Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Host immunomodulatory lipids created by symbionts from dietary amino acids

Abstract

Small molecules derived from symbiotic microbiota critically contribute to intestinal immune maturation and regulation1. However, little is known about the molecular mechanisms that control immune development in the host–microbiota environment. Here, using a targeted lipidomic analysis and synthetic approach, we carried out a multifaceted investigation of immunomodulatory α-galactosylceramides from the human symbiont Bacteroides fragilis (BfaGCs). The characteristic terminal branching of BfaGCs is the result of incorporation of branched-chain amino acids taken up in the host gut by B. fragilis. A B. fragilis knockout strain that cannot metabolize branched-chain amino acids showed reduced branching in BfaGCs, and mice monocolonized with this mutant strain had impaired colonic natural killer T (NKT) cell regulation, implying structure-specific immunomodulatory activity. The sphinganine chain branching of BfaGCs is a critical determinant of NKT cell activation, which induces specific immunomodulatory gene expression signatures and effector functions. Co-crystal structure and affinity analyses of CD1d–BfaGC–NKT cell receptor complexes confirmed the interaction of BfaGCs as CD1d-restricted ligands. We present a structural and molecular-level paradigm of immunomodulatory control by interactions of endobiotic metabolites with diet, microbiota and the immune system.

This is a preview of subscription content

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Chemical structure assignment of chain-length and branching variation in BfaGCs.
Fig. 2: BfaGC branching is dictated by host dietary BCAAs, and loss of BCAA utilization in B. fragilis impairs its ability to modulate host colonic NKT cells.
Fig. 3: BfaGCs cause distinct immunomodulatory signalling and actions.
Fig. 4: Crystal structure of 2C12 NKT cell receptor (TCR)–mCD1d–BfaGC ternary complexes showed conserved and distinct molecular interactions of BfaGCs with mCD1d and the 2C12 TCR.

Data availability

Raw data for NKT cell transcriptomic analysis was deposited in the NCBI Sequence Read Archive (SRA) with accession PRJNA750126. The crystal structures of the 2C12 TCR–mCD1d–SB2217 and 2C12 TCR–mCD1d–SB2219 ternary complexes were deposited in the Protein Data Bank under accession numbers 7M72 and 6XNG, respectively. Lipidomic analysis data containing MS1 scans were deposited to Metabolomics Workbench study number ST001910.

References

  1. 1.

    Surana, N. K. & Kasper, D. L. Deciphering the tête-à-tête between the microbiota and the immune system. J. Clin. Invest. 124, 4197–4203 (2014).

    PubMed  PubMed Central  Google Scholar 

  2. 2.

    Skelly, A. N., Sato, Y., Kearney, S. & Honda, K. Mining the microbiota for microbial and metabolite-based immunotherapies. Nat. Rev. Immunol. 19, 305–323 (2019).

    CAS  PubMed  Google Scholar 

  3. 3.

    Surana, N. K. & Kasper, D. L. The yin yang of bacterial polysaccharides: lessons learned from B. fragilis PSA. Immunol. Rev. 245, 13–26 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. 4.

    Erturk-Hasdemir, D. et al. Symbionts exploit complex signaling to educate the immune system. Proc. Natl Acad. Sci. USA 116, 26157–26166 (2019).

    CAS  PubMed Central  Google Scholar 

  5. 5.

    Vatanen, T. et al. Variation in microbiome LPS immunogenicity contributes to autoimmunity in humans. Cell 165, 842–853 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. 6.

    d’Hennezel, E., Abubucker, S., Murphy, L. O. & Cullen, T. W. Total lipopolysaccharide from the human gut microbiome silences Toll-like receptor signaling. mSystems 2, (2017).

  7. 7.

    Kawahara, K., Tsukano, H., Watanabe, H., Lindner, B. & Matsuura, M. Modification of the structure and activity of lipid A in Yersinia pestis lipopolysaccharide by growth temperature. Infect. Immun. 70, 4092–4098 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. 8.

    Erturk-Hasdemir, D. & Kasper, D. L. Finding a needle in a haystack: Bacteroides fragilis polysaccharide a as the archetypical symbiosis factor. Ann. NY Acad. Sci. 1417, 116–129 (2018).

    ADS  CAS  PubMed  Google Scholar 

  9. 9.

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

    PubMed  PubMed Central  Google Scholar 

  10. 10.

    An, D. et al. Sphingolipids from a symbiotic microbe regulate homeostasis of host intestinal natural killer T cells. Cell 156, 123–133 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. 11.

    Wingender, G. et al. Intestinal microbes affect phenotypes and functions of invariant natural killer T cells in mice. Gastroenterology 143, 418–428 (2012).

    CAS  PubMed  Google Scholar 

  12. 12.

    Kinjo, Y. et al. Recognition of bacterial glycosphingolipids by natural killer T cells. Nature 434, 520–525 (2005).

    ADS  CAS  PubMed  Google Scholar 

  13. 13.

    Brondz, I. & Olsen, I. Multivariate analyses of cellular fatty acids in Bacteroides, Prevotella, Porphyromonas, Wolinella, and Campylobacter spp. J. Clin. Microbiol. 29, 183–189 (1991).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Miyagawa, E., Azuma, R., Suto, T. & Yano, I. Occurrence of free ceramides in Bacteroides fragilis NCTC 9343. J. Biochem. 86, 311–320 (1979).

    CAS  PubMed  Google Scholar 

  15. 15.

    Leo, R. F. & Parker, P. L. Branched-chain fatty acids in sediments. Science 152, 649–650 (1966).

    ADS  CAS  PubMed  Google Scholar 

  16. 16.

    Naik, D. N. & Kaneda, T. Biosynthesis of branched long-chain fatty acids by species of Bacillus: relative activity of three alpha-keto acid substrates and factors affecting chain length. Can. J. Microbiol. 20, 1701–1708 (1974).

    CAS  PubMed  Google Scholar 

  17. 17.

    Beck, H. C. Branched-chain fatty acid biosynthesis in a branched-chain amino acid aminotransferase mutant of Staphylococcus carnosus. FEMS Microbiol. Lett. 243, 37–44 (2005).

    CAS  PubMed  Google Scholar 

  18. 18.

    Kaneda, T. Iso-and anteiso-fatty acids in bacteria: biosynthesis, function, and taxonomic significance. Microbiol. Rev. 55, 288–302 (1991).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. 19.

    Liberzon, A. et al. The Molecular Signatures Database Hallmark gene set collection. Cell Syst. 1, 417–425 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. 20.

    Pellicci, D. G. et al. Differential recognition of CD1d-α-galactosyl ceramide by the Vβ8.2 and Vβ7 semi-invariant NKT T cell receptors. Immunity 31, 47–59 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. 21.

    Girardi, E. & Zajonc, D. M. Molecular basis of lipid antigen presentation by CD1d and recognition by natural killer T cells. Immunol. Rev. 250, 167–179 (2012).

    PubMed  PubMed Central  Google Scholar 

  22. 22.

    Rossjohn, J., Pellicci, D. G., Patel, O., Gapin, L. & Godfrey, D. I. Recognition of CD1d-restricted antigens by natural killer T cells. Nat. Rev. Immunol. 12, 845–857 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Chennamadhavuni, D. et al. Dual modifications of α-galactosylceramide synergize to promote activation of human invariant natural killer T cells and stimulate anti-tumor immunity. Cell Chem. Biol. 25, 571-584.e8 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. 24.

    Li, Y. et al. The Vα14 invariant natural killer T cell TCR forces microbial glycolipids and CD1d into a conserved binding mode. J. Exp. Med. 207, 2383–2393 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. 25.

    Wun, K. S. et al. A molecular basis for the exquisite CD1d-restricted antigen specificity and functional responses of natural killer T cells. Immunity 34, 327–339 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. 26.

    Natori, T., Koezuka, Y. & Higa, T. Agelasphins, novel α-galactosylceramides from the marine sponge Agelas mauritianus. Tetrahedron Lett. 34, 5591–5592 (1993).

    CAS  Google Scholar 

  27. 27.

    Kobayashi, E. et al. Enhancing effects of agelasphin-11 on natural killer cell activities of normal and tumor-bearing mice. Biol. Pharm. Bull. 19, 350–353 (1996).

    CAS  PubMed  Google Scholar 

  28. 28.

    Kobayashi, E., Motoki, K., Uchida, T., Fukushima, H. & Koezuka, Y. KRN7000, a novel immunomodulator, and its antitumor activities. Oncol. Res. 7, 529–534 (1995).

    CAS  PubMed  Google Scholar 

  29. 29.

    Li, X. et al. Design of a potent CD1d-binding NKT cell ligand as a vaccine adjuvant. Proc. Natl Acad. Sci. USA 107, 13010–13015 (2010).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Laurent, X. et al. Switching invariant natural killer T (iNKT) cell response from anticancerous to anti-inflammatory effect: molecular bases. J. Med. Chem. 57, 5489–5508 (2014).

    CAS  PubMed  Google Scholar 

  31. 31.

    Sag, D., Krause, P., Hedrick, C. C., Kronenberg, M. & Wingender, G. IL-10–producing NKT10 cells are a distinct regulatory invariant NKT cell subset. J. Clin. Invest. 124, 3725–3740 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Olszak, T. et al. Protective mucosal immunity mediated by epithelial CD1d and IL-10. Nature 509, 497–502 (2014).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Brutkiewicz, R. R. CD1d ligands: the good, the bad, and the ugly. J. Immunol. 177, 769–775 (2006).

    CAS  PubMed  Google Scholar 

  34. 34.

    Joyce, S., Girardi, E. & Zajonc, D. M. NKT cell ligand recognition logic: molecular basis for a synaptic duet and transmission of inflammatory effectors. J. Immunol. 187, 1081–1089 (2011).

    CAS  PubMed  Google Scholar 

  35. 35.

    Chung, H. et al. Gut immune maturation depends on colonization with a host-specific microbiota. Cell 149, 1578–1593 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. 36.

    Stewart, C. J. et al. Temporal development of the gut microbiome in early childhood from the TEDDY study. Nature 562, 583–588 (2018).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  37. 37.

    Sefik, E. et al. Individual intestinal symbionts induce a distinct population of ROR+ regulatory T cells. Science 349, 993–997 (2015).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  38. 38.

    Varel, V. H. & Bryant, M. P. Nutritional features of Bacteroides fragilis subsp. fragilis. Appl. Microbiol. 28, 251–257 (1974).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. 39.

    Matyash, V., Liebisch, G., Kurzchalia, T. V., Shevchenko, A. & Schwudke, D. Lipid extraction by methyl- tert -butyl ether for high-throughput lipidomics. J. Lipid Res. 49, 1137–1146 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Comstock, L. E. et al. Analysis of a capsular polysaccharide biosynthesis locus of Bacteroides fragilis. Infect. Immun. 67, 3525–3532 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. 41.

    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.e15 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. 42.

    Olszak, T. et al. Microbial exposure during early life has persistent effects on natural killer T cell function. Science 336, 489–493 (2012).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

    CAS  Google Scholar 

  44. 44.

    Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).

    CAS  Google Scholar 

  45. 45.

    Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

    PubMed  PubMed Central  Google Scholar 

  46. 46.

    Wickham, H. ggplot2: elegant graphics for data analysis. https://ggplot2.tidyverse.org/ (accessed: 9 March 2021).

  47. 47.

    Korotkevich, G. et al. Fast gene set enrichment analysis. Preprint at https://doi.org/10.1101/060012 (2016).

  48. 48.

    Matsuda, J. L. et al. Tracking the response of natural killer T cells to a glycolipid antigen using CD1d tetramers. J. Exp. Med. 192, 741–754 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. 49.

    Kabsch, W. XDS. Acta Crystallogr. D 66, 125–132 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. 50.

    Evans, P. Scaling and assessment of data quality. Acta Crystallogr. D 62, 72–82 (2006).

    PubMed  Google Scholar 

  51. 51.

    Adams, P. D. et al. PHENIX: A comprehensive Python-based system for macromolecular structure solution. Acta Crystallogr. D 66, 213–221 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. 52.

    Emsley, P., Lohkamp, B., Scott, W. G. & Cowtan, K. Features and development of Coot. Acta Crystallogr. D 66, 486–501 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. 53.

    Bricogne G. et al. BUSTER Version 2.10.3 (Global Phasing Ltd, 2017).

  54. 54.

    Tong, J., Liu, C., Summanen, P., Xu, H., Finegold, S. M. Application of quantitative real-time PCR for rapid identification of Bacteroides fragilis group and related organisms in human wound samples. Anaerobe 17, 64–68 (2011).

    CAS  PubMed  Google Scholar 

  55. 55.

    Suzuki, M. T., Taylor, L. T. & DeLong, E. F. Quantitative analysis of small-subunit rRNA genes in mixed microbial populations via 5′-nuclease assays. Appl. Environ. Microbiol. 66, 4605–4614 (2000).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank J. McCoy and E. J. Paik for manuscript preparation, R. T. Bronson for histopathological scoring, S. Iyer, L. Gebremedhin, E. Choi and T. Yanostang for technical assistance, and the staff at the Australian Synchrotron for assistance with data collection. This work was supported by National Institutes of Health (K01-DK102771 and R01-AT010268 to S.F.O., and R01-DK044319 to R.S.B.), Department of Defense (W81XWH-19-1-0625 to D.L.K.), Brigham and Women’s Hospital (Department of Anesthesiology, Perioperative and Pain Medicine Basic Science Grant to S.F.O.), the National Research Foundation of Korea (2014R1A3A2030423 and 2012M3A9C4048780 to S.B.P.), and the Australian Research Council (ARC) (CE140100011 and ARC Laureate Fellowship to J.R., and ARC Future Fellowship to J.L.N.). Graphical images used for the Fig. 2 were created with BioRender.com.

Author information

Affiliations

Authors

Contributions

S.F.O., D.L.K. and R.S.B. conceived the idea and designed the outline of the research. S.F.O., H.B.S. and S.B.P. designed the structures of synthetic BfaGCs; H.B.S., Y.S.H., H.K. and J.L. synthesized BfaGC molecules. T.P., J.L.N. and J.R. generated crystals of 2C12 TCR–CD1d–BfaGCs and carried out X-ray crystallography analysis as well as affinity measurements by SPR. S.F.O., J.-S.Y. and C.C.L. designed and carried out all experiments with microorganisms. S.F.O., D.-J.J. and D.E.-H. executed in vitro and in vivo cytokine assays. S.F.O. and D.-J.J. designed and carried out all animal experiments. J.-S.Y. carried out transcriptomic analysis. S.F.O., S.B.P., J.R. and D.L.K. wrote the manuscript, and all authors contributed to relevant discussions.

Corresponding authors

Correspondence to Sungwhan F. Oh, Jamie Rossjohn, Seung Bum Park or Dennis L. Kasper.

Ethics declarations

Competing interests

S.F.O., R.S.B. and D.L.K. have filed a patent on the functions of BfaGCs and related structures (US patent 10,329,315). S.F.O., S.B.P. and D.L.K. filed a patent on the functions of BfaGCs and related structures (under review).

Additional information

Peer review information Nature thanks the anonymous reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Molecular structures of prototypic NKT agonist KRN7000, OCH and a representative B. fragilis-derived aGC (SB2217)

.

Extended Data Fig. 2 LC-MS profile of BfaGCs.

(A) Representative extracted ion chromatograms (XICs) of C32–C36 BfaGCs. (B) C34 BfaGCs are the major component of B. fragilis glycosphingolipids (N=5).

Extended Data Fig. 3 LC-MS/MS assignment of C34 BfaGC structural variants.

(A) The MS/MS-XIC of total C34 BfaGCs (762→698) shows that BfaGCs are isobaric mixtures separated by RP-HPLC. (B, C) MS/MS-XICs of C34 BfaGCs reveal co-eluting chemical homologues. Two isobaric species with aliphatic chains of C17/C17 (B) and C18/C16 (C) were assigned MS/MS fingerprints of 490 and 504, respectively. (D) MS/MS fingerprints of three peaks show a distinct difference in relative intensity between MS/MS fragments of 490 (C17/C17) and 504 (C18/C16), implying that the latter two peaks are a mixture of chain-length homologues. Chromatograms and spectra represent triplicate observations. (E-H) MS/MS spectra of the most abundant peaks of (E) C32, (F) C33, (G) C35 and (H) C36 BfaGCs. MS/MS fingerprint of 462–518 indicates lengths of sphinganine and acyl chains. Spectra are representative of triplicate observation.

Extended Data Fig. 4 Chemical structures of 23 synthetic BfaGCs.

(SB2201–SB2223).

Extended Data Fig. 5 BCAA dictates branching of BfaGCs by direct incorporation in vivo.

(A–E) Ratios among differently branched C34 BfaGCs (MS1 XIC=762.57, as [M+HCOO-]) are clearly different for B. fragilis grown in rich medium (A) and B. fragilis grown in minimal medium (B). Supplementation with individual BCAAs (C–E) on defined medium increases production of branched-chain (both dibranched and monobranched) BfaGCs. (F–H) MS/MS fingerprints confirm the incorporation of leucine and isoleucine into the C17/C17 ceramide backbone (via C5 branched acyl-CoA) and of valine into the C18/C16 backbone (via C4 branched acyl-CoA). Chromatograms and spectra are representative of triplicate observations. (I) An MS/MS-XIC of d3- and d6-C34 BfaGC shows that deuterium-labeled leucine is actively incorporated into BfaGC. (J-K) MS/MS pattern shows distinctive differences between gut luminal BfaGC (M+3 isotopolog) in (J) presence or (K) absence of d3-leucine, showing MS2 fragments in presence of d3-leucine reflect inclusion of deuterium-labeled leucine in the structure. Chromatograms and spectra are representative results of four mice.

Extended Data Fig. 6 Genetic study of B. fragilis Bcat orthologue (BF9343-3671).

(A) Confirmation of the target gene deletion by PCR. (B) The knockout strain (BF9343-Δ3671) shows comparable growth pattern to isogenic WT strain (grown in duplicate per group), and a complemented strain of KO strain with empty vector shows same pattern to BF9343-3671 complemented strain. (C) BF9343-Δ3671 complementation can recover the production of di-branched C17/C17 BfaGC production to wild-type level. (D) WT and mutant strain (N=5 for each group) can colonize mouse in comparable density. All results represent of two independent experiments with similar trend. For gel source data, see Supplementary Fig. 1.

Extended Data Fig. 7 Structure-specific actions of BfaGCs.

(A) NKT cell–APC co-culture assays show that branching of sphinganine chain is, but 3’-OH group is not, critical for IL-2 inducing activity. Results are shown in duplicate and represent three independent experiment sets with similar trend (p=0.017 for 100nM and p=0.026 for 1000nM). (B-C) When injected intraperitoneally (N=5 per group, one sample in OCH group in panel C was lost), unlike Th1- or Th2-skewed prototypic ligands such as KRN7000 or OCH, SB2217 only weakly induce IFN-γ and did not induce IL-4 in vivo. (D-F) SB2217 weakly induced expression of co-stimulatory molecules such as CD86, CD40 and CD80 in splenic DCs, where SB2219 did not (N=5 per group).

Extended Data Fig. 8 Transcriptomic landscape of splenic NKT cells in responses to agonists.

(A) A heatmap shown with the Euclidean distances between different treatment groups. (B) Transcriptomic profile comparison of SB2217, SB2219 and OCH. (C) Pathway enrichment analysis of SB2217 reveals increased expression of immunoregulatory pathways in NKT cells when compared to vehicle or SB2219.

Extended Data Fig. 9 Comparison between SB2217 and SB2219 in mCD1d-BfaGC-2C12 complexes.

(A) 2Fo-Fc electron density map (in blue) contoured at a 0.8σ level of the BfaGCs within each ternary complex. (B) Fo-Fc electron density map (in brown) contoured at a 2.2σ level of the BfaGCs and spacer lipids within each ternary complex. SB2217 is shown as blue and SB2219 is shown as green; Spacer lipids are shown as black sticks. (C) Superimposition of the headgroups of BfaGCs and KRN7000 (PDB code: 6BNK). (D) 2C12 TCR molecular interactions with SB2217 (in blue). mCD1d and CDR loops are colored as in Fig. 4a. Hydrogen bonds are shown as red dashed lines. (E-F) The mCD1d–SB2217 complex shows higher affinity to 2C12 TCR than the mCD1d–SB2219 complex. (E) Each SPR datapoint is mean of techincal duplicate and KD values (mean±SD) were calculated from two independent results, using a single-site binding model with KD as a shared variable. (F) The sensorgrams are results of single experiment.

Extended Data Fig. 10 BfaGC profile in human microbiota-associated mice.

(A) BfaGC and B. fragilis abundance shows positive correlation in B. fragilis-gavaged HMB mice. Results are from longitudinally collected samples (2, 3 and 7 days after B. fragilis oral introduction) from five mice (total N=15). (B) BfaGC (C17/C17 dibranched and monobranched) are identified from neonatal (p14) GI contents. Chromatogram and spectrum represent seven samples.

Supplementary information

Supplementary Information

This file contains Supplementary Tables; Supplementary Figs. 1 (raw gel data) and 2 (FACS gating strategies for immune cell analysis); raw data (weight monitoring over disease time course) of in vivo experiment (oxazolone colitis); and total organic synthesis of BfaGC analogue (SB2201‐SB2223) library.

Reporting Summary

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Oh, S.F., Praveena, T., Song, H. et al. Host immunomodulatory lipids created by symbionts from dietary amino acids. Nature (2021). https://doi.org/10.1038/s41586-021-04083-0

Download citation

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links