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Sulfamethoxazole drug stress upregulates antioxidant immunomodulatory metabolites in Escherichia coli

Abstract

Escherichia coli is an important model organism in microbiology and a prominent member of the human microbiota1. Environmental isolates readily colonize the gastrointestinal tract of humans and other animals, and they can serve diverse probiotic, commensal and pathogenic roles in the host2,3,4. Although certain strains have been associated with the severity of inflammatory bowel disease (IBD)2,5, the diverse immunomodulatory phenotypes remain largely unknown at the molecular level. Here, we decode a previously unknown E. coli metabolic pathway that produces a family of hybrid pterin–phenylpyruvate conjugates, which we named the colipterins. The metabolites are upregulated by subinhibitory levels of the antifolate sulfamethoxazole, which is used to treat infections including in patients with IBD6,7. The genes folX/M and aspC/tyrB involved in monapterin biosynthesis8,9,10 and aromatic amino acid transamination,11 respectively, were required to initiate the colipterin pathway. We show that the colipterins are antioxidants, harbour diverse immunological activities in primary human tissues, activate anti-inflammatory interleukin-10 and improve colitis symptoms in a colitis mouse model. Our study defines an antifolate stress response in E. coli and links its associated metabolites to a major immunological marker of IBD.

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Fig. 1: Colipterins upregulated by SMX antifolate drug stress in E. coli Nissle1917.
Fig. 2: Genetic and biomimetic synthesis support for the colipterin pathway.
Fig. 3: Immunomodulatory activities of the colipterins.
Fig. 4: Colipterins reduce colitis severity in an IL-10-dependent manner.

Data availability

HR–ESI–Q–TOF–MS/MS datasets for colipterins are available from GNPS public MassIVE under accession no. MSV000085621. CP3 analysis was facilitated by applets provided by the Goodman Group (http://www-jmg.ch.cam.ac.uk/tools/nmr/CP3.html). Supplementary Information and Source data are provided with this Letter. Additional data that support the findings of this study are available from the corresponding author upon reasonable request.

Code availability

No custom code was used.

References

  1. Blount, Z. D. The unexhausted potential of E. coli. eLife 4, e05826 (2015).

    PubMed Central  Google Scholar 

  2. Kaper, J. B., Nataro, J. P. & Mobley, H. L. Pathogenic Escherichia coli. Nat. Rev. Microbiol. 2, 123–140 (2004).

    CAS  PubMed  Google Scholar 

  3. Tenaillon, O., Skurnik, D., Picard, B. & Denamur, E. The population genetics of commensal Escherichia coli. Nat. Rev. Microbiol. 8, 207–217 (2010).

    CAS  PubMed  Google Scholar 

  4. Wassenaar, T. M. Insights from 100 years of research with probiotic E. coli. Eur. J. Microbiol. Immunol. 6, 147–161 (2016).

    Google Scholar 

  5. Mirsepasi-Lauridsen, H. C., Vallance, B. A., Krogfelt, K. A. & Petersen, A. M. Escherichia coli pathobionts associated with inflammatory bowel disease. Clin. Microbiol. Rev. 32, e00060-18 (2019).

    PubMed  PubMed Central  Google Scholar 

  6. Smilack, J. D. Trimethoprim-sulfamethoxazole. Mayo Clin. Proc. 74, 730–734 (1999).

    CAS  PubMed  Google Scholar 

  7. Stallmach, A. et al. Medical and surgical therapy of inflammatory bowel disease in the elderly—prospects and complications. J. Crohns Colitis 5, 177–188 (2011).

    PubMed  Google Scholar 

  8. Haußmann, C. et al. Biosynthesis of pteridines in Escherichia coli. Structural and mechanistic similarity of dihydroneopterin-triphosphate epimerase and dihydroneopterin aldolase. J. Biol. Chem. 273, 17418–17424 (1998).

    PubMed  Google Scholar 

  9. Giladi, M. et al. FolM, a new chromosomally encoded dihydrofolate reductase in Escherichia coli. J. Bacteriol. 185, 7015–7018 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Pribat, A. et al. FolX and FolM are essential for tetrahydromonapterin synthesis in Escherichia coli and Pseudomonas aeruginosa. J. Bacteriol. 192, 475–482 (2010).

    CAS  PubMed  Google Scholar 

  11. Gelfand, D. H. & Steinberg, R. A. Escherichia coli mutants deficient in the aspartate and aromatic amino acid aminotransferases. J. Bacteriol. 130, 429–440 (1977).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Lobritz, M. A. et al. Antibiotic efficacy is linked to bacterial cellular respiration. Proc. Natl Acad. Sci. USA 112, 8173–8180 (2015).

    CAS  PubMed  Google Scholar 

  13. Belenky, P. et al. Bactericidal antibiotics induce toxic metabolic perturbations that lead to cellular damage. Cell. Rep. 13, 968–980 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Mitosch, K., Rieckh, G. & Bollenbach, T. Noisy response to antibiotic stress predicts subsequent single-cell survival in an acidic environment. Cell. Syst. 4, 393–403 (2017).

    CAS  PubMed  Google Scholar 

  15. Zampieri, M., Zimmermann, M., Claassen, M. & Sauer, U. Nontargeted metabolomics reveals the multilevel response to antibiotic perturbations. Cell. Rep. 19, 1214–1228 (2017).

    CAS  PubMed  Google Scholar 

  16. Zampieri, M. et al. Metabolic constraints on the evolution of antibiotic resistance. Mol. Syst. Biol. 13, 917 (2017).

    PubMed  PubMed Central  Google Scholar 

  17. Zampieri, M. et al. High-throughput metabolomic analysis predicts mode of action of uncharacterized antimicrobial compounds. Sci. Transl. Med. 10, eaal3973 (2018).

    PubMed  PubMed Central  Google Scholar 

  18. Zampieri, M. et al. Regulatory mechanisms underlying coordination of amino acid and glucose catabolism in Escherichia coli. Nat. Commun. 10, 3354 (2019).

    PubMed  PubMed Central  Google Scholar 

  19. Anuforom, O., Wallace, G. R. & Piddock, L. V. The immune response and antibacterial therapy. Med. Microbiol. Immunol. 204, 151–159 (2015).

    CAS  PubMed  Google Scholar 

  20. Rubin, B. K. & Tamaoki, J. Antibiotics as Anti-inflammatory and Immunomodulatory Agents (Springer Science & Business Media, 2005).

  21. Cho, I. et al. Antibiotics in early life alter the murine colonic microbiome and adiposity. Nature 488, 621–626 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  23. Lopez, C. A., Kingsbury, D. D., Velazquez, E. M. & Bäumler, A. J. Collateral damage: microbiota-derived metabolites and immune function in the antibiotic era. Cell Host Microbe 16, 156–163 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Becattini, S., Taur, Y. & Pamer, E. G. Antibiotic-induced changes in the intestinal microbiota and disease. Trends Mol. Med. 22, 458–478 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Dornisch, E. et al. Biosynthesis of the enterotoxic pyrrolobenzodiazepine natural product tilivalline. Angew. Chem. Int. Ed. 56, 14753–14757 (2017).

    CAS  Google Scholar 

  26. Routy, B. et al. Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors. Science 359, 91–97 (2018).

    CAS  Google Scholar 

  27. Yang, J. H. et al. Antibiotic-induced changes to the host metabolic environment inhibit drug efficacy and alter immune function. Cell Host Microbe 22, 757–765 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Gopinath, S. et al. Topical application of aminoglycoside antibiotics enhances host resistance to viral infections in a microbiota-independent manner. Nat. Microbiol. 3, 611–621 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Park, H. B. et al. Bacterial autoimmune drug metabolism transforms an immunomodulator into structurally and functionally divergent antibiotics. Angew. Chem. Int. Ed. 59, 2–12 (2020).

    Google Scholar 

  30. Oh, J., Patel, J., Park, H. B. & Crawford, J. M. β-Lactam biotransformations activate innate immunity. J. Org. Chem. 83, 7173–7179 (2018).

    CAS  PubMed  Google Scholar 

  31. Wormser, G. P., Keusch, G. T. & Heel, R. C. Co-trimoxazole (trimethoprim-sulfamethoxazole): an updated review of its antibacterial activity and clinical efficacy. Drugs 24, 459–518 (1982).

    CAS  PubMed  Google Scholar 

  32. Baker, D. J. et al. The binding of trimethoprim to bacterial dihydrofolate reductase. FEBS Lett. 126, 49–52 (1981).

    CAS  PubMed  Google Scholar 

  33. Achari, A. et al. Crystal structure of the anti-bacterial sulfonamide drug target dihydropteroate synthase. Nat. Struct. Biol. 4, 490–497 (1997).

    CAS  PubMed  Google Scholar 

  34. Okada, B. K. & Seyedsayamdost, M. R. Antibiotic dialogues: induction of silent biosynthetic gene clusters by exogenous small molecules. FEMS Microbiol. Rev. 41, 19–33 (2017).

    CAS  PubMed  Google Scholar 

  35. Kim, C. S. et al. Characterization of autoinducer-3 atructure and biosynthesis in E. coli. ACS Cent. Sci. 6, 197–206 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Nougayrède, J. P. et al. Escherichia coli induces DNA double-strand breaks in eukaryotic cells. Science 313, 848–851 (2006).

    PubMed  Google Scholar 

  37. Xue, M. et al. Structure elucidation of colibactin and its DNA cross-links. Science 365, eaax2685 (2019).

  38. Arthur, J. C. et al. Intestinal inflammation targets cancer-inducing activity of the microbiota. Science 338, 120–123 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Arthur, J. C. et al. Microbial genomic analysis reveals the essential role of inflammation in bacteria-induced colorectal cancer. Nat. Commun. 5, 4724 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Cougnoux, A. et al. Small-molecule inhibitors prevent the genotoxic and protumoural effects induced by colibactin-producing bacteria. Gut 65, 278–285 (2016).

    CAS  PubMed  Google Scholar 

  41. Tomkovich, S. et al. Locoregional effects of microbiota in a preclinical model of colon carcinogenesis. Cancer Res. 77, 2620–2632 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Dejea, C. M. et al. Patients with familial adenomatous polyposis harbor colonic biofilms containing tumorigenic bacteria. Science 359, 592–597 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Wiegand, I., Hilpert, K. & Hancock, R. E. Agar and broth dilution methods to determine the minimal inhibitory concentration (MIC) of antimicrobial substances. Nat. Protoc. 3, 163–175 (2008).

    CAS  PubMed  Google Scholar 

  44. Thomas, A. H. et al. Fluorescence of pterin, 6-formylpterin, 6-carboxypterin and folic acid in aqueous solution: pH effects. Photochem. Photobiol. Sci. 1, 421–426 (2002).

    CAS  PubMed  Google Scholar 

  45. Kim, Y., Kang, Y. & Baek, D. Oxidative synthesis of benzoylpteridines from benzylpteridines by potassium penmanganate. Bull. Korean Chem. Soc. 22, 141–144 (2001).

    CAS  Google Scholar 

  46. Bermingham, A. & Derrick, J. P. The folic acid biosynthesis pathway in bacteria: evaluation of potential for antibacterial drug discovery. Bioessays 24, 637–648 (2002).

    CAS  PubMed  Google Scholar 

  47. de Crécy-Lagard, V. et al. Comparative genomics of bacterial and plant folate synthesis and salvage: predictions and validations. BMC Genomics 8, 245 (2007).

    PubMed  PubMed Central  Google Scholar 

  48. Feirer, N. et al. A pterin-dependent signaling pathway regulates a dual-function diguanylate cyclase-phosphodiesterase controlling surface attachment in Agrobacterium tumefaciens. mBio 6, e00156-15 (2015).

    PubMed  PubMed Central  Google Scholar 

  49. Ahn, C., Byun, J. & Yim, J. Purification, cloning, and functional expression of dihydroneopterin triphosphate 2′-epimerase from Escherichia coli. J. Biol. Chem. 272, 15323–15328 (1997).

    CAS  PubMed  Google Scholar 

  50. Shan, Y. et al. Genetic basis of persister tolerance to aminoglycosides in Escherichia coli. mBio 6, e00078-15 (2015).

    PubMed  PubMed Central  Google Scholar 

  51. Mathieu, A. et al. Discovery and function of a general core hormetic stress response in E. coli induced by sublethal concentrations of antibiotics. Cell. Rep. 17, 46–57 (2016).

    CAS  PubMed  Google Scholar 

  52. Kim, C. S. et al. Cellular stress upregulates indole signaling metabolites in Escherichia coli. Cell Chem. Biol. 27, 698–707 (2020).

    CAS  PubMed  Google Scholar 

  53. Perez, C. E., Park, H. B. & Crawford, J. M. Functional characterization of a condensation domain that links nonribosomal peptide and pteridine biosynthetic machineries in Photorhabdus luminescens. Biochemistry 57, 354–361 (2018).

    CAS  PubMed  Google Scholar 

  54. Brown, G. M. The biosynthesis of pteridines. Adv. Enzymol. Relat. Areas Mol. Biol 35, 35–77 (1971).

  55. Nichol, C. A. et al. Biosynthesis of tetrahydrobiopterin by de novo and salvage pathways in adrenal medulla extracts, mammalian cell cultures, and rat brain in vivo. Proc. Natl Acad. Sci. USA 80, 1546–1550 (1983).

    CAS  PubMed  Google Scholar 

  56. Groehn, V. et al. Pteridine-based photoaffinity probes for nitric oxide synthase and aromatic amino acid hydroxylases. Helv. Chim. Acta 83, 2738–2750 (2000).

    CAS  Google Scholar 

  57. Crabtree, M. J. et al. Critical role for tetrahydrobiopterin recycling by dihydrofolate reductase in regulation of endothelial nitric-oxide synthase coupling: relative importance of the de novo biopterin synthesis versus salvage pathways. J. Biol. Chem. 284, 28128–28136 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  58. Kirsch, M. et al. The autoxidation of tetrahydrobiopterin revisited. Proof of superoxide formation from reaction of tetrahydrobiopterin with molecular oxygen. J. Biol. Chem. 278, 24481–24490 (2003).

    CAS  PubMed  Google Scholar 

  59. Oettl, K. & Reibnegger, G. Pteridines as inhibitors of xanthine oxidase: structural requirements. Biochim. Biophys. Acta 1430, 387–395 (1999).

    CAS  PubMed  Google Scholar 

  60. Vásquez-Vivar, J. Tetrahydrobiopterin, superoxide, and vascular dysfunction. Free Radic. Biol. Med. 47, 1108–1119 (2009).

    PubMed  PubMed Central  Google Scholar 

  61. Kojima, S., Icho, T., Mori, H. & Arai, T. Enhancing potency of neopterin toward B-16 melanoma cell damage induced by UV-A irradiation and its possible application for skin tumor treatment. Anticancer Res. 15, 1975–1980 (1995).

    CAS  PubMed  Google Scholar 

  62. Becker, C., Fantini, M. C. & Neurath, M. F. High resolution colonoscopy in live mice. Nat. Protoc. 1, 2900–2904 (2006).

    CAS  PubMed  Google Scholar 

  63. Dorrestein, P. C., Mazmanian, S. K. & Knight, R. Finding the missing links among metabolites, microbes, and the host. Immunity 40, 824–832 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. Kruis, W. et al. Maintaining remission of ulcerative colitis with the probiotic Escherichia coli Nissle 1917 is as effective as with standard mesalazine. Gut 53, 1617–1623 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  65. Palmela, C. et al. Adherent-invasive Escherichia coli in inflammatory bowel disease. Gut 67, 574–587 (2018).

    CAS  PubMed  Google Scholar 

  66. Rembacken, B. J. et al. Non-pathogenic Escherichia coli versus mesalazine for the treatment of ulcerative colitis: a randomised trial. Lancet 354, 635–639 (1999).

    CAS  PubMed  Google Scholar 

  67. Smith, S. G. & Goodman, J. M. Assigning the stereochemistry of pairs of diastereoisomers using GIAO NMR shift calculation. J. Org. Chem. 74, 4597–4607 (2009).

    CAS  PubMed  Google Scholar 

  68. Kamanaka, M. et al. Expression of interleukin-10 in intestinal lymphocytes detected by an interleukin-10 reporter knockin tiger mouse. Immunity 25, 941–952 (2006).

    CAS  PubMed  Google Scholar 

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Acknowledgements

This work was supported by the National Institutes of Health (nos. 1DP2-CA186575 and R00-GM097096 to J.M.C.), the Burroughs Wellcome Fund (no. 1016720 to J.M.C.), the Camille & Henry Dreyfus Foundation (no. TC-17-011 to J.M.C.), the Howard Hughes Medical Institute (to R.A.F.) and the Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education (no. 2019R1A6A3A12033304 to C.S.K.). Z.W. was supported by the China Scholarship Council.

Author information

Authors and Affiliations

Authors

Contributions

H.B.P. and J.M.C. conceived the study and designed the metabolism experiments. H.B.P. characterized the colipterin pathway from E. coli by drug stress, metabolome analysis, isolation, structure characterization, synthesis, genetic complementation and antioxidant assays. Z.W. performed ELISA assays for IL-8/-10 and all mouse studies. J.O. performed CP3 computational analysis on colipterins 1/2 and contributed to colipterin accumulation and NMR measurements. H.X. maintained the IL-10eGFP mice, isolated immune cells from the small intestine and analysed FACS data for IL-10 expression. C.S.K. constructed double-mutant strains of aspC and tyrB. R.W., T.P.W. and G.P. contributed to BioMap analysis of colipterins. R.A.F. conceived and supervised in vivo mouse studies. H.B.P. and J.M.C. wrote the manuscript with input from all authors. All authors reviewed and edited the manuscript.

Corresponding authors

Correspondence to Richard A. Flavell or Jason M. Crawford.

Ethics declarations

Competing interests

R.A.F. is a recipient of a grant from AbbVie, Inc. R.W., T.P.W. and G.P. are employees of Merck Exploratory Science Center, Merck & Co., Inc., Kenilworth, NJ, USA. Employees may hold stocks and/or stock options in Merck & Co., Inc., Kenilworth, NJ, USA. The remaining authors declare no competing interests.

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Extended data

Extended Data Fig. 1 UV-LC-MS detection of colipterins 1-8 produced by the probiotic E. coli Nissle1917.

a, Dose-responses of 1-8 from the probiotic E. coli Nissle1917 exposed to the sub-lethal levels of sulfamethoxazole (SMX). Intensity was determined by extracted ion counts (EICs) with m/z corresponding to each colipterin within a 10 ppm error window. High-resolution ESI-QTOF-LC-MS spectra of samples were analyzed using Phenomenex Kinetex C18 (100 Å) 5 μm (250 × 4.6 mm) column with a gradient from 10%-100% aqueous acetonitrile in 0.1% formic acid over 30 min and with a 0.7 ml min-1 flow rate. Data were collected in biological triplicate, and representative EIC chromatograms are shown. b, UV-Vis spectra of colipterins 1-8 and pterin.

Extended Data Fig. 2 Production profiles of colipterins from E. coli Nissle1917 cultures.

a, Time-course analyses of major colipterins 1-4 from E. coli Nissle1917 cultures. Peaks were extracted using the EIC method corresponding to the m/z of 1-4 within a 10 ppm window. The mean and s.d. (error bars) from three biological experiments (n = 3) are shown. Statistical significance (two-tailed unpaired t-test) is compared to 12 h; nd, not detected. b, Detection of col253 (3) and col267 (4) from the cell pellet extracts. SMX was supplemented into E. coli cultures with a sub-lethal concentration of 200 μg ml-1. Representative data from 24 h cultures are given from three biological replicates (n = 3). The mean and s.d. (error bars) are presented. A two-tailed unpaired t-test was used to calculate P values. Concentrations of 3 and 4 in cell pellet extracts without (and with SMX 200 μg ml-1) drug stress are as follows: 3, ~ 0.7 (~ 4.0) μM; 4, ~ 0.3 (~ 4.8) μM. c, Calibration curves for the colipterin quantification. Concentrations of 1-8 in culture without (and with SMX 400 μg ml-1) drug stress are as follows: 1, ~ 0.2 (~ 1.0) μM; 2, ~ 0.3 (~ 1.5) μM; 3, ~ 2.0 (~ 7.1) μM; 4, ~ 1.3 (~ 5.3) μM; 5, ~ 0.06 (~ 0.2) μM; 6, nd (~ 0.6) μM; 8, ~ 0.07 (~ 0.2) μM. 7 oxidized to 8 in the methanol solution during the acquisition of Q-TOF-MS experiments. Data are shown as the mean ± s.d., n = 3 from 3 technical triplicates.

Source data

Extended Data Fig. 3 Sulfamethoxazole (SMX) drug stress responses of colipterins 1–8 in the pathogenic E. coli LF82 and commensalistic E. coli BW25113.

Yellow area for optical density (OD600) measurement represents a range of sub-lethal concentrations of SMX against both E. coli LF82 (a) and BW25113 (b) strains. Peaks were extracted using EIC method corresponding to the m/z of colipterins 18 within a 10 ppm window. Red and black lines indicate Ctrl (Control, no SMX treatment) and SMX, respectively, in the MS chromatogram. Intensities in the bar graphs indicate integration value of EIC peak area. The mean and s.d. (error bars) from three biological experiments (n = 3) are shown. P values were analyzed by a two-tailed unpaired t-test; ns, not significant.

Source data

Extended Data Fig. 4 Functional characterization of FolX and FolM involved in colipterin production.

a, Folate and monapterin pathway are shown. b, Genetic complementation of folX and folM. Note that the production of colipterins is abolished in ΔfolX and ΔfolM strains. While the colipterins were not detected in both ΔfolX and ΔfolM carrying pBAD empty vector, complementation of folX and folM in pBAD into ΔfolX and ΔfolM strains, respectively, resulted in the recovery of major colipterins 3 and 4 production. 24 h E. coli cultures were analyzed by high-resolution ESI-QTOF-LC-MS using Phenomenex Kinetex C18 (100 Å) 5 μm (250 × 4.6 mm) column with a gradient from 10%-100% aqueous acetonitrile in 0.1% formic acid over 30 min and with a 0.7 ml min-1 flow rate. Data are mean ± s.d. from three biological replicates (n = 3); nd, not detected.

Extended Data Fig. 5 UV-LC-MS profiles of biomimetic synthesis of colipterins in various conditions.

a, Differential production of 5 and 6 from the tetrahydropterin (THP)-phenylpyruvate (PP) coupling reaction. 5 and 6 were observed to be major products from the reaction in pH 5.0 and pH 6.0 in water, respectively. b, 3 (m/z 254.1042) and 4 (m/z 268.0834) from the reaction with THP in the presence of initially expected substrate, phenylacetic acid (PA), were not observed. c, Individual incubation of 3, 4, 5, and 6 in methanol at room temperature for 12 h was monitored by HPLC. While 4 was most stable, 5 and 6 were interconvertible and irreversibly degraded to 3 and 4 as anticipated. Image for 4 is not shown. d, 7 (~0.5 mg) in 2 ml methanol was incubated at room temperature for 96 h and analyzed at five different time-points (6, 24, 48, 72, and 96 h). Auto-oxidation of 7 to 8 was observed over time. Image for the color change of 7 (colorless) to 8 (yellow) is shown in inset. e, Demonstration of the oxidation state of the pterin reactant. Independent reactions with pterin-PP and THP-PP were performed. While colipterins were not detected in reactions with pterin as expected, a reaction with THP in the presence of oxygen led to the colipterins. Representatively, 3 and 4 are shown. f, Reaction with THP under anaerobic conditions in vitro yielded either no detectable levels or basal levels of production. The reaction materials were analyzed by LC-MS with Phenomenex Kinetex C18 (100 Å) 5 μm (250 × 4.6 mm) column with a gradient from 10%-100% acetonitrile in water containing 0.1% formic acid for 30 min and with a 0.7 ml min-1 flow rate. All reaction was analyzed by UV (254 and 310 nm) and MS using EIC method.

Extended Data Fig. 6 Pterin profile for the demonstration of DHP substrate origins.

a, Previously described recycling and side-chain cleavage mechanism of biopterin in mammalian cells. Pterin and 7,8-dihydroxanthopterin (XPH2) are known as break-down products of biopterin. Similarly, we observed pterin (m/z 164.0572) and XPH2 (m/z 182.0678) in the BH4 in vitro chemical reaction via hydrogenation of commercial BH2 followed by aerobic incubation in water, but not in the BH2 solution. Additionally, colipterins were detected in BH4 solution supplemented with PP. Representatively, col327 (6) (m/z 328.1046) is shown. b, Upregulation of pterin and XPH2 in E. coli Nissle1917 in response to the sub-lethal levels of SMX. Dose-responses of pterin and XPH2 in antifolate SMX stress. The mean and s.d. (error bars) from three biological experiments (n = 3) are shown. Statistical significance was accessed using a two-tailed unpaired t-test. MS intensity of EIC chromatogram was determined by ion counts corresponding to pterin ((M + H)+ m/z 164.0572) and XPH2 ((M + H)+ m/z 182.0678) within a 10 ppm error window. High-resolution ESI-QTOF-LC-MS spectra of samples were analyzed using Phenomenex Kinetex C18 (100 Å) 5 μm (250 × 4.6 mm) column with a gradient from 10%-100% aqueous acetonitrile in 0.1% formic acid over 30 min and with a 0.7 ml min-1 flow rate.

Source data

Extended Data Fig. 7 E. coli BW25113 exposed to SMX drug stress reduce colitis severity in an IL-10-dependent manner.

a, Primary evaluation on the reduction of colitis severity in SMX-treated colitis mice (IL-10+/+ and IL-10-/-) that were colonized with E. coli (wild-type E. coli BW25113 and its folM mutant strain). CFUs, body weight, and clinical scores were obtained as the same procedure that we described in Fig. 4. HR-ESI-QTOF-MS quantification of colipterins 3 and 6 in stool samples. P values were determined by a two-tailed unpaired t-test. Error bars represent mean ± s.e.m.; ns, not significant. b, Effects of SMX-treated E. coli (wild-type E. coli BW25113 and its folM mutant strain) in the IL-10-/- male and female mice that spontaneously develop colitis. IL-10+/+ male and female mice that do not develop spontaneous colitis were used as control groups. E. coli was colonized at week-3. CFUs were measured at 3 weeks after colonization. Body weight was monitored weekly. SMX was mixed in the drinking water at 0.3 mg ml−1 after the E. coli colonization. At week-10, endoscopy was performed and clinical scores were used as a metric of colitis severity. Data are presented by mean ± s.e.m. (error bars).

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Park, H.B., Wei, Z., Oh, J. et al. Sulfamethoxazole drug stress upregulates antioxidant immunomodulatory metabolites in Escherichia coli. Nat Microbiol 5, 1319–1329 (2020). https://doi.org/10.1038/s41564-020-0763-4

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