Amino acids change liver growth factors gene expression in malnourished rats

Background: Glutamine and proline are metabolized in the liver and may collaborate on its regeneration. Parenteral nutrition (PN) containing either glutamine or proline was given to partially hepatectomized rats. The total RNA content and growth factor gene expression in hepatic remnants was measured, to determine the effects of these amino acid supplementation on the expression of growth factors during liver regeneration. Methods: Wistar rats nourished (HN) and malnourished (HM) were hepatectomized and divided in two groups: 20 receiving PN enriched with Alanyl-Glutamine (HN-Gln and HM-Gln) and 20 PN enriched with proline+alanine (HN-Pro and HM-Pro). The control groups comprised 7 nourished (CN) and 7 malnourished (CM) rats that didn`t undergo surgery. Growth factor and thymidine kinase mRNA levels were measured by RT-PCR. Results: In nourished rats, total hepatic RNA levels were lower in the HN-Gln and HN-Pro groups (0.75 and 0.63 mu g/mg tissue, respectively) than in control group (1.67 mu g/mg tissue) (P<0.05). In malnourished rats, total hepatic RNA content was higher in the HM-Pro group than FIN-Pro, HM-Gln, and CM (3.18 vs. 0.63, 0.93 and 1.10 mu g/mg, respectively; P<0.05). Hepatocyte growth factor mRNA was more abundant in the HM-Gln group when compared to CM (031 vs. 0.23 arbitrary units) and also in HM-Pro in relation to HM-Gln, HN-Pro, and CM (0.46 vs. 033 and 0.23, respectively, P<0.05). Conclusions: Proline or glutamine supplementation in malnourished rats improves total RNA content in the remnant hepatic tissue. Amino acids administration increased HGF gene expression after partial hepatectomy in malnourished rats, with a greater effect of proline than glutamine.

A reliable measure of similarity based on dependency for short time series: an application to gene expression networks

Background: Microarray techniques have become an important tool to the investigation of genetic relationships and the assignment of different phenotypes. Since microarrays are still very expensive, most of the experiments are performed with small samples. This paper introduces a method to quantify dependency between data series composed of few sample points. The method is used to construct gene co-expression subnetworks of highly significant edges. Results: The results shown here are for an adapted subset of a Saccharomyces cerevisiae gene expression data set with low temporal resolution and poor statistics. The method reveals common transcription factors with a high confidence level and allows the construction of subnetworks with high biological relevance that reveals characteristic features of the processes driving the organism adaptations to specific environmental conditions. Conclusion: Our method allows a reliable and sophisticated analysis of microarray data even under severe constraints. The utilization of systems biology improves the biologists ability to elucidate the mechanisms underlying celular processes and to formulate new hypotheses.

A score system for quality evaluation of RNA sequence tags: an improvement for gene expression profiling

Background: High-throughput molecular approaches for gene expression profiling, such as Serial Analysis of Gene Expression (SAGE), Massively Parallel Signature Sequencing (MPSS) or Sequencing-by-Synthesis (SBS) represent powerful techniques that provide global transcription profiles of different cell types through sequencing of short fragments of transcripts, denominated sequence tags. These techniques have improved our understanding about the relationships between these expression profiles and cellular phenotypes. Despite this, more reliable datasets are still necessary. In this work, we present a web-based tool named S3T: Score System for Sequence Tags, to index sequenced tags in accordance with their reliability. This is made through a series of evaluations based on a defined rule set. S3T allows the identification/selection of tags, considered more reliable for further gene expression analysis. Results: This methodology was applied to a public SAGE dataset. In order to compare data before and after filtering, a hierarchical clustering analysis was performed in samples from the same type of tissue, in distinct biological conditions, using these two datasets. Our results provide evidences suggesting that it is possible to find more congruous clusters after using S3T scoring system. Conclusion: These results substantiate the proposed application to generate more reliable data. This is a significant contribution for determination of global gene expression profiles. The library analysis with S3T is freely available at http://gdm.fmrp.usp.br/s3t/.S3T source code and datasets can also be downloaded from the aforementioned website.

Use of the real time RT-PCR for immune related gene expression quantitation in experimentally infected Neospora caninum bovine calves

Neospora caninum is one of the main causes of abortion and natimortality in cattle. Host immune defense is capable to inhibit tachyzoite activity during acute infection, but there is no action against bradyzoites in tissue cysts. Activation and modulation of this response is controlled by cell mediators. The real-time RT-PCR technique was employed to detect some of those mediators during N. caninum infection. Holstein and Nelore calves intramuscularly infected with tachyzoites and uninfected controls were slaughtered at the sixth day post-infection and popliteal lymph node, liver and brain cortex samples were analyzed. Real-time RT-PCR detected gene expression in all tissues. No significant variation of GAPDH gene expression was detected among groups, its amplification efficiency was similar to the other genes tested and it was used as the endogenous control for the analysis. Comparisons between infected and uninfected groups allowed the relative gene expression quantification. IFN-gamma and TNF-alpha genes showed increased expression in some samples. iNOS and TGF-beta 1 genes had some non-significant variations and IL-4 and IL-10 stayed pratically inaltered.

INSULIN REGULATES CYTOKINES AND INTERCELLULAR ADHESION MOLECULE-1 GENE EXPRESSION THROUGH NUCLEAR FACTOR-kappa B ACTIVATION IN LPS-INDUCED ACUTE LUNG INJURY IN RATS

Diabetic patients have increased susceptibility to infection, which may be related to impaired inflammatory response observed in experimental models of diabetes, and restored by insulin treatment. The goal of this study was to investigate whether insulin regulates transcription of cytokines and intercellular adhesion molecule 1 (ICAM-1) via nuclear factor-kappa B (NF-kappa B) signaling pathway in Escherichia coli LIPS-induced lung inflammation. Diabetic male Wistar rats (alloxan, 42 mg/kg, iv., 10 days) and controls were instilled intratracheally with saline containing LPS (750 mu g/0.4 mL) or saline only. Some diabetic rats were given neutral protamine Hagedorn insulin (4 IU, s.c.) 2 h before LIPS. Analyses performed 6 h after LPS included: (a) lung and mesenteric lymph node IL-1 beta, TNF-alpha, IL-10, and ICAM-1 messenger RNA (mRNA) were quantified by real-time reverse transcriptase-polymerase chain reaction; (b) number of neutrophils in the bronchoalveolar lavage (BAL) fluid, and concentrations of IL-1 beta, TNF-alpha, and IL-10 in the BAL were determined by the enzyme-linked immunosorbent assay; and (c) activation of NF-kappa B p65 subunit and phosphorylation of I-kappa B alpha were quantified by Western blot analysis. Relative to controls, diabetic rats exhibited a reduction in lung and mesenteric lymph node IL-1 beta (40%), TNF-alpha (similar to 30%), and IL-10 (similar to 40%) mRNA levels and reduced concentrations of IL-1 beta (52%), TNF-alpha (62%), IL-10 (43%), and neutrophil counts (72%) in the BAL. Activation of NF-kappa B p65 subunit and phosphorylation of I-kappa B alpha were almost suppressed in diabetic rats. Treatment of diabetic rats with insulin completely restored mRNA and protein levels of these cytokines and potentiated lung ICAM-1 mRNA levels (30%) and number of neutrophils (72%) in the BAL. Activation of NF-kappa B p65 subunit and phosphorylation of I-kappa B alpha were partially restored by insulin treatment. In conclusion, data presented suggest that insulin regulates transcription of proinflammatory (IL-1 beta, TNF-alpha) and anti-inflammatory (IL-10) cytokines, and expression of ICAM-1 via the NF-kappa B signaling pathway.

Hypothyroidism decreases proinsulin gene expression and the attachment of its mRNA and eEF1A protein to the actin cytoskeleton of INS-1E cells

The actions of thyroid hormone (TH) on pancreatic beta cells have not been thoroughly explored, with current knowledge being limited to the modulation of insulin secretion in response to glucose, and beta cell viability by regulation of pro-mitotic and pro-apoptotic factors. Therefore, the effects of TH on proinsulin gene expression are not known. This led us to measure: a) proinsulin mRNA expression, b) proinsulin transcripts and eEF1A protein binding to the actin cytoskeleton, c) actin cytoskeleton arrangement, and d) proinsulin mRNA poly(A) tail length modulation in INS-1E cells cultured in different media containing: i) normal fetal bovine serum - FBS (control); ii) normal FBS plus 1 µM or 10 nM T3, for 12 h, and iii) FBS depleted of TH for 24 h (Tx). A decrease in proinsulin mRNA content and attachment to the cytoskeleton were observed in hypothyroid (Tx) beta cells. The amount of eEF1A protein anchored to the cytoskeleton was also reduced in hypothyroidism, and it is worth mentioning that eEF1A is essential to attach transcripts to the cytoskeleton, which might modulate their stability and rate of translation. Proinsulin poly(A) tail length and cytoskeleton arrangement remained unchanged in hypothyroidism. T3 treatment of control cells for 12 h did not induce any changes in the parameters studied. The data indicate that TH is important for proinsulin mRNA expression and translation, since its total amount and attachment to the cytoskeleton are decreased in hypothyroid beta cells, providing evidence that effects of TH on carbohydrate metabolism also include the control of proinsulin gene expression.

Pre-processing for noise detection in gene expression classification data

Due to the imprecise nature of biological experiments, biological data is often characterized by the presence of redundant and noisy data. This may be due to errors that occurred during data collection, such as contaminations in laboratorial samples. It is the case of gene expression data, where the equipments and tools currently used frequently produce noisy biological data. Machine Learning algorithms have been successfully used in gene expression data analysis. Although many Machine Learning algorithms can deal with noise, detecting and removing noisy instances from the training data set can help the induction of the target hypothesis. This paper evaluates the use of distance-based pre-processing techniques for noise detection in gene expression data classification problems. This evaluation analyzes the effectiveness of the techniques investigated in removing noisy data, measured by the accuracy obtained by different Machine Learning classifiers over the pre-processed data.

Xylella fastidiosa gene expression analysis by DNA microarrays

Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcription reactions and which were obtained from bacteria grown under two different conditions (liquid XDM2 and liquid BCYE). All data were statistically analyzed to verify which genes were differentially expressed. In addition to exploring conditions for X. fastidiosa genome-wide transcriptome analysis, the present work observed the differential expression of several classes of genes (energy, protein, amino acid and nucleotide metabolism, transport, degradation of substances, toxins and hypothetical proteins, among others). The understanding of expressed genes in these two different media will be useful in comprehending the metabolic characteristics of X. fastidiosa, and in evaluating how important certain genes are for the functioning and survival of these bacteria in plants.

Yerba Maté (Ilex paraguariensis) aqueous extract decreases intestinal SGLT1 gene expression but does not affect other biochemical parameters in alloxan-diabetic wistar rats

Yerba mate´ (Ilex paraguariensis) is rich in polyphenols, especially chlorogenic acids. Evidence suggests that dietary polyphenols could play a role in glucose absorption and metabolism. The aim of this study was to evaluate the antidiabetic properties of yerba mate´ extract in alloxan-induced diabetic Wistar rats. Animals (n ) 41) were divided in four groups: nondiabetic control (NDC, n=11), and diabetic yerba maté (DY, n = 10). The intervention consisted in the administration of yerba mate´ extract in a 1 g extract/ kg body weight dose for 28 days; controls received saline solution only. There were no significant differences in serum glucose, insulin, and hepatic glucose-6-phosphatase activity between the groups that ingested yerba maté extract (NDY and DY) and the controls (NDC and DC). However, the intestinal SGLT1 gene expression was significantly lower in animals that received yerba maté both in upper (p = 0.007) and middle (p < 0.001) small intestine. These results indicate that bioactive compounds present in yerba maté might be capable of interfering in glucose absorption, by decreasing SGLT1 expression

The full Bayesian significance test for mixture models: results in gene expression clustering

Gene clustering is a useful exploratory technique to group together genes with similar expression levels under distinct cell cycle phases or distinct conditions. It helps the biologist to identify potentially meaningful relationships between genes. In this study, we propose a clustering method based on multivariate normal mixture models, where the number of clusters is predicted via sequential hypothesis tests: at each step, the method considers a mixture model of m components (m = 2 in the first step) and tests if in fact it should be m - 1. If the hypothesis is rejected, m is increased and a new test is carried out. The method continues (increasing m) until the hypothesis is accepted. The theoretical core of the method is the full Bayesian significance test, an intuitive Bayesian approach, which needs no model complexity penalization nor positive probabilities for sharp hypotheses. Numerical experiments were based on a cDNA microarray dataset consisting of expression levels of 205 genes belonging to four functional categories, for 10 distinct strains of Saccharomyces cerevisiae. To analyze the method's sensitivity to data dimension, we performed principal components analysis on the original dataset and predicted the number of classes using 2 to 10 principal components. Compared to Mclust (model-based clustering), our method shows more consistent results.

Gene expression profile of the plant pathogen Fusarium graminearum under the antagonistic effect of Pantoea agglomerans

The pathogenic fungus Fusarium graminearum is an ongoing threat to agriculture, causing losses in grain yield and quality in diverse crops. Substantial progress has been made in the identification of genes involved in the suppression of phytopathogens by antagonistic microorganisms; however, limited information regarding responses of plant pathogens to these biocontrol agents is available. Gene expression analysis was used to identify differentially expressed transcripts of the fungal plant pathogen F. graminearum under antagonistic effect of the bacterium Pantoea agglomerans. A macroarray was constructed, using 1014 transcripts from an F. graminearum cDNA library. Probes consisted of the cDNA of F. graminearum grown in the presence and in the absence of P. agglomerans. Twenty-nine genes were either up (19) or down (10) regulated during interaction with the antagonist bacterium. Genes encoding proteins associated with fungal defense and/or virulence or with nutritional and oxidative stress responses were induced. The repressed genes coded for a zinc finger protein associated with cell division, proteins containing cellular signaling domains, respiratory chain proteins, and chaperone-type proteins. These data give molecular and biochemical evidence of response of F. graminearum to an antagonist and could help develop effective biocontrol procedures for pathogenic plant fungi.

Effects of trans-10, cis-12 conjugated linoleic acid on gene expression and lipid metabolism of adipose tissue of growing pigs

The objective of the present study was to determine the effects of trans-10, cis-12 conjugated linoleic acid (CLA) in adipose tissue explant cultures of growing pigs on the following responses: lipogenesis (measured as rate of C-14-labeled glucose incorporation over a subsequent 2-h incubation in the presence or absence of insulin), lipolysis (release of non-esterified fatty acid over a 2-h incubation in the presence or absence of isoproterenol), activities of lipogenic enzymes, and mRNA abundance of fatty acid synthase (FAS). Adipose tissue explants from nine growing pigs (78 +/- 3 kg) were cultured in 199 medium with insulin, dexamethasone and antibiotics for 4, 12, 24, and 48 h. The treatments were 1) control: 100 mu M polyvinyl alcohol (PVA); 2) pGH: 100 ng/mL porcine growth hormone (pGH) plus 100 mu M PVA; 3) CLA200: 200 mu M trans-10, cis-12 CLA; 4) CLA50: 50 mu M trans-10, cis-12 CLA, and 5) LA: 200 mu M linoleic acid. Fatty acids were added along with PVA (2: 1), respectively, for 24 h. Explants were collected after each culture period and assayed for lipogenesis. Transcripts of FAS mRNA were quantified by real-time RT-PCR after 24 and 48 h. Lipolysis and activities of FAS, glucose 6-phosphate dehydrogenase, 6-phosphogluconate dehydrogenase, and NADP-malate dehydrogenase were determined after 48 h. As expected, glucose incorporation was decreased (P < 0.05) in response to pGH treatment (positive control). LA had no effect on any parameter evaluated. Treatment with trans-10, cis-12 CLA decreased FAS activity (P < 0.05), but NADPH-generating enzymes were unaffected by treatments. Consistent with reduction in FAS activity, both lipid synthesis and FAS mRNA abundance were reduced with chronic CLA treatment, pGH increased baseline and stimulated lipolysis (P < 0.05) after 48 h of culture, while CLA treatment had no effect on non-esterified fatty acid release. Results of this study showed that trans-10, cis-12 CLA alters lipogenesis but has no effect on lipolysis in cultures of pig adipose tissue.

Sub-telomere directed gene expression during initiation of invasive aspergillosis

Aspergillus fumigatus is a common mould whose spores are a component of the normal airborne flora. Immune dysfunction permits developmental growth of inhaled spores in the human lung causing aspergillosis, a significant threat to human health in the form of allergic, and life-threatening invasive infections. The success of A. fumigatus as a pathogen is unique among close phylogenetic relatives and is poorly characterised at the molecular level. Recent genome sequencing of several Aspergillus species provides an exceptional opportunity to analyse fungal virulence attributes within a genomic and evolutionary context. To identify genes preferentially expressed during adaptation to the mammalian host niche, we generated multiple gene expression profiles from minute samplings of A. fumigatus germlings during initiation of murine infection. They reveal a highly co-ordinated A. fumigatus gene expression programme, governing metabolic and physiological adaptation, which allows the organism to prosper within the mammalian niche. As functions of phylogenetic conservation and genetic locus, 28% and 30%, respectively, of the A. fumigatus subtelomeric and lineage-specific gene repertoires are induced relative to laboratory culture, and physically clustered genes including loci directing pseurotin, gliotoxin and siderophore biosyntheses are a prominent feature. Locationally biased A. fumigatus gene expression is not prompted by in vitro iron limitation, acid, alkaline, anaerobic or oxidative stress. However, subtelomeric gene expression is favoured following ex vivo neutrophil exposure and in comparative analyses of richly and poorly nourished laboratory cultured germlings. We found remarkable concordance between the A. fumigatus host-adaptation transcriptome and those resulting from in vitro iron depletion, alkaline shift, nitrogen starvation and loss of the methyltransferase LaeA. This first transcriptional snapshot of a fungal genome during initiation of mammalian infection provides the global perspective required to direct much-needed diagnostic and therapeutic strategies and reveals genome organisation and subtelomeric diversity as potential driving forces in the evolution of pathogenicity in the genus Aspergillus.

Validation of reference genes for gene expression studies in the honey bee, Apis mellifera, by quantitative real-time RT-PCR

For obtaining accurate and reliable gene expression results it is essential that quantitative real-time RT-PCR (qRT-PCR) data are normalized with appropriate reference genes. The current exponential increase in postgenomic studies on the honey bee, Apis mellifera, makes the standardization of qRT-PCR results an important task for ongoing community efforts. For this aim we selected four candidate reference genes (actin, ribosomal protein 49, elongation factor 1-alpha, tbp-association factor) and used three software-based approaches (geNorm, BestKeeper and NormFinder) to evaluate the suitability of these genes as endogenous controls. Their expression was examined during honey bee development, in different tissues, and after juvenile hormone exposure. Furthermore, the importance of choosing an appropriate reference gene was investigated for two developmentally regulated target genes. The results led us to consider all four candidate genes as suitable genes for normalization in A. mellifera. However, each condition evaluated in this study revealed a specific set of genes as the most appropriated ones.

Lineage relationship of prostate cancer cell types based on gene expression

Background: Prostate tumor heterogeneity is a major factor in disease management. Heterogeneity could be due to multiple cancer cell types with distinct gene expression. Of clinical importance is the so-called cancer stem cell type. Cell type-specific transcriptomes are used to examine lineage relationship among cancer cell types and their expression similarity to normal cell types including stem/progenitor cells. Methods: Transcriptomes were determined by Affymetrix DNA array analysis for the following cell types. Putative prostate progenitor cell populations were characterized and isolated by expression of the membrane transporter ABCG2. Stem cells were represented by embryonic stem and embryonal carcinoma cells. The cancer cell types were Gleason pattern 3 (glandular histomorphology) and pattern 4 (aglandular) sorted from primary tumors, cultured prostate cancer cell lines originally established from metastatic lesions, xenografts LuCaP 35 (adenocarcinoma phenotype) and LuCaP 49 (neuroendocrine/small cell carcinoma) grown in mice. No detectable gene expression differences were detected among serial passages of the LuCaP xenografts. Results: Based on transcriptomes, the different cancer cell types could be clustered into a luminal-like grouping and a non-luminal-like (also not basal-like) grouping. The non-luminal-like types showed expression more similar to that of stem/progenitor cells than the luminal-like types. However, none showed expression of stem cell genes known to maintain stemness. Conclusions: Non-luminal-like types are all representatives of aggressive disease, and this could be attributed to the similarity in overall gene expression to stem and progenitor cell types.