Tissue-specific Gene Expression in Rat Hearts and Aortas in a Model of Vascular Nitrate Tolerance.

Nitroglycerin exerts a direct myocardial anti-ischemic effect even in the state of vascular nitrate tolerance. To examine the potentially diverse molecular responses in vascular and cardiac tissues, we investigated the gene expression profile of the heart and the aorta by DNA microarray in male Wistar rats that were previously made tolerant to the vascular effects of nitroglycerin. The blood pressure-lowering effect of nitroglycerin (1-100 µg/kg) was markedly attenuated in rats pretreated for 3 days with 3 × 100 mg/kg nitroglycerin. Nitric oxide content was significantly elevated in the heart but not in the aorta of nitrate-tolerant animals, which indicated tissue-specific differences in nitroglycerin bioconversion. Of 7742 genes analyzed by DNA microarray, we found that although the expression of 25 genes changed significantly in the heart (increased: Tas2r119, Map6, Cd59, Kcnh2, Kcnh3, Senp6, Mcpt1, Tshb, Haus1, Vipr1, Lrn3, Lifr; decreased: Ihh, Fgfr1, Cryge, Krt9, Agrn, C4bpb, Fcer1a, Csf3, Hsd17b11, Hsd11b2, Ctnnbl1, Prpg1, Hsf1), only 14 genes were altered in the aorta (increased: Tas2r119, Ihh, Rrad, Npm1, Snai1; decreased: Tubb2b, Usp15, Sema6c, Wfdc2, Rps21, Ramp2, Galr1, Atxn1, Lhx1) in vascular nitrate tolerance. Quantitative reverse transcription polymerase chain reaction analysis of genes related to oxidative/nitrative/nitrosative stress also showed differential expression pattern in the heart and aorta. This is the first pharmacogenomic analysis showing that nitroglycerin treatment leading to vascular nitrate tolerance differentially impacts gene expression in vascular and cardiac tissues, which indicates different tissue-specific downstream signaling pathways.

Modeling of chromosomal epigenetic silencing processes.

Silenced genes in eukaryotes are packaged into heterochromatin. In addition to establishing a passive storage site for inactive genes in differentiated cells, silencing can play an active role in promoting cellular differentiation. Here, we describe quantitative modeling of silencing processes.

Spatial epigenetic control of mono- and bistable gene expression.

Bistability in signaling networks is frequently employed to promote stochastic switch-like transitions between cellular differentiation states. Differentiation can also be triggered by antagonism of activators and repressors mediated by epigenetic processes that constitute regulatory circuits anchored to the chromosome. Their regulatory logic has remained unclear. A reaction-diffusion model reveals that the same reaction mechanism can support both graded monostable and switch-like bistable gene expression, depending on whether recruited repressor proteins generate a single silencing gradient or two interacting gradients that flank a gene. Our experiments confirm that chromosomal recruitment of activator and repressor proteins permits a plastic form of control; the stability of gene expression is determined by the spatial distribution of silencing nucleation sites along the chromosome. The unveiled regulatory principles will help to understand the mechanisms of variegated gene expression, to design synthetic genetic networks that combine transcriptional regulatory motifs with chromatin-based epigenetic effects, and to control cellular differentiation.

Control and signal processing by transcriptional interference.

A transcriptional activator can suppress gene expression by interfering with transcription initiated by another activator. Transcriptional interference has been increasingly recognized as a regulatory mechanism of gene expression. The signals received by the two antagonistically acting activators are combined by the polymerase trafficking along the DNA. We have designed a dual-control genetic system in yeast to explore this antagonism systematically. Antagonism by an upstream activator bears the hallmarks of competitive inhibition, whereas a downstream activator inhibits gene expression non-competitively. When gene expression is induced weakly, the antagonistic activator can have a positive effect and can even trigger paradoxical activation. Equilibrium and non-equilibrium models of transcription shed light on the mechanism by which interference converts signals, and reveals that self-antagonism of activators imitates the behavior of feed-forward loops. Indeed, a synthetic circuit generates a bell-shaped response, so that the induction of expression is limited to a narrow range of the input signal. The identification of conserved regulatory principles of interference will help to predict the transcriptional response of genes in their genomic context.

Toxicogenomics screening of small molecules using high-density, nanocapillary real-time PCR.

Compounds which induce toxicity through similar mechanisms lead to characteristic gene expression patterns. The concept that structurally similar compounds may have similar biological profiles, the so-called generalized neighborhood behavior, is less obvious to be demonstrated. We screened 625 compounds from a fully combinatorial library for their gene expression profiles in vitro over a selected toxicity panel of 56 genes. We used the novel nanocapillary, quantitative real-time PCR OpenArray technology that is coupling outstanding analytical performance with the medium-throughput ideal for such a sample-per-feature ratio. Applying a hybrid clustering on the gene expression data, correlation was analyzed between molecular scaffold and biological fingerprint. Structurally highly dissimilar, but similarly hepatotoxic compounds show similar fingerprint on our toxicity panel, however compounds of the same scaffold and of unknown biological effect do not always share similar fingerprints. Out of 12 different scaffolds, 4 families show non-correlating, uniform distribution among clusters whilst 8 families show neighborhood behavior of varying strength. Structurally not similar compounds may have highly similar biological activity, on the other hand, compounds of the same scaffold family do not all share the same biological effects based on toxicology related gene expression fingerprint.

Gene and protein expression changes in response to normoxic perfusion in mouse hearts.

INTRODUCTION: Although crystalloid-perfused isolated heart models are widely used in cardiovascular research, there are several limitations of these techniques. Changes in cardiac gene expression pattern due to normoxic perfusion itself have not been studied, despite its potential importance to provide useful information on limitations of this model. Therefore, here we investigated the time-dependent effect of normoxic, normothermic perfusion on global gene expression at mRNA and protein levels. METHODS: Hearts from male CFLP mice were perfused according to the Langendorff technique. We assessed relative gene expression changes by DNA microarray analysis of 8000 genes after 0, 60 and 120 min perfusion. RESULTS: Twelve genes exhibited significant up-regulation and 27 showed repression in hearts perfused for 60 or 120 min as compared to 0 min controls. Expression changes of 17 selected genes were verified and an additional 19 genes were examined by real-time quantitative PCR. Genes with altered expression included those coding for Creatin kinase, Lactate dehydrogenase, Voltage-dependent anion channel 1, a Disintegrin and Metalloprotease domain 3, Integrin alpha 7, Long-chain acyl-CoA dehydrogenase, Casein kinase II, Ketohexokinase, Chloride ion current inducer protein, Matrix metalloproteinase 2 and 9, Superoxide dismutases and Nitric oxide synthases, etc. DISCUSSION: Our results show that normoxic crystalloid perfusion itself results in time-dependent changes in cardiac gene expression which should be considered when designing ex vivo perfusion protocols in the mouse heart to mimic cardiac pathologies as many of these genes have been suspected to influence several cardiovascular diseases.

Kalman filtering for disease-state estimation from microarray data.

MOTIVATION: In this paper, we propose using the Kalman filter (KF) as a pre-processing step in microarray-based molecular diagnosis. Incorporating the expression covariance between genes is important in such classification problems, since this represents the functional relationships that govern tissue state. Failing to fulfil such requirements may result in biologically implausible class prediction models. Here, we show that employing the KF to remove noise (while retaining meaningful covariance and thus being able to estimate the underlying biological state from microarray measurements) yields linearly separable data suitable for most classification algorithms. RESULTS: We demonstrate the utility and performance of the KF as a robust disease-state estimator on publicly available binary and multi-class microarray datasets in combination with the most widely used classification methods to date. Moreover, using popular graphical representation schemes we show that our filtered datasets also have an improved visualization capability.

Improved DOP-PCR-based representational whole-genome amplification using quantitative real-time PCR.

In many cases, only a minute amount of partially degraded genomic DNA can be extracted from archived clinical samples. Diverse whole-genome amplification methods are applied to provide sufficient amount of DNA for comparative genome hybridization, single-nucleotide polymorphism, and microsatellite analyses. In these applications, the reliability of the amplification techniques is particularly important. In PCR-based approaches, the plateau effect can seriously alter the original relative copy number of certain chromosomal regions. To eliminate this distorting effect, we improved the standard degenerate oligonucleotide-primed PCR (DOP-PCR) technique by following the amplification status with quantitative real-time PCR (QRT-PCR). With real-time detection of the products, we could eliminate DNA overamplification. Probes were prepared from 10 different tumor samples: primary and metastatic melanoma tissues, epidermoid and bronchioloalveolar lung carcinomas, 2 renal cell carcinomas, 2 colorectal carcinomas, and a Conn and Cushing adenoma. Probes were generated by using nonamplified and amplified genomic DNA with DOP-PCR and DOP-PCR combined with QRT-PCR. To demonstrate the reliability of the QRT-PCR based amplification protocol, altogether 152 relative copy number changes of 44 regions were determined. There was 85.6% concordance in copy number alterations between the QRT-PCR protocol and the nonamplified samples, whereas this value was only 63.8% for the traditional DOP-PCR. Our results demonstrate that our protocol preserves the original copy number of different chromosomal regions in amplified genomic DNA than standard DOP-PCR techniques more accurately.

Over-expression of dopamine D2 receptor and inwardly rectifying potassium channel genes in drug-naive schizophrenic peripheral blood lymphocytes as potential diagnostic markers.

Schizophrenia is one of the most common neuropsychiatric disorders affecting nearly 1% of the human population. Current diagnosis of schizophrenia is based on complex clinical symptoms. The use of easily detectable peripheral molecular markers could substantially help the diagnosis of psychiatric disorders. Recent studies showed that peripheral blood lymphocytes (PBL) express subtypes of D1 and D2 subclasses of dopamine receptors. Recently, dopamine receptor D3 (DRD3) was found to be over-expressed in schizophrenic PBL and proposed to be a diagnostic and follow-up marker for schizophrenia. In this study we screened PBL of 13 drug-naive/drug-free schizophrenic patients to identify additional markers of schizophrenia. One of the benefits of our study is the use of blood samples of non-medicated, drug-naive patients. This excludes the possibility that changes detected in gene expression levels might be attributed to the medication rather than to the disorder itself. Among others, genes for dopamine receptor D2 (DRD2) and the inwardly rectifying potassium channel (Kir2.3) were found to be over-expressed in microarray analysis. Increased mRNA levels were confirmed by quantitative real-time PCR (QRT-PCR) using the SybrGreen method and dual labeled TaqMan probes. The use of both molecular markers allows a more rapid and precise prediction of schizophrenia and might help find the optimal medication for schizophrenic patients.

Real-time polymerase chain reaction-based exponential sample amplification for microarray gene expression profiling.

Conventional approaches to target labeling for gene expression analysis using microarray technology typically require relatively large amounts of RNA, a serious limitation when the available sample is limited. Here we describe an alternative exponential sample amplification method by using quantitative real-time polymerase chain reaction (QRT-PCR) to follow the amplification and eliminate the overamplified cDNA which could distort the quantitative ratio of the starting mRNA population. Probes generated from nonamplified, PCR-amplified, and real-time-PCR-amplified cDNA samples were generated from lipopolysaccharide-treated and nontreated mouse macrophages and hybridized to mouse cDNA microarrays. Signals obtained from the three protocols were compared. Reproducibility and reliability of the methods were determined. The Pearson correlation coefficients for replica experiments were r=0.927 and r=0.687 for QRT-PCR-amplification and PCR-overamplification protocols, respectively. Chi2 test showed that overamplification resulted in major biases in expression ratios, while these alterations could be eliminated by following the cycling status with QRT-PCR. Our exponential sample amplification protocol preserves the original expression ratios and allows unbiased gene expression analysis from minute amounts of starting material.