Biomedical discovery with DNA arrays

Expression of cytochrome P4502E1 gene in hepatocellular carcinoma

AIM: To investigate cytpchrome P4502E1 (CYP2E1) gene expression in occurrence and progression of hepatocellular carcinoma (HCC).

METHODS: The human liver arrayed library was spotted onto the nylon membranes to make cDNA array. Hybridization of cDNA array was performed with labeled probes synthesized from RNA isolated from HCC and adjacent liver tissues. Sprague-Dawley rats were administrated diethylnitrosamine (DENA) to induce HCC. CYP2E1 expression was detected by the method of RT-PCR and Northern blot analysis.

RESULTS: CYP2E1 was found by cDNA array hybridization to express differently between HCC and liver tissues. CYP2E1 only expressed in liver, but did not express in HCC tissues and expressed lowly in cirrhotic tissues. In the progression of cirrhosis and HCC, the expression level of CYP2E1 was gradually decreased and hardly detected until the late stage of HCC.

CONCLUSION: Using arrayed library to make cDNA arrays is an effective method to find differential expression genes. CYP2E1 is a unique gene expressing in liver but did not express in HCC. CYP2E1 expression descended along with the initiation and progression of HCC, which is noteworthy further investigations in its significance in the development of HCC.

Comprehensive search for HNF-1beta-regulated genes in mouse hepatoma cells perturbed by transcription regulatory factor-targeted RNAi

The identification of genes targeted by a specific transcription regulatory factor (TRF) is essential to our understanding of the regulatory mechanism of gene expression. We constructed a system for the comprehensive identification of genes directly regulated by a TRF. It includes a combination of perturbation of gene expression by RNA interference (RNAi) of the TRF, cDNA microarray analysis, computer searches for the putative TRF recognition sequences, and in vivo and in vitro TRF-DNA binding assays. Endogenous hepatocyte nuclear factor-1beta (HNF-1beta) mRNA was efficiently degraded by transfection of mouse hepatoma cells with short interfering RNAs. Expression profile analysis with 20 K mouse cDNA microarrays detected 243 genes whose expression levels were decreased by >50% upon RNAi of HNF-1beta. The upstream regions of the top 26 downregulated genes were searched for the HNF-1beta consensus recognition sequences leading to the extraction of 13 candidate genes. Finally, TRF-DNA binding assays identified five novel as well as three known HNF-1beta-regulated genes. In combination with quantitative real-time RT-PCR, the present system revealed the existence of a more expanded regulatory network among seven HNF family members, demonstrating its practicability to identify the TRF network as well as genes directly regulated by a specific TRF.

Gene expression profiles in dendritic cells conditioned by 1alpha,25-dihydroxyvitamin D3 analog

Inhibition of dendritic cell (DC) maturity is an important immunomodulatory effect of 1alpha,25-dihydroxyvitamin D(3) (1alpha,25(OH)(2)D(3)) and related analogs (D(3) analogs). The mechanisms underlying 1alpha,25(OH)(2)D(3)-mediated DC modulation are Vitamin D receptor (VDR)-dependent and likely involve direct or indirect regulation of multiple genes. Gene expression profiles of bone marrow-derived DCs (BMDCs) generated in the absence or presence of a potent D(3) analog were analyzed using microarray technology. Results for D(3) analog-conditioned DCs were also compared with glucocorticoid-conditioned BMDCs and with BMDCs conditioned with D(3) analog and glucocorticoid combined. Of approximately 12,000 gene products assayed, 52% were considered to have detectable expression in unconditioned BMDCs. Based on relative expression levels, 5.3% of these expressed genes were "silenced" or "suppressed" in D(3) analog-conditioned BMDCs and 2.1% were "augmented". In addition, 1.7% of gene products undetectable in control BMDCs were "induced" by D(3) analog. Functional grouping of modulated genes demonstrated important effects of D(3) analog on immunoreceptors, on chemokines and chemokine receptors, on growth factors/cytokines and related receptors, and on neuroendocrine hormones and related receptors. Many of these gene products were unaffected or differently regulated by glucocorticoid suggesting specific VDR-mediated regulatory effects. Confirmation of microarray analysis results for two differentially regulated chemokines (MIP-1alpha and RANTES) was obtained by RT-PCR and ELISA. The methodology provides novel insights into DC gene regulation by 1alpha,25(OH)(2)D(3) agonists.

Gene expression in the developing rat mandible: a gene array study

To analyse the molecular events that occur in the developing mandible, gene arrays containing probes for 1176 known genes were used. Total RNA was extracted from the mandibles of 1- and 6-day-old rats. Radiolabeled probes were then synthesised and used to probe the DNA arrays. Of the 1176 genes examined, 306 were detectable, and the latter were analyzed by bioinformatics algorithms. K-means clustering grouped 72 genes into Up, 56 genes into Down and 178 genes into NO change. A large number of genes related to cell receptors (by ligands) were grouped into the Down cluster. Gene array technology appears to be a useful tool for studying the complex process of mandibular development.

Identification and handling of artifactual gene expression profiles emerging in microarray hybridization experiments

Mathematical methods of analysis of microarray hybridizations deal with gene expression profiles as elementary units. However, some of these profiles do not reflect a biologically relevant transcriptional response, but rather stem from technical artifacts. Here, we describe two technically independent but rationally interconnected methods for identification of such artifactual profiles. Our diagnostics are based on detection of deviations from uniformity, which is assumed as the main underlying principle of microarray design. Method 1 is based on detection of non-uniformity of microarray distribution of printed genes that are clustered based on the similarity of their expression profiles. Method 2 is based on evaluation of the presence of gene-specific microarray spots within the slides' areas characterized by an abnormal concentration of low/high differential expression values, which we define as 'patterns of differentials'. Applying two novel algorithms, for nested clustering (method 1) and for pattern detection (method 2), we can make a dual estimation of the profile's quality for almost every printed gene. Genes with artifactual profiles detected by method 1 may then be removed from further analysis. Suspicious differential expression values detected by method 2 may be either removed or weighted according to the probabilities of patterns that cover them, thus diminishing their input in any further data analysis.

Single-channel quantitative multiplex reverse transcriptase-polymerase chain reaction for large numbers of gene products differentiates nondemented from neuropathological Alzheimer's disease

Effective approaches using array technologies are critical to understand the molecular bases of human diseases. The results obtained using such procedures require analysis and validation procedures that are still under development. In the context of Alzheimer's disease, in which the identification of molecular mechanisms of underlying pathologies is vital, we describe a robust assay that is the first real-time reverse transcriptase-polymerase chain reaction-based high-throughput approach that can simultaneously quantitate the expression of a large number of genes at the copy number level from a minute amount of starting material. Using this approach within the human brain, we were able to quantitate as many as 19 genes at a time with only one type of fluorescent probe. The number of genes included can be considerably increased. Examples of consistent changes in Alzheimer's disease within these 19 candidate genes included reductions in targets related to the dendritic and synaptic apparatus. These changes were specific to Alzheimer's disease when compared with Parkinson's disease cases. We also present comparison data with microarray analysis from the same brain region and the same patients. The high sensitivity and reproducibility of this technology coupled with appropriate multivariate analysis is proposed here to form a biotechnology platform that can be widely used for diagnostic purposes as well as basic research.

Cluster Analysis of Gene Expression Data Based on Self-Splitting and Merging Competitive Learning

Cluster analysis of gene expression data from a cDNA microarray is useful for identifying biologically relevant groups of genes. However, finding the natural clusters in the data and estimating the correct number of clusters are still two largely unsolved problems. In this paper, we propose a new clustering framework that is able to address both these problems. By using the one-prototype-take-one-cluster (OPTOC) competitive learning paradigm, the proposed algorithm can find natural clusters in the input data, and the clustering solution is not sensitive to initialization. In order to estimate the number of distinct clusters in the data, we propose a cluster splitting and merging strategy. We have applied the new algorithm to simulated gene expression data for which the correct distribution of genes over clusters is known a priori. The results show that the proposed algorithm can find natural clusters and give the correct number of clusters. The algorithm has also been tested on real gene expression changes during yeast cell cycle, for which the fundamental patterns of gene expression and assignment of genes to clusters are well understood from numerous previous studies. Comparative studies with several clustering algorithms illustrate the effectiveness of our method.

Profound influence of microarray scanner characteristics on gene expression ratios: analysis and procedure for correction

BACKGROUND

High throughput gene expression data from spotted cDNA microarrays are collected by scanning the signal intensities of the corresponding spots by dedicated fluorescence scanners. The major scanner settings for increasing the spot intensities are the laser power and the voltage of the photomultiplier tube (PMT). It is required that the expression ratios are independent of these settings. We have investigated the relationships between PMT voltage, spot intensities, and expression ratios for different scanners, in order to define an optimal scanning procedure.

RESULTS

All scanners showed a limited intensity range from 200 to 50 000 (mean spot intensity), for which the expression ratios were independent of PMT voltage. This usable intensity range was considerably less than the maximum detection range of the PMTs. The use of spot and background intensities outside this range led to errors in the ratios. The errors at high intensities were caused by saturation of pixel intensities within the spots. An algorithm was developed to correct the intensities of these spots, and, hence, extend the upper limit of the usable intensity range.

CONCLUSIONS

It is suggested that the PMT voltage should be increased to avoid intensities of the weakest spots below the usable range, allowing the brightest spots to reach the level of saturation. Subsequently, a second set of images should be acquired with a lower PMT setting such that no pixels are in saturation. Reliable data for spots with saturation in the first set of images can easily be extracted from the second set of images by the use of our algorithm. This procedure would lead to an increase in the accuracy of the data and in the number of data points achieved in each experiment compared to traditional procedures.

Identification of Genetic Networks

In this report, we propose the use of structural equations as a tool for identifying and modeling genetic networks and genetic algorithms for searching the most likely genetic networks that best fit the data. After genetic networks are identified, it is fundamental to identify those networks influencing cell phenotypes. To accomplish this task we extend the concept of differential expression of the genes, widely used in gene expression data analysis, to genetic networks. We propose a definition for the differential expression of a genetic network and use the generalized T  2 statistic to measure the ability of genetic networks to distinguish different phenotypes. However, describing the differential expression of genetic networks is not enough for understanding biological systems because differences in the expression of genetic networks do not directly reflect regulatory strength between gene activities. Therefore, in this report we also introduce the concept of differentially regulated genetic networks, which has the potential to assess changes of gene regulation in response to perturbation in the environment and may provide new insights into the mechanism of diseases and biological processes. We propose five novel statistics to measure the differences in regulation of genetic networks. To illustrate the concepts and methods for reconstruction of genetic networks and identification of association of genetic networks with function, we applied the proposed models and algorithms to three data sets.

Gene expression profiling in intestinal-type gastric carcinoma by cDNA microarray

AIM: To identify a set of genes involved in the development of intestinal-type gastric carcinoma.

METHODS: Pure mRNAs from 6 cases of intestinal-type gastric carcinoma and corresponding noncancerous mucosae were reversely transcribed into cDNAs labeled with Cy5 and Cy3 dyes for probes, then mixed and hybridized with the cDNA microarray consisting of 4 096 genes, and the fluorescent signals were scanned.

RESULTS: Among total genes, 333 were up-regulated and 333 down-regulated in intestinal-type gastric cancer tissues. Within altered expression of those genes, cell-cycle regulators and growth factors were up-regulated, and the promoter genes of apoptosis were down-regulated; Oncogenes and cell-adhesion molecules were more up-regulated; The cancer progression genes were up-regulated, while the anti-cancer progression genes were down-regulated.

CONCLUSION: The quick and high-throughout method of gene expression profile by cDNA array provides us with an overview of gene changes that may involved in intestinal-type gastric cancer development, and will open up new possibilities to identify novel molecular targets for diagnosis and therapy. Several genes are altered in intestinal-type gastric cancer, which need to be further investigated.

Microspotting Streptavidin and Double-Stranded DNA Arrays on Gold for High-Throughput Studies of Protein−DNA Interactions by Surface Plasmon Resonance Microscopy

We present two strategies for microspotting 10 x 12 arrays of double-stranded DNAs (dsDNAs) onto a gold-coated glass slide for high-throughput studies of protein-DNA interactions by surface plasmon resonance (SPR) microscopy. Both methods use streptavidin (SA) as a linker layer between a biotin-containing mixed self-assembled monolayer (SAM) and biotinylated dsDNAs to produce arrays with high packing density. The primary mixed SAM is produced from biotin- and oligo(ethylene glycol)-terminated thiols bonded as thiolates onto the gold surface. In the first method, a robotic microspotter is used to deliver nanoliter droplets of dsDNA solution onto a uniform layer of this SA ( approximately 2 x 10(12) SA/cm(2)). SPR microscopy shows a density of (5-6) x 10(11) dsDNA/cm(2) (0.2-0.3 dsDNA/SA) in the array elements. The second method uses instead a microspotted array of this SA linker layer, onto which the microspots of dsDNA are added with spatial registry. SPR microscopy before addition of the dsDNA shows a SA coverage of 2 x 10(12) SA/cm(2) within the spots and a dsDNA density of 8.5 +/- 3.5 x 10(11) dsDNA/cm(2) (0.3-0.7 dsDNA/SA, depending on the length of dsDNA) after dsDNA spotting. We demonstrate the ability to simultaneously monitor protein binding with the SPR microscope in many 200-microm spots with 1-s time resolution and sensitivity to <1 pg of protein.

Molecular markers to identify patients at risk for recurrence after primary treatment for prostate cancer

Accurate prognostication is a prerequisite for accurate therapeutics and management of prostate cancer because indolent tumors may require no intervention, whereas aggressive tumors lead to patient mortality. There is a critical need to define these subgroups of patients with prostate cancer differing in clinical outcome. Prognostic nomograms based on clinical data provide useful predictions of clinical states and outcomes, but they need further refinements to improve accuracy and universality. Genomic and proteomic analyses have provided many novel markers that may help define prognostic parameters based on the underlying biology of prostate cancer progression at the molecular level. These molecular markers are likely to augment traditional prognostic modalities by providing a set of molecularly defined and quantifiable variables. Encompassing the genome, transcriptome, and proteome of prostate cancer will likely provide "molecular signatures" that will bridge prognostication, prediction, and treatment in a single continuum.

Global phenotypic analysis and transcriptional profiling defines the weak acid stress response regulon in Saccharomyces cerevisiae

Weak organic acids such as sorbate are potent fungistatic agents used in food preservation, but their intracellular targets are poorly understood. We thus searched for potential target genes and signaling components in the yeast genome using contemporary genome-wide functional assays as well as DNA microarray profiling. Phenotypic screening of the EUROSCARF collection revealed the existence of numerous sorbate-sensitive strains. Sorbate hypersensitivity was detected in mutants of the shikimate biosynthesis pathway, strains lacking the PDR12 efflux pump or WAR1, a transcription factor mediating stress induction of PDR12. Using DNA microarrays, we also analyzed the genome-wide response to acute sorbate stress, allowing for the identification of more than 100 genes rapidly induced by weak acid stress. Moreover, a novel War1p- and Msn2p/4p-independent regulon that includes HSP30 was identified. Although induction of the majority of sorbate-induced genes required Msn2p/4p, weak acid tolerance was unaffected by a lack of Msn2p/4p. Ectopic expression of PDR12 from the GAL1-10 promoter fully restored sorbate resistance in a strain lacking War1p, demonstrating that PDR12 is the major target of War1p under sorbic acid stress. Interestingly, comparison of microarray data with results from the phenotypic screening revealed that PDR12 remained as the only gene, which is both stress inducible and required for weak acid resistance. Our results suggest that combining functional assays with transcriptome profiling allows for the identification of key components in large datasets such as those generated by global microarray analysis.

Use of Microarray Analysis to Unveil Transcription Factor and Gene Networks Contributing to β Cell Dysfunction and Apoptosis

The beta cell fate following immune-mediated damage depends on an intricate pattern of dozens of genes up- or downregulated in parallel and/or sequentially. We are utilizing microarray analysis to clarify the pattern of gene expression in primary rat beta cells exposed to the proapoptotic cytokines, IL-1beta and/or IFN-gamma. The picture emerging from these experiments is that beta cells are not passive bystanders of their own destruction. On the contrary, beta cells respond to damage by activating diverse networks of transcription factors and genes that may either lead to apoptosis or preserve viability. Of note, cytokine-exposed beta cells produce and release chemokines that may contribute to the homing and activation of T cells and macrophages during insulitis. Several of the effects of cytokines depend on the activation of the transcription factor, NF-kappaB. NF-kappaB blocking prevents cytokine-induced beta cell death, and characterization of NF-kappaB-dependent genes by microarray analysis indicated that this transcription factor controls diverse networks of transcription factors and effector genes that are relevant for maintenance of beta cell differentiated status, cytosolic and ER calcium homeostasis, attraction of mononuclear cells, and apoptosis. Identification of this and additional "transcription factor networks" is being pursued by cluster analysis of gene expression in insulin-producing cells exposed to cytokines for different time periods. Identification of complex gene patterns poses a formidable challenge, but is now technically feasible. These accumulating evidences may finally unveil the molecular mechanisms regulating the beta cell "decision" to undergo or not apoptosis in early T1DM.

From the messenger RNA saga to the transcriptome era

This review attempts to provide an overview of the evolution of the ideas and techniques that prevailed at the beginning of research on ribonucleic acids, until the contemporary era of cellular transcript analysis using DNA biochips and microarrays. Certain applications derived from the use of microarrays and the corresponding analyses of transcriptomes are discussed, particularly concerning diagnosis and prevision of evolution of certain cancers.

A comprehensive search for HNF-3α-regulated genes in mouse hepatoma cells by 60K cDNA microarray and chromatin immunoprecipitation/PCR analysis

To characterize the regulatory pattern by a specific transcription regulatory factor, we used a combination of expression analysis with the mouse cDNA microarray composed of 60,000 cDNA clones and cross-linking/chromatin immunoprecipitation (X-ChIP) followed by comparative PCR. Overexpression of mouse hepatocyte nuclear factor-3alpha (HNF-3alpha) in a mouse hepatoma cell line resulted in accompanied perturbed expression of more than 1500 genes. Search for HNF-3alpha consensus recognition sequences in the upstream regions of their coding sequences, which were mapped on the mouse genome, enabled us to mine 300 genes as the potential HNF-3alpha-regulated genes and classify 135 annotated ones into several functional categories. Further X-ChIP/PCR analysis demonstrated in vivo binding of HNF-3alpha to the 5(')-flanking sequences of 25 members selected out of these genes. Besides known HNF-3alpha-regulated genes such as albumin and alpha-fetoprotein genes, the genes newly identified as the HNF-3alpha-regulated ones include three encoding CDP-diacylglycerol-inositol 3-phosphatidyltransferase, phosphatidylserine decarboxylase, and phospholipase A2, which are located en suite in the lipid metabolic pathway in liver. The potential usefulness of the present approach to extensive characterization of gene expression framework directed by a specific transcription regulatory factor is discussed.

Development of a sensitive DNA microarray suitable for rapid detection of Campylobacter spp

Campylobacter is the most common cause of human acute bacterial gastroenteritis worldwide, widely distributed and isolated from human clinical samples as well as from many other different sources. To comply with the demands of consumers for food safety, there is a need for development of a rapid, sensitive and specific detection method for Campylobacter. In this study, we present the development of a novel sensitive DNA-microarray based detection method, evaluated on Campylobacter and non-Campylobacter reference strains, to detect Campylobacter directly from the faecal cloacal swabs. The DNA-microarray method consists of two steps: first, both universal bacterial sequences and specific Campylobacter sequences (size range: 149-307 bp) are amplified and fluorescently labeled using multiplex-PCR, targeting the 16S rRNA, the 16S-23S rRNA intergenic region and specific Campylobacter genes. Secondly, the Cy5 labeled PCR-amplicons are hybridised to immobilised capture probes on the microarray. The method allows detection of three to thirty genome equivalents (6-60 fg DNA) of Campylobacter within 3 h, with a hands on time of only 15 min. Using the DNA-microarrays, two closely related Campylobacter species, Campylobacter jejuni and Campylobacter coli could be detected and differentiated directly from chicken faeces. The DNA-microarray method has a high potential for automation and incorporation into a dedicated mass screening microsystem.

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Whole-genome microarrays of fission yeast: characteristics, accuracy, reproducibility, and processing of array data

BACKGROUND

The genome of the fission yeast Schizosaccharomyces pombe has recently been sequenced, setting the stage for the post-genomic era of this increasingly popular model organism. We have built fission yeast microarrays, optimised protocols to improve array performance, and carried out experiments to assess various characteristics of microarrays.

RESULTS

We designed PCR primers to amplify specific probes (180-500 bp) for all known and predicted fission yeast genes, which are printed in duplicate onto separate regions of glass slides together with control elements (approximately 13,000 spots/slide). Fluorescence signal intensities depended on the size and intragenic position of the array elements, whereas the signal ratios were largely independent of element properties. Only the coding strand is covalently linked to the slides, and our array elements can discriminate transcriptional direction. The microarrays can distinguish sequences with up to 70% identity, above which cross-hybridisation contributes to the signal intensity. We tested the accuracy of signal ratios and measured the reproducibility of array data caused by biological and technical factors. Because the technical variability is lower, it is best to use samples prepared from independent biological experiments to obtain repeated measurements with swapping of fluorochromes to prevent dye bias. We also developed a script that discards unreliable data and performs a normalization to correct spatial artefacts.

CONCLUSIONS

This paper provides data for several microarray properties that are rarely measured. The results define critical parameters for microarray design and experiments and provide a framework to optimise and interpret array data. Our arrays give reproducible and accurate expression ratios with high sensitivity. The scripts for primer design and initial data processing as well as primer sequences and detailed protocols are available from our website.

Fibroblast-specific expression of a kinase-deficient type II transforming growth factor beta (TGFbeta) receptor leads to paradoxical activation of TGFbeta signaling pathways with fibrosis in transgenic mice

To better understand the role of disrupted transforming growth factor beta (TGFbeta) signaling in fibrosis, we have selectively expressed a kinase-deficient human type II TGFbeta receptor (TbetaRIIDeltak) in fibroblasts of transgenic mice, using a lineage-specific expression cassette subcloned from the pro-alpha2(I) collagen gene. Surprisingly, despite previous studies that characterized TbetaRIIDeltak as a dominant negative inhibitor of TGFbeta signaling, adult mice expressing this construct demonstrated TGFbeta overactivity and developed dermal and pulmonary fibrosis. Compared with wild type cells, transgenic fibroblasts proliferated more rapidly, produced more extracellular matrix, and showed increased expression of key markers of TGFbeta activation, including plasminogen activator inhibitor-1, connective tissue growth factor, Smad3, Smad4, and Smad7. Smad2/3 phosphorylation was increased in transgenic fibroblasts. Overall, the gene expression profile of explanted transgenic fibroblasts using cDNA microarrays was very similar to that of littermate wild type cells treated with recombinant TGFbeta1. Despite basal up-regulation of TGFbeta signaling pathways, transgenic fibroblasts were relatively refractory to further stimulation with TGFbeta1. Thus, responsiveness of endogenous genes to TGFbeta was reduced, and TGFbeta-regulated promoter-reporter constructs transiently transfected into transgenic fibroblasts showed little activation by recombinant TGFbeta1. Responsiveness was partially restored by overexpression of wild type type II TGFbeta receptors. Activation of MAPK pathways by recombinant TGFbeta1 appeared to be less perturbed than Smad-dependent signaling. Our results show that expression of TbetaRIIDeltak selectively in fibroblasts leads to paradoxical ligand-dependent activation of downstream signaling pathways and causes skin and lung fibrosis. As well as confirming the potential for nonsignaling receptors to regulate TGFbeta activity, these findings support a direct role for perturbed TGFbeta signaling in fibrosis and provide a novel genetically determined animal model of fibrotic disease.

Rpb4p, a subunit of RNA polymerase II, mediates mRNA export during stress

Changes in gene expression represent a major mechanism by which cells respond to stress. We and other investigators have previously shown that the yeast RNA polymerase II subunit Rpb4p is required for transcription under various stress conditions, but not under optimal growth conditions. Here we show that, in addition to its role in transcription, Rpb4p is also required for mRNA export, but only when cells are exposed to stress conditions. The roles of Rpb4p in transcription and in mRNA export can be uncoupled genetically by specific mutations in Rpb4p. Both functions of Rpb4p are required to maintain cell viability during stress. We propose that Rpb4p participates in the cellular responses to stress at the interface of the transcription and the export machineries.

DNA expression analysis: serial analysis of gene expression, microarrays and kidney disease

PURPOSE OF REVIEW

Expression profiling using serial analysis of gene expression and microarray technologies allows global description of expressed genes present in biological systems. Although relatively new technologies, each having been developed in the mid-1990s, both have become established and widely used tools for identification of gene networks and gene function.

RECENT FINDINGS

This review highlights DNA expression analyses published in 2002, emphasizing primarily serial analysis of gene expression and microarray technologies. We focus on the applicability of DNA expression analysis to renal disease, especially as some investigators have developed custom serial analysis of gene expression kidney libraries and kidney disease-specific 'designer chip' microarrays. Data analysis techniques and statistics are also discussed, since the challenge is generation of accurate messenger RNA profiles and interpretation of data in a manner that is both coherent and reproducible.

SUMMARY

Because kidney disease pathophysiology is complex, expression analysis can identify candidate nephropathy pathogenesis genes and gene networks, which eventually could become targets for therapeutic intervention.

Overview of microarrays in drug discovery and development

With the sequencing of the human genome, new tools and technologies have been developed to identify and quantify global gene-expression changes occurring in the cell. One of the main tools being utilized is microarray technology, which allows one to quantitate expression changes of thousands of genes in a single experiment. Microarrays allow researchers to gain an unprecedented understanding of the function and regulation of genes, and are transforming virtually all areas of biological research. In the drug-discovery process, microarrays have the potential to play a role in all stages, from new target discovery through compound profiling and safety assessment. This overview highlights some of these studies and discusses how this technology is transforming the field of drug discovery and development.

Microarray analysis reveals interleukin-6 as a novel secretory product of the hypothalamo-neurohypophyseal system

Physiological activation of the hypothalamo-neurohypophyseal system (HNS) by dehydration results is a massive release of vasopressin (VP) from the posterior pituitary. This is accompanied by a functional remodeling of the HNS. In this study we used cDNA arrays in an attempt to identify genes that exhibit differential expression in the hypothalamus following dehydration. Our study revealed nine candidate genes, including interleukin-6 (IL-6) as a putative novel secretory product of HNS worthy of further analysis. In situ hybridization and immunocytochemistry confirmed that IL-6 is robustly expressed in the supraoptic (SON) and the paraventricular (PVN) nuclei of the hypothalamus. By double staining immunofluorescence we showed that IL-6 is largely co-localized with VP in the SON and PVN. In situ hybridization, immunocytochemistry, and Western blotting all revealed IL-6 up-regulation in the SON and PVN following dehydration, thus validating the array data. The same dehydration stimulus resulted in an increase in IL-6 immunoreactivity in the axons of the internal zone of the median eminence and a marked reduction in IL-6-like material in the posterior pituitary gland. We thus suggest that IL-6 takes the same secretory pathway as VP and is secreted from the posterior pituitary following a physiological stimulus.

A novel family in Medicago truncatula consisting of more than 300 nodule-specific genes coding for small, secreted polypeptides with conserved cysteine motifs

Transcriptome analysis of Medicago truncatula nodules has led to the discovery of a gene family named NCR (nodule-specific cysteine rich) with more than 300 members. The encoded polypeptides were short (60-90 amino acids), carried a conserved signal peptide, and, except for a conserved cysteine motif, displayed otherwise extensive sequence divergence. Family members were found in pea (Pisum sativum), broad bean (Vicia faba), white clover (Trifolium repens), and Galega orientalis but not in other plants, including other legumes, suggesting that the family might be specific for galegoid legumes forming indeterminate nodules. Gene expression of all family members was restricted to nodules except for two, also expressed in mycorrhizal roots. NCR genes exhibited distinct temporal and spatial expression patterns in nodules and, thus, were coupled to different stages of development. The signal peptide targeted the polypeptides in the secretory pathway, as shown by green fluorescent protein fusions expressed in onion (Allium cepa) epidermal cells. Coregulation of certain NCR genes with genes coding for a potentially secreted calmodulin-like protein and for a signal peptide peptidase suggests a concerted action in nodule development. Potential functions of the NCR polypeptides in cell-to-cell signaling and creation of a defense system are discussed.

Genomic analysis of stress response genes

Mammalian cells respond to a wide range of external stimuli including growth factors, peptide hormones, cytokines, osmotic stress, heat shock, pharmacological agents and toxicants via multiple signalling pathways. Genome-wide transcript profiling simultaneously monitors the gene expression programs downstream of all signal transduction pathways and can identify novel molecular targets for stress-inducing signals. Our laboratory has combined transcript profiling of cytotoxic compounds with experimental systems in which signalling components are disrupted (e.g. small molecule protein kinase inhibitors) to reveal the contribution of specific signalling pathways to the transcriptional response to toxicant-induced stress. A complementary approach for elucidating the molecular mechanisms that regulate transcriptional responses to toxicants involves DNA sequence analysis of gene regulatory regions obtained via data mining of recently completed mammalian genome sequences. Together, these approaches reveal the molecular mechanisms used to finely tune alterations in gene expression, enabling cells to react in an appropriate manner to external stress-inducing stimuli.

Monitoring global messenger RNA changes in externally controlled microarray experiments

Expression profiling is a universal tool, with a range of applications that benefit from the accurate determination of differential gene expression. To allow normalization using endogenous transcript levels, current microarray analyses assume that relatively few transcripts vary, or that any changes that occur are balanced. When normalization using endogenous genes is carried out, changes in expression levels are calculated relative to the behaviour of most of the transcripts. This does not reflect absolute changes if global shifts in messenger RNA populations occur. Using external RNA controls, we have set up microarray experiments to monitor global changes. The levels of most mRNAs were found to change during yeast stationary phase and human heat shock when external controls were included. Even small global changes had a significant effect on the number of genes reported as being differentially expressed. This suggests that global mRNA changes occur more frequently than is assumed at present, and shows that monitoring such effects may be important for the accurate determination of changes in gene expression.

High-throughput epidemiologic typing in clinical microbiology

Mapping, and ultimately preventing, the dissemination of infectious agents is an important topic in public health. Newly developed molecular-microbiological methods have contributed significantly to recent advances in the efficient tracking of the nosocomial and environmental spread of microbial pathogens. Not only has the application of novel technologies led to improved understanding of microbial epidemiology, but the concepts of population structure and dynamics of many of the medically significant microorganisms have advanced significantly also. Currently, genetic identification of microbes is also within the reach of clinical microbiology laboratory professionals including those without specialized technology research interests. This review summarizes the possibilities for high-throughput molecular-microbiological typing in adequately equipped medical microbiology laboratories from both clinical and fundamental research perspectives. First, the development and application of methods for large-scale comparative typing of serially isolated microbial strains are discussed. The outcome of studies employing these methods allows for long-term epidemiologic surveillance of infectious diseases. Second, recent methods enable an almost nucleotide-by-nucleotide genetic comparison of smaller numbers of strains, thereby facilitating the identification of the genetic basis of, for instance, medically relevant microbiological traits. Whereas the first approach provides insights into the dynamic spread of infectious agents, the second provides insights into intragenomic dynamics and genetic functionality. The current state of technology is summarized, and future perspectives are sketched.

In vivo gene transfer studies on the regulation and function of the vasopressin and oxytocin genes

Novel genes can be introduced into the germline of rats and mice by microinjecting fertilized one-cell eggs with fragments of cloned DNA. A gene sequence can thus be studied within the physiological integrity of the resulting transgenic animals, without any prior knowledge of its regulation and function. These technologies have been used to elucidate the mechanisms by which the expression of the two genes in the locus that codes for the neuropeptides vasopressin and oxytocin is confined to, and regulated physiologically within, specific groups of neurones in the hypothalamus. A number of groups have described transgenes, derived from racine, murine and bovine sources, in both rat and mouse hosts, that mimic the appropriate expression of the endogenous vasopressin and genes in magnocellular neurones (MCNs) of the supraoptic and paraventricular nuclei. However, despite considerable effort, a full description of the cis-acting sequences mediating the regulation of the vasopressin-oxytocin locus remains elusive. Two general conclusions have nonetheless been reached. First, that the proximal promoters of both genes are unable to confer any cell-specific regulatory controls. Second, that sequences downstream of the promoter, within the structural gene and/or the intergenic region that separates the two genes, are crucial for appropriate expression. Despite these limitations, sufficient knowledge has been garnered to specifically direct the expression of reporter genes to vasopressin and oxytocin MCNs. Further, it has been shown that reporter proteins can be directed to the regulated secretory pathway, from where they are subject to appropriate physiological release. The use of MCN expression vectors will thus enable the study of the physiology of these neurones through the targeted expression of biologically active molecules. However, the germline transgenic approach has a number of limitations involving the interpretation of phenotypes, as well as the large cost, labour and time demands. High-throughput somatic gene transfer techniques, principally involving the stereotaxic injection of hypothalamic neuronal groups with replication-deficient adenoviral vectors, are now being developed that obviate these difficulties, and which enable the robust, long-lasting expression of biologically active proteins in vasopressin and oxytocin MCNs.

SMART amplification maintains representation of relative gene expression: quantitative validation by real time PCR and application to studies of alcoholic liver disease in primates

The small quantities of tissue available for most studies of human disease are a significant limitation for meaningful gene expression profiling. The Atlas Switch Mechanism At the 5' end of Reverse Transcript (SMART) probe amplification kit uses as little as 50 ng of total RNA to generate complex cDNA probes for DNA array and other analyses. However, the extent to which this attractive methodology maintains representation of relative gene expression has not been quantified. In this study, we demonstrate using real-time quantitative PCR analysis that the relative expression levels of a range of low- to high-abundance mRNAs are retained after SMART amplification independent of transcript abundance and full-length transcript, coding region and PCR product size. Using this technology, a mean amplification of 3800-fold was achieved in human liver samples, greatly enhancing the ability to perform replicate DNA array experiments. Probes generated with the SMART amplification method were used to detect increased expression of genes involved with inflammation, fibrosis, xenobiotic metabolism, immune function, oxidant stress and endothelium in liver from the baboon model of alcoholic liver disease.

Gene expression studies using microarrays: principles, problems, and prospects

A number of mammalian genomes having been sequenced, an important next step is to catalog the expression patterns of all transcription units in health and disease by use of microarrays. Such discovery programs are crucial to our understanding of the gene networks that control developmental, physiological, and pathological processes. However, despite the excitement, the full promise of microarray technology has yet to be realized, as the superficial simplicity of the concept belies considerable problems. Microarray technology is very new; methodologies are still evolving, common standards have yet to be established, and many problems with experimental design and variability have still to be fully understood and overcome. This review will describe the time course of a microarray experiment-RNA isolation from sample, target preparation, hybridization to the microarray probe, data capture, and bioinformatic analysis. For each stage, the advantages and disadvantages of competing techniques are compared, and inherent sources of error are identified and discussed.

Analysis of baseline and cisplatin-inducible gene expression in Fanconi anemia cells using oligonucleotide-based microarrays

BACKGROUND: Patients with Fanconi anemia (FA) suffer from multiple defects, most notably of the hematological compartment (bone marrow failure), and susceptibility to cancer. Cells from FA patients show increased spontaneous chromosomal damage, which is aggravated by exposure to low concentrations of DNA cross-linking agents such as mitomycin C or cisplatin. Five of the identified FA proteins form a nuclear core complex. However, the molecular function of these proteins remains obscure. METHODS: Oligonucleotide microarrays were used to compare the expression of approximately 12,000 genes from FA cells with matched controls. Expression profiles were studied in lymphoblastoid cell lines derived from three different FA patients, one from the FA-A and two from the FA-C complementation groups. The isogenic control cell lines were obtained by either transfecting the cells with vectors expressing the complementing cDNAs or by using a spontaneous revertant cell line derived from the same patient. In addition, we analyzed expression profiles from two cell line couples at several time points after a 1-hour pulse treatment with a discriminating dose of cisplatin. RESULTS: Analysis of the expression profiles showed differences in expression of a number of genes, many of which have unknown function or are difficult to relate to the FA defect. However, from a selected number of proteins involved in cell cycle regulation, DNA repair and chromatin structure, Western blot analysis showed that p21waf1/Cip1 was significantly upregulated after low dose cisplatin treatment in FA cells specifically (as well as being expressed at elevated levels in untreated FA cells). CONCLUSIONS: The observed increase in expression of p21waf1/Cip1 after treatment of FA cells with crosslinkers suggests that the sustained elevated levels of p21waf1/Cip1 in untreated FA cells detected by Western blot analysis likely reflect increased spontaneous damage in these cells.

Improving DNA array data quality by minimising 'neighbourhood' effects

Gene expression studies using cDNA arrays require robust and sensitive detection methods. Being extremely sensitive, radioactive detection suffers from the influence of signals positioned in each other's vicinity, the 'neighbourhood' effect. This limits the gene density of arrays and the quality of the results obtained. We have investigated the quantitative influence of different parameters on the 'neighbourhood' effect. By using a model experimental system, we could show that the effect is linear and depends only on the intensity of the hybridisation signal. We identified a common factor that can describe the influence of the neighbour spots based on their intensities. This factor is <1%, but it has to be taken into account if a high dynamic range of gene expression is to be detected. We could also derive the factor, although with less precision, from comparison of duplicate spots on arrays of 4565 different clones and replication of the hybridisation experiments. The calculated coefficient applied to our actual experimental results not only revealed previously undetected tissue or cell-specific expression differences, but also increased the dynamic range of detection. It thus provides a relatively simple way of improving DNA array data quality with few experimental modifications.

The future of reproductive cellular engineering in male infertility

Understanding of the pathophysiology of defective spermatogenesis, spermatozoa, and germ cell function must be advanced so that appropriate rational treatment, such as gene therapy, can be developed. Despite the dramatic advances in ART, one ultimate goal must be to develop treatment so that the couple can conceive naturally. Because such treatment will not be possible in all cases, a complementary step will be the ability to induce the production of haploid, functionally competent germ cells that can be used for ART. The achievement of these goals will be based on advances in many other disciplines. Whatever the future holds, it promises to be exciting.

Gene expression profiling reveals role for EGF-family ligands in mesangial cell proliferation

Control of mesangial cell growth and matrix accumulation is critical for normal development of the glomerular tuft and progression of glomerular injury, but the genes that control mesangial cell growth are not well understood. We used high-density oligonucleotide microarrays to analyze gene expression in well-differentiated human mesangial cells treated with serum to stimulate proliferation. Parallel measurement of >12,000 genes and expressed sequence tags identified 5,806 mRNA transcripts in quiescent, unstimulated cells and 609 genes significantly induced or repressed by serum. Functional classification of serum-regulated genes revealed many genes not directly related to cell cycle progression that, instead, might control renal hemodynamics and glomerular filtration or cause tissue injury, leukocyte exudation, matrix accumulation, and fibrosis. Hierarchical cluster analysis defined sets of coregulated genes with similar functions and identified networks of proinflammatory genes with similar expression patterns. Pathway analysis of the gene expression profile suggested an autocrine role in mesangial cell proliferation for three growth factors in the epidermal growth factor (EGF) family: heparin-binding EGF-like growth factor, amphiregulin, and epiregulin. A functional role for EGF receptor (EGFR) activation was confirmed by blocking serum-induced proliferation with an EGFR-selective kinase inhibitor and a specific EGFR-neutralizing antibody. Taken together, these results suggest a role for EGFR signaling in control of mesangial cell growth in response to serum.

Quality indicators increase the reliability of microarray data

Large-scale gene expression profiling with DNA microarrays opens new dimensions to molecular biology but still lacks the overall precision of traditional low-scale techniques. We developed a novel strategy of data processing linking search stringency to quality indicators for efficient detection of low-level, regulated genes. Using retinoid-induced differentiation of NB-4 promyelocytic cells, the variation of expression profiles between biological duplicates was studied and compared with the changes induced by all-trans retinoic acid (atRA) treatment. An analysis of 4320 genes showed that retinoic acid has mainly geneactivating function in NB-4 cells. Treatment with atRA for 18 hours induced metabolic genes that may be associated with cell differentiation and signaling factors triggering later events leading to apoptosis; cytokine genes were among the highest stimulated by atRA. Notably, we identified a regulatory loop inhibiting MYC action: as MYC was downregulated, a cognate repressor of MYC was upregulated.

Expression profiling with oligonucleotide arrays: technologies and applications for neurobiology

DNA microarrays have been used in applications ranging from the assignment of gene function to analytical uses in prognostics. However, the detection sensitivity, cross hybridization, and reproducibility of these arrays can affect experimental design and data interpretation. Moreover, several technologies are available for fabrication of oligonucleotide microarrays. We review these technologies and performance attributes and, with data sets generated from human brain RNA, present statistical tools and methods to analyze data quality and to mine and visualize the data. Our data show high reproducibility and should allow an investigator to discern biological and regional variability from differential expression. Although we have used brain RNA as a model system to illustrate some of these points, the oligonucleotide arrays and methods employed in this study can be used with cell lines, tissue sections, blood, and other fluids. To further demonstrate this point, we provide data generated from total RNA sample sizes of 200 ng.

DNA chips for yeast biotechnology. The case of wine yeasts

The yeast Saccharomyces cerevisiae is one of the most popular model organisms. It was the first eukaryote whose genome was sequenced. Since then many functional analysis projects have tried to find the function of many genes and to understand its metabolism in a holistic way. Apart from basic science this microorganism is of great interest in several biotechnology processes, such as winemaking. Only global studies of the cell as a whole can help us to understand many of the technical problems facing winemaking. DNA chip technology is one of the most promising tools for the analysis of cell physiology. Yeast has been the model organism for the development of this technique. Many of the studies can be applied to improve our knowledge of wine strains. Nevertheless wine strains are quite different in some aspects from the laboratory reference strains so a particular study of wine strains and especially during the winemaking process is needed. During the past two years some groups have started this study and the first results have been published. We review here the current state of the knowledge of wine yeast and the capacity of DNA chip technology for its improvement.

Identification of cross-linked peptides for protein interaction studies using mass spectrometry and 18O labeling

A new method is presented to screen proteolytic mass maps of cross-linked protein complexes for the presence of cross-linked peptides and for the verification of proposed structures. On the basis of the incorporation of 18O from isotopically enriched water into the C-termini of proteolytic peptides, cross-linked peptides are readily distinguished in mass spectra by a characteristic 8 amu shift. This is due to the incorporation of two 18O atoms in each C-terminus, so that normal and surface-labeled peptides shift 4 amu and cross-linked peptides containing two C-termini will shift 8 amu compared with their unlabeled counterparts. The method is fast, sensitive, and reliable and can be combined with any available cross-linking reagent and a wide range of proteolytic agents. As proof of principle, we successfully applied the method to a complex of two DNA repair proteins (Rad18-Rad6) and identified the interaction domain.

Retinoblastoma-cyclin-dependent kinase pathway deregulation in vestibular schwannomas

OBJECTIVES

The purpose of the study was to identify genes of the retinoblastoma protein (pRb)-cyclin-dependent kinase (CDK) pathway that are deregulated in vestibular schwannomas when compared with normal vestibular nerve tissues.

STUDY DESIGN

Expression profiles in eight vestibular schwannomas (four sporadic tumors, one neurofibromatosis type 2 tumor, and three cystic tumors) and a paired normal vestibular nerve from one of the eight patients were chosen. Genes examined included the retinoblastoma susceptibility gene (Rb-1); cyclins D1, D2, A, and E; the CDK inhibitors p18, p19, and p27; CDK2 and CDK6; transcription factors E2F-4, E2F-5, and DP-1; and the neurofibromatosis type 2 gene.

METHODS

Total RNA samples were extracted from normal vestibular nerve and vestibular schwannoma tissues and used to generate radiolabeled complementary DNA (cDNA) samples. Labeled cDNA probes were then hybridized to cDNA microarray filters. The hybridization signal was captured and quantified. Differential gene expression profiles between the normal vestibular nerve and vestibular schwannoma were compared. Real-time polymerase chain reaction and immunohistochemistry were used to further confirm the cDNA microarray data.

RESULTS

Among genes in the pRb-CDK pathway, CDK2 was substantially underexpressed in seven of the eight vestibular schwannoma tumors examined. Quantitative RNA expression analysis using real-time polymerase chain reaction also showed consistent downregulation of CDK2 in the tumors. Anti-CDK2 antibody stained predominantly in the vestibular nerve and ganglion cells but only weakly in the vestibular schwannoma tissues.

CONCLUSIONS

The pRb-CDK pathway was altered in all vestibular schwannoma tumors examined, with CDK2 significantly downregulated in seven of the eight tumors. Further investigation into the regulatory mechanisms governing CDK2 expression may lead to a better understanding of vestibular schwannoma tumorigenesis.

Defining signal thresholds in DNA microarrays: exemplary application for invasive cancer

BACKGROUND

Genome-wide or application-targeted microarrays containing a subset of genes of interest have become widely used as a research tool with the prospect of diagnostic application. Intrinsic variability of microarray measurements poses a major problem in defining signal thresholds for absent/present or differentially expressed genes. Most strategies have used fold-change threshold values, but variability at low signal intensities may invalidate this approach and it does not provide information about false-positives and false negatives.

RESULTS

We introduce a method to filter false-positives and false-negatives from DNA microarray experiments. This is achieved by evaluating a set of positive and negative controls by receiver operating characteristic (ROC) analysis. As an advantage of this approach, users may define thresholds on the basis of sensitivity and specificity considerations. The area under the ROC curve allows quality control of microarray hybridizations. This method has been applied to custom made microarrays developed for the analysis of invasive melanoma derived tumor cells. It demonstrated that ROC analysis yields a threshold with reduced missclassified genes in microarray experiments.

CONCLUSIONS

Provided that a set of appropriate positive and negative controls is included on the microarray, ROC analysis obviates the inherent problem of arbitrarily selecting threshold levels in microarray experiments. The proposed method is applicable to both custom made and commercially available DNA microarrays and will help to improve the reliability of predictions from DNA microarray experiments.

Microarray optimizations: increasing spot accuracy and automated identification of true microarray signals

In this paper, fluorescent microarray images and various analysis techniques are described to improve the microarray data acquisition processes. Signal intensities produced by rarely expressed genes are initially correctly detected, but they are often lost in corrections for background, log or ratio. Our analyses indicate that a simple correlation between the mean and median signal intensities may be the best way to eliminate inaccurate microarray signals. Unlike traditional quality control methods, the low intensity signals are retained and inaccurate signals are eliminated in this mean and median correlation. With larger amounts of microarray data being generated, it becomes increasingly more difficult to analyze data on a visual basis. Our method allows for the automatic quantitative determination of accurate and reliable signals, which can then be used for normalization. We found that a mean to median correlation of 85% or higher not only retains more data than current methods, but the retained data is more accurate than traditional thresholds or common spot flagging algorithms. We have also found that by using pin microtapping and microvibrations, we can control spot quality independent from initial PCR volume.

Identification of gene expression profile of dorsal root ganglion in the rat peripheral axotomy model of neuropathic pain

Phenotypic modification of dorsal root ganglion (DRG) neurons represents an important mechanism underlying neuropathic pain. However, the nerve injury-induced molecular changes are not fully identified. To determine the molecular alterations in a broader way, we have carried out cDNA array on the genes mainly made from the cDNA libraries of lumbar DRGs of normal rats and of rats 14 days after peripheral axotomy. Of the 7,523 examined genes and expressed sequence tags (ESTs), the expression of 122 genes and 51 expressed sequence tags is strongly changed. These genes encompass a large number of members of distinct families, including neuropeptides, receptors, ion channels, signal transduction molecules, synaptic vesicle proteins, and others. Of particular interest is the up-regulation of gamma-aminobutyric acid(A) receptor alpha5 subunit, peripheral benzodiazepine receptor, nicotinic acetylcholine receptor alpha7 subunit, P2Y1 purinoceptor, Na(+) channel beta2 subunit, and L-type Ca(2+) channel alpha2delta-1 subunit. Our findings therefore reveal dynamic and complex changes in molecular diversity among DRG neurons after axotomy. Sequences reported in this paper have been deposited in the GenBank database (accession numbers BG 662484-BG 673712)

Hormonal genomics

The availability of the human genomic sequence is changing the way in which biological questions are addressed. Based on the prediction of genes from nucleotide sequences, homologies among their encoded amino acids can be analyzed and used to place them in distinct families. This serves as a first step in building hypotheses for testing the structural and functional properties of previously uncharacterized paralogous genes. As genomic information from more organisms becomes available, these hypotheses can be refined through comparative genomics and phylogenetic studies. Instead of the traditional single-gene approach in endocrine research, we are beginning to gain an understanding of entire mammalian genomes, thus providing the basis to reveal subfamilies and pathways for genes involved in ligand signaling. The present review provides selective examples of postgenomic approaches in the analysis of novel genes involved in hormonal signaling and their chromosomal locations, polymorphisms, splicing variants, differential expression, and physiological function. In the postgenomic era, scientists will be able to move from a gene-by-gene approach to a reconstructionistic one by reading the encyclopedia of life from a global perspective. Eventually, a community-based approach will yield new insights into the complexity of intercellular communications, thereby offering us an understanding of hormonal physiology and pathophysiology.

Optimization of oligonucleotide-based DNA microarrays

Oligonucleotide-based DNA microarrays are becoming increasingly useful for the analysis of gene expression and single nucleotide polymorphisms. Here we report a systematic study of the sensitivity, specificity and dynamic range of microarray signals and their dependence on the labeling and hybridization conditions as well as on the length, concentration, attachment moiety and purity of the oligonucleotides. Both a controlled set of in vitro synthesized transcripts and RNAs from biological samples were used in these experiments. An algorithm is presented that allows the efficient selection of oligonucleotides able to discriminate a single nucleotide mismatch. Critical parameters for various applications are discussed based on statistical analysis of the results. These data will facilitate the design and standardization of custom-made microarrays applicable to gene expression profiling and sequencing analyses.

Paradoxical overexpression and translocation of connexin43 in homocysteine-treated endothelial cells

Hyperhomocysteinemia is an established cause of defective vasorelaxation. Gene expression screening of human umbilical vein endothelial cells (HUVEC) treated with homocysteine (Hcy) revealed that connexin43 (Cx43) was upregulated. Expression of Cx43 was increased more than twofold in Hcy-treated HUVEC. Gap junctional communication (Lucifer yellow and whole cell patch clamp) was not enhanced in Hcy-treated HUVEC. HUVEC expressing chimeric Cx43-green fluorescent protein exhibited it at cell-cell contacts in control but showed redistribution to the intracellular compartment(s) in Hcy-treated cells. Confocal microscopy of HUVEC stained with anti-Cx43, mitochondrial, and endoplasmic reticulum fluorescent markers showed the localization of Cx43 to the plasma membrane of control cells and its colocalization with the mitochondrial marker in Hcy-treated HUVEC. Studies of isolated mitochondria confirmed overexpression of Cx43 in the mitochondria of Hcy-treated HUVEC. Microdissected renal interlobar arteries, which normally exhibit endothelium-derived hyperpolarizing factor-induced vasorelaxation, showed reduced nitric oxide synthase- and cyclooxygenase-independent vasorelaxation to acetylcholine after pretreatment with Hcy. In summary, Hcy-induced upregulation of Cx43 transcript and protein expression are associated with unaltered intercellular communication, redistribution of Cx43 in HUVEC, and reduced nitric oxide- and prostanoid-independent vascular responses to acetylcholine in Hcy-treated arteries.

Protein interaction verification and functional annotation by integrated analysis of genome-scale data

Assays capable of determining the properties of thousands of genes in parallel present challenges with regard to accurate data processing and functional annotation. Collections of microarray expression data are applied here to assess the quality of different high-throughput protein interaction data sets. Significant differences are found. Confidence in 973 out of 5342 putative two-hybrid interactions from S. cerevisiae is increased. Besides verification, integration of expression and interaction data is employed to provide functional annotation for over 300 previously uncharacterized genes. The robustness of these approaches is demonstrated by experiments that test the in silico predictions made. This study shows how integration improves the utility of different types of functional genomic data and how well this contributes to functional annotation.