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Microbial metabolism of l-tyrosine protects against allergic airway inflammation

Nature Immunology volume 22, pages 279–286 (2021)Cite this article

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Abstract

The constituents of the gut microbiome are determined by the local habitat, which itself is shaped by immunological pressures, such as mucosal IgA. Using a mouse model of restricted antibody repertoire, we identified a role for antibody–microbe interactions in shaping a community of bacteria with an enhanced capacity to metabolize l-tyrosine. This model led to increased concentrations of p-cresol sulfate (PCS), which protected the host against allergic airway inflammation. PCS selectively reduced CCL20 production by airway epithelial cells due to an uncoupling of epidermal growth factor receptor (EGFR) and Toll-like receptor 4 (TLR4) signaling. Together, these data reveal a gut microbe–derived metabolite pathway that acts distally on the airway epithelium to reduce allergic airway responses, such as those underpinning asthma.

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Fig. 1: MD4 mice with a restricted antibody repertoire to HEL fail to mount allergic responses to HDM extract.
Fig. 2: Microbiota of MD4 mice confers protection against HDM-induced allergic airway inflammation.
Fig. 3: Antibodies in MD4 mice shape the microbiome and the metabolome of the host.
Fig. 4: Administration of PCS or l-tyrosine confers protection in an HDM model of asthma.
Fig. 5: The l-tyrosine–PCS axis modulates DC activation via inhibition of epithelial cell–derived CCL20.

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Data availability

All raw 16S rRNA amplicons and shotgun metagenomics sequences with corresponding metadata are deposited on the NCBI server under BioProject PRJNA641984. The metabolomics dataset is deposited on the Mendeley data repository (https://doi.org/10.17632/z2knkcmntc.1). The SILVA database can be found at https://www.arb-silva.de/documentation/release-123. Functional annotation of predicted genes was performed using Uniref90 retrieved on 1 October 2020. The data that support the findings of this study are available from the corresponding author on request.

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Acknowledgements

We thank H. Mitchell for help with the shotgun metagenomics library preparation and M. Macowan for help with shotgun metagenomics data analysis. This work was supported by the MASSIVE HPC facility (http://www.massive.org.au). T.P.W. is supported by a Postdoc Mobility Fellowship from the Swiss National Science Foundation. B.J.M. is an NHMRC Senior Research Fellow and VESKI Innovation Fellow. This work has been supported by an Alfred Research Trusts Major Grant (ANM20001).

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Authors and Affiliations

  1. Department of Immunology and Pathology, Central Clinical School, Monash University, Melbourne, Victoria, Australia

    Tomasz P. Wypych, Céline Pattaroni, Olaf Perdijk, Carmen Yap, Nicola L. Harris & Benjamin J. Marsland

  2. Faculty of Biology and Medicine, University of Lausanne, Service de Pneumologie, CHUV, Epalinges, Switzerland

    Aurélien Trompette

  3. Monash Proteomics and Metabolomics Facility, Monash Institute of Pharmaceutical Sciences, Monash University, Melbourne, Victoria, Australia

    Dovile Anderson & Darren J. Creek

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  1. Tomasz P. Wypych
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Contributions

T.P.W. conceptualized the study; T.P.W. and B.J.M. designed the study; T.P.W., O.P., C.Y., A.T. and D.A. performed experiments; T.P.W., C.P., C.Y., D.A. and A.T. analyzed data; T.P.W., D.J.C., N.L.H. and B.J.M. provided critical analyses and discussions; T.P.W. wrote the manuscript and B.J.M. revised the manuscript.

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Correspondence to Tomasz P. Wypych or Benjamin J. Marsland.

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Two provisional Australian patents have been filed by Monash University with B.J.M. and T.P.W. listed as inventors.

Additional information

Peer review information Nature Immunology thanks Dylan Dodd and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. L. A. Dempsey was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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Extended data

Extended Data Fig. 1 MD4 but not B-cell deficient mice fail to mount type 2 immunity to HDM.

a, Cytokine concentrations in culture supernatants from co-cultures of DCs and in vivo-primed lung CD4+ CD44+ T cells restimulated with HDM for 4 days. b, Total numbers of eosinophils, dendritic cells and surface expression of PD-L2 on dendritic cells from WT or B cell-deficient (JhT) mice exposed to HDM as per Fig. 1. Data in a, are representative of two experiments and represent technical replicates (n = 4 WT, n = 4 MD4). Data in b are pooled from 2 experiments (n = 8 per group), or are representative of 2 experiments (PD-L2 expression) (n = 4 per group). All data are presented as mean values ± SEM.

Extended Data Fig. 2 MD4 mice harbour a diverse microbiota.

Alpha diversity measure (based on Shannon and Chao1 indexes) based on 16 S rDNA amplicons in WT and MD4 fecal samples. The upper and lower hinges correspond to the first and third quartiles (the 25th and 75th percentiles) and line the median (50% quantile). Data pooled from 5 experiments (n = 37 MD4, n = 27 WT).

Extended Data Fig. 3 Levels and specificity of secretory antibodies in the feces of MD4 mice.

Quantification of antibody levels in the feces of WT or MD4 mice and their reactivity to HEL. All data are pooled from two experiments, n = 11 WT, n = 13 MD4. All data are presented as mean values ± SEM. Statistical significance was evaluated with unpaired Student’s t-test (in the case of Gaussian distribution) or Mann-Whitney test (non-Gaussian distribution). Data distribution was assessed with D’Agostino & Pearson normality test. ****p ≤ 0.0001.

Extended Data Fig. 4 Correlation inference network with annotated bacterial taxa bound by anti-HEL IgM (blue font) within MD4 microbiota.

Blue nodes represent taxa differentially abundant in the MD4 or WT mice, respectively, while open nodes represent non-differentially abundant hits. Node size is proportional to the MD4 IgM binding index calculated from IgM+ and IgM− fractions. Data represent analysis from one sorting experiment.

Extended Data Fig. 5 Taxonomic analyses of WT and MD4 bacteria using shotgun metagenomics.

A heat map representing differentially abundant species between MD4 and WT mice. Data represent samples with the highest quality DNA from 4 pooled experiments (n = 11 MD4, n = 9 WT).

Extended Data Fig. 6 Shotgun metagenomics analyses of metabolic pathways from tyrosine to p-cresol.

a, Metabolic pathways related to tyrosine conversion to p-cresol by bacteria16. Enzymes: tyrosine lyase (ThiH), tyrosine aminotransferase B (TyrB), phenyllactate dehydrogenase (FldH), phenyllactate dehydratase (FldBC), acyl-CoA dehydrogenase (AcdA), pyruvate ferredoxin oxidoreductase A (PorA) and hydroxyphenylacetate decarboxylase (Hpd). Unknown enzymes are indicated by a question mark. b, Volcano plot depicting differential abundance of bacterial genes related to p-cresol production from tyrosine in fecal samples from WT and MD4 mice. Each color (squares in a and dots in b) represents a different gene encoding for an enzyme or enzyme subunit of the described pathways. TyrB, PorA, and FldH were not found in metagenomics data. Data represent samples with the highest quality DNA from 4 pooled experiments (n = 11 MD4, n = 9 WT).

Extended Data Fig. 7 PCS concentration increases in the feces and in the airways of L-tyrosine-fed mice.

Mice were fed with L-tyrosine in drinking water (100 mg/kg/day) for 14 days, after which feces were collected. BALF samples were collected after HDM immunization as per Fig. 1. PCS was measured using LC-MS targeted metabolomics (n = 5 per group). Data represent samples from one experiment. All data are presented as mean values ± SEM.

Extended Data Fig. 8 Microbiota depletion abrogates the beneficial effect of L-Tyrosine feeding.

a, Experimental setup: WT C57BL6/J mice were treated with a combination of enrofloxacin (Baytril®) and amoxicillin with clavulanic acid for one week and maintained on amoxicillin/clavulanic acid until end of experiment. L-tyrosine treatment was initiated 2 weeks after the antibiotic treatment until end of experiment b, total number of eosinophils in the BALF and lungs, p = 0.0342 (BALF), p = 0.0173 (Lungs), c, total number of DCs in the lungs d, concentrations of IL-5 in the BALF, p = 0.042; n = 5 per group for all except for Water/Water group in b and d where n = 4. Results are representative of two independent experiments. All data are presented as mean values ± SEM. Statistical significance was evaluated with unpaired Student’s t-test (in the case of Gaussian distribution) or Mann-Whitney test (non-Gaussian distribution). Data distribution was assessed with Kolmogorov-Smirnov normality test.

Extended Data Fig. 9 MD4 mice have impaired production of CCL20 upon HDM exposure.

. a, CCL20 levels in culture supernatants of lung cells isolated from WT or MD4 mice and stimulated in vitro with HDM, p = 0.0002. b, CCL20 concentration in BALF of WT or MD4 mice 2 hours after intranasal exposure to HDM, p = 0.032. N = 6 per group for all graphs except from MD4 group in b, where n = 5. Results are pooled from two independent experiments. All data are presented as mean values ± SEM. Statistical significance was evaluated with unpaired Student’s t-test (in the case of Gaussian distribution) or Mann-Whitney test (non-Gaussian distribution). Data distribution was assessed with Kolmogorov-Smirnov normality test. *p ≤ 0.05, ***p ≤ 0.001.

Extended Data Fig. 10 Administration of PCS confers protection in an OVA/LPS model of pulmonary type 1 response.

a, Experimental setup of PCS administration in a protocol of OVA/LPS exposure. b, Numbers of neutrophils, CD4+ and CD8+ T cells in the BALF of vehicle or PCS-treated mice. Results are from one experiment (n = 4 per group, p = 0.0335). All data are presented as mean values ± SEM. *p ≤ 0.05. Statistical significance was evaluated with Mann-Whitney test.

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Wypych, T.P., Pattaroni, C., Perdijk, O. et al. Microbial metabolism of l-tyrosine protects against allergic airway inflammation. Nat Immunol 22, 279–286 (2021). https://doi.org/10.1038/s41590-020-00856-3

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