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.

Resistance to octreotide LAR in acromegalic patients with high SSTR2 expression: analysis of AIP expression

We present here the clinical and molecular data of two patients with acromegaly treated with octreotide LAR after non-curative surgery, and who presented different responses to therapy. Somatostatin receptor type 2 and 5 (SSTR2 and SSTR5), and aryl hydrocarbon receptor-interacting protein (AIP) expression levels were analyzed by qPCR. In both cases, high SSTR2 and low SSTR5 expression levels were detected; however, only one of the patients achieved disease control after octreotide LAR therapy. When we analyzed AIP expression levels of both cases, the patient whose disease was controlled after therapy exhibited AIP expression levels that were two times higher than the patient whose disease was still active. These two cases illustrate that, although the currently available somatostatin analogs bind preferentially to SSTR2, some patients are not responsive to therapy despite high expression of this receptor. This difference could be explained by differences in post-receptor signaling pathways, including the recently described involvement of AIP. Arq Bras Endocrinol Metab. 2012;56(8):501-6

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.

CLONING AND EXPRESSION ANALYSIS OF ALLOGRAFT INFLAMMATORY FACTOR TYPE 1 IN COELOMOCYTES OF ANTARCTIC SEA URCHIN (STERECHINUS NEUMAYERI)

We have cloned and characterized for the first time an allograft inflammatory factor 1 (Sn-AIF-1) from the Antarctic sea urchin. We report the cloning of Sn-AIF-1 cDNA and the characterization of its expression in coelomocytes after a bacterial challenge. The cDNA Sn-AIF-1 has a size of 608 bp and encodes a polypeptide of 151 aa. The deduced amino acid sequence has a putative size of 17.430 Da, an isoelectric point of 4.92, and shows 2 elongation factor handlike motifs that normally bind calcium ions. BLAST analysis revealed close matches with other known AIF-1. The deduced amino acid sequence of Sn-AIF-1 showed high homology with AIF-1 in vertebrates such as fish, mice, and humans; and in the case of invertebrates, the major degree of identity (55%) was with a predicted sequence of the purple sea urchin AIF-1, and 52% corresponded to a sponge. Expression of Sn-AIF-1 mRNA was analyzed by qPCR. Sn-AIF-1 mRNA expression was measured from coelomocytes after a bacterial challenge using RT-PCR and revealed that the gene was upregulated after 24 h. Sn-AIF-1 could participate in the inflammatory response, particularly in the activation of coelomocytes and their survival.

Expression analysis of stem cell-related genes reveal OCT4 as a predictor of poor clinical outcome in medulloblastoma

Aberrant expression of stem cell-related genes in tumors may confer more primitive and aggressive traits affecting clinical outcome. Here, we investigated expression and prognostic value of the neural stem cell marker CD133, as well as of the pluripotency genes LIN28 and OCT4 in 37 samples of pediatric medulloblastoma, the most common and challenging type of embryonal tumor. While most medulloblastoma samples expressed CD133 and LIN28, OCT4 expression was found to be more sporadic, with detectable levels occurring in 48% of tumors. Expression levels of OCT4, but not CD133 or LIN28, were significantly correlated with shorter survival (P <= 0.0001). Median survival time of patients with tumors hyperexpressing OCT4 and tumors displaying low/undetectable OCT4 expression were 6 and 153 months, respectively. More importantly, when patients were clinically stratified according to their risk of tumor recurrence, positive OCT4 expression in primary tumor specimens could discriminate patients classified as average risk but which further deceased within 5 years of diagnosis (median survival time of 28 months), a poor clinical outcome typical of high risk patients. Our findings reveal a previously unknown prognostic value for OCT4 expression status in medulloblastoma, which might be used as a further indicator of poor survival and aid postoperative treatment selection, with a particular potential benefit for clinically average risk patients.

Single-cell expression analysis of BMP15 and GDF9 in mature oocytes and BMPR2 in cumulus cells of women with polycystic ovary syndrome undergoing controlled ovarian hyperstimulation

To detect expression of bone morphogenetic protein 15 (BMP15) and growth differentiation factor 9 (GDF9) in oocytes, and their receptor type 2 receptor for BMPs (BMPR2) in cumulus cells in women with polycystic ovary syndrome (PCOS) undergoing in vitro fertilization (IVF), and determine if BMPR2, BMP15, and GDF9 expression correlate with hyperandrogenism in FF of PCOS patients. Prospective case-control study. Eighteen MII-oocytes and their respective cumulus cells were obtained from 18 patients with PCOS, and 48 MII-oocytes and cumulus cells (CCs) from 35 controls, both subjected to controlled ovarian hyperstimulation (COH), and follicular fluid (FF) was collected from small (10-14 mm) and large (> 18 mm) follicles. RNeasy Micro Kit (Qiagen(A (R))) was used for RNA extraction and gene expression was quantified in each oocyte individually and in microdissected cumulus cells from cumulus-oocyte complexes retrieved from preovulatory follicles using qRT-PCR. Chemiluminescence and RIA assays were used for hormone assays. BMP15 and GDF9 expression per oocyte was higher among women with PCOS than the control group. A positive correlation was found between BMPR2 transcripts and hyperandrogenism in FF of PCOS patients. Progesterone values in FF were lower in the PCOS group. We inferred that BMP15 and GDF9 transcript levels increase in mature PCOS oocytes after COH, and might inhibit the progesterone secretion by follicular cells in PCOS follicles, preventing premature luteinization in cumulus cells. BMPR2 expression in PCOS cumulus cells might be regulated by androgens.

Expression Analysis of Wound Healing Genes in Human Periapical Granulomas of Progressive and Stable Nature

Introduction: Wound healing process involves the activation of extracellular matrix components, remodeling enzymes, cellular adhesion molecules, growth factors, cytokines and chemokines genes. However, the molecular patterns underlying the healing process periapical environment remain unclear. Here we hypothesized that endodontic infection might result in an imbalance in the expression of wound healing genes involved in the pathogenesis of periapical lesions. Furthermore, we suggest that differential expression of wound healing markers in active and latent granulomas could account for different clinical outcomes for such lesions. Methods: Study samples consisted of 93 periapical granulomas collected after endodontic surgeries and 24 healthy periodontal ligament tissues collected from premolars extracted for orthodontic purposes as control samples. Of these, 10 periapical granulomas and 5 healthy periapical tissues were used for expression analysis of 84 wound healing genes by using a pathway-specific real-time polymerase chain reaction array. The remaining 83 granulomas and all 24 control specimens were used to validate the obtained array data by real-time polymerase chain reaction. Observed variations in expression of wound healing genes were analyzed according to the classification of periapical granulomas as active/progressive versus inactive/stable (as determined by receptor activator for nuclear factor kappa B ligand/osteoprotegerin expression ratio). Results: We observed a marked increase of 5-fold or greater in SERPINE1, TIMP1, COL1A1, COL5A1, VTN, CTGF, FGF7, TGFB1, TNF, CXCL11, ITGA4, and ITGA5 genes in the periapical granulomas when compared with control samples. SERPINE1, TIMP1, COL1A1, TGFB1, and ITGA4 mRNA expression was significantly higher in inactive compared with active periapical granulomas (P < .001), whereas TNF and CXCL11 mRNA expression was higher in active lesions (P < .001). Conclusions: The identification of novel gene targets that curb the progression status of periapical lesions might contribute to a more accurate diagnosis and lead to treatment modalities more conducive to endodontic success. (J Endod 2012;38:185-190)

Identification and expression analysis of microRNAs and targets in the biofuel crop sugarcane

Abstract Background MicroRNAs (miRNAs) are small regulatory RNAs, some of which are conserved in diverse plant genomes. Therefore, computational identification and further experimental validation of miRNAs from non-model organisms is both feasible and instrumental for addressing miRNA-based gene regulation and evolution. Sugarcane (Saccharum spp.) is an important biofuel crop with publicly available expressed sequence tag and genomic survey sequence databases, but little is known about miRNAs and their targets in this highly polyploid species. Results In this study, we have computationally identified 19 distinct sugarcane miRNA precursors, of which several are highly similar with their sorghum homologs at both nucleotide and secondary structure levels. The accumulation pattern of mature miRNAs varies in organs/tissues from the commercial sugarcane hybrid as well as in its corresponding founder species S. officinarum and S. spontaneum. Using sugarcane MIR827 as a query, we found a novel MIR827 precursor in the sorghum genome. Based on our computational tool, a total of 46 potential targets were identified for the 19 sugarcane miRNAs. Several targets for highly conserved miRNAs are transcription factors that play important roles in plant development. Conversely, target genes of lineage-specific miRNAs seem to play roles in diverse physiological processes, such as SsCBP1. SsCBP1 was experimentally confirmed to be a target for the monocot-specific miR528. Our findings support the notion that the regulation of SsCBP1 by miR528 is shared at least within graminaceous monocots, and this miRNA-based post-transcriptional regulation evolved exclusively within the monocots lineage after the divergence from eudicots. Conclusions Using publicly available nucleotide databases, 19 sugarcane miRNA precursors and one new sorghum miRNA precursor were identified and classified into 14 families. Comparative analyses between sugarcane and sorghum suggest that these two species retain homologous miRNAs and targets in their genomes. Such conservation may help to clarify specific aspects of miRNA regulation and evolution in the polyploid sugarcane. Finally, our dataset provides a framework for future studies on sugarcane RNAi-dependent regulatory mechanisms.

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.

Expression analysis and in silico characterization of intronic long noncoding RNAs in renal cell carcinoma: emerging functional associations

Abstract Background Intronic and intergenic long noncoding RNAs (lncRNAs) are emerging gene expression regulators. The molecular pathogenesis of renal cell carcinoma (RCC) is still poorly understood, and in particular, limited studies are available for intronic lncRNAs expressed in RCC Methods Microarray experiments were performed with custom-designed arrays enriched with probes for lncRNAs mapping to intronic genomic regions. Samples from 18 primary RCC tumors and 11 nontumor adjacent matched tissues were analyzed. Meta-analyses were performed with microarray expression data from three additional human tissues (normal liver, prostate tumor and kidney nontumor samples), and with large-scale public data for epigenetic regulatory marks and for evolutionarily conserved sequences. Results A signature of 29 intronic lncRNAs differentially expressed between RCC and nontumor samples was obtained (false discovery rate (FDR) <5%). A signature of 26 intronic lncRNAs significantly correlated with the RCC five-year patient survival outcome was identified (FDR <5%, p-value ≤0.01). We identified 4303 intronic antisense lncRNAs expressed in RCC, of which 22% were significantly (p <0.05) cis correlated with the expression of the mRNA in the same locus across RCC and three other human tissues. Gene Ontology (GO) analysis of those loci pointed to 'regulation of biological processes’ as the main enriched category. A module map analysis of the protein-coding genes significantly (p <0.05) trans correlated with the 20% most abundant lncRNAs, identified 51 enriched GO terms (p <0.05). We determined that 60% of the expressed lncRNAs are evolutionarily conserved. At the genomic loci containing the intronic RCC-expressed lncRNAs, a strong association (p <0.001) was found between their transcription start sites and genomic marks such as CpG islands, RNA Pol II binding and histones methylation and acetylation. Conclusion Intronic antisense lncRNAs are widely expressed in RCC tumors. Some of them are significantly altered in RCC in comparison with nontumor samples. The majority of these lncRNAs is evolutionarily conserved and possibly modulated by epigenetic modifications. Our data suggest that these RCC lncRNAs may contribute to the complex network of regulatory RNAs playing a role in renal cell malignant transformation.

Identification of protein expression signatures in gastric carcinomas using clustering analysis

Background and Aim: The identification of gastric carcinomas (GC) has traditionally been based on histomorphology. Recently, DNA microarrays have successfully been used to identify tumors through clustering of the expression profiles. Random forest clustering is widely used for tissue microarrays and other immunohistochemical data, because it handles highly-skewed tumor marker expressions well, and weighs the contribution of each marker according to its relatedness with other tumor markers. In the present study, we e identified biologically- and clinically-meaningful groups of GC by hierarchical clustering analysis of immunohistochemical protein expression. Methods: We selected 28 proteins (p16, p27, p21, cyclin D1, cyclin A, cyclin B1, pRb, p53, c-met, c-erbB-2, vascular endothelial growth factor, transforming growth factor [TGF]-beta I, TGF-beta II, MutS homolog-2, bcl-2, bax, bak, bcl-x, adenomatous polyposis coli, clathrin, E-cadherin, beta-catenin, mucin (MUC) 1, MUC2, MUC5AC, MUC6, matrix metalloproteinase [ MMP]-2, and MMP-9) to be investigated by immunohistochemistry in 482 GC. The analyses of the data were done using a random forest-clustering method. Results: Proteins related to cell cycle, growth factor, cell motility, cell adhesion, apoptosis, and matrix remodeling were highly expressed in GC. We identified protein expressions associated with poor survival in diffuse-type GC. Conclusions: Based on the expression analysis of 28 proteins, we identified two groups of GC that could not be explained by any clinicopathological variables, and a subgroup of long-surviving diffuse-type GC patients with a distinct molecular profile. These results provide not only a new molecular basis for understanding the biological properties of GC, but also better prediction of survival than the classic pathological grouping.

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.

Swimming Training in Rats Increases Cardiac MicroRNA-126 Expression and Angiogenesis

DA SILVA, N. D. JR, T. FERNANDES, U. P. R. SOCI, A. W. A. MONTEIRO, M. I. PHILLIPS, and E. M. DE OLIVEIRA. Swimming Training in Rats Increases Cardiac MicroRNA-126 Expression and Angiogenesis. Med. Sci. Sports Exerc., Vol. 44, No. 8, pp. 1453-1462, 2012. Purpose: MicroRNA (miRNA)-126 is angiogenic and has two validated targets: Sprouty-related protein 1 (Spred-1) and phosphoinositol-3 kinase regulatory subunit 2 (PI3KR2), negative regulators of angiogenesis by VEGF pathway inhibition. We investigated the role of swimming training on cardiac miRNA-126 expression related to angiogenesis. Methods: Female Wistar rats were assigned to three groups: sedentary (S), training 1 (T1, moderate volume), and training 2 (T2, high volume). T1 consisted of 60 min.d(-1) of swimming, five times per week for 10 wk with 5% body overload. T2 consisted of the same protocol of T1 until the eighth week; in the ninth week, rats trained for two times a day, and in the 10th week, rats trained for three times a day. MiRNA and PI3KR2 gene expression analysis was performed by real-time polymerase chain reaction in heart muscle. We assessed markers of training, the cardiac capillary-fiber ratio, cardiac protein expression of VEGF, Spred-1, Raf-1/ERK 1/2, and PI3K/Akt/eNOS. Results: The cardiac capillary-fiber ratio increased in T1 (58%) and T2 (101%) compared with S. VEGF protein expression was increased 42% in T1 and 108% in T2. Cardiac miRNA-126 expression increased 26% (T1) and 42% (T2) compared with S, correlated with angiogenesis. The miRNA-126 target Spred-1 protein level decreased 41% (T1) and 39% (T2), which consequently favored an increase in angiogenic signaling pathway Raf-1/ERK 1/2. On the other hand, the gene expression of PI3KR2, the other miRNA-126 target, was reduced 39% (T1) and 78% (T2), and there was an increase in protein expression of components of the PI3K/Akt/eNOS signaling pathway in the trained groups. Conclusions: This study showed that aerobic training promotes an increase in the expression of miRNA-126 and that this may be related to exercise-induced cardiac angiogenesis, by indirect regulation of the VEGF pathway and direct regulation of its targets that converged in an increase in angiogenic pathways, such as MAPK and PI3K/Akt/eNOS.