PACAP interactions in the mouse brain: implications for behavioral and other disorders.

As an activator of adenylate cyclase, the neuropeptide Pituitary Adenylate Cyclase Activating Peptide (PACAP) impacts levels of cyclic AMP, a key second messenger available in brain cells. PACAP is involved in certain adult behaviors. To elucidate PACAP interactions, a compendium of microarrays representing mRNA expression in the adult mouse whole brain was pooled from the Phenogen database for analysis. A regulatory network was computed based on mutual information between gene pairs using gene expression data across the compendium. Clusters among genes directly linked to PACAP, and probable interactions between corresponding proteins were computed. Database "experts" affirmed some of the inferred relationships. The findings suggest ADCY7 is probably the adenylate cyclase isoform most relevant to PACAP's action. They also support intervening roles for kinases including GSK3B, PI 3-kinase, SGK3 and AMPK. Other high-confidence interactions are hypothesized for future testing. This new information has implications for certain behavioral and other disorders.

Using the Phenogen website for 'in silico' analysis of morphine-induced analgesia: identifying candidate genes.

The identification of genes that contribute to polygenic (complex) behavioral phenotypes is a key goal of current genetic research. One approach to this goal is to combine gene expression information with genetic information, i.e. to map chromosomal regions that regulate gene expression levels. This approach has been termed 'genetical genomics', and, when used in conjunction with the identification of genomic regions (QTLs) that regulate the complex physiological trait under investigation, provides a strong basis for candidate gene discovery. In this paper, we describe the implementation of the genetical genomic/phenotypic approach to identify candidate genes for sensitivity to the analgesic effect of morphine in BXD recombinant inbred mice. Our analysis was performed 'in silico', using an online interactive resource called PhenoGen (http://phenogen.ucdenver.edu). We describe in detail the use of this resource, which identified a set of candidate genes, some of whose products regulate the cellular localization and activity of the mu opiate receptor. The results demonstrate how PhenoGen can be used to identify a novel set of genes that can be further investigated for their potential role in pain, morphine analgesia and/or morphine tolerance.

Genomic insights into acute alcohol tolerance.

Alcohol "sensitivity" has been proposed as a predictive factor for development of alcohol dependence (Schuckit et al., 2005). Most measures of alcohol sensitivity in humans and animals include a component that can be ascribed to acute functional tolerance (AFT). AFT is a form of tolerance that develops within a single period of alcohol exposure and has a genetic component. We used microarray technology as well as quantitative trait locus analysis of phenotypic and gene expression data across 30 BXD recombinant inbred strains of mice, 20 inbred strains of mice, and two replicate lines of mice selectively bred for differences in AFT, to identify differentially expressed candidate genes that contribute to predisposition to AFT. Eight candidate genes were identified by our statistical and filtering methods. The location of brain expression of these genes was mapped using the Allen Brain Atlas (http://www.brain-map.org), and the transcript location and molecular pathway analysis indicated that brain structures and biochemical pathways implicated in long-term potentiation and memory might also participate in the generation of acute functional alcohol tolerance.

The genomic determinants of alcohol preference in mice.

Searches for the identity of genes that influence the levels of alcohol consumption by humans and other animals have often been driven by presupposition of the importance of particular gene products in determining positively or negatively reinforcing effects of ethanol. We have taken an unbiased approach and performed a meta-analysis across three types of mouse populations to correlate brain gene expression with levels of alcohol intake. Our studies, using filtering procedures based on QTL analysis, produced a list of eight candidate genes with highly heritable expression, which could explain a significant amount of the variance in alcohol preference in mice. Using the Allen Brain Atlas for gene expression, we noted that the candidate genes' expression was localized to the olfactory and limbic areas as well as to the orbitofrontal cortex. Informatics techniques and pathway analysis illustrated the role of the candidate genes in neuronal migration, differentiation, and synaptic remodeling. The importance of olfactory cues, learning and memory formation (Pavlovian conditioning), and cortical executive function, for regulating alcohol intake by animals (including humans), is discussed.

Expression quantitative trait loci and the PhenoGen database.

Researchers from a wide variety of backgrounds and with a broad range of goals have utilized high-throughput screening technologies (i.e., microarray technologies) to identify candidate genes that may be associated with an observable characteristic or behavior (i.e., phenotype) of interest. However, the initial microarray analyses typically also yield many genes that are not related to the phenotype of interest. Therefore, additional analyses are necessary to select the most likely candidates and eventually identify one or more genes that actually underlie that phenotype. After briefly explaining how microarray data are generated, this article describes one approach to narrowing down the resulting candidate genes and a database that can help in this analysis.

How adaptation of the brain to alcohol leads to dependence: a pharmacological perspective.

The development of alcohol dependence is posited to involve numerous changes in brain chemistry (i.e., neurotransmission) that lead to physiological signs of withdrawal upon abstinence from alcohol as well as promote vulnerability to relapse in dependent people. These neuroadaptive changes often occur in those brain neurotransmission systems that are most sensitive to the acute, initial effects of alcohol and/or contribute to a person's initial alcohol consumption. Studies of these neuroadaptive changes have been aided by the development of animal models of alcohol dependence, withdrawal, and relapse behavior. These animal models, as well as findings obtained in humans, have shed light on the effects that acute and chronic alcohol exposure have on signaling systems involving the neurotransmitters glutamate, γaminobutyric acid (GABA), dopamine, and serotonin, as well as on other signaling molecules, including endogenous opioids and corticotrophin-releasing factor (CRF). Adaptation to chronic alcohol exposure by these systems has been associated with behavioral effects, such as changes in reinforcement, enhanced anxiety, and increased sensitivity to stress, all of which may contribute to relapse to drinking in abstinent alcoholics. Moreover, some of these systems are targets of currently available therapeutic agents for alcohol dependence.

The PhenoGen informatics website: tools for analyses of complex traits.

BACKGROUND: With the advent of "omics" (e.g. genomics, transcriptomics, proteomics and phenomics), studies can produce enormous amounts of data. Managing this diverse data and integrating with other biological data are major challenges for the bioinformatics community. Comprehensive new tools are needed to store, integrate and analyze the data efficiently. DESCRIPTION: The PhenoGen Informatics website http://phenogen.uchsc.edu is a comprehensive toolbox for storing, analyzing and integrating microarray data and related genotype and phenotype data. The site is particularly suited for combining QTL and microarray data to search for "candidate" genes contributing to complex traits. In addition, the site allows, if desired by the investigators, sharing of the data. Investigators can conduct "in-silico" microarray experiments using their own and/or "shared" data. CONCLUSION: The PhenoGen website provides access to tools that can be used for high-throughput data storage, analyses and interpretation of the results. Some of the advantages of the architecture of the website are that, in the future, the present set of tools can be adapted for the analyses of any type of high-throughput "omics" data, and that access to new tools, available in the public domain or developed at PhenoGen, can be easily provided.

Gene array profiles of alcohol and aldehyde metabolizing enzymes in brains of C57BL/6 and DBA/2 mice.

BACKGROUND: Differences in ethanol metabolizing enzymes expressed in brain have been suggested to contribute to the significant differences in ethanol (alcohol) preference between inbred C57BL/6 and DBA/2 mouse strains. METHODS: We have utilized 2 different platforms of oligonucleotide microarray technology (CodeLink UniSet I BioArray from G.E. Healthcare and MG U74A v2.0 from Affymetrix) to simultaneously assess expression of alcohol and acetaldehyde metabolizing enzymes in the whole brain of naïve (no exposure to alcohol) C57BL/6 and DBA/2 mice. RESULTS: There were no significant differences between the 2 strains of mice in gene expression intensity for alcohol dehydrogenases (ADH), catalase, and a number of the cytochrome P450 family of genes, which can be involved in ethanol catabolism. However, significantly higher expression of mRNA for aldehyde dehydrogenase 2 (ALDH2), an isoform mainly responsible for the catabolism of acetaldehyde, was observed in whole brains of DBA/2 mice with both platforms. Aldehyde dehydrogenase 2 protein was also higher in DBA/2 brain. Expression of aldehyde dehydrogenase 1A1 (ALDH1A1) mRNA was found to be higher in brains of DBA/2 mice, when measured with the CodeLink platform, but not when measured with Affymetrix arrays or quantitative reverse transcriptase-real-time polymerase chain reaction (qRT-PCR). The ALDH1A1 protein, however, reflected the results obtained with the CodeLink arrays and was higher in DBA/2 brain, compared with brains of C57BL/6 mice. In contrast, the expression intensity for the aldehyde dehydrogenase 7A1 (ALDH7A1) mRNA and protein was significantly higher in C57BL/6 mice than DBA/2 mice. These expression differences are consistent with more rapid metabolism of acetaldehyde in brains of DBA/2 mice. CONCLUSIONS: The use of 2 different microarray platforms provides important cross-validation of many results, and some discrepancies can be resolved with qRT-PCR and immunoblotting. The expression differences that were validated may affect alcohol/aldehyde metabolism in brain and/or alcohol preference in the 2 strains of mice.

Candidate genes and their regulatory elements: alcohol preference and tolerance.

QTL analysis of behavioral traits and mouse brain gene expression studies were combined to identify candidate genes involved in the traits of alcohol preference and acute functional alcohol tolerance. The systematic application of normalization and statistical analysis of differential gene expression, behavioral and expression QTL location, and informatics methodologies resulted in identification of 8 candidate genes for the trait of alcohol preference and 22 candidate genes for acute functional tolerance. Pathway analysis, combined with clustering by ontology, indicated the importance of transcriptional regulation and DNA and protein binding elements in the acute functional tolerance trait, and protein kinases and intracellular signal transduction elements in the alcohol preference trait. A rudimentary search for transcription control elements that could indicate coregulation of the panels of candidate genes produced modest results, implicating SMAD-3 in the regulation of four of the eight candidate genes for alcohol preference. However, the realization of the many caveats related to transcription factor binding site analysis, and attempts to correlate between transcription factor binding and function, forestalled any definitive global analysis of transcriptional control of differentially expressed candidate genes.

Complex genetics of interactions of alcohol and CNS function and behavior.

This work summarizes the proceedings of a symposium at the 2004 RSA Meeting in Vancouver, Canada. The organizers were R. W. Williams and D. B. Matthews; the Chair was M. F. Miles. The presentations were (1) WebQTL: A resource for analysis of gene expression variation and the genetic dissection of alcohol related phenotypes, by E. J. Chesler, (2) The marriage of microarray and qtl analyses: what's to gain, by J. K. Belknap, (3) Use of WebQTL to identify QTLs associated with footshock stress and ethanol related behaviors, by D. B. Matthews, (4) A high throughput strategy for the detection of quantitative trait genes, by R. J. Hitzemann, and (5) The use of gene arrays in conjunction with transgenic and selected animals to understand anxiety in alcoholism, by. B. Tabakoff.

Phosphatidylinositol 3'-OH kinase and protein kinase A pathways mediate the anti-apoptotic effect of pituitary adenylyl cyclase-activating polypeptide in cultured cerebellar granule neurons: modulation by ethanol.

Cerebellar granule neurons cultured in the presence of 5 mm KCl undergo spontaneous apoptosis, which is reduced by exposure to pituitary adenylyl cyclase-activating polypeptide (PACAP). Previous work has suggested roles for the cyclic AMP/PKA and MAP kinase signaling pathways in the anti-apoptotic effect of PACAP. In the present study, the use of specific inhibitors confirmed the role of the cyclic AMP/PKA pathway, and also demonstrated a role for the phosphatidylinositol 3'-OH kinase (PI 3-kinase) neuroprotective pathway in the action of PACAP. Ethanol exposure accelerates the anti-apoptotic effect of PACAP by a mechanism that involves the PKA and PI-3 kinase pathways. The results demonstrate that ethanol can increase neuroprotection induced by PACAP. As previous work has shown that ethanol can increase apoptosis of cerebellar granule neurons by inhibiting the protective effect of agents such as NMDA or IGF-1, the overall effect of ethanol on cerebellar neuron apoptosis during development may reflect the balance between inhibition and enhancement of the actions of various endogenous neuroprotective agents.

Selective breeding, quantitative trait locus analysis, and gene arrays identify candidate genes for complex drug-related behaviors.

Acute functional tolerance to ethanol develops during a single exposure to ethanol; it has been suggested to be a predisposing factor for the development of ethanol dependence. Genetic determinants of acute functional tolerance, as well as of ethanol dependence, have been clearly demonstrated. We describe a novel approach that uses a combination of selective breeding (to segregate genes contributing to the phenotype of interest, i.e., acute functional tolerance to the incoordinating effect of ethanol), quantitative trait locus analysis (to define chromosomal regions associated with acute functional tolerance), and DNA microarray technology (to identify differentially expressed genes in the brains of the selected lines of mice) to identify candidate genes for the complex phenotype of ethanol tolerance. The results indicate the importance of a signal transduction cascade that involves the glutamate receptor delta2 protein, the Ephrin B3 ligand, and the NMDA receptor, as well as a transcriptional regulatory protein that may be induced by activation of the NMDA receptor (zinc finger protein 179) and a protein that can modulate downstream responses to NMDA receptor activation (peroxiredoxin), in mediating acute tolerance to the incoordinating effect of ethanol.