Genetic study of alcoholism and novel gene expression in the alcoholic brain

Alcohol dependence may result from neuroadaptation involving alteration of gene expression after long-term alcohol exposure. The systematic study of gene expression profiles of the human alcoholic brain was initiated using the method of polymerase chain reaction (PCR)-differential display and was followed by DNA microarray. To date, more than 100 alcohol-responsive genes have been identified from the frontal cortex, motor cortex and nucleus accumbens of the human brain. These genes have a wide range of functions in the brain and indicate diverse actions of alcohol on neuronal function. This review discusses the current information on the genetic basis of alcoholism and the induction and characterization of these alcohol-responsive genes.

Gene expression profiles in murine hematopoietic stem cells revisited: Analysis of cDNA libraries reveals high levels of translational and metabolic activities

Gene expression studies from hematopoietic stem cell (HSC) populations purified to variable degrees have defined a set of sternness genes. Unexpectedly, results also hinted toward a HSC chromatin poised in a wide-open state. With the aim of providing a robust tool for further studies into the molecular biology of HSCs, the studies herein describe the construction and comparative molecular analysis of A-phage cDNA libraries from highly purified HSCs that retained their long-term repopulating activities (long-term HSCs [LT-HSCs]) and from short-term repopulating HSCs that were largely depleted of these activities. Microarray analysis of the libraries confirmed the previous results but also revealed an unforeseen preferential expression of translation- and metabolism-associated genes in the LT-HSCs. Therefore, these data indicate that HSCs are quiescent only in regard of proliferative activities but are in a state of readiness to provide the metabolic and translational activities required after induction of proliferation and exit from the HSC pool.

A Mixture model with random-effects components for clustering correlated gene-expression profiles

Motivation: The clustering of gene profiles across some experimental conditions of interest contributes significantly to the elucidation of unknown gene function, the validation of gene discoveries and the interpretation of biological processes. However, this clustering problem is not straightforward as the profiles of the genes are not all independently distributed and the expression levels may have been obtained from an experimental design involving replicated arrays. Ignoring the dependence between the gene profiles and the structure of the replicated data can result in important sources of variability in the experiments being overlooked in the analysis, with the consequent possibility of misleading inferences being made. We propose a random-effects model that provides a unified approach to the clustering of genes with correlated expression levels measured in a wide variety of experimental situations. Our model is an extension of the normal mixture model to account for the correlations between the gene profiles and to enable covariate information to be incorporated into the clustering process. Hence the model is applicable to longitudinal studies with or without replication, for example, time-course experiments by using time as a covariate, and to cross-sectional experiments by using categorical covariates to represent the different experimental classes. Results: We show that our random-effects model can be fitted by maximum likelihood via the EM algorithm for which the E(expectation) and M(maximization) steps can be implemented in closed form. Hence our model can be fitted deterministically without the need for time-consuming Monte Carlo approximations. The effectiveness of our model-based procedure for the clustering of correlated gene profiles is demonstrated on three real datasets, representing typical microarray experimental designs, covering time-course, repeated-measurement and cross-sectional data. In these examples, relevant clusters of the genes are obtained, which are supported by existing gene-function annotation. A synthetic dataset is considered too.

Cell cycle alterations in biopsied olfactory neuroepithelium in schizophrenia and bipolar I disorder using cell culture and gene expression analyses

We previously demonstrated that olfactory cultures front individuals with schizophrenia had increased cell proliferation compared to Cultures from healthy controls. The aims of this study were to (a) replicate this observation in a new group Of individuals with schizophrenia, (b) examine the specificity of these findings by including individuals with bipolar I disorder and (c) explore gene expression differences that may underlie cell cycle differences in these diseases. Compared to controls (n = 10), there was significantly more mitosis in schizophrenia patient cultures (it = 8) and significantly more cell death in the bipolar I disorder patient cultures (n=8). Microarray data showed alterations to the cell cycle and phosphatidylinositol signalling pathways in schizophrenia and bipolar I disorder, respectively. Whilst caution is required in the interpretation of the array results, the study provides evidence indicating that cell proliferation and cell death in olfactory neuroepithelial cultures is differentially altered in schizophrenia and bipolar disorder. (c) 2005 Elsevier B.V. All rights reserved.

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.

Transcriptome analysis of a cnidarian-dinoflagellate mutualism reveals complex modulation of host gene expression

Background: Cnidarian - dinoflagellate intracellular symbioses are one of the most important mutualisms in the marine environment. They form the trophic and structural foundation of coral reef ecosystems, and have played a key role in the evolutionary radiation and biodiversity of cnidarian species. Despite the prevalence of these symbioses, we still know very little about the molecular modulators that initiate, regulate, and maintain the interaction between these two different biological entities. In this study, we conducted a comparative host anemone transcriptome analysis using a cDNA microarray platform to identify genes involved in cnidarian - algal symbiosis. Results: We detected statistically significant differences in host gene expression profiles between sea anemones ( Anthopleura elegantissima) in a symbiotic and non-symbiotic state. The group of genes, whose expression is altered, is diverse, suggesting that the molecular regulation of the symbiosis is governed by changes in multiple cellular processes. In the context of cnidarian dinoflagellate symbioses, we discuss pivotal host gene expression changes involved in lipid metabolism, cell adhesion, cell proliferation, apoptosis, and oxidative stress. Conclusion: Our data do not support the existence of symbiosis- specific genes involved in controlling and regulating the symbiosis. Instead, it appears that the symbiosis is maintained by altering expression of existing genes involved in vital cellular processes. Specifically, the finding of key genes involved in cell cycle progression and apoptosis have led us to hypothesize that a suppression of apoptosis, together with a deregulation of the host cell cycle, create a platform that might be necessary for symbiont and/or symbiont-containing host cell survival. This first comprehensive molecular examination of the cnidarian - dinoflagellate associations provides critical insights into the maintenance and regulation of the symbiosis.

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.

Real-Time Gene-Expression Extraction with Fast Classification (FC) Networks

Fast Classification (FC) networks were inspired by a biologically plausible mechanism for short term memory where learning occurs instantaneously. Both weights and the topology for an FC network are mapped directly from the training samples by using a prescriptive training scheme. Only two presentations of the training data are required to train an FC network. Compared with iterative learning algorithms such as Back-propagation (which may require many hundreds of presentations of the training data), the training of FC networks is extremely fast and learning convergence is always guaranteed. Thus FC networks may be suitable for applications where real-time classification is needed. In this paper, the FC networks are applied for the real-time extraction of gene expressions for Chlamydia microarray data. Both the classification performance and learning time of the FC networks are compared with the Multi-Layer Proceptron (MLP) networks and support-vector-machines (SVM) in the same classification task. The FC networks are shown to have extremely fast learning time and comparable classification accuracy.

MILVA:An interactive tool for the exploration of multidimensional microarray data

Clustering techniques such as k-means and hierarchical clustering are commonly used to analyze DNA microarray derived gene expression data. However, the interactions between processes underlying the cell activity suggest that the complexity of the microarray data structure may not be fully represented with discrete clustering methods.

Gene expression profile suggests that pigs (Sus scrofa) are susceptible to Anaplasma phagocytophilum but control infection

BACKGROUND Anaplasma phagocytophilum infects a wide variety of hosts and causes granulocytic anaplasmosis in humans, horses and dogs and tick-borne fever in ruminants. Infection with A. phagocytophilum results in the modification of host gene expression and immune response. The objective of this research was to characterize gene expression in pigs (Sus scrofa) naturally and experimentally infected with A. phagocytophilum trying to identify mechanisms that help to explain low infection prevalence in this species. RESULTS For gene expression analysis in naturally infected pigs, microarray hybridization was used. The expression of differentially expressed immune response genes was analyzed by real-time RT-PCR in naturally and experimentally infected pigs. Results suggested that A. phagocytophilum infection affected cytoskeleton rearrangement and increased both innate and adaptive immune responses by up regulation of interleukin 1 receptor accessory protein-like 1 (IL1RAPL1), T-cell receptor alpha chain (TCR-alpha), thrombospondin 4 (TSP-4) and Gap junction protein alpha 1 (GJA1) genes. Higher serum levels of IL-1 beta, IL-8 and TNF-alpha in infected pigs when compared to controls supported data obtained at the mRNA level. CONCLUSIONS These results suggested that pigs are susceptible to A. phagocytophilum but control infection, particularly through activation of innate immune responses, phagocytosis and autophagy. This fact may account for the low infection prevalence detected in pigs in some regions and thus their low or no impact as a reservoir host for this pathogen. These results advanced our understanding of the molecular mechanisms at the host-pathogen interface and suggested a role for newly reported genes in the protection of pigs against A. phagocytophilum.