Abstract
The gut microbiome has major roles in modulating host physiology. One such function is colonization resistance, or the ability of the microbial collective to protect the host against enteric pathogens1,2,3, including enterohaemorrhagic Escherichia coli (EHEC) serotype O157:H7, an attaching and effacing (AE) food-borne pathogen that causes severe gastroenteritis, enterocolitis, bloody diarrhea and acute renal failure4,5 (haemolytic uremic syndrome). Although gut microorganisms can provide colonization resistance by outcompeting some pathogens or modulating host defence provided by the gut barrier and intestinal immune cells6,7, this phenomenon remains poorly understood. Here, we show that activation of the neurotransmitter receptor dopamine receptor D2 (DRD2) in the intestinal epithelium by gut microbial metabolites produced upon dietary supplementation with the essential amino acid l-tryptophan protects the host against Citrobacter rodentium, a mouse AE pathogen that is widely used as a model for EHEC infection8,9. We further find that DRD2 activation by these tryptophan-derived metabolites decreases expression of a host actin regulatory protein involved in C. rodentium and EHEC attachment to the gut epithelium via formation of actin pedestals. Our results reveal a noncanonical colonization resistance pathway against AE pathogens that features an unconventional role for DRD2 outside the nervous system in controlling actin cytoskeletal organization in the gut epithelium. Our findings may inspire prophylactic and therapeutic approaches targeting DRD2 with dietary or pharmacological interventions to improve gut health and treat gastrointestinal infections, which afflict millions globally.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 51 print issues and online access
$199.00 per year
only $3.90 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Data availability
Next-generation sequencing reads have been deposited at NCBI BioProject under accession number PRJNA1049399. Source data are provided with this paper.
Code availability
R script for statistical analysis, box pots, and QIIME2 code are available at https://zenodo.org/records/10535214.
References
Buffie, C. G. & Pamer, E. G. Microbiota-mediated colonization resistance against intestinal pathogens. Nat. Rev. Immunol. 13, 790–801 (2013).
McKenney, P. T. & Pamer, E. G. From hype to hope: the gut microbiota in enteric infectious disease. Cell 163, 1326–1332 (2015).
Caballero, S. & Pamer, E. G. Microbiota-mediated inflammation and antimicrobial defense in the intestine. Annu. Rev. Immunol. 33, 227–256 (2015).
Croxen, M. A. & Finlay, B. B. Molecular mechanisms of Escherichia coli pathogenicity. Nat. Rev. Microbiol. 8, 26–38 (2010).
Kaper, J. B., Nataro, J. P. & Mobley, H. L. T. Pathogenic Escherichia coli. Nat. Rev. Microbiol. 2, 123–140 (2004).
Kamada, N. et al. Regulated virulence controls the ability of a pathogen to compete with the gut microbiota. Science 336, 1325–1329 (2012).
Willing, B. P., Vacharaksa, A., Croxen, M., Thanachayanont, T. & Finlay, B. B. Altering host resistance to infections through microbial transplantation. PLoS ONE 6, 2–10 (2011).
Collins, J. W. et al. Citrobacter rodentium: infection, inflammation and the microbiota. Nat. Rev. Microbiol. 12, 612–623 (2014).
Mullineaux-Sanders, C. et al. Citrobacter rodentium–host–microbiota interactions: immunity, bioenergetics and metabolism. Nat. Rev. Microbiol. 17, 701–715 (2019).
Garmendia, J., Frankel, G. & Crepin, V. F. Enteropathogenic and enterohemorrhagic Escherichia coli infections: translocation, translocation, translocation. Infect. Immun. 73, 2573–2585 (2005).
Battle, S. E., Brady, M. J., Vanaja, S. K., Leong, J. M. & Hecht, G. A. Actin pedestal formation by enterohemorrhagic Escherichia coli enhances bacterial host cell attachment and concomitant type III translocation. Infect. Immun. 82, 3713–3722 (2014).
Mallick, E. M. et al. The ability of an attaching and effacing pathogen to trigger localized actin assembly contributes to virulence by promoting mucosal attachment. Cell Microbiol. 16, 1405–1424 (2014).
Law, R. J., Gur-Arie, L., Rosenshine, I. & Finlay, B. B. In vitro and in vivo model systems for studying enteropathogenic Escherichia coli infections. Cold Spring Harb. Perspect. Med. 3, a009977–a009977 (2013).
Dorrestein, P. C., Mazmanian, S. K. & Knight, R. Finding the missing links among metabolites, microbes, and the host. Immunity 40, 824–832 (2014).
Donia, M. S. & Fischbach, M. A. Small molecules from the human microbiota. Science 349, 1254766 (2015).
Furusawa, Y. et al. Commensal microbe-derived butyrate induces the differentiation of colonic regulatory T cells. Nature 504, 446–450 (2013).
Smith, P. M. et al. The microbial metabolites, short-chain fatty acids, regulate colonic Treg cell homeostasis. Science 341, 569–573 (2013).
Arpaia, N. et al. Metabolites produced by commensal bacteria promote peripheral regulatory T-cell generation. Nature 504, 451–455 (2013).
Zhao, L. et al. Gut bacteria selectively promoted by dietary fibers alleviate type 2 diabetes. Science 359, 1151–1156 (2018).
Hang, S. et al. Bile acid metabolites control TH17 and Treg cell differentiation. Nature 576, 143–148 (2019).
Bender, M. J. et al. Dietary tryptophan metabolite released by intratumoral Lactobacillus reuteri facilitates immune checkpoint inhibitor treatment. Cell 186, 1846–1862 (2023).
Rangan, K. J. & Hang, H. C. Biochemical mechanisms of pathogen restriction by intestinal bacteria. Trends Biochem. Sci. 42, 887–898 (2017).
Chang, P. V. Chemical mechanisms of colonization resistance by the gut microbial metabolome. ACS Chem. Biol. 15, 1119–1126 (2020).
Rooks, M. G. & Garrett, W. S. Gut microbiota, metabolites and host immunity. Nat. Rev. Immunol. 16, 341–352 (2016).
Postler, T. S. & Ghosh, S. Understanding the holobiont: how microbial metabolites affect human health and shape the immune system. Cell Metab. 26, 110–130 (2017).
Belkaid, Y. & Hand, T. W. Role of the microbiota in immunity and inflammation. Cell 157, 121–141 (2014).
Brestoff, J. R. & Artis, D. Commensal bacteria at the interface of host metabolism and the immune system. Nat. Immunol. 14, 676–684 (2013).
Scott, S. A., Fu, J. & Chang, P. V. Microbial tryptophan metabolites regulate gut barrier function via the aryl hydrocarbon receptor. Proc. Natl Acad. Sci. USA 117, 19376–19387 (2020).
Kumar, A. & Sperandio, V. Indole signaling at the host–microbiota–pathogen interface. MBio 10, e01031–19 (2019).
Bansal, T., Alaniz, R. C., Wood, T. K. & Jayaraman, A. The bacterial signal indole increases epithelial-cell tight-junction resistance and attenuates indicators of inflammation. Proc. Natl Acad. Sci. USA 107, 228–233 (2010).
Bommarius, B. et al. A family of indoles regulate virulence and Shiga toxin production in pathogenic E. coli. PLoS ONE 8, e54456–16 (2013).
Keiser, M. J. et al. Relating protein pharmacology by ligand chemistry. Nat. Biotechnol. 25, 197–206 (2007).
Missale, C., Russel Nash, S., Robinson, S. W., Jaber, M. & Caron, M. G. Dopamine receptors: from structure to function. Physiol. Rev. 78, 189–225 (1998).
Beaulieu, J. & Gainetdinov, R. R. The physiology, signaling, and pharmacology of dopamine receptors. Pharmacol. Rev. 63, 182–217 (2011).
Kulagowski, J. J. et al. 3-[[4-(4-Chlorophenyl)piperazin-1-yl]-methyl]-1H-pyrrolo[2,3-b]pyridine: an antagonist with high affinity and selectivity for the human dopamine D4 receptor. J. Med. Chem. 39, 1941–1942 (1996).
Binkowski, B. F. et al. A luminescent biosensor with increased dynamic range for intracellular cAMP. ACS Chem. Biol. 6, 1193–1197 (2011).
Barnea, G. et al. The genetic design of signaling cascades to record receptor activation. Proc. Natl Acad. Sci. USA 105, 64–69 (2008).
Murata, K., Noda, K., Kohno, K. & Samejima, M. Bioavailability and pharmacokinetics of oral dopamine in dogs. J. Pharm. Sci. 77, 565–568 (1988).
Alex, K. D. & Pehek, E. A. Pharmacologic mechanisms of serotonergic regulation of dopamine neurotransmission. Pharmacol. Ther. 113, 296–320 (2007).
Łukasiewicz, S., Błasiak, E., Szafran-Pilch, K. & Dziedzicka-Wasylewska, M. Dopamine D2 and serotonin 5-HT1A receptor interaction in the context of the effects of antipsychotics—in vitro studies. J. Neurochem. 137, 549–560 (2016).
Kumar, A. et al. The serotonin neurotransmitter modulates virulence of enteric pathogens. Cell Host Microbe 28, 41–53 (2020).
Suetsugu, S. et al. Sustained activation of N-WASP through phosphorylation is essential for neurite extension. Dev. Cell 3, 645–658 (2002).
Sasahara, Y. et al. Mechanism of recruitment of WASP to the immunological synapse and of its activation following TCR ligation. Mol. Cell 10, 1269–1281 (2002).
Martinez-Quiles, N. et al. WIP regulates N-WASP-mediated actin polymerization and filopodium formation. Nat. Cell Biol. 3, 484–491 (2001).
Desai, M. S. et al. A dietary fiber-deprived gut microbiota degrades the colonic mucus barrier and enhances pathogen susceptibility. Cell 167, 1339–1353 (2016).
Schulthess, J. et al. The short chain fatty acid butyrate imprints an antimicrobial program in macrophages. Immunity 50, 432–445 (2019).
Chen, H. et al. A forward chemical genetic screen reveals gut microbiota metabolites that modulate host physiology. Cell 177, 1217–1231.e18 (2019).
Colosimo, D. A. et al. Mapping interactions of microbial metabolites with human G-protein-coupled receptors. Cell Host Microbe 26, 273–282 (2019).
Zhao, X. et al. Chemoproteomics reveals microbiota-derived aromatic monoamine agonists for GPRC5A. Nat. Chem. Biol. 19, 1205–1214 (2023).
Thompson, L. R. et al. A communal catalogue reveals Earth’s multiscale microbial diversity. Nature 551, 457–463 (2017).
Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37, 852–857 (2019).
Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).
DeSantis, T. Z. et al. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl. Environ. Microbiol. 72, 5069–5072 (2006).
Acknowledgements
The authors thank the Arnold and Mabel Beckman Foundation (Beckman Young Investigator Award to P.V.C.) and a President’s Council for Cornell Women Affinito-Stewart Grant (P.V.C.) for support. This work was supported in part by a grant from the National Institutes of Health (NIH R35GM133501). J.F. was supported by a Cornell Institute of Host-Microbe Interactions and Disease (CIHMID) Postdoctoral Fellowship. Imaging data was acquired through the Cornell Institute of Biotechnology BRC Imaging Facility (RRID:SCR_021741), with NYSTEM (C029155) and NIH (S10OD018516) funding for the shared Zeiss LSM 880 confocal/multiphoton microscope. We thank the Weill Institute for Cell and Molecular Biology for additional resources and reagents.
Author information
Authors and Affiliations
Contributions
S.A.S. and P.V.C. conceptualized the study. S.A.S., J.F. and P.V.C. designed the experiments. J.F. performed the targeted metabolomic studies. S.A.S. carried out all other studies and bioinformatic analyses. S.A.S., J.F. and P.V.C. wrote the manuscript.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Peer review
Peer review information
Nature thanks Vanessa Sperandio and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Additional information
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 The Trp metabolites I3A, IPyA, and IEt protect against Citrobacter rodentium infection in mice.
C57Bl/6 mice were pre-treated with antibiotics (ABX) for 7 d, followed by Trp metabolites, I3A (1000 mg/kg), IPyA (2900 mg/kg), or IEt (600 mg/kg) by oral gavage daily for 2 d. The mice were then administered C. rodentium (CR, oral gavage, 108 CFU) with continued ABX (except neomycin) and metabolite treatment for 10 d. Colon sections were stained with H&E. Shown are representative images. Scale bar: 50 μm. Data are representative of at least 3 independent experiments, n = 10 mice per group.
Extended Data Fig. 2 Tryptophan metabolites do not affect C. rodentium and EHEC growth and virulence in vitro.
C. rodentium (CR) (a–e) and EHEC O157:H7 (f–k) were cultured in the presence of I3A, IPyA, or IEt (100 μM). a, f, Growth was monitored by measuring OD600 absorbance readings over 24 h. b, g, Cultures were plated after 24 h, and CFUs were counted. (c–e, h–k) Bacteria were cultured in low glucose DMEM under anaerobic (ana), microaerophilic (micro), and aerobic (aero) conditions to activate locus of enterocyte effacement-pathogenicity island expression with I3A, IPyA, or IEt (100 μM). RNA was isolated after cultures reached late-log phase (OD600 = 0.6–0.8), and cDNA was synthesized and analyzed by qPCR for the indicated genes. Relative expression of mRNA transcripts was normalized to the RNA polymerase subunit alpha rpoA. Data are represented as the fold induction over control samples, bars = mean, error bars = standard deviation. Statistical analysis was performed using a two-tailed Student’s t-test (a–b, f–g), or one-way ANOVA, followed by post-hoc Tukey multiple comparison test (c–e, h–k), n = 3 biological replicates examined over 3 independent experiments.
Extended Data Fig. 3 Effects of I3A, IPyA, and IEt depend on dopamine receptor D2 (DRD2).
a–b, Polarized Caco-2 monolayers were pre-treated with haloperidol (HAL, 10 μM) for 24 h, followed by metabolites (I3A, IPyA, or IEt, 100 μM) for 2 d, and then infection with EHEC O157:H7 for 16 h. b, Representative images of pedestals (denoted by arrows) from Caco-2 cells stained with DAPI and Alexa Fluor 647-phalloidin and imaged by confocal microscopy. Shown are maximum intensity z-projections. Scale bar: 5 μm. c, Western blot analysis of Caco-2 monolayers to verify CRISPR/Cas9-mediated knockout (KO) of Drd2, Drd3, and Drd4. GAPDH is shown as a loading control. d–f, Caco-2 monolayers (WT vs. KO) were pre-treated with metabolites (I3A, IPyA, or IEt, 100 μM) for 2 d and then infected with EHEC O157:H7 for 16 h. (a, d–f) Pedestal formation = # of pedestals per Caco-2 cell (HAL: I3A, n = 955; IPyA, n = 970; IEt, n = 1024; Drd3 KO: I3A, n = 1089; IPyA, n = 1094; IEt, n = 1012; Drd4 KO: I3A, n = 1032; IPyA, n = 887; IEt, n = 1026; Drd2 KO: I3A, n = 1032; IPyA, n = 1026; IEt, n = 1073 cells examined over 3 independent experiments). For box plots, interquartile ranges (IQRs, boxes), median values (line within box), whiskers (lowest and highest values within 1.5 times IQR from the first and third quartiles), and outliers beyond whiskers (dots), are shown. g-m, Caco-2 cells (WT vs KO) were pre-treated with metabolites (I3A, IPyA, or IEt, 100 μM) for 24 h and then infected with EHEC O157:H7 for 12 h. Cell lysates were analyzed by Western blotting with the indicated antibodies. Source data are provided in Supplementary Fig. 9. (h, j, l, m) Densitometry was performed using FIJI, bars = mean, error bars = standard deviation. Data are representative of at least 3 independent experiments, n = 3 biological replicates. Statistical analysis was performed using one-way ANOVA, followed by post-hoc Tukey multiple comparison test.
Extended Data Fig. 4 I3A, IPyA, and IEt are ligands of dopamine receptor D2 (DRD2), which signals via Gαi, and Drd2 is knocked out in intestinal epithelial cells in Drd2fl/fl x Villin-Cre mice fed Trp diet during C. rodentium infection.
a, c–f, HEK 293 T cells overexpressing either DRD2 and a split luciferase-based cAMP sensor (GloSensor) or b, DRD2-Tango and a β-arrestin-TEV fusion were incubated with dopamine (DA), I3A, IPyA, or IEt (1 mM each in a–b; concentrations indicated in c–f) for 15 min (a, c–f) or 24 h (b), after which luminescence was measured to quantify ligand-induced (a) decrease in cAMP or (b) increase in β-arrestin recruitment. RLU = relative luminescence units. EC50 and Kd values were calculated using GraphPad Prism. (g–h) Drd2fl/fl x Villin (Vil)-Cre or Drd2fl/fl mice were fed a conventional (2 g Trp/kg diet, ad libitum) or Trp (42 g Trp/kg diet, ad libitum) diet for 7 d and then infected with C. rodentium (CR, oral gavage, 108 CFU) with continued Trp feeding. Ten days post-infection, intestinal cryosections were stained with DAPI and an anti-DRD2 antibody, followed by an anti-mouse Alexa Fluor 594 antibody. (g) Shown are representative z-slices. Scale bar: 20 μm. (h) Image brightness was quantified using FIJI. Statistical analysis was performed using one-way ANOVA, followed by post-hoc Tukey multiple comparison test; bars = mean, error bars = standard deviation, (a–f) n = 3 biological replicates and (g–h) n = 10 mice per group examined over 3 independent experiments.
Extended Data Fig. 5 Drd2 is knocked out in intestinal epithelial cells in Drd2fl/fl x Villin-Cre mice administered Trp metabolites during C. rodentium infection.
Drd2fl/fl x Villin (Vil)-Cre or Drd2fl/fl mice were treated with Trp metabolites, I3A (1000 mg/kg), IPyA (2900 mg/kg), or IEt (600 mg/kg), by oral gavage daily for 2 d, and then infected with C. rodentium (CR, oral gavage, 108 CFU) with continued metabolite treatment. Ten days post-infection, intestinal cryosections were stained with DAPI and an anti-DRD2 antibody, followed by an anti-mouse Alexa Fluor 594 antibody. (a) Shown are representative z-slices. Scale bar: 20 μm. (b–d) Image brightness was quantified using FIJI. Data are representative of at least 3 independent experiments, n = 10 mice per group, bars = mean, error bars = standard deviation. Statistical analysis was performed using one-way ANOVA, followed by post-hoc Tukey multiple comparison test.
Extended Data Fig. 6 Effects of the tryptophan (Trp) diet and metabolites I3A, IPyA, and IEt in protecting against C. rodentium infection depend on dopamine receptor D2 (DRD2) in intestinal epithelial cells (IECs).
Drd2fl/fl x Villin (Vil)-Cre or Drd2fl/fl mice were fed a conventional (2 g Trp/kg diet, ad libitum) or Trp (42 g Trp/kg diet, ad libitum) diet for 7 d or Trp metabolites, I3A (1000 mg/kg), IPyA (2900 mg/kg), or IEt (600 mg/kg), by oral gavage daily for 2 d, and then infected with C. rodentium (CR, oral gavage, 108 CFU) with continued Trp feeding or metabolite treatment. a–b, Bacterial load in (a) feces and (b) colon tissue was measured (a) every 1–2 d for 24 d post-infection and (b) at the peak of infection, 10 d post-infection. c–e, Colon sections were stained with H&E and (c) blindly scored for submucosal edema (0-3), goblet cell depletion (0-3), epithelial hyperplasia (0-3), epithelial integrity (0-4), and neutrophil and mononuclear cell infiltration (0-3). Data are expressed as the sum of these individual scores (0-16). See Methods for full description of scoring rubric. (d) Crypt heights were measured. (e) Representative images. Scale bar: 50 μm. (f) Representative images of pedestals from Fig. 4a (denoted by arrows) stained with DAPI and Alexa Fluor 647-phalloidin and imaged by confocal microscopy. Shown are maximum intensity z-projections. Scale bar: 5 μm. (g) Pedestal formation = # of pedestals per host cell (I3A, n = 1079; IPyA, n = 1027 cells examined over 3 independent experiments). For box plots, interquartile ranges (IQRs, boxes), median values (line within box), whiskers (lowest and highest values within 1.5 times IQR from the first and third quartiles), and outliers beyond whiskers (dots), are shown. h, i, Intestinal epithelial cells were isolated, and cell lysates were analyzed by Western blotting with the indicated antibodies. Source data are provided in Supplementary Fig. 9. (i) Densitometry was performed using FIJI, n = 3 biological replicates. Data are representative of at least 3 independent experiments, n = 10 mice per group, bars = mean, error bars = standard deviation. Statistical analysis was performed using the two-tailed Student’s t-test (a) or one-way ANOVA, followed by post-hoc Tukey multiple comparison test: *p < 0.05, **p < 0.01, ***p < 0.001.
Extended Data Fig. 7 Synthetic DRD2 agonist protects against a mouse model of EHEC infection using C. rodentium, strain DBS100, whereas a DRD2 antagonist blocks the effects.
a–i, Drd2fl/fl x Villin (Vil)-Cre or Drd2fl/fl mice were pre-treated with DRD2 agonist sumanirole (SUM, 4 mg/kg, IP injection) daily for 2 d. j–r, Drd2fl/fl x Vil-Cre or Drd2fl/fl mice were pre-treated with DRD2 antagonist L-741,626 (1 mg/kg, IP injection) daily for 2 d, followed by conventional (2 g Trp/kg diet, ad libitum) or Trp (42 g Trp/kg diet, ad libitum) diet for 7 d. a–r, The mice were then administered C. rodentium (CR, oral gavage, 108 colony-forming units, CFU) with continued (a–i) SUM treatment or (j–r) L-741,626 and Trp feeding. a, j Timeline for (a) SUM and (j) L-741,626 study. b–c, k–l, Bacterial load in (b, k) feces and (c, l) colon tissue was measured (b, k) every 1–2 d for 10 d post-infection and (c, l) at the peak of infection, 10 d post-infection. (d–f, m–o) Colon sections were stained with H&E and (d, m) blindly scored for submucosal edema (0-3), goblet cell depletion (0-3), epithelial hyperplasia (0-3), epithelial integrity (0-4), and neutrophil and mononuclear cell infiltration (0-3). Data are expressed as the sum of these individual scores (0-16). See Methods for full description of scoring rubric. (e, n) Crypt heights were measured. (f, o) Representative images. Scale bar: 50 μm. (g, p) Intestinal cryosections were stained with DAPI and Alexa Fluor 647-phalloidin. Pedestal formation = # of pedestals per host cell (SUM, n = 883; L-741,626, n = 1775 cells examined over 3 independent experiments). For box plots, interquartile ranges (IQRs, boxes), median values (line within box), whiskers (lowest and highest values within 1.5 times IQR from the first and third quartiles), and outliers beyond whiskers (dots), are shown. h–i, q–r, Intestinal epithelial cells were isolated, and cell lysates were analyzed by Western blotting with the indicated antibodies. Source data are provided in Supplementary Fig. 9. (q) Samples derive from the same experiment, and Western blots were processed in parallel. (i, r) Densitometry was performed using FIJI, n = 3 biological replicates. Data are representative of at least 3 independent experiments, n = 10 mice per group, bars = mean, error bars = standard deviation. Statistical analysis was performed using the two-tailed Student’s t-test (b, k) or one-way ANOVA, followed by post-hoc Tukey multiple comparison test: ***p < 0.001.
Extended Data Fig. 8 Effects of Trp metabolites do not depend on Gαi and β-arrestin signaling.
Caco-2 cells were pre-treated with (a–d) Gαi inhibitor pertussis toxin (PTx, 100 ng/mL) for 18 h or (e–h) β-arrestin inhibitor barbadin (100 μM) for 30 min, followed by Trp metabolite (I3A, IPyA, or IEt, 100 μM) for 24 h. The cells were then infected with EHEC (MOI 50) for 12 h, (a, e) fixed, and stained with DAPI and Alexa Fluor 647-phalloidin. Pedestal formation = # of pedestals per Caco-2 cell (PTx: I3A, n = 994; IPyA, n = 916; IEt, n = 905; barbadin: I3A, n = 934; IPyA, n = 993; IEt, n = 1087 cells examined over 3 independent experiments). For box plots, interquartile ranges (IQRs, boxes), median values (line within box), whiskers (lowest and highest values within 1.5 times IQR from the first and third quartiles), and outliers beyond whiskers (dots), are shown. b–d, f–h, Alternatively, cells were lysed and analyzed by Western blotting with the indicated antibodies. Source data are provided in Supplementary Fig. 9. (c–d, g–h) Densitometry was performed using FIJI. Data are representative of at least 3 independent experiments, n = 3 biological replicates, bars = mean, error bars = standard deviation. Statistical analysis was performed using one-way ANOVA, followed by post-hoc Tukey multiple comparison test.
Extended Data Fig. 9 Effects of Trp metabolites depend on Gβγ and phospholipase C.
Caco-2 cells were pre-treated with (a–h) Gβγ inhibitor gallein (10 μM) for 30 min or (i–p) PLC inhibitor U-73122 (10 μM) for 30 min, followed by Trp metabolite (I3A, IPyA, or IEt, 100 μM) for 24 h. The cells were then infected with EHEC (MOI 50) for 12 h, (a, i) fixed, and stained with DAPI and Alexa Fluor 647-phalloidin. Pedestal formation = # of pedestals per Caco-2 cell (gallein: I3A, n = 944; IPyA, n = 1073; IEt, n = 905; U-73122: I3A, n = 977; IPyA, n = 1068; IEt, n = 1075 cells examined over 3 independent experiments). For box plots, interquartile ranges (IQRs, boxes), median values (line within box), whiskers (lowest and highest values within 1.5 times IQR from the first and third quartiles), and outliers beyond whiskers (dots), are shown. b–h, j–p, Alternatively, cells were lysed and analyzed by Western blotting with the indicated antibodies. Source data are provided in Supplementary Fig. 9. (c, e, g, h, k, m, o, p) Densitometry was performed using FIJI. Data are representative of at least 3 independent experiments, n = 3 biological replicates, bars = mean, error bars = standard deviation. Statistical analysis was performed using one-way ANOVA, followed by post-hoc Tukey multiple comparison test.
Extended Data Fig. 10 Effects of Trp metabolites depend on protein kinase C (PKC).
Caco-2 cells were pre-treated with pan-PKC inhibitor sotrastaurin (Sotra, 5 μM) for 30 min, followed by Trp metabolite (I3A, IPyA, or IEt, 100 μM) for 24 h. The cells were then infected with EHEC (MOI 50) for 12 h, (a) fixed, and stained with DAPI and Alexa Fluor 647-phalloidin. Pedestal formation = # of pedestals per Caco-2 cell (I3A, n = 912; IPyA, n = 1138; IEt, n = 1086 cells examined over 3 independent experiments). For box plots, interquartile ranges (IQRs, boxes), median values (line within box), whiskers (lowest and highest values within 1.5 times IQR from the first and third quartiles), and outliers beyond whiskers (dots), are shown. b–f, Alternatively, cells were lysed and analyzed by Western blotting with the indicated antibodies. Source data are provided in Supplementary Fig. 9. (c, e, f) Densitometry was performed using FIJI. Data are representative of at least 3 independent experiments, n = 3 biological replicates, bars = mean, error bars = standard deviation. Statistical analysis was performed using one-way ANOVA, followed by post-hoc Tukey multiple comparison test.
Extended Data Fig. 11 Effects of Trp metabolites depend on protein kinase C (PKC)-θ.
Caco-2 cells were pre-treated with (a–f) isoform-selective PKC-θ inhibitor (PKCθi, 5 μM) for 24 h, or (g–l) PKC-θ was knocked down using two different siRNA duplexes (1 and 2) or a negative control siRNA duplex (C), followed by Trp metabolite (I3A, IPyA, or IEt, 100 μM) for 24 h. The cells were then infected with EHEC (MOI 50) for 12 h, (a, g) fixed, and stained with DAPI and Alexa Fluor 647-phalloidin. Pedestal formation = # of pedestals per Caco-2 cell (PKCθi: I3A, n = 1063; IPyA, n = 1005; IEt, n = 1033; siRNA: I3A, n = 1680; IPyA, n = 1462; IEt, n = 1502 cells examined over 3 independent experiments). For box plots, interquartile ranges (IQRs, boxes), median values (line within box), whiskers (lowest and highest values within 1.5 times IQR from the first and third quartiles), and outliers beyond whiskers (dots), are shown. b–f, h–l, Alternatively, cells were lysed and analyzed by Western blotting with the indicated antibodies. Source data are provided in Supplementary Fig. 9. (c, e, f, i, k, l) Densitometry was performed using FIJI. Data are representative of at least 3 independent experiments, n = 3 biological replicates, bars = mean, error bars = standard deviation. Statistical analysis was performed using one-way ANOVA, followed by post-hoc Tukey multiple comparison test.
Extended Data Fig. 12 Effects of Trp metabolites depend on proteasomal degradation.
Caco-2 cells were pre-treated with proteasomal inhibitor MG-132 (10 μM) for 1 h, followed by Trp metabolite (I3A, IPyA, or IEt, 100 μM) for 24 h. The cells were then infected with EHEC (MOI 50) for 12 h, (a) fixed, and stained with DAPI and Alexa Fluor 647-phalloidin. Pedestal formation = # of pedestals per Caco-2 cell (I3A, n = 1079; IPyA, n = 999; IEt, n = 911 cells examined over 3 independent experiments). For box plots, interquartile ranges (IQRs, boxes), median values (line within box), whiskers (lowest and highest values within 1.5 times IQR from the first and third quartiles), and outliers beyond whiskers (dots), are shown. b–h, Alternatively, cells were lysed and analyzed by Western blotting with the indicated antibodies. Source data are provided in Supplementary Fig. 9. (c, e, g, h) Densitometry was performed using FIJI. Data are representative of at least 3 independent experiments, n = 3 biological replicates, bars = mean, error bars = standard deviation. Statistical analysis was performed using one-way ANOVA, followed by post-hoc Tukey multiple comparison test.
Supplementary information
Supplementary Information
Supplementary Figs. 1–9
Source data
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Scott, S.A., Fu, J. & Chang, P.V. Dopamine receptor D2 confers colonization resistance via microbial metabolites. Nature 628, 180–185 (2024). https://doi.org/10.1038/s41586-024-07179-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41586-024-07179-5
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.
