Integrated metabolite and gene expression profiling revealing phytochrome A regulation of polyamine biosynthesis of Arabidopsis thaliana

In this study, metabolite profiling was demonstrated as a usefultool to plot a specific metabolic pathway, which is regulatedby phytochrome A (phyA). Etiolated Arabidopsis wild-type (WT)and phyA mutant seedlings were irradiated with either far-redlight (FR) or white light (W). Primary metabolites of the irradiatedseedlings were profiled by gas chromatography time-of-flightmass spectrometry (GC/TOF-MS) to obtain new insights on phyA-regulatedmetabolic pathways. Comparison of metabolite profiles in phyAand WT seedlings grown under FR revealed a number of metabolitesthat contribute to the differences between phyA and the WT.Several metabolites, including some amino acids, organic acids,and major sugars, as well as putrescine, were found in smalleramounts in WT compared with the content in phyA seedlings grownunder FR. There were also significant differences between metaboliteprofiles of WT and phyA seedlings during de-etiolation underW. The polyamine biosynthetic pathway was investigated further,because putrescine, one of the polyamines existing in a widevariety of living organisms, was found to be present in loweramounts in WT than in phyA under both light conditions. Theexpression levels of polyamine biosynthesis-related genes wereinvestigated by quantitative real-time RT-PCR. The gene expressionprofiles revealed that the arginine decarboxylase 2 (ADC2) genewas transcribed less in the WT than in phyA seedlings underboth light conditions. This finding suggests that ADC2 is negativelyregulated by phyA during photomorphogenesis. In addition, S-adenosylmethioninedecarboxylase 2 and 4 (SAMDC2 and SAMDC4) were found to be regulatedby phyA but in a different manner from the regulation of ADC2. Key words: Arabidopsis thaliana, gene expression profiling, metabolite profiling, phytochrome A, polyamine biosynthesis Received 19 October 2007; Revised 17 January 2008 Accepted 18 January 2008     

The glutamine synthetase gene family of Arabidopsis thaliana: light-regulation and differential expression in leaves, roots and seeds.

Summary Glutamine synthetase (GS) plays an important role in the assimilation of nitrogen by higher plants. We present here a molecular analysis of the GS polypeptides, mRNAs, and genes of Arabidopsis thaliana. Western blot analysis of leaf and root protein extracts revealed at least two distinct GS polypeptides; 43 kDa and 39 kDa GS polypeptides were present in leaves, while only a 39 kDa GS was detected in roots. The 43 kDa GS polypeptide is light-inducible. In etiolated seedlings only the 39 kDa GS was detected. However, upon greening the 43 kDa GS increased to levels comparable to those observed in light-grown plants. Four distinct GS cDNA clones, Atgsl1, Atgsrl, Atgsr2 and Atk6 were isolated and characterized. Their complete nucleotide and deduced amino acid sequences are presented. The coding sequences of the four clones are 70–88% similar while their 5 and 3 untranslated regions exhibit less than 50% similarity. Northern blots of leaf, root and germinated seed RNA revealed that the four cDNAs hybridize to mRNAs which are differentially expressed in the organs of Arabidopsis thaliana. Atgsl1 is leaf-specific and hybridizes to a 1.6 kb mRNA. Both Atgsr1 and Atgskb6 hybridize to 1.4 kb mRNAs which are expressed in both roots and germinated seeds. Atgsr2 hybridizes to a 1.4 kb mRNA, which is primarily expressed in roots with low levels of expression in seeds and leaves. Atgsl1, which represents the leaf-specific mRNA, is induced by light. Atgsl1 mRNA levels increase during the greening of etiolated seedlings while Atgsr1 levels remain constant. Southern blot analysis indicated that the Arabidopsis genome contains at least four and possibly five distinct GS genes.     

Dynamic models of gene expression and classification

Powerful new methods, like expression profiles using cDNA arrays, have been used to monitor changes in gene expression levels as a result of a variety of metabolic, xenobiotic or pathogenic challenges. This potentially vast quantity of data enables, in principle, the dissection of the complex genetic networks that control the patterns and rhythms of gene expression in the cell. Here we present a general approach to developing dynamic models for analyzing time series of whole genome expression. In this approach, a self-consistent calculation is performed that involves both linear and non-linear response terms for interrelating gene expression levels. This calculation uses singular value decomposition (SVD) not as a statistical tool but as a means of inverting noisy and near-singular matrices. The linear transition matrix that is determined from this calculation can be used to calculate the underlying network reflected in the data. This suggests a direct method of classifying genes according to their place in the resulting network. In addition to providing a means to model such a large multivariate system this approach can be used to reduce the dimensionality of the problem in a rational and consistent way, and suppress the strong noise amplification effects often encountered with expression profile data. Non-linear and higher-order Markov behavior of the network are also determined in this self-consistent method. In data sets from yeast, we calculate the Markov matrix and the gene classes based on the linear-Markov network. These results compare favorably with previously used methods like cluster analysis. Our dynamic method appears to give a broad and general framework for data analysis and modeling of gene expression arrays. Electronic Publication     

细菌卤代烷烃脱卤酶基因在拟南芥菜中的高效表达

报道了细菌Xanthobacter autotrophicus编码卤代烷烃脱卤酶基因在拟南芥菜中的高效表达。以土壤农杆菌介导将该基因整合到拟南芥菜基因组中,经数代筛选得到了转基因纯合种子,Northern印迹和气相色谱检测表明,转基因的表达程度很高,酶量占细胞总可溶性蛋白的8%,酶活力达7.8mU·ml^-1提取物。转基因植株在含二氯乙烷的培养基上不能生长。     

High-throughput analysis of gene expression on tissue sections by in situ hybridization

Genome-scale sequencing projects, high-throughput RNAi screens, systematic gene targeting, and system-biology-based network predictions all depend on a validation of biological significance in order to understand the relevance of a particular finding. Such validation, for the most part, rests on low-throughput technologies. This article provides protocols that, in combination with suitable instrumentation, make possible a semi-automated analysis of gene expression on tissue sections by means of in situ hybridization. Knowledge of gene expression localization has the potential to aid, and thereby accelerate, the validation of gene functions.     

The clustering of regression models method with applications in gene expression data

Identification of differentially expressed genes and clustering of genes are two important and complementary objectives addressed with gene expression data. For the differential expression question, many "per-gene" analytic methods have been proposed. These methods can generally be characterized as using a regression function to independently model the observations for each gene; various adjustments for multiplicity are then used to interpret the statistical significance of these per-gene regression models over the collection of genes analyzed. Motivated by this common structure of per-gene models, we proposed a new model-based clustering method--the clustering of regression models method, which groups genes that share a similar relationship to the covariate(s). This method provides a unified approach for a family of clustering procedures and can be applied for data collected with various experimental designs. In addition, when combined with per-gene methods for assessing differential expression that employ the same regression modeling structure, an integrated framework for the analysis of microarray data is obtained. The proposed methodology was applied to two microarray data sets, one from a breast cancer study and the other from a yeast cell cycle study.     

Nitric oxide modulates ozone-induced cell death, hormone biosynthesis and gene expression in Arabidopsis thaliana

Nitric oxide (NO) is involved together with reactive oxygen species (ROS) in the activation of various stress responses in plants. We have used ozone (O₃) as a tool to elicit ROS-activated stress responses, and to activate cell death in plant leaves. Here, we have investigated the roles and interactions of ROS and NO in the induction and regulation of O₃-induced cell death. Treatment with O₃ induced a rapid accumulation of NO, which started from guard cells, spread to adjacent epidermal cells and eventually moved to mesophyll cells. During the later time points, NO production coincided with the formation of hypersensitive response (HR)-like lesions. The NO donor sodium nitroprusside (SNP) and O₃ individually induced a large set of defence-related genes; however, in a combined treatment SNP attenuated the O₃ induction of salicylic acid (SA) biosynthesis and other defence-related genes. Consistent with this, SNP treatment also decreased O₃-induced SA accumulation. The O₃-sensitive mutant rcd1 was found to be an NO overproducer; in contrast, Atnoa1/rif1 ( Arabidopsis nitric oxide associated 1/resistant to inhibition by FSM1 ), a mutant with decreased production of NO, was also O₃ sensitive. This, together with experiments combining O₃ and the NO donor SNP suggested that NO can modify signalling, hormone biosynthesis and gene expression in plants during O₃ exposure, and that a functional NO production is needed for a proper O₃ response. In summary, NO is an important signalling molecule in the response to O₃.     

Time-synchronized clustering of gene expression trajectories

Current clustering methods are routinely applied to gene expressiontime course data to find genes with similar activation patternsand ultimately to understand the dynamics of biological processes.As the dynamic unfolding of a biological process often involvesthe activation of genes at different rates, successful clusteringin this context requires dealing with varying time and shapepatterns simultaneously. This motivates the combination of anovel pairwise warping with a suitable clustering method todiscover expression shape clusters. We develop a novel clusteringmethod that combines an initial pairwise curve alignment toadjust for time variation within likely clusters. The cluster-specifictime synchronization method shows excellent performance overstandard clustering methods in terms of cluster quality measuresin simulations and for yeast and human fibroblast data sets.In the yeast example, the discovered clusters have high concordancewith the known biological processes.     

Gene expression profiling of human diseases by serial analysis of gene expression

Until recently, the approach to understanding the molecular basis of complex syndromes such as cancer, coronary artery disease, and diabetes was to study the behavior of individual genes. However, it is generally recognized that expression of a number of genes is coordinated both spatially and temporally and that this coordination changes during the development and progression of diseases. Newly developed functional genomic approaches, such as serial analysis of gene expression (SAGE) and DNA microarrays have enabled researchers to determine the expression pattern of thousands of genes simultaneously. One attractive feature of SAGE compared to microarrays is its ability to quantify gene expression without prior sequence information or information about genes that are thought to be expressed. SAGE has been successfully applied to the gene expression profiling of a number of human diseases. In this review, we will first discuss SAGE technique and contrast it to microarray. We will then highlight new biological insights that have emerged from its application to the study of human diseases.     

Wilt-induced ABA biosynthesis, gene expression and down-regulation of rbcS mRNA levels in Arabidopsis thaliana

The kinetics of wilt-induced abscisic acid (ABA) biosynthesis were investigated in shoots of Arabidopsis thaliana (L.) Heynh Landsberg erecta. ABA concentrations were measured using a radioimmunoassay (RIA) based on the monoclonal antibody MAC 252, and the RIA validated by comparison with combined gas chromatography-mass spectrometry using a [²H₃] labelled internal standard. The basal ABA content of Arabidopsis shoots was ca 10 ng g^?1 fresh weight; the concentrations had increased ca 4-fold within 30 min of the initiation of wilting, increased ca 8-fold after 4 h and 11-fold after 8 h. This stress-induced ABA production was dependent on de novo gene expression; pre-treatment of leaves and shoots with the metabolic inhibitors cordycepin and cycloheximide reduced the rate of subsequent stress-induced ABA biosynthesis from 12.5 ng g^?1 h^?1 to 1 ng g^?1 h^?1 and 0 ng g^?1 h^?1, respectively. In vitro translation of mRNA isolated from shoots subjected to wilting or ABA treatment followed by one-dimensional sodium dodecyl sulphate polyacrylamide gel electrophoresis revealed only minor changes. The effects of wilting and ABA on the content of total ribulose 1,5-bisphosphate carboxylase/oxygenase small sub-unit (rbcS) mRNA were also determined. Both wilting and exogenous ABA resulted in a substantial reduction in the amount of rbcS mRNA, an effect readily reversed by rehydration of wilted shoots. However, the effects of wilting were not mediated solely by newly-synthesised endogenous ABA, as wilting also reduced rbcS mRNA levels in the ABA-deficient aba-1 mutant, which did not produce ABA in response to loss of turgor. The amount of rbcS mRNA was higher in aba-1 shoots, suggesting that cellular rbcS mRNA levels are normally down-regulated by ABA. Cold treatment induced ABA production in wild type shoots only, but resulted in an increased rbcS mRNA content of both wild type and aba-1 shoots.     

Monitoring genome-wide changes in gene expression in response to endogenous cytokinin reveals targets in Arabidopsis thaliana

Cytokinins have been implicated in developmental and growth processes in plants including cell division, chloroplast biogenesis, shoot meristem initiation and senescence. The regulation of these processes requires changes in cytokinin-responsive gene expression. Here, we induced the expression of a bacterial isopentenyl transferase gene, IPT, in transgenic Arabidopsis thaliana seedlings to study the regulation of genome-wide gene expression in response to endogenous cytokinin. Using MPSS (massively parallel signature sequencing) we identified 823 and 917 genes that were up- and downregulated, respectively, following 24 h of IPT induction. When comparing the response to cytokinin after 6 and 24 h, we identified different clusters of genes showing a similar course of regulation. Our study provides researchers with the opportunity to rapidly assess whether genes of interest are regulated by cytokinins.