Gut bacterial metabolites modulate endoplasmic reticulum stress View Full Text


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Article Info

DATE

2021-10-15

AUTHORS

Xiaobo Ke, Kwontae You, Matthieu Pichaud, Henry J. Haiser, Daniel B. Graham, Hera Vlamakis, Jeffrey A. Porter, Ramnik J. Xavier

ABSTRACT

BackgroundThe endoplasmic reticulum (ER) is a membranous organelle that maintains proteostasis and cellular homeostasis, controlling the fine balance between health and disease. Dysregulation of the ER stress response has been implicated in intestinal inflammation associated with inflammatory bowel disease (IBD), a chronic condition characterized by changes to the mucosa and alteration of the gut microbiota. While the microbiota and microbially derived metabolites have also been implicated in ER stress, examples of this connection remain limited to a few observations from pathogenic bacteria. Furthermore, the mechanisms underlying the effects of bacterial metabolites on ER stress signaling have not been well established.ResultsUtilizing an XBP1s-GFP knock-in reporter colorectal epithelial cell line, we screened 399 microbiome-related metabolites for ER stress pathway modulation. We find both ER stress response inducers (acylated dipeptide aldehydes and bisindole methane derivatives) and suppressors (soraphen A) and characterize their activities on ER stress gene transcription and translation. We further demonstrate that these molecules modulate the ER stress pathway through protease inhibition or lipid metabolism interference.ConclusionsOur study identified novel links between classes of gut microbe-derived metabolites and the ER stress response, suggesting the potential for these metabolites to contribute to gut ER homeostasis and providing insight into the molecular mechanisms by which gut microbes impact intestinal epithelial cell homeostasis. More... »

PAGES

292

References to SciGraph publications

  • 2014-12-15. Bacteria, the endoplasmic reticulum and the unfolded protein response: friends or foes? in NATURE REVIEWS MICROBIOLOGY
  • 2008-06-29. Genome-wide association defines more than 30 distinct susceptibility loci for Crohn's disease in NATURE GENETICS
  • 2010-03-14. Genome-wide association identifies multiple ulcerative colitis susceptibility loci in NATURE GENETICS
  • 2018-12-10. Gut microbiome structure and metabolic activity in inflammatory bowel disease in NATURE MICROBIOLOGY
  • 2000-05-08. Dynamic interaction of BiP and ER stress transducers in the unfolded-protein response in NATURE CELL BIOLOGY
  • 2012-07-20. Identification of Toyocamycin, an agent cytotoxic for multiple myeloma cells, as a potent inhibitor of ER stress-induced XBP1 mRNA splicing in BLOOD CANCER JOURNAL
  • 2010-03-29. Sustained production of spliced X-box binding protein 1 (XBP1) induces pancreatic beta cell dysfunction and apoptosis in DIABETOLOGIA
  • 1999-01. Protein translation and folding are coupled by an endoplasmic-reticulum-resident kinase in NATURE
  • 2010-10-24. Production of indole-3-acetic acid and related indole derivatives from L-tryptophan by Rubrivivax benzoatilyticus JA2 in APPLIED MICROBIOLOGY AND BIOTECHNOLOGY
  • 2007-09. Trierixin, a Novel Inhibitor of ER Stress-induced XBP1 Activation from Streptomyces sp. in THE JOURNAL OF ANTIBIOTICS
  • 2018-01-08. Dynamics of metatranscription in the inflammatory bowel disease gut microbiome in NATURE MICROBIOLOGY
  • 2019-05-22. Potent inhibition of breast cancer by bis-indole-derived nuclear receptor 4A1 (NR4A1) antagonists in BREAST CANCER RESEARCH AND TREATMENT
  • 1996-04. Characterization and inhibition of a cholecystokinin-inactivating serine peptidase in NATURE
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    http://dx.doi.org/10.1186/s13059-021-02496-8

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    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/34654459


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    41 ER stress response
    42 activity
    43 alterations
    44 bacteria
    45 bacterial metabolites
    46 balance
    47 bowel disease
    48 cell homeostasis
    49 cell lines
    50 cellular homeostasis
    51 changes
    52 chronic conditions
    53 class
    54 conditions
    55 connection
    56 disease
    57 dysregulation
    58 effect
    59 endoplasmic reticulum
    60 endoplasmic reticulum stress
    61 epithelial cell homeostasis
    62 epithelial cell line
    63 example
    64 fine balance
    65 gene transcription
    66 gut bacterial metabolites
    67 gut microbes
    68 gut microbiota
    69 health
    70 homeostasis
    71 inducer
    72 inflammation
    73 inflammatory bowel disease
    74 inhibition
    75 insights
    76 interference
    77 intestinal epithelial cell homeostasis
    78 intestinal inflammation
    79 knock
    80 lines
    81 link
    82 mechanism
    83 membranous organelles
    84 metabolites
    85 microbes
    86 microbiota
    87 modulation
    88 molecular mechanisms
    89 molecules
    90 mucosa
    91 novel link
    92 observations
    93 organelles
    94 pathogenic bacteria
    95 pathway
    96 pathway modulation
    97 potential
    98 protease inhibition
    99 proteostasis
    100 response
    101 reticulum
    102 reticulum stress
    103 stress
    104 stress gene transcription
    105 stress pathways
    106 stress response
    107 study
    108 suppressor
    109 transcription
    110 translation
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