Amygdala gene expression of NMDA and GABAA receptors in patients with mesial temporal lobe epilepsy

Temporal lobe epilepsy (TLE) is the most common form of partial epilepsy and affects 40% of the patients. Seizures arising from the mesial temporal lobe structures (i.e., amygdala and hippocampus) are common, whereas neocortical seizures are rare. In recent years, many studies aimed to identify the pattern of gene expression of neurotransmitters involved in molecular mechanisms of epilepsy. We used real-time PCR to quantify the expression of GABAA (subunits a1, beta 1, beta 2) and NMDA (subunits NR1, NR2A, and NR2B) receptor genes in amygdalae of 27 patients with TLE and 14 amygdalae from autopsy controls. The NR1 subunit was increased in patients with epilepsy when compared with controls. No differences were found in expression of NMDA subunits NR2A and NR2B or in a1, beta 1, and beta 2 subunits of GABAA receptors. Our results suggest that the NR1 subunit of NMDA receptors is involved in the amygdala hyperexcitability in some of the patients with TLE. (C) 2010 Wiley Periodicals, Inc., Inc.

Potential costs of bacterial infection on storage protein gene expression and reproduction in queenless Apis mellifera worker bees on distinct dietary regimes

Insects are able to combat infection by initiating an efficient immune response that involves synthesizing antimicrobial peptides and a range of other defense molecules. These responses may be costly to the organism, resulting in it exploiting endogenous resources to maintain homeostasis or support defense to the detriment of other physiological needs. We used queenless worker bees on distinct dietary regimes that may alter hemolymph protein storage and ovary activation to investigate the physiological costs of infection with Serratia marcescens. The expression of the genes encoding the storage proteins vitellogenin and hexamerin 70a, the vitellogenin receptor, and vasa (which has a putative role in reproduction), was impaired in the infected bees. This impairment was mainly evident in the bees fed beebread, which caused significantly higher expression of these genes than did royal jelly or syrup, and this was confirmed at the vitellogenin and hexamerin 70a protein levels. Beebread was also the only diet that promoted ovary activation in the queenless bees, but this activation was significantly impaired by the infection. The expression of the genes encoding the storage proteins apolipophorins-I and -III and the lipophorin receptor was not altered by infection regardless the diet provided to the bees. Similarly, the storage of apolipophorin-I in the hemolymph was only slightly impaired by the infection, independently of the supplied diet. Taken together these results indicate that, infection demands a physiological cost from the transcription of specific protein storage-related genes and from the reproductive capacity. (C) 2012 Elsevier Ltd. All rights reserved.

Trypanosoma cruzi Gene Expression in Response to Gamma Radiation

Trypanosoma cruzi is an organism highly resistant to ionizing radiation. Following a dose of 500 Gy of gamma radiation, the fragmented genomic DNA is gradually reconstructed and the pattern of chromosomal bands is restored in less than 48 hours. Cell growth arrests after irradiation but, while DNA is completely fragmented, RNA maintains its integrity. In this work we compared the transcriptional profiles of irradiated and non-irradiated epimastigotes at different time points after irradiation using microarray. In total, 273 genes were differentially expressed; from these, 160 were up-regulated and 113 down-regulated. We found that genes with predicted functions are the most prevalent in the down-regulated gene category. Translation and protein metabolic processes, as well as generation of precursor of metabolites and energy pathways were affected. In contrast, the up-regulated category was mainly composed of obsolete sequences (which included some genes of the kinetoplast DNA), genes coding for hypothetical proteins, and Retrotransposon Hot Spot genes. Finally, the tyrosyl-DNA phosphodiesterase 1, a gene involved in double-strand DNA break repair process, was up-regulated. Our study demonstrated the peculiar response to ionizing radiation, raising questions about how this organism changes its gene expression to manage such a harmful stress.

Differential gene expression and developmental competence in in vitro produced bovine embryos

The embryonic developmental block occurs at the 8-cell stage in cattle and is characterized by a lengthening of the cell cycle and an increased number of embryos that stop development. The maternal-embryonic transition arises at the same stage resulting in the transcription of many genes. Gene expression studies during this stage may contribute to the understanding of the physiological mechanisms involved in the maternal-embryonic transition. Herein we identified genes differentially expressed between embryos with high or low developmental competence to reach the blastocyst stage using differential display PCR. Embryos were analysed according to developmental kinetics: fast cleavage embryos showing 8 cells at 48 h post insemination (hpi) with high potential of development (F8), and embryos with slow cleavage presenting 4 cells at 48 hpi (54) and 8 cells at 90 hpi (S8), both with reduced rates of development to blastocyst. The fluorescence DDPCR method was applied and allowed the recovery of 176 differentially expressed bands with similar proportion between high and low development potential groups (52% to F8 and 48% in S4 and S8 groups). A total of 27 isolated fragments were cloned and sequenced, confirming the expected primer sequences and allowing the identification of 27 gene transcripts. PI3KCA and ITM2B were chosen for relative quantification of mRNA using real-time PCR and showed a kinetic and a time-related pattern of expression respectively. The observed results suggest the existence of two different embryonic genome activation mechanisms: fast-developing embryos activate genes related to embryonic development, and slow-developing embryos activate genes related to cellular survival and/or death.

Changes in spatial and temporal gene expression during incompatible interaction between common bean and anthracnose pathogen

Common bean, one of the most important legumes for human consumption, may have drastic reduction in yield due to anthracnose, a disease caused by the fungus Colletotrichum lindemuthianum. Rapid induction of the plant defense mechanisms is essential to establish an incompatible interaction with this pathogenic fungus. In this study, we evaluated spatial (leaves, epicotyls and hypocotyls) and temporal (24, 48, 72 and 96 hours after inoculation [HAI]) relative expression (RE) of 12 defense-related transcripts selected from previously developed ESTs libraries, during incompatible interaction between the resistant common bean genotype SEL 1308 and the avirulent anthracnose pathogen race 73, using real time quantitative RT-PCR (RT-qPCR) analysis. All selected transcripts, including the ones coding for pathogenesis-related (PR) proteins (PR1a, PR1b, PR2, and PR16a and PR16b) were differentially regulated upon pathogen inoculation. The expression levels of these transcripts were dependent on the tissue and time post inoculation. This study contributes to a better understanding of the kinetics of induced defenses against a fungal pathogen of common bean and may be used as a base line to study defenses against a broad range of pathogens including bacteria as well as non-host resistance. (C) 2012 Elsevier GmbH. All rights reserved.

GATA3 and a dominant regulatory gene expression profile discriminate operational tolerance in human transplantation

Some organ-transplanted patients achieve a state of "operational tolerance" (01) in which graft function is maintained after the complete withdrawal of immunosuppressive drugs. We used a gene panel of regulatory/inflammatory molecules (FOXP3, GATA3, 100, TGFB1, TGFBR1/TBX21, TNF and IFNG) to investigate the gene expression profile in peripheral blood mononuclear cells of renal-transplanted individuals experiencing OT compared to transplanted individuals not displaying OT and healthy individuals (HI). OT subjects showed a predominant regulatory (REG) profile with higher gene expression of GATA3, FOXP3, TGFB1 and TGFB receptor 1 compared to the other groups. This predominant REG gene expression profile displayed stability over time. The significant GATA3 gene and protein expressions in OT individuals suggest that a Th2 deviation may be a relevant pathway to OT. Moreover, the capacity of the REG/INFLAMMA gene panel to discriminate OT by peripheral blood analysis indicates that this state has systemic repercussions. (C) 2011 Elsevier Inc. 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.

Simcluster: clustering enumeration gene expression data on the simplex space

Abstract Background Transcript enumeration methods such as SAGE, MPSS, and sequencing-by-synthesis EST "digital northern", are important high-throughput techniques for digital gene expression measurement. As other counting or voting processes, these measurements constitute compositional data exhibiting properties particular to the simplex space where the summation of the components is constrained. These properties are not present on regular Euclidean spaces, on which hybridization-based microarray data is often modeled. Therefore, pattern recognition methods commonly used for microarray data analysis may be non-informative for the data generated by transcript enumeration techniques since they ignore certain fundamental properties of this space. Results Here we present a software tool, Simcluster, designed to perform clustering analysis for data on the simplex space. We present Simcluster as a stand-alone command-line C package and as a user-friendly on-line tool. Both versions are available at: http://xerad.systemsbiology.net/simcluster. Conclusion Simcluster is designed in accordance with a well-established mathematical framework for compositional data analysis, which provides principled procedures for dealing with the simplex space, and is thus applicable in a number of contexts, including enumeration-based gene expression 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.

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.

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.