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Immune Cells Harbor Their Own Microbiome-Derived Metabolome: A New Layer of Immunometabolic Regulation

Publicada
Servidor
Preprints.org
DOI
10.20944/preprints202604.0942.v1

Current models of microbiome–immune crosstalk center on extracellular receptor-mediated signaling, yet a critical observation challenges this paradigm: intracellular concentrations of gut-derived bacterial metabolites (GDBMs) in CD4⁺ T cells do not correlate with paired plasma levels, and it is intracellular — not circulating — GDBM burden that associates with metabolic pathway disruption and immune senescence. Here we propose the concept of an intracellular microbiome metabolome: a pool of aromatic GDBMs actively accumulated through carrier-mediated transport, retained through transcriptional suppression of efflux transporters, and integrated into host metabolic networks where metabolites directly engage intracellular senescence pathways. Using p-cresol sulfate (PCS) as a mechanistic prototype, we review transcriptomic, proteomic, and metabolomic evidence implicating SLCO4A1/OATP4A1 as the primary entry transporter, whose suppression following PCS exposure creates a feed-forward intracellular retention loop. Once accumulated, PCS functions as a direct agonist of the aryl hydrocarbon receptor (AhR), engaging five downstream effector programs — TGF-β/SMAD signaling, Wnt/β-catenin reprogramming, Foxp3-dependent Treg induction, Notch dysregulation, and PTGS2/COX-2 induction with coordinate HPGD suppression driving PGE₂ excess via EP2/EP4/cAMP/CREM — that converge on mTOR suppression, glycolytic collapse, and mitochondrial dysfunction. This metabolic collapse in turn activates the GCN2/integrated stress response as a downstream consequence, driving p16/CDKN2A and p21/CDKN1A induction and the full immunometabolic signature of accelerated CD4⁺ T cell aging. The plasma–intracellular dissociation explains why circulating GDBM levels have failed to predict immune outcomes in HIV-1 infection, chronic kidney disease, and aging, and positions intracellular GDBM quantification as the biologically relevant exposure metric. We discuss three therapeutic intervention layers: reduction of microbial metabolite production, blockade of SLCO4A1-mediated entry and efflux suppression, and targeting the AhR signaling axis with downstream metabolic and GCN2/ISR consequences.

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