Virus-specific CD8+ T lymphocytes within the normal human liver

The frequency and phenotype of human antiviral memory CD8(+) T cells in blood are well studied, yet little is known about their distribution within tissues. Analysis of antiviral CD8(+) T cell populations derived from a unique set of normal liver and blood samples identified a consistent population of virus-specific cells within the liver. In comparison to the circulating T cells, the liver-derived T cells were present at frequencies which were variably enriched compared to that in the blood, and showed significant differences with regard to the expression of CD45RA, CD45RO, CD95, CCR7, CD27 and CD28. The differences in these cell surface markers are consistent with a mature 'effector memory' phenotype of antigen-specific CD8(+) T cells within the liver. An enrichment of an activated subset of NKT cells (Valpha24/Vbeta11) was also observed, a finding which may be relevant to the regulation of the antiviral population:.

Regulatory T-cells infiltrate periodontal disease tissues

CD4(+) CD25(+) regulatory T ( Tr) cells are critical in regulating the immune response and thereby play an important role in the defense against infection and control of autoimmune diseases. Our previous studies demonstrated the involvement of autoimmune responses in periodontitis. The aim of this study was to identify CD4(+) CD25(+) Tr cells in periodontitis tissues and compare them with those in gingivitis tissues. Immunohistological analysis of CD4, CD25, and CTLA- 4 and the gene expression analysis of FOXP3, TGF- beta 1, and IL-10 on gingival biopsies revealed the presence of CD4(+) CD25(+) Tr cells in all tissues. In periodontitis, the percentage of CD4(+) CD25(+) Tr cells increased with increasing proportions of B-cells relative to T- cells. FOXP3, a characteristic marker for CD4(+) CD25(+) Tr cells, TGF- beta 1 and IL-10 were expressed more highly in periodontitis compared with gingivitis. These findings suggest that CD4(+) CD25(+) Tr cells and possibly other regulatory T- cell populations do exist and may play regulatory roles in periodontal diseases.

In vitro and in silico analysis of signal peptides from the human blood fluke, Schistosoma mansoni

Proteins secreted by and anchored on the surfaces of parasites are in intimate contact with host tissues. The transcriptome of infective cercariae of the blood fluke, Schistosoma mansoni, was screened using signal sequence trap to isolate cDNAs encoding predicted proteins with an N-terminal signal peptide. Twenty cDNA fragments were identified, most of which contained predicted signal peptides or transmembrane regions, including a novel putative seven-transmembrane receptor and a membrane-associated mitogen-activated protein kinase. The developmental expression pattern within different life-cycle stages ranged from ubiquitous to a transcript that was highly upregulated in the cercaria. A bioinformatics-based comparison of 100 signal peptides from each of schistosomes, humans, a parasitic nematode and Escherichia coli showed that differences in the sequence composition of signal peptides, notably the residues flanking the predicted cleavage site, might account for the negative bias exhibited in the processing of schistosome signal peptides in mammalian cells. (c) 2005 Federation of European Microbiological Societies. Published by Elsevier B.V. All rights reserved.

Analysis of distinct tartrate-resistant acid phosphatase promoter regions in transgenic mice

The tartrate-resistant acid phosphatase (TRAP) is present in multiple tissues, including kidney, liver, lung, spleen, and bone. Recent study of (TRAP) gene expression has provided evidence for distinct promoters within the (TRAP) gene, suggesting that the gene has alternative, tissue-preferred mRNA transcripts. Examination of endogenous (TRAP) exon 1B and 1C mRNA transcripts revealed tissue-preferred transcript abundance with increased exon 1B transcripts detected in liver and kidney and increased exon 1C transcripts detected in bone and spleen. In this investigation, we have made transgenic mice that express a marker gene driven by two candidate promoters, designated BC and C, within the (TRAP) gene. The BC and C promoters are 2.2 and 1.6 kb, respectively, measured from the translation initiation site. Evaluation of BC transgenic lines demonstrated robust expression in multiple tissues. In contrast, significant transgene expression was not detected in C transgenic lines. Evaluation of transgene mRNAs in BC transgenic lines revealed that virtually all expression was in the form of B transcripts, suggesting that the tissue-preferred pattern of endogenous (TRAP) was not replicated in the BC transgenic line. Likewise, osteoclastogenic cultures from BC, but not C, transgenic bone marrow cells expressed the transgene following receptor activator of NFkappaB ligand/macrophage colony-stimulating factor stimulation. In conclusion, when compared with the 2.2-kb BC portion of the (TRAP) promoter region, the 1.6-kb C portion does not account for significant gene expression in vivo or in vitro; production of the bone- and spleen-preferred (TRAP) C transcript must depend on regulatory elements outside of the 2.2-kb promoter. As the majority of currently investigated transcription factors that influence transcriptional regulation of osteoclast gene expression bind within the 1.6-kb C portion of the (TRAP) promoter, it is likely that transcription binding sites outside of the 2.2-kb region will have profound effects on regulation of the gene in vivo and in vitro.

Expression analysis of a human hepatic cell line in response to palmitate

Saturated fat plays a role in common debilitating diseases such as obesity, type 2 diabetes, and coronary heart disease. It is also clear that certain fatty acids act as regulators of metabolism via both direct and indirect signalling of target tissues. As the molecular mechanisms of saturated fatty acid signalling in the liver are poorly defined, hepatic gene expression analysis was undertaken in a human hepatocyte cell line after incubation with palmitate. Profiling of mRNA expression using cDNA microarray analysis revealed that 162 of approximately 18,000 genes tested were differentially expressed after incubation with palmitate for 48 h. Altered transcription profiles were observed in a wide variety of genes, including genes involved in lipid and cholesterol transport, cholesterol catabolism, cell growth and proliferation, cell signalling, P-oxidation, and oxidative stress response. While palinitate signalling has been examined in pancreatic beta-cells, this is the first report showing that palmitate regulates expression of numerous genes via direct molecular signalling mechanisms in liver cells. (C) 2005 Elsevier Inc. All rights reserved.

Genome-wide analysis of mammalian promoter architecture and evolution

Mammalian promoters can be separated into two classes, conserved TATA box-enriched promoters, which initiate at a welldefined site, and more plastic, broad and evolvable CpG-rich promoters. We have sequenced tags corresponding to several hundred thousand transcription start sites (TSSs) in the mouse and human genomes, allowing precise analysis of the sequence architecture and evolution of distinct promoter classes. Different tissues and families of genes differentially use distinct types of promoters. Our tagging methods allow quantitative analysis of promoter usage in different tissues and show that differentially regulated alternative TSSs are a common feature in protein-coding genes and commonly generate alternative N termini. Among the TSSs, we identified new start sites associated with the majority of exons and with 3' UTRs. These data permit genome-scale identification of tissue-specific promoters and analysis of the cis-acting elements associated with them.

Sugarcane ShSUT1: analysis of sucrose transport activity and inhibition by sucralose

Plant sucrose transporters (SUTs) are members of the glycoside-pentoside-hexuronide (GPH) cation symporter family (TC2.A.2) that is part of the major facilitator superfamily (MFS). All plant SUTs characterized to date function as proton-coupled symporters and catalyze the cellular uptake of sucrose. SUTs are involved in loading sucrose into the phloem and sink tissues, such as seeds, roots and flowers. Because monocots are agriculturally important, SUTs from cereals have been the focus of recent research. Here we present a functional analysis of the SUT ShSUT1 from sugarcane, an important crop species grown for its ability to accumulate high amounts of sucrose in the stem. ShSUT1 was previously shown to be expressed in maturing stems and plays an important role in the accumulation of sucrose in this tissue. Using two-electrode voltage clamping in Xenopus oocytes expressing ShSUT1, we found that ShSUT1 is highly selective for sucrose, but has a relatively low affinity for sucrose (K-0.5 = 8.26 mM at pH 5.6 and a membrane potential of -137 mV). We also found that the sucrose analog sucralose (4,1 ',6 '-trichloro-4,1 ',6 '-trideoxygalactosucrose) is a competitive inhibitor of ShSUT1 with an inhibition coefficient (K-i) of 16.5 mM. The presented data contribute to our understanding of sucrose transport in plants in general and in monocots in particular.

On the simultaneous use of clinical and microarray expression data in the cluster analysis of tissue samples

This paper considers a model-based approach to the clustering of tissue samples of a very large number of genes from microarray experiments. It is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. Frequently in practice, there are also clinical data available on those cases on which the tissue samples have been obtained. Here we investigate how to use the clinical data in conjunction with the microarray gene expression data to cluster the tissue samples. We propose two mixture model-based approaches in which the number of components in the mixture model corresponds to the number of clusters to be imposed on the tissue samples. One approach specifies the components of the mixture model to be the conditional distributions of the microarray data given the clinical data with the mixing proportions also conditioned on the latter data. Another takes the components of the mixture model to represent the joint distributions of the clinical and microarray data. The approaches are demonstrated on some breast cancer data, as studied recently in van't Veer et al. (2002).