People living with HIV who are receiving antiretroviral therapy, often called ART, can suppress the virus to very low levels. Even with effective treatment, some infected cells continue to produce small amounts of HIV RNA. These rare cells are thought to contribute to chronic inflammation and may play a role in viral rebound if therapy is stopped.

Studying these cells has been challenging. Standard single cell RNA sequencing methods are not well suited to detecting HIV RNA because infected cells are rare and HIV transcripts often lack the polyadenylated tails that typical RNA sequencing protocols rely on for capture.

To address this challenge, researchers at the Gladstone Institutes have developed a modified sequencing method called HIV-seq. The approach adds special capture sequences during single cell RNA sequencing that target conserved regions of the HIV genome. This increases the likelihood that HIV transcripts will be detected during sequencing.

HIV-seq increases detection of HIV RNA+ cells from PWH without affecting host transcriptome

A Schematic illustrating the genomic location and nucleotide position (based on HXB2) of HIV-specific capture primers for HIV-seq. B HIV-seq does not affect host transcriptome analysis by scRNA-seq. Shown are UMAP plots of CD4 + T cells from two ART-naïve viremic PWH (PID1052 and PID8027) processed in the absence (blue) vs. presence (yellow) of HIV capture sequences. C HIV-seq increases numbers of HIV RNA+ cells identified from viremic PWH. UMAP plots of scRNA-seq analysis of pre-ART CD4 + T cells from PID1052 and PID8027, showing HIV RNA+ cells (colored dots) among total CD4 + T cells (gray dots), with vs. without the addition of HIV capture sequences. Colors represent the number of HIV reads, from low (blue) to high (red).The percentages of HIV RNA+ cells among CD4 + T cells are indicated in the lower right of each plot. D HIV-seq increases the numbers of HIV RNA reads detected per infected cell. Normalized numbers of HIV reads in the absence (blue) vs. presence (yellow) of HIV capture sequences are shown for each HIV RNA+ cell identified from PID1052 and PID8027 in panel B. Horizontal lines indicate medians. The analysis includes 64 cells detected without HIV capture oligos and 99 cells detected with HIV capture sequences. **P = 0.0012, as determined using a two-sided Mann-Whitney test. E HIV-seq increases detection of HIV reads throughout the HIV genome. HIV reads from PID1052 and PID8027 were aligned to the HIV-1 subtype B consensus reference genome. The y-axis depicts individual HIV regions, and the x-axis shows the normalized number of HIV transcripts per 10,000 CD4 + T cells, in the absence (blue) vs. presence (yellow) of the HIV capture sequences. 

Using HIV-seq, the researchers were able to detect about twice as many HIV reads per infected cell compared with conventional approaches. This improved sensitivity allowed them to better identify cells actively transcribing HIV RNA.

The results showed that HIV RNA positive cells are commonly found among T effector memory cells, a subset of immune cells involved in long term immune responses. Interestingly, these cells behave differently depending on whether HIV is actively replicating or suppressed by treatment.

During active infection, HIV-transcribing cells showed a cytotoxic gene expression signature, meaning they expressed genes associated with immune cell killing functions. However, when the virus was suppressed by ART, these cells displayed a different pattern. Instead of cytotoxic signals, they showed an anti inflammatory signature, including increased activity of the TGF-β pathway and reduced interferon signaling.

These findings suggest that HIV infected cells that persist during treatment may adopt a state that dampens immune activation. This may help them survive in the body despite ongoing therapy.

By improving the ability of RNA sequencing to detect rare HIV-transcribing cells, HIV-seq provides a valuable tool for studying viral persistence and immune responses in treated individuals. Understanding how these cells survive may help guide future strategies aimed at eliminating HIV reservoirs and preventing viral rebound.