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Single-cell epigenetic, transcriptional, and protein states of HIV-1-infected cells [Feature_Barcoding]

ABSTRACT: The heterogeneity and rarity of HIV-1-infected cells hampers effective cure strategies. We used single-cell DOGMA-seq to simultaneously capture transcription factor accessibility, transcriptome, 156 surface proteins, HIV-1 DNA, and HIV-1 RNA from six HIV-1+ individuals during viremia and after suppressive antiretroviral therapy. We identified 252 transcriptionally inactive (HIV-1 DNA+ RNA–) and 270 transcriptionally active (HIV-1 RNA+) HIV-1-infected cells from 82,549 memory CD4+ T cells. We identified increased transcription factor accessibility in HIV-1 DNA+ RNA– cells (RORC) and HIV-1 RNA+ cells (IRF and AP-1), in addition to CNC and MAF in both. Both HIV-1 DNA+ RNA– and HIV-1 RNA+ cells upregulate IKZF3 (Aiolos) that correlates with proliferation of HIV-1-infected cells. We revealed that the heterogeneous HIV-1-infected T cells comprise four distinct immune programs driven by epigenetic regulators – IRF-activation, Eomes-cytotoxic effector, AP-1-migration, and cell death. Our study revealed the single-cell epigenetic, transcriptional, and protein states of transcriptionally inactive and active HIV-1-infected cells.

ORGANISM(S): Homo sapiens

PROVIDER: GSE239903 | GEO | 2023/09/20

REPOSITORIES: GEO

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Project description:Background: The cellular reservoir of latent HIV infection remains the main barrier to cure this virus. Elimination of this reservoir would be possible, if molecular identity of latently infected cells were fully elucidated. Biomarkers proposed previously were able to capture only a relatively small fraction of all reservoir cells. In the present study, we set out to conduct comprehensive molecular profiling, at the protein and RNA levels, of CD4+ T cells latently infected with HIV in vitro, using liquid chromatography-mass spectrometry (LC-MS) and RNA sequencing (RNA-Seq), respectively. Protein-based methods such as quantitative proteomic profiling using LC-MS may be more beneficial due to direct transferability of results to antibody-based approaches to capture latently infected cells. Integrated analysis of proteomic and transcriptomic data adds a level of validation and increases confidence in identified biomarkers. Flow cytometry and integrated HIV DNA assay were further used to enrich for latently infected cells with antibodies against selected biomarker proteins. Results: Using quantitative proteomics, we identified a total of 10,886 proteins (peptide level FDR < 0.05), of which 673 were up- and 780 down-regulated in latently infected compared to mock-infected cells in vitro (p < 0.05). Among these proteins, 21 were dysregulated at the RNA level in the same direction. Pathway analysis identified p53, mTOR, Wnt and NOTCH signaling, demonstrating that our in vitro model reflects known mechanisms of latency establishment and maintenance. Comparison of identified proteins with other proteomics studies revealed that identified molecular signatures of latency depend on technology and cell types used; however, a subset of proteins were identified both in the present, and at least one other study. Antibodies against selected protein markers, CEACAM1 and PLXNB2, could enrich for latently infected cells from mixed cell population 3-10 fold (5.8 fold average, p < 0.001). Conclusion: Two new molecules, CEACAM1 and PLXNB2, were identified as biomarkers for HIV latency. However, the level of enrichment for latently infected cells compared to biomarkers proposed previously was not improved. These results are consistent with the idea that each proposed biomarker defines only a subset of latently infected cells, and that a combined biomarker will be required to capture or target the latent HIV reservoir represented by different cell types.

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Single-cell epigenetic, transcriptional, and protein states of HIV-1-infected cells [Feature_Barcoding]

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