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Microbiome-derived metabolites shape CD4+ T cell differentiation and immune aging in HIV-1 infection
Amanda Cabral Da Silva, Luke Flantzer, Jaclyn Weinberg, Shuya Kyu, Lisa P. Daley-Bauer, Anyce Godoy, Ana Carolina Santana, Aarthi Talla, Amber Lynn Rittgers, Sarah Welbourn, David Ezra Gordon, Jeffery Alan Tomalka, Vincent C. Marconi, Dean P. Jones, Souheil-Antoine Younes
Amanda Cabral Da Silva, Luke Flantzer, Jaclyn Weinberg, Shuya Kyu, Lisa P. Daley-Bauer, Anyce Godoy, Ana Carolina Santana, Aarthi Talla, Amber Lynn Rittgers, Sarah Welbourn, David Ezra Gordon, Jeffery Alan Tomalka, Vincent C. Marconi, Dean P. Jones, Souheil-Antoine Younes
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Research Article AIDS/HIV Aging Immunology

Microbiome-derived metabolites shape CD4+ T cell differentiation and immune aging in HIV-1 infection

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Abstract

The role of aromatic gut-derived bacterial metabolites (GDBMs) in shaping immune cell metabolism and function remains poorly explored. Using ex vivo metabolomic profiling of paired plasma and CD4+ T cells from people living with HIV-1 (PLWH), we identified a network of aromatic GDBMs whose cell-associated abundance, rather than systemic levels, was linked to broad alterations in CD4+ T cell metabolic and functional states. Among these, p-cresol sulfate (PCS) emerged as a mechanistic prototype. Ex vivo flow cytometry and scRNA-seq of CD4+ T cells stratified by cell-associated PCS levels revealed dose-dependent enrichment of transcriptional programs associated with impaired differentiation, regulatory-like identity, and cellular senescence. In vitro transcriptomic and proteomic analyses of PCS-exposed CD4+ T cells demonstrated induction of cell-cycle arrest, mitochondrial dysfunction, and senescence-associated programs, including upregulation of p16 and p21. Integration of these immunometabolic findings with HIV-1 reservoir measurements revealed that CD4+ T cell states defined by cell-associated GDBMs track with intact proviral DNA levels in vivo. These findings define a microbiome-derived axis that reshapes CD4+ T cell metabolism and fate, promotes immune aging in PLWH, and may foster immunometabolic states linked to long-term HIV-1 reservoir persistence.

Authors

Amanda Cabral Da Silva, Luke Flantzer, Jaclyn Weinberg, Shuya Kyu, Lisa P. Daley-Bauer, Anyce Godoy, Ana Carolina Santana, Aarthi Talla, Amber Lynn Rittgers, Sarah Welbourn, David Ezra Gordon, Jeffery Alan Tomalka, Vincent C. Marconi, Dean P. Jones, Souheil-Antoine Younes

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Figure 2

Metabolic pathway correlations with intact and total HIV-1 reservoir levels in CD4+ T cells and relationship to the GDBMs.

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Metabolic pathway correlations with intact and total HIV-1 reservoir lev...
(A) Volcano plot showing Spearman correlations between CD4+ T cell metabolite intensities and intact HIV-1 reservoir size. Red points indicate statistically significant correlations (P < 0.05), and boxed regions highlight metabolites with strong negative (left) and positive (right) associations. (B) Linear regression of intact versus total HIV-1 copies per million CD4+ T cells, demonstrating a strong positive correlation (R = 0.79, P = 5.6 × 10 –6, n = 25). (C) Heatmap of negatively correlated metabolites (highlighted in A, left box), categorized by metabolic pathways. (D) Heatmap of positively correlated metabolites (highlighted in A, right box), with pathway annotations. Circle size and color scale represent strength and direction of Spearman correlation coefficients between each metabolite and reservoir size (intact and total IPDA values). Targeted quantification was performed for PCS, PAG, PCG, and IAA. Values represent Spearman correlation coefficients between the indicated GDBMs (x axis) and metabolites within key pathways (y axis). Pathway annotations on the right summarize functional categories significantly associated with GDBM levels. Positive correlations (red) indicate coenrichment between GDBMs and metabolites, while negative correlations (blue) indicate reciprocal relationships suggestive of metabolic suppression. Data were obtained ex vivo from freshly isolated CD4+ T cells (n = 26 donors). Spearman correlations between HIV reservoir measurements and CD4+ T cell metabolites (A) are shown with unadjusted P values due to the limited number of significant associations, whereas correlations within the metabolomics dataset (C and D) were corrected for multiple comparisons using the FDR method.

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