmerman, A. W., Ruterjans, H., Veerkamp, J. H. & Lucke, C. Solution structure of fatty acid-binding protein from human brain. Mol. Cell. Biochem. 239, 61–68 (2002).

    Article  CAS  PubMed  Google Scholar 

  72. He, Y. et al. Solution-state molecular structure of apo and oleate-liganded liver fatty acid-binding protein. Biochemistry 46, 12543–12556 (2007).

    Article  CAS  PubMed  Google Scholar 

  73. Zimmerman, A. W., van Moerkerk, H. T. & Veerkamp, J. H. Ligand specificity and conformational stability of human fatty acid-binding proteins. Int. J. Biochem. Cell Biol. 33, 865–876 (2001).

    Article  CAS  PubMed  Google Scholar 

  74. Hanhoff, T., Lucke, C. & Spener, F. Insights into binding of fatty acids by fatty acid binding proteins. Mol. Cell. Biochem. 239, 45–54 (2002).

    Article  CAS  PubMed  Google Scholar 

  75. Liberles, S. D. Trace amine-associated receptors: ligands, neural circuits, and behaviors. Curr. Opin. Neurobiol. 34, 1–7 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Butini, S. et al. Polypharmacology of dopamine receptor ligands. Prog. Neurobiol. 142, 68–103 (2016).

    Article  CAS  PubMed  Google Scholar 

  77. Chebib, M. & Johnston, G. A. The ‘ABC’ of GABA receptors: a brief review. Clin. Exp. Pharmacol. Physiol. 26, 937–940 (1999).

    Article  CAS  PubMed  Google Scholar 

  78. Callery, P. S. & Geelhaar, L. A. 1-Piperideine as an in vivo precursor of the γ-aminobutyric acid homologue 5-aminopentanoic acid. J. Neurochem. 45, 946–948 (1985).

    Article  CAS  PubMed  Google Scholar 

  79. Schlessinger, A. et al. High selectivity of the γ-aminobutyric acid transporter 2 (GAT-2, SLC6A13) revealed by structure-based approach. J. Biol. Chem. 287, 37745–37756 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Pacher, P., Batkai, S. & Kunos, G. The endocannabinoid system as an emerging target of pharmacotherapy. Pharmacol. Rev. 58, 389–462 (2006).

    Article  CAS  PubMed  Google Scholar 

  81. Yin, H. et al. Lipid G protein-coupled receptor ligand identification using β-arrestin PathHunter assay. J. Biol. Chem. 284, 12328–12338 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Werner, L., Guzner-Gur, H. & Dotan, I. Involvement of CXCR4/CXCR7/CXCL12 interactions in inflammatory bowel disease. Theranostics 3, 40–46 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Davis, E. A., Zhou, W. & Dailey, M. J. Evidence for a direct effect of the autonomic nervous system on intestinal epithelial stem cell proliferation. Physiol. Rep. 6, e13745 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  84. D’Amato, M. et al. Neuropeptide S receptor 1 gene polymorphism is associated with susceptibility to inflammatory bowel disease. Gastroenterology 133, 808–817 (2007).

    Article  PubMed  Google Scholar 

  85. Su, Q. et al. Polymorphisms of PRLHR and HSPA12A and risk of gastric and colorectal cancer in the Chinese Han population. BMC Gastroenterol. 15, 107 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  86. Glas, J. et al. PTGER4 expression-modulating polymorphisms in the 5p13.1 region predispose to Crohn’s disease and affect NF-κB and XBP1 binding sites. PLoS ONE 7, e52873 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Hannedouche, S. et al. Oxysterols direct immune cell migration via EBI2. Nature 475, 524–527 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Gessier, F. et al. Identification and characterization of small molecule modulators of the Epstein–Barr virus-induced gene 2 (EBI2) receptor. J. Med. Chem. 57, 3358–3368 (2014).

    Article  CAS  PubMed  Google Scholar 

  89. Poyet, M. et al. A library of human gut bacterial isolates paired with longitudinal multiomics data enables mechanistic microbiome research. Nat. Med. 25, 1442–1452 (2019).

    Article  CAS  PubMed  Google Scholar 

  90. Dixit, S. & Das, M. Fatty acid composition including trans-fatty acids in edible oils and fats: probable intake in Indian population. J. Food Sci. 77, T188–T199 (2012).

    Article  CAS  PubMed  Google Scholar 

  91. Williams, B. B. et al. Discovery and characterization of gut microbiota decarboxylases that can produce the neurotransmitter tryptamine. Cell Host Microbe 16, 495–503 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Asano, Y. et al. Critical role of gut microbiota in the production of biologically active, free catecholamines in the gut lumen of mice. Am. J. Physiol. Gastrointest. Liver Physiol. 303, G1288–G1295 (2012).

    Article  CAS  PubMed  Google Scholar 

  93. Yano, J. M. et al. Indigenous bacteria from the gut microbiota regulate host serotonin biosynthesis. Cell 161, 264–276 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Aminov, R. I. et al. Molecular diversity, cultivation, and improved detection by fluorescent in situ hybridization of a dominant group of human gut bacteria related to Roseburia spp. or Eubacterium rectale. Appl. Environ. Microbiol. 72, 6371–6376 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Porter, H. P. & Saunders, D. R. Isolation of the aqueous phase of human intestinal contents during the digestion of a fatty meal. Gastroenterology 60, 997–1007 (1971).

    Article  CAS  PubMed  Google Scholar 

  96. Britanova, L. & Diefenbach, A. Interplay of innate lymphoid cells and the microbiota. Immunol. Rev. 279, 36–51 (2017).

    Article  CAS  PubMed  Google Scholar 

  97. Pantazi, E. & Powell, N. Group 3 ILCs: peacekeepers or troublemakers? What’s your gut telling you?! Front. Immunol. 10, 676 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Gatto, D., Paus, D., Basten, A., Mackay, C. R. & Brink, R. Guidance of B cells by the orphan G protein-coupled receptor EBI2 shapes humoral immune responses. Immunity 31, 259–269 (2009).

    Article  CAS  PubMed  Google Scholar 

  99. Wyss, A. et al. The EBI2-oxysterol axis promotes the development of intestinal lymphoid structures and colitis. Mucosal Immunology https://doi.org/10.1038/s41385-019-0140-x (2019).

  100. Benned-Jensen, T. et al. Small molecule antagonism of oxysterol-induced Epstein–Barr virus induced gene 2 (EBI2) activation. FEBS Open Bio 3, 156–160 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Forbes, J. D., Van Domselaar, G. & Bernstein, C. N. The gut microbiota in immune-mediated inflammatory diseases. Front. Microbiol. 7, 1081 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  102. Geva-Zatorsky, N. et al. Mining the human gut microbiota for immunomodulatory organisms. Cell 168, 928–943 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Jostins, L. et al. Host–microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 491, 119–124 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. Takahashi, H. et al. Cloning and characterization of a Streptomyces single module type non-ribosomal peptide synthetase catalyzing a blue pigment synthesis. J. Biol. Chem. 282, 9073–9081 (2007).

    Article  CAS  PubMed  Google Scholar 

  105. Meyer, A. J., Segall-Shapiro, T. H., Glassey, E., Zhang, J. & Voigt, C. A. Escherichia coli “Marionette” strains with 12 highly optimized small-molecule sensors. Nat. Chem. Biol. 15, 196–204 (2019).

    Article  CAS  PubMed  Google Scholar 

  106. Frank, J. A. et al. Critical evaluation of two primers commonly used for amplification of bacterial 16S rRNA genes. Appl. Environ. Microbiol. 74, 2461–2470 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank T. Wyche and J. Clardy (Harvard Medical School) for help with nuclear magnetic resonance. We also thank S. Abubucker and H. Haiser (Novartis) for help with experimental design. The stool samples were graciously provided by E. Alm (MIT) and M. Poyet (MIT) of the OpenBiome. This work is funded by the US Defense Advanced Research Projects Agency (DARPA) Living Foundries 1KM award no. HR0011-15-C-0084. F.-Y.C., C.A.V. and D.B.G. are funded by a research award from the Novartis Institute for Biomedical Research (NIMBR).

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Authors and Affiliations

  1. Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Fang-Yuan Chang, Emerson Glassey, David Benjamin Gordon & Christopher A. Voigt

  2. The Foundry, Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Fang-Yuan Chang, Thomas Williams, David Benjamin Gordon & Christopher A. Voigt

  3. Synthetic Biology Group, Global Discovery Chemistry, Novartis Institutes for BioMedical Research, Cambridge, MA, USA

    Piro Siuti & Horst Hemmerle

  4. Disease Area X, Novartis Institutes for BioMedical Research, Basel, Switzerland

    Stephane Laurent & Andreas W. Sailer

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Contributions

F.-Y.C., P.S., D.B.G., H.H. and C.A.V. conceived the study and designed the experiments. F.-Y.C. performed the bioinformatics, experiments and data analysis. S.L. and A.W.S. performed and analysed the EBI2 assays. T.W., E.G. and D.B.G. analysed MS data and performed experiments with the faecal samples. F.-Y.C. and C.A.V. wrote the manuscript.

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Correspondence to Christopher A. Voigt.

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Peer review information Nature Microbiology thanks Vanessa Phelan for her contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Pathway boundary analysis.

a, Genetic diagrams for the eighteen Clostridia pathways, consisting of the eight HMP-derived pathways (top) and the ten NCBI nr database (bottom), with pathway boundaries predicted by antiSMASH. Pink = biosynthetic genes (1 = condensation domain protein, 2 = thiolation domain protein, 3 = adenylation domain protein). Yellow = accessory genes (4 = alpha/beta-fold hydrolase, 5 = PPTase, 6 = sterol transfer protein). Colorless = other genes (7 = TetR regulator, 8 = AraC regulator, 9 = Renal dipeptidase, 10 = HisJ phosphatase, 11 = MerR regulator, 12 = Cell wall glycosyltransferase, 13 = DMT transporter, 14 = CorA transporter, 15 = Citrate transporter. b, Annotation of the E. recale pathway including two additional genes outside of the antiSMASH-predicted boundary. Each gene was investigated for the presence of a homolog in other FAA pathways.

Extended Data Fig. 2 In vitro substrate screening for pathways producing same major compounds.

Six Clostridia-derived pathways encoding for major FAA compounds that are equivalent to the pathways from Fig. 3d. Top: Major compound based on fatty acid and amine substrate with highest activity level in the panel assay. Bottom: Bar graph representing adenylation and condensation activity from the substrate panel assay. The amines are color-coded based on the FAA classes as in Fig. 3c. The data represent means of three experiments performed on different days. The data values are provided in Source Data Extended Data Fig. 2.

Source data

Extended Data Fig. 3 Fatty acid specificity profile.

a, Overall average of product peak area of the eighteen Clostridia A domain proteins on the following fatty acid substrates (from left to right data point): stearic acid (F12), palmitic acid (F11), arachidonic acid (F22), docosahexaenoic acid (F25), linoleic acid (F18), α-linolenic acid (F20), and oleic acid (F16). This is correlated with the dissociation constant of human brain fatty acid binding protein measured by isothermal titration calorimetry (ITC), as reported in previous study74. b, Substrate specificity profile of the Clostridia adenylation protein by the length of fatty acid substrate structure. The reported value of product peak is the overall average from the eighteen Clostridia A domain proteins. The structure length is calculated by importing the structure from PubChem onto Chem3D version 15 (in the U-bent configuration for unsaturated fatty acids) and measuring the distance from the carboxylic acid carbon to the most distal carbon.

Extended Data Fig. 4 GPCR activity assay for oleoyl dopamine.

Cell-based β-arrestin reporter assay (DiscoverX) with a panel of 168 GPCRs with known ligands in agonist mode and antagonist mode, and also 73 orphan GPCRs in agonist mode at 10 µM. Agonist mode measures % activity of target GPCR by the compound, relative to the baseline value (0% activity) and maximum value with a known ligand, or two-fold increase over baseline for orphan GPCR (100% activation). Antagonist mode measures % inhibition of target GPCR by the compound in the presence of a known ligand, relative to the value at the EC80 (0% inhibition) and basal value (100% inhibition). GPCR targets with activity/inhibition higher than the empirical threshold provided by DiscoverX (30%, 35%, or 50% for GPCR agonist, GPCR antagonist, or orphan GPCR agonist, respectively; plotted as dotted line) are highlighted in red.

Extended Data Fig. 5 GPCR activity assay for oleoyl tyramine.

Cell-based β-arrestin reporter assay (DiscoverX) with a panel of 168 GPCRs with known ligands in agonist mode and antagonist mode, and also 73 orphan GPCRs in agonist mode at 10 µM. Agonist mode measures % activity of target GPCR by the compound, relative to the baseline value (0% activity) and maximum value with a known ligand, or two-fold increase over baseline for orphan GPCR (100% activation). Antagonist mode measures % inhibition of target GPCR by the compound in the presence of a known ligand, relative to the value at the EC80 (0% inhibition) and basal value (100% inhibition). GPCR targets with activity/inhibition higher than the empirical threshold provided by DiscoverX (30%, 35%, or 50% for GPCR agonist, GPCR antagonist, or orphan GPCR agonist, respectively; plotted as dotted line) are highlighted in red.

Extended Data Fig. 6 GPCR activity assay for oleoyl aminovaleric acid.

Cell-based β-arrestin reporter assay (DiscoverX) with a panel of 168 GPCRs with known ligands in agonist mode and antagonist mode, and also 73 orphan GPCRs in agonist mode at 10 µM. Agonist mode measures % activity of target GPCR by the compound, relative to the baseline value (0% activity) and maximum value with a known ligand, or two-fold increase over baseline for orphan GPCR (100% activation). Antagonist mode measures % inhibition of target GPCR by the compound in the presence of a known ligand, relative to the value at the EC80 (0% inhibition) and basal value (100% inhibition). GPCR targets with activity/inhibition higher than the empirical threshold provided by DiscoverX (30%, 35%, or 50% for GPCR agonist, GPCR antagonist, or orphan GPCR agonist, respectively; plotted as dotted line) are highlighted in red.

Extended Data Fig. 7 Activity of FAAs.

a, Dose response curves (sigmoidal) of the inhibitory activity of lauroyl tryptamine, tryptamine, and lauric acid on P2RY4 in the presence of the native agonist UTP at 2.79 µM (EC80). IC50 > 100 µM for all three compounds. The points were measured in duplicate. b, Dose response curves (sigmoidal) of the stimulatory activity of lauroyl tryptamine, tryptamine, and lauric acid on GPR132. EC50: lauroyl tryptamine = 1.45 µM; lauric acid = 25.2 µM; tryptamine > 100 µM. The points were measured in duplicate. c, Summary table of EC50s and IC50s calculated using data from the DiscoverX cell-based assay. d, Dose response curves (sigmoidal) of the calcium release-based stimulatory activity on EBI2. The error bars are the standard deviations of the three mean quadruplicate values. EC50: lauroyl tryptamine > 20 µM; 7α,25-OHC = 0.002 µM. e, Dose response curves (sigmoidal) of the radioligand binding activity of different compounds on EBI2. The error bars are the standard deviations of the three mean quadruplicate values. f, Dose response curves (sigmoidal) of the calcium release-based inhibitory activity of different compounds on EBI2 in the presence of the native agonist 7α,25-OHC at 3.7 nM (EC80). The error bars are the standard deviations of the three mean quadruplicate values. g, Dose response curves (sigmoidal) of the calcium release-based stimulatory activity of different compounds on EBI2. The error bars are the standard deviations of the three mean quadruplicate values. h, Summary table of EC50 and IC50 from radioligand binding and calcium release assays. NIBR51 and NIBR189 are known EBI2 antagonists. 7α,25-Dihydroxycholesterol (7α,25-OHC), 7β,25-Dihydroxycholesterol (7β,25-OHC), 25-Hydroxycholesterol (25-OHC), cholesterol, and 7β-Hydroxycholesterol (7-OHC) are known EBI2 agonists.

Extended Data Fig. 8 Lauroyl tryptamine produced by Eubacterium rectale.

a, Lauroyl tryptamine production by E. rectale in culture. Extracts were evaluated without substrate feeding in RCM media. MS chromatogram: (EIC ESI+ [M + H]+ m/z of lauroyl tryptamine, theoretical = 343.2744, experimental = 343.2369). The samples are injected alongside a chemically-synthesized and structurally-verified standard. The data shown are representative of three experiments performed on different days, all showing similar results. b, MS-MS chromatogram (lauroyl tryptamine quantifier ion 343.3 m/z -> 144.1) is shown for the product obtained from an E. rectale culture alongside a structurally-verified standard. c, UV spectrum for lauroyl tryptamine in E. rectale culture alongside a structurally-verified standard. d, Standard curve of 280 nm absorbance (0.5 nm tolerance) peak area by injection of the chemically synthesized lauroyl tryptamine standard. Standard curve was used to calculate the FAA concentrations in E. rectale culture, including Fig. 4e. The standards were originally measured in ng/mL in solution, as injected into the LC-MS. This was converted to mg/L, where L is bacterial culture volume, by multiplying by a factor of 0.002 (Methods). The FAA concentration was measured on three different days. A new standard curve was constructed for each day, one curve of which is shown.

Extended Data Fig. 9 Lauroyl tryptamine in human fecal samples.

a, Total count of MS peaks with the matching exact mass (within 0.002 ppm), or isomers, of the primary FAAs (bold) and secondary FAAs that are present in BIO-ML collection of human fecal samples89. The number indicates the isomers that have the same mass as the compound indicated, but one could not be proven to be that compound without additional experimentation. b, Standard curve of LCMS-MS peak area by injection of structurally-verified standard for quantification of lauroyl tryptamine titer in fecal samples. The standard curve was used to calculate the concentrations in c (Methods). The standards were originally measured in pg/mL in solution, as injected into the LC-MS. This was converted to ng/g, where g is “fresh fecal” wet weight, by multiplying by a factor of 0.04 (Methods). c, Summary FAA titers in select BIO-ML fecal samples (ng/g fresh fecal weight). ‘**’ indicates no compound detected.

Extended Data Fig. 10 Enzyme activity assay time course.

Fatty acid (left) and amine (right) substrate panel assay for C. eutactus pathway proteins. a, Unnormalized product level data are shown for 8 representative fatty acid (left) or amine (right) substrates. Product level data with adenylation protein (black lines) are normalized with respect to data without adenylation protein (red lines) for enzyme activity data with fatty acid substrates (left). Product level data with condensation protein (black lines) are normalized with respect to data without condensation protein (red lines) for enzyme activity data with amine substrates (right). b, For all 25 fatty acid (left) or 53 amine (right) substrates, normalized activity data are shown. The time point with the largest difference between the highest point and the remainder of the curves is marked with an arrow. The means were calculated based on three triplicates performed in different days and the error bars are the standard deviations.

Supplementary information

Supplementary Information

Supplementary Figs. 1–12, Tables 1–8 and references.

Reporting Summary

Supplementary Data 1

Human gut-associated bacteria genomic datasets.

Supplementary Data 2

Data values for Supplementary Fig. 10.

Source data

Source Data Fig. 3

Data values for Fig. 3d.

Source Data Extended Data Fig. 2

Data values for Extended Data Fig. 2.

Source Data Fig. 4

Full scan of Fig. 4h. Lanes for Ladder and Stool (ere) are shown in Fig. 4h. Different BIO-ML stool DNA was subject to PCR detection for each lane. BIO-ML stool ID for each lane is as follows: lane 1, af-0003; 2, am-0015; 3, am-0111; 4, aq-0015; 5, bu-0080; 6, cj-0004; and Stool (ere), dc-0028.

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Chang, FY., Siuti, P., Laurent, S. et al. Gut-inhabiting Clostridia build human GPCR ligands by conjugating neurotransmitters with diet- and human-derived fatty acids. Nat Microbiol 6, 792–805 (2021). https://doi.org/10.1038/s41564-021-00887-y

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