Host immunomodulatory lipids created by symbionts from dietary amino acids

J. Clin. 124, 4197– 4203 (2014 ).
PubMed.
PubMed Central.

Google Scholar.

Rev. Immunol. 19, 305– 323 (2019 ).
CAS.
PubMed.

Google Scholar.

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

Google Scholar.

4.Erturk-Hasdemir, D. et al. Symbionts exploit complex signaling to educate the immune system. U.S.A. 116, 26157– 26166 (2019 ).
CAS.
PubMed Central.

Google Scholar.

5. Vatanen, T. et al. Variation in microbiome LPS immunogenicity adds to autoimmunity in humans. Cell 165, 842– 853 (2016 ).
CAS.
PubMed.
PubMed Central.

Google Scholar.

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

Google Scholar.

Google Scholar.

Google Scholar.

Wieland Brown, L. C. et al. Production of α-galactosylceramide by a popular member of the human gut microbiota.
PubMed.
PubMed Central.

NY Acad. 1417, 116– 129 (2018 ).
ADS.
CAS.
PubMed.

10. An, D. et al. Sphingolipids from a cooperative microorganism regulate homeostasis of host intestinal tract natural killer T cells. Cell 156, 123– 133 (2014 ).
CAS.
PubMed.
PubMed Central.

Google Scholar.

11. Wingender, G. et al. Digestive tract microorganisms impact phenotypes and functions of invariant natural killer T cells in mice. Gastroenterology 143, 418– 428 (2012 ).
CAS.
PubMed.

Google Scholar.

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. 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.

J. Biochem. 86, 311– 320 (1979 ).
CAS.
PubMed.

Google Scholar.

15. Leo, R. F. & & Parker, P. L. Branched-chain fats in sediments. Science 152, 649– 650 (1966 ).
ADS.
CAS.
PubMed.

Google Scholar.

16. Naik, D. N. & & Kaneda, T. Biosynthesis of branched long-chain fatty acids by types of Bacillus: relative activity of 3 alpha-keto acid substrates and aspects impacting chain length. Can. J. Microbiol. 20, 1701– 1708 (1974 ).
CAS.
PubMed.

Google Scholar.

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

Google Scholar.

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

Google Scholar.

Liberzon, A. et al. Cell Syst.
CAS.
PubMed.
PubMed Central.

Google Scholar.

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. Resistance 31, 47– 59 (2009 ).
CAS.
PubMed.
PubMed Central.

Google Scholar.

Google Scholar.

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

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.

Chennamadhavuni, D. et al. Dual adjustments of α-galactosylceramide synergize to promote activation of human invariant natural killer T cells and promote anti-tumor immunity. Cell Chem.
CAS.
PubMed.
PubMed Central.

Google Scholar.

Li, Y. et al. The Vα14 invariant natural killer T cell TCR forces microbial glycolipids and CD1d into a conserved binding mode. J. Exp.
CAS.
PubMed.
PubMed Central.

Google Scholar.

Google Scholar.

25. Wun, K. S. et al. A molecular basis for the beautiful CD1d-restricted antigen specificity and practical reactions of natural killer T cells. Immunity 34, 327– 339 (2011 ).
CAS.
PubMed.
PubMed Central.

Google Scholar.

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

Kobayashi, E. et al. Enhancing results of agelasphin-11 on natural killer cell activities of regular and tumor-bearing mice. Biol.
CAS.
PubMed.

Google Scholar.

Google Scholar.

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

Google Scholar.

29. Li, X. et al. Design of a powerful CD1d-binding NKT cell ligand as a vaccine adjuvant. Proc. Natl Acad. Sci. U.S.A. 107, 13010– 13015 (2010 ).
ADS.
CAS.
PubMed.
PubMed Central.

Google Scholar.

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

Google Scholar.

Google Scholar.

Brutkiewicz, R. R. CD1d ligands: the great, the bad, and the awful. J. Immunol.
CAS.
PubMed.

Google Scholar.

Sag, D., Krause, P., Hedrick, C. C., Kronenberg, M. & & Wingender, G. IL-10– producing NKT10 cells are an unique regulatory invariant NKT cell subset. J. Clin.
CAS.
PubMed.
PubMed Central.

Olszak, T. et al. Nature 509, 497– 502 (2014 ).
ADS.
CAS.
PubMed.
PubMed Central.

Google Scholar.

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

Google Scholar.

Stewart, C. J. et al. Temporal advancement of the gut microbiome in early youth from the TEDDY study.
ADS.
CAS.
PubMed.
PubMed Central.

Sefik, E. et al. Private intestinal symbionts induce an unique population of ROR+ regulative T cells.
ADS.
CAS.
PubMed.
PubMed Central.

Google Scholar.

Google Scholar.

38. Varel, V. H. & & Bryant, M. P. Nutritional functions of Bacteroides fragilis subsp. fragilis. Appl. Microbiol. 28, 251– 257 (1974 ).
CAS.
PubMed.
PubMed Central.

Google Scholar.

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. 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. Cell 169, 547– 558.
CAS.
PubMed.
PubMed Central.

Google Scholar.

42. Olszak, T. et al. Microbial exposure during early life has relentless results on natural killer T cell function. Science 336, 489– 493 (2012 ).
ADS.
CAS.
PubMed.
PubMed Central.

Google Scholar.

Dobin, A. et al. Bioinformatics 29, 15– 21 (2013 ).
CAS.

Google Scholar.

44. Liao, Y., Smyth, G. K. & & Shi, W. featureCounts: an efficient basic function program for assigning sequence reads to genomic functions. Bioinformatics 30, 923– 930 (2014 ).
CAS.

Google Scholar.

Google Scholar.

Genome Biol. 15, 550 (2014 ).
PubMed.
PubMed Central.

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

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

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

Google Scholar.

49. Kabsch, W. XDS. Acta Crystallogr. D 66, 125– 132 (2010 ).
CAS.
PubMed.
PubMed Central.

Google Scholar.

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

Google Scholar.

51. Adams, P. D. et al. PHENIX: A thorough Python-based system for macromolecular structure service. Acta Crystallogr. D 66, 213– 221 (2010 ).
CAS.
PubMed.
PubMed Central.

Google Scholar.

Google Scholar.

Acta Crystallogr. D 66, 486– 501 (2010 ).
CAS.
PubMed.
PubMed Central.

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

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

Google Scholar.

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

Google Scholar.

4.Erturk-Hasdemir, D. et al. An, D. et al. Pellicci, D. G. et al. Chennamadhavuni, D. et al. Adams, P. D. et al.