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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 1

Galunisertib upregulates metabolic pathways in lymph node CD4+ T cells.

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Galunisertib upregulates metabolic pathways in lymph node CD4+ T cells.
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(A) Schematic of the study: Eight macaques were infected with SIVmac239M2 intravenously, and ART was started at week 6 post-infection. The red rectangle indicates the time points analyzed by scRNA-seq: before (BC1; week 35 post-infection) and after the first galunisertib (Gal) cycle (AC1; week 37 post-infection) when the lymph nodes were collected. LN BX, lymph node biopsy; R BX, rectal biopsy; ATI, Antiretroviral therapy interruption; FNA, fine-needle aspiration; Nivo, nivolumab. (B) UMAP projection of scRNA-seq data from lymph node cells, showing annotation of distinct cell subsets. (C) Volcano plot showing differentially expressed genes (DEGs) resulting from the comparison of CD4+ T cells by MAST hurdle model at BC1 versus AC1. Labeled genes that reached significance (BH FDR–adjusted q ≤ 0.1) and log2FC ≥ 1 are shown in the bubble plot. (D and E) Enriched hallmark (D) and KEGG metabolic (E) pathways in total CD4+ T cells based on GSEA (BC1 vs. AC1). Upregulated pathways (red) and downregulated pathways (blue) are shown with their respective normalized enrichment scores (BH FDR *q ≤ 0.1).

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