Additional file 1 of Neuroinflammatory transcriptional programs induced in rhesus pre-frontal cortex white matter during acute SHIV infection

Additional file 1: Fig. S1. Ranked genes by median normalized read counts in units of Log2 counts per million (Log2CPM) in the subcortical white matter of the pre-frontal cortex (PFCw), and gray matter of the superior temporal sulcus (STS), caudate nucleus (CN), and hippocampus (HP) of uninfected animals. Dotted lines indicate location of marker genes associated with neurons (MAP2), astrocytes (GFAP), microglia (P2RY12), and oligodendrocytes (MOG) within ranked distribution. Fig. S2. T-stochastic neighborhood embedding analysis (t-SNE) of gene expression profiles from the pre-frontal cortex white matter (black), superior temporal sulcus (blue), caudate nucleus (red), and hippocampus (green) of uninfected animals. Outlier sample [Animal 43661 pre-frontal cortex white matter] is included. Symbols represent individual animals. Circles indicate 95% confidence intervals. Fig. S3. Regional eigengene expression and corresponding top fifteen most significantly enriched (p < 0.01 by Fisher’s exact test) biological processes GO terms within region specific modules (PFCw-specific [MEmagenta, MEmidnightblue], STS-specific [MEtan], CN-specific [MEpurple, MEred], HP-specific [MEsalmon]) determined by weighted gene co-expression network analysis from uninfected animals. *p < 0.05 by linear mixed effects model (region effect). Boxplots represent quartiles. Fig. S4. Normalized read counts of genes encoding for chemokines in the STS (blue), PFCw (black), CN (red), and HP (green) of uninfected animals. Expression levels are displayed in normalized read counts in units of Log2 counts per million (Log2CPM). Brackets indicate structural chemokine classes. Fig. S5. Log2 Fold change of genes regulating inflammatory processes and synaptic functions between SHIV infected and uninfected animals in all brain regions (gray), STS (blue), and PFCw (red). Dotted line indicates a fold change of 1. Fig. S6. T-stochastic neighborhood embedding (t-SNE) analysis of gene expression profiles from SHIV infected and uninfected animals. (Left) t-SNE plot indicates clustering of gene expression profiles by region and SHIV infection status (SHIV infected [pink], uninfected [black]) with removal of outlier sample [Animal 43661 Pre-frontal cortex white matter]. (Right) t-SNE plot shows all samples including the outlier with data points indicating regions (pre-frontal cortex white matter (P), superior temporal sulcus [S], caudate nucleus [C], hippocampus [H]) and infection status (color) and individual animals (symbols). Circles indicate 95% confidence intervals. Fig. S7 Expression levels of genes (expressed as normalized read counts in units of Log2 Counts per million [CPM]) related to synaptic functions, endoplasmic reticulum stress, and ATP synthase subunits in the PFCw of SHIV infected (red) and uninfected (gray) animals. Violin plots indicate quartiles. P values determined by linear mixed effects model. Table S1 Animal/Sample Data. Animal information—Animal ID, Sex, Age, SHIV infection status, and medical cull rationale. Sample Information—Sample ID, Sample Code, Tissue identity, Tissue weight (mg), purified RNA absorbance ratios (A260/A280 and A260/A230), and sample RNA yield. Table S3. Reagents used for flow cytometric analysis

Additional file 2 of Neuroinflammatory transcriptional programs induced in rhesus pre-frontal cortex white matter during acute SHIV infection

Additional file 2: Table S2. Normalized Read Counts. Normalized read counts in units of Log2 Counts per Million (CPM). Sample IDs are listed in row 1 and correspond to Code in Table S1. Corresponding Gene.stable.ID and Gene names are listed in columns 1 and 2

SIVRNA localizes with immune clusters in brain and spleen.

(A) Genes enriched in TEM and TCM clusters in control and SIV brain (p.adj B) UMAP of immune clusters in brain and vRNA expression in clusters in control and SIV. (C) UMAP of immune clusters in spleen and vRNA expression in clusters in control and SIV. Acute 251 (n = 4) cohort assessed. (TIF)</p

CSF CCR5+ CD8 T cell frequencies do not decrease during acute SIV infection.

shows % CD8 T cells, % CD28- CD95+ CD8 T cells, �R5+ CD8 T cells, and % CD69+ CD8 T cells in CSF in Chronic 251 cohort (n = 6). Significant differences by one-tailed Wilcoxon matched-pairs signed rank test, *, p (TIFF)</p

T cell effector molecular programs induced within the SIV-Infected brain.

Differential gene expression (DGE) analysis of the immune clusters across conditions was performed using functions from Seurat; selection threshold of (adjusted p-value  0.25) based on Benjamini-Hochberg correction. (A) Heat map of DGE genes in controls (C) versus SIV for each immune cluster. (B) Venn diagram shows shared interferon stimulated genes upregulated post SIV across brain and spleen CD4 T cell and monocyte/macrophage immune clusters. (C) Chord plot show pathways and corresponding genes enriched in SIV versus control CD4 TCM cell cluster in brain. (D) Venn diagram shows shared genes downregulated post SIV in brain and spleen CD4 T cell clusters. We used the monocle3 based workflow to estimate lineage differentiation between the cell populations based on the experimental conditions. We extracted the subsets of identified cell types from our integrated Seurat object and further inferred the trajectory graphs. Using the defined root node (TCM), we chose lineages based on the shortest path connecting the root node and the leaf node. After establishing different lineages, we implemented a differential gene test to find genes that changed as a function of pseudotime based on a combination of Moran’s statistic and q-value and visualized using heatmaps and individual gene trajectory plots. (E) Heatmap (Lineage 3) shows changes in gene expression in lineage comprising of T cells. Along this trajectory was induction of genes associated with cell cycle progression (TK1, MKI67, EIF1, S100A10, S100A4), immune cell activation and differentiation (ZEB2, KLF2, CD52) [41], cytotoxic function (PFN1, GZMB, GZMH, NKG7, and CST7). Canonical TCM genes, such as IL7R and LTB, were downregulated in this lineage. (F) shows expression levels genes of select genes from heat map (ZEB2, LTB, GZMB) along pseudo-time as a function of infection. Schematics were generated using BioRender.</p

Gating strategy for CNS tissues in SIV unexposed controls.

Gating strategy for CNS tissues in SIV unexposed controls.</p

Decrease in vRNA in brain during antiretroviral therapy.

(A) Chronic 251 cohort (n = 6) assessed. (B) Kinetics of plasma (red lines) and CSF (blue lines) viral suppression and rebound (vRNA copies/mL fluid, measured by RT-qPCR) over the course of ART initiation and interruption. Green bars indicate periods of ART with FTC, TDF, and DTG. Horizontal dashed line indicates limit of detection (15 vRNA copies/ml). (C) Concentration of ARVs (ng/mL) in plasma and CSF quantified by LC-MS. (D) Concentration of ARVs (ng/mg) in PFC and colonic tissue. (E) shows active phosphorylated forms of TFV and FTC. Spearman correlation, two-tailed p value shown. Sampling was performed 2–4 weeks post ART initiation with last ARV dose administered 9–12 hours prior to necropsy, FTC = emtricitabine, TDF = tenofovir disoproxil fumarate, DTG = dolutegravir, Gray shaded area represents lower limit of quantification of assay. (F) SIV vRNA (G) SIV vDNA (copies/10^6 cells) in brain region (RT-qPCR on post-mortem punch biopsies from specified regions. Gray shaded area represents viral loads below threshold of detection. Significant differences by two tailed Wilcoxon matched-pairs signed rank test, * p< 0.05 in C-E. Schematics were generated using BioRender.</p

T cell clusters within SIV-Infected brain.

(A) Schematic of single cell profiling of CD45+ cells in brain (n = 4 Acute 251 cohort, n = 2 Control cohort 1). Sequence alignment to M.mulatta (Mmul_10) reference using 10X Genomics protocol (CellRanger V.6.0) was performed. The generated cell-by-gene count matrix was used for downstream analysis using the Seurat based integrative analysis workflow. The filtered count matrix (percentage of mitochondrial reads B) UMAP of scRNA-seq transcriptional profiles from brain shows 6 clusters. Cell clusters are color-coded based on cell types. Cluster identity was assigned by a combination of approaches—cluster-specific differentially expressed genes, expert knowledge, canonical list of marker genes, and automated annotations using immune reference atlas through SingleR. Inset shows cell proportions in each cluster by experimental group. (C) Dot plot of select marker gene expression. Dot size represents proportion of cells expressing gene and color designates expression level. To quantify viral transcripts, we designed a custom reference using CellRanger mkref pipeline. We integrated FASTA and GTF files of SIVmac251 into M. mulatta (Mmul_10) genome references. This tailored reference facilitated downstream analysis by including viral transcripts in the count matrix. UMAP of SIV RNA expression in cell clusters (SIV RNA+ cell size increased for clarity) in (D) brain and (E) spleen. Number of cells from each cluster positive for vRNA provided. After filtering cells expressing SIV transcript above a threshold 1, %SIV+ for CD4 T cells was determined by dividing the count of the SIV transcript by the total gene count (inset). (F) shows SIV RNA in parenchyma and perivascular regions of the brain using ISH with probe against SIV RNA. SIV RNA+ (green) CD3+ T cells (red) with nucleus (DAPI, blue) in PFC; box (CD3+ SIV+ cell). Schematics were generated using BioRender.</p

Plasma and CSF vRNA in Chronic 251 cohort.

Virologic suppression with antiretroviral therapy (ART) has significantly improved health outcomes for people living with HIV, yet challenges related to chronic inflammation in the central nervous system (CNS)—known as Neuro-HIV- persist. As primary targets for HIV-1 with the ability to survey and populate the CNS and interact with myeloid cells to co-ordinate neuroinflammation, CD4 T cells are pivotal in Neuro-HIV. Despite their importance, our understanding of CD4 T cell distribution in virus-targeted CNS tissues, their response to infection, and potential recovery following initiation of ART remain limited. To address these gaps, we studied ten SIVmac251-infected rhesus macaques using an ART regimen simulating suboptimal adherence. We evaluated four macaques during the acute phase pre-ART and six during the chronic phase. Our data revealed that HIV target CCR5+ CD4 T cells inhabit both the brain parenchyma and adjacent CNS tissues, encompassing choroid plexus stroma, dura mater, and the skull bone marrow. Aligning with the known susceptibility of CCR5+ CD4 T cells to viral infection and their presence within the CNS, high levels of viral RNA were detected in the brain parenchyma and its border tissues during acute SIV infection. Single-cell RNA sequencing of CD45+ cells from the brain revealed colocalization of viral transcripts within CD4 clusters and significant activation of antiviral molecules and specific effector programs within T cells, indicating CNS CD4 T cell engagement during infection. Acute infection led to marked imbalance in the CNS CD4/CD8 ratio which persisted into the chronic phase. These observations underscore the functional involvement of CD4 T cells within the CNS during SIV infection, enhancing our understanding of their role in establishing CNS viral presence. Our findings offer insights for potential T cell-focused interventions while underscoring the challenges in eradicating HIV from the CNS, particularly in the context of sub-optimal ART.</div

Persistent CD4 depletion in CNS during chronic infection.

(A) Chronic 251 cohort assessed; flow cytometry analysis performed on 4/6 animals. (B) Flow cytometry plots illustrate frequencies of CD4 and CD8 T cells in blood, CNS tissues, and dCLN. (C) Bar graphs show T cell frequencies across blood, CNS tissues, and dCLN in control and Chronic SIV infected macaques (n = 4, plasma viral RNA+ shown in star symbols). (D) flow plots (top to bottom) show CD4 CD95 cells co-expressing CXCR3 and CCR5; Th1 cells expressing α4β1, and α4β1 Th1 cells expressing CCR5. Bar graphs show frequencies in brain and spleen and pie charts illustrate relative proportion of subsets in brain (n = 4). (E) Contingency plots show distribution of CCR5 / CCR7 CD4 T cells in chronic SIV infection (n = 3 based on criterion of CD4 events > 100 in all CNS tissues). (F) t-SNE plots gated on CD4+CD95+ cells expressing CCR7/CCR5/PD-1/CD69 (n = 3). (G) pie chart demonstrates proportion of CD4 T cells expressing combination of markers (CCR7/CCR5/PD-1/CD69). (H) shows distribution of specific subsets. Significant differences by one tailed Mann Whitney test, *, p< 0.05. Schematics were generated using BioRender.</p