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Cytokine gene expression: analysis using northern blotting, polymerase chain reaction and in situ hybridization.

We describe here the use of northern blotting, PCR and in situ hybridization for the analysis of cytokine gene expression. These techniques, each with their advantages and disadvantages, have been used to monitor cytokine gene expression in sites of immune reactivity and in the developing thymus. Whilst expression of a gene usually correlates well with protein production from that gene, this may not always be the case. The development of methods to analyze protein production in situ, for instance by immunohistochemistry, together with analysis of mRNA expression will allow us to begin to understand the role of cytokines within the immune system of the intact animal.

Animals↗

Comparative gene expression analysis by differential clustering approach: application to the Candida albicans transcription program.

Differences in gene expression underlie many of the phenotypic variations between related organisms, yet approaches to characterize such differences on a genome-wide scale are not well developed. Here, we introduce the "differential clustering algorithm" for revealing conserved and diverged co-expression patterns. Our approach is applied at different levels of organization, ranging from pair-wise correlations within specific groups of functionally linked genes, to higher-order correlations between such groups. Using the differential clustering algorithm, we systematically compared the transcription program of the fungal pathogen Candida albicans with that of the model organism Saccharomyces cerevisiae. Many of the identified differences are related to the differential requirement for mitochondrial function in the two yeasts. Distinct regulation patterns of cell cycle genes and of amino acid metabolic genes were also revealed and, in some cases, could be linked to the differential appearance of cis-regulatory elements in the gene promoter regions. Our study provides a comprehensive framework for comparative gene expression analysis and a rich source of hypotheses for uncharacterized open reading frames and putative cis-regulatory elements in C. albicans.

Candida albicans↗

Candidate genes affecting Drosophila life span identified by integrating microarray gene expression analysis and QTL mapping.

The current increase in life expectancy observed in industrialized societies underscores the need to achieve a better understanding of the aging process that could help the development of effective strategies to achieve healthy aging. This will require not only identifying genes involved in the aging process, but also understanding how their effects are modulated by environmental factors, such as dietary intake and life style. Although the human genome has been sequenced, it may be impractical to study humans or other long-lived organisms to gain a mechanistic understanding about the aging process. Thus, short-lived animal models are essential to identifying the mechanisms and genes that affect the rate and quality of aging as a first step towards identifying genetic variants in humans. In this study, we investigated gene expression changes between two strains of Drosophila (Oregon and 2b) for which quantitative trait loci (QTLs) affecting life span were identified previously. We collected males and females from both strains at young and old ages, and assessed whole genome variation in transcript abundance using Affymetrix GeneChips. We observed 8217 probe sets with detectable transcripts. A total of 2371 probe sets, representing 2220 genes, exhibited significant changes in transcript abundance with age; and 839 probe sets were differentially expressed between Oregon and 2b. We focused on the 359 probe sets (representing 354 genes) that exhibited significant changes in gene expression both with age and between strains. We used these genes to integrate the analysis of microarray gene expression data, bioinformatics, and the results of genetic mapping studies reported previously, to identify 49 candidate genes and four pathways that could potentially be responsible for regulating life span and involved in the process of aging in Drosophila and humans.

Aging↗

Gene expression analysis of strawberry achene and receptacle maturation using DNA microarrays.

Large-scale, single pass sequencing and parallel gene expression analysis using DNA microarrays were employed for the comprehensive investigation of ripening in strawberry fruit. A total of 1701 cDNA clones (comprising 1100 strawberry ESTs and 601 unsequenced cDNAs) obtained from a strawberry (Fragariaxananassa) ripe fruit cDNA library were displayed on microarrays, and used for monitoring concurrent gene expression in receptacle and achene tissues. Analysis of expression ratios identified 66 out of the 259 (25%) achene-related clones and 80 out of 182 (44%) receptacle-related clones with more than a 4-fold difference in expression between the two tissue types. Half of the achene-associated genes putatively encode proteins with unknown function, and a large number of the remainder were proteins predicted to form part of the signal and regulation cascades related to achene maturation and acquisition of stress and desiccation tolerance. These included phosphatases, protein kinases, 14-3-3 proteins, transcription factors, and others. In the receptacle, key processes and novel genes that could be associated with ripening were identified. Genes putatively encoding proteins related to stress, the cell wall, DNA/RNA/protein, and primary metabolism were highly represented. Apart from providing a global observation on gene expression programmes and metabolic pathways in the developing strawberry, this study has made available a large database and unique information for gene discovery, promoter selection and markers for molecular breeding approaches.

Abscisic Acid↗

A hybrid SOM-SVM approach for the zebrafish gene expression analysis.

Microarray technology can be employed to quantitatively measure the expression of thousands of genes in a single experiment. It has become one of the main tools for global gene expression analysis in molecular biology research in recent years. The large amount of expression data generated by this technology makes the study of certain complex biological problems possible, and machine learning methods are expected to play a crucial role in the analysis process. In this paper, we present our results from integrating the self-organizing map (SOM) and the support vector machine (SVM) for the analysis of the various functions of zebrafish genes based on their expression. The most distinctive characteristic of our zebrafish gene expression is that the number of samples of different classes is imbalanced. We discuss how SOM can be used as a data-filtering tool to improve the classification performance of the SVM on this data set.

Animals↗

Direct gene expression analysis.

The direct analysis of single biological molecules is getting increasingly important in basic as well as pharmaceutical research (e.g. for gene expression analysis). In particular single-molecule fluorescence detection provides exciting new opportunities to probe biochemical processes in unprecedented detail. Currently several academic and industrial research groups work on the development of single molecule detection based technologies in order to directly detect and analyze RNA and DNA molecules. As these developed methods are characterized as homogenous assays and obviate any amplification of the target or the signal, they provide clear advantages compared to methods like real-time PCR or DNA- arrays. In the following we describe a recently developed approach based on fluorescence correlation spectroscopy (FCS). This expression assay is based on gene-specific hybridization of two dye-labeled DNA probes to a selected target molecule (either DNA or RNA) in solution. The subsequent dual color cross-correlation analysis allows the quantification of the bio-molecule of interest in absolute numbers. Target concentrations of less than 10(-12) M can be easily monitored, covering the direct analysis of the expression levels of high, medium and low abundant genes.

Animals↗

An evaluation of tyramide signal amplification and archived fixed and frozen tissue in microarray gene expression analysis.

Archival formalin-fixed, paraffin-embedded and ethanol-fixed tissues represent a potentially invaluable resource for gene expression analysis, as they are the most widely available material for studies of human disease. Little data are available evaluating whether RNA obtained from fixed (archival) tissues could produce reliable and reproducible microarray expression data. Here we compare the use of RNA isolated from human archival tissues fixed in ethanol and formalin to frozen tissue in cDNA microarray experiments. Since an additional factor that can limit the utility of archival tissue is the often small quantities available, we also evaluate the use of the tyramide signal amplification method (TSA), which allows the use of small amounts of RNA. Detailed analysis indicates that TSA provides a consistent and reproducible signal amplification method for cDNA microarray analysis, across both arrays and the genes tested. Analysis of this method also highlights the importance of performing non-linear channel normalization and dye switching. Furthermore, archived, fixed specimens can perform well, but not surprisingly, produce more variable results than frozen tissues. Consistent results are more easily obtainable using ethanol-fixed tissues, whereas formalin-fixed tissue does not typically provide a useful substrate for cDNA synthesis and labeling.

Animals↗

Multiplex gene expression analysis for high-throughput drug discovery: screening and analysis of compounds affecting genes overexpressed in cancer cells.

Drug discovery strategies are needed that can rapidly exploit multiple therapeutic targets associated with the complex gene expression changes that characterize a polygenic disease such as cancer. We report a new cell-based high-throughput technology for screening chemical libraries against several potential cancer target genes in parallel. Multiplex gene expression (MGE) analysis provides direct and quantitative measurement of multiple endogenous mRNAs using a multiplexed detection system coupled to reverse transcription-PCR. A multiplex assay for six genes overexpressed in cancer cells was used to screen 9000 chemicals and known drugs in the human prostate cancer cell line PC-3. Active compounds that modulated gene expression levels were identified, and IC50 values were determined for compounds that bind DNA, cell surface receptors, and components of intracellular signaling pathways. A class of steroids related to the cardiac glycosides was identified that potently inhibited the plasma membrane Na(+)K(+)-ATPase resulting in the inhibition of four of the prostate target genes including transcription factors Hoxb-13, hPSE/PDEF, hepatocyte nuclear factor-3alpha, and the inhibitor of apoptosis, survivin. Representative compounds selectively induced apoptosis in PC-3 cells compared with the nonmetastatic cell line BPH-1. The multiplex assay distinguished potencies among structural variants, enabling structure-activity analysis suitable for chemical optimization studies. A second multiplex assay for five toxicological markers, Hsp70, Gadd153, Gadd45, O6-methylguanine-DNA methyltransferase, and cyclophilin, detected compounds that caused DNA damage and cellular stress and was a more sensitive and specific indicator of potential toxicity than measurement of cell viability. MGE analysis facilitates rapid drug screening and compound optimization, the simultaneous measurement of toxicological end points, and gene function analysis.

Actins↗

Gene expression analysis of distinct populations of cells isolated from mouse and human inner ear FFPE tissue using laser capture microdissection--a technical report based on preliminary findings.

Laser Capture Microdissection (LCM) allows microscopic procurement of specific cell types from tissue sections that can then be used for gene expression analysis. We first tested this method with sections of adult mouse inner ears and subsequently applied it to human inner ear sections. The morphology of the various cell types within the inner ear is well preserved in formalin fixed paraffin embedded (FFPE) sections, making it easier to identify cell types and their boundaries. Recovery of good quality RNA from FFPE sections can be challenging, however, recent studies in cancer research demonstrated that it is possible to carry out gene expression analysis of FFPE material. Thus, a method developed using mouse FFPE tissue can be applied to human archival temporal bones. This is important because the majority of human temporal bone banks have specimens preserved in formalin and a technique for retrospective analysis of human archival ear tissue is needed. We used mouse FFPE inner ear sections to procure distinct populations of cells from the various functional domains (organ of Corti, spiral ganglion, etc.) by LCM. RNA was extracted from captured cells, amplified, and assessed for quality. Expression of selected genes was tested by RT-PCR. In addition to housekeeping genes, we were able to detect cell type specific markers, such as Myosin 7a, p27(kip1) and neurofilament gene transcripts that confirmed the likely composition of cells in the sample. We also tested the method described above on FFPE sections from human crista ampullaris. These sections were approximately a year old. Populations of cells from the epithelium and stroma were collected and analyzed independently for gene expression. The method described here has potential use in many areas of hearing research. For example, following exposure to noise, ototoxic drugs or age, it would be highly desirable to analyze gene expression profiles of selected populations of cells within the organ of Corti or spiral ganglion cells rather than a mixed population of cells from whole inner ear tissue. Also, this method can be applied for analysis of human archival ear tissue.

Animals↗

Gene expression analysis of single neoplastic cells and the pathogenesis of Hodgkin's lymphoma.

The origin of the Reed-Sternberg cell of Hodgkin's disease remained clouded in mystery for almost a century after its discovery in 1898. The major obstacle to its understanding is that, unlike other cancers, the malignant cell of Hodgkin's disease is vastly outnumbered by surrounding non-neoplastic cells at approximately 1000:1. We have devised several strategies to isolate Reed-Sternberg T-cells to determine their origin, global gene expression and, ultimately, their pathogenesis. This has increased the number of genes known to be expressed in Reed-Sternberg cells by >100-fold to over 12,000. Approaches such as density gradients, microdissection, and cell sorting help to enrich Reed-Sternberg cells for genomic DNA analysis. However, single-cell micromanipulation of living Reed-Sternberg cells was required to determine the genome-wide gene expression profile of these cells. Combined analysis of single cells and cell lines revealed the expression of 2666 named genes. Further analysis with high-density gene expression microarrays has demonstrated the expression of approximately 12,000 genes by Reed-Sternberg cells. The gene expression profile is that of an aberrant germinal center B-lymphocyte that resists apoptosis through CD40 signaling and NFkappaB activation. Gene expression analysis of Hodgkin's disease is an extreme test case demonstrating the application of high-throughput gene expression studies even to individual cells from clinical samples.

B-Lymphocytes↗

Assessment of representational difference analysis (RDA) to construct informative cDNA microarrays for gene expression analysis of species with limited transcriptome information, using red and green tomatoes as a model.

Microarray technology makes it feasible to analyse the expression of thousands of different gene elements in a single experiment. Most informative are 'whole genome' arrays, where all gene expression products of a single species or variety are represented. Such arrays are now available for a limited number of model species. However, for other, less well-documented species other routes are still necessary to obtain informative arrays. This includes the use of cDNA libraries. To enhance the amount of information that can be obtained from cDNA libraries, redundancy needs to be minimised, and the number of cDNAs relevant for the conditions of interest needs to be increased. Here, we used representational difference analysis (RDA), a mRNA subtraction procedure, as a tool to enhance the efficiency of cDNA libraries to be used to generate microarrays. Tomato was chosen as a model system for a less well-documented species. cDNA libraries for two distinct physiological conditions of tomato fruits, red and green, were made. The libraries were characterized by sequencing and hybridisation analysis. The RDA procedure was shown to be effective in selecting for genes of relevance for the physiological conditions under investigation, and against constitutively expressed genes. At the same time, redundancy was reduced, but complete normalisation was not obtained, and subsequent sequence analysis will be required to obtain non-redundant arrays. Further, known and putative ripening-related cDNAs were identified in hybridisation experiments on the basis of RNA populations as isolated from the green and red stage of ripening.

Fruit↗

In situ gene expression analysis of cancer using laser capture microdissection, microarrays and real time quantitative PCR.

The simultaneous development of laser capture microdissection (LCM) and high-throughput mRNA analysis platforms has provided a significant technological advance in the world of cancer biology. The combination of such technologies provides a unique and powerful opportunity to directly assess the in situ molecular genetic events that are associated with initiation and progression of human malignancies. Despite these technological advances, the integration of LCM with high-throughput gene expression analysis has been met with various challenges. The goal of this review is to highlight some of the obstacles that we have faced and continue to face as we try to optimally apply LCM to in situ gene expression analysis.

Gene Expression Regulation, Neoplastic↗

Gene expression analysis reveals that histone deacetylation sites may serve as partitions of chromatin gene expression domains.

BACKGROUND: It has been a long-term puzzle whether chromatin can be further divided into distinct gene expression domains. Because histone deacetylation affects chromatin structure, that in turn may affect the expression of nearby genes, histone deacetylation sites may act to partition chromatin into different gene expression domains. In this article, we explore the relationship between histone deacetylation sites and gene expression patterns on the genome scale using different data sources, including microarray data measuring gene expression levels, microarray data measuring histone deacetylation sites, and information on regulatory targets of transcription factors. RESULTS: Using 269 Saccharomyces cerevisiae microarray datasets, histone deacetylation datasets, and regulatory targets of transcription factors assembled from the Yeast Proteome Database and ChIP-chip data, we found that histone deacetylation sites can reduce the level of co-expression of neighboring genes. CONCLUSION: Histone deacetylation sites may serve as possible partition sites for chromatin domains and affect gene expression.

Binding Sites↗

Large scale gene expression analysis of osteoclastogenesis in vitro and elucidation of NFAT2 as a key regulator.

To understand the molecular events coupling between cell proliferation and differentiation by elucidating genes essential for the process, we conducted a large scale gene expression analysis of an in vitro osteoclastogenesis system consisting of recombinant RANKL and mouse RAW264 cells. The entire process leading to the formation of tartrate resistant acid phosphatase-positive multinucleated cells takes 3 days and plates become fully covered with multinucleated cells at 4 days. Microarray probing at eight time points revealed 635 genes that showed greater than 2-fold differential expression for at least one time point and they could be classified into six groups by the "k-means" clustering analysis. Among a group of 106 early inducible genes (within 2-5 h after RANKL stimulation), four genes including NFAT2 were identified as genes whose enhanced expressions were fairly correlated with an efficient induction of matured osteoclasts. Moreover, cyclosporin A significantly suppressed the multinucleated cell formation accompanying the reduction of the nuclear localization of NFAT2. When the expression of NFAT2 was suppressed by introducing antisense NFAT2, multinucleated cell formation was severely hampered. Functional analysis thus combined with gene analysis by microarray technology elucidated a key role of NFAT2 in osteoclastogenesis in vitro.

Animals↗

Gene expression analysis with universal n-mer arrays.

Gene expression profiling is one of the many applications that have benefited from the massively parallel nucleic acid detection capability of DNA microarrays. Current expression arrays, however, are expensive and inflexible. They are custom-designed for each organism and they do not offer the possibility of incorporating updated genomic information without production of a new chip. One possible solution is the development of a universal chip, consisting of all 4n possible DNA sequences of length n. Studying different organisms or new genes would simply require modifications to the hybridization pattern analysis software. The key problem is to find a value of n that is large enough to afford sufficient specificity, yet is small enough for practical fabrication and readout. We developed an analytical model, supported by computer-assisted calculation with yeast and mouse transcript data, to argue that it is both practical and useful to fabricate n-mer arrays with 10 < or = n < or = 16.

Alternative Splicing↗

The use of gene expression analysis and proteomic databases in the development of a screening system to determine the value of natural medicinal products.

A rapid throughput screening system involving gene expression analysis was developed in order to investigate the potential of bioactive chemicals contained in natural health products as effective drug therapy, in particular the ability of these chemicals to alleviate the inflammatory response in human airway epithelial cells. A number of databases were searched to retrieve the information needed to properly analyze the gene expression profiles obtained. The gene expression of human bronchial epithelial cells infected with rhinovirus and/or exposed to platelet activating factor was analyzed. Following analysis of the gene expression data the total number of expressed proteins that may potentially act as a marker for monitoring the modulation of airway inflammation was narrowed to 19. Further studies will involve selecting antibodies for these proteins, culturing airway epithelial cells in the presence of extracts of natural health products, extracting the proteins and identifying them by western blot analysis.

Journal Article↗

Integrated assessment by multiple gene expression analysis of quercetin bioactivity on anticancer-related mechanisms in colon cancer cells in vitro.

BACKGROUND: Many different mechanisms are involved in nutrient-related prevention of colon cancer. In this study, a comprehensive assessment of the spectrum of possible biological actions of the bioactive compound quercetin is made using multiple gene expression analysis. Quercetin is a flavonoid that can inhibit proliferation of tumor cells and reduce the number of aberrant crypt foci, although increase of number of colon tumors was also reported. AIM OF THE STUDY: In order to elucidate possible mechanisms involved in its mode of action the effect of quercetin on expression of 4000 human genes in Caco-2 cells was studied and related to functional effects. METHODS: Caco-2 cells were exposed to 5 or 50 microM quercetin for 48 hours, differential expression of 4000 human genes was studied using microarrays and related to functional effects. Differentially expressed genes were categorized in seven functional groups: cell cycle and differentiation, apoptosis, tumor suppressor genes and oncogenes, cell adhesion and cell-cell interaction, transcription, signal transduction and energy metabolism. Also, cell proliferation and cell cycle distribution were measured. RESULTS: Quercetin (5 microM) downregulated expression of cell cycle genes (for example CDC6, CDK4 and cyclin D1), downregulated cell proliferation and induced cell cycle arrest in Caco-2 cells. After exposure to 50 microM quercetin cell proliferation decreased to 51.3% of control, and further decrease of the percentage of cells in the G1 phase coincided with an increase of the percentage of cells in the sub-G1 phase. Quercetin upregulated expression of several tumor suppressor genes. In addition, genes involved in signal transduction pathways like beta catenin/TCF signalling and MAPK signal transduction were influenced by quercetin. CONCLUSIONS: This study shows that large-scale gene expression analysis in combination with functional assays yields a considerable amount of information on (anti-)carcinogenic potential of food components like quercetin.

Antineoplastic Agents↗