# Single-Cell Transcriptomics of Non-Activated Latently Infected T cells Isolated from HIV+ Drug Users > **NIH NIH R61** · J. DAVID GLADSTONE INSTITUTES · 2020 · $658,493 ## Abstract SINGLE-CELL TRANSCRIPTOMICS OF NON-ACTIVATED LATENTLY INFECTED T CELLS ISOLATED FROM HIV+ DRUG USERS Opioid use alters the epigenetic structure of the brain but its effects on CD4+ memory T cells, the main reservoir for latent HIV-1, remain unknown. The central hypothesis of this application is that the identity of memory T cells carrying latent HIV-1 is altered by opioid exposure, and thus, identifying specific biomarkers in patients with opioid use would be valuable. This hypothesis was formulated based on published results showing that opioid receptors are expressed on CD4+ T cells and signaling through these receptors modulates T-cell activation and differentiation. The central hypothesis will be tested in a two-pronged, highly milestone-driven approach. In the innovation phase (R61), our aims will optimize two necessary technologies: 1) Tracker-Cas9-Q, a new CRISPR- based in vivo DNA-labeling technique to visualize latently infected T cells, and 2) single-cell RNA sequencing and associated computational analysis for robust biomarker development. Aim 1: To label the HIV-1 proviral locus in intact cells by harnessing novel CRISPR-Cas protein technologies. Tracker-Cas9-Q is a new fluorescently labeled, but internally quenched, complex of catalytically inactive CRISPR/Cas9 and specific CRISPR guide RNAs that only fluoresces upon DNA binding (Murthy Lab). The underlying working hypothesis is that Tracker-Cas9-Q delivered within nanogold microparticles (CRISPR-Gold) allows efficient in vivo labeling and flow sorting of T cell lines containing latent HIV DNA. Aim 2: To establish single-cell RNA-Seq and computational biomarker identification in primary T cells ex vivo infected with dual-fluorescent HIV-1 with and without opioid exposure. The transcriptome of individual cells – alone or in complex cell populations – can now be analyzed at sufficient depth (Ott Lab) to allow reliable biomarker development in HIV-infected primary cell populations (Yosef Lab). Our working hypothesis is that individual latently infected primary T cells can be efficiently isolated and analyzed on a single-cell basis using RNA-Seq. In order to progress to the R33 phase, at the end of the R61 period we will have developed an HIV-specific DNA labeling system with efficient delivery (>50%) and sortable fluorescence intensities and established single-cell RNA-Seq and computational platforms for biomarker development. The R33 phase has one aim combining the experimental systems from Aims 1 and 2 in primary T cells isolated from aviremic HIV+ individuals under antiretroviral therapy. Aim 3: To characterize latently infected memory T cells at the single-cell level, isolated from HIV+ individuals with and without opioid use, using novel CRISPR-based labeling techniques. Our working hypothesis is that the newly developed Tracker-Cas9-Q and CRISPR-Gold technologies will efficiently label the latent provirus in patient-derived T cells, and combined with single-cell RNA-Seq and comput... ## Key facts - **NIH application ID:** 9876995 - **Project number:** 5R61DA048444-02 - **Recipient organization:** J. DAVID GLADSTONE INSTITUTES - **Principal Investigator:** Melanie Maria Ott - **Activity code:** R61 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $658,493 - **Award type:** 5 - **Project period:** 2019-03-01 → 2021-12-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/9876995 ## Citation > US National Institutes of Health, RePORTER application 9876995, Single-Cell Transcriptomics of Non-Activated Latently Infected T cells Isolated from HIV+ Drug Users (5R61DA048444-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9876995. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*