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 microbiome modulates gut–brain axis glycerophospholipid metabolism in a region-specific manner in a nonhuman primate model of depression

Abstract

Emerging research demonstrates that microbiota-gut–brain (MGB) axis changes are associated with depression onset, but the mechanisms underlying this observation remain largely unknown. The gut microbiome of nonhuman primates is highly similar to that of humans, and some subordinate monkeys naturally display depressive-like behaviors, making them an ideal model for studying these phenomena. Here, we characterized microbial composition and function, and gut–brain metabolic signatures, in female cynomolgus macaque (Macaca fascicularis) displaying naturally occurring depressive-like behaviors. We found that both microbial and metabolic signatures of depressive-like macaques were significantly different from those of controls. The depressive-like monkeys had characteristic disturbances of the phylum Firmicutes. In addition, the depressive-like macaques were characterized by changes in three microbial and four metabolic weighted gene correlation network analysis (WGCNA) clusters of the MGB axis, which were consistently enriched in fatty acyl, sphingolipid, and glycerophospholipid metabolism. These microbial and metabolic modules were significantly correlated with various depressive-like behaviors, thus reinforcing MGB axis perturbations as potential mediators of depression onset. These differential brain metabolites were mainly mapped into the hippocampal glycerophospholipid metabolism in a region-specific manner. Together, these findings provide new microbial and metabolic frameworks for understanding the MGB axisʼ role in depression, and suggesting that the gut microbiome may participate in the onset of depressive-like behaviors by modulating peripheral and central glycerophospholipid metabolism.

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

Access options

Buy this article

USD 39.95

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

Fig. 1: Behavioral phenotypes of healthy (HC) versus depressive-like (DL) M. fascicularis.
Fig. 2: Gut microbiome differences in healthy (HC) versus depression-like (DL) M. fascicularis.
Fig. 3: Metagenomic species (MGS) differences in healthy (HC) versus depression-like (DL) M. fascicularis.
Fig. 4: Metagenomic modules correlate with depressive-like (DL) phenotypes in M. fascicularis.
Fig. 5: Metabolomic correlations with behavioral phenotypes in depressive-like (DL) M. fascicularis.
Fig. 6: Disturbance of hippocampal glycerophospholipid metabolism in depressive-like (DL) M. fascicularis.

Similar content being viewed by others

References

  1. Frankish H, Boyce N, Horton R. Mental health for all: a global goal. Lancet. 2018;392:1493–4.

    Article  PubMed  Google Scholar 

  2. Yano JM, Yu K, Donaldson GP, Shastri GG, Ann P, Ma L, et al. Indigenous bacteria from the gut microbiota regulate host serotonin biosynthesis. Cell. 2015;161:264–76.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Warden D, Rush AJ, Trivedi MH, Fava M, Wisniewski SR. The STAR*D Project results: a comprehensive review of findings. Curr psychiatry Rep. 2007;9:449–59.

    Article  PubMed  Google Scholar 

  4. Ruelaz AR. Treatment-resistant depression: strategies for management. 2006;23:34–7.

  5. Willner P. Validity, reliability and utility of the chronic mild stress model of depression: a 10-year review and evaluation. Psychopharmacology. 1997;134:319–29.

    Article  CAS  PubMed  Google Scholar 

  6. Willner P. Chronic mild stress (CMS) revisited: consistency and behavioural-neurobiological concordance in the effects of CMS. Neuropsychobiology. 2005;52:90–110.

    Article  CAS  PubMed  Google Scholar 

  7. Canuto A, Weber K, Baertschi M, Andreas S, Volkert J, Dehoust MC, et al. Anxiety disorders in old age: psychiatric comorbidities, quality of life, and prevalence according to age, gender, and country. Am J Geriatr Psychiatry. 2018;26:174–85.

    Article  PubMed  Google Scholar 

  8. Hassard J, Teoh KRH, Visockaite G, Dewe P, Cox T. The cost of work-related stress to society: a systematic review. J Occup Health Psychol. 2018;23:1–17.

    Article  PubMed  Google Scholar 

  9. Sheikh MA. The potential protective effect of friendship on the association between childhood adversity and psychological distress in adulthood: a retrospective, preliminary, three-wave population-based study. J Affect Disord. 2018;226:21–7.

    Article  PubMed  Google Scholar 

  10. Xu F, Wu Q, Xie L, Gong W, Zhang J, Zheng P, et al. Macaques exhibit a naturally-occurring depression similar to humans. Sci Rep. 2015;5:9220.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Li X, Xu F, Xie L, Ji Y, Cheng K, Zhou Q, et al. Depression-like behavioral phenotypes by social and social plus visual isolation in the adult female Macaca fascicularis. PloS ONE. 2013;8:e73293.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Shively CA, Laber-Laird K, Anton RF. Behavior and physiology of social stress and depression in female cynomolgus monkeys. Biol Psychiatry. 1997;41:871.

    Article  CAS  PubMed  Google Scholar 

  13. Lea AJ, Akinyi MY, Nyakundi R, Mareri P, Nyundo F, Kariuki T, et al. Dominance rank-associated gene expression is widespread, sex-specific, and a precursor to high social status in wild male baboons. Proc Natl Acad Sci. 2018;115:E12163–71.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Snyder-Mackler N, Sanz J, Kohn JN, Voyles T, Pique-Regi R, Wilson ME, et al. Social status alters chromatin accessibility and the gene regulatory response to glucocorticoid stimulation in rhesus macaques. Proc Natl Acad Sci. 2019;116:1219–28.

    Article  CAS  PubMed  Google Scholar 

  15. Keeney A, Jessop DS, Harbuz MS, Marsden CA, Hogg S, Blackburn-Munro RE. Differential effects of acute and chronic social defeat stress on hypothalamic-pituitary-adrenal axis function and hippocampal serotonin release in mice. J Neuroendocrinol. 2006;18:330–8.

    Article  CAS  PubMed  Google Scholar 

  16. Wood SK, Wood CS, Lombard CM, Lee CS, Zhang XY, Finnell JE, et al. Inflammatory factors mediate vulnerability to a social stress-induced depressive-like phenotype in passive coping rats. Biol Psychiatry. 2015;78:38–48.

    Article  CAS  PubMed  Google Scholar 

  17. Kelly JR, Borre Y, Brien CO, Patterson E, Aidy SE, Deane J, et al. Transferring the blues: depression-associated gut microbiota induces neurobehavioural changes in the rat. J Psychiatr Res. 2016;82:109–18.

    Article  PubMed  Google Scholar 

  18. Cryan JF, O’Riordan KJ, Cowan CSM, Sandhu KV, Bastiaanssen TFS, Boehme M, et al. The Microbiota-Gut-Brain Axis. Physiol Rev. 2019;99:1877–2013.

    Article  CAS  PubMed  Google Scholar 

  19. Zheng P, Zeng B, Zhou C, Liu M, Fang Z, Xu X, et al. Gut microbiome remodeling induces depressive-like behaviors through a pathway mediated by the host’s metabolism. Mol Psychiatry. 2016;21:786–96.

    Article  CAS  PubMed  Google Scholar 

  20. Zheng P, Yang J, Li Y, Wu J, Liang W, Yin B, et al. Gut microbial signatures can discriminate unipolar from bipolar depression. Adv Sci. 2020:1902862.

  21. Zheng P, Zeng B, Liu M, Chen J, Pan J, Han Y, et al. The gut microbiome from patients with schizophrenia modulates the glutamate-glutamine-GABA cycle and schizophrenia-relevant behaviors in mice. Sci Adv. 2019;5:eaau8317.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Li X, Liang S, Xia Z, Qu J, Liu H, Liu C et al. Establishment of a Macaca fascicularis gut microbiome gene catalog and comparison with the human, pig, and mouse gut microbiomes. GigaScience. 2018;7:giy100.

    PubMed Central  Google Scholar 

  23. Menzel P, Ng KL, Krogh A. Fast and sensitive taxonomic classification for metagenomics with Kaiju. Nat Commun. 2016;7:11257.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Bradley W, Steven H, Robert P. Utilities for quantifying separation in PCA/PLS-DA scores plots. Anal Biochem. 2013;433:102–4.

    Article  CAS  Google Scholar 

  25. Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinforma. 2008;9:559.

    Article  CAS  Google Scholar 

  26. Sousa AMM, Zhu Y, Raghanti MA, Kitchen RR, Onorati M, Tebbenkamp ATN, et al. Molecular and cellular reorganization of neural circuits in the human lineage. Science. 2017;358:1027–32.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Weatheall D. The use of non-human primates in research. London: Academy of Medical Sciences; 2006.

    Google Scholar 

  28. Kikuchi T, Morizane A, Doi D, Magotani H, Onoe H, Hayashi T, et al. Human iPS cell-derived dopaminergic neurons function in a primate Parkinson’s disease model. Nature. 2017;548:592–6.

    Article  CAS  PubMed  Google Scholar 

  29. Chu X. Preliminary validation of natural depression in macaques with acute treatments of the fast-acting antidepressant ketamine. Behavioural Brain Res. 2019;360:60–8.

    Article  CAS  Google Scholar 

  30. Zheng P, Li Y, Wu J, Zhang H, Huang Y, Tan X, et al. Perturbed microbial ecology in myasthenia gravis: evidence from the gut microbiome and fecal metabolome. Adv Sci. 2019;6:1901441.

    Article  CAS  Google Scholar 

  31. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Newell C, Bomhof MR, Reimer RA, Hittel DS, Rho JM, Shearer J. Ketogenic diet modifies the gut microbiota in a murine model of autism spectrum disorder. Mol Autism. 2016;7:37.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  33. Segata N, Izard J, Waldron L, Gevers D, Miropolsky L, Garrett WS, et al. Metagenomic biomarker discovery and explanation. Genome Biol. 2011;12:R60.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Nielsen HB, Almeida M, Juncker AS, Rasmussen S, Li J, Sunagawa S, et al. Identification and assembly of genomes and genetic elements in complex metagenomic samples without using reference genomes. Nat Biotechnol. 2014;32:822–8.

    Article  CAS  PubMed  Google Scholar 

  35. Naseribafrouei A, Hestad K, Avershina E, Sekelja M, Linlokken A, Wilson R, et al. Correlation between the human fecal microbiota and depression. Neurogastroenterol Motil: Off J Eur Gastrointest Motil Soc. 2014;26:1155–62.

    Article  CAS  Google Scholar 

  36. Jiang H, Ling Z, Zhang Y, Mao H, Ma Z, Yin Y, et al. Altered fecal microbiota composition in patients with major depressive disorder. Brain Behav Immun. 2015;48:186–94.

    Article  PubMed  Google Scholar 

  37. Valles-Colomer M, Falony G, Darzi Y, Tigchelaar EF, Wang J, Tito RY, et al. The neuroactive potential of the human gut microbiota in quality of life and depression. Nat Microbiol. 2019;4:623–32.

    Article  CAS  PubMed  Google Scholar 

  38. Pearson-Leary J, Zhao C, Bittinger K, Eacret D, Luz S, Vigderman AS, et al. The gut microbiome regulates the increases in depressive-type behaviors and in inflammatory processes in the ventral hippocampus of stress vulnerable rats. Molecular psychiatry. 2019;4:1–2.

    Google Scholar 

  39. Bozek K, Wei Y, Yan Z, Liu X, Xiong J, Sugimoto M, et al. Organization and evolution of brain lipidome revealed by large-scale analysis of human, chimpanzee, macaque, and mouse tissues. Neuron. 2015;85:695–702.

    Article  CAS  PubMed  Google Scholar 

  40. Yadav RS, Tiwari NK. Lipid integration in neurodegeneration: an overview of Alzheimer’s disease. Mol Neurobiol. 2014;50:168–76.

    Article  CAS  PubMed  Google Scholar 

  41. Kornhuber J, Rhein C, Müller CP, Mühle C. Secretory sphingomyelinase in health and disease. Biol Chem. 2015;396:707–36.

    Article  CAS  PubMed  Google Scholar 

  42. Adibhatla RM, Hatcher JF. Phospholipase A(2), reactive oxygen species, and lipid peroxidation in CNS pathologies. BMB Rep. 2008;41:560–7.

    Article  CAS  PubMed  Google Scholar 

  43. Liu X, Li J, Zheng P, Zhao X, Zhou C, Hu C, et al. Plasma lipidomics reveals potential lipid markers of major depressive disorder. Anal Bioanal Chem. 2016;408:6497–507.

    Article  CAS  PubMed  Google Scholar 

  44. Liu X, Zheng P, Zhao X, Zhang Y, Hu C, Li J, et al. Discovery and validation of plasma biomarkers for major depressive disorder classification based on liquid chromatography-mass spectrometry. J Proteome Res. 2015;14:2322–30.

    Article  CAS  PubMed  Google Scholar 

  45. Zheng P, Gao HC, Li Q, Shao WH, Zhang ML, Cheng K, et al. Plasma metabonomics as a novel diagnostic approach for major depressive disorder. J Proteome Res. 2012;11:1741–8.

    Article  CAS  PubMed  Google Scholar 

  46. Jia HM, Li Q, Zhou C, Yu M, Yang Y, Zhang HW, et al. Chronic unpredictive mild stress leads to altered hepatic metabolic profile and gene expression. Sci Rep. 2016;6:23441.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Zhang Y, Yuan S, Pu J, Yang L, Zhou X, Liu L, et al. Integrated metabolomics and proteomics analysis of hippocampus in a rat model of depression. Neuroscience. 2018;371:207–20.

    Article  CAS  PubMed  Google Scholar 

  48. Oliveira TG, Chan RB, Bravo FV, Miranda A, Silva RR, Zhou B, et al. The impact of chronic stress on the rat brain lipidome. Mol Psychiatry. 2016;21:80–88.

    Article  CAS  PubMed  Google Scholar 

  49. Romme IA, de Reus MA, Ophoff RA, Kahn RS, van den Heuvel MP. Connectome disconnectivity and cortical gene expression in patients with schizophrenia. Biol Psychiatry. 2017;81:495–502.

    Article  CAS  PubMed  Google Scholar 

  50. Lee JC, Park SM, Kim IY, Sung H, Seong JK, Moon MH. High-fat diet-induced lipidome perturbations in the cortex, hippocampus, hypothalamus, and olfactory bulb of mice. Biochim biophys Acta Mol cell Biol lipids. 2018;1863:980–90.

    Article  CAS  PubMed  Google Scholar 

  51. Sacchet MD, Gotlib IH. Myelination of the brain in major depressive disorder: an in vivo quantitative magnetic resonance imaging study. Sci Rep. 2017;7:2200.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. Fields RD. White matter in learning, cognition and psychiatric disorders. Trends Neurosci. 2008;31:361–70.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Funding

This work was supported by the National Key R&D Program of China (2017YFA0505700, 2016YFC1307200), Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences (2019PT320002), Projects of International Cooperation and Exchanges NSFC (81820108015), the Natural Science Foundation Project of China (81971296, 81771490, 81371310, and 81200899), Chongqing Science & Technology Commission (cstc 2019 jcyjjqX0009), and institutional funds from the State University of New York (SUNY) Upstate Medical University. This paper is subject to the SUNY Open Access Policy.

Author information

Authors and Affiliations

Authors

Contributions

Designed the experiments: PX and JL. Performed the metagenomic analysis: PZ, JW, HPZ, and YFL. Performed the metabolomic analysis: PZ, JW, YFL, and JJD. Analyzed the metagenomic and metabolomic data: PZ, JW, XMT, TJC, and H.P.Z. Animal behaviors: BMY, WWL, and YH. Drafted the paper: PX and PZ. Revised the paper for intellectual content: PX, JL, SWP, and MLW.

Corresponding authors

Correspondence to Julio Licinio or Peng Xie.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zheng, P., Wu, J., Zhang, H. et al. The gut microbiome modulates gut–brain axis glycerophospholipid metabolism in a region-specific manner in a nonhuman primate model of depression. Mol Psychiatry 26, 2380–2392 (2021). https://doi.org/10.1038/s41380-020-0744-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41380-020-0744-2

This article is cited by

Search

Quick links