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.

Advertisement

npj Parkinson's Disease
  • View all journals
  • Search
  • My Account Login
  • Content Explore content
  • About the journal
  • Publish with us
  • Sign up for alerts
  • RSS feed
  1. nature
  2. npj parkinson's disease
  3. articles
  4. article
Faecalibacterium prausnitzii, depleted in the Parkinson’s disease microbiome, improves motor deficits in α-synuclein overexpressing mice
Download PDF
Download PDF
  • Article
  • Open access
  • Published: 05 March 2026

Faecalibacterium prausnitzii, depleted in the Parkinson’s disease microbiome, improves motor deficits in α-synuclein overexpressing mice

  • Anastasiya Moiseyenko1,2,
  • Giacomo Antonello2,3,4,
  • Aubrey M. Schonhoff1,2,
  • Joseph C. Boktor1,2,
  • Kaelyn Long2,3,4,
  • Blake Dirks5,
  • Anastasiya D. Oguienko1,
  • Alexander Viloria Winnett1,6,
  • Patrick Simpson1,
  • Dorsa Daeizadeh5,
  • Rustem F. Ismagilov1,7,
  • Rosa Krajmalnik-Brown5,8,
  • Nicola Segata2,4,
  • Levi D. Waldron2,3,4 &
  • …
  • Sarkis K. Mazmanian1,2 

npj Parkinson's Disease , Article number:  (2026) Cite this article

  • 2578 Accesses

  • 27 Altmetric

  • Metrics details

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Microbiology
  • Neurology
  • Neuroscience

Abstract

Gut microbiome composition is altered in Parkinson’s disease (PD), the fastest-growing neurological condition, that is characterized by neurodegeneration, motor dysfunction, and is frequently accompanied by gastrointestinal (GI) symptoms. Notably, microbial taxa with anti-inflammatory properties are consistently depleted in PD patients compared to controls. To explore whether specific gut bacteria may be disease-protective, we assembled a microbial consortium of 8 human-associated taxa that are reduced in individuals with PD. Treatment of α-synuclein overexpressing (Thy1-ASO) mice, an animal model of PD, with this consortium improved motor and GI deficits. A single bacterial species from this consortium, Faecalibacterium prausnitzii, was sufficient to correct gut microbiome deviations in Thy1-ASO mice, induce anti-inflammatory immune responses, and promote protective colonic gene expression profiles. Accordingly, oral treatment with F. prausnitzii robustly ameliorated motor and GI deficits and reduced α-synuclein aggregates in the brain. These findings support the emerging hypothesis of functional contributions by the microbiome to PD outcomes, and embolden the development of potential probiotic therapies to treat motor and non-motor symptoms.

Similar content being viewed by others

Metagenomics of Parkinson’s disease implicates the gut microbiome in multiple disease mechanisms

Article Open access 15 November 2022

Proinflammatory and GABA eating bacteria in Parkinson's disease gut microbiome from a meta-analysis perspective

Article Open access 03 June 2025

Supplementation with short-chain fatty acids and a prebiotic improves clinical outcome in Parkinson’s disease: a randomized double-blind prospective study

Article Open access 05 December 2025

Data availability

The data, code, protocols, and key lab materials used and generated in this study are listed in the Key Resource Table (Supplementary Table 2, also available at https://doi.org/10.5281/zenodo.17137678) alongside their persistent identifiers. For microbiome analysis data, raw FASTQ files were deposited in the SRA (PRJNA1259538) along with sample metadata, and code to generate data, figures, and statistics is available at https://doi.org/10.5281/zenodo.17128213. For RNA sequencing analysis data, raw FASTQ files were deposited in the SRA (PRJNA1308739) along with sample metadata, and code to generate data, figures, and statistics is available at https://doi.org/10.5281/zenodo.17981510. Raw flow cytometry data were deposited to Zenodo (https://doi.org/10.5281/zenodo.16929959) along with sample metadata. All other raw data and analyses, including behavior data analysis, original blot images, multiplex, and VFA data, can be found at https://doi.org/10.5281/zenodo.17137678.

References

  1. Tysnes, O.-B. & Storstein, A. Epidemiology of Parkinson’s disease. J. Neural Transm. (Vienna) 124, 901–905 (2017).

    Google Scholar 

  2. Poewe, W. et al. Parkinson disease. Nat. Rev. Dis. Prim. 3, 17013 (2017).

    Google Scholar 

  3. Dorsey, E. R., Sherer, T., Okun, M. S. & Bloem, B. R. The emerging evidence of the Parkinson pandemic. J. Parkinsons Dis. 8, S3–S8 (2018).

    Google Scholar 

  4. Koga, S., Sekiya, H., Kondru, N., Ross, O. A. & Dickson, D. W. Neuropathology and molecular diagnosis of synucleinopathies. Mol. Neurodegener. 16, 83 (2021).

    Google Scholar 

  5. Hawkes, C. H., Del Tredici, K. & Braak, H. A timeline for Parkinson’s disease. Parkinsonism Relat. Disord. 16, 79–84 (2010).

    Google Scholar 

  6. Pardo-Moreno, T. et al. Current treatments and new, tentative therapies for Parkinson’s disease. Pharmaceutics 15, 770 (2023).

    Google Scholar 

  7. Parkinson, J. An essay on the shaking palsy. JNP 14, 223–236 (2002).

    Google Scholar 

  8. Forsyth, C. B. et al. Increased intestinal permeability correlates with sigmoid mucosa alpha-synuclein staining and endotoxin exposure markers in early Parkinson’s disease. PLoS ONE 6, e28032 (2011).

    Google Scholar 

  9. Yang, D. et al. The role of the gut microbiota in the pathogenesis of Parkinson’s disease. Front. Neurol. 10, 1155 (2019).

    Google Scholar 

  10. Pellicano, C. et al. Prodromal non-motor symptoms of Parkinson’s disease. Neuropsychiatr. Dis. Treat. 3, 145–151 (2007).

    Google Scholar 

  11. Galbiati, A., Verga, L., Giora, E., Zucconi, M. & Ferini-Strambi, L. The risk of neurodegeneration in REM sleep behavior disorder: a systematic review and meta-analysis of longitudinal studies. Sleep. Med. Rev. 43, 37–46 (2019).

    Google Scholar 

  12. Postuma, R. B. & Berg, D. Advances in markers of prodromal Parkinson disease. Nat. Rev. Neurol. 12, 622–634 (2016).

    Google Scholar 

  13. Dorsey, E. R., De Miranda, B. R., Horsager, J. & Borghammer, P. The body, the brain, the environment, and Parkinson’s disease. J. Parkinsons Dis. 14, 363–381 (2024).

    Google Scholar 

  14. Berg, D. et al. Prodromal Parkinson disease subtypes - key to understanding heterogeneity. Nat. Rev. Neurol. 17, 349–361 (2021).

    Google Scholar 

  15. Braak, H., Rüb, U., Gai, W. P. & Del Tredici, K. Idiopathic Parkinson’s disease: possible routes by which vulnerable neuronal types may be subject to neuroinvasion by an unknown pathogen. J. Neural Transm. (Vienna) 110, 517–536 (2003).

    Google Scholar 

  16. Kim, S. et al. Transneuronal propagation of pathologic α-synuclein from the gut to the brain models Parkinson’s disease. Neuron 103, 627–641.e7 (2019).

    Google Scholar 

  17. Challis, C. et al. Gut-seeded α-synuclein fibrils promote gut dysfunction and brain pathology specifically in aged mice. Nat. Neurosci. 23, 327–336 (2020).

    Google Scholar 

  18. Liu, B. et al. Vagotomy and Parkinson disease: a Swedish register-based matched-cohort study. Neurology 88, 1996–2002 (2017).

    Google Scholar 

  19. Svensson, E. et al. Vagotomy and subsequent risk of Parkinson’s disease. Ann. Neurol. 78, 522–529 (2015).

    Google Scholar 

  20. Sampson, T. The impact of indigenous microbes on Parkinson’s disease. Neurobiol. Dis. 135, 104426 (2020).

    Google Scholar 

  21. Hill-Burns, E. M. et al. Parkinson’s disease and Parkinson’s disease medications have distinct signatures of the gut microbiome. Mov. Disord. 32, 739–749 (2017).

    Google Scholar 

  22. Aho, V. T. E. et al. Gut microbiota in Parkinson’s disease: Temporal stability and relations to disease progression. EBioMedicine 44, 691–707 (2019).

    Google Scholar 

  23. Bedarf, J. R. et al. Functional implications of microbial and viral gut metagenome changes in early stage L-DOPA-naïve Parkinson’s disease patients. Genome Med. 9, 39–39 (2017).

    Google Scholar 

  24. Wallen, Z. D. et al. Metagenomics of Parkinson’s disease implicates the gut microbiome in multiple disease mechanisms. Nat. Commun. 13, 6958 (2022).

    Google Scholar 

  25. Elford, J. D., Becht, N., Garssen, J., Kraneveld, A. D. & Perez-Pardo, P. Buty and the beast: the complex role of butyrate in Parkinson’s disease. Front. Pharm. 15, 1388401 (2024).

    Google Scholar 

  26. Dalile, B., Van Oudenhove, L., Vervliet, B. & Verbeke, K. The role of short-chain fatty acids in microbiota–gut–brain communication. Nat. Rev. Gastroenterol. Hepatol. 16, 461–478 (2019).

    Google Scholar 

  27. Fernández, J. et al. Colon microbiota fermentation of dietary prebiotics towards short-chain fatty acids and their roles as anti-inflammatory and antitumour agents: a review. J. Funct. Foods 25, 511–522 (2016).

    Google Scholar 

  28. Hamilton, A. M., Krout, I. N., White, A. C. & Sampson, T. R. Microbiome-based therapeutics for Parkinson’s disease. Neurotherapeutics 21, e00462 (2024).

    Google Scholar 

  29. Tan, A. H. et al. Probiotics for Constipation in Parkinson disease: a randomized placebo-controlled study. Neurology 96, e772–e782 (2021).

    Google Scholar 

  30. Ibrahim, A. et al. Multi-strain probiotics (Hexbio) containing MCP BCMC strains improved constipation and gut motility in Parkinson’s disease: a randomised controlled trial. PLoS ONE 15, e0244680 (2020).

    Google Scholar 

  31. Barichella, M. et al. Probiotics and prebiotic fiber for constipation associated with Parkinson disease: an RCT. Neurology 87, 1274–1280 (2016).

    Google Scholar 

  32. Keshavarzian, A. et al. Colonic bacterial composition in Parkinson’s disease. Mov. Disord. 30, 1351–1360 (2015).

    Google Scholar 

  33. Unger, M. M. et al. Short chain fatty acids and gut microbiota differ between patients with Parkinson’s disease and age-matched controls. Parkinsonism Relat. Disord. 32, 66–72 (2016).

    Google Scholar 

  34. Li, W. et al. Structural changes of gut microbiota in Parkinson’s disease and its correlation with clinical features. Sci. China Life Sci. 60, 1223–1233 (2017).

    Google Scholar 

  35. Petrov, V. A. et al. Analysis of gut microbiota in patients with Parkinson’s disease. Bull. Exp. Biol. Med. 162, 734–737 (2017).

    Google Scholar 

  36. Boktor, J. C. et al. Integrated multi-cohort analysis of the Parkinson’s disease gut metagenome. Mov. Disord. 38, 399–409 (2023).

    Google Scholar 

  37. Sokol, H. et al. Faecalibacterium prausnitzii is an anti-inflammatory commensal bacterium identified by gut microbiota analysis of Crohn disease patients. Proc. Natl. Acad. Sci. USA 105, 16731–16736 (2008).

    Google Scholar 

  38. Quévrain, E. et al. Identification of an anti-inflammatory protein from Faecalibacterium prausnitzii, a commensal bacterium deficient in Crohn’s disease. Gut 65, 415–425 (2016).

    Google Scholar 

  39. Martín, R., Bermúdez-Humarán, L. G. & Langella, P. Searching for the bacterial effector: the example of the multi-skilled commensal bacterium Faecalibacterium prausnitzii. Front Microbiol 9, 346 (2018).

    Google Scholar 

  40. Zhou, L. et al. Faecalibacterium prausnitzii produces butyrate to maintain Th17/Treg balance and to ameliorate colorectal colitis by inhibiting histone deacetylase 1. Inflamm. Bowel Dis. 24, 1926–1940 (2018).

    Google Scholar 

  41. Li, H.-X. et al. Inflammatory bowel disease and risk of Parkinson’s disease: evidence from a meta-analysis of 14 studies involving more than 13.4 million individuals. Front. Med. (Lausanne) 10, 1137366 (2023).

    Google Scholar 

  42. Zhu, Y. et al. Association between inflammatory bowel diseases and Parkinson’s disease: systematic review and meta-analysis. Neural Regen. Res. 17, 344–353 (2022).

    Google Scholar 

  43. Chesselet, M.-F. et al. A progressive mouse model of Parkinson’s disease: the Thy1-aSyn (“Line 61”) mice. Neurotherapeutics 9, 297–314 (2012).

    Google Scholar 

  44. Richter, F., Stanojlovic, M., Käufer, C., Gericke, B. & Feja, M. A mouse model to test novel therapeutics for Parkinson’s disease: an update on the Thy1-aSyn (‘line 61’) mice. Neurotherapeutics 20, 97–116 (2023).

    Google Scholar 

  45. Anderson, J. P. et al. Phosphorylation of Ser-129 is the dominant pathological modification of alpha-synuclein in familial and sporadic Lewy body disease. J. Biol. Chem. 281, 29739–29752 (2006).

    Google Scholar 

  46. Geistlinger, L. et al. BugSigDB captures patterns of differential abundance across a broad range of host-associated microbial signatures. Nat. Biotechnol. 42, 790–802 (2024).

    Google Scholar 

  47. Martín, R. et al. Faecalibacterium: a bacterial genus with promising human health applications. FEMS Microbiol. Rev. 47, fuad039 (2023).

    Google Scholar 

  48. Yang, X., Qian, Y., Xu, S., Song, Y. & Xiao, Q. Longitudinal analysis of fecal microbiome and pathologic processes in a rotenone induced mice model of Parkinson’s disease. Front. Aging Neurosci. 9, 441 (2017).

    Google Scholar 

  49. Sampson, T. R. et al. Alpha synuclein overexpression can drive microbiome dysbiosis in mice. Sci. Rep. 15, 4014 (2025).

    Google Scholar 

  50. Abdel-Haq, R. et al. A prebiotic diet modulates microglial states and motor deficits in α-synuclein overexpressing mice. eLife 11, e81453 (2022).

    Google Scholar 

  51. Aktas, B. Gut Microbial alteration in MPTP mouse model of Parkinson disease is administration regimen dependent. Cell. Mol. Neurobiol. 43, 2815–2829 (2023).

    Google Scholar 

  52. Yan, Y. et al. Gut microbiota and metabolites of α-synuclein transgenic monkey models with early stage of Parkinson’s disease. NPJ Biofilms Microbiomes 7, 69 (2021).

    Google Scholar 

  53. Wrzosek, L. et al. Bacteroides thetaiotaomicron and Faecalibacterium prausnitzii influence the production of mucus glycans and the development of goblet cells in the colonic epithelium of a gnotobiotic model rodent. BMC Biol. 11, 61 (2013).

    Google Scholar 

  54. Miquel, S. et al. Identification of metabolic signatures linked to anti-inflammatory effects of Faecalibacterium prausnitzii. mBio 6, e00300-15 (2015).

    Google Scholar 

  55. Kim, H., Jeong, Y., Kang, S., You, H. J. & Ji, G. E. Co-Culture with Bifidobacterium catenulatum improves the growth, gut colonization, and butyrate production of Faecalibacterium prausnitzii: in vitro and in vivo studies. Microorganisms 8, 788 (2020).

    Google Scholar 

  56. Moon, J. et al. Faecalibacterium prausnitzii alleviates inflammatory arthritis and regulates IL-17 production, short chain fatty acids, and the intestinal microbial flora in experimental mouse model for rheumatoid arthritis. Arthritis Res. Ther. 25, 130 (2023).

    Google Scholar 

  57. Bredon, M. et al. Faecalibaterium prausnitzii strain EXL01 boosts efficacy of immune checkpoint inhibitors. Oncoimmunology 13, 2374954 (2024).

    Google Scholar 

  58. Shi, Z. et al. Faecalibacterium prausnitzii promotes anti-PD-L1 efficacy in natural killer/T-cell lymphoma by enhancing antitumor immunity. BMC Med. 23, 387 (2025).

    Google Scholar 

  59. Park, S.-Y. et al. Alpha-synuclein-specific regulatory T cells ameliorate Parkinson’s disease progression in mice. Int. J. Mol. Sci. 24, 15237 (2023).

    Google Scholar 

  60. Reynolds, A. D., Banerjee, R., Liu, J., Gendelman, H. E. & Mosley, R. L. Neuroprotective activities of CD4+CD25+ regulatory T cells in an animal model of Parkinson’s disease. J. Leukoc. Biol. 82, 1083–1094 (2007).

    Google Scholar 

  61. Arce-Sillas, A. et al. Increased levels of regulatory T cells and IL-10-producing regulatory B cells are linked to improved clinical outcome in Parkinson’s disease: a 1-year observational study. J. Neural Transm. (Vienna) 131, 901–916 (2024).

    Google Scholar 

  62. Miquel, S. et al. Ecology and metabolism of the beneficial intestinal commensal bacterium Faecalibacterium prausnitzii. Gut Microbes 5, 146–151 (2014).

    Google Scholar 

  63. Lenoir, M. et al. Butyrate mediates anti-inflammatory effects of Faecalibacterium prausnitzii in intestinal epithelial cells through Dact3. Gut Microbes 12, 1–16 (2020).

    Google Scholar 

  64. Mohebali, N. et al. Faecalibacterium prausnitzii, Bacteroides faecis and Roseburia intestinalis attenuate clinical symptoms of experimental colitis by regulating Treg/Th17 cell balance and intestinal barrier integrity. Biomed. Pharmacother. 167, 115568 (2023).

    Google Scholar 

  65. Jabara, H. H. et al. A missense mutation in TFRC, encoding transferrin receptor 1, causes combined immunodeficiency. Nat. Genet. 48, 74–78 (2016).

    Google Scholar 

  66. Bolen, M. L. et al. Peripheral blood immune cells from individuals with Parkinson’s disease or inflammatory bowel disease share deficits in iron storage and transport that are modulated by non-steroidal anti-inflammatory drugs. Neurobiol. Dis. 207, 106794 (2025).

    Google Scholar 

  67. Sabbir, M. G. Loss of calcium/calmodulin-dependent protein kinase kinase 2, transferrin, and transferrin receptor proteins in the temporal cortex of Alzheimer’s patients postmortem is associated with abnormal iron homeostasis: implications for patient survival. Front. Cell Dev. Biol. 12, 1469751 (2024).

    Google Scholar 

  68. Ayton, S., Lei, P., Mclean, C., Bush, A. I. & Finkelstein, D. I. Transferrin protects against Parkinsonian neurotoxicity and is deficient in Parkinson’s substantia nigra. Signal Transduct. Target Ther. 1, 16015 (2016).

    Google Scholar 

  69. Rentzos, M. et al. Circulating interleukin-15 and RANTES chemokine in Parkinson’s disease. Acta Neurol. Scand. 116, 374–379 (2007).

    Google Scholar 

  70. Tang, P. et al. Correlation between serum RANTES levels and the severity of Parkinson’s disease. Oxid. Med. Cell. Longev. 2014, 208408 (2014).

    Google Scholar 

  71. Galiano-Landeira, J., Torra, A., Vila, M. & Bové, J. CD8 T cell nigral infiltration precedes synucleinopathy in early stages of Parkinson’s disease. Brain 143, 3717–3733 (2020).

    Google Scholar 

  72. Williams, G. P. et al. CD4 T cells mediate brain inflammation and neurodegeneration in a mouse model of Parkinson’s disease. Brain 144, 2047–2059 (2021).

    Google Scholar 

  73. Sekijima, Y. Recent progress in the understanding and treatment of transthyretin amyloidosis. J. Clin. Pharm. Ther. 39, 225–233 (2014).

    Google Scholar 

  74. Maetzler, W. et al. Serum and cerebrospinal fluid levels of transthyretin in Lewy body disorders with and without dementia. PLoS ONE 7, e48042 (2012).

    Google Scholar 

  75. Sárkány, Z. et al. Transthyretin has conformation-selective proteolytic activity against α-synuclein. Preprint at bioRxiv https://doi.org/10.1101/2023.08.10.552896 (2023).

  76. Cardoso, B. R., Roberts, B. R., Bush, A. I. & Hare, D. J. Selenium, selenoproteins and neurodegenerative diseases. Metallomics 7, 1213–1228 (2015).

    Google Scholar 

  77. Xu, K. et al. Engineered selenium/human serum albumin nanoparticles for efficient targeted treatment of Parkinson’s disease via oral gavage. ACS Nano 17, 19961–19980 (2023).

    Google Scholar 

  78. De Miranda, B. R., Goldman, S. M., Miller, G. W., Greenamyre, J. T. & Dorsey, E. R. Preventing Parkinson’s disease: an environmental agenda. J. Parkinsons Dis. 12, 45–68 (2022).

    Google Scholar 

  79. Scheperjans, F. et al. Gut microbiota are related to Parkinson’s disease and clinical phenotype. Mov. Disord. 30, 350–358 (2015).

    Google Scholar 

  80. Tan, A. H. et al. Small intestinal bacterial overgrowth in Parkinson’s disease. Parkinsonism Relat. Disord. 20, 535–540 (2014).

    Google Scholar 

  81. Sampson, T. R. et al. Gut microbiota regulate motor deficits and neuroinflammation in a model of Parkinson’s disease. Cell 167, 1469–1480.e12 (2016).

    Google Scholar 

  82. Choi, J. G. et al. Oral administration of Proteus mirabilis damages dopaminergic neurons and motor functions in mice. Sci. Rep. 8, 1275 (2018).

    Google Scholar 

  83. Matheoud, D. et al. Intestinal infection triggers Parkinson’s disease-like symptoms in Pink1−/− mice. Nature 571, 565–569 (2019).

    Google Scholar 

  84. Zhao, Z. et al. Fecal microbiota transplantation protects rotenone-induced Parkinson’s disease mice via suppressing inflammation mediated by the lipopolysaccharide-TLR4 signaling pathway through the microbiota–gut–brain axis. Microbiome 9, 226–226 (2021).

    Google Scholar 

  85. Sun, M.-F. et al. Neuroprotective effects of fecal microbiota transplantation on MPTP-induced Parkinson’s disease mice: gut microbiota, glial reaction and TLR4/TNF-α signaling pathway. Brain Behav. Immun. 70, 48–60 (2018).

    Google Scholar 

  86. Zhong, Z. et al. Fecal microbiota transplantation exerts a protective role in MPTP-induced Parkinson’s disease via the TLR4/PI3K/AKT/NF-κB pathway stimulated by α-synuclein. Neurochem. Res. 46, 3050–3058 (2021).

    Google Scholar 

  87. Xie, Z. et al. Healthy human fecal microbiota transplantation into mice attenuates MPTP-induced neurotoxicity via AMPK/SOD2 pathway. Aging Dis. 14, 2193–2214 (2023).

    Google Scholar 

  88. Bruggeman, A. et al. Safety and efficacy of faecal microbiota transplantation in patients with mild to moderate Parkinson’s disease (GUT-PARFECT): a double-blind, placebo-controlled, randomised, phase 2 trial. EClinicalMedicine 71, 102563 (2024).

    Google Scholar 

  89. Cheng, Y. et al. Efficacy of fecal microbiota transplantation in patients with Parkinson’s disease: clinical trial results from a randomized, placebo-controlled design. Gut Microbes 15, 2284247 (2023).

    Google Scholar 

  90. DuPont, H. L. et al. Fecal microbiota transplantation in Parkinson’s disease—a randomized repeat-dose, placebo-controlled clinical pilot study. Front. Neurol. 14, 1104759 (2023).

    Google Scholar 

  91. Scheperjans, F. et al. Fecal microbiota transplantation for treatment of Parkinson disease: a randomized clinical trial. JAMA Neurol. e242305 (2024) https://doi.org/10.1001/jamaneurol.2024.2305.

  92. Peter, I. et al. Anti-tumor necrosis factor therapy and incidence of Parkinson disease among patients with inflammatory bowel disease. JAMA Neurol. 75, 939–946 (2018).

    Google Scholar 

  93. Gao, X., Chen, H., Schwarzschild, M. A. & Ascherio, A. Use of ibuprofen and risk of Parkinson disease. Neurology 76, 863–869 (2011).

    Google Scholar 

  94. Barnum, C. J. et al. Peripheral administration of the selective inhibitor of soluble tumor necrosis factor (TNF) XPro®1595 attenuates nigral cell loss and glial activation in 6-OHDA hemiparkinsonian rats. J. Parkinsons Dis. 4, 349–360 (2014).

    Google Scholar 

  95. Swiątkiewicz, M., Zaremba, M., Joniec, I., Członkowski, A. & Kurkowska-Jastrzębska, I. Potential neuroprotective effect of ibuprofen, insights from the mice model of Parkinson’s disease. Pharm. Rep. 65, 1227–1236 (2013).

    Google Scholar 

  96. Zhao, P. et al. Neuroprotective effects of fingolimod in mouse models of Parkinson’s disease. FASEB J. 31, 172–179 (2017).

    Google Scholar 

  97. Nie, K. et al. Roseburia intestinalis: a beneficial gut organism from the discoveries in genus and species. Front. Cell. Infect. Microbiol. 11, 757718 (2021).

    Google Scholar 

  98. Zhu, C. et al. Roseburia intestinalis inhibits interleukin‑17 excretion and promotes regulatory T cells differentiation in colitis. Mol. Med. Rep. 17, 7567–7574 (2018).

    Google Scholar 

  99. Han, H. S. et al. Roseburia intestinalis-derived extracellular vesicles ameliorate colitis by modulating intestinal barrier, microbiome, and inflammatory responses. J. Extracell. Vesicles 13, e12487 (2024).

    Google Scholar 

  100. Choi, S. I. et al. The protective effect of Roseburia faecis against repeated water avoidance stress-induced irritable bowel syndrome in a Wister rat model. J. Cancer Prev. 28, 93–105 (2023).

    Google Scholar 

  101. He, T., Cheng, X. & Xing, C. The gut microbial diversity of colon cancer patients and the clinical significance. Bioengineered 12, 7046–7060 (2021).

    Google Scholar 

  102. Ai, D. et al. Identifying gut microbiota associated with colorectal cancer using a zero-inflated lognormal model. Front. Microbiol. 10, 826 (2019).

    Google Scholar 

  103. Chen, W. et al. Enhanced microbiota profiling in patients with quiescent Crohn’s disease through comparison with paired healthy first-degree relatives. Cell Rep. Med. 5, 101624 (2024).

    Google Scholar 

  104. Liu, D. et al. Anaerostipes hadrus, a butyrate-producing bacterium capable of metabolizing 5-fluorouracil. mSphere 9, e0081623 (2024).

    Google Scholar 

  105. Ihekweazu, F. D. et al. Bacteroides ovatus ATCC 8483 monotherapy is superior to traditional fecal transplant and multi-strain bacteriotherapy in a murine colitis model. Gut Microbes 10, 504–520 (2019).

    Google Scholar 

  106. Ihekweazu, F. D. et al. Bacteroides ovatus promotes IL-22 production and reduces trinitrobenzene sulfonic acid-driven colonic inflammation. Am. J. Pathol. 191, 704–719 (2021).

    Google Scholar 

  107. Hayase, E. et al. Bacteroides ovatus alleviates dysbiotic microbiota-induced graft-versus-host disease. Cell Host Microbe 32, 1621–1636.e6 (2024).

    Google Scholar 

  108. Liu, N. et al. Eubacterium rectale Improves the efficacy of anti-PD1 immunotherapy in melanoma via l-serine-mediated NK cell activation. Research (Washington, DC) 6, 0127 (2023).

    Google Scholar 

  109. Lu, H. et al. Butyrate-producing Eubacterium rectale suppresses lymphomagenesis by alleviating the TNF-induced TLR4/MyD88/NF-κB axis. Cell Host Microbe 30, 1139–1150.e7 (2022).

    Google Scholar 

  110. Marietta, E. V. et al. Suppression of inflammatory arthritis by human gut-derived Prevotella histicola in humanized mice. Arthritis Rheumatol. 68, 2878–2888 (2016).

    Google Scholar 

  111. Shahi, S. K. et al. Prevotella histicola, a human gut commensal, is as potent as COPAXONE® in an animal model of multiple sclerosis. Front. Immunol. 10, 462 (2019).

    Google Scholar 

  112. Qiu, X., Zhang, M., Yang, X., Hong, N. & Yu, C. Faecalibacterium prausnitzii upregulates regulatory T cells and anti-inflammatory cytokines in treating TNBS-induced colitis. J. Crohns Colitis 7, e558–e568 (2013).

    Google Scholar 

  113. Martín, R. et al. The commensal bacterium Faecalibacterium prausnitzii is protective in DNBS-induced chronic moderate and severe colitis models. Inflamm. Bowel Dis. 20, 417–430 (2014).

    Google Scholar 

  114. Arpaia, N. et al. Metabolites produced by commensal bacteria promote peripheral regulatory T-cell generation. Nature 504, 451–455 (2013).

    Google Scholar 

  115. Aktas, B., Aslim, B. & Ozdemir, D. A. A neurotherapeutic approach with Lacticaseibacillus rhamnosus E9 on gut microbiota and intestinal barrier in MPTP-induced mouse model of Parkinson’s disease. Sci. Rep. 14, 15460 (2024).

    Google Scholar 

  116. Liu, X. et al. Polymannuronic acid prebiotic plus Lacticaseibacillus rhamnosus GG probiotic as a novel synbiotic promoted their separate neuroprotection against Parkinson’s disease. Food Res. Int. 155, 111067 (2022).

    Google Scholar 

  117. Liao, J.-F. et al. Lactobacillus plantarum PS128 alleviates neurodegenerative progression in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-induced mouse models of Parkinson’s disease. Brain Behav. Immun. 90, 26–46 (2020).

    Google Scholar 

  118. Lee, Y. Z. et al. Neuroprotective effects of Lactobacillus plantarum PS128 in a mouse model of Parkinson’s disease: the role of gut microbiota and microRNAs. Int. J. Mol. Sci. 24, 6794 (2023).

    Google Scholar 

  119. Qiao, C.-M. et al. Akkermansia muciniphila is beneficial to a mouse model of Parkinson’s disease, via alleviated neuroinflammation and promoted neurogenesis, with involvement of SCFAs. Brain Sci. 14, 238 (2024).

    Google Scholar 

  120. Lu, C.-S. et al. The add-on effect of Lactobacillus plantarum PS128 in patients with Parkinson’s disease: a pilot study. Front Nutr. 8, 650053 (2021).

    Google Scholar 

  121. Chu, C. et al. Meta-analysis of randomized controlled trials of the effects of probiotics in Parkinson’s disease. Food Funct. 14, 3406–3422 (2023).

    Google Scholar 

  122. Cheng, A. G. et al. Design, construction, and in vivo augmentation of a complex gut microbiome. Cell 185, 3617–3636.e19 (2022).

    Google Scholar 

  123. Han, S. et al. A metabolomics pipeline for the mechanistic interrogation of the gut microbiome. Nature 595, 415–420 (2021).

    Google Scholar 

  124. Rockenstein, E. et al. Differential neuropathological alterations in transgenic mice expressing α-synuclein from the platelet-derived growth factor and Thy-1 promoters. J. Neurosci. Res. 68, 568–578 (2002).

    Google Scholar 

  125. Fleming, S. M. et al. Early and progressive sensorimotor anomalies in mice overexpressing wild-type human alpha-synuclein. J. Neurosci. 24, 9434–9440 (2004).

    Google Scholar 

  126. Zhang, J. et al. Motor impairments, striatal degeneration, and altered dopamine–glutamate interplay in mice lacking PSD-95. J. Neurogenet. 28, 98–111 (2014).

    Google Scholar 

  127. Lewis, S. J. & Heaton, K. W. Stool form scale as a useful guide to intestinal transit time. Scand. J. Gastroenterol. 32, 920–924 (1997).

    Google Scholar 

  128. Nagakura, Y., Naitoh, Y., Kamato, T., Yamano, M. & Miyata, K. Compounds possessing 5-HT3 receptor antagonistic activity inhibit intestinal propulsion in mice. Eur. J. Pharm. 311, 67–72 (1996).

    Google Scholar 

  129. Camilleri, M. & Linden, D. R. Measurement of gastrointestinal and colonic motor functions in humans and animals. Cell. Mol. Gastroenterol. Hepatol. 2, 412–428 (2016).

    Google Scholar 

  130. Koslo, R. J., Burks, T. F. & Porreca, F. Centrally administered bombesin affects gastrointestinal transit and colonic bead expulsion through supraspinal mechanisms. J. Pharm. Exp. Ther. 238, 62–67 (1986).

    Google Scholar 

  131. Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B: Stat. Methodol. 57, 289–300 (1995).

  132. Cliff, N. Dominance statistics: ordinal analyses to answer ordinal questions. Psychol. Bull. 114, 494–509 (1993).

    Google Scholar 

  133. Efron, B. Better bootstrap confidence intervals. J. Am. Stat. Assoc. 82, 171–185 (1987).

  134. Cochran, W. G. The combination of estimates from different experiments. Biometrics 10, 101–129 (1954).

    Google Scholar 

  135. Higgins, J. P. T. & Thompson, S. G. Quantifying heterogeneity in a meta-analysis. Stat. Med. 21, 1539–1558 (2002).

    Google Scholar 

  136. Lee, B. R. & Kamitani, T. Improved immunodetection of endogenous α-synuclein. PLoS ONE 6, e23939 (2011).

    Google Scholar 

  137. Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

    Google Scholar 

  138. Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).

    Google Scholar 

  139. 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).

    Google Scholar 

  140. Yu, G., Wang, L.-G., Han, Y. & He, Q.-Y. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS 16, 284–287 (2012).

    Google Scholar 

  141. Wickham, H. Data analysis. In ggplot2: Elegant Graphics for Data Analysis (ed. Wickham, H.) 189–201 (Springer International Publishing, 2016).

  142. Reynolds, M. C. et al. Delineating the drivers and functionality of methanogenic niches within an arid landfill. Appl. Environ. Microbiol. 88, e0243821 (2022).

    Google Scholar 

  143. Mohana Rangan, S. et al. Decoupling Fe0 application and bioaugmentation in space and time enables microbial reductive dechlorination of trichloroethene to ethene: evidence from soil columns. Environ. Sci. Technol. 57, 4167–4179 (2023).

    Google Scholar 

  144. Davis, T. L. et al. Chemical oxygen demand can be converted to gross energy for food items using a linear regression model. J. Nutr. 151, 445–453 (2021).

    Google Scholar 

  145. Dirks, B. et al. Methanogenesis associated with altered microbial production of short-chain fatty acids and human-host metabolizable energy. ISME J. 19, wraf103 (2025).

    Google Scholar 

  146. Corbin, K. D. et al. Host-diet-gut microbiome interactions influence human energy balance: a randomized clinical trial. Nat. Commun. 14, 3161 (2023).

    Google Scholar 

  147. Blanco-Míguez, A. et al. Extending and improving metagenomic taxonomic profiling with uncharacterized species using MetaPhlAn 4. Nat. Biotechnol. 41, 1633–1644 (2023).

    Google Scholar 

  148. Beghini, F. et al. Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3. Elife 10, e65088 (2021).

    Google Scholar 

  149. Anderson, M. J. Permutational multivariate analysis of variance (PERMANOVA). In Wiley StatsRef: Statistics Reference Online (eds Balakrishnan, N. et al.) (John Wiley & Sons, 2017).

  150. Nickols, W. A. et al. MaAsLin 3: refining and extending generalized multivariable linear models for meta-omic association discovery. Nat. Methods https://doi.org/10.1038/s41592-025-02923-9 (2026).

  151. Baron, R. M. & Kenny, D. A. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J. Pers. Soc. Psychol. 51, 1173–1182 (1986).

    Google Scholar 

  152. King, G., Tomz, M. & Wittenberg, J. Making the most of statistical analyses: improving interpretation and presentation. Am. J. Political Sci. 44, 347–361 (2000).

    Google Scholar 

Download references

Acknowledgements

The authors would like to thank the members of the Mazmanian laboratory for their helpful critiques and review of the manuscript. We thank T. Thron for husbandry and maintenance of the Thy1-ASO “Line 61” mouse line, and L.B. De los Santos, I. Cardenas, and J. Gutierrez for animal care. We are grateful to C. Oikonomou for manuscript editing and submission support, and Y. Garcia-Flores for lab administrative support. We would also like to thank J. Griffiths for help with tissue collections. Flow cytometric analysis was performed at the Caltech Flow Cytometry and Cell Sorting Facility, with support from M. Gregory. Multiplex analysis was done at the Caltech Protein Expression Center, with support from M. Anaya. RNA sequencing was carried out by the UCLA Technology Center for Genomics & Bioinformatics (TCGB). Metagenomics sequencing was made possible by Prebiomics S.r.l. (Trento, Italy), with support from M. Bolzan. Figures 1A, B and 2A were created in BioRender (Moiseyenko, A., 2025, https://BioRender.com/zvkyy6g, RRID: SCR_018361). This research was funded in part by Aligning Science Across Parkinson’s (ASAP-020495 and ASAP-000375) through the Michael J. Fox Foundation for Parkinson’s Research (MJFF) and the Heritage Medical Research Institute to S.K.M., as well as by the Jacobs Institute for Molecular Engineering for Medicine (Caltech) and Beckman Institute at Caltech to R.F.I. For the purpose of open access, the authors have applied a CC BY public copyright license to all Author Accepted Manuscripts arising from this submission.

Author information

Authors and Affiliations

  1. Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA

    Anastasiya Moiseyenko, Aubrey M. Schonhoff, Joseph C. Boktor, Anastasiya D. Oguienko, Alexander Viloria Winnett, Patrick Simpson, Rustem F. Ismagilov & Sarkis K. Mazmanian

  2. Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, USA

    Anastasiya Moiseyenko, Giacomo Antonello, Aubrey M. Schonhoff, Joseph C. Boktor, Kaelyn Long, Nicola Segata, Levi D. Waldron & Sarkis K. Mazmanian

  3. Department of Epidemiology and Biostatistics and Institute for Implementation Science in Population Health, Graduate School of Public Health and Health Policy, City University of New York (CUNY), New York, NY, USA

    Giacomo Antonello, Kaelyn Long & Levi D. Waldron

  4. Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Povo, Trento, Italy

    Giacomo Antonello, Kaelyn Long, Nicola Segata & Levi D. Waldron

  5. Biodesign Center for Health through Microbiomes, Arizona State University, Tempe, AZ, USA

    Blake Dirks, Dorsa Daeizadeh & Rosa Krajmalnik-Brown

  6. UCLA-Caltech Medical Scientist Training Program, University of California Los Angeles, Los Angeles, CA, USA

    Alexander Viloria Winnett

  7. Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, USA

    Rustem F. Ismagilov

  8. School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ, USA

    Rosa Krajmalnik-Brown

Authors
  1. Anastasiya Moiseyenko
    View author publications

    Search author on:PubMed Google Scholar

  2. Giacomo Antonello
    View author publications

    Search author on:PubMed Google Scholar

  3. Aubrey M. Schonhoff
    View author publications

    Search author on:PubMed Google Scholar

  4. Joseph C. Boktor
    View author publications

    Search author on:PubMed Google Scholar

  5. Kaelyn Long
    View author publications

    Search author on:PubMed Google Scholar

  6. Blake Dirks
    View author publications

    Search author on:PubMed Google Scholar

  7. Anastasiya D. Oguienko
    View author publications

    Search author on:PubMed Google Scholar

  8. Alexander Viloria Winnett
    View author publications

    Search author on:PubMed Google Scholar

  9. Patrick Simpson
    View author publications

    Search author on:PubMed Google Scholar

  10. Dorsa Daeizadeh
    View author publications

    Search author on:PubMed Google Scholar

  11. Rustem F. Ismagilov
    View author publications

    Search author on:PubMed Google Scholar

  12. Rosa Krajmalnik-Brown
    View author publications

    Search author on:PubMed Google Scholar

  13. Nicola Segata
    View author publications

    Search author on:PubMed Google Scholar

  14. Levi D. Waldron
    View author publications

    Search author on:PubMed Google Scholar

  15. Sarkis K. Mazmanian
    View author publications

    Search author on:PubMed Google Scholar

Contributions

A.M. and S.K.M. designed the studies and wrote the manuscript. A.M. led all investigations and drafted figures. Metagenomic analysis and figure creation were executed by G.A., while data processing was done by K.L., with supervision from N.S. and L.D.W. A.M.S. assisted with flow cytometry experiments, tissue collections, and initial manuscript editing. J.C.B. carried out downstream RNA sequencing analysis and figure creation for this data. B.D. collected volatile fatty acid measurements with assistance from D.D., and supervision from R.K.B. A.D.O. performed statistical analysis for motor and GI function assays. A.V.W. supported the design and quality control of RNA sequencing methodology and raw data processing, with supervision from R.F.I. P.S. assisted with behavior data collection and tissue collections. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Anastasiya Moiseyenko or Sarkis K. Mazmanian.

Ethics declarations

Competing interests

S.K.M. is a founder and board member of Vertero Therapeutics and has equity in Nuanced Health and Seed Health. A.M. and S.K.M. hold a patent (US20240066074A1) on the use of Faecalibacterium prausnitzii and Prevotella histicola for the treatment of PD and have a pending application (US patent application 63/883,383) for the use of Faecalibacterium prausnitzii as a treatment for PD. The other authors do not have a competing interest.

Additional information

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

Supplementary information

Supplementary_Information (download PDF )

Supplementary_Data. (download XLSX )

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Moiseyenko, A., Antonello, G., Schonhoff, A.M. et al. Faecalibacterium prausnitzii, depleted in the Parkinson’s disease microbiome, improves motor deficits in α-synuclein overexpressing mice. npj Parkinsons Dis. (2026). https://doi.org/10.1038/s41531-026-01287-x

Download citation

  • Received: 18 September 2025

  • Accepted: 30 January 2026

  • Published: 05 March 2026

  • DOI: https://doi.org/10.1038/s41531-026-01287-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Download PDF

Associated content

Collection

Parkinson’s Disease and the Microbiome

Advertisement

Explore content

  • Research articles
  • Reviews & Analysis
  • News & Comment
  • Collections
  • Follow us on Facebook
  • Follow us on X
  • Sign up for alerts
  • RSS feed

About the journal

  • Aims & Scope
  • Content types
  • Journal Information
  • About the Editors
  • Open Access
  • Contact
  • Calls for Papers
  • Article Processing Charges
  • Editorial policies
  • Journal Metrics
  • About the Partner
  • 5 Questions with Our Editor-in-Chief

Publish with us

  • For Authors and Referees
  • Language editing services
  • Open access funding
  • Submit manuscript

Search

Advanced search

Quick links

  • Explore articles by subject
  • Find a job
  • Guide to authors
  • Editorial policies

npj Parkinson's Disease (npj Parkinsons Dis.)

ISSN 2373-8057 (online)

nature.com footer links

About Nature Portfolio

  • About us
  • Press releases
  • Press office
  • Contact us

Discover content

  • Journals A-Z
  • Articles by subject
  • protocols.io
  • Nature Index

Publishing policies

  • Nature portfolio policies
  • Open access

Author & Researcher services

  • Reprints & permissions
  • Research data
  • Language editing
  • Scientific editing
  • Nature Masterclasses
  • Research Solutions

Libraries & institutions

  • Librarian service & tools
  • Librarian portal
  • Open research
  • Recommend to library

Advertising & partnerships

  • Advertising
  • Partnerships & Services
  • Media kits
  • Branded content

Professional development

  • Nature Awards
  • Nature Careers
  • Nature Conferences

Regional websites

  • Nature Africa
  • Nature China
  • Nature India
  • Nature Japan
  • Nature Middle East
  • Privacy Policy
  • Use of cookies
  • Legal notice
  • Accessibility statement
  • Terms & Conditions
  • Your US state privacy rights
Springer Nature

© 2026 Springer Nature Limited

Nature Briefing Microbiology

Sign up for the Nature Briefing: Microbiology newsletter — what matters in microbiology research, free to your inbox weekly.

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