Single-cell transcriptomics identifies prothymosin α restriction of HIV-1 in vivo

Abstract

Host restriction factors play key roles in innate antiviral defense, but it remains poorly understood which of them restricts HIV-1 in vivo. Here, we used single-cell transcriptomic analysis to identify host factors associated with HIV-1 control during acute infection by correlating host gene expression with viral RNA abundance within individual cells. Wide sequencing of cells from one participant with the highest plasma viral load revealed that intracellular viral RNA transcription correlates inversely with expression of the gene PTMA, which encodes prothymosin α. This association was genome-wide significant (P_adjusted < 0.05) and was validated in 28 additional participants from Thailand and the Americas with HIV-1 CRF01_AE and subtype B infections, respectively. Overexpression of prothymosin α in vitro confirmed that this cellular factor inhibits HIV-1 transcription and infectious virus production. Our results identify prothymosin α as a host factor that restricts HIV-1 infection in vivo, which has implications for viral transmission and cure strategies.

Fig. 1.. Longitudinal single-cell multiomics confirm that IFN responses dominate differences between the AHI and ART time points in an acutely treated HIV cohort.

(A) scRNA-seq, TCR sequencing, and plasma proteomics data were generated from samples collected from 14 people living with HIV (PLWH) who initiated treatment during AHI. Data were generated for samples from all 14 participants at two time points, including AHI and ART. Viral RNA phenotypes from single cells within participants and across participants that were used to assess correlations with host gene expression are indicated. Analytical approaches are also shown, and the method used to validate findings in individuals with different VLs and subtypes is highlighted in bold and underlined font. (B) Unsupervised clustering of single-cell transcriptomic phenotypes from the 14 PLWH who were treated during acute infection at two time points (AHI and ART). HSC, hematopoietic stem cell; mDC, myeloid dendritic cells; NK, natural killer; pDC, plasmacytoid DC. (C) DEGs between the two time points from the scRNA-seq dataset showing significant ISGs as red symbols. Gray dashed line indicates genes up-regulated more than 25-fold. (D) Differentially enriched protein pathways between the two time points from the plasma proteomics datasets. Significant results [false discovery rate (FDR) < 0.05] are shown with an asterisk. (E) Differences in TCR expansion between the two time points. Clone size indicates the number of cells in which the same TCR was detected.

Fig. 2.. HIV-1 vRNA transcripts identified during AHI span full viral transcriptomes and correlate with clinical parameters.

(A) High dimensionality reduction plot of single cells from PBMCs showing high viral reads mainly in the memory CD4⁺ T cell cluster in 14 participants at both AHI and ART time points. (B) For the PBMC clusters determined in (A), the expression of host genes identifying these populations is shown, as well as the number of cells with ≥10 HIV-1 transcripts. (C) Three representative cells of viral transcripts were mapped to the HIV-1 genome, showing detection of both full-length virus and active splicing. Gray bars represent coverage of viral sequences from three individual cells, colored bars in these coverage tracks represent single-nucleotide changes from the reference sequence, and colored arches show splicing events. Donor and acceptor splice sites and gene annotation of the HIV-1 reference genome are shown as separate tracks. (D) Frequency of vRNA⁺ cells (%) in memory CD4⁺ T cells is shown for each participant during AHI and ART time points. (E) Correlation of frequencies of vRNA⁺ CD4⁺ or memory CD4⁺ T cells obtained from scRNA-seq (red font) with significant clinical parameters (*P < 0.05, **P < 0.01, and ***P < 0.001).

Fig. 3.. Host and TCR diversity in memory CD4⁺ T cells with viral transcripts.

(A) Clustering based on scRNA-seq host transcriptomes of memory CD4⁺ T cells from one donor identifies four distinct subpopulations. (B) For each cluster in (A), the total number of cells, as well as the number and percentage of cells with viral transcripts, is shown. (C) Gene expression values are plotted for the top DEGs discriminating the four memory CD4⁺ T cell clusters (***P < 0.001 and ****P < 0.0001). (D) Proportion of expanded TCR clonotypes in the four clusters. Bar widths reflect the number of cells in each cluster. Clone size indicates the number of cells in which the same TCR was detected. (E) Categorical DEGs performed between cells with and without viral transcript in memory CD4⁺ T cells from all four clusters. Statistical significance and fold change are displayed as a volcano plot, with Bonferroni significant genes indicated in blue (vRNA⁻ direction) or red (vRNA⁺ direction). Black dots are nominally significant genes. (F) Violin plots showing the expression of some top DEGs from the categorical analysis (all adjusted P < 0.05; ****P < 0.0001). (G and H) The top 100 DEGs shown in (E) were used in pathway analysis identifying associations with the presence of viral transcripts in memory CD4⁺ T cells (G) and preranked GSEA based on fold change of the genes (H). Pathways in (G) are shown in different colored font representing their source, including Gene Ontology (GO) terms (green), Canonical Pathways (gray), Reactome (blue), WikiPathways (pink), and Kyoto Encyclopedia of Genes and Genomes (KEGG) (brown). In (H) are the top five significant gene sets in both directions. NES, normalized enrichment score. (I) Leading edge analysis with the 10 gene sets from (H).

Fig. 4.. Individual cell and participant-specific PTMA expression at AHI and ART associate with decreased vRNA transcripts identified in memory CD4⁺ T cells at the single-cell resolution.

(A) Correlation of PTMA with abundance of vRNA detected in the same individual memory CD4⁺ T cells from participant 0059. The color of the dots indicates degree of significance for each gene at P < 0.05: green, nominal; purple, FDR; pink, Bonferroni. Gray dots denote genes with absolute log fold change (logFC) of <0.01. (B and C) Correlation of PTMA with abundance of vRNA detected in sorted memory CD4⁺ T cells from each of two additional participants, participant 2 (B) and participant 3 (C), with samples at peak viremia and with high viral loads. (D and E) Similarly, correlation of PTMA with intracellular vRNA counts from the same single cells in a combined analysis of cells from different participants with varying viral loads from 6 participants infected with HIV-1 subtype B (D) and 21 participants of whom most were infected with subtype CRF01_AE (E). For (A) to (E), the horizontal bars in the violin plots indicate median normalized expression of PTMA. (F and G) Correlation of frequency of vRNA⁺ memory CD4⁺ T cells at the AHI time point and participant-specific PTMA expression at the ART time point in 21 individuals from whom longitudinal data were available (F) or among the 7 participants having gene expression at three longitudinal time points, including preinfection, AHI, and ART (G).

Fig. 5.. PTMA overexpression inhibits transcription of HIV-1 in vitro.

(A) Proviral HIV-1 constructs and increasing amounts of a plasmid expressing PTMA (fivefold incremental change ranging from 0.0016 to 1 μg) were cotransfected into HEK293T cells. Infectious virus yield was measured using the TZM-bl reporter cell infectivity assay. The top panel shows absolute infectivity, and the lower panel shows values normalized to the infectious virus yield obtained in the absence of PTMA overexpression (100%). (B and C) p24 antigen measured by ELISA (B) and normalized infectivity produced by HEK293T cells (C) were measured in the presence of increasing quantities of PTMA. (D) Expression of HIV-1 proteins, PTMA, and GAPDH in viral particles (Sups.) or cellular extracts (Cells) was determined by Western blot. (E) Abundance of viral transcripts determined by qRT-PCR in multiplex reactions with GAPDH as control. Bar diagrams show mean values (±SEM) derived from three or four independent experiments performed in technical triplicates. *P < 0.05, **P < 0.01, and ***P < 0.001.