Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

The gut metabolite indole-3 propionate promotes nerve regeneration and repair

Abstract

The regenerative potential of mammalian peripheral nervous system neurons after injury is critically limited by their slow axonal regenerative rate1. Regenerative ability is influenced by both injury-dependent and injury-independent mechanisms2. Among the latter, environmental factors such as exercise and environmental enrichment have been shown to affect signalling pathways that promote axonal regeneration3. Several of these pathways, including modifications in gene transcription and protein synthesis, mitochondrial metabolism and the release of neurotrophins, can be activated by intermittent fasting (IF)4,5. However, whether IF influences the axonal regenerative ability remains to be investigated. Here we show that IF promotes axonal regeneration after sciatic nerve crush in mice through an unexpected mechanism that relies on the gram-positive gut microbiome and an increase in the gut bacteria-derived metabolite indole-3-propionic acid (IPA) in the serum. IPA production by Clostridium sporogenes is required for efficient axonal regeneration, and delivery of IPA after sciatic injury significantly enhances axonal regeneration, accelerating the recovery of sensory function. Mechanistically, RNA sequencing analysis from sciatic dorsal root ganglia suggested a role for neutrophil chemotaxis in the IPA-dependent regenerative phenotype, which was confirmed by inhibition of neutrophil chemotaxis. Our results demonstrate the ability of a microbiome-derived metabolite, such as IPA, to facilitate regeneration and functional recovery of sensory axons through an immune-mediated mechanism.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: IF promotes axonal regeneration affecting gut microbiota metabolites.
Fig. 2: IF promotes axonal regeneration through a gut gram-positive microbiome-dependent mechanism that produces IPA.
Fig. 3: IPA promotes axonal regeneration of DRG neurons after SNC.
Fig. 4: IPA-dependent axonal regeneration requires neutrophil chemotaxis and accelerates recovery of thermal heat sensation and epidermal innervation.

Similar content being viewed by others

Data availability

All RNA sequencing data are available from the NCBI GEO database under accession number GSE161342. Source data are provided with this paper.

References

  1. Scheib, J. & Hoke, A. Advances in peripheral nerve regeneration. Nat. Rev. Neurol. 9, 668–676 (2013).

    Article  CAS  PubMed  Google Scholar 

  2. Ferguson, T. A. & Son, Y. J. Extrinsic and intrinsic determinants of nerve regeneration. J. Tissue Eng. 2, 2041731411418392 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  3. Hutson, T. H. et al. Cbp-dependent histone acetylation mediates axon regeneration induced by environmental enrichment in rodent spinal cord injury models. Sci. Transl. Med. 11, eaaw2064 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Mattson, M. P., Moehl, K., Ghena, N., Schmaedick, M. & Cheng, A. Intermittent metabolic switching, neuroplasticity and brain health. Nat. Rev. Neurosci. 19, 63–80 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Longo, V. D. & Mattson, M. P. Fasting: molecular mechanisms and clinical applications. Cell Metab. 19, 181–192 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Asplund, M., Nilsson, M., Jacobsson, A. & von Holst, H. Incidence of traumatic peripheral nerve injuries and amputations in Sweden between 1998 and 2006. Neuroepidemiology 32, 217–228 (2009).

    Article  PubMed  Google Scholar 

  7. Evans, G. R. Peripheral nerve injury: a review and approach to tissue engineered constructs. Anat. Rec. 263, 396–404 (2001).

    Article  CAS  PubMed  Google Scholar 

  8. Taylor, C. A., Braza, D., Rice, J. B. & Dillingham, T. The incidence of peripheral nerve injury in extremity trauma. Am. J. Phys. Med. Rehabil. 87, 381–385 (2008).

    Article  PubMed  Google Scholar 

  9. Seddighi, A. et al. Peripheral nerve injury: a review article. Int. Clin. Neurosci. J. 3, 1–6 (2016).

    Google Scholar 

  10. Li, R. et al. Peripheral nerve injuries treatment: a systematic review. Cell Biochem. Biophys. 68, 449–454 (2014).

    Article  CAS  PubMed  Google Scholar 

  11. Lee, S. K. & Wolfe, S. W. Peripheral nerve injury and repair. J. Am. Acad. Orthop. Surg. 8, 243–252 (2000).

    Article  CAS  PubMed  Google Scholar 

  12. Mahar, M. & Cavalli, V. Intrinsic mechanisms of neuronal axon regeneration. Nat. Rev. Neurosci. 19, 323–337 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Lindborg, J. A. et al. Molecular and cellular identification of the immune response in peripheral ganglia following nerve injury. J. Neuroinflammation 15, 192 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  14. Strand, N. S. et al. Wnt/β-catenin signaling promotes regeneration after adult zebrafish spinal cord injury. Biochem. Biophys. Res. Commun. 477, 952–956 (2016).

    Article  CAS  PubMed  Google Scholar 

  15. Ghosh, S. & Hui, S. P. Axonal regeneration in zebrafish spinal cord. Regeneration 5, 43–60 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Shimizu, Y., Ueda, Y. & Ohshima, T. Wnt signaling regulates proliferation and differentiation of radial glia in regenerative processes after stab injury in the optic tectum of adult zebrafish. Glia 66, 1382–1394 (2018).

    Article  PubMed  Google Scholar 

  17. Chandran, V. et al. A systems-level analysis of the peripheral nerve intrinsic axonal growth program. Neuron 89, 956–970 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Fann, D. Y. et al. Intermittent fasting attenuates inflammasome activity in ischemic stroke. Exp. Neurol. 257, 114–119 (2014).

    Article  CAS  PubMed  Google Scholar 

  19. Fann, D. Y., Ng, G. Y., Poh, L. & Arumugam, T. V. Positive effects of intermittent fasting in ischemic stroke. Exp. Gerontol. 89, 93–102 (2017).

    Article  PubMed  Google Scholar 

  20. Jeong, M. A. et al. Intermittent fasting improves functional recovery after rat thoracic contusion spinal cord injury. J. Neurotrauma 28, 479–492 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Plunet, W. T. et al. Dietary restriction started after spinal cord injury improves functional recovery. Exp. Neurol. 213, 28–35 (2008).

    Article  PubMed  Google Scholar 

  22. Fontan-Lozano, A. et al. Caloric restriction increases learning consolidation and facilitates synaptic plasticity through mechanisms dependent on NR2B subunits of the NMDA receptor. J. Neurosci. 27, 10185–10195 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Dasgupta, A., Kim, J., Manakkadan, A., Arumugam, T. V. & Sajikumar, S. Intermittent fasting promotes prolonged associative interactions during synaptic tagging/capture by altering the metaplastic properties of the CA1 hippocampal neurons. Neurobiol. Learn. Mem. 154, 70–77 (2017).

    Article  PubMed  Google Scholar 

  24. Lee, J., Seroogy, K. B. & Mattson, M. P. Dietary restriction enhances neurotrophin expression and neurogenesis in the hippocampus of adult mice. J. Neurochem. 80, 539–547 (2002).

    Article  CAS  PubMed  Google Scholar 

  25. Hervera, A. et al. Reactive oxygen species regulate axonal regeneration through the release of exosomal NADPH oxidase 2 complexes into injured axons. Nat. Cell Biol. 20, 307–319 (2018).

    Article  CAS  PubMed  Google Scholar 

  26. Poplawski, G. et al. Schwann cells regulate sensory neuron gene expression before and after peripheral nerve injury.Glia 66, 1577–1590 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  27. Lindsay, R. M. Nerve growth factors (NGF, BDNF) enhance axonal regeneration but are not required for survival of adult sensory neurons. J. Neurosci. 8, 2394–2405 (1988).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Hollis, E. R.II, Jamshidi, P., Löw, K., Blesch, A. & Tuszynski, M. H. Induction of corticospinal regeneration by lentiviral trkB-induced Erk activation. Proc. Natl Acad. Sci. USA 106, 7215–7220 (2009).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  29. Liu, Y. et al. NT-3 promotes proprioceptive axon regeneration when combined with activation of the mTor intrinsic growth pathway but not with reduction of myelin extrinsic inhibitors. Exp. Neurol. 283, 73–84 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Boyd, J. G. & Gordon, T. Neurotrophic factors and their receptors in axonal regeneration and functional recovery after peripheral nerve injury. Mol. Neurobiol. 27, 277–324 (2003).

    Article  CAS  PubMed  Google Scholar 

  31. Hoke, A. et al. Schwann cells express motor and sensory phenotypes that regulate axon regeneration. J. Neurosci. 26, 9646–9655 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Anson, R. M. et al. Intermittent fasting dissociates beneficial effects of dietary restriction on glucose metabolism and neuronal resistance to injury from calorie intake. Proc. Natl Acad. Sci. USA 100, 6216–6220 (2003).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  33. Patterson, R. E. & Sears, D. D. Metabolic effects of intermittent fasting. Annu. Rev. Nutr. 37, 371–393 (2017).

    Article  CAS  PubMed  Google Scholar 

  34. Aragozzini, F., Ferrari, A., Pacini, N. & Gualandris, R. Indole-3-lactic acid as a tryptophan metabolite produced by Bifidobacterium spp. Appl. Environ. Microbiol. 38, 544–546 (1979).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  35. Zhang, L. S. & Davies, S. S. Microbial metabolism of dietary components to bioactive metabolites: opportunities for new therapeutic interventions. Genome Med. 8, 46 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Dodd, D. et al. A gut bacterial pathway metabolizes aromatic amino acids into nine circulating metabolites. Nature 551, 648–652 (2017).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  37. Qiu, Z. et al. Pregnane X receptor regulates pathogen-induced inflammation and host defense against an intracellular bacterial infection through toll-like receptor 4. Sci. Rep. 6, 31936 (2016).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  38. Venkatesh, M. et al. Symbiotic bacterial metabolites regulate gastrointestinal barrier function via the xenobiotic sensor PXR and Toll-like receptor 4. Immunity 41, 296–310 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Alexeev, E. E. et al. Microbiota-derived indole metabolites promote human and murine intestinal homeostasis through regulation of interleukin-10 receptor. Am. J. Pathol. 188, 1183–1194 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Hudson, G. et al. Pregnane X receptor activation triggers rapid ATP release in primed macrophages that mediates NLRP3 inflammasome activation. J. Pharmacol. Exp. Ther. 370, 44–53 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Wang, S. et al. Xenobiotic pregnane X receptor (PXR) regulates innate immunity via activation of NLRP3 inflammasome in vascular endothelial cells. J. Biol. Chem. 289, 30075–30081 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Biondo, C. et al. The interleukin-1β/CXCL1/2/neutrophil axis mediates host protection against group B streptococcal infection. Infect. Immun. 82, 4508–4517 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Dubrac, S., Elentner, A., Ebner, S., Horejs-Hoeck, J. & Schmuth, M. Modulation of T lymphocyte function by the pregnane X receptor. J. Immunol. 184, 2949–2957 (2010).

    Article  CAS  PubMed  Google Scholar 

  44. Schote, A. B., Turner, J. D., Schiltz, J. & Muller, C. P. Nuclear receptors in human immune cells: expression and correlations. Mol. Immunol. 44, 1436–1445 (2007).

    Article  CAS  PubMed  Google Scholar 

  45. Lindborg, J. A., Mack, M. & Zigmond, R. E. Neutrophils are critical for myelin removal in a peripheral nerve injury model of Wallerian degeneration. J. Neurosci. 37, 10258–10277 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Stirling, D. P., Liu, S., Kubes, P. & Yong, V. W. Depletion of Ly6G/Gr-1 leukocytes after spinal cord injury in mice alters wound healing and worsens neurological outcome. J. Neurosci. 29, 753–764 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Kurimoto, T. et al. Neutrophils express oncomodulin and promote optic nerve regeneration. J. Neurosci. 33, 14816–14824 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Sas, A. R. et al. A new neutrophil subset promotes CNS neuron survival and axon regeneration. Nat. Immunol. 21, 1496–1505 (2020).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  49. Kigerl, K. A. et al. Gut dysbiosis impairs recovery after spinal cord injury. J. Exp. Med. 213, 2603–2620 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Staudinger, J. L. et al. The nuclear receptor PXR is a lithocholic acid sensor that protects against liver toxicity. Proc. Natl Acad. Sci. USA 98, 3369–3374 (2001).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  51. Li,M.,Fecal microbiota transplantation and bacterial consortium transplantation have comparable effects on the re-establishment of mucosal barrier function in mice with intestinal dysbiosis. Front. Microbiol. 6, 692 (2015).

    PubMed  PubMed Central  Google Scholar 

  52. Zhou, D. et al. Total fecal microbiota transplantation alleviates high-fat diet-induced steatohepatitis in mice via beneficial regulation of gut microbiota. Sci. Rep. 7, 1529 (2017).

    Article  PubMed  PubMed Central  ADS  CAS  Google Scholar 

  53. Behrends, V., Tredwell, G. D. & Bundy, J. G. A software complement to AMDIS for processing GC-MS metabolomic data. Anal. Biochem. 415, 206–208 (2011).

    Article  CAS  PubMed  Google Scholar 

  54. Trygg, J. & Wold, S. Orthogonal projections to latent structures (O-PLS). J. Chemom. 16, 119–128 (2002).

    Article  CAS  Google Scholar 

  55. Thévenot, E. A., Roux, A., Xu, Y., Ezan, E. & Junot, C. Analysis of the human adult urinary metabolome variations with age, body mass index, and gender by implementing a comprehensive workflow for univariate and OPLS statistical analyses. J. Proteome Res. 14, 3322–3335 (2015).

    Article  PubMed  CAS  Google Scholar 

  56. Callahan, B. J. et al. DADA2: high-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. McMurdie, P. J. & Holmes, S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8, e61217 (2013).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  58. McMurdie, P. J. & Holmes, S. Waste not, want not: why rarefying microbiome data is inadmissible. PLoS Comput. Biol. 10, e1003531 (2014).

    Article  PubMed  PubMed Central  ADS  CAS  Google Scholar 

  59. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  60. Iwai, S. et al. Piphillin: improved prediction of metagenomic content by direct inference from human microbiomes. PLoS ONE 11, e0166104 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

Download references

Acknowledgements

We thank I. Palmisano for reading the manuscript and providing feedback, K. Shkura for providing guidance on computational analysis and S. Mani for providing PXRKO sperm. This work was supported by start-up funds from the Department of Brain Sciences, Imperial College London (S.D.G.); Wings for Life (S.D.G.); Rosetrees Trust (S.D.G.); Spinal Research (S.D.G.); and the Imperial PhD Presidential Scholarship (J.S.C.). The laboratory of M.E.D. has received funding by METACARDIS (HEALTH-F4-2012-305312) and the UK Medical Research Council (MRC grants “µNeuroInf” MR/M501797/1 and “National Mouse Genetics Network Microbiome Cluster” MR/W022532/1), and by grants from the French National Research Agency (ANR-10-LABX-46 [European Genomics Institute for Diabetes]), from the National Center for Precision Diabetic Medicine – PreciDIAB, which is jointly supported by the French National Agency for Research (ANR-18-IBHU-0001), by the European Union (FEDER), by the Hauts-de-France Regional Council (Agreement 20001891/NP0025517) and by the European Metropolis of Lille (MEL, Agreement 2019_ESR_11) and by Isite ULNE (R-002-20-TALENT-DUMAS), also jointly funded by ANR (ANR-16-IDEX-0004-ULNE), the Hauts-de-France Regional Council (20002845) and by the European Metropolis of Lille (MEL). This research was also supported by the National Institute for Health Research (NIHR) Imperial Biomedical Research Centre (MED, S.D.G.). Diagrams in the figures were created with BioRender.com. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.

Author information

Authors and Affiliations

Authors

Contributions

E.S. designed the study, performed experiments and data analysis and wrote the manuscript. J.S.C., L.L.-G., G.K., L.Z., G.C., A.M., A.B. and A.S.-V. performed experiments and data analysis. F.M. and A.T.B. performed data analysis. P.L. and F.D.V. performed experiments. M.E.D. performed data analysis and edited the manuscript; J.S., S.M. and D.D. provided experimental advice and edited the manuscript. S.D.G. designed experiments, provided funding and wrote the manuscript.

Corresponding author

Correspondence to Simone Di Giovanni.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature thanks Gerard Clarke, Roman Giger and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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 Intermittent fasting promotes axonal regeneration and DRG neurite outgrowth. Assessment of macrophages, Schwann cells and neurotrophic factors in the nerve and DRG in IF vs AL following sciatic injury.

a. Schematic of the experimental design. Mice underwent either 10 days or 30 days of intermittent fasting regime, followed a sciatic nerve crush and 24 h of axonal regeneration. b. Micrographs showing representative longitudinal sections of sciatic nerves stained with SCG-10 and ßIII-Tubulin (ßIIITub) 24 h after SNC. The dashed lines indicate the crush site at 0 and the distances of 500 µm and 1,000 µm from the crush site. c. Quantification of the percentage of SCG-10 positive fibers and normalised to the number of fibers at the crush site. (N = 4 biologically independent animals per group with a bilateral sciatic nerve crush, two-way-ANOVA with Tukey’s multiple comparisons test, data are presented as mean values +/− SEM). d. Schematic of the experimental design. e. Representative images of DRG neurons immunostained with ßIII-Tubulin (ßIIITub). f. Quantification of DRG neurite outgrowth (N = 4 biologically independent animals per group, two-sided Student’s unpaired t-test, Scale bar: 100 µm, examined over two independent experiments, data are presented as mean values +/− SEM). g-h. Representative images of nerves dissected from 10 days AL or IF treated animals at 3 days post sciatic injury. Sections were immunostained for a) CD68 (macrophage marker, red) or b) SOX10 (Schwann cell marker, white). Scale bar 500 µm. Asterisk indicates the crush site. i. Quantification of CD68 (red) was conducted by intensity measurements 1,000 µm proximal and distal to the crush site (N = 6 nerves per group from 3 biologically independent animals per group, data are presented as mean values +/− SEM). j. Quantification of SOX10 (white) was conducted by intensity measurements 1,000 µm proximal and distal to the crush site (N = 5 nerves per group from 3 biologically independent animals per group, data are presented as mean values +/- SEM) k. ELISA measurements of NGF, BDNF, NT3 and NT4/5 from DRG tissue following 10 days IF or AL (N = 3 biologically independent animals per group, data are presented as mean values +/ − SEM). Samples were collected on the refed day.

Source data

Extended Data Fig. 2 O-PLS-DA model discriminating AL and IF groups with and without Vancomycin using GC-MS-based metabolic profiles. Faecal microbiota transplantation from IF mice promote axonal regeneration.

a. Score plot of the O-PLS-DA model of the IF group vs AL group. The number of components and the cumulative R2X, R2Y and Q2Y are indicated below the plot. b. Significance diagnostic of the OPLS-DA: the R2Y and Q2Y of the model are compared with the corresponding values obtained after random permutation (1,000) of the y response. c. Model overview: Inertia bar plot. d. Schematic of the experiment presented in b and c. Faecal transplantation of faeces from either IF or AL mice for 1 days, followed by sciatic nerve crush and 3 days of axonal regeneration time. e. Micrographs of representative longitudinal sections of sciatic nerves after faecal transplantation from AL and IF treated mice, 3 days post sciatic nerve crush, immunostained with SCG-10. Scale bar: 1,000 µm. The dashed line indicates the crush site. f. Quantification of the percentage of fibers past the crush site and normalised to the number of fibers at the crush site revealed increased regeneration in IF-FMT mice compared to AL-FMT (N = 4 biologically independent animals per group; ****p < 0.0001, two-way-ANOVA with Tukey’s multiple comparisons test, data are presented as mean values +/− SEM). g. Score plot of the PLS-DA model discriminating IF, AL, IF+V and AL+V. h. Permutation testing of the PLS-DA model: the R2Y and Q2Y of the original model are compared with the corresponding values obtained after random permutation of the group classes (n = 1,000 iterations). i. Model overview: Inertia bar plot. j. Table showing metabolites differentially enriched in the serum of IF vs AL treated mice. Shown are the log fold change (logFC), IFvsAL p-value, vancomycin vs non-vancomycin (Ab vs non-Ab) p-value and the interaction p-value between intermittent fasting and vancomycin treatment (interaction) (bold p < 0.001, partial least-squares discriminant analysis was used to identify the significantly differential metabolites between the groups). R-square (Rsq, the coefficient of determination) showed the highest predictability (79.4%) for indole-3-propionic acid.

Source data

Extended Data Fig. 3 16S rDNA amplicon sequencing reveals increased number of Clostridiales following intermittent fasting.

a. Shannon index reveals significant differences in Alpha diversity between vancomycin vs non-vancomycin treated groups (16S sequencing was carried out from cecum of AL, AL+vancomyin, IF, IF+vancomycin treated animals (N = 8 biologically independent animals per group, unpaired, two-sided Mann Whitney U test). The centre line shows the median value (50th percentile), while the box edges correspond to the 25th (Q1) to 75th (Q3) percentiles of dataset. The whiskers mark 1.5 x IQR (interquartile range) below Q1 and above Q3. b. Beta diversity reveals differences in microbiota composition between IF and AL groups c-d. Relative abundance (%) of bacterial phyla (c) and bacterial order (d) between AL, AL+ vancomycin, IF and IF+ vancomycin. e. Plot showing that the top 25 bacterial Amplicon sequence variants (ASVs) that are statistically different (p < 0.05, FDR corrected, plotted as log2FoldChange, data are presented as mean values +/ − SEM) between IF and AL belong to either Bacteroidetes or Firmicutes phyla, Bacteroida or Clostridia classes and Bacteroidales or Clostridiales orders.

Extended Data Fig. 4 Piphillin analysis reveals increased abundance of specific metabolic pathways.

Error bar blot showing the abundance of selected KEGG pathways compared between the four treatment groups (n=8 biologically independent animals per group, Tukey-Kramer post-hoc test, mean +/ − SD). The plot provides a p-value and effect size measure for each pair of groups. Of the pathways of interest we selected, “Xenobiotic biodegradation and metabolism”, “Drug resistance: antimicrobial” and “Metabolism of cofactors and vitamins” showed significantly higher abundance in IF vs AL, which was abolished in IF+V.

Extended Data Fig. 5 Indole-3-proprionate-dependent axonal regeneration.

a. Schematic of the experiment presented in b and c. Mice were gavaged with 10 mg/kg IPA daily for 10 days followed by 3 days of regeneration time post sciatic nerve crush. b. Micrographs of representative longitudinal sections of sciatic nerves immunostained with SCG-10. Scale bar: 1000 µm. The dashed line indicates the crush site. c. Quantification of the percentage of fibers past the crush site at the indicated distances and normalised to the number of fibers at the crush site. revealed no difference in regeneration potential when treated with 10 mg/kg/day. (N = 4 biologically independent animals per group with a bilateral sciatic nerve crush, two-way-ANOVA with Sidak multiple comparisons test, data are presented as mean values +/ − SEM). d. Quantification of IPA concentration in serum at 20 min, 1 h, 6 h and 12 h post gavage of 20 mg/kg IPA. e. Quantification of IPA concentration in naïve DRG tissue at 20 min, 1 h, 6 h and 12 h post gavage of 20 mg/kg IPA. f. Schematic of the experiment presented in g and h. Mice received daily intraperitoneal injections of 20 mg/kg IPA for 10 days, followed by 3 days of regeneration time post sciatic nerve crush. g. Micrographs of representative longitudinal sections of sciatic nerves immunostained with SCG-10. Scale bar: 1000 µm. The dashed line indicates the crush site. h. Quantification of the percentage of fibers past the crush site at the indicated distances and normalised to the number of fibers at the crush site in nerves of mice injected intraperitoneally with 20 mg/kg/day IPA (N = 4 biologically independent animals per group, ****P < 0.0001, two-way-ANOVA with Sidak test, data are presented as mean values +/ − SEM). i. DRG neurons were treated with 10 μM, 100 μM and 1000 μM IPA. Representative images of DRG neurons immunostained with ßIII-Tub. Scale bar: 50 µm. j. Quantification of neurite outgrowth by measuring the length of neurites (N = 4 independent experiments per group; one-way ANOVA, Dunnett’s multiple comparisons test, examined over two experiments, data are presented as mean values +/ − SEM). k+m. Micrographs of representative sections of DRG slices 72h post dextran injection to the nerve co-immunostained for neuronal markers NF200 and IB4. Scale bar: 200 µm. l+n. Quantification of the percentage of double positive NF200+ and IB4+ neurons in IPA and PBS post-injury treated sciatic DRG (N = 5 biologically independent animals per group, Student’s unpaired t-test, data are presented as mean values +/ − SEM).

Source data

Extended Data Fig. 6 RNA sequencing from DRG following IPA treatment and injury and increased number of neutrophils in the DRG following IPA treatment.

a-b. Shown are heatmaps of differentially regulated genes (FPKMs, P < 0.05) following 10 days IPA vs PBS treatment as, preceding (a) and 3 days following SN crush (b). Green: downregulated, red: upregulated. c. Heatmap showing the logarithmic expression fold change (logFC (P < 0.05)) of all genes belonging to “Neutrophil-Endothelial interaction” or “BP Neutrophil chemotaxis” GO class for the comparisons IPA-SNCvsPBS, PBS-SNCvsPBS and IPAvsPB. d. Representative image of a DRG stained for Ly6G (red), ßIIITubulin (ßIIITub, green) and DAPI (blue). Scale bar: 100 µm. e. Quantitative analysis of neutrophils, shown as number of neutrophils per 1 mm2 (N = 4 biologically independent animals per group, One-way Anova with Holm-Sidak multiple comparison test, if not indicated otherwise p-value compares to PBS group, data are presented as mean values +/ − SEM). f. Representative images of Ly6G+ cells in DRG tissue. Scale bar: 50 µm. g. Images of the sciatic nerve crush site, immunostained for Ly6G (red) after IPA and PBS treatment. Asterisk indicates the crush site. Scale bar: 250 µm. Magnified image scale bar: 50 µm. h. Quantitative analysis showing the number of neutrophils 1000 µm proximal and distal to the crush site (N = 4 biologically independent animals per group, data are presented as mean values +/ − SEM). i. FACS analysis of the nerve crush site following 10 days of IPA treatment and 3 days SNC. j+k. Bar graphs showing Ly6G+ cell counts (g) and percentage of Ly6G+ cells of the total CD45+ cells (h) in nerve crush site 3 days following SNC (N = 3 biologically independent animals per group, data are presented as mean values +/ − SEM).

Source data

Extended Data Fig. 7 FACS gating strategies.

a. Gating strategy for the quantification of Ly6G+hi neutrophils (as % of CD45+ and total cell counts) from the nerve crush site following IPA or PBS treatment (corresponding to Extended Data Fig. 6i–k). b. Gating strategy for the verification of neutrophil depletion following αLy6G or αIgG2A treatment (corresponding to Extended Data Fig. 8h, i). Gr-1+ neutrophils were quantified from the spleen as percentage of CD45+.

Source data

Extended Data Fig. 8 Immune cell quantification following IPA and PBS treatment including 3 days after SNC.

a. CD8, CD4, B220, CD68 and NK1.1 (red) coimmunostained with βIIITubulin (green) and DAPI (blue) in DRG sections from IPA and PBS treated groups 3 days after SNC. Scale bar: 50 µm. Scale bar in magnification: 10 µm. b. Quantification of CD8 T-cells, CD4 T-cells, B-cells (B220), Macrophages (CD68) and NK cells (NK1.1) number in IPA and PBS treated DRG 3 days after SNC (N = 4 biologically independent animals per group, Student’s unpaired t-test, data are presented as mean values +/− SEM).

Source data

Extended Data Fig. 9 Reduced regeneration following neutrophil depletion and in PXR KO mice.

a. Schematic of the experiment presented in b and c. Mice were cotreated for 10 days with either IPA (20 mg/kg/day) or PBS and anti-IgG or anti-Ly6G, followed by a sciatic nerve crush and 3 days of regeneration time. b. Quantification of the percentage of fibers past the crush site at the indicated distances and normalised to the number of fibers at the crush site. (N = 4 biologically independent animals per group with a bilateral sciatic nerve crush; ****p < 0.0001, two-way-ANOVA with Tukey’s multiple comparisons test, data are presented as mean values +/ − SEM). c. Micrographs of representative longitudinal sections of sciatic nerves immunostained with SCG-10. Scale bar: 1000 µm. The dashed line indicates the crush site. d. Representative images of Ly6G immunostaining in sciatic nerve sections (crush site) of mice treated with IPA or PBS and anti-Ly6G or anti-IgG monoclonal antibody 3 days after SNC. Scale bar: 250 µm. Scale bar in magnification: 50 µm. e. Quantification of the number of Ly6G+ cells in the sciatic nerve crush site of mice treated with IPA or PBS and anti-Ly6G or anti-IgG monoclonal antibody 3 days after SNC (N = 4 biologically independent animals per group with a bilateral sciatic nerve crush, One-way Anova with Holm-Sidak multiple comparisons test, data are presented as mean values +/ − SEM). f. Representative images of Ly6G immunostaining in sciatic DRG sections of mice treated with IPA or PBS and anti-Ly6G or anti-IgG monoclonal antibody 3 days after SNC. Scale bar: 50 µm. g. Quantification of the number of Ly6G+ cells in sciatic DRG sections of mice treated with IPA or PBS and anti-Ly6G or anti-IgG monoclonal antibody 3 days after SNC (N = 4 biologically independent animals per group, one way Anova with Tukey’s multiple comparisons test. Data are presented as mean values +/− SEM). h. Representative flow cytometry plots showing Ly6G+ neutrophil depletion following anti-Ly6G monoclonal antibody vs control IgG. i. Quantification of the percentage of neutrophils of the total CD45+ cells in spleen following control IgG or anti-Ly6G monoclonal antibody treatment (N = 4 biologically independent animals per group, two-sided Student’s unpaired t-test, data are presented as mean values +/− SEM). j. Representative images of Ly6G immunostaining in sciatic DRG sections of PXR WT (PXR+/+) and PXR KO (PXR−/−) mice treated with IPA or PBS for 3 days following SNC. Scale bar: 50 µm. k. Quantification of the number of Ly6G+ cells in sciatic DRG sections of PXR WT (PXR+/+) and PXR KO (PXR-/-) mice treated with IPA or PBS for 3 days following SNC (N = 4 biologically independent animals per group, One-way Anova with Tukey’s multiple comparisons test, data are presented as mean values +/ − SEM). l. Micrographs of representative longitudinal sections of sciatic nerves of PXR WT (PXR+/+) and PXR KO (PXR−/−) mice treated with IPA or PBS for 3 days following SNC immunostained with SCG-10. Scale bar: 1000 µm. The dashed line indicates the crush site. m. Schematic of the experiment presented in l and n. n. Quantification of the percentage of fibers past the crush site at the indicated distances and normalised to the number of fibers at the crush site. (N = 4 biologically independent animals per group with a bilateral sciatic nerve crush, ****p < 0.0001, two-way-ANOVA with Tukey’s multiple comparison test, data are presented as mean values +/− SEM).

Source data

Extended Data Fig. 10 Increased number of CXCR2+ neutrophils following IPA treatment and depletion with anti-CXCR2 antibody in nerve tissue.

a. Representative images of CXCR2+Ly6G+ cells in DRG tissue. Scale bar: 20 µm. b. Quantitative analysis of CXCR2+Ly6G+ cells in DRG tissue (N = 4 biologically independent animals per group, two-sided Student t-test, p-value compares CXCR2+Ly6G+ groups, data are presented as mean values +/ − SEM). c. Representative images of Ly6G immunostaining in sciatic nerve sections (crush site) of mice treated with IPA or PBS and anti-CXCR2 or anti-IgG monoclonal antibody 3 days after SNC. Scale bar: 250 µm. Scale bar in magnification: 50 µm. d. Quantification of the number of Ly6G+ cells in the sciatic nerve crush site of mice treated with IPA or PBS and anti-CXCR2 or anti-IgG monoclonal antibody 3 days after SNC (N = 4 biologically independent animals per group with a bilateral sciatic nerve crush; data are presented as mean values +/− SEM).

Source data

Extended Data Fig. 11 IFNy is required for IPA-dependent axonal regeneration after SNC and increases RAG phosphorylation and expression in DRG neurons.

a. Table showing IPA dependently upregulated genes assigned to GO BP cellular response to interferon gamma before and after injury. b-c. Mice were treated for 10 days with either IPA (20 mg/kg/day) or PBS (by gavage) and injected (IP) with anti-IFNγ/ anti-IgG/PBS (IFNγ neutralisation). Axonal regeneration was assessed at 3 days post sciatic nerve crush. b. Micrographs of representative longitudinal sections of sciatic nerves for all groups immunostained with SCG-10 following. Scale bar: 1000 µm. The dashed line indicates the crush site. c. Quantification of the percentage of fibers past the crush site at the indicated distances and normalised to the number of fibers at the crush site. (N = 4 biologically independent animals per group with a bilateral sciatic nerve crush, ****p < 0.0001, by two-way-ANOVA with Tukey’s multiple comparisons test, comparing IPA-αIFNγ and IPA-αIgG, data are presented as mean values +/− SEM). d-e. Ex vivo culture of DRG neurons 48 h after IFNγ i.p. injection. d. Representative images of DRG neuron for each treatment, immunostained with ßIII-Tubulin (ßIIITub, white). Scale bar: 100 μm. e. Quantification of DRG neurite outgrowth (n = 3 independent experiments per group, two-sided Student’s t-test, data are presented as mean values +/ − SEM). f-g. DRG neurons were treated with 5 ng/ml of IFNγ and co-treated with increasing concentrations of αIFNγR (0 ng/ml, 100 ng/ml, 200 ng/ml) in vitro and neurite outgrowth was assessed. f. Representative images of DRG neurons for each treatment were immunostained with ßIII-Tubulin (ßIIITub). Cultured for 12 h. Scale bar: 100 μm. g. Quantification of DRG neurite outgrowth (N = 3 independent experiments per group; one-way ANOVA with Dunnett’s multiple comparisons test, data are presented as mean values +/− SEM). h. Immunofluorescence of DRG sections from mice at three days post sciatic nerve crush for NCAM and IFNγR reveal expression of IFNγ receptor in DRG neurons, Scale bar: 50 µm. i. Immunofluorescence of the sciatic crush site at three days post sciatic nerve crush for bIIITubulin and IFNγR reveal the lack of expression of IFNγ receptor in DRG peripheral axons. Scale bar: 200 µm. Scale bar in magnified image: 50 µm. j. Immunohistochemistry of DRG sections from IFNγ or vehicle for regeneration associated genes (RAGs, red): MYC, pMYC, GAP43, ATF3, pERK, pAKT, cJUN, p-cJUN, co-stained for bIIITubulin (green). k. Quantification of RAGs as intensity or % of positive neurons versus total of IFNγ compared to vehicle treated (N = 4 biologically independent animals per group with a bilateral crush, Student’s t-test, data are presented as mean values +/− SEM). Scale bar: 50 µm.

Supplementary information

Reporting Summary

Peer Review File

Supplementary Data 1

16S-Seq DESeq2 data

Supplementary Data 2

16S-Seq percentage abundances

Supplementary Data 3

IPA RNAseq DE genes

Supplementary Data 4

IPA-dependent DE genes

Supplementary Data 5

IPA vs PBS RNAseq GOBP

Source data

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Serger, E., Luengo-Gutierrez, L., Chadwick, J.S. et al. The gut metabolite indole-3 propionate promotes nerve regeneration and repair. Nature 607, 585–592 (2022). https://doi.org/10.1038/s41586-022-04884-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41586-022-04884-x

This article is cited by

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.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing