Robert F. Siliciano

The paper assesses whether HIV-1 infection confers resistance to CTL-mediated cell death and finds no intrinsic resistance, with survival differences attributed to MHC class I downregulation.

This study compares acute infection and viral rebound dynamics in ART-treated infant rhesus macaques using a mathematical model to identify increased infected cell death during rebound.

The paper identifies autologous neutralizing antibodies (aNAbs) as critical determinants of HIV-1 rebound after treatment interruption, defining quantitative limits on rebound-competent reservoirs.

This study shows antigen stimulation can reactivate HIV-1 proviruses integrated in repressive chromatin, suggesting deeper latency may contribute to viral rebound.

This paper demonstrates that HLA-E-targeting diabodies can induce CD8+ T cell-mediated lysis of HIV-1-infected cells, bypassing limitations of classical MHC class I antigens.

This paper describes a user-managed 100 keV electron microscope setup for structural virology, enabling high-quality cryo-EM data collection and analysis within a laboratory setting.

The paper investigates superinfection with intact HIV-1 in people living with HIV-1, showing it leads to conditional replication of defective proviruses and nonsuppressible viremia.

HIV-1 viremia not suppressed by effective ART can be caused by proviruses in CD4+ T cells reactive to autologous antigens.

This study uses scRNA-seq to analyze immune changes in SIV-infected rhesus macaques over time, revealing immune shifts during infection and ART, and identifying transcriptional signatures linked to immune dysregulation and treatment outcomes.

The paper shows that cognate antigen engagement in CD4+ T cells on long-term ART increases HIV-1 transcription through T cell activation, suggesting a role in viral rebound.

This study examines how early ART initiation in HIV-infected infants affects antibody development and latent reservoir dynamics, showing their opposing impacts on post-treatment viral rebound.

The paper introduces a method to quantify diverse perturbation responses and discover novel biological insights in single-cell perturbation datasets.