Global gene expression under nitrogen starvation in Xylella fastidiosa: contribution of the σ54 regulon

Abstract Background Xylella fastidiosa, a Gram-negative fastidious bacterium, grows in the xylem of several plants causing diseases such as citrus variegated chlorosis. As the xylem sap contains low concentrations of amino acids and other compounds, X. fastidiosa needs to cope with nitrogen limitation in its natural habitat. Results In this work, we performed a whole-genome microarray analysis of the X. fastidiosa nitrogen starvation response. A time course experiment (2, 8 and 12 hours) of cultures grown in defined medium under nitrogen starvation revealed many differentially expressed genes, such as those related to transport, nitrogen assimilation, amino acid biosynthesis, transcriptional regulation, and many genes encoding hypothetical proteins. In addition, a decrease in the expression levels of many genes involved in carbon metabolism and energy generation pathways was also observed. Comparison of gene expression profiles between the wild type strain and the rpoN null mutant allowed the identification of genes directly or indirectly induced by nitrogen starvation in a σ54-dependent manner. A more complete picture of the σ54 regulon was achieved by combining the transcriptome data with an in silico search for potential σ54-dependent promoters, using a position weight matrix approach. One of these σ54-predicted binding sites, located upstream of the glnA gene (encoding glutamine synthetase), was validated by primer extension assays, confirming that this gene has a σ54-dependent promoter. Conclusions Together, these results show that nitrogen starvation causes intense changes in the X. fastidiosa transcriptome and some of these differentially expressed genes belong to the σ54 regulon.

Gene expression down-regulation in CD90+ prostate tumor-associated stromal cells involves potential organ-specific genes

Abstract Background The prostate stroma is a key mediator of epithelial differentiation and development, and potentially plays a role in the initiation and progression of prostate cancer. The tumor-associated stroma is marked by increased expression of CD90/THY1. Isolation and characterization of these stromal cells could provide valuable insight into the biology of the tumor microenvironment. Methods Prostate CD90+ stromal fibromuscular cells from tumor specimens were isolated by cell-sorting and analyzed by DNA microarray. Dataset analysis was used to compare gene expression between histologically normal and tumor-associated stromal cells. For comparison, stromal cells were also isolated and analyzed from the urinary bladder. Results The tumor-associated stromal cells were found to have decreased expression of genes involved in smooth muscle differentiation, and those detected in prostate but not bladder. Other differential expression between the stromal cell types included that of the CXC-chemokine genes. Conclusion CD90+ prostate tumor-associated stromal cells differed from their normal counterpart in expression of multiple genes, some of which are potentially involved in organ development.

Modeling gene expression regulatory networks with the sparse vector autoregressive model

Abstract Background To understand the molecular mechanisms underlying important biological processes, a detailed description of the gene products networks involved is required. In order to define and understand such molecular networks, some statistical methods are proposed in the literature to estimate gene regulatory networks from time-series microarray data. However, several problems still need to be overcome. Firstly, information flow need to be inferred, in addition to the correlation between genes. Secondly, we usually try to identify large networks from a large number of genes (parameters) originating from a smaller number of microarray experiments (samples). Due to this situation, which is rather frequent in Bioinformatics, it is difficult to perform statistical tests using methods that model large gene-gene networks. In addition, most of the models are based on dimension reduction using clustering techniques, therefore, the resulting network is not a gene-gene network but a module-module network. Here, we present the Sparse Vector Autoregressive model as a solution to these problems. Results We have applied the Sparse Vector Autoregressive model to estimate gene regulatory networks based on gene expression profiles obtained from time-series microarray experiments. Through extensive simulations, by applying the SVAR method to artificial regulatory networks, we show that SVAR can infer true positive edges even under conditions in which the number of samples is smaller than the number of genes. Moreover, it is possible to control for false positives, a significant advantage when compared to other methods described in the literature, which are based on ranks or score functions. By applying SVAR to actual HeLa cell cycle gene expression data, we were able to identify well known transcription factor targets. Conclusion The proposed SVAR method is able to model gene regulatory networks in frequent situations in which the number of samples is lower than the number of genes, making it possible to naturally infer partial Granger causalities without any a priori information. In addition, we present a statistical test to control the false discovery rate, which was not previously possible using other gene regulatory network models.

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.

Global gene expression profiling of oral cavity cancers suggests molecular heterogeneity within anatomic subsites

Abstract Background Oral squamous cell carcinoma (OSCC) is a frequent neoplasm, which is usually aggressive and has unpredictable biological behavior and unfavorable prognosis. The comprehension of the molecular basis of this variability should lead to the development of targeted therapies as well as to improvements in specificity and sensitivity of diagnosis. Results Samples of primary OSCCs and their corresponding surgical margins were obtained from male patients during surgery and their gene expression profiles were screened using whole-genome microarray technology. Hierarchical clustering and Principal Components Analysis were used for data visualization and One-way Analysis of Variance was used to identify differentially expressed genes. Samples clustered mostly according to disease subsite, suggesting molecular heterogeneity within tumor stages. In order to corroborate our results, two publicly available datasets of microarray experiments were assessed. We found significant molecular differences between OSCC anatomic subsites concerning groups of genes presently or potentially important for drug development, including mRNA processing, cytoskeleton organization and biogenesis, metabolic process, cell cycle and apoptosis. Conclusion Our results corroborate literature data on molecular heterogeneity of OSCCs. Differences between disease subsites and among samples belonging to the same TNM class highlight the importance of gene expression-based classification and challenge the development of targeted therapies.

Adjunct effect of the antimicrobial photodynamic therapy to an association of non-surgical and surgical periodontal treatment in modulation of gene expression

Background: This study has evaluated the effect of antimicrobial photodynamic therapy (aPDT) used in conjunction with non-surgical and surgical periodontal treatment (PT) in modulating gene expression during periodontal wound healing. Methods: Fifteen patients with chronic periodontitis, presenting bilaterally lower molars with class III furcation lesions and scheduled for extraction, were selected. In initial therapy, scaling and root planing (SRP) was performed in the Control Group (CG), while SRP + aPDT were performed in the Test Group (TG). 45 days later, flap surgery plus SRP, and flap surgery plus SRP + aPDT were performed in the CG and TG, respectively. At 21 days post-surgery, the newly formed granulation tissue was collected, and Real-time PCR evaluated the expression of the genes: tumor necrosis factor-?, interleukin-1?, interleukin-4, interleukin-10, matrix metalloproteinase-2 (MMP-2), tissue inhibitor of metalloproteinase-2 (TIMP-2), osteoprotegerin (OPG), receptor activator of nuclear factor- ?B ligand (RANKL), type I collagen, alkaline phosphatase, osteopontin, osteocalcin, and bone sialoprotein. Results: There were statistically significant differences between the groups in relation to mRNA levels for MMP-2 (TG = 3.26 ± 0.89; CG = 4.23 ± 0.97; p = 0.01), TIMP-2/MMP-2 ratio (TG = 0.91 ± 0.34; CG = 0.73 ± 0.32; p = 0.04), OPG (TG = 0.84 ± 0.45; CG = 0.30 ± 0.26; p = 0.001), and OPG/RANKL ratio (TG = 0.60 ± 0.86; CG = 0.23 ± 0.16; p = 0.04), favoring the TG. Conclusion: The present data suggest that the aPDT associated to nonsurgical and surgical periodontal therapy may modulate the extracellular matrix and bone remodeling by up regulating the TIMP- 2/MMP-2 and OPG/RANKL mRNA ratio, but the clinical relevance needs to be evaluated in further studies.

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.

Functional clustering of time series gene expression data by Granger causality

Background: A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes. Results: In this study we perform gene clustering through the identification of Granger causality between and within sets of time series gene expression data. Granger causality is based on the idea that the cause of an event cannot come after its consequence. Conclusions: This kind of analysis can be used as a complementary approach for functional clustering, wherein genes would be clustered not solely based on their expression similarity but on their topological proximity built according to the intensity of Granger causality among them.

Behavioral meaningful opioidergic stimulation activates kappa receptor gene expression

The periaqueductal gray (PAG) has been reported to be a location for opioid regulation of pain and a potential site for behavioral selection in females. Opioid-mediated behavioral and physiological responses differ according to the activity of opioid receptor subtypes. The present study investigated the effects of the peripheral injection of the kappa-opioid receptor agonist U69593 into the dorsal subcutaneous region of animals on maternal behavior and on Oprk1 gene activity in the PAG of female rats. Female Wistar rats weighing 200-250 g at the beginning of the study were randomly divided into 2 groups for maternal behavior and gene expression experiments. On day 5, pups were removed at 7:00 am and placed in another home cage that was distant from their mother. Thirty minutes after removing the pups, the dams were treated with U69593 (0.15 mg/kg, sc) or 0.9% saline (up to 1 mL/kg) and after 30 min were evaluated in the maternal behavior test. Latencies in seconds for pup retrieval, grouping, crouching, and full maternal behavior were scored. The results showed that U69593 administration inhibited maternal behavior (P < 0.05) because a lower percentage of kappa group dams showed retrieval of first pup, retrieving all pups, grouping, crouching and displaying full maternal behavior compared to the saline group. Opioid gene expression was evaluated using real-time reverse-transcription polymerase chain reaction (RT-PCR). A single injection of U69593 increased Oprk1 PAG expression in both virgin (P < 0.05) and lactating female rats (P < 0.01), with no significant effect on Oprm1 or Oprd1 gene activity. Thus, the expression of kappa-opioid receptors in the PAG may be modulated by single opioid receptor stimulation and behavioral meaningful opioidergic transmission in the adult female might occur simultaneously to specific changes in gene expression of kappa-opioid receptor subtype. This is yet another alert for the complex role of the opioid system in female reproduction

Physical training prevents body weight gain but does not modify adipose tissue gene expression

The relationship of body weight (BW) with white adipose tissue (WAT) mass and WAT gene expression pattern was investigated in mice submitted to physical training (PT). Adult male C57BL/6 mice were submitted to two 1.5-h daily swimming sessions (T, N = 18), 5 days/week for 4 weeks or maintained sedentary (S, N = 15). Citrate synthase activity increased significantly in the T group (P < 0.05). S mice had a substantial weight gain compared to T mice (4.06 ± 0.43 vs 0.38 ± 0.28 g, P < 0.01). WAT mass, adipocyte size, and the weights of gastrocnemius and soleus muscles, lung, kidney, and adrenal gland were not different. Liver and heart were larger and the spleen was smaller in T compared to S mice (P < 0.05). Food intake was higher in T than S mice (4.7 ± 0.2 vs 4.0 ± 0.3 g/animal, P < 0.05) but oxygen consumption at rest did not differ between groups. T animals showed higher serum leptin concentration compared to S animals (6.37 ± 0.5 vs 3.11 ± 0.12 ng/mL). WAT gene expression pattern obtained by transcription factor adipocyte determination and differentiation-dependent factor 1, fatty acid synthase, malic enzyme, hormone-sensitive lipase, adipocyte lipid binding protein, leptin, and adiponectin did not differ significantly between groups. Collectively, our results showed that PT prevents BW gain and maintains WAT mass due to an increase in food intake and unchanged resting metabolic rate. These responses are closely related to unchanged WAT gene expression patterns.

Arginine induces GH gene expression by activating NOS/NO signaling in rat isolated hemi-pituitaries

The amino acid arginine (Arg) is a recognized secretagogue of growth hormone (GH), and has been shown to induce GH gene expression. Arg is the natural precursor of nitric oxide (NO), which is known to mediate many of the effects of Arg, such as GH secretion. Arg was also shown to increase calcium influx in pituitary cells, which might contribute to its effects on GH secretion. Although the mechanisms involved in the effects of Arg on GH secretion are well established, little is known about them regarding the control of GH gene expression. We investigated whether the NO pathway and/or calcium are involved in the effects of Arg on GH gene expression in rat isolated pituitaries. To this end, pituitaries from approximately 170 male Wistar rats (~250 g) were removed, divided into two halves, pooled (three hemi-pituitaries) and incubated or not with Arg, as well as with different pharmacological agents. Arg (71 mM), the NO donor sodium nitroprusside (SNP, 1 and 0.1 mM) and a cyclic guanosine monophosphate (cGMP) analogue (8-Br-cGMP, 1 mM) increased GH mRNA expression 60 min later. The NO acceptor hemoglobin (0.3 µM) blunted the effect of SNP, and the combined treatment with Arg and L-NAME (a NO synthase (NOS) inhibitor, 55 mM) abolished the stimulatory effect of Arg on GH gene expression. The calcium channel inhibitor nifedipine (3 µM) also abolished Arg-induced GH gene expression. The present study shows that Arg directly induces GH gene expression in hemi-pituitaries isolated from rats, excluding interference from somatostatinergic neurons, which are supposed to be inhibited by Arg. Moreover, the data demonstrate that the NOS/NO signaling pathway and calcium mediate the Arg effects on GH gene expression.

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.

Gene expression and phenotypic traits of Aggregatibacter actinomycetemcomitans in response to environmental changes

Background and Objective: Periodontopathogens experience several challenges in the oral cavity that may influence their transcription profile and resulting phenotype. This study evaluated the effect of environmental changes on phenotype and gene expression in a serotype b Aggregatibacter actinomycetemcomitans isolate. Material and Methods: Cultures in early exponential phase and at the start of stationary growth phase in microaerophilic and anaerobic atmospheres were evaluated. Cell hydrophobic properties were measured by adherence to n-hexadecane; in addition, adhesion to, and the ability to invade, KB cells was evaluated. Relative transcription of 12 virulence-associated genes was determined by real-time reverse transcritption quantitative PCR. Results: The culture conditions tested in this study were found to influence the phenotypic and genotypic traits of A. actinomycetemcomitans. Cells cultured in microaerophilic conditions were the most hydrophobic, reached the highest adhesion efficiency and showed up-regulation of omp100 (which encodes an adhesion) and pga (related to polysaccharide synthesis). Cells grown anaerobically were more invasive to epithelial cells and showed up-regulation of genes involved in host-cell invasion or apoptosis induction (such as apaH, omp29, cagE and cdtB) and in adhesion to extracellular matrix protein (emaA). Conclusion: Environmental conditions of different oral habitats may influence the expression of factors involved in the binding of A. actinomycetemcomitans to host tissues and the damage resulting thereby, and thus should be considered in in-vitro studies assessing its pathogenic potential.