Estrogen Modulates Hepatic Gene Expression and Survival of Rainbow Trout Infected with Pathogenic Bacteria Yersinia ruckeri

In the aquatic environment, fish are exposed to various stimuli at once and have developed different response mechanisms to deal with these multiple stimuli. The current study assessed the combined impacts of estrogens and bacterial infection on the physiological status of fish. Juvenile rainbow trout were exposed to two different concentrations of 17 beta-estradiol (E2) (2 or 20 mg/kg feed) and then infected with three concentrations of Yersinia ruckeri, a bacterial pathogen causing massive losses in wild and farmed salmonid populations. Organism-level endpoints to assess the impact of the single and combined treatments included hepatic vitellogenin transcript expression to evaluate the E2 exposure efficiency and survival rate of pathogen-challenged fish. The two E2 doses increased vitellogenin levels within the physiological range. Infection with Y. ruckeri caused mortality of trout, and this effect was significantly enhanced by a simultaneous exposure to high E2 dose. The hormone reduced survival at intermediate and high (10(4) and 10(6) colony forming units, cfu) bacterial concentrations, but not for a low one (10(2) cfu). Analysis of hepatic gene expression profiles by a salmonid 2 k cDNA microarray chip revealed complex regulations of pathways involved in immune responses, stress responses, and detoxicification pathways. E2 markedly reduced the expression of several genes implicated in xenobiotic metabolism. The results suggest that the interaction between pathogen and E2 interfered with the fish's capability of clearing toxic compounds. The findings of the current study add to our understanding of multiple exposure responses in fish.

Recursive partitioning for tumor classification with gene expression microarray data

Precise classification of tumors is critically important for cancer diagnosis and treatment. It is also a scientifically challenging task. Recently, efforts have been made to use gene expression profiles to improve the precision of classification, with limited success. Using a published data set for purposes of comparison, we introduce a methodology based on classification trees and demonstrate that it is significantly more accurate for discriminating among distinct colon cancer tissues than other statistical approaches used heretofore. In addition, competing classification trees are displayed, which suggest that different genes may coregulate colon cancers.

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.

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.

Spatial gene expression in the T-stage mouse metanephros

The E11.5 mouse metanephros is comprised of a T-stage ureteric epithelial tubule sub-divided into tip and trunk cells surrounded by metanephric mesenchyme (MM). Tip cells are induced to undergo branching morphogenesis by the MM. In contrast, signals within the mesenchyme surrounding the trunk prevent ectopic branching of this region. In order to identify novel genes involved in the molecular regulation of branching morphogenesis we compared the gene expression profiles of isolated tip, trunk and MM cells using Compugen mouse long oligo microarrays. We identified genes enriched in the tip epithelium, sim-1, Arg2, Tacstd1, Crlf-1 and BMP7; genes enriched in the trunk epithelium, Innp1, Itm2b, Mkrn1, SPARC, Emu2 and Gsta3 and genes spatially restricted to the mesenchyme surrounding the trunk, CSPG2 and CV-2, with overlapping and complimentary expression to BMP4, respectively. This study has identified genes spatially expressed in regions of the developing kidney involved in branching morphogenesis, nephrogenesis and the development of the collecting duct system, calyces, renal pelvis and ureter. (c) 2006 Elsevier B.V. All rights reserved.

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.

Comparative gene expression analysis of NKT cell subpopulations

Natural killer T (NKT) cells are a lymphocyte lineage, which has diverse immune regulatory activities in many disease settings. Most previous studies have investigated the functions of this family of cells as a single entity, but more recent evidence highlights the distinct functional and phenotypic properties of NKT cell subpopulations. It is likely that the diverse functions of NKT cells are regulated and coordinated by these different NKT subsets. Little is known about how NKT subsets differ in their interactions with the host. We have undertaken the first microarray analysis comparing the gene expression profiles of activated human NKT cell subpopulations, including CD8(+) NKT cells, which have often been overlooked. We describe the significant gene expression differences among NKT cell subpopulations and some of the molecules likely to confer their distinct functional roles. Several genes not associated previously with NKT cells were shown to be expressed differentially in specific NKT cell subpopulations. Our findings provide new insights into the NKT cell family, which may direct further research toward better manipulation of NKT cells for therapeutic applications.

Identifying cancer-related microRNAs based on gene expression data

International audience

The plant energy-dissipating mitochondrial systems: Depicting the genomic structure and the expression profiles of the gene families of uncoupling protein and alternative oxidase in monocots and dicots

The simultaneous existence of alternative oxidases and uncoupling proteins in plants has raised the question as to why plants need two energy-dissipating systems with apparently similar physiological functions. A probably complete plant uncoupling protein gene family is described and the expression profiles of this family compared with the multigene family of alternative oxidases in Arabidopsis thaliana and sugarcane (Saccharum sp.) employed as dicot and monocot models, respectively. In total, six uncoupling protein genes, AtPUMP1-6, were recognized within the Arabidopsis genome and five (SsPUMP1-5) in a sugarcane EST database. The recombinant AtPUMP5 protein displayed similar biochemical properties as AtPUMP1. Sugarcane possessed four Arabidopsis AOx1-type orthologues (SsAOx1a-1d); no sugarcane orthologue corresponding to Arabidopsis AOx2-type genes was identified. Phylogenetic and expression analyses suggested that AtAOx1d does not belong to the AOx1-type family but forms a new (AOx3-type) family. Tissue-enriched expression profiling revealed that uncoupling protein genes were expressed more ubiquitously than the alternative oxidase genes. Distinct expression patterns among gene family members were observed between monocots and dicots and during chilling stress. These findings suggest that the members of each energy-dissipating system are subject to different cell or tissue/organ transcriptional regulation. As a result, plants may respond more flexibly to adverse biotic and abiotic conditions, in which oxidative stress is involved. © The Author [2006]. Published by Oxford University Press [on behalf of the Society for Experimental Biology]. All rights reserved.

Spatial and temporal profiles for anti-inflammatory gene expression in leukocytes during a resolving model of peritonitis

The recent appreciation of the role played by endogenous counterregulatory mechanisms in controlling the outcome of the host inflammatory response requires specific analysis of their spatial and temporal profiles. In this study, we have focused on the glucocorticoid-regulated anti-inflammatory mediator annexin 1. Induction of peritonitis in wild-type mice rapidly (4 h) produced the expected signs of inflammation, including marked activation of resident cells (e.g., mast cells), migration of blood-borne leukocytes, mirrored by blood neutrophilia. These changes subsided after 48-96 h. In annexin 1null mice, the peritonitis response was exaggerated (∼40% at 4 h), with increased granulocyte migration and cytokine production. In blood leukocytes, annexin 1 gene expression was activated at 4, but not 24, h postzymosan, whereas protein levels were increased ai both time points. Locally, endothelial and mast cell annexin 1 gene expression was not detectable in basal conditions, whereas it was switched on during the inflammatory response. The significance of annexin 1 system plasticity in the anti-inflammatory properties of dexamethasone was assessed. Clear induction of annexin 1 gene in response to dexamethasone treatment was evident in the circulating and migrated leukocytes, and in connective tissue mast cells; this was associated with the steroid failure to inhibit leukocyte trafficking, cytokine synthesis, and mast cell degranulation in the annexin 1null mouse. In conclusion, understanding how inflammation is brought under control will help clarify the complex interplay between pro- and anti-inflammatory pathways operating during the host response to injury and infection. Copyright © 2006 by The American Association of Immunologists, Inc.

Changes in gene expression in PBMCs profiles of PPAR alpha target genes in obese and non-obese individuals during fasting

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Dynamics of Gene Expression Revealed by Comparison of Serial Analysis of Gene Expression Transcript Profiles from Yeast Grown on Two Different Carbon SourcesD⃞

We describe a genome-wide characterization of mRNA transcript levels in yeast grown on the fatty acid oleate, determined using Serial Analysis of Gene Expression (SAGE). Comparison of this SAGE library with that reported for glucose grown cells revealed the dramatic adaptive response of yeast to a change in carbon source. A major fraction (>20%) of the 15,000 mRNA molecules in a yeast cell comprised differentially expressed transcripts, which were derived from only 2% of the total number of ∼6300 yeast genes. Most of the mRNAs that were differentially expressed code for enzymes or for other proteins participating in metabolism (e.g., metabolite transporters). In oleate-grown cells, this was exemplified by the huge increase of mRNAs encoding the peroxisomal β-oxidation enzymes required for degradation of fatty acids. The data provide evidence for the existence of redox shuttles across organellar membranes that involve peroxisomal, cytoplasmic, and mitochondrial enzymes. We also analyzed the mRNA profile of a mutant strain with deletions of the PIP2 and OAF1 genes, encoding transcription factors required for induction of genes encoding peroxisomal proteins. Induction of genes under the immediate control of these factors was abolished; other genes were up-regulated, indicating an adaptive response to the changed metabolism imposed by the genetic impairment. We describe a statistical method for analysis of data obtained by SAGE.

Validation of reference genes for gene expression studies in the honey bee, Apis mellifera, by quantitative real-time RT-PCR

For obtaining accurate and reliable gene expression results it is essential that quantitative real-time RT-PCR (qRT-PCR) data are normalized with appropriate reference genes. The current exponential increase in postgenomic studies on the honey bee, Apis mellifera, makes the standardization of qRT-PCR results an important task for ongoing community efforts. For this aim we selected four candidate reference genes (actin, ribosomal protein 49, elongation factor 1-alpha, tbp-association factor) and used three software-based approaches (geNorm, BestKeeper and NormFinder) to evaluate the suitability of these genes as endogenous controls. Their expression was examined during honey bee development, in different tissues, and after juvenile hormone exposure. Furthermore, the importance of choosing an appropriate reference gene was investigated for two developmentally regulated target genes. The results led us to consider all four candidate genes as suitable genes for normalization in A. mellifera. However, each condition evaluated in this study revealed a specific set of genes as the most appropriated ones.

Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

Influence of the interaction between nodal fibroblast and breast cancer cells on gene expression

Our aim was to evaluate the interaction between breast cancer cells and nodal fibroblasts, by means of their gene expression profile. Fibroblast primary cultures were established from negative and positive lymph nodes from breast cancer patients and a similar gene expression pattern was identified, following cell culture. Fibroblasts and breast cancer cells (MDA-MB231, MDA-MB435, and MCF7) were cultured alone or co-cultured separated by a porous membrane (which allows passage of soluble factors) for comparison. Each breast cancer lineage exerted a particular effect on fibroblasts viability and transcriptional profile. However, fibroblasts from positive and negative nodes had a parallel transcriptional behavior when co-cultured with a specific breast cancer cell line. The effects of nodal fibroblasts on breast cancer cells were also investigated. MDA MB-231 cells viability and migration were enhanced by the presence of fibroblasts and accordingly, MDA-MB435 and MCF7 cells viability followed a similar pattern. MDA-MB231 gene expression profile, as evaluated by cDNA microarray, was influenced by the fibroblasts presence, and HNMT, COMT, FN3K, and SOD2 were confirmed downregulated in MDA-MB231 co-cultured cells with fibroblasts from both negative and positive nodes, in a new series of RT-PCR assays. In summary, transcriptional changes induced in breast cancer cells by fibroblasts from positive as well as negative nodes are very much alike in a specific lineage. However, fibroblasts effects are distinct in each one of the breast cancer lineages, suggesting that the inter-relationships between stromal and malignant cells are dependent on the intrinsic subtype of the tumor.