| Literature DB >> 29967602 |
Malika Aid1, Frank P Dupuy2, Eirini Moysi3, Susan Moir4, Elias K Haddad5, Jacob D Estes6, Rafick Pierre Sekaly7, Constantinos Petrovas3, Susan Pereira Ribeiro7.
Abstract
Effective antiretroviral therapy (ART) has prevented the progression to AIDS and reduced HIV-related morbidities and mortality for the majority of infected individuals. However, a lifelong administration of ART is necessary, placing an inordinate burden on individuals and public health systems. Therefore, discovering therapeutic regimens able to eradicate or functionally cure HIV infection is of great importance. ART interruption leads to viral rebound highlighting the establishment and maintenance of a latent viral reservoir compartment even under long-term treatment. Follicular helper CD4 T cells (TFH) have been reported as a major cell compartment contributing to viral persistence, consequent to their susceptibility to infection and ability to release replication-competent new virions. Here, we discuss the molecular profiles and potential mechanisms that support the role of TFH cells as one of the major HIV reservoirs.Entities:
Keywords: HIV; TFH cell; cure; gene expression; lymph nodes
Mesh:
Substances:
Year: 2018 PMID: 29967602 PMCID: PMC6015877 DOI: 10.3389/fimmu.2018.00895
Source DB: PubMed Journal: Front Immunol ISSN: 1664-3224 Impact factor: 7.561
Figure 1(A) Main areas of a tonsillar follicle defined by IgD (yellow), CD20 (cyan), and Ki67 (magenta) are shown: marginal zone (IgDhlCD20dim), germinal center light zone (IgDnegsCD20hiKi67hi/lo) and dark zone (IgDnegPCD20dimKi67hi). The distribution of CD4 T cells (purple) is shown in the lower image. (B) Differential gene expression analysis was performed using Limma model by comparing sorted TFH cells (CXCRShigh) vs. Non-TFH (CXCR5low) from eight HIV- donors in LNs. A corrected p-value cutoff of 0.05 (BH method) was used to select significant upregulated genes (731 genes) in CXCR5high vs. CXCR5low TFH cells. Linear regression model to correlate these genes to viral load in a cohort of HIV viremic subjects (10 viremic subjects) was performed in R. Heatmap shows the log2 normalized expression of each gene transformed to z-score where the average expression of each gene was subtracted and divided by its SD across samples. Genes that correlated significantly to viral load (p-value <0.05) were shown on the heatmap. (C) Pathways enrichment analysis using genes in panel (B) and a compiled set of pathways from MsigDB C2 collection (http://software.broadinstitute.org/gsea/msigdb/collections.jsp#C2) and pathways from Chaussabel et al. (16) was performed. A FDR cutoff of 0.05 was used to selected pathways significantly correlated to viral loads. Interferon, metabolism, T cell activation and differentiation, apoptosis, and chromatin regulators were enriched. Cytoscape was used to infer gene-interacting networks of the leading genes of these pathways. Yellow nodes represent pathways name, red nodes represent genes shared by more than three pathways, orange nodes represent genes shared by two pathways, and white nodes represent genes specific to each pathway.
Figure 2(A) BCL-6 target genes are enriched in genes from interferon, metabolism, T cell activation and differentiation, cell cycle, and chromatin regulators pathways. A linear regression model to correlate BCL-6 targets to viral load, integrated DNA, and inducible RNA (TILDA) from a cohort of viremic subjects was performed using R. BCL-6 targets correlated significantly to viral load, integrated DNA and TILDA (p-value <0.05) were used to infer a gene-interacting network using Cytoscape. Yellow nodes represent BCL-6 targets correlated respectively to intDNA, TILDA, and viral loads. Red nodes represent genes correlated to viral load, integrated DNA, and TILDA, orange nodes represent genes correlated to two pathways and white nodes represent genes specific to each outcome. Circles color depict the different molecular functions enriched in these genes; (B) downregulation of restriction factors and genes involved in interferon type 1 signaling in CXCRShigh vs. CXCR5low cells from TFH cells from HIV− donors in LNs. Heatmap representing the gene log2-fold change expression ranging from blue ( down regulation) to red ( upregulation).