Xylella fastidiosa: An in vivo system to study possible survival strategies within citrus xylem vessels based on global gene expression analysis

Xylella fastidiosa inhabits the plant xylem, a nutrient-poor environment, so that mechanisms to sense and respond to adverse environmental conditions are extremely important for bacterial survival in the plant host. Although the complete genome sequences of different Xylella strains have been determined, little is known about stress responses and gene regulation in these organisms. In this work, a DNA microarray was constructed containing 2,600 ORFs identified in the genome sequencing project of Xylella fastidiosa 9a5c strain, and used to check global gene expression differences in the bacteria when it is infecting a symptomatic and a tolerant citrus tree. Different patterns of expression were found in each variety, suggesting that bacteria are responding differentially according to each plant xylem environment. The global gene expression profile was determined and several genes related to bacterial survival in stressed conditions were found to be differentially expressed between varieties, suggesting the involvement of different strategies for adaptation to the environment. The expression pattern of some genes related to the heat shock response, toxin and detoxification processes, adaptation to atypical conditions, repair systems as well as some regulatory genes are discussed in this paper. DNA microarray proved to be a powerful technique for global transcriptome analyses. This is one of the first studies of Xylella fastidiosa gene expression in vivo which helped to increase insight into stress responses and possible bacterial survival mechanisms in the nutrient-poor environment of xylem vessels.

rpb2 is a reliable reference gene for quantitative gene expression analysis in the dermatophyte Trichophyton rubrum

The selection of reference genes used for data normalization to quantify gene expression by real-time PCR amplifications (qRT-PCR) is crucial for the accuracy of this technique. In spite of this, little information regarding such genes for qRT-PCR is available for gene expression analyses in pathogenic fungi. Thus, we investigated the suitability of eight candidate reference genes in isolates of the human dermatophyte Trichophyton rubrum subjected to several environmental challenges, such as drug exposure, interaction with human nail and skin, and heat stress. The stability of these genes was determined by geNorm, NormFinder and Best-Keeper programs. The gene with the most stable expression in the majority of the conditions tested was rpb2 (DNA-dependent RNA polymerase II), which was validated in three T. rubrum strains. Moreover, the combination of rpb2 and chs1 (chitin synthase) genes provided for the most reliable qRT-PCR data normalization in T. rubrum under a broad range of biological conditions. To the best of our knowledge this is the first report on the selection of reference genes for qRT-PCR data normalization in dermatophytes and the results of these studies should permit further analysis of gene expression under several experimental conditions, with improved accuracy and reliability.

Multivariate gene expression analysis reveals functional connectivity changes between normal/tumoral prostates

Abstract Background Prostate cancer is a leading cause of death in the male population, therefore, a comprehensive study about the genes and the molecular networks involved in the tumoral prostate process becomes necessary. In order to understand the biological process behind potential biomarkers, we have analyzed a set of 57 cDNA microarrays containing ~25,000 genes. Results Principal Component Analysis (PCA) combined with the Maximum-entropy Linear Discriminant Analysis (MLDA) were applied in order to identify genes with the most discriminative information between normal and tumoral prostatic tissues. Data analysis was carried out using three different approaches, namely: (i) differences in gene expression levels between normal and tumoral conditions from an univariate point of view; (ii) in a multivariate fashion using MLDA; and (iii) with a dependence network approach. Our results show that malignant transformation in the prostatic tissue is more related to functional connectivity changes in their dependence networks than to differential gene expression. The MYLK, KLK2, KLK3, HAN11, LTF, CSRP1 and TGM4 genes presented significant changes in their functional connectivity between normal and tumoral conditions and were also classified as the top seven most informative genes for the prostate cancer genesis process by our discriminant analysis. Moreover, among the identified genes we found classically known biomarkers and genes which are closely related to tumoral prostate, such as KLK3 and KLK2 and several other potential ones. Conclusion We have demonstrated that changes in functional connectivity may be implicit in the biological process which renders some genes more informative to discriminate between normal and tumoral conditions. Using the proposed method, namely, MLDA, in order to analyze the multivariate characteristic of genes, it was possible to capture the changes in dependence networks which are related to cell transformation.

Semantic integration of gene expression analysis tools and data sources using software connectors

Abstract Background The study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heteregeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data. Results We have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data. Conclusions The proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools and data sources. The methodology can be used in the development of connectors supporting both simple and nontrivial processing requirements, thus assuring accurate data exchange and information interpretation from exchanged data.

GEDI: a user-friendly toolbox for analysis of large-scale gene expression data

Abstract Background Several mathematical and statistical methods have been proposed in the last few years to analyze microarray data. Most of those methods involve complicated formulas, and software implementations that require advanced computer programming skills. Researchers from other areas may experience difficulties when they attempting to use those methods in their research. Here we present an user-friendly toolbox which allows large-scale gene expression analysis to be carried out by biomedical researchers with limited programming skills. Results Here, we introduce an user-friendly toolbox called GEDI (Gene Expression Data Interpreter), an extensible, open-source, and freely-available tool that we believe will be useful to a wide range of laboratories, and to researchers with no background in Mathematics and Computer Science, allowing them to analyze their own data by applying both classical and advanced approaches developed and recently published by Fujita et al. Conclusion GEDI is an integrated user-friendly viewer that combines the state of the art SVR, DVAR and SVAR algorithms, previously developed by us. It facilitates the application of SVR, DVAR and SVAR, further than the mathematical formulas present in the corresponding publications, and allows one to better understand the results by means of available visualizations. Both running the statistical methods and visualizing the results are carried out within the graphical user interface, rendering these algorithms accessible to the broad community of researchers in Molecular Biology.

Impact of hypoxia on IGF-I, IGF-II, IGFBP-3, ALS and IGFBP-1 regulation and on IGF1R gene expression in children

Hypoxia is one of many factors involved in the regulation of the IGF system. However, no information is available regarding the regulation of the IGF system by acute hypoxia in humans. Objective: The aim of this study was to evaluate the effect of acute hypoxia on the IGF system of children. Design: Twenty-seven previously health children (14 boys and 13 girls) aged 15 days to 9.5 years were studied in two different situations: during a hypoxemic state (HS) due to acute respiratory distress and after full recovery to a normoxemic state (NS). In these two situations oxygen saturation was assessed with a pulse-oximeter and blood samples were collected for serum IGF-I, IGF-II, IGFBP-1, IGFBP-3, ALS and insulin determination by ELISA; fluoroimmunometric assay determination for GH and also for IGF1R gene expression analysis in peripheral lymphocytes by quantitative real-time PCR. Data were paired and analyzed by the Wilcoxon non-parametric test. Results: Oxygen saturation was significantly lower during HS than in NS (P<0.0001). IGF-I and IGF-II levels were lower during HS than in NS (P<0.0001 and P=0.0004. respectively). IGFBP-3 levels were also lower in HS than in NS (P=0.0002) while ALS and basal GH levels were higher during HS (P=0.0015 and P=0.014, respectively). Moreover, IGFBP-1 levels were higher during HS than in NS (P=0.004). No difference was found regarding insulin levels. The expression of IGF1R mRNA as 2(-Delta Delta CT) was higher during HS than in NS (P=0.03). Conclusion: The above results confirm a role of hypoxia in the regulation of the IGF system also in humans. This effect could be direct on the liver and/or mediated by GH and it is not restricted to the hepatocytes but involves other cell lines. During acute hypoxia a combination of alterations usually associated with reduced IGF action was observed. The higher expression of IGF1R mRNA may reflect an up-regulation of the transcriptional process. (C) 2012 Elsevier Ltd. All rights reserved.

Differential Gene Expression Profiles May Differentiate Responder and Nonresponder Patients with Rheumatoid Arthritis for Methotrexate (MTX) Monotherapy and MTX plus Tumor Necrosis Factor Inhibitor Combined Therapy

Objective. We aimed to evaluate whether the differential gene expression profiles of patients with rheumatoid arthritis (RA) could distinguish responders from nonresponders to methotrexate (MTX) and, in the case of MTX nonresponders, responsiveness to MTX plus anti-tumor necrosis factor-alpha (anti-TNF) combined therapy. Methods. We evaluated 25 patients with RA taking MTX 15-20 mg/week as a monotherapy (8 responders and 17 nonresponders). All MTX nonresponders received intliximab and were reassessed after 20 weeks to evaluate their anti-TNF responsiveness using the European League Against Rheumatism response criteria. A differential gene expression analysis from peripheral blood mononuclear cells was performed in terms of hierarchical gene clustering, and an evaluation of differentially expressed genes was performed using the significance analysis of microarrays program. Results. Hierarchical gene expression clustering discriminated MTX responders from nonresponders, and MTX plus anti-TNF responders from nonresponders. The evaluation of only highly modulated genes (fold change > 1.3 or < 0.7) yielded 5 induced (4 antiapoptotic and CCL4) and 4 repressed (4 proapoptotic) genes in MTX nonresponders compared to responders. In MTX plus anti-TNF nonresponders, the CCL4, CD83, and BCL2A1 genes were induced in relation to responders. Conclusion. Study of the gene expression profiles of RA peripheral blood cells permitted differentiation of responders from nonresponders to MTX and anti-TNF. Several candidate genes in MTX non-responders (CCL4, HTRA2, PRKCD, BCL2A1, CAV1, TNIP1 CASP8AP2, MXD1, and BTG2) and 3 genes in MTX plus anti-TNF nonresponders (CCL4, CD83, and BCL2A1) were identified for further study. (First Release July 1 2012; J Rheumatol 2012;39:1524-32; doi:10.3899/jrheum.120092)

Study of cerebral gene expression densities using Voronoi analysis

As the available public cerebral gene expression image data increasingly grows, the demand for automated methods to analyze such large amount of data also increases. An important study that can be carried out on these data is related to the spatial relationship between gene expressions. Similar spatial density distribution of expression between genes may indicate they are functionally correlated, thus the identification of these similarities is useful in suggesting directions of investigation to discover gene interactions and their correlated functions. In this paper, we describe the use of a high-throughput methodology based on Voronoi diagrams to automatically analyze and search for possible local spatial density relationships between gene expression images. We tested this method using mouse brain section images from the Allen Mouse Brain Atlas public database. This methodology provided measurements able to characterize the similarity of the density distribution between gene expressions and allowed the visualization of the results through networks and Principal Component Analysis (PCA). These visualizations are useful to analyze the similarity level between gene expression patterns, as well as to compare connection patterns between region networks. Some genes were found to have the same type of function and to be near each other in the PCA visualizations. These results suggest cerebral density correlations between gene expressions that could be further explored. (C) 2011 Elsevier B.V. All rights reserved.

Bayesian model accounting for within-class biological variability in Serial Analysis of Gene Expression (SAGE)

Abstract Background An important challenge for transcript counting methods such as Serial Analysis of Gene Expression (SAGE), "Digital Northern" or Massively Parallel Signature Sequencing (MPSS), is to carry out statistical analyses that account for the within-class variability, i.e., variability due to the intrinsic biological differences among sampled individuals of the same class, and not only variability due to technical sampling error. Results We introduce a Bayesian model that accounts for the within-class variability by means of mixture distribution. We show that the previously available approaches of aggregation in pools ("pseudo-libraries") and the Beta-Binomial model, are particular cases of the mixture model. We illustrate our method with a brain tumor vs. normal comparison using SAGE data from public databases. We show examples of tags regarded as differentially expressed with high significance if the within-class variability is ignored, but clearly not so significant if one accounts for it. Conclusion Using available information about biological replicates, one can transform a list of candidate transcripts showing differential expression to a more reliable one. Our method is freely available, under GPL/GNU copyleft, through a user friendly web-based on-line tool or as R language scripts at supplemental web-site.

Analysis of ripening-related gene expression in papaya using an Arabidopsis-based microarray

Abstract Background Papaya (Carica papaya L.) is a commercially important crop that produces climacteric fruits with a soft and sweet pulp that contain a wide range of health promoting phytochemicals. Despite its importance, little is known about transcriptional modifications during papaya fruit ripening and their control. In this study we report the analysis of ripe papaya transcriptome by using a cross-species (XSpecies) microarray technique based on the phylogenetic proximity between papaya and Arabidopsis thaliana. Results Papaya transcriptome analyses resulted in the identification of 414 ripening-related genes with some having their expression validated by qPCR. The transcription profile was compared with that from ripening tomato and grape. There were many similarities between papaya and tomato especially with respect to the expression of genes encoding proteins involved in primary metabolism, regulation of transcription, biotic and abiotic stress and cell wall metabolism. XSpecies microarray data indicated that transcription factors (TFs) of the MADS-box, NAC and AP2/ERF gene families were involved in the control of papaya ripening and revealed that cell wall-related gene expression in papaya had similarities to the expression profiles seen in Arabidopsis during hypocotyl development. Conclusion The cross-species array experiment identified a ripening-related set of genes in papaya allowing the comparison of transcription control between papaya and other fruit bearing taxa during the ripening process.

Gene expression profiles displayed by peripheral blood mononuclear cells from patients with type 2 diabetes mellitus focusing on biological processes implicated on the pathogenesis of the disease

Patients with type 2 diabetes mellitus (T2DM) exhibit insulin resistance associated with obesity and inflammatory response, besides an increased level of oxidative DNA damage as a consequence of the hyperglycemic condition and the generation of reactive oxygen species (ROS). In order to provide information on the mechanisms involved in the pathophysiology of T2DM, we analyzed the transcriptional expression patterns exhibited by peripheral blood mononuclear cells (PBMCs) from patients with T2DM compared to non-diabetic subjects, by investigating several biological processes: inflammatory and immune responses, responses to oxidative stress and hypoxia, fatty acid processing, and DNA repair. PBMCs were obtained from 20 T2DM patients and eight non-diabetic subjects. Total RNA was hybridized to Agilent whole human genome 4x44K one-color oligo-microarray. Microarray data were analyzed using the GeneSpring GX 11.0 software (Agilent). We used BRB-ArrayTools software (gene set analysis - GSA) to investigate significant gene sets and the Genomica tool to study a possible influence of clinical features on gene expression profiles. We showed that PBMCs from T2DM patients presented significant changes in gene expression, exhibiting 1320 differentially expressed genes compared to the control group. A great number of genes were involved in biological processes implicated in the pathogenesis of T2DM. Among the genes with high fold-change values, the up-regulated ones were associated with fatty acid metabolism and protection against lipid-induced oxidative stress, while the down-regulated ones were implicated in the suppression of pro-inflammatory cytokines production and DNA repair. Moreover, we identified two significant signaling pathways: adipocytokine, related to insulin resistance; and ceramide, related to oxidative stress and induction of apoptosis. In addition, expression profiles were not influenced by patient features, such as age, gender, obesity, pre/post-menopause age, neuropathy, glycemia, and HbA(1c) percentage. Hence, by studying expression profiles of PBMCs, we provided quantitative and qualitative differences and similarities between T2DM patients and non-diabetic individuals, contributing with new perspectives for a better understanding of the disease. (C) 2012 Elsevier B.V. All rights reserved.

Gene Expression in Bovine Oocytes and Cumulus Cells After Meiotic Inhibition with the Cyclin-Dependent Kinase Inhibitor Butyrolactone I

Contents The aim of this study was to determine the effect of temporary inhibition of meiosis using the cyclin-dependent kinase inhibitor butyrolactone I (BLI) on gene expression in bovine oocytes and cumulus cells. Immature bovine cumulusoocyte complexes (COCs) were assigned to groups: (i) Control COCs collected immediately after recovery from the ovary or (ii) after in vitro maturation (IVM) for 24 h, (iii) Inhibited COCs collected 24 h after incubation with 100 mu m BLI or (iv) after meiotic inhibition for 24 h followed by IVM for a further 22 h. For mRNA relative abundance analysis, pools of 10 denuded oocytes and respective cumulus cells were collected. Transcripts related to cell cycle regulation and oocyte competence were evaluated in oocytes and cumulus cells by quantitative real-time PCR (qPCR). Most of the examined transcripts were downregulated (p < 0.05) after IVM in control and inhibited oocytes (19 of 35). Nine transcripts remained stable (p > 0.05) after IVM in control oocytes; only INHBA did not show this pattern in inhibited oocytes. Seven genes were upregulated after IVM in control oocytes (p < 0.05), and only PLAT, RBP1 and INHBB were not upregulated in inhibited oocytes after IVM. In cumulus cells, six genes were upregulated (p < 0.05) after IVM and eight were downregulated (p < 0.05). Cells from inhibited oocytes showed the same pattern of expression regarding maturation profile, but were affected by the temporary meiosis inhibition of the oocyte when the same maturation stages were compared between inhibited and control groups. In conclusion, changes in transcript abundance in oocytes and cumulus cells during maturation in vitro were mostly mirrored after meiotic inhibition followed by maturation.

Gene copy number and differential gene expression in haploid and diploid males of the stingless bee, Melipona quadrifasciata

Complementary sex determination in Hymenoptera implies that heterozygosity at the sex locus leads to the development of diploid females, whereas hemizygosity results in haploid males. Diploid males can arise through inbreeding. In social species, these pose a double burden on colony fitness, from significant reduction in its worker force and through being less viable and fertile than haploid males. Apart from being "misfits", diploid males are of interest to assess molecular correlates for possibly ploidy-related bionomic differences. Herein, we generated suppression subtractive cDNA libraries from newly emerged haploid and diploid males of the stingless bee Melipona quadrifasciata to enrich for differentially expressed genes. Gene Ontology classification revealed that in haploid males more DEGs were related to stress responsiveness, biosynthetic processes, reproductive processes and spermatogenesis, whereas in diploid ones differentially expressed genes were associated with cellular organization, nervous system development and amino acid transport were prevalent. Furthermore, both libraries contained over 40 % ESTs representing possibly novel transcripts. Quantitative RT-PCR analyses confirmed the differential expression of a representative DEG set in newly emerged males. Several muscle formation and energy metabolism-related genes were under-expressed in diploid males. On including 5-day-old males in the analysis, changes in transcript abundance during sexual maturation were revealed.

Homeobox gene expression profile indicates HOXA5 as a candidate prognostic marker in oral squamous cell carcinoma

The search for molecular markers to improve diagnosis, individualize treatment and predict behavior of tumors has been the focus of several studies. This study aimed to analyze homeobox gene expression profile in oral squamous cell carcinoma (OSCC) as well as to investigate whether some of these genes are relevant molecular markers of prognosis and/or tumor aggressiveness. Homeobox gene expression levels were assessed by microarrays and qRT-PCR in OSCC tissues and adjacent non-cancerous matched tissues (margin), as well as in OSCC cell lines. Analysis of microarray data revealed the expression of 147 homeobox genes, including one set of six at least 2-fold up-regulated, and another set of 34 at least 2-fold down-regulated homeobox genes in OSCC. After qRT-PCR assays, the three most up-regulated homeobox genes (HOXA5, HOXD10 and HOXD11) revealed higher and statistically significant expression levels in OSCC samples when compared to margins. Patients presenting lower expression of HOXA5 had poorer prognosis compared to those with higher expression (P=0.03). Additionally, the status of HOXA5, HOXD10 and HOXD11 expression levels in OSCC cell lines also showed a significant up-regulation when compared to normal oral keratinocytes. Results confirm the presence of three significantly upregulated (>4-fold) homeobox genes (HOXA5, HOXD10 and HOXD11) in OSCC that may play a significant role in the pathogenesis of these tumors. Moreover, since lower levels of HOXA5 predict poor prognosis, this gene may be a novel candidate for development of therapeutic strategies in OSCC.

T-3 Rapidly Increases SLC2A4 Gene Expression and GLUT4 Trafficking to the Plasma Membrane in Skeletal Muscle of Rat and Improves Glucose Homeostasis

Background: Glucose transporter 4 (GLUT4) is highly expressed in muscle and fat tissue, where triiodothyronine (T-3) induces solute carrier family 2 facilitated glucose transporter member 4 (SLC2A4) gene transcription. T-3 was also shown to rapidly increase glucose uptake in myocytes exposed to cycloheximide, indicating that it might act nongenomically to regulate GLUT4 availability. We tested this hypothesis by evaluating, in thyroidectomized rats (Tx rats), the acute and/or chronic T-3 effects on GLUT4 mRNA expression and polyadenylation, protein content, and trafficking to the plasma membrane (PM) in skeletal muscle, as well as on blood glucose disappearance rate (kITT) after insulin administration. Methods: Rats were surgically thyroidectomized and treated with T-3 (0.3 to 100 mu g/100 g body weight) from 10 minutes to 5 days, and killed thereafter. Sham-operated (SO) rats were used as controls. Total RNA was extracted from the skeletal muscles (soleus [SOL] and extensorum digitalis longus [EDL]) and subjected to Northern blotting analysis using rat GLUT4 cDNA probe. Total protein was extracted and subjected to specific centrifugations for subcellular fractionation, and PM as well as microsomal (M) fractions were subjected to Western blotting analysis, using anti-GLUT4 antiserum as a probe. GLUT4 mRNA polyadenylation was examined by a rapid amplification of cDNA ends-poly(A) test (RACE-PAT). Results: Thyroidectomy reduced skeletal muscle GLUT4 mRNA, mRNA poly(A) tail length, protein content, and trafficking to the PM, as well as the kITT. The acute T-3 treatment rapidly (30 minutes) increased all these parameters compared with Tx rats. The 5-day T-3 treatment increased GLUT4 mRNA and protein expression, and restored GLUT4 trafficking to the PM and kITT to SO values. Conclusions: The results presented here show for the first time that, in parallel to its transcriptional action on the SLC2A4 gene, T-3 exerts a rapid post-transcriptional effect on GLUT4 mRNA polyadenylation, which might increase transcript stability and translation efficiency, leading to the increased GLUT4 content and availability to skeletal muscle, as well as on GLUT4 translocation to the PM, improving the insulin sensitivity, as shown by the kITT.