Lipophosphoglycan from Leishmania suppresses agonist-induced interleukin 1β gene expression in human monocytes via a unique promoter sequence

Leishmania are parasites that survive within macrophages by mechanism(s) not entirely known. Depression of cellular immunity and diminished production of interleukin 1β (IL-1β) and tumor necrosis factor α are potential ways by which the parasite survives within macrophages. We examined the mechanism(s) by which lipophosphoglycan (LPG), a major glycolipid of Leishmania, perturbs cytokine gene expression. LPG treatment of THP-1 monocytes suppressed endotoxin induction of IL-1β steady-state mRNA by greater than 90%, while having no effect on the expression of a control gene. The addition of LPG 2 h before or 2 h after endotoxin challenge significantly suppressed steady-state IL-1β mRNA by 90% and 70%, respectively. LPG also inhibited tumor necrosis factor α and Staphylococcus induction of IL-1β gene expression. The inhibitory effect of LPG is agonist-specific because LPG did not suppress the induction of IL-1β mRNA by phorbol 12-myristate 13-acetate. A unique DNA sequence located within the −310 to −57 nucleotide region of the IL-1β promoter was found to mediate LPG’s inhibitory activity. The requirement for the −310 to −57 promoter gene sequence for LPG’s effect is demonstrated by the abrogation of LPG’s inhibitory activity by truncation or deletion of the −310 to −57 promoter gene sequence. Furthermore, the minimal IL-1β promoter (positions −310 to +15) mediated LPG’s inhibitory activity with dose and kinetic profiles that were similar to LPG’s suppression of steady-state IL-1β mRNA. These findings delineated a promoter gene sequence that responds to LPG to act as a “gene silencer,” a function, to our knowledge, not previously described. LPG’s inhibitory activity for several mediators of inflammation and the persistence of significant inhibitory activity 2 h after endotoxin challenge suggest that LPG has therapeutic potential and may be exploited for therapy of sepsis, acute respiratory distress syndrome, and autoimmune diseases.

Global analysis of gene expression in pulmonary fibrosis reveals distinct programs regulating lung inflammation and fibrosis

The molecular mechanisms of pulmonary fibrosis are poorly understood. We have used oligonucleotide arrays to analyze the gene expression programs that underlie pulmonary fibrosis in response to bleomycin, a drug that causes lung inflammation and fibrosis, in two strains of susceptible mice (129 and C57BL/6). We then compared the gene expression patterns in these mice with 129 mice carrying a null mutation in the epithelial-restricted integrin β6 subunit (β6−/−), which develop inflammation but are protected from pulmonary fibrosis. Cluster analysis identified two distinct groups of genes involved in the inflammatory and fibrotic responses. Analysis of gene expression at multiple time points after bleomycin administration revealed sequential induction of subsets of genes that characterize each response. The availability of this comprehensive data set should accelerate the development of more effective strategies for intervention at the various stages in the development of fibrotic diseases of the lungs and other organs.

Knowledge-based analysis of microarray gene expression data by using support vector machines

We introduce a method of functionally classifying genes by using gene expression data from DNA microarray hybridization experiments. The method is based on the theory of support vector machines (SVMs). SVMs are considered a supervised computer learning method because they exploit prior knowledge of gene function to identify unknown genes of similar function from expression data. SVMs avoid several problems associated with unsupervised clustering methods, such as hierarchical clustering and self-organizing maps. SVMs have many mathematical features that make them attractive for gene expression analysis, including their flexibility in choosing a similarity function, sparseness of solution when dealing with large data sets, the ability to handle large feature spaces, and the ability to identify outliers. We test several SVMs that use different similarity metrics, as well as some other supervised learning methods, and find that the SVMs best identify sets of genes with a common function using expression data. Finally, we use SVMs to predict functional roles for uncharacterized yeast ORFs based on their expression data.

Generation of longer cDNA fragments from serial analysis of gene expression tags for gene identification

We have developed a technique called the generation of longer cDNA fragments from serial analysis of gene expression (SAGE) tags for gene identification (GLGI), to convert SAGE tags of 10 bases into their corresponding 3′ cDNA fragments covering hundred bases. A primer containing the 10-base SAGE tag is used as the sense primer, and a single base anchored oligo(dT) primer is used as an antisense primer in PCR, together with Pfu DNA polymerase. By using this approach, a cDNA fragment extending from the SAGE tag toward the 3′ end of the corresponding sequence can be generated. Application of the GLGI technique can solve two critical issues in applying the SAGE technique: one is that a longer fragment corresponding to a SAGE tag, which has no match in databases, can be generated for further studies; the other is that the specific fragment corresponding to a SAGE tag can be identified from multiple sequences that match the same SAGE tag. The development of the GLGI method provides several potential applications. First, it provides a strategy for even wider application of the SAGE technique for quantitative analysis of global gene expression. Second, a combined application of SAGE/GLGI can be used to complete the catalogue of the expressed genes in human and in other eukaryotic species. Third, it can be used to identify the 3′ cDNA sequence from any exon within a gene. It can also be used to confirm the reality of exons predicted by bioinformatic tools in genomic sequences. Fourth, a combined application of SAGE/GLGI can be applied to define the 3′ boundary of expressed genes in the genomic sequences in human and in other eukaryotic genomes.

Gene expression, synthesis, and secretion of interleukin 18 and interleukin 1β are differentially regulated in human blood mononuclear cells and mouse spleen cells

Interleukin (IL)-18, formerly called interferon γ (IFN-γ)-inducing factor, is biologically and structurally related to IL-1β. A comparison of gene expression, synthesis, and processing of IL-18 with that of IL-1β was made in human peripheral blood mononuclear cells (PBMCs) and in human whole blood. Similar to IL-1β, the precursor for IL-18 requires processing by caspase 1. In PBMCs, mature but not precursor IL-18 induces IFN-γ; in whole human blood stimulated with endotoxin, inhibition of caspase 1 reduces IFN-γ production by an IL-1β-independent mechanism. Unlike the precursor for IL-1β, precursor for IL-18 was expressed constitutively in PBMCs and in fresh whole blood from healthy human donors. Western blotting of endotoxin-stimulated PBMCs revealed processed IL-1β in the supernatants via an caspase 1-dependent pathway. However, in the same supernatants, only unprocessed precursor IL-18 was found. Unexpectedly, precursor IL-18 was found in freshly obtained PBMCs and constitutive IL-18 gene expression was present in whole blood of healthy donors, whereas constitutive IL-1β gene expression is absent. Similar to human PBMCs, mouse spleen cells also constitutively contained the preformed precursor for IL-18 and expressed steady-state IL-18 mRNA, but there was no IL-1β protein and no spontaneous gene expression for IL-1β in these same preparations. We conclude that although IL-18 and IL-1β are likely members of the same family, constitutive gene expression, synthesis, and processing are different for the two cytokines.

A binding site for homeodomain and Pax proteins is necessary for L1 cell adhesion molecule gene expression by Pax-6 and bone morphogenetic proteins

The cell adhesion molecule L1 regulates axonal guidance and fasciculation during development. We previously identified the regulatory region of the L1 gene and showed that it was sufficient for establishing the neural pattern of L1 expression in transgenic mice. In the present study, we characterize a DNA element within this region called the HPD that contains binding motifs for both homeodomain and Pax proteins and responds to signals from bone morphogenetic proteins (BMPs). An ATTA sequence within the core of the HPD was required for binding to the homeodomain protein Barx2 while a separate paired domain recognition motif was necessary for binding to Pax-6. In cellular transfection experiments, L1-luciferase reporter constructs containing the HPD were activated an average of 4-fold by Pax-6 in N2A cells and 5-fold by BMP-2 and BMP-4 in Ng108 cells. Both of these responses were eliminated on deletion of the HPD from L1 constructs. In transgenic mice, deletion of the HPD from an L1-lacZ reporter resulted in a loss of β-galactosidase expression in the telencephalon and mesencephalon. Collectively, our experiments indicate that the HPD regulates L1 expression in neural tissues via homeodomain and Pax proteins and is likely to be a target of BMP signaling during development.