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Microbial metabolites regulate host lipid metabolism through NR5A–Hedgehog signalling

Nature Cell Biology volume 19, pages 550–557 (2017)Cite this article

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Abstract

Microorganisms and their hosts share the same environment, and microbial metabolic molecules (metabolites) exert crucial effects on host physiology1. Environmental factors not only shape the composition of the host’s resident microorganisms, but also modulate their metabolism2. However, the exact molecular relationship among the environment, microbial metabolites and host metabolism remains largely unknown. Here, we discovered that environmental methionine tunes bacterial methyl metabolism to regulate host mitochondrial dynamics and lipid metabolism in Caenorhabditis elegans through an endocrine crosstalk involving NR5A nuclear receptor and Hedgehog signalling. We discovered that methionine deficiency in bacterial medium decreases the production of bacterial metabolites that are essential for phosphatidylcholine synthesis in C. elegans. Reductions of diundecanoyl and dilauroyl phosphatidylcholines attenuate NHR-25, a NR5A nuclear receptor, and release its transcriptional suppression of GRL-21, a Hedgehog-like protein. The induction of GRL-21 consequently inhibits the PTR-24 Patched receptor cell non-autonomously, resulting in mitochondrial fragmentation and lipid accumulation. Together, our work reveals an environment–microorganism–host metabolic axis regulating host mitochondrial dynamics and lipid metabolism, and discovers NR5A–Hedgehog intercellular signalling that controls these metabolic responses with critical consequences for host health and survival.

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Figure 1: Bacterial methyl metabolism links host lipid accumulation with environmental methionine availability.
Figure 2: Specific phosphatidylcholines mediate host lipid metabolic responses.
Figure 3: PCs act on NHR-25 to regulate host lipid metabolic responses.
Figure 4: Endocrine crosstalk of NHR-25 and Hedgehog signalling regulates host lipid metabolic responses by tuning mitochondrial dynamics.
Figure 5: Summary model.

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Acknowledgements

We thank J. Mello (Harvard Medical School, USA) for providing strains JM45 and JM43, J. Mamrosh (Caltech, USA) for providing MH1955 strain, HeLa cells and discussion, G. Ruvkun (Harvard Medical School, USA) for providing daf-16(mgDf47), J. J. Wang (University of Wisconsin-Madison, USA) for providing MG1655 bacteria and discussion, J. Sowa and I. Neve for providing OP50 RNAi bacteria, K. H. L. Mak for providing strain raxIs49, W. Dang and H. Liu for biochemical support, Y. Yu and A. S. Mutlu for the SRS support, A. Dervisefendic, H. D. Oakley and P. Svay for maintenance support, H. Liang and L. Han for RNA-seq bioinformatic support, C. Herman, D. Moore, A. Yu, A. Folick and S. Choi for discussions, and H. Dierick, C. Herman and C.-L. F. Li for critical reading of the manuscript. We appreciate the NBRP (Japan) and the CGC (USA) for providing mutant strains. The CGC is funded by NIH Office of Research Infrastructure Programs (P40 OD010440). This work was supported by grants from HHMI (M.C.W.) and National Institute of Health (R01AG045183, R01AT009050, DP1DK113644, M.C.W.), and in part by a training fellowship from the Burroughs Wellcome Fund—The Houston Laboratory and Population Science Training Program in Gene-Environment Interaction of the University of Texas Health Science Center at Houston (BWF Grant 1008200, C.-C.J.L.).

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Authors and Affiliations

  1. Huffington Center on Aging, Baylor College of Medicine, One Baylor Plaza, Houston, Texas 77030, USA

    Chih-Chun Janet Lin & Meng C. Wang

  2. Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, Texas 77030, USA

    Chih-Chun Janet Lin & Meng C. Wang

  3. Dan L. Duncan Cancer Center, Baylor College of Medicine, One Baylor Plaza, Houston, Texas 77030, USA

    Meng C. Wang

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  1. Chih-Chun Janet Lin
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Contributions

C.-C.J.L. and M.C.W. wrote the manuscript. C.-C.J.L. and M.C.W. conceived and designed the study. C.-C.J.L. conducted the experiments.

Corresponding author

Correspondence to Meng C. Wang.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Physiological measurements in C. elegans living on MG1655LB and MG1655M9.

(a) Adult C. elegans significantly increase or decrease fat content levels within 24 hours of switching to MG1655M9 or MG1655LB, respectively. ∗p < 0.05, ∗∗p < 0.01, Student’s t-test; n = 3 biologically independent experiments. (b,c) C. elegans raised on MG1655LB and on MG1655M9 show similar rates of pharyngeal pumping (b) and defecation (c), indicating comparable food intake rate and food retention time. Error bars represent standard deviation (SD). p > 0.05, Student’s t-test; n = 3 biologically independent experiments. (d) C. elegans raised on MG1655LB and MG1655M9 show indistinguishable rates of lipid absorption, assayed by a lipophilic BODIPY fluorescence dye. p > 0.05, Student’s t-test; n = 10 biologically independent animals. The box plots were generated to indicate ranges of min to max values, with 25th, 50th and 75th percentiles. (e–g) C. elegans raised on MG1655LB and MG1655M9 show similar levels of mobility (e, p > 0.05, Student’s t-test; n = 11 biologically independent animals), lifespan (f, p > 0.05, Log-rank test; n = 100 biologically independent animals), and brood size (g, p > 0.05, Student’s t-test; n = 18 biologically independent animals). The experiments were independently replicated in laboratory 3 times with similar results. (h) C. elegans raised on E. coli cultured in M9 medium supplemented with either peptone or casamino acids (CAA) show reduced lipid accumulation, compared with those on MG1655M9. ∗∗p < 0.01, ∗∗∗p < 0.001, Student’s t-test; n = 5 biologically independent experiments. (i) With bacteria killed by carbenicillin (60 μg/ml), MG1655M9-conferred lipid accumulation in C. elegans can still be significantly suppressed by supplementation of methionine but not betaine or homocysteine. ∗∗∗p < 0.001, ∗∗p < 0.01, n.s. p > 0.05, Student’s t-test. ##p < 0.01, n.s. p > 0.05, two-way ANOVA; n = 3 biologically independent experiments. (j) Mitochondrial DNA copy numbers are not significantly different among C. elegans raised on MG1655LB, MG1655LB+Methionine, MG1655M9, and MG1655M9+Methionine, n.s. p > 0.05, one-way ANOVA; n = 3 biologically independent experiments. (k) The fzo-1(tm1333) mutant exhibits completely fragmented mitochondrial morphology. p < 0.001, Chi-squared test; n = 50 biologically independent cells. The experiments were independently replicated in laboratory 3 times with similar results. Error bars represent mean ± standard error of the mean (SEM).

Supplementary Figure 2 Nutritional characterizations in E. coli MG1655LB and E. coli MG1655M9.

(a) Oxygen bomb calorimetry revealed similar caloric values in MG1655LB and MG1655M9. (b,c) The levels of triacylglycerides (b) and proteins (c) were measured biochemically and found no significant differences between MG1655LB and MG1655M9. n.s. p > 0.05, Student’s t-test; n = 7 biologically independent experiments (b), n = 5 biologically independent experiments (c). (d) MG1655M9 has a higher level of carbohydrates than MG1655LB. ∗p < 0.05, Student’s t test; n = 6 biologically independent experiments. (e) Fermenting MG1655LB+glucose (with 0.2% glucose), as verified in (f), is not sufficient to recapitulate MG1655M9-conferred lipid accumulation in C. elegans. C. elegans on MG1655LB (without glucose) served as negative controls. n.s. p > 0.05, Student’s t-test; n = 3 biologically independent experiments. (f) In phenol red fermentation tests, MG1655M9 shows positive fermentation (yellow), but MG1655LB shows negative fermentation (red). Addition of glucose (0.2%) to LB is sufficient to drive MG1655LB+glucose to undergo fermentation. The experiments were independently replicated in laboratory 3 times with similar results. Error bars represent mean ± SEM.

Supplementary Figure 3 Search of endocrine signaling candidates by bioinformatics.

The Venn diagram showing 188 overlapped genes that are differentially regulated between C. elegans grown on MG1655LB and MG1655M9 (NCBI BioProject ID PRJNA378539) and are found in NHR-25 ChIP-seq (modENCODE project, NCBI BioProject ID PRJNA13758). The identities of these 188 genes are listed in Supplementary Table 3a.

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Lin, CC., Wang, M. Microbial metabolites regulate host lipid metabolism through NR5A–Hedgehog signalling. Nat Cell Biol 19, 550–557 (2017). https://doi.org/10.1038/ncb3515

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