Transcriptional profile reveals altered hepatic lipid and cholesterol metabolism in hyposulfatemic NaS1 null mice

Sulfate plays an essential role in human growth and development, and its circulating levels are maintained by the renal Na+-SO42- cotransporter, NaS1. We previously generated a NaS1 knockout ( Nas1(-/-)) mouse, an animal model for hyposulfatemia, that exhibits reduced growth and liver abnormalities including hepatomegaly. In this study, we investigated the hepatic gene expression profile of Nas1(-/-) mice using oligonucleotide microarrays. The mRNA expression levels of 92 genes with known functional roles in metabolism, cell signaling, cell defense, immune response, cell structure, transcription, or protein synthesis were increased ( n = 51) or decreased ( n = 41) in Nas1(-/-) mice when compared with Nas1(-/-) mice. The most upregulated transcript levels in Nas1(-/-) mice were found for the sulfotransferase genes, Sult3a1 ( approximate to 500% increase) and Sult2a2 ( 100% increase), whereas the metallothionein-1 gene, Mt1, was among the most downregulated genes ( 70% decrease). Several genes involved in lipid and cholesterol metabolism, including Scd1, Acly, Gpam, Elov16, Acsl5, Mvd, Insig1, and Apoa4, were found to be upregulated ( >= 30% increase) in Nas1(+/+) mice. In addition, Nas1(+/+) mice exhibited increased levels of hepatic lipid ( approximate to 16% increase), serum cholesterol ( approximate to 20% increase), and low-density lipoprotein ( approximate to 100% increase) and reduced hepatic glycogen ( approximate to 50% decrease) levels. In conclusion, these data suggest an altered lipid and cholesterol metabolism in the hyposulfatemic Nas1(-/-) mouse and provide new insights into the metabolic state of the liver in Nas1(-/-) mice.

Comparative gene expression in brain regions of human alcoholics

The mesocorticolimbic system is the reward centre of the brain and the major target for drugs of abuse including alcohol. Neuroadaptive changes in this region are thought to underlie the process of tolerance and dependence. Recently, several research groups have searched for alcohol-responsive genes using high-throughput microarrays and well-characterized human post-mortem material. Comparison of data from these studies of cortical regions highlights the differences in experimental approach and selection of cases. However, alcohol-responsive gene sets associated with transcription, oxidative stress and energy production were common to these studies. In marked contrast, alcohol-responsive genes in the nucleus accumbens and the ventral tegmental area are primarily associated with changes in neurotransmission and signal transduction. These data support the concept that, within cortical regions, changes in gene expression are associated with alcoholism-related pathology. In the dopaminergic tract of the mesocorticolimbic system, alcohol-responsive gene sets suggest long-term neuroplastic changes in synaptic transmission.

Glass transition and enthalpy relaxation of amorphous food saccharides: A review

Many food materials exist in a disordered amorphous solid state due to processing. Therefore, understanding the concept of amorphous state, its important phase transition (i.e., glass transition), and the related phenomena (e.g., enthalpy relaxation) is important to food scientists. Food saccharides, including mono-, di-, oligo-, and polysaccharides, are among the most important major components in food. Focusing on the food saccharides, this review covers important topics related to amorphous solids, including the concept and molecular arrangement of amorphous solid, the formation of amorphous food saccharides, the concept of glass transition and enthalpy relaxation, physical property changes and molecular mobility around the glass transition, measurement of the glass transition and enthalpy relaxation, their mathematical descriptions and models, and influences on food stability.

Suppressor of cytokine signaling 3 limits protection of leukemia inhibitory factor receptor signaling against central demyelination

Enhancement of oligodendrocyte survival through activation of leukemia inhibitory factor receptor (LIFR) signaling is a candidate therapeutic strategy for demyelinating disease. However, in other cell types, LIFR signaling is under tight negative regulation by the intracellular protein suppressor of cytokine signaling 3 (SOCS3). We, therefore, postulated that deletion of the SOCS3 gene in oligodendrocytes would promote the beneficial effects of LIFR signaling in limiting demyelination. By studying wild-type and LIF-knockout mice, we established that SOCS3 expression by oligodendrocytes was induced by the demyelinative insult, that this induction depended on LIF, and that enclogenously produced LIF was likely to be a key determinant of the CNS response to oligodendrocyte loss. Compared with wild-type controls, oligo-dendrocyte-specific SOCS3 conditional-knockout mice displayed enhanced c-fos activation and exogenous LIF-induced phosphorylation of signal transducer and activator of transcription 3. Moreover, these SOCS3-deficient mice were protected against cupri-zone-induced oligodendrocyte loss relative to wild-type animals. These results indicate that modulation of SOCS3 expression could facilitate the endogenous response to CNS injury.

The human genome and gene expression profiling

The mapping and sequencing of the human genome has generated a large resource for answering questions about human disease. This achievement is akin in scientific importance to developing the periodic table of elements. Plastic surgery has always been at the frontier medical research. This resource will help us to improve our understanding on the many unknown physiological and pathogical conditions we deal with daily, such as wound heating keloid scar formation, Dupuytren's disease, rheumatoid arthritis, vascular malformation and carcinogenesis. We are primed in obtaining both disease and normal tissues to use this resource and applying it to clinical use. This review is about the human genome, the basis of gene expression profiling and how it will affect our clinical and research practices in the future and for those embarking on the use of this new technology as a research tool, we provide a brief insight on its limitations and pitfalls. (C) 2006 The British Association of Plastic Surgeons. Published by Elsevier Ltd. All rights reserved.

Transcriptome analysis of Neotyphodium and Epichloë grass endophytes

Large-scale gene discovery has been performed for the grass fungal endophytes Neotyphodium coenophialum, Neotyphodium lolii, and Epichloe festucae. The resulting sequences have been annotated by comparison with public DNA and protein sequence databases and using intermediate gene ontology annotation tools. Endophyte sequences have also been analysed for the presence of simple sequence repeat and single nucleotide polymorphism molecular genetic markers. Sequences and annotation are maintained within a MySQL database that may be queried using a custom web interface. Two cDNA-based microarrays have been generated from this genome resource, They permit the interrogation of 3806 Neotyphodium genes (Nchip (TM) rnicroarray), and 4195 Neotyphodium and 920 Epichloe genes (EndoChip (TM) microarray), respectively. These microarrays provide tools for high-throughput transcriptome analysis, including genome-specific gene expression studies, profiling of novel endophyte genes, and investigation of the host grass-symbiont interaction. Comparative transcriptome analysis in Neotyphodium and Epichloe was performed. (c) 2006 Elsevier

Microarray-based comparative genomic hybridisation of breast cancer patients receiving neoadjuvant chemotherapy

We analysed the molecular genetic profiles of breast cancer samples before and after neoadjuvant chemotherapy with combination doxorubicin and cyclophosphamide (AC). DNA was obtained from microdissected frozen breast core biopsies from 44 patients before chemotherapy. Additional samples were obtained before the second course of chemotherapy (D21) and after the completion of the treatment (surgical specimens) in 17 and 21 patients, respectively. Microarray-based comparative genome hybridisation was performed using a platform containing approx5800 bacterial artificial chromosome clones (genome-wide resolution: 0.9 Mb). Analysis of the 44 pretreatment biopsies revealed that losses of 4p, 4q, 5q, 12q13.11–12q13.12, 17p11.2 and 17q11.2; and gains of 1p, 2p, 7q, 9p, 11q, 19p and 19q were significantly associated with oestrogen receptor negativity. 16q21–q22.1 losses were associated with lobular and 8q24 gains with ductal types. Losses of 5q33.3–q4 and 18p11.31 and gains of 6p25.1–p25.2 and Xp11.4 were associated with HER2 amplification. No correlations between DNA copy number changes and clinical response to AC were found. Microarray-based comparative genome hybridisation analysis of matched pretreatment and D21 biopsies failed to identify statistically significant differences, whereas a comparison between matched pretreatment and surgical samples revealed a statistically significant acquired copy number gain on 11p15.2–11p15.5. The modest chemotherapy-driven genomic changes, despite profound loss of cell numbers, suggest that there is little therapeutic selection of resistant non-modal cell lineages.

Dietary supplementation of vitamin E and -lipoic acid upregulates cell growth and signaling genes in rat myocardium

The efficacy of antioxidant supplementation in the prevention of cardiovascular disease appears equivocal, however the use of more potent antioxidant combinations than those traditionally used may exert a more positive effect. We have shown previously that supplementation of vitamin E and α-lipoic acid increases cardiac performance during post-ischemia reperfusion in older rats and increases Bcl-2 levels in endothelial cells. The purpose of this study was to examine the effects of vitamin E and α-lipoic acid supplementation on myocardial gene expression with a view to determine their mechanism of action. Young male rats received either a control (n=7) or vitamin E and α-lipoic acid supplemented diet (n=8) for 14 weeks. RNA from myocardial tissue was then amplified and samples were pooled within groups and competitively hybridized to 5K oligonucleotide rat microarrays. The relative expression of each gene was then compared to the control sample. Animals that received the antioxidant-supplemented diet exhibited upregulation (>1.5×) of 13 genes in the myocardium with 2 genes downregulated.� �Upregulated genes include those involved in cell growth and maintenance (LynB, Csf1r, Akt2, Tp53), cell signaling (LynB, Csf1r) and signal transduction (Pacsin2, Csf1r). Downregulated genes encode thyroid (Thrsp) and F-actin binding proteins (Nexilin).

DNA Motifs Suppressing TLR9 Responses

Immune cells respond to bacterial DNA containing unmethylated CpG motifs via Toll-like receptor 9 (TLR9). Given the apparent role of TLR9 in development of systemic lupus erythernatosus (SLE), there is interest in the development of TLR9 inhibitors. TLR9-mediated responses are reported to be inhibited by a confusing variety of different DNA sequences and structures. To aid characterization, we have provisionally categorized TLR9-inhibitory oligodeoxynucleoti des (ODN) into 4 classes, on the basis of sequence and probable mode of action. Class I are short G-rich ODN, which show sequence-specific inhibition of all TLR9 responses, and may be direct competitive inhibitors for DNA binding to TLR9. Class II are telomeric repeat motifs that inhibit STAT signaling, and thus are not specific to TLR9 responses. Because Class II ODN are generally made as 24-base phosphorothioate-modified ODN (PS-ODN), they also fall into Class IV, defined as long PS-ODN, which inhibit TLR9 responses in a sequence-nonspecific manner. Class III includes oligo (dG) that forms a 4-stranded structure and inhibits DNA uptake. The Class I G-rich motifs show the most promise as selective and potent TLR9 inhibitors for therapeutic applications.

Molecular classification of cutaneous malignant melanoma by gene expression profiling

The most common human cancers are malignant neoplasms of the skin(1,2). Incidence of cutaneous melanoma is rising especially steeply, with minimal progress in non-surgical treatment of advanced disease(3,4). Despite significant effort to identify independent predictors of melanoma outcome, no accepted histopathological, molecular or immunohistochemical marker defines subsets of this neoplasm(2,3). Accordingly, though melanoma is thought to present with different 'taxonomic' forms, these are considered part of a continuous spectrum rather than discrete entities(2). Here we report the discovery of a subset of melanomas identified by mathematical analysis of gene expression in a series of samples. Remarkably, many genes underlying the classification of this subset are differentially regulated in invasive melanomas that form primitive tubular networks in vitro, a feature of some highly aggressive metastatic melanomas(5). Global transcript analysis can identify unrecognized subtypes of cutaneous melanoma and predict experimentally verifiable phenotypic characteristics that may be of importance to disease progression.

Gene expression in human alcoholism: Microarray analysis of frontal cortex

Background: Changes in brain gene expression are thought to be responsible for the tolerance, dependence, and neurotoxicity produced by chronic alcohol abuse, but there has been no large scale study of gene expression in human alcoholism. Methods: RNA was extracted from postmortem samples of superior frontal cortex of alcoholics and nonalcoholics. Relative levels of RNA were determined by array techniques. We used both cDNA and oligonucleotide microarrays to provide coverage of a large number of genes and to allow cross-validation for those genes represented on both types of arrays. Results: Expression levels were determined for over 4000 genes and 163 of these were found to differ by 40% or more between alcoholics and nonalcoholics. Analysis of these changes revealed a selective reprogramming of gene expression in this brain region, particularly for myelin-related genes which were downregulated in the alcoholic samples. In addition, cell cycle genes and several neuronal genes were changed in expression. Conclusions: These gene expression changes suggest a mechanism for the loss of cerebral white matter in alcoholics as well as alterations that may lead to the neurotoxic actions of ethanol.

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).

Upregulation of beta catenin in superior frontal cortex of chronic alcoholics

Chronic alcohol abuse causes neurotoxicity and the development of tolerance and dependence. At the molecular level, however, knowledge about mechanisms underlying alcoholism remains limited. In this study we examined the superior frontal cortex, one of the most vulnerable brain regions, of alcoholics and of age- and gender-matched control subjects by means of antibody microarrays and Western blot analyses, and identified an up-regulation of beta-catenin level in the superior frontal cortex of alcoholics. Beta-catenin is the orthologue of the Drosophila armadillo segment polarity gene and a down stream component of the Wnt and Akt signaling pathway. Beta-catenin was identified as a cell adhesion molecule of the cadherin family which binds to the actin cytoskeleton. Genetic and biochemical analyses also found that beta-catenin can be translocated from the cytoplasm to the nucleus and acts as a transcription factor. In addition, electron microscopy performed on rat brain tissue sections has localized the beta-catenin and cadherin complexes to the synapses where they border the active zone. Because of the multi-functional role of beta-catenin in the nervous system, this study provides the premise for further investigation of mechanisms underlying the up-regulation of beta-catenin in alcoholism, which may have considerable pathogenic and therapeutic relevance.

Genomic and proteomic analysis of synaptic protein expression in the brains of human alcoholics

Alcoholism results in changes in the human brain which reinforce the cycle of craving and dependency, and these changes are manifest in the pattern of expression of mRNA and proteins in key cells and brain areas. Long-term alcohol abuse also results in damage to selected regions of the cortex. We have used cDNA microarrays to show that less than 1% of mRNA transcripts differ signifi cantly between cases and controls in the susceptible area and that the expression profi le of a subset of these transcripts is suffi cient to distinguish alcohol abusers from controls. In addition, we have utilized a 2D gel proteomics based approach to determine the identity of proteins in the superior frontal cortex (SFC) of the human brain that show differential expression in controls and long term alcohol abusers. Overall, 182 proteins differed by the criterion of > 2-fold between case and control samples. Of these, 139 showed signifi cantly lower expression in alcoholics, 35 showed signifi cantly higher expression, and 8 were new or had disappeared. To date 63 proteins have been identifi ed. The expression of one family of proteins, the synucleins, has been further characterized using Real Time PCR and Western Blotting. The expression of alpha-synuclein mRNA was signifi cantly lower in the SFC of alcoholics compared with the same area in controls (P = 0.01) whereas no such difference in expression was found in the motor cortex. The expression of beta- and gamma- synuclein were not signifi cantly different between alcoholics and controls. In contrast, the pattern of alphasynuclein protein expression differs from that of the corresponding RNA transcript. Because of the key role of synaptic proteins in the pathogenesis of alcoholism, we are developing 2-D DIGE based techniques to quantify expression changes in synaptosomes prepared from the SFC of controls and alcoholics.

Multilevel modelling for inference of genetic regulatory networks

Time-course experiments with microarrays are often used to study dynamic biological systems and genetic regulatory networks (GRNs) that model how genes influence each other in cell-level development of organisms. The inference for GRNs provides important insights into the fundamental biological processes such as growth and is useful in disease diagnosis and genomic drug design. Due to the experimental design, multilevel data hierarchies are often present in time-course gene expression data. Most existing methods, however, ignore the dependency of the expression measurements over time and the correlation among gene expression profiles. Such independence assumptions violate regulatory interactions and can result in overlooking certain important subject effects and lead to spurious inference for regulatory networks or mechanisms. In this paper, a multilevel mixed-effects model is adopted to incorporate data hierarchies in the analysis of time-course data, where temporal and subject effects are both assumed to be random. The method starts with the clustering of genes by fitting the mixture model within the multilevel random-effects model framework using the expectation-maximization (EM) algorithm. The network of regulatory interactions is then determined by searching for regulatory control elements (activators and inhibitors) shared by the clusters of co-expressed genes, based on a time-lagged correlation coefficients measurement. The method is applied to two real time-course datasets from the budding yeast (Saccharomyces cerevisiae) genome. It is shown that the proposed method provides clusters of cell-cycle regulated genes that are supported by existing gene function annotations, and hence enables inference on regulatory interactions for the genetic network.