| Literature DB >> 16384534 |
Eleonora Aricò1, Ena Wang, Maria Lina Tornesello, Maria Tagliamonte, George K Lewis, Francesco M Marincola, Franco M Buonaguro, Luigi Buonaguro.
Abstract
We have recently developed a candidate HIV-1 vaccine model based on HIV-1 Pr55gag Virus-Like Particles (HIV-VLPs), produced in a baculovirus expression system and presenting a gp120 molecule from an Ugandan HIV-1 isolate of the clade A (HIV-VLPAs). The HIV-VLPAs induce in Balb/c mice systemic and mucosal neutralizing Antibodies as well as cytotoxic T lymphocytes, by intra-peritoneal as well as intra-nasal administration. Moreover, we have recently shown that the baculovirus-expressed HIV-VLPs induce maturation and activation of monocyte-derived dendritic cells (MDDCs) which, in turn, produce Th1- and Th2-specific cytokines and stimulate in vitro a primary and secondary response in autologous CD4+ T cells. In the present manuscript, the effects of the baculovirus-expressed HIV-VLPAs on the genomic transcriptional profile of MDDCs obtained from normal healthy donors have been evaluated. The HIV-VLPA stimulation, compared to both PBS and LPS treatment, modulate the expression of genes involved in the morphological and functional changes characterizing the MDDCs activation and maturation. The results of gene profiling analysis here presented are highly informative on the global pattern of gene expression alteration underlying the activation of MDDCs by HIV-VLPAs at the early stages of the immune response and may be extremely helpful for the identification of exclusive activation markers.Entities:
Year: 2005 PMID: 16384534 PMCID: PMC1360684 DOI: 10.1186/1479-5876-3-45
Source DB: PubMed Journal: J Transl Med ISSN: 1479-5876 Impact factor: 5.531
Figure 1Maturation of DCs by baculovirus-expressed HIV-VLPs. Immature MDDCs were incubated in the presence of the indicated stimulus for 16 hours. The expression of CD80, CD83, CD86 and HLA-DR was analyzed on fixed cells by FACScalibur flow cytometer and data analysis was carried out with FlowJo software. The results of a representative experiment are shown; the shadowed curve represents the untreated cells.
Figure 2Unsupervised hierarchical clustering of all filtered data. The clusterogram represents 3,119 genes obtained by Eisen hierarchical clustering of the complete 17K dataset filtered for genes that are expressed in a minimum of 80% of the samples 4 and 8 h after HIV-VLPs or LPS stimulation. The PBS treatments was evaluated after 8 h of stimulation. The clustering is defined by the dendrogram and each treatment/time point is represented by a single branch.
Figure 3Pattern of gene expression in human monocyte-derived DCs. Regulated genes by HIV-VLPs or LPS treatment in MDDCs, showing at least a 2-fold modulation (up or downregulation), have been evaluated. Each circle represents the whole set of genes identified in the indicated comparisons, based on the 2-fold modulation parameter. Numbers in overlapping regions represent common regulated genes. Numbers in non-overlapping regions represent unique regulated genes. Circles are drawn in arbitrary scale.
Figure 4Supervised hierarchical clustering of genes differentially expressed in HIV-VLP-treated MDDCs. The clusterograms represent an Eisen hierarchical clustering of the 281 genes differentially expressed (p < 0.005) in HIV-VLPs-treated MDDCs, compared to PBS treatment (A), and of 217 genes differentially expressed (p < 0.005) in HIV-VLPs-treated MDDCs, compared to LPS treatment (B). The clustering is defined by the dendrogram on the top and on the side of the clusterogram.
Figure 5Supervised hierarchical clustering of genes upregulated by HIV-VLPs in MDDCs. 3,119 genes included in this analysis were filtered upon the criteria of showing less than 20% missing data and a minimum of 3-fold modulation in expression. The expanded section shows nodes including genes upregulated by HIV-VLPs. Individual genes are indicated on the right.
Pathways involved in the HIV-VLPs-activated MDDCs. The pathways are derived from the BioCarta through the Cancer Genome Anatomy Project at . Genes with at least a 2-fold modulation (up or downregulation) have been taken into consideration. Upregulated genes in bold and underline; Downregulated genes in plain text.
| Cadmium induces DNA synthesis and proliferation in macrophages | Acetylation and Deacetylation of RelA in The Nucleus | AKT Signaling Pathway | ||||||
| Caspase Cascade in Apoptosis | Activation of PKC through G protein coupled receptor | B Lymphocyte Cell Surface Molecules | ||||||
| Free Radical Induced Apoptosis | Chaperones modulate interferon Signaling Pathway | CD40L Signaling Pathway | ||||||
| Induction of apoptosis through DR3 and DR4/5 Death Receptors | Double Stranded RNA Induced Gene Expression | CTL mediated immune response against target cells | ||||||
| Neuropeptides VIP and PACAP inhibit the apoptosis of activated T cells | Human Cytomegalovirus and Map Kinase Pathways | fMLP induced chemokine gene expression in HMC-1 cells | ||||||
| Regulation of BAD phosphorylation | NFkB activation by Nontypeable Hemophilus influenzae | Monocyte and its Surface Molecules | ||||||
| Role of Mitochondria in Apoptotic Signaling | NF-kB Signaling Pathway | T Cytotoxic Cell Surface Molecules | ||||||
| SODD/TNFR1 Signaling Pathway | Signal transduction through IL1R | T Helper Cell Surface Molecules | ||||||
| Stress Induction of HSP Regulation | CASP9 | TNFR1 Signaling Pathway | The 4-1BB-dependent immune response | |||||
| TNF/Stress Related Signaling | TNFR2 Signaling Pathway | Toll-Like Receptor Pathway | ||||||
| Cells and Molecules involved in local acute inflammatory response | Instracellular protein transport | APG9L1 | ||||||
| Cytokine Network | ||||||||
| Cytokines and Inflammatory Response | Cellular motiliyshape | |||||||
| IL 17 Signaling Pathway | ||||||||
| Th1/Th2 Differentiation | ||||||||
Functional categories of genes differentially upregulated in HIV-VLPs-induced MDDCs. (+) 1.5-fold upregulation; (++) 2–5-fold upregulation; (+++) >5-fold upregulation.
| Pathway | HIV-VLP vs PBS | HIV-VLP vs LPS | Pathway | HIV-VLP vs PBS | HIV-VLP vs LPS |
| TNF | ++ | + | |||
| BIRC3 | ++ | IL8 | +++ | ++ | |
| CASP7 | + | CXCL1 | ++ | ++ | |
| BID | ++ | IL1a | ++ | ++ | |
| PAK2 | ++ | IL1b | ++ | ||
| TRAF2 | ++ | IL6 | ++ | ||
| BCL2L1 | + | CCL4 | ++ | ||
| IGF1R | ++ | IFNG | + | ||
| TNFAIP3 | ++ | PTGER4 | |||
| TANK | ++ | ||||
| PSEN1 | + | EBI2 | ++ | ||
| TNFRSF1B | +++ | + | ICAM1 | ++ | |
| B2M | + | ||||
| NFKB1 | + | ||||
| NFKBIA | ++ | IL15RA | ++ | ||
| IRAK1 | + | IL18R1 | ++ | ||
| MAP3K1 | + | IL23A | ++ | ||
| JUNB | + | IL2RB | ++ | ||
| FCGR2A | ++ | ||||
| MAP2K7IP2 | + | IL7R | ++ | ||
| DUSP1 | ++ | + | CD83 | ++ | |
| MAP2K3 | + | ||||
| PAK2 | ++ | CSF1 | ++ | ||
| RB1 | + | CSF2 | + | ||
| FOXO3A | + | ||||
| FYN | + | CCR7 | + | ||
| GNAQ | + | FPR1 | ++ | ||
| MEF2A | + | SELE | ++ | ||
| RAPGEF2 | + | CD44 | ++ | ||
| LTBR | + | ||||
| CD40 | ++ | ||||
| TNFSF9 | + | ||||
| IL18 | + | ||||