Ethanol and gene expression in brain

This article represents the proceedings of a symposium at the 2000 ISBRA Meeting in Yokohama, Japan. The chairs were Izuru Matusmoto and Peter A. Wilce. The presentations were (1) GABA receptor subunit expression in the human alcoholic brain, by Tracey Buckley and Peter Dodd; (2) NMDAR gene expression during ethanol addiction, by Jorg Puzke, Rainer Spanagel, Walther Zieglgansberger, and Gerald Wolf; (3) Differentially expressed gene in the nucleus accumbens from ethanol-administered rat, by Shuangying Leng; (4) Expression of a novel gene in the alcoholic brain, by Peter A. Wilce; and (5) Investigations of haplotypes of the dopamine Da-receptor gene in alcoholics, by Hans Rommelspacher, Ulrich Finckh, and Lutz G. Schmidt.

Genetic and physical interactions between Microphthalmia transcription factor and PU.1 are necessary for osteoclast gene expression and differentiation

The microphthalmia transcription factor (MITF), a basic-helix-loop-helix zipper factor, regulates distinct target genes in several cell types. We hypothesized that interaction with the Ets family factor PU.1, whose expression is limited to hematopoietic cells, might be necessary for activation of target genes like tartrate-resistant acid phosphatase (TRAP) in osteoclasts. Several lines of evidence were consistent with this model. The combination of MITF and PU.1 synergistically activated the TRAP promoter in transient assays. This activation was dependent on intact binding sites for both factors in the TRAP promoter. MITF and PU.1 physically interacted when coexpressed in COS cells or in vitro when purified recombinant proteins were studied. The minimal regions of MITF and PU.1 required for the interaction were the basic-helix-loop-helix zipper domain and the Ets DNA binding domain, respectively. Significantly, mice heterozygous for both the mutant mi allele and a PU.1 null allele developed osteopetrosis early in life which resolved with age. The size and number of osteoclasts were not altered in the double heterozygous mutant mice, indicating that the defect lies in mature osteoclast function. Taken in total, the results afford an example of how lineage-specific gene regulation can be achieved by the combinatorial action of two broadly expressed transcription factors.

Patterns of gene expression are altered in the frontal and motor cortices of human alcoholics

Alcoholism is a major health problem in Western countries, yet relatively little is known about the mechanisms by which chronic alcohol abuse causes the pathologic changes associated with the disease. It is likely that chronic alcoholism affects a number of signaling cascades and transcription factors, which in turn result in distinct gene expression patterns. These patterns are difficult to detect by traditional experiments measuring a few mRNAs at a time, but are well suited to microarray analyses. We used cDNA microarrays to analyze expression of approximately 10 000 genes in the frontal and motor cortices of three groups of chronic alcoholic and matched control cases. A functional hierarchy was devised for classification of brain genes and the resulting groups were compared based on differential expression. Comparison of gene expression patterns in these brain regions revealed a selective reprogramming of gene expression in distinct functional groups. The most pronounced differences were found in myelin-related genes and genes involved in protein trafficking. Significant changes in the expression of known alcohol-responsive genes, and genes involved in calcium, cAMP, and thyroid signaling pathways were also identified. These results suggest that multiple pathways may be important for neuropathology and altered neuronal function observed in alcoholism.

Tissue-specific gene expression in soybean (Glycine max) detected by cDNA microarray analysis

We have constructed cDNA microarrays for soybean (Glycine max L. Merrill), containing approximately 4,100 Unigene ESTs derived from axenic roots, to evaluate their application and utility for functional genomics of organ differentiation in legumes. We assessed microarray technology by conducting studies to evaluate the accuracy of microarray data and have found them to be both reliable and reproducible in repeat hybridisations. Several ESTs showed high levels (>50 fold) of differential expression in either root or shoot tissue of soybean. A small number of physiologically interesting, and differentially expressed sequences found by microarray analysis were verified by both quantitative real-time RT-PCR and Northern blot analysis. There was a linear correlation (r(2) = 0.99, over 5 orders of magnitude) between microarray and quantitative real-time RT-PCR data. Microarray analysis of soybean has enormous potential not only for the discovery of new genes involved in tissue differentiation and function, but also to study the expression of previously characterised genes, gene networks and gene interactions in wild-type, mutant or transgenic; plants.

Systemic gene expression in arabidopsis during an incompatible interaction with Alternaria brassicicola

Pathogen challenge can trigger an integrated set of signal transduction pathways, which ultimately leads to a state of high alert, otherwise known as systemic or induced resistance in tissue remote to the initial infection. Although large-scale gene expression during systemic acquired resistance, which is induced by salicylic acid or necrotizing pathogens has been previously reported using a bacterial pathogen, the nature of systemic defense responses triggered by an incompatible necrotrophic fungal pathogen is not known. We examined transcriptional changes that occur during systemic defense responses in Arabidopsis plants inoculated with the incompatible fungal pathogen Alternaria brassicicola. Substantial changes (2.00-fold and statistically significant) were demonstrated in distal tissue of inoculated plants for 35 genes (25 up-regulated and 10 down-regulated), and expression of a selected subset of systemically expressed genes was confirmed using real-time quantitative polymerase chain reaction. Genes with altered expression in distal tissue included those with putative functions in cellular housekeeping, indicating that plants modify these vital processes to facilitate a coordinated response to pathogen attack. Transcriptional up-regulation of genes encoding enzymes functioning in the beta-oxidation pathway of fatty acids was particularly interesting. Transcriptional up-regulation was also observed for genes involved in cell wall synthesis and modification and genes putatively involved in signal transduction. The results of this study, therefore, confirm the notion that distal tissue of a pathogen-challenged plant has a heightened preparedness for subsequent pathogen attacks.

Effects of A1 adenosine receptor overexpression on normoxic and post-ischemic gene expression

Objectives: To identify potential molecular genetic determinants of cardiovascular ischemic tolerance in wild-type and transgenic hearts overexpressing A(1) adenosine receptors (A(1)ARs). Methods: cDNA microarrays were used to explore expression of 1824 genes ill wild-type hearts and ischemia-tolerant mouse hearts overexpressing A(1)ARs. Results: Overexpression of A(1)ARs reduced post-ischemic contractile dysfunction, limited arrhythmogenesis, and reduced necrosis by similar to80% in hearts subjected to 30 min global ischemia 60 mill reperfusion. Cardioprotection was abrogated by acute A(1)AR antagonism, and only a small number (19) of genes were modified by A(1)AR overexpression in normoxic hearts. Ischemia-reperfusion significantly altered expression of 75 genes in wild-type hearts (14 induced, 61 down-regulated), including genes for metabolic enzymes, structural/motility proteins, cell signaling proteins, defense/growth proteins, and regulators of transcription and translation. A(1)AR overexpression reversed the majority of gene down-regulation whereas gene induction was generally unaltered. Additionally, genes involved in cell defence, signaling and gene expression were selectively modified by ischemia in transgenic hearts (33 induced, 10 down-regulated), possibly contributing to the protected phenotype. Real-time PCR verified changes in nine selected genes, revealing concordance with array data. Transcription of the A(1)AR gene was also modestly reduced post-ischemia, consistent with impaired functional sensitivity to A(1)AR stimulation Conclusions: Data are presented regarding the early post-ischemic gene profile of intact heart. Reduced A(1)AR transcription is observed which may contribute to poor outcome from ischemia. A(1)AR overexpression selectively modifies post-ischemic gene expression, potentially contributing to ischemic-tolerance. (C) 2003 European Society of Cardiology. Published by Elsevier Science B.V. All rights reserved.

Gene expression during early ascidian metamorphosis requires signaling by Hemps, an EGF-like protein

Hemps, a novel epidermal growth factor (EGF)-like protein, is expressed during larval development and early metamorphosis in the ascidian Herdmania curvata and plays a direct role in triggering metamorphosis. In order to identify downstream genes in the Hemps pathway we used a gene expression profiling approach, in which we compared post-larvae undergoing normal metamorphosis with larval metamorphosis blocked with an anti-Hemps antibody. Molecular profiling revealed that there are dynamic changes in gene expression within the first 30 minutes of normal metamorphosis with a significant portion of the genome (approximately 49%) being activated or repressed. A more detailed analysis of the expression of 15 of these differentially expressed genes through embryogenesis, larval development and metamorphosis revealed that while there is a diversity of temporal expression patterns, a number of genes are transiently expressed during larval development and metamorphosis. These and other differentially expressed genes were localised to a range of specific cell and tissue types in Herdmania larvae and post-larvae. The expression of approximately 24% of the genes that were differentially expressed during early metamorphosis was affected in larvae treated with the anti-Hemps antibody. Knockdown of Hemps activity affected the expression of a range of genes within 30 minutes of induction, suggesting that the Hemps pathway directly regulates early response genes at metamorphosis. In most cases, it appears that the Hemps pathway contributes to the modulation of gene expression, rather than initial gene activation or repression. A total of 151 genes that displayed the greatest alterations in expression in response to anti-Hemps antibody were sequenced. These genes were implicated in a range of developmental and physiological roles, including innate immunity, signal transduction and in the regulation of gene transcription. These results suggest that there is significant gene activity during the very early stages of H. curvata metamorphosis and that the Hemps pathway plays a key role in regulating the expression of many of these genes.

Genes and gene expression in the brain of the alcoholic

Chronic alcoholism leads to localized brain damage, which is prominent in superior frontal cortex but mild in motor cortex. The likelihood of developing alcohol dependence is associated with genetic markers. GABA(A) receptor expression differs between alcoholics and controls, whereas glutamate receptor differences are muted. We determined whether genotype differentiated the localized expression of glutamate and gamma-aminobutyric acid (GABA) receptors to influence the severity of alcohol-induced brain damage. Cerebrocortical tissue was obtained at autopsy from alcoholics without alcohol-related disease, alcoholics with cirrhosis, and matched controls. DRD2A, DRD2B, GABB2, EAAT2, and 5HTT genotypes did not divide alcoholic cases and controls on N-methyl-D-aspartate (NMDA) receptor parameters. In contrast, alcohol dehydrogenase (ADH)3 genotype interacted significantly with NMDA receptor efficacy and affinity in a region-specific manner. EAAT2 genotype interacted significantly with local GABAA receptor subunit mRNA expression, and GABB2 and DRD2B genotypes with p subunit isoform protein expression. Genotype may modulate amino acid transmission locally so as to mediate neuronal vulnerability. This has implications for the effectiveness of pharmacological interventions aimed at ameliorating brain damage and, possibly, dependence. (C) 2004 Elsevier Ltd. All rights reserved

Gene expression in profiling in individual cases reveals consistent transcriptional changes in alcoholic human brain

Chronic alcohol exposure induces lasting behavioral changes, tolerance, and dependence. This results, at least partially, from neural adaptations at a cellular level. Previous genome-wide gene expression studies using pooled human brain samples showed that alcohol abuse causes widespread changes in the pattern of gene expression in the frontal and motor cortices of human brain. Because these studies used pooled samples, they could not determine variability between different individuals. In the present study, we profiled gene expression levels of 14 postmortem human brains (seven controls and seven alcoholic cases) using cDNA microarrays (46 448 clones per array). Both frontal cortex and motor cortex brain regions were studied. The list of genes differentially expressed confirms and extends previous studies of alcohol responsive genes. Genes identified as differentially expressed in two brain regions fell generally into similar functional groups, including metabolism, immune response, cell survival, cell communication, signal transduction and energy production. Importantly, hierarchical clustering of differentially expressed genes accurately distinguished between control and alcoholic cases, particularly in the frontal cortex.

Patterns of gene expression in the frontal cortex discriminate alcoholic from non-alcoholic individuals

Alcohol dependence is characterized by tolerance, physical dependence, and craving. The neuroadaptations underlying these effects of chronic alcohol abuse are likely due to altered gene expression. Previous gene expression studies using human post-mortem brain demonstrated that several gene families were altered by alcohol abuse. However, most of these changes in gene expression were small. It is not clear if gene expression profiles have sufficient power to discriminate control from alcoholic individuals and how consistent gene expression changes are when a relatively large sample size is examined. In the present study, microarray analysis (similar to 47 000 elements) was performed on the superior frontal cortex of 27 individual human cases ( 14 well characterized alcoholics and 13 matched controls). A partial least squares statistical procedure was applied to identify genes with altered expression levels in alcoholics. We found that genes involved in myelination, ubiquitination, apoptosis, cell adhesion, neurogenesis, and neural disease showed altered expression levels. Importantly, genes involved in neurodegenerative diseases such as Alzheimer's disease were significantly altered suggesting a link between alcoholism and other neurodegenerative conditions. A total of 27 genes identified in this study were previously shown to be changed by alcohol abuse in previous studies of human post-mortem brain. These results revealed a consistent re-programming of gene expression in alcohol abusers that reliably discriminates alcoholic from non-alcoholic individuals.

A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays

Motivation: An important problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. We provide a straightforward and easily implemented method for estimating the posterior probability that an individual gene is null. The problem can be expressed in a two-component mixture framework, using an empirical Bayes approach. Current methods of implementing this approach either have some limitations due to the minimal assumptions made or with more specific assumptions are computationally intensive. Results: By converting to a z-score the value of the test statistic used to test the significance of each gene, we propose a simple two-component normal mixture that models adequately the distribution of this score. The usefulness of our approach is demonstrated on three real datasets.

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.