BayGO: Bayesian analysis of ontology term enrichment in microarray data

Abstract Background The search for enriched (aka over-represented or enhanced) ontology terms in a list of genes obtained from microarray experiments is becoming a standard procedure for a system-level analysis. This procedure tries to summarize the information focussing on classification designs such as Gene Ontology, KEGG pathways, and so on, instead of focussing on individual genes. Although it is well known in statistics that association and significance are distinct concepts, only the former approach has been used to deal with the ontology term enrichment problem. Results BayGO implements a Bayesian approach to search for enriched terms from microarray data. The R source-code is freely available at http://blasto.iq.usp.br/~tkoide/BayGO in three versions: Linux, which can be easily incorporated into pre-existent pipelines; Windows, to be controlled interactively; and as a web-tool. The software was validated using a bacterial heat shock response dataset, since this stress triggers known system-level responses. Conclusion The Bayesian model accounts for the fact that, eventually, not all the genes from a given category are observable in microarray data due to low intensity signal, quality filters, genes that were not spotted and so on. Moreover, BayGO allows one to measure the statistical association between generic ontology terms and differential expression, instead of working only with the common significance analysis.

Extracytoplasmic function (ECF) sigma factor sigma(F) is involved in Caulobacter crescentus response to heavy metal stress

Background: The alpha-proteobacterium Caulobacter crescentus inhabits low-nutrient environments and can tolerate certain levels of heavy metals in these sites. It has been reported that C. crescentus responds to exposure to various heavy metals by altering the expression of a large number of genes. Results: In this work, we show that the ECF sigma factor sigma(F) is one of the regulatory proteins involved in the control of the transcriptional response to chromium and cadmium. Microarray experiments indicate that sigma(F) controls eight genes during chromium stress, most of which were previously described as induced by heavy metals. Surprisingly, sigma(F) itself is not strongly auto-regulated under metal stress conditions. Interestingly, sigma(F)-dependent genes are not induced in the presence of agents that generate reactive oxygen species. Promoter analyses revealed that a conserved sigma(F)-dependent sequence is located upstream of all genes of the sigma(F) regulon. In addition, we show that the second gene in the sigF operon acts as a negative regulator of sigma(F) function, and the encoded protein has been named NrsF (Negative regulator of sigma F). Substitution of two conserved cysteine residues (C131 and C181) in NrsF affects its ability to maintain the expression of sigma(F)-dependent genes at basal levels. Furthermore, we show that sigma(F) is released into the cytoplasm during chromium stress and in cells carrying point mutations in both conserved cysteines of the protein NrsF. Conclusion: A possible mechanism for induction of the sigma(F)-dependent genes by chromium and cadmium is the inactivation of the putative anti-sigma factor NrsF, leading to the release of sigma(F) to bind RNA polymerase core and drive transcription of its regulon.

Signal transduction-related responses to phytohormones and environmental challenges in sugarcane

Abstract Background Sugarcane is an increasingly economically and environmentally important C4 grass, used for the production of sugar and bioethanol, a low-carbon emission fuel. Sugarcane originated from crosses of Saccharum species and is noted for its unique capacity to accumulate high amounts of sucrose in its stems. Environmental stresses limit enormously sugarcane productivity worldwide. To investigate transcriptome changes in response to environmental inputs that alter yield we used cDNA microarrays to profile expression of 1,545 genes in plants submitted to drought, phosphate starvation, herbivory and N2-fixing endophytic bacteria. We also investigated the response to phytohormones (abscisic acid and methyl jasmonate). The arrayed elements correspond mostly to genes involved in signal transduction, hormone biosynthesis, transcription factors, novel genes and genes corresponding to unknown proteins. Results Adopting an outliers searching method 179 genes with strikingly different expression levels were identified as differentially expressed in at least one of the treatments analysed. Self Organizing Maps were used to cluster the expression profiles of 695 genes that showed a highly correlated expression pattern among replicates. The expression data for 22 genes was evaluated for 36 experimental data points by quantitative RT-PCR indicating a validation rate of 80.5% using three biological experimental replicates. The SUCAST Database was created that provides public access to the data described in this work, linked to tissue expression profiling and the SUCAST gene category and sequence analysis. The SUCAST database also includes a categorization of the sugarcane kinome based on a phylogenetic grouping that included 182 undefined kinases. Conclusion An extensive study on the sugarcane transcriptome was performed. Sugarcane genes responsive to phytohormones and to challenges sugarcane commonly deals with in the field were identified. Additionally, the protein kinases were annotated based on a phylogenetic approach. The experimental design and statistical analysis applied proved robust to unravel genes associated with a diverse array of conditions attributing novel functions to previously unknown or undefined genes. The data consolidated in the SUCAST database resource can guide further studies and be useful for the development of improved sugarcane varieties.

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.

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.

Extracytoplasmic function (ECF) sigma factor σF is involved in Caulobacter crescentus response to heavy metal stress

Background The α-proteobacterium Caulobacter crescentus inhabits low-nutrient environments and can tolerate certain levels of heavy metals in these sites. It has been reported that C. crescentus responds to exposure to various heavy metals by altering the expression of a large number of genes. Results In this work, we show that the ECF sigma factor σF is one of the regulatory proteins involved in the control of the transcriptional response to chromium and cadmium. Microarray experiments indicate that σF controls eight genes during chromium stress, most of which were previously described as induced by heavy metals. Surprisingly, σF itself is not strongly auto-regulated under metal stress conditions. Interestingly, σF-dependent genes are not induced in the presence of agents that generate reactive oxygen species. Promoter analyses revealed that a conserved σF-dependent sequence is located upstream of all genes of the σF regulon. In addition, we show that the second gene in the sigF operon acts as a negative regulator of σF function, and the encoded protein has been named NrsF (Negative regulator of sigma F). Substitution of two conserved cysteine residues (C131 and C181) in NrsF affects its ability to maintain the expression of σF-dependent genes at basal levels. Furthermore, we show that σF is released into the cytoplasm during chromium stress and in cells carrying point mutations in both conserved cysteines of the protein NrsF. Conclusion A possible mechanism for induction of the σF-dependent genes by chromium and cadmium is the inactivation of the putative anti-sigma factor NrsF, leading to the release of σF to bind RNA polymerase core and drive transcription of its regulon.

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.

Eutrophication and macroalgal blooms in temperate and tropical coastal waters: nutrient enrichment experiments with Ulva spp.

Receiving coastal waters and estuaries are among the most nutrient-enriched environments on earth, and one of the symptoms of the resulting eutrophication is the proliferation of opportunistic, fast-growing marine seaweeds. Here, we used a widespread macroalga often involved in blooms, Ulva spp., to investigate how supply of nitrogen (N) and phosphorus (P), the two main potential growth-limiting nutrients, influence macroalgal growth in temperate and tropical coastal waters ranging from low- to high-nutrient supplies. We carried out N and P enrichment field experiments on Ulva spp. in seven coastal systems, with one of these systems represented by three different subestuaries, for a total of nine sites. We showed that rate of growth of Ulva spp. was directly correlated to annual dissolved inorganic nitrogen (DIN) concentrations, where growth increased with increasing DIN concentration. Internal N pools of macroalgal fronds were also linked to increased DIN supply, and algal growth rates were tightly coupled to these internal N pools. The increases in DIN appeared to be related to greater inputs of wastewater to these coastal waters as indicated by high delta 15N signatures of the algae as DIN increased. N and P enrichment experiments showed that rate of macroalgal growth was controlled by supply of DIN where ambient DIN concentrations were low, and by P where DIN concentrations were higher, regardless of latitude or geographic setting. These results suggest that understanding the basis for macroalgal blooms, and management of these harmful phenomena, will require information as to nutrient sources, and actions to reduce supply of N and P in coastal waters concerned.

Bearded capuchin monkeys` and a human`s efficiency at cracking palm nuts with stone tools: field experiments

Wild bearded capuchins, Cebus libidinosus, in Fazenda Boa Vista, Brazil crack tough palm nuts using hammer stones. We analysed the contribution of intrinsic factors (body weight, behaviour), size of the nuts and the anvil surface (flat or pit) to the efficiency of cracking. We provided capuchins with local palm nuts and a single hammer stone at an anvil. From video we scored the capuchins` position and actions with the nut prior to each strike, and outcomes of each strike. The most efficient capuchin opened 15 nuts per 100 strikes (6.6 strikes per nut). The least efficient capuchin that succeeded in opening a nut opened 1.32 nuts per 100 strikes (more than 75 strikes per nut). Body weight and diameter of the nut best predicted whether a capuchin would crack a nut on a given strike. All the capuchins consistently placed nuts into pits. To provide an independent analysis of the effect of placing the nut into a pit, we filmed an adult human cracking nuts on the same anvil using the same stone. The human displaced the nut on proportionally fewer strikes when he placed it into a pit rather than on a flat surface. Thus the capuchins placed the nut in a more effective location on the anvil to crack it. Nut cracking as practised by bearded capuchins is a striking example of a plastic behaviour where costs and benefits vary enormously across individuals, and where efficiency requires years to attain. (C) 2009 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

EMERGENT CONDITIONAL RELATIONS IN A GO/NO-GO PROCEDURE: FIGURE-GROUND AND STIMULUS-POSITION COMPOUND RELATIONS

Past research has demonstrated emergent conditional relations using a go/no-go procedure with pairs of figures displayed side-by-side on a computer screen. The present Study sought to extend applications Of this procedure. In Experiment, 1, we evaluated whether emergent conditional relations Could be demonstrated when two-component stimuli were displayed in figure-ground relationships-abstract figures displayed on backgrounds of different colors. Five normal)), capable adults participated. During training, each two-component stimulus Was presented successively. Responses emitted in the presence of some Stimulus pairs (A1B1, A2B2, A3B3, B1C1, B2C2 and B3C3) were reinforced, whereas responses emitted in the presence of other pairs (A1B2, A1B3, A2B1, A2B3, A3B1, A3B2, B1C2, B1C3, B2C1, B2C3, B3C1 and B3C2) were not. During tests, new configurations (AC and CA) were presented, thus emulating structurally the matching-to-sample tests employed in typical equivalence Studies. All participants showed emergent relations consistent with stimulus equivalence during testing. In Experiment 2, we systematically replicated the procedures with Stimulus compounds consisting Of four figures (A1, A2, C1 and C2) and two locations (left - B1 and right - 132). A,11 6 normally capable adults exhibited emergent stimulus-stimulus relations. Together, these experiments show that the go/no-go procedure is a potentially useful alternative for Studying emergent. conditional relations when matching-to-sample is procedurally cumbersome or impossible to use.

Tank experiments with borehole self-potential data

Despite their importance in the evaluation of petroleum and gas reservoirs, measurements of self-potential data under borehole conditions (well-logging) have found only minor applications in aquifer and waste-site characterization. This can be attributed to lower signals from the diffusion fronts in near-surface environments because measurements are made long after the drilling of the well, when concentration fronts are already disappearing. Proportionally higher signals arise from streaming potentials that prevent using simple interpretation models that assume signals from diffusion only. Our laboratory experiments found that dual-source self-potential signals can be described by a simple linear model, and that contributions (from diffusion and streaming potentials) can be isolated by slightly perturbing the borehole conditions. Perturbations are applied either by changing the concentration of the borehole-filling solution or its column height. Parameters useful for formation evaluation can be estimated from data measured during perturbations, namely, pore water resistivity, pressure drop across the borehole wall, and electrokinetic coupling parameter. These are important parameters to assess, respectively, water quality, aquifer lateral continuity, and interfacial properties of permeable formations.

Coupling Between GABA(A)-R Ligand-Binding Activity and Membrane Organization in beta-Cyclodextrin-Treated Synaptosomal Membranes from Bovine Brain Cortex: New Insights from EPR Experiments

Correlations between GABA(A) receptor (GABA(A)-R) activity and molecular organization of synaptosomal membranes (SM) were studied along the protocol for cholesterol (Cho) extraction with beta-cyclodextrin (beta-CD). The mere pre-incubation (PI) at 37A degrees C accompanying the beta-CD treatment was an underlying source of perturbations increasing [H-3]-FNZ maximal binding (70%) and K (d) (38%), plus a stiffening of SMs' hydrocarbon core region. The latter was inferred from an increased compressibility modulus (K) of SM-derived Langmuir films, a blue-shifted DPH fluorescence emission spectrum and the hysteresis in DPH fluorescence anisotropy (A (DPH)) in SMs submitted to a heating-cooling cycle (4-37-4A degrees C) with A (DPH,heating) < A (DPH,cooling). Compared with PI samples, the beta-CD treatment reduced B (max) by 5% which correlated with a 45%-decrement in the relative Cho content of SM, a decrease in K and in the order parameter in the EPR spectrum of a lipid spin probe labeled at C5 (5-SASL), and significantly increased A (TMA-DPH). PI, but not beta-CD treatment, could affect the binding affinity. EPR spectra of 5-SASL complexes with beta-CD-, SM-partitioned, and free in solution showed that, contrary to what is usually assumed, beta-CD is not completely eliminated from the system through centrifugation washings. It was concluded that beta-CD treatment involves effects of at least three different types of events affecting membrane organization: (a) effect of PI on membrane annealing, (b) effect of residual beta-CD on SM organization, and (c) Cho depletion. Consequently, molecular stiffness increases within the membrane core and decreases near the polar head groups, leading to a net increase in GABA(A)-R density, relative to untreated samples.

Long-distance correlations in TCABR biasing experiments

Long-distance correlations (LDCs) of plasma potential fluctuations in the plasma edge have been investigated in the TCABR tokamak in the regime of edge biasing H-mode using an array of multi-pin Langmuir probes. This activity was carried out as part of the scientific programme of the 4th IAEA Joint Experiment (2009). The experimental data confirm the effect of amplification of LDCs in potential fluctuations during biasing recently observed in stellarators and tokamaks. For long toroidal distances between probes, the cross-spectrum is concentrated at low frequencies f < 60 kHz with peaks at f < 5 kHz, f = 13-15 kHz and f similar to 40 kHz and low wave numbers with a maximum at k = 0. The effects of MHD activity on the LDCs in potential fluctuation are investigated.

Prediction of tolerance in children with IgE mediated cow's milk allergy by microarray profiling and chemometric approach

The sera of a retrospective cohort (n = 41) composed of children with well characterized cow's milk allergy collected from multiple visits were analyzed using a protein microarray system measuring four classes of immunoglobulins. The frequency of the visits, age and gender distribution reflected real situation faced by the clinicians at a pediatric reference center for food allergy in 530 Paulo, Brazil. The profiling array results have shown that total IgG and IgA share similar specificity whilst IgM and in particular IgE are distantly related. The correlation of specificity of IgE and IgA is variable amongst the patients and this relationship cannot be used to predict atopy or the onset of tolerance to milk. The array profiling technique has corroborated the clinical selection criteria for this cohort albeit it clearly suggested that 4 out of the 41 patients might have allergies other than milk origin. There was also a good correlation between the array data and ImmunoCAP results, casein in particular. By using qualitative and quantitative multivariate analysis routines it was possible to produce validated statistical models to predict with reasonable accuracy the onset of tolerance to milk proteins. If expanded to larger study groups, the array profiling in combination with the multivariate techniques show potential to improve the prognostic of milk allergic patients. (C) 2012 Elsevier B.V. All rights reserved.

Calcium nitrate addition to control the internal load of phosphorus from sediments of a tropical eutrophic reservoir: Microcosm experiments

The main objective of this study was to perform laboratory experiments on calcium nitrate addition to sediments of a tropical eutrophic urban reservoir (Ibirite reservoir, SE Brazil) to immobilize the reactive soluble phosphorus (RSP) and to evaluate possible geochemical changes and toxic effects caused by this treatment. Reductions of 75 and 89% in the concentration of RSP were observed in the water column and interstitial water, respectively, after 145 days of nitrate addition. The nitrate application increased the rate of autotrophic denitrification, causing a consumption of 98% of the added nitrate and oxidation of 99% of the acid volatile sulfide. As a consequence, there were increases in the sulfate and iron (II) concentrations in the sediment interstitial water and water column, as well as changes in the copper speciation in the sediments. Toxicity tests initially indicated that the high concentrations of nitrate and nitrite in the sediment interstitial water (up to 2300 mg L-1 and 260 mg L-1, respectively) were the major cause of mortality of Ceriodaphnia silvestrii and Chironomus xanthus. However, at the end of the experiment, the sediment toxicity was completely removed and a reduction in the 48 h-EC50 of the water was also observed. Based on these results we can say that calcium nitrate treatment proved to be a valuable tool in remediation of eutrophic aquatic ecosystems leading to conditions that can support a great diversity of organisms after a restoration period. (C) 2012 Elsevier Ltd. All rights reserved.