HIV Reservoir Dynamics and Latency Mechanisms Under Current and Emerging Antiviral Strategies

Dear Colleagues,

Despite significant advances in antiretroviral therapy (ART), human immunodeficiency virus (HIV) infection remains a global public health challenge. ART can suppress but not eliminate the integrated HIV DNA from the infected cells and reservoirs. A key barrier to viral eradication is the persistence of latent viral reservoirs, which enable HIV to evade human immune surveillance and re-emerge upon treatment interruption. Understanding the dynamics of HIV reservoirs and the mechanisms regulating latency is essential for developing future novel curative strategies.

In recent years, researchers have uncovered new layers of complexity in reservoir biology, which includes the heterogeneous distribution of latent HIV reservoirs in diverse tissue compartments, their variable decay kinetics under ART, and host and viral factors that contribute to latency. At the same time, emerging antiviral strategies, including long-acting agents, CRISPR-mediated gene editing, and latency-reversing agents alone or in combination with broadly neutralizing antibodies, are showing promise in reshaping reservoir dynamics and reducing the size of the latent reservoir.

Moreover, the application of artificial intelligence (AI) and machine learning approaches has enabled the development of predictive models for reservoir dynamics and the evaluation of treatment responses, paving the way for precision medicine approaches in HIV care.

In this Special Issue, we invite original research articles and review papers that highlight recent advances in understanding HIV reservoir dynamics and latency regulation, particularly in the context of modern antiviral strategies. We welcome submissions offering translational insights from preclinical models, clinical cohorts, mechanistic investigations, and computational approaches aimed at eradicating the reservoir.

Topics of interest include, but are not limited to, the following:

-HIV reservoir dynamics;

-Molecular and epigenetic mechanisms of HIV latency;

-Tissue-specific reservoir persistence and immune interactions;

-Impact of current and emerging antiretroviral therapies on reservoir size and composition;

-Predictive modeling of HIV latency and reservoir dynamics using AI and machine learning;

-Strategies for latency reversal and reservoir elimination;

-Multimodal therapies targeting latent reservoirs;

-New delivery methods for carrying gene-editing cargos targeting viral reservoirs.

We look forward to receiving your contributions, which will help to deepen our understanding of this critical area and foster the development of effective strategies for creating an HIV cure.

Sincerely,

Dr. Chen Zhang
Dr. Prasanta K. Dash
Guest Editors

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• HIV reservoirs
• HIV latency mechanisms
• reservoir persistence
• reservoir dynamics prediction
• HIV therapies
• reservoir targeting
• reservoir eradication strategies
• new gene-editing delivery vehicles