We ran the ATAC-Seq data through a pipeline that includes, peak calling and differential peak analysis

We ran the ATAC-Seq data through a pipeline that includes, peak calling and differential peak analysis. partly due to virus persistence in immune sanctuary sites such as germinal centres within lymph node (LN) tissues. Recent evidence suggests that LNs harbour a novel subset of regulatory T cells, termed follicular regulatory T cells (TFRs), but their role in HIV pathogenesis is not fully elucidated. Results Paired excisional LN and peripheral blood samples obtained from 20 HIV-uninfected and 31 HIV-infected treated and 7 chronic untreated, were used to determine if and how HIV infection modulate frequencies, function and spatial localization of TFRs within LN tissues. Imaging studies showed that most TFRs are localized in extra-follicular regions. Co-culture assays showed TFRs suppression of TFH help to B cells. Importantly, epigenetic and transcriptional studies identified DPP4 and FCRL3 as novel phenotypic Abacavir markers that define four functionally distinct TFR subpopulations in human LNs regardless of HIV status. Imaging studies confirmed the regulatory phenotype of DPP4+TFRs. Conclusion Together these studies describe TFRs dynamic changes during HIV infection and reveal previously underappreciated TFR heterogeneity within human LNs. Supplementary Information The online version contains supplementary material available at 10.1186/s12865-022-00508-1. values were determined using MannCWhitney U test. values were determined using MannCWhitney U test Transcriptomic definition of TFRs and TFH cells Abacavir Given the reported overlap between TFR and TFH in terms of phenotype and functions [30C32], we next investigated their transcriptomic differences. We performed RNA-seq on 7 biological replicates of FACs-sorted TFRs and TFH cells obtained from 4 HIV-infected and 3 healthy donors (Additional file 5). RNA was extracted from sorted TFRs and TFH cells and subjected to high-throughput sequencing. Principal component analysis (PCA) segregated TFRs from TFH cells showing 38.75% of the variance in principal component 1 [PC1] (Fig.?4A). Next, we generated a list of differentially expressed (DE) genes between TFRs and TFH cells. Differential expression analysis was performed using Sleuth [33] and genes with Abacavir false discovery rate (FDR)? ?0.05 and 1.5-fold change were considered to be differentially expressed. We identified 904 DE genes, of which 229 genes were up-regulated and 675 down-regulated in TFRs relative to TFH cells (Additional file 6). We next generated a volcano plot highlighting the top 40 TFRs up-regulated and top 40 TFH up-regulated (TFR down-regulated) genes (Fig.?4B). GBP5 was the most DE gene between TFH and TFRs (Fig.?5B), followed by Rabbit Polyclonal to GIT1 IL2RA, a signature marker of regulatory T cells, HAPLN3 and FCLR3 (Fig.?4B). The DE genes were further grouped into two major groups: surface Abacavir molecules (Fig.?4C) and transcription factors (Fig.?4D). We then looked at the expression of lineage-defining markers and found both TFHs and TFRs displayed the expected expression pattern of signature markers such as high CXCR5 and IL2RA, respectively. As expected, costimulatory molecules such as CD40L and ICOS involved in B-T cell cooperation were highly expressed by TFH cells. Open in a separate window Fig. 4 Transcriptomic definition of TFRs and TFH cells. A PCA plot of gene expression data of TFR and TFH cells. B Volcano plot depicting genes differentially expressed genes between TFRs and TFH cells, highlighting top 40 genes. Each colored dot denotes an individual gene passing our value and fold difference thresholds, grey dots represent the genes below the selected threshold (0.05). Heatmap of TFR and TFH cells representing differentially expressed C surface molecules and D Transcription factors. E RNA-Seq WGCNA modules. The colors represent each module. WGCNA functional enrichment with hub genes for TFRs F and G TFH cells Open in a separate window Fig. 5 Epigenomic definition of TFRs and TFH cells. A Experimental design for ATAC-Seq and RNA-Seq experiments. B PCA plot of ATAC-Seq signal in TFRs and TFH cells. The top 10% of ATAC-Seq peaks (merged between subsets) by variance were used to create the PCA plot. Differential accessibility of canonical TFRs and TFH genes C FOXP3 D IL-21 and novel genes E FRL3 F DPP4 To identify dominant signalling pathways for each subset, we performed Weighted Gene Correlated Network Analysis (WGCNA) [34] on our RNA-Seq data set. WGCNA is a network analysis that is used to identify modules (clusters) of highly co-expressed genes. It assigns colours to each module as an identification mark. TFR genes were highly enriched in the saddlebrown module, whereas TFH genes were mostly enriched in the black module (Fig.?4E). To investigate Abacavir the putative functions associated with each module, all the identified modules were subjected to functional enrichment analysis. Functional enrichment analysis of the saddlebrown module demonstrated tolerance induction, negative regulation of leukocytes and lymphocytes proliferation, negative regulation of leukocyte cell-to-cell adhesion and production of cytokines involved immune responses (Fig.?4F). Of note was.