A Single-Cell Perspective on the Effects of Dopamine in the Regulation of HIV Latency Phenotypes in a Myeloid Cell Model

TL;DR

This study explores how dopamine affects HIV latency in myeloid cells, suggesting that high dopamine levels may reverse HIV dormancy and increase inflammation.

Contribution

The study introduces a novel single-cell approach to investigate dopamine's impact on HIV latency mechanisms in a myeloid cell model.

Findings

DA exposure reduces latency signature genes and histone linkers, promoting HIV transcription.

High dopamine levels are linked to increased metabolic pathways potentially contributing to neurodegeneration.

The study identifies computational methods to detect latency reversal mechanisms in HIV-infected cells.

Abstract

Psychostimulants such as methamphetamine (Meth) induce high dopamine (DA) levels in the brain, which can modify immune cells expressing DA receptors. This is relevant in conditions of infection with the human immunodeficiency virus (HIV), overlapping with substance use. However, the effects of DA on HIV latency phenotypes are largely unknown. We used single-cell methods and gene network computational analysis to understand these relationships, using the U1 latent promonocyte model to identify signatures of latency and its reversal in the context of DA exposure. Our findings point to mechanisms by which high DA levels in the brains of substance users may impact HIV transcription and neuroinflammation. Our data indicate that latency is maintained along with the expression of histone linkers and components of chromatin organization, with increased metabolic pathways that may lead to pathways in neurodegeneration. DA exposure decreased latency signature genes, histone linkers, and protein-containing complex organization components, unleashing inflammatory pathways and HIV gene transcription. Overall, this work suggests that DA can induce latency reversal through mechanisms that can be harnessed to drive cells. The proposed methods developed here in cell lines can be used to identify latency signatures in other HIV infection systems.

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