Single-Cell Transcriptomics of Human Tonsils Reveals Nicotine Enhances HIV-1-Induced NLRP3 Inflammasome and Mitochondrial Activation

Abstract

Background: HIV-1 infection, even with effective antiretroviral therapy (ART), is associated with chronic inflammation and immune dysfunction, contributing to long-term health complications. Nicotine use, prevalent among people with HIV (PWH), is known to exacerbate immune activation and disease progression, but the precise biological mechanisms remain to be fully understood. This study sought to uncover the synergistic effects of HIV-1 infection and nicotine on immune cell function, focusing on beneficial insights into NLRP3 inflammasome activation, oxidative stress, and mitochondrial pathways.

Methods: Human tonsil explants were infected with HIV-1 and exposed to nicotine. Single-cell RNA sequencing was used to profile immune cell populations and gene expression linked to inflammasome activation, oxidative stress, and mitochondrial function. Gene set enrichment analysis (GSEA) and synergy assessments were conducted to investigate how nicotine modulates immune responses in the context of HIV.

Results: The combination of HIV infection and nicotine exposure significantly increased NLRP3 inflammasome activation, thioredoxin, and components of oxidative phosphorylation.

Conclusions: This study highlights how the combined effects of HIV-1 and nicotine offer valuable insights into immune modulation, opening doors for future therapeutic strategies. Targeting the NLRP3 inflammasome and addressing nicotine use may contribute to improved outcomes for PWH.

Keywords: HIV-1; NLRP3 inflammasome; mitochondrial dysfunction; nicotine; oxidative stress.

Figure 1

Infection of human tonsil explants by X4-tropic HIV-1_NL-CI treated with nicotine. Human tonsil explants were cultured on collagen rafts and infected with HIV-1_NL-CI or vehicle media. Supernatants were collected on days 2, 5, and 8 post-infection. Sloughed-off cells and media were separated by centrifugation, and a full media change was performed at each indicated time cells were collected. Cells were subjected to LIVE/DEAD staining and flow cytometry to evaluate viability (A). Suspension cells in supernatants were collected on day 8 for single-cell dissociation and processing for single-cell sequencing. Flow cytometry results are quantified as percent infection and percent viability in tonsils unexposed or exposed to HIV-1 (B). Mean values ± standard errors of the means from three to five donors.

Figure 2

UMAP projections of single-cell RNA sequencing data from human tonsil explants. (A) Cells are color-coded by clusters identified through unsupervised clustering. (B) Cells are annotated with specific immune cell types based on marker expression from the Massoni reference dataset. (C) Cells are labeled as either infected or uninfected with HIV-1. (D) Cells are categorized into broader cell types, including B cells, T cells, ILC, myeloid, and epithelial cells. (E) Cells are color-coded by tonsil donors, representing data from nine individual donors. (F) Cells are stratified by HIV exposure, infection, and nicotine treatment status.

Figure 3

Expression dot plot representation of inflammasome pathway enrichment across all cells, T cells, and myeloid cells under HIV exposure, infection, and nicotine treatment. Expression of inflammasome-related genes across three cell populations—all cells, T cells, and myeloid cells—under various experimental conditions, including HIV exposure, HIV infection, and nicotine treatment. The y-axis lists inflammasome genes organized into relevant gene sets. The x-axis represents the combinations of experimental conditions indicated as either present (+) or absent (−) for HIV exposure, HIV infection, and nicotine treatment. The final two columns for myeloid cells are shaded to indicate that no infected myeloid cells were observed in these conditions. Dot size correlates with the abundance of gene expression within each population, while color intensity signifies the magnitude of expression.

Figure 4

Expression dot plot representation of respiratory gene signatures in all cells, T cells, and myeloid cells under HIV exposure, infection, and nicotine treatment. This figure shows the expression of respiratory gene signatures across three cell populations—all cells, T cells, and myeloid cells—under different experimental conditions, including HIV exposure, HIV infection, and nicotine treatment. The y-axis lists respiratory gene signatures, including Complex IV, mitochondrial, transporter, enzyme, and mitochondrial DNA regulation signatures. The x-axis represents the experimental conditions, indicated by the presence (+) or absence (−) of HIV exposure, HIV infection, and nicotine treatment. The final two columns for myeloid cells are shaded to indicate that no infected myeloid cells were observed in these conditions. Dot size correlates with the percentage of cells expressing each gene signature, with larger dots indicating higher percentages. The color intensity (blue to red gradient) reflects the average expression level of the gene signature, with red representing higher expression and blue representing lower expression.

Figure 5

Expression of TXN and related genes in all cells, T cells, and myeloid cells under HIV exposure, infection, and nicotine treatment. This figure illustrates the expression patterns of TXN (thioredoxin) and related oxidative stress genes across three cell populations—all cells, T cells, and myeloid cells—under conditions of HIV exposure, HIV infection, and nicotine treatment. The y-axis lists key oxidative stress-related genes, including TXN, TXNRD1, TXNIP, PRDX1, APEX1, NFKB1, PRDX5, PRDX2, TXN2, and GLRX. The x-axis denotes combinations of experimental conditions, marked as present (+) or absent (−) for HIV exposure, HIV infection, and nicotine treatment. The final two columns for myeloid cells are shaded to indicate that no infected myeloid cells were observed in these conditions. Dot size represents the percentage of cells expressing each gene. The color intensity (blue to red gradient) reflects the average expression level, with red indicating higher expression and blue indicating lower expression.

Figure 6

Gene set enrichment analysis (GSEA) for infected vs. unexposed and exposed uninfected vs. unexposed conditions untreated and with nicotine treatment. Gene set enrichment analysis (GSEA) is shown for all cells untreated infected vs. unexposed (A) and exposed vs. uninfected (B) for and for all cells nicotine-treated infected vs. unexposed (C) and nicotine-treated exposed uninfected (D). Comparative dot plots are shown (E) in cell populations (all, T cells, and myeloid cells) for infected vs. unexposed (left) and exposed uninfected vs. unexposed (right) conditions. The dot size represents the significance level (p-value), and the color intensity indicates the normalized enrichment score (NES). Pathways analyzed include Complex I biogenesis, respiratory electron transport, pro-inflammatory cell recruitment, and purinergic signaling. Color-coded circles represent different experimental conditions: unexposed (gray), exposed uninfected (peach), infected (red), unexposed nicotine (tan), exposed uninfected nicotine (light tan), and infected nicotine (light red).

Figure 7

Synergy analysis combined HIV and nicotine exposure on key pathways in T cells and myeloid cells. (A) Hypothetical model demonstrating how synergy is calculated. The bar graph compares the expected additive model (gray) to the actual measured combinatorial effect (dark red/maroon) for key biological processes such as Complex I biogenesis, respiratory electron transport, cell recruitment (pro-inflammatory response), and purinergic signaling in Leishmaniasis infection. Synergistic effects occur when the actual measured effect exceeds the predicted additive effect, indicated by a positive synergistic effect (>0). (B) Bar graphs represent the log2 fold change (log2FC) in pathway activity for Complex I biogenesis, respiratory electron transport, cell recruitment (pro-inflammatory response), and purinergic signaling in Leishmaniasis infection. Pathway changes are shown for T cells (left) and myeloid cells (right) under infected (left) and exposed uninfected (right) conditions. The experimental conditions compared are HIV, nicotine, and combined HIV+ nicotine exposure. The predicted additive effect (gray) is compared with the actual observed effect (dark red/maroon). This synergy analysis highlights the comparison between the predicted additive effect (gray) and the actual observed effect (dark red/maroon). (C) Synergy categories displayed using overrepresentation analysis (ORA) for all gene sets in all cells and T cells during infection. Pathway enrichment is shown based on adjusted p-values (−log10), with dot sizes indicating the magnitude of significance for each enriched pathway and color indicating the directionality of change. (D) Synergy analysis for exposed uninfected cells, showing pathway enrichment across all cells, T cells, and myeloid cells. This analysis visualizes synergy in terms of adjusted p-values (−log10 FDR), with dot size reflecting the level of significance and color intensity showing the strength of the synergy effect.

Figure 8

Synergistic effect of nicotine and HIV on oxidative phosphorylation and inflammatory signaling in T cells and macrophages. (A) Schematic representation of T cells and macrophages under four conditions: untreated, HIV-infected, nicotine-treated, and HIV-infected with nicotine treatment. The arrows indicate the levels of oxidative phosphorylation (OxPhos) in T cells and inflammasome activation in macrophages across the conditions. HIV infection alone increases OxPhos and ATP release from T cells, leading to inflammasome activation and interleukin-1β (IL-1β) production in macrophages. Nicotine treatment further enhances these effects, leading to higher reactive oxygen species (ROS) production and ATP efflux in T cells, amplifying inflammasome activation and IL-1β secretion in macrophages. (B) In the absence of nicotine, HIV infection leads to increased OxPhos and ROS in T cells, resulting in ATP release. This activates the NLRP3 inflammasome in macrophages, producing IL-1β. (C) Nicotine treatment in HIV-infected T cells results in a synergistic increase in OxPhos and ROS, leading to higher ATP efflux and exaggerated inflammasome activation in macrophages. The result is a robust production of pro-inflammatory IL-1β, suggesting that nicotine accelerates HIV-associated inflammation and may play a role in maintaining viral latency through chronic immune activation. Abbreviations: OxPhos, oxidative phosphorylation; ROS, reactive oxygen species; ATP, adenosine triphosphate; IL-1β, interleukin-1β; TXN, transcription; NLRP3, NOD-, LRR-, and pyrin domain-containing protein 3. Created with Biorender.