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Single-cell capture of on-ART SIV transcription reveals TGF-β–mediated metabolic control of viral latency
Romaila Abd-El-Raouf, Jakob Harrison-Gleason, Jinhee Kim, Ching Man Wai, Kayla L. Yerlioglu, Catarina Ananias-Saez, Alec Ksiazek, Jeffrey T. Poomkudy, Mariluz Araínga, Deepanwita Bose, Claudia Cicala, James Arthos, Francois J. Villinger, Ramon Lorenzo-Redondo, Elena Martinelli
Romaila Abd-El-Raouf, Jakob Harrison-Gleason, Jinhee Kim, Ching Man Wai, Kayla L. Yerlioglu, Catarina Ananias-Saez, Alec Ksiazek, Jeffrey T. Poomkudy, Mariluz Araínga, Deepanwita Bose, Claudia Cicala, James Arthos, Francois J. Villinger, Ramon Lorenzo-Redondo, Elena Martinelli
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Research Article AIDS/HIV Immunology Metabolism

Single-cell capture of on-ART SIV transcription reveals TGF-β–mediated metabolic control of viral latency

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Abstract

We previously demonstrated that blocking TGF-β with galunisertib, a safe, orally available small drug, reactivated latent SIV in vivo by shifting T cells toward a transitional effector phenotype. Here, we investigated the mechanisms underlying this effect using single-cell RNA sequencing, metabolic profiling, and high-dimensional spectral flow cytometry of samples from SIV-infected, antiretroviral therapy–treated (ART-treated) macaques before and after galunisertib. To characterize virus-transcribing, infected cells during ART, we developed a novel, sensitive SIV Transcripts Capture Assay (SCAP) that detected 127 SIV-expressing cells within lymph node single-cell transcriptome libraries. Galunisertib drove broad metabolic reprogramming in CD4+ T cells, with transcriptional upregulation of inflammatory and mitochondrial biosynthesis pathways, confirmed by Seahorse profiling. Metabolomics revealed increased energy metabolites and amino acids and enhanced metabolic flux without proliferation. SIV transcript–positive cells before galunisertib were metabolically quiescent compared with cells without detectable viral transcripts. After galunisertib, virus-expressing cells showed a dramatic metabolic activation, with upregulation of glycolysis, fatty acid metabolism, and TNF-α signaling. High-dimensional flow cytometry demonstrated effects beyond CD4+ T cells, including fewer tissue-resident memory T cells, but more inflammatory macrophages. In conclusion, SCAP represents a specific tool for characterizing rare SIV-infected cells transcribing virus during ART, and it reveals TGF-β as a key mediator of viral latency in vivo through metabolic suppression.

Authors

Romaila Abd-El-Raouf, Jakob Harrison-Gleason, Jinhee Kim, Ching Man Wai, Kayla L. Yerlioglu, Catarina Ananias-Saez, Alec Ksiazek, Jeffrey T. Poomkudy, Mariluz Araínga, Deepanwita Bose, Claudia Cicala, James Arthos, Francois J. Villinger, Ramon Lorenzo-Redondo, Elena Martinelli

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Figure 7

TGF-β blockade decreases resident T cells and increases inflammatory macrophages in the gut tissue.

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TGF-β blockade decreases resident T cells and increases inflammatory mac...
Cells from rectal biopsies were gated within live, CD45+, and CD4+ T cells (A), CD8+ T cells (B), macrophages (CD64+, C), and NK cells (CD3–, CD20–NKG2A+, D). Visualization of final FlowSOM clustering results mapped onto t-SNE plots is shown. Bubble plots comparing cluster proportions between before (BC1, before cycle 1; week 35 post-infection) and after (AC4, after cycle 4; week 49 post-infection) all 4 galunisertib cycles are shown next to each cluster with color proportional to the effect size of the change calculated as Hedges’ g (red for increased from BC1 to AC4; blue for decreased). Bubble size is proportional to the statistical significance of the change, with larger bubbles corresponding to smaller adjusted P values. Clusters with adjusted q ≤ 0.05 (Wilcoxon signed-rank test, Holm-Šidák correction) are marked with a star.

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