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Dietary- and host-derived metabolites are used by diverse gut bacteria for anaerobic respiration

Nature Microbiology volume 9, pages 55–69 (2024)Cite this article

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Abstract

Respiratory reductases enable microorganisms to use molecules present in anaerobic ecosystems as energy-generating respiratory electron acceptors. Here we identify three taxonomically distinct families of human gut bacteria (Burkholderiaceae, Eggerthellaceae and Erysipelotrichaceae) that encode large arsenals of tens to hundreds of respiratory-like reductases per genome. Screening species from each family (Sutterella wadsworthensis, Eggerthella lenta and Holdemania filiformis), we discover 22 metabolites used as respiratory electron acceptors in a species-specific manner. Identified reactions transform multiple classes of dietary- and host-derived metabolites, including bioactive molecules resveratrol and itaconate. Products of identified respiratory metabolisms highlight poorly characterized compounds, such as the itaconate-derived 2-methylsuccinate. Reductase substrate profiling defines enzyme–substrate pairs and reveals a complex picture of reductase evolution, providing evidence that reductases with specificities for related cinnamate substrates independently emerged at least four times. These studies thus establish an exceptionally versatile form of anaerobic respiration that directly links microbial energy metabolism to the gut metabolome.

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Fig. 1: Respiratory reductase orthologues are highly over-represented in three distinct lineages of gut bacteria.
Fig. 2: ‘High reductase’ gut bacteria exhibit respiratory growth properties.
Fig. 3: ‘High reductase’ gut bacteria use diverse respiratory electron acceptors.
Fig. 4: Flavin reductases are induced by their electron acceptors and exhibit relatively narrow substrate specificities.
Fig. 5: Independent evolutionary trajectories and distinct active sites distinguish flavin reductases with related electron acceptors.

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Data availability

The datasets generated in our study are available within the paper and Supplementary Information. Quantitative metabolomic raw data files can be found on the MassIVE repository (ID MSV000093291). Transcriptomic datasets generated in this study can be found under BioProject PRJNA1012298. Metagenomic data used in this study are publicly available on NCBI under BioProject IDs PRJNA912122 and PRJNA838648. Proteomic datasets can be accessed at https://doi.org/10.7910/DVN/OY9MPE. NCBI accession codes for studied proteins are provided in Supplementary Table 10. Source data are provided with this paper.

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Acknowledgements

We thank H. Lin and N. P. Dylla for assistance with data analyses and L. Comstock for helpful feedback. We thank the University of Chicago Animal Resources Center for their assistance with mouse work (RRID: SCR_021806). Research reported in this publication was supported by funding from the National Institutes of Health (T32DK007074 to M.A.O., 1S10OD020062-01 to A.T.I., and K22AI144031 and R35GM146969 to S.H.L) and the Searle Scholars Program (to S.H.L.).

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Authors and Affiliations

  1. Duchossois Family Institute, University of Chicago, Chicago, IL, USA

    Alexander S. Little, Isaac T. Younker, Matthew S. Schechter, Paola Nol Bernardino, Joshua Stemczynski, Kaylie Scorza, Michael W. Mullowney, Deepti Sharan, Emily Waligurski, Rita Smith, Ramanujam Ramanswamy, William Leiter, David Moran, Mary McMillin, Matthew A. Odenwald, Ashley M. Sidebottom, Anitha Sundararajan, Eric G. Pamer & Samuel H. Light

  2. Department of Microbiology, University of Chicago, Chicago, IL, USA

    Alexander S. Little, Isaac T. Younker, Matthew S. Schechter, Paola Nol Bernardino, Joshua Stemczynski, Kaylie Scorza, Deepti Sharan, Eric G. Pamer & Samuel H. Light

  3. Génomique Métabolique, CEA, Genoscope, Institut François Jacob, Université d’Évry, Université Paris-Saclay, CNRS, Evry, France

    Raphaël Méheust

  4. Section of Gastroenterology, Hepatology, and Nutrition, Department of Medicine, University of Chicago, Chicago, IL, USA

    Matthew A. Odenwald

  5. QB3/Chemistry Mass Spectrometry Facility, University of California, Berkeley, Berkeley, CA, USA

    Anthony T. Iavarone

  6. Section of Infectious Diseases & Global Health, Department of Medicine, University of Chicago, Chicago, IL, USA

    Eric G. Pamer

  7. Helmholtz Institute for Functional Marine Biodiversity, Oldenburg, Germany

    A. Murat Eren

  8. Institute for Chemistry and Biology of the Marine Environment, University of Oldenburg, Oldenbug, Germany

    A. Murat Eren

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  1. Alexander S. Little
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Contributions

A.S.L., E.G.P. and S.H.L. conceptualized the project. A.S.L., I.T.Y., P.N.B., J.S., K.S. and D.S. performed the experiments. A.S.L., M.S.S., P.N.B. and S.H.L. analysed the data. A.S.L., I.T.Y., P.N.B., J.S. and K.S. performed growth assays. A.S.L. performed ATP determination assays. A.S.L. and J.S. performed protein expression and purification and reductase activity assays. M.S.S., R.M. and A.M.E. performed bioinformatic analysis, including phylogeny and pangenomes. A.S.L., R.R., R.S. and A.S. performed bioinformatics analysis of transcriptomic data. M.W.M., W.L., D.M., M.M. and A.M.S. performed and analysed mass spectrometry. A.T.I. performed and analysed proteomics data. A.S.L., P.N.B., J.S. and E.W. performed animal experiments and maintenance. M.A.O. provided human faecal samples for analysis. A.S.L. and S.H.L. wrote the paper.

Corresponding author

Correspondence to Samuel H. Light.

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Nature Microbiology thanks Emily Balskus, Chris Greening and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Distribution and identity of flavin and molybdopterin reductases in three taxonomic families.

Phylogenetic trees constructed with representative genomes from each Genome Taxonomy Database (GTDB) species in (a) Eggerthellaceae (88 genomes, 2387 amino acid sites), (b) Burkholderiaceae (1510 genomes, 2379 amino acid sites), and (c) Erysipelotrichaceae (116 genomes, 2464 amino acid sites). Each maximum likelihood tree was constructed based on a concatenated alignment of 16 ribosomal proteins under an LG + I + G4 model of evolution. The numbers of flavin (blue) and molybdopterin (red) reductases with a computationally predicted signal peptide in each genome are graphed on the outer ring of the trees. (d) Flavin reductase pangenomes of E. lenta, S. wadsworthensis, and H. filiformis. For each pangenome, the inner concentric layers represent unique genomes while the radial elements represent gene cluster presence (darker color) or absence (lighter color) across the genomes. The outermost concentric circle, ‘Max num paralogues,’ indicates the maximum number of paralogues (defined as reductases with ~60% sequence identity) one genome contributes to the gene cluster. The second outermost circle, ‘SCG clusters,’ indicates single-copy core reductase that is, gene clusters for which every genome contributed exactly one gene. Genomes (inner concentric layers) are clustered by the presence/absence of reductase gene clusters. All vs all genome average nucleotide identity is depicted in the heat map above the genome concentric layers.

Source data

Extended Data Fig. 2 E. lenta uses multiple respiratory electron acceptors.

E. lenta DSM2243 growth in formate-supplemented media provisioned with electron acceptors: (a) p-coumarate, (b) ferulate, (c) chlorogenate, (d) rosmarinate, (e) sinapate, (f) shikimate, (g) itaconate, (h) methionine sulfoxide, (i) S-methyl-L-cysteine sulfoxide, and (j) dimethyl sulfoxide. A ‘no electron acceptor’ condition and conditions with predicted reduction products are included as controls. Extracted ion chromatograms of peaks (matched to available authentic standards) in uninoculated and inoculated growth media. (A)-(D),(G)-(J) were measured by GC-MS; (E), (F) were measured by LC-MS; support for identification of hydro-shikimate in (F) is provided in Supplementary Fig. 5. Data are mean ±SD (n = 3 independent biological replicates). *p < 0.05, **p < 0.01, *** p < 0.001. Two-way ANOVA, multiple test vs media alone.

Extended Data Fig. 3 S. wadsworthensis growth-stimulating electron acceptors.

S. wadsworthensis growth in formate-supplemented media provisioned with electron acceptors: (a) labeled C4-dicarboxylates, (b) shikimate, (c) dimethyl sulfoxide, and (d) methionine sulfoxide. A ‘no electron acceptor’ condition and conditions with predicted products are included as controls. Extracted ion chromatograms of peaks (matched to available authentic standards) in uninoculated and inoculated growth media. (A) Fumarate and its succinate reduction were measured by LC-MS, the rest of (A) and (D) were measured by GC-MS; (B) was measured by LC-MS; support for identification of hydro-shikimate in (B) is provided in Supplementary Fig. 5. Data are mean ±SD (n = 3 independent biological replicates). *p < 0.05, **p < 0.01, *** p < 0.001. Two-way ANOVA, multiple test vs media alone.

Extended Data Fig. 4 H. filiformis growth-stimulating electron acceptors.

H. filiformis growth in media provisioned with electron acceptors: (a) cinnamate (b) m-coumarate, (c) p-coumarate (d) ferulate, and (e) sinapate. A ‘no electron acceptor’ condition and conditions with predicted products are included as controls. Extracted ion chromatograms of peaks (matched to available authentic standards) in uninoculated and inoculated growth media. Data are mean ±SD (n = 3 independent biological replicates). *p < 0.05, **p < 0.01, *** p < 0.001. Two-way ANOVA, multiple test vs media alone.

Extended Data Fig. 5 Electron acceptors not observed to stimulate growth.

(a) GC-MS analysis of resveratrol-spiked media before and after E. lenta DSM2243 growth and LC-MS analysis of resveratrol-spiked media before and after H. filiformis DFI.9.20 growth. The low solubility of resveratrol hindered experiments to assess whether this electron acceptor supported respiratory growth. (b) Potential modification flow for (+)-catechin and (−)-epicatechin, and GC-MS of media spiked with either (+)-catechin or (−)-epicatechin before and after E. lenta DSM2243 or S. wadsworthensis DFI.4.78 growth. (c) Resting cell suspensions of E. lenta and S. wadsworthensis in buffer supplemented with 1mM formate assayed cellular ATP concentrations after incubation with buffer alone or (−)-epicatechin, data are mean ±SD (n = 3 technical replicates). Support for identification of catechin and epicatechin derivatives in (B) is provided in Supplementary Figs. 2 and 3.

Extended Data Fig. 6 ATP generation facilitated by electron acceptors.

Resting cell suspensions of E. lenta and S. wadsworthensis in buffer supplemented with 1mM formate assayed cellular ATP concentrations after incubation with different classes of electron acceptors, (a) cinnamates, (b) C4-dicarboxylates, (c) other enolates, (d) alkenes, (e) sulfoxides, (f) catechols, and (g) electron donor-acceptor combination dependence. Data are mean ±SD (n = 3 technical replicates).

Extended Data Fig. 7 Caffeate utilization by E. lenta and tungstate inhibition of sulfoxide growth enhancement.

(a) GC-MS analysis of supernatant collected from E. lenta DSM2243 grown in caffeate-spiked media. Extracted ion chromatograms of peaks (matched to authentic standards) in uninoculated and inoculated growth media. Proposed reaction pathways are shown, with peaks for each compound provided beneath its chemical structure. The previously characterized hydrocaffeate dehydroxylase may catalyze the observed dehydroxylation reactions. The observed caffeate reduction to hydrocaffeate provides evidence of a caffeate reductase, while the accumulation of m-coumarate suggests that this enzyme may specifically use caffeate. (b) E. lenta DSM2243 growth in media supplemented with formate and different cinnamates. The pattern of cinnamate-dependent growth enhancement supports the conclusions that: (1) dehydroxylation can support respiratory growth and (2) m-coumarate is a poor electron acceptor for E. lenta. (c) The effect of the molybdopterin reductase inhibitor, tungstate, on E. lenta DSM2243 growth. Media was supplemented with formate and the noted electron acceptor, with or without the addition of tungstate. (d) Reactions catalyzed by urocanate and sulfoxide reductases. Tungstate’s selective growth inhibition is consistent with sulfoxide, but not urocanate, reduction being catalyzed by a molybdopterin reductase. Data are mean ±SD (n = 3 independent biological replicates). *p < 0.05, **p < 0.01, *** p < 0.001. Two-way ANOVA, multiple test vs media alone.

Extended Data Fig. 8 Microbiome composition of fecal samples used for metabolite measurements.

(a) Taxonomy abundance in human fecal samples used for metabolomics analyses assessed by shotgun metagenomics. (b) Taxonomy abundance in mouse fecal samples used for metabolomics analyses assessed by 16S rRNA amplicon sequencing. The Inverse Simpson measure of microbiome diversity is also presented.

Extended Data Fig. 9 Expression of recombinant reductase enzymes.

SDS-PAGE gels of reductase enzymes expressed and purified from E. coli. (a) H. filiformis enzymes, except where indicated. (b) E. lenta enzymes, except where indicated. Proteins run on a 12% acrylamide Bis-Tris gel in a MOPS running buffer, compared to PageRuler Plus prestained protein ladder (Thermo. #26619). Expected kDa for both ladder and proteins are labeled. Experiments (A, B) were repeated twice, with similar results.

Source data

Extended Data Fig. 10 Presence of irdA predicts itaconate reductase activity of E. lenta strains.

(a) Schematic diagram of itaconate reduction by IrdA, and sequence identity of the reductase with greatest similarity to IrdA is shown for indicated E. lenta strains strain. (b) Extracted ion chromatograms of authentic standard-matched methylsuccinate peaks from media collected after cultivation with the indicated strain.

Supplementary information

Supplementary Information

Supplementary discussion, Figs. 1–5 and references.

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Supplementary Tables 1–14.

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Source Data Extended Data Fig. 9

Raw whole-gel images.

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Little, A.S., Younker, I.T., Schechter, M.S. et al. Dietary- and host-derived metabolites are used by diverse gut bacteria for anaerobic respiration. Nat Microbiol 9, 55–69 (2024). https://doi.org/10.1038/s41564-023-01560-2

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