Glycogen synthase kinases 3α and 3β in cardiac myocytes: regulation and consequences of their inhibition

Inhibition of glycogen synthase kinase 3β (GSK3β) as a consequence of its phosphorylation by protein kinase B/Akt (PKB/Akt) has been implicated in cardiac myocyte hypertrophy in response to endothelin-1 or phenylephrine. We examined the regulation of GSK3α (which we show to constitute a significant proportion of the myocyte GSK3 pool) and GSK3β in cardiac myocytes. Although endothelin increases phosphorylation of GSK3 and decreases its activity, the response is less than that induced by insulin (which does not promote cardiac myocyte hypertrophy). GSK3 phosphorylation induced by endothelin requires signalling through the extracellular signal-regulated kinase 1/2 (ERK1/2) cascade and not the PKB/Akt pathway, whereas the reverse is true for insulin. Cardiac myocyte hypertrophy involves changes in morphology, and in gene and protein expression. The potent GSK3 inhibitor 1-azakenpaullone increases myocyte area as a consequence of increased cell length whereas phenylephrine increases both length and width. Azakenpaullone or insulin promotes AP1 transcription factor binding to an AP1 consensus oligonucleotide, but this was significantly less than that induced by endothelin and derived principally from increased binding of JunB protein, the expression of which was increased. Azakenpaullone promotes significant changes in gene expression (assessed by Affymetrix microarrays), but the overall response is less than with endothelin and there is little overlap between the genes identified. Thus, although GSK3 may contribute to cardiac myocyte hypertrophy in some respects (and presumably plays an important role in myocyte metabolism), it does not appear to contribute as significantly to the response induced by endothelin as has been maintained.

The transcriptome of Populus in elevated CO2

The consequences of increasing atmospheric carbon dioxide for long-term adaptation of forest ecosystems remain uncertain, with virtually no studies undertaken at the genetic level. A global analysis using cDNA microarrays was conducted following 6 yr exposure of Populus × euramericana (clone I-214) to elevated [CO2] in a FACE (free-air CO2 enrichment) experiment.• Gene expression was sensitive to elevated [CO2] but the response depended on the developmental age of the leaves, and < 50 transcripts differed significantly between different CO2 environments. For young leaves most differentially expressed genes were upregulated in elevated [CO2], while in semimature leaves most were downregulated in elevated [CO2].• For transcripts related only to the small subunit of Rubisco, upregulation in LPI 3 and downregulation in LPI 6 leaves in elevated CO2 was confirmed by anova. Similar patterns of gene expression for young leaves were also confirmed independently across year 3 and year 6 microarray data, and using real-time RT–PCR.• This study provides the first clues to the long-term genetic expression changes that may occur during long-term plant response to elevated CO2.

Gene-chip technology and its applications

Gene Chips are finding extensive use in animal and plant science. Generally microarrays are of two kind, cDNA or oligonucleotide. cDNA microarrays were developed at Stanford University, whereas oligonucleotide were developed by Affymetrix. The construction of cDNA or oligonucleotide on a glass slide helps to compare the gene expression level of treated and control samples by labeling mRNA with green (Cy3) and red (Cy5) dyes. The hybridized gene chip emit fluorescence whose intensity and colour can be measured. RNA labeling can be done directly or indirectly. Indirect method involves amino allyle modified dUTP instead of pre-labelled nucleotide. Hybridization of gene chip generally occurs in a minimum volume possible and to ensure the hetroduplex formation, a ten fold more DNA is spotted on slide than in the solutions. A confocal or semi confocal laser technologies coupled with CCD camera are used for image acquisition. For standardization, house keeping genes are used or cDNA are spotted in gene chip that are not present in treated or control samples. Moreover, statistical analysis (image analysis) and cluster analysis softwares have been developed by Stanford University. The gene-chip technology has many applications like expression analysis, gene expression signatures (molecular phenotypes) and promoter regulatory element co-expression.

Eight-plex iTRAQ analysis of variant metastatic human prostate cancer cells identifies candidate biomarkers of progression: an exploratory study.

BACKGROUND: Due to the heterogeneity in the biological behavior of prostate cancer, biomarkers that can reliably distinguish indolent from aggressive disease are urgently needed to inform treatment choices. METHODS: We employed 8-plex isobaric Tags for Relative and Absolute Quantitation (iTRAQ), to profile the proteomes of two distinct panels of isogenic prostate cancer cells with varying growth and metastatic potentials, in order to identify novel biomarkers associated with progression. The LNCaP, LNCaP-Pro5, and LNCaP-LN3 panel of cells represent a model of androgen-responsive prostate cancer, while the PC-3, PC-3M, and PC-3M-LN4 panel represent a model of androgen-insensitive disease. RESULTS: Of the 245 unique proteins identified and quantified (>or=95% confidence; >or=2 peptides/protein), 17 showed significant differential expression (>or=+/-1.5), in at least one of the variant LNCaP cells relative to parental cells. Similarly, comparisons within the PC-3 panel identified 45 proteins to show significant differential expression in at least one of the variant PC-3 cells compared with parental cells. Differential expression of selected candidates was verified by Western blotting or immunocytochemistry, and corresponding mRNA expression was determined by quantitative real-time PCR (qRT-PCR). Immunostaining of prostate tissue microarrays for ERp5, one of the candidates identified, showed a significant higher immunoexpression in pre-malignant lesions compared with non-malignant epithelium (P < 0.0001, Mann-Whitney U-test), and in high Gleason grade (4-5) versus low grade (2-3) cancers (P < 0.05). CONCLUSIONS: Our study provides proof of principle for the application of an 8-plex iTRAQ approach to uncover clinically relevant candidate biomarkers for prostate cancer progression.

Feedback regulation by Atf3 in the endothelin-1-responsive transcriptome of cardiomyocytes: Egr1 is a principal Atf3 target

Endothelin-1 promotes cardiomyocyte hypertrophy by inducing changes in gene expression. Immediate early genes including activating transcription factor 3 (Atf3), Egr1 and Ptgs2 are rapidly and transiently upregulated by endothelin-1 in cardiomyocytes. Atf3 regulates expression of downstream genes and is implicated in negative feedback regulation of other immediate early genes. To identify Atf3-regulated genes, we knocked down Atf3 expression in cardiomyocytes exposed to endothelin-1 and used microarrays to interrogate the transcriptomic effects. Of upregulated mRNAs, expression of 23 (including Egr1, Ptgs2) was enhanced and expression of 25 was inhibited by Atf3 knockdown. Using quantitative PCR, we determined that knockdown of Atf3 had little effect on upregulation of Egr1 mRNA over 30 min, but abolished the subsequent decline, causing sustained Egr1 mRNA expression and enhanced protein expression. This resulted from direct binding of Atf3 to the Egr1 promoter. Mathematical modelling established that Atf3 can suffice to suppress Egr1 expression. Given the widespread co-regulation of Atf3 with Egr1, we suggest that the Atf3-Egr1 negative feedback loop is of general significance. Loss of Atf3 caused abnormal cardiomyocyte growth, presumably resulting from dysregulation of target genes. Our data therefore identify Atf3 as a nexus in cardiomyocyte hypertrophy required to facilitate the full and proper growth response.

Optical genetic mapping defines regions of chromosomal variation in serovars of S. enterica subsp enterica of concern for human and animal health

Infections involving Salmonella enterica subsp. enterica serovars have serious animal and human health implications; causing gastroenteritis in humans and clinical symptoms, such as diarrhoea and abortion, in livestock. In this study an optical genetic mapping technique was used to screen 20 field isolate strains from four serovars implicated in disease outbreaks. The technique was able to distinguish between the serovars and the available sequenced strains and group them in agreement with similar data from microarrays and PFGE. The optical maps revealed variation in genome maps associated with antimicrobial resistance and prophage content in S. Typhimurium, and separated the S. Newport strains into two clear geographical lineages defined by the presence of prophage sequences. The technique was also able to detect novel insertions that may have had effects on the central metabolism of some strains. Overall optical mapping allowed a greater level of differentiation of genomic content and spatial information than more traditional typing methods.

Genome scale reconstruction of a Salmonella metabolic model comparison of similarity and differences with a commensal Escherichia coli strain

Salmonella are closely related to commensal Escherichia coli but have gained virulence factors enabling them to behave as enteric pathogens. Less well studied are the similarities and differences that exist between the metabolic properties of these organisms that may contribute toward niche adaptation of Salmonella pathogens. To address this, we have constructed a genome scale Salmonella metabolic model (iMA945). The model comprises 945 open reading frames or genes, 1964 reactions, and 1036 metabolites. There was significant overlap with genes present in E. coli MG1655 model iAF1260. In silico growth predictions were simulated using the model on different carbon, nitrogen, phosphorous, and sulfur sources. These were compared with substrate utilization data gathered from high throughput phenotyping microarrays revealing good agreement. Of the compounds tested, the majority were utilizable by both Salmonella and E. coli. Nevertheless a number of differences were identified both between Salmonella and E. coli and also within the Salmonella strains included. These differences provide valuable insight into differences between a commensal and a closely related pathogen and within different pathogenic strains opening new avenues for future explorations.

The anti-epileptic drug Valproic Acid (VPA) inhibits steroidogenesis in bovine theca and granulosa cells in vitro

Valproic acid (VPA) is used widely to treat epilepsy and bipolar disorder. Women undergoing VPA treatment reportedly have an increased incidence of polycystic ovarian syndrome (PCOS)-like symptoms including hyperandrogenism and oligo- or amenorrhoea. To investigate potential direct effects of VPA on ovarian steroidogenesis we used primary bovine theca (TC) and granulosa (GC) cells maintained under conditions that preserve their 'follicular' phenotype. Effects of VPA (7.8-500 µg/ml) on TC were tested with/without LH. Effects of VPA on GC were tested with/without FSH or IGF analogue. VPA reduced (P<0.0001) both basal (70% suppression; IC(50) 67±10 µg/ml) and LH-induced (93% suppression; IC(50) 58±10 µg/ml) androstenedione secretion by TC. VPA reduced CYP17A1 mRNA abundance (>99% decrease; P<0.0001) with lesser effects on LHR, STAR, CYP11A1 and HSD3B1 mRNA (<90% decrease; P<0.05). VPA only reduced TC progesterone secretion induced by the highest (luteinizing) LH dose tested; TC number was unaffected by VPA. At higher concentrations (125-500 µg/ml) VPA inhibited basal, FSH- and IGF-stimulated estradiol secretion (P<0.0001) by GC without affecting progesterone secretion or cell number. VPA reversed FSH-induced upregulation of CYP19A1 and HSD17B1 mRNA abundance (P<0.001). The potent histone deacetylase (HDAC) inhibitors trichostatin A and scriptaid also suppressed TC androstenedione secretion and granulosal cell oestrogen secretion suggesting that the action of VPA reflects its HDAC inhibitory properties. In conclusion, these findings refute the hypothesis that VPA has a direct stimulatory action on TC androgen output. On the contrary, VPA inhibits both LH-dependent androgen production and FSH/IGF-dependent estradiol production in this in vitro bovine model, likely by inhibition of HDAC.

The early transcriptomic response to interleukin 1β and interleukin 33 in rat neonatal cardiomyocytes

In the heart, inflammatory cytokines including interleukin (IL) 1β are implicated in regulating adaptive and maladaptive changes, whereas IL33 negatively regulates cardiomyocyte hypertrophy and promotes cardioprotection. These agonists signal through a common co-receptor but, in cardiomyocytes, IL1β more potently activates mitogen-activated protein kinases and NFκB, pathways that regulate gene expression. We compared the effects of external application of IL1β and IL33 on the cardiomyocyte transcriptome. Neonatal rat cardiomyocytes were exposed to IL1β or IL33 (0.5, 1 or 2h). Transcriptomic profiles were determined using Affymetrix rat genome 230 2.0 microarrays and data were validated by quantitative PCR. IL1β induced significant changes in more RNAs than IL33 and, generally, to a greater degree. It also had a significantly greater effect in downregulating mRNAs and in regulating mRNAs associated with selected pathways. IL33 had a greater effect on a small, select group of specific transcripts. Thus, differences in intensity of intracellular signals can deliver qualitatively different responses. Quantitatively different responses in production of receptor agonists and transcription factors may contribute to qualitative differences at later times resulting in different phenotypic cellular responses.

Error, reproducibility and sensitivity: a pipeline for data processing of Agilent oligonucleotide expression arrays

Background: Expression microarrays are increasingly used to obtain large scale transcriptomic information on a wide range of biological samples. Nevertheless, there is still much debate on the best ways to process data, to design experiments and analyse the output. Furthermore, many of the more sophisticated mathematical approaches to data analysis in the literature remain inaccessible to much of the biological research community. In this study we examine ways of extracting and analysing a large data set obtained using the Agilent long oligonucleotide transcriptomics platform, applied to a set of human macrophage and dendritic cell samples. Results: We describe and validate a series of data extraction, transformation and normalisation steps which are implemented via a new R function. Analysis of replicate normalised reference data demonstrate that intrarray variability is small (only around 2 of the mean log signal), while interarray variability from replicate array measurements has a standard deviation (SD) of around 0.5 log(2) units (6 of mean). The common practise of working with ratios of Cy5/Cy3 signal offers little further improvement in terms of reducing error. Comparison to expression data obtained using Arabidopsis samples demonstrates that the large number of genes in each sample showing a low level of transcription reflect the real complexity of the cellular transcriptome. Multidimensional scaling is used to show that the processed data identifies an underlying structure which reflect some of the key biological variables which define the data set. This structure is robust, allowing reliable comparison of samples collected over a number of years and collected by a variety of operators. Conclusions: This study outlines a robust and easily implemented pipeline for extracting, transforming normalising and visualising transcriptomic array data from Agilent expression platform. The analysis is used to obtain quantitative estimates of the SD arising from experimental (non biological) intra- and interarray variability, and for a lower threshold for determining whether an individual gene is expressed. The study provides a reliable basis for further more extensive studies of the systems biology of eukaryotic cells.

Changes in gene expression in Arabidopsis shoots during phosphate starvation and the potential for developing smart plants

Our aim was to generate and prove the concept of "smart" plants to monitor plant phosphorus (P) status in Arabidopsis. Smart plants can be genetically engineered by transformation with a construct containing the promoter of a gene up-regulated specifically by P starvation in an accessible tissue upstream of a marker gene such as beta-glucuronidase (GUS). First, using microarrays, we identified genes whose expression changed more than 2.5-fold in shoots of plants growing hydroponically when P, but not N or K, was withheld from the nutrient solution. The transient changes in gene expression occurring immediately (4 h) after P withdrawal were highly variable, and many nonspecific, shock-induced genes were up-regulated during this period. However, two common putative cis-regulatory elements (a PHO-like element and a TATA box-like element) were present significantly more often in the promoters of genes whose expression increased 4 h after the withdrawal of P compared with their general occurrence in the promoters of all genes represented on the microarray. Surprisingly, the expression of only four genes differed between shoots of P-starved and -replete plants 28 h after P was withdrawn. This lull in differential gene expression preceded the differential expression of a new group of 61 genes 100 h after withdrawing P. A literature survey indicated that the expression of many of these "late" genes responded specifically to P starvation. Shoots had reduced P after 100 h, but growth was unaffected. The expression of SQD1, a gene involved in the synthesis of sulfolipids, responded specifically to P starvation and was increased 100 h after withdrawing P. Leaves of Arabidopsis bearing a SQD1::GUS construct showed increased GUS activity after P withdrawal, which was detectable before P starvation limited growth. Hence, smart plants can monitor plant P status. Transferring this technology to crops would allow precision management of P fertilization, thereby maintaining yields while reducing costs, conserving natural resources, and preventing pollution.

Gene expression changes in phosphorus deficient potato (Solanum tuberosum L.) leaves and the potential for diagnostic gene expression markers

Background: There are compelling economic and environmental reasons to reduce our reliance on inorganic phosphate (Pi) fertilisers. Better management of Pi fertiliser applications is one option to improve the efficiency of Pi fertiliser use, whilst maintaining crop yields. Application rates of Pi fertilisers are traditionally determined from analyses of soil or plant tissues. Alternatively, diagnostic genes with altered expression under Pi limiting conditions that suggest a physiological requirement for Pi fertilisation, could be used to manage Pifertiliser applications, and might be more precise than indirect measurements of soil or tissue samples. Results: We grew potato (Solanum tuberosum L.) plants hydroponically, under glasshouse conditions, to control their nutrient status accurately. Samples of total leaf RNA taken periodically after Pi was removed from the nutrient solution were labelled and hybridised to potato oligonucleotide arrays. A total of 1,659 genes were significantly differentially expressed following Pi withdrawal. These included genes that encode proteins involved in lipid, protein, and carbohydrate metabolism, characteristic of Pi deficient leaves and included potential novel roles for genes encoding patatin like proteins in potatoes. The array data were analysed using a support vector machine algorithm to identify groups of genes that could predict the Pi status of the crop. These groups of diagnostic genes were tested using field grown potatoes that had either been fertilised or unfertilised. A group of 200 genes could correctly predict the Pi status of field grown potatoes. Conclusions: This paper provides a proof-of-concept demonstration for using microarrays and class prediction tools to predict the Pi status of a field grown potato crop. There is potential to develop this technology for other biotic and abiotic stresses in field grown crops. Ultimately, a better understanding of crop stresses may improve our management of the crop, improving the sustainability of agriculture.

Using genomic DNA-based probe-selection to improve the sensitivity of high-density oligonucleotide arrays when applied to heterologous species

High-density oligonucleotide (oligo) arrays are a powerful tool for transcript profiling. Arrays based on GeneChip® technology are amongst the most widely used, although GeneChip® arrays are currently available for only a small number of plant and animal species. Thus, we have developed a method to improve the sensitivity of high-density oligonucleotide arrays when applied to heterologous species and tested the method by analysing the transcriptome of Brassica oleracea L., a species for which no GeneChip® array is available, using a GeneChip® array designed for Arabidopsis thaliana (L.) Heynh. Genomic DNA from B. oleracea was labelled and hybridised to the ATH1-121501 GeneChip® array. Arabidopsis thaliana probe-pairs that hybridised to the B. oleracea genomic DNA on the basis of the perfect-match (PM) probe signal were then selected for subsequent B. oleracea transcriptome analysis using a .cel file parser script to generate probe mask files. The transcriptional response of B. oleracea to a mineral nutrient (phosphorus; P) stress was quantified using probe mask files generated for a wide range of gDNA hybridisation intensity thresholds. An example probe mask file generated with a gDNA hybridisation intensity threshold of 400 removed > 68 % of the available PM probes from the analysis but retained >96 % of available A. thaliana probe-sets. Ninety-nine of these genes were then identified as significantly regulated under P stress in B. oleracea, including the homologues of P stress responsive genes in A. thaliana. Increasing the gDNA hybridisation intensity thresholds up to 500 for probe-selection increased the sensitivity of the GeneChip® array to detect regulation of gene expression in B. oleracea under P stress by up to 13-fold. Our open-source software to create probe mask files is freely available http://affymetrix.arabidopsis.info/xspecies/ webcite and may be used to facilitate transcriptomic analyses of a wide range of plant and animal species in the absence of custom arrays.

Genes driving potato tuber initiation and growth: identification based on transcriptional changes using the POCI array

The increasing amount of available expressed gene sequence data makes whole-transcriptome analysis of certain crop species possible. Potato currently has the second largest number of publicly available expressed sequence tag (EST) sequences among the Solanaceae. Most of these ESTs, plus other proprietary sequences, were combined and used to generate a unigene assembly. The set of 246,182 sequences produced 46,345 unigenes, which were used to design a 44K 60-mer oligo array (Potato Oligo Chip Initiative: POCI). In this study, we attempt to identify genes controlling and driving the process of tuber initiation and growth by implementing large-scale transcriptional changes using the newly developed POCI array. Major gene expression profiles could be identified exhibiting differential expression at key developmental stages. These profiles were associated with functional roles in cell division and growth. A subset of genes involved in the regulation of the cell cycle, based on their Gene Ontology classification, exhibit a clear transient upregulation at tuber onset indicating increased cell division during these stages. The POCI array allows the study of potato gene expression on a much broader level than previously possible and will greatly enhance analysis of transcriptional control mechanisms in a wide range of potato research areas. POCI sequence and annotation data are publicly available through the POCI database (http://pgrc.ipk-gatersleben.de/poci).

Root transcriptional responses of two melon genotypes with contrasting resistance to Monosporascus cannonballus (Pollack et Uecker) infection

Background: Monosporascus cannonballus is the main causal agent of melon vine decline disease. Several studies have been carried out mainly focused on the study of the penetration of this pathogen into melon roots, the evaluation of symptoms severity on infected roots, and screening assays for breeding programs. However, a detailed molecular view on the early interaction between M. cannonballus and melon roots in either susceptible or resistant genotypes is lacking. In the present study, we used a melon oligo-based microarray to investigate the gene expression responses of two melon genotypes, Cucumis melo 'Piel de sapo' ('PS') and C. melo 'Pat 81', with contrasting resistance to the disease. This study was carried out at 1 and 3 days after infection (DPI) by M. cannonballus. Results: Our results indicate a dissimilar behavior of the susceptible vs. the resistant genotypes from 1 to 3 DPI. 'PS' responded with a more rapid infection response than 'Pat 81' at 1 DPI. At 3 DPI the total number of differentially expressed genes identified in 'PS' declined from 451 to 359, while the total number of differentially expressed transcripts in 'Pat 81' increased from 187 to 849. Several deregulated transcripts coded for components of Ca2+ and jasmonic acid (JA) signalling pathways, as well as for other proteins related to defence mechanisms. Transcriptional differences in the activation of the JA-mediated response in 'Pat 81' compared to 'PS' suggested that JA response might be partially responsible for their observed differences in resistance. Conclusions: As a result of this study we have identified for the first time a set of candidate genes involved in the root response to the infection of the pathogen causing melon vine decline. This information is useful for understanding the disease progression and resistance mechanisms few days after inoculation.