# Single cell RNA-seq and single molecule RNA-FISH approaches to study stochasticity of latent HIV-1 reactivation > **NIH NIH R21** · ALBERT EINSTEIN COLLEGE OF MEDICINE · 2021 · $210,000 ## Abstract The persistent reservoirs are the ultimate hurdle to HIV-1 cure. ‘Shock and Kill’ strategy to eliminate HIV- 1 reservoirs requires reactivation of all latent proviruses with latency reversing agents (LRA), which is currently not possible. Quantitation of patient derived latent reservoirs by QVOA (Quantitative Viral Outgrowth Assay) indicated that only ~1/60th of full-length replication competent latent proviruses are activated by LRA. The reason for this variability is not completely understood but has been attributed to differential epigenetic regulation of provirus (due to different sites of proviral integration), differences in the viral genome (genetic variability), differential expression of cellular factors or different transcriptional or post-transcriptional blocks in the patient- derived latent cells. In the ExVivo and cell culture models of latency, where a single viral clone is used for infection with no genetic heterogeneity, reactivation of only a small percentage of cells and different levels of expression of viral RNA and proteins indicate cell-to-cell variation in reactivation. These studies also revealed that the majority of latent cells are not activated by current approaches. Current strategies do not address cell-to-cell variation in proviral reactivation and understanding this variability in vivo is essential to achieve either full reactivation or full suppression of these reservoirs. The goal of this application is to employ innovative single-cell and multi-omics platforms to investigate mechanisms of HIV persistence at the single-cell level with greater precision and higher resolution than has been achieved previously using traditional techniques. Stellaris-based quantitative single molecule RNA-FISH (smRNA-FISH), that allows the greater resolution and precise quantitation of the number of RNA molecules within single cells, have been used to study stochasticity in eukaryotic gene transcription. We have applied smRNA-FISH combined with Immunofluorescence (IF) termed SMIRA (Single cell and single molecule IF and RNA-FISH based Assay) to study HIV-1 reactivation in latency models and quantitated the single RNA molecules using FISH-quant, a computational algorithm. In addition, we have combined these studies with a high speed and high resolution scanning (HSHRS) microscopy to identify rare positive cell/s in a large pool of negative cells. Using these methods, our goal is to quantitate the cell-to-cell variability in latent cells. Our hypothesis is that cell- to-cell variation in HIV-1 reactivation is due to both ‘intrinsic’ and ‘extrinsic’ factors. By combining single cell and single molecule approaches with single cell RNA-sequencing (scRNA-seq) methodologies we propose to identify the determinants responsible for variation in the HIV-1 reactivation and extend these studies to identify these markers in patient samples. In aim I, we will characterize and determine the genes and pathways involved in the stochastic activation in... ## Key facts - **NIH application ID:** 10168452 - **Project number:** 5R21AI152826-02 - **Recipient organization:** ALBERT EINSTEIN COLLEGE OF MEDICINE - **Principal Investigator:** GANJAM V KALPANA - **Activity code:** R21 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2021 - **Award amount:** $210,000 - **Award type:** 5 - **Project period:** 2020-05-20 → 2023-04-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10168452 ## Citation > US National Institutes of Health, RePORTER application 10168452, Single cell RNA-seq and single molecule RNA-FISH approaches to study stochasticity of latent HIV-1 reactivation (5R21AI152826-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10168452. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*