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Anti-infective bile acids bind and inactivate a Salmonella virulence regulator

Nature Chemical Biology volume 19, pages 91–100 (2023)Cite this article

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Abstract

Bile acids are prominent host and microbiota metabolites that modulate host immunity and microbial pathogenesis. However, the mechanisms by which bile acids suppress microbial virulence are not clear. To identify the direct protein targets of bile acids in bacterial pathogens, we performed activity-guided chemical proteomic studies. In Salmonella enterica serovar Typhimurium, chenodeoxycholic acid (CDCA) most effectively inhibited the expression of virulence genes and invasion of epithelial cells and interacted with many proteins. Notably, we discovered that CDCA can directly bind and inhibit the function of HilD, an important transcriptional regulator of S. Typhimurium virulence and pathogenesis. Our characterization of bile acid-resistant HilD mutants in vitro and in S. Typhimurium infection models suggests that HilD is one of the key protein targets of anti-infective bile acids. This study highlights the utility of chemical proteomics to identify the direct protein targets of microbiota metabolites for mechanistic studies in bacterial pathogens.

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Fig. 1: CDCA most effectively inhibits S. Typhimurium virulence in vitro.
Fig. 2: Chemoproteomic profiling of CDCA-interacting proteins in S. Typhimurium.
Fig. 3: HilD mutants confer resistance to bile and CDCA inhibition of S. Typhimurium virulence.
Fig. 4: CDCA interferes with HilD dimerization and DNA binding.
Fig. 5: The S. Typhimurium hilDQ39E,N44D,H95L mutant is resistant to microbiota suppression of virulence in vivo.
Fig. 6: The S. Typhimurium hilDQ39E,N44D,H95L mutant is more virulent in CDCA-supplemented mice.

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Data availability

The proteome database (UP000002695) used in this study is available from UniProt. The MS proteomics raw data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD034373. The Rns crystal structure (6XIV) and ToxT crystal structure (3GBG) are available on the RCSB Protein Data Bank. Source data are provided with this paper. All other data supporting the findings of this study are available within the article and its supplementary information files and from the corresponding author on reasonable request.

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Acknowledgements

We thank The Rockefeller Proteomics Resource Center for LC–MS analysis, Z.J. Zhang and other Hang lab members for helpful discussions. We also thank J. Hammond from the Scripps Research Biophysics and Biochemistry Core for help on mass photometry experiments. H.C.H. acknowledges support from NIH grant R01AI172915. K.R.S. acknowledges support from the Scripps Research T32 Immunology Training Grant T32AI007244. Some figures were created with BioRender.com.

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Authors and Affiliations

  1. Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA

    Xinglin Yang, Kathryn R. Stein & Howard C. Hang

  2. Department of Chemistry, Scripps Research, La Jolla, CA, USA

    Howard C. Hang

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  1. Xinglin Yang
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Contributions

H.C.H. and X.Y. conceived the project, X.Y. performed experiments and K.R.S. performed lipocalin-2 analysis. X.Y., K.R.S. and H.C.H. analyzed the data and wrote the paper.

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Correspondence to Howard C. Hang.

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Extended data

Extended Data Fig. 1 Chemoproteomic analysis of bile acid reporter-interacting proteins in S. Typhimurium.

a,b,c, LFQ proteomic analysis of bile acid reporters-labeled proteins in S. Typhimurium under UV irradiation (biologically independent samples, n = 4). S. Typhimurium cell lysates were reacted with az-biotin for the enrichment of bile acid reporters-labeled proteins with streptavidin beads and identification by LC-MS/MS. Volcano plots were presented for alk-X-CDCA (a), alk-X-LCA (b) and alk-X-UDCA (c). d, Gene ontology analysis of the shared 129 protein targets identified by LFQ proteomic reveals their association with pathogenesis (analyzed by The Database for Annotation, Visualization and Integrated Discovery (DAVID)). The names of the 16 proteins specifically assigned to the functional cluster of “virulence” are shown. e, Cellular component analysis of protein hits in a by gene ontology (GO).

Source data

Extended Data Fig. 2 Identification of bile acid resistant HilD mutations.

a, Three amino acids (N260, K264, R267) which are adjacent to potential binding pocket are highlighted in Robetta predicted HilD dimer. Green: DNA binding domain, orange: “jelly roll” motif, the putative binding domain. b. An overnight culture of S. Typhimurium (hilD-HAWT or hilD-HAmutants generated by CRISPR-Cas9) were diluted 1/50 into 4 mL SPI-1 inducing LB aliquots containing DMSO or CDCA (0.5 mM) and incubated for 4 h at 37 °C with 220 rpm shaking. SPI-1 effectors and flagella components levels in S. Typhimurium growth media were monitored by SDS-PAGE followed by Coomassie blue staining55. Experiments were repeated at least two times with similar results. c, Schematic for screening of mutant hilD library. Generally, hilD mutant library was generated from pTXB1-HilD by error prone PCR. The mutant library was transformed to reporter strain (S. Typhimurium tetRA-hilD-3XFLAG attλ::pDX1::hilA’-lacZ) and screened by plates (IPTG, carbenicillin, X-gal and 2.5 % bile acids)56. Plasmids from blue colonies were sequenced.

Source data

Extended Data Fig. 3 Investigation of HilD and CDCA interaction.

a, HilA-HA expression of HilD-mutant strains in presence of CDCA (500 µM). SPI-1 transcriptional factor HilA-HA expression of hilDWT or hilDmutant S. Typhimurium (hilA-HA) strains grown with or without 0.5 mM of CDCA. Western blot was quantified by grayscale analysis. Two-way ANOVA followed by Sidak’s multiple comparisons test, adjusted P value. Centerline, average. Error bar, SD. (biologically independent samples, n = 3). Comparisons with P > 0.05 were not considered significant. b,c, Docking of CDCA into HilD model. HilD protein model was generated based on AraC family protein Rns (PDB 6XIV32) by SWISS-MODEL. The structure model of HilD was generated with the protein preparation wizard using Maestro software (12.4, Schrödinger, LLC), and Q39, N44, H95 were chosen as centroid of selected residues and the Ligand Docking protocol was used to model potential binding modes. Green: DNA binding domain, orange: “jelly roll” motif, the putative binding domain.

Source data

Extended Data Fig. 4 HilD Asparagine 44 mutations affect Salmonella response to bile acids and long chain fatty acid.

a,c, HilA-HA expression of hilDWT or hilDmutant S. Typhimurium (HilA-HA) strains grown with or without 2% bile acids (a) and 25 μM HDA (cis-2-hexadecenoic acid) (c). Western blot was quantified by grayscale analysis. b, Gentamicin protection assay of S. Typhimurium grown with 2% bile acids infecting HT-29 cells at MOI = 10. Statistical analysis for a,b,c, (a, biologically independent samples, n = 3; b, biologically independent samples, n = 6; c, biologically independent samples, n = 3) Two-way ANOVA followed by Sidak’s multiple comparisons test, adjusted P value. Centerline, average. Error bar, SD. Comparisons with P > 0.05 were not considered significant. d, Western blot for c.

Source data

Extended Data Fig. 5 CDCA inhibits hilD transcription and has little effect on HilD stability.

a,c,e, Overnight culture of Salmonella Typhimurium (hilD-HA for a,e; hilD-HA, lon:: cat for c) was subcultured 1:50 to 20 mL LB (300 mM NaCl). Bacteria was cultured for 3.5 h and another half an hour with treatment of CDCA or DMSO control (a,c) or cultured for 4 h with treatment of CDCA or DMSO (e). Then these cultures were treated with rifampin (100 ug/ml), streptomycin (200 ug/ml), and spectinomycin (50 ug/ml) to halt gene transcription and protein translation and kept at 37 oC with 220 rpm. Samples are picked at indicated time point. HilD-HA protein level was analyzed by Western blot. b,d,f, western blot was quantified by grayscale analysis for a,c,e correspondingly. For b,d Data was analyzed by two-way ANOVA and Sidak’s multiple comparisons test. Comparisons with P > 0.05 were not considered significant. Centerline, average. Error bar, SD (biologically independent samples, n = 3). e,f was repeated twice with similar results. g,h, Overnight culture of Salmonella (HilD-HA) was subcultured 1:50 to 20 mL LB (300 mM NaCl). Bacteria was cultured for 4 h with treatment of CDCA or DMSO. HilD-HA and GroEL protein level was analyzed by Western blot (biologically independent samples, n = 6). Unpaired t test (two-sided). Centerline, average. Error bar, SD. i. Expression of SPI-1 and control genes of S. Typhimurium grown with DMSO, CDCA (concentration = 0.5 mM) measured by qRT-PCR (biologically independent samples, n = 6, results are pooled from two independent experiments, one independent experiment was carried out together with Fig. 1f, three replicates of control gene ftsZ were shared with 1 f). Unpaired t test (two-sided). Centerline, average. Error bar, SD. Comparisons had P > 0.05 were not considered significant.

Source data

Extended Data Fig. 6 HilDQ39E+N44D+H95L Salmonella is resistant to other gut microbiota metabolized small molecules.

a, SPI-1 transcriptional factor HilA-HA expression of S. Typhimurium (hilA-HA, hilDWT or Q39E+N44D+H95) grown with propionic acid (10 mM), palmitic acid (0.1 mM) and cis-2-hexadecenoic acid (0.025 mM). b, Western blot was quantified by grayscale analysis, normalized with OD 600 value. All metabolites were compared to DMSO with one-way ANOVA and Dunnett’s multiple comparisons test, adjusted P value. Centerline, average. Error bar, SD. (biologically independent samples, n = 3). Comparisons with P > 0.05 were not considered significant. c, chemical structures of propionic acid, palmitic acid and cis-2-hexadecenoic acid.

Source data

Extended Data Fig. 7 Mice fecal metabolites inhibit Salmonella virulence.

a, feces were collected from C57BL/6 mice one day post with or without 20 mg streptomycin treatment. Feces from 4 mice were pooled together and added to lysing matrix D (Methanol: H2O = 9: 1, 100 mg/mL). Feces were then homogenized by Fastprep-24 5 G (MP Biomedicals, 4 m/s, 3 cycles, 5 s for each cycle). Supernatant after centrifugation (18 000 g, 4 oC, 30 min) were lyophilized and the corresponding residues were redissolved in LB for bacterial culture (metabolites from 50 mg of feces were dissolved in 1 mL of LB). Overnight culture of Salmonella (hilA-HA, hilDWT or Q39E+N44D+H95) was subcultured 1:50 to LB with or without metabolites. Bacteria were cultured for 4 h at 37 oC. Expression of HilA-HA and GroEL was analyzed by western blot analysis. b,c, Western blot was quantified by grayscale analysis, normalized with GroEL expression. Bacteria treated with metabolites were compared to bacteria treated with LB by one-way ANOVA and Dunnett’s multiple comparisons test, adjusted P value. Centerline, average. Error bar, SD. (biologically independent samples, n = 3). Comparisons with P > 0.05 were not considered significant.

Source data

Supplementary information

Supplementary Information

Supplementary Figs. 1–13, Tables 1–4, materials, synthesis of bile acid reporters and NMR spectra of bile acid reporters.

Reporting Summary

Supplementary Data 1

Proteomics dataset.

Supplementary Data 2

Robetta-predicted HilD dimer structure model.

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Yang, X., Stein, K.R. & Hang, H.C. Anti-infective bile acids bind and inactivate a Salmonella virulence regulator. Nat Chem Biol 19, 91–100 (2023). https://doi.org/10.1038/s41589-022-01122-3

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