Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

INFERENCE FOR EIGENVALUES AND EIGENVECTORS OF GAUSSIAN SYMMETRIC MATRICES

This article presents maximum likelihood estimators (MLEs) and log-likelihood ratio (LLR) tests for the eigenvalues and eigenvectors of Gaussian random symmetric matrices of arbitrary dimension, where the observations are independent repeated samples from one or two populations. These inference problems are relevant in the analysis of diffusion tensor imaging data and polarized cosmic background radiation data, where the observations are, respectively, 3 x 3 and 2 x 2 symmetric positive definite matrices. The parameter sets involved in the inference problems for eigenvalues and eigenvectors are subsets of Euclidean space that are either affine subspaces, embedded submanifolds that are invariant under orthogonal transformations or polyhedral convex cones. We show that for a class of sets that includes the ones considered in this paper, the MLEs of the mean parameter do not depend on the covariance parameters if and only if the covariance structure is orthogonally invariant. Closed-form expressions for the MLEs and the associated LLRs are derived for this covariance structure.

Functional microarray analysis suggests repressed cell-cell signaling and cell survival-related modules inhibit progression of head and neck squamous cell carcinoma

Background: Cancer shows a great diversity in its clinical behavior which cannot be easily predicted using the currently available clinical or pathological markers. The identification of pathways associated with lymph node metastasis (N+) and recurrent head and neck squamous cell carcinoma (HNSCC) may increase our understanding of the complex biology of this disease. Methods: Tumor samples were obtained from untreated HNSCC patients undergoing surgery. Patients were classified according to pathologic lymph node status (positive or negative) or tumor recurrence (recurrent or non-recurrent tumor) after treatment (surgery with neck dissection followed by radiotherapy). Using microarray gene expression, we screened tumor samples according to modules comprised by genes in the same pathway or functional category. Results: The most frequent alterations were the repression of modules in negative lymph node (N0) and in non-recurrent tumors rather than induction of modules in N+ or in recurrent tumors. N0 tumors showed repression of modules that contain cell survival genes and in non-recurrent tumors cell-cell signaling and extracellular region modules were repressed. Conclusions: The repression of modules that contain cell survival genes in N0 tumors reinforces the important role that apoptosis plays in the regulation of metastasis. In addition, because tumor samples used here were not microdissected, tumor gene expression data are represented together with the stroma, which may reveal signaling between the microenvironment and tumor cells. For instance, in non-recurrent tumors, extracellular region module was repressed, indicating that the stroma and tumor cells may have fewer interactions, which disable metastasis development. Finally, the genes highlighted in our analysis can be implicated in more than one pathway or characteristic, suggesting that therapeutic approaches to prevent tumor progression should target more than one gene or pathway, specially apoptosis and interactions between tumor cells and the stroma.

A NEW PROOF OF OKAJI'S THEOREM FOR A CLASS OF SUM OF SQUARES OPERATORS

Let P be a linear partial differential operator with analytic coefficients. We assume that P is of the form ""sum of squares"", satisfying Hormander's bracket condition. Let q be a characteristic point; for P. We assume that q lies on a symplectic Poisson stratum of codimension two. General results of Okaji Show that P is analytic hypoelliptic at q. Hence Okaji has established the validity of Treves' conjecture in the codimension two case. Our goal here is to give a simple, self-contained proof of this fact.

Placebo Response of Non-Pharmacological and Pharmacological Trials in Major Depression: A Systematic Review and Meta-Analysis

Background: Although meta-analyses have shown that placebo responses are large in Major Depressive Disorder (MDD) trials; the placebo response of devices such as repetitive transcranial magnetic stimulation (rTMS) has not been systematically assessed. We proposed to assess placebo responses in two categories of MDD trials: pharmacological (antidepressant drugs) and non-pharmacological (device-rTMS) trials. Methodology/Principal Findings: We performed a systematic review and meta-analysis of the literature from April 2002 to April 2008, searching MEDLINE, Cochrane, Scielo and CRISP electronic databases and reference lists from retrieved studies and conference abstracts. We used the keywords placebo and depression and escitalopram for pharmacological studies; and transcranial magnetic stimulation and depression and sham for non-pharmacological studies. All randomized, double-blinded, placebo-controlled, parallel articles on major depressive disorder were included. Forty-one studies met our inclusion criteria-29 in the rTMS arm and 12 in the escitalopram arm. We extracted the mean and standard values of depression scores in the placebo group of each study. Then, we calculated the pooled effect size for escitalopram and rTMS arm separately, using Cohen's d as the measure of effect size. We found that placebo response are large for both escitalopram (Cohen's d-random-effects model-1.48; 95% C.I. 1.26 to 1.6) and rTMS studies (0.82; 95% C.I. 0.63 to 1). Exploratory analyses show that sham response is associated with refractoriness and with the use of rTMS as an add-on therapy, but not with age, gender and sham method utilized. Conclusions/Significance: We confirmed that placebo response in MDD is large regardless of the intervention and is associated with depression refractoriness and treatment combination (add-on rTMS studies). The magnitude of the placebo response seems to be related with study population and study design rather than the intervention itself.

Structure-Function Analysis of the HrpB2-HrcU Interaction in the Xanthomonas citri Type III Secretion System

Bacterial type III secretion systems deliver protein virulence factors to host cells. Here we characterize the interaction between HrpB2, a small protein secreted by the Xanthomonas citri subsp. citri type III secretion system, and the cytosolic domain of the inner membrane protein HrcU, a paralog of the flagellar protein FlhB. We show that a recombinant fragment corresponding to the C-terminal cytosolic domain of HrcU produced in E. coli suffers cleavage within a conserved Asn264-Pro265-Thr266-His267 (NPTH) sequence. A recombinant HrcU cytosolic domain with N264A, P265A, T266A mutations at the cleavage site (HrcU(AAAH)) was not cleaved and interacted with HrpB2. Furthermore, a polypeptide corresponding to the sequence following the NPTH cleavage site also interacted with HrpB2 indicating that the site for interaction is located after the NPTH site. Non-polar deletion mutants of the hrcU and hrpB2 genes resulted in a total loss of pathogenicity in susceptible citrus plants and disease symptoms could be recovered by expression of HrpB2 and HrcU from extrachromossomal plasmids. Complementation of the Delta hrcU mutant with HrcU(AAAH) produced canker lesions similar to those observed when complemented with wild-type HrcU. HrpB2 secretion however, was significantly reduced in the Delta hrcU mutant complemented with HrcU(AAAH), suggesting that an intact and cleavable NPTH site in HrcU is necessary for total functionally of T3SS in X. citri subsp. citri. Complementation of the Delta hrpB2 X. citri subsp. citri strain with a series of hrpB2 gene mutants revealed that the highly conserved HrpB2 C-terminus is essential for T3SS-dependent development of citrus canker symptoms in planta.

LATENT RANK CHANGE DETECTION FOR ANALYSIS OF SPLICE-JUNCTION MICROARRAYS WITH NONLINEAR EFFECTS

Alternative splicing of gene transcripts greatly expands the functional capacity of the genome, and certain splice isoforms may indicate specific disease states such as cancer. Splice junction microarrays interrogate thousands of splice junctions, but data analysis is difficult and error prone because of the increased complexity compared to differential gene expression analysis. We present Rank Change Detection (RCD) as a method to identify differential splicing events based upon a straightforward probabilistic model comparing the over-or underrepresentation of two or more competing isoforms. RCD has advantages over commonly used methods because it is robust to false positive errors due to nonlinear trends in microarray measurements. Further, RCD does not depend on prior knowledge of splice isoforms, yet it takes advantage of the inherent structure of mutually exclusive junctions, and it is conceptually generalizable to other types of splicing arrays or RNA-Seq. RCD specifically identifies the biologically important cases when a splice junction becomes more or less prevalent compared to other mutually exclusive junctions. The example data is from different cell lines of glioblastoma tumors assayed with Agilent microarrays.

Interaction between polymorphisms of the Human Leukocyte Antigen and HPV-16 Variants on the risk of invasive cervical cancer

Background: Persistent infection with oncogenic types of human papillomavirus (HPV) is the major risk factor for invasive cervical cancer (ICC), and non-European variants of HPV-16 are associated with an increased risk of persistence and ICC. HLA class II polymorphisms are also associated with genetic susceptibility to ICC. Our aim is to verify if these associations are influenced by HPV-16 variability. Methods: We characterized HPV-16 variants by PCR in 107 ICC cases, which were typed for HLA-DQA1, DRB1 and DQB1 genes and compared to 257 controls. We measured the magnitude of associations by logistic regression analysis. Results: European ( E), Asian-American ( AA) and African (Af) variants were identified. Here we show that inverse association between DQB1*05 ( adjusted odds ratio [ OR] = 0.66; 95% confidence interval [CI]: 0.39-1.12]) and HPV-16 positive ICC in our previous report was mostly attributable to AA variant carriers ( OR = 0.27; 95% CI: 0.10-0.75). We observed similar proportions of HLA DRB1*1302 carriers in E-P positive cases and controls, but interestingly, this allele was not found in AA cases ( p = 0.03, Fisher exact test). A positive association with DRB1*15 was observed in both groups of women harboring either E ( OR = 2.99; 95% CI: 1.13-7.86) or AA variants ( OR = 2.34; 95% CI: 1.00-5.46). There was an inverse association between DRB1*04 and ICC among women with HPV-16 carrying the 350T [83L] single nucleotide polymorphism in the E6 gene ( OR = 0.27; 95% CI: 0.08-0.96). An inverse association between DQB1*05 and cases carrying 350G (83V) variants was also found ( OR = 0.37; 95% CI: 0.15-0.89). Conclusion: Our results suggest that the association between HLA polymorphism and risk of ICC might be influenced by the distribution of HPV-16 variants.

GPIomics: global analysis of glycosylphosphatidylinositol-anchored molecules of Trypanosoma cruzi

Glycosylphosphatidylinositol (GPI) anchoring is a common, relevant posttranslational modification of eukaryotic surface proteins. Here, we developed a fast, simple, and highly sensitive (high attomole-low femtomole range) method that uses liquid chromatography-tandem mass spectrometry (LC-MS(n)) for the first large-scale analysis of GPI-anchored molecules (i.e., the GPIome) of a eukaryote, Trypanosoma cruzi, the etiologic agent of Chagas disease. Our genome-wise prediction analysis revealed that approximately 12% of T. cruzi genes possibly encode GPI-anchored proteins. By analyzing the GPIome of T. cruzi insect-dwelling epimastigote stage using LC-MS(n), we identified 90 GPI species, of which 79 were novel. Moreover, we determined that mucins coded by the T. cruzi small mucin-like gene (TcSMUG S) family are the major GPI-anchored proteins expressed on the epimastigote cell surface. TcSMUG S mucin mature sequences are short (56-85 amino acids) and highly O-glycosylated, and contain few proteolytic sites, therefore, less likely susceptible to proteases of the midgut of the insect vector. We propose that our approach could be used for the high throughput GPIomic analysis of other lower and higher eukaryotes. Molecular Systems Biology 7 April 2009; doi:10.1038/msb.2009.13

Flow injection analysis of paracetamol using a biomimetic sensor as a sensitive and selective amperometric detector

This work describes the coupling of a biomimetic sensor to a flow injection system for the sensitive determination of paracetamol. The sensor was prepared as previously described in the literature (M. D. P. T. Sotomayor, A. Sigoli, M. R. V. Lanza, A. A. Tanaka and L. T. Kubota, J. Braz. Chem. Soc., 2008, 19, 734) by modifying a glassy carbon electrode surface with a Nafion (R) membrane doped with iron tetrapyridinoporphyrazine (FeTPyPz), a biomimetic catalyst of the P450 enzyme. The performance of the sensor for paracetamol detection was investigated and optimized in a flow injection system (FIA) using a wall jet electrochemical cell. Under optimized conditions a wide linear response range (1.0 x 10(-5) to 5.0 x 10(-2) mol L(-1)) was obtained, with a sensitivity of 2579 (+/- 129) mu A L mu mol(-1). The detection and quantification limits of the sensor for paracetamol in the FIA system were 1.0 and 3.5 mu mol L(-1), respectively. The analytical frequency was 51 samples h(-1), and over a period of five days (320 determinations) the biosensor maintained practically the same response. The system was successfully applied to paracetamol quantification in seven pharmaceutical formulations and in water samples from six rivers in Sao Paulo State, Brazil.

Wavelet analysis of MODIS time series to detect expansion and intensification of row-crop agriculture in Brazil

Since 2000, the southwestern Brazilian Amazon has undergone a rapid transformation from natural vegetation and pastures to row-crop agricultural with the potential to affect regional biogeochemistry. The goals of this research are to assess wavelet algorithms applied to MODIS time series to determine expansion of row-crops and intensification of the number of crops grown. MODIS provides data from February 2000 to present, a period of agricultural expansion and intensification in the southwestern Brazilian Amazon. We have selected a study area near Comodoro, Mato Grosso because of the rapid growth of row-crop agriculture and availability of ground truth data of agricultural land-use history. We used a 90% power wavelet transform to create a wavelet-smoothed time series for five years of MODIS EVI data. From this wavelet-smoothed time series we determine characteristic phenology of single and double crops. We estimate that over 3200 km(2) were converted from native vegetation and pasture to row-crop agriculture from 2000 to 2005 in our study area encompassing 40,000 km(2). We observe an increase of 2000 km(2) of agricultural intensification, where areas of single crops were converted to double crops during the study period. (C) 2007 Elsevier Inc. All rights reserved.

Discharge-calcium concentration relationships in streams of the Amazon and Cerrado of Brazil: soil or land use controlled

Stream discharge-concentration relationships are indicators of terrestrial ecosystem function. Throughout the Amazon and Cerrado regions of Brazil rapid changes in land use and land cover may be altering these hydrochemical relationships. The current analysis focuses on factors controlling the discharge-calcium (Ca) concentration relationship since previous research in these regions has demonstrated both positive and negative slopes in linear log(10)discharge-log(10)Ca concentration regressions. The objective of the current study was to evaluate factors controlling stream discharge-Ca concentration relationships including year, season, stream order, vegetation cover, land use, and soil classification. It was hypothesized that land use and soil class are the most critical attributes controlling discharge-Ca concentration relationships. A multilevel, linear regression approach was utilized with data from 28 streams throughout Brazil. These streams come from three distinct regions and varied broadly in watershed size (< 1 to > 10(6) ha) and discharge (10(-5.7)-10(3.2) m(3) s(-1)). Linear regressions of log(10)Ca versus log(10)discharge in 13 streams have a preponderance of negative slopes with only two streams having significant positive slopes. An ANOVA decomposition suggests the effect of discharge on Ca concentration is large but variable. Vegetation cover, which incorporates aspects of land use, explains the largest proportion of the variance in the effect of discharge on Ca followed by season and year. In contrast, stream order, land use, and soil class explain most of the variation in stream Ca concentration. In the current data set, soil class, which is related to lithology, has an important effect on Ca concentration but land use, likely through its effect on runoff concentration and hydrology, has a greater effect on discharge-concentration relationships.

Determination of the geographical origin of Brazilian wines by isotope and mineral analysis

In the present research, we studied wines from three different south Brazilian winemaking regions with the purpose of differentiating them by geographical origin of the grapes. Brazil`s wide territory and climate diversity allow grape cultivation and winemaking in many regions of different and unique characteristics. The wine grape cultivation for winemaking concentrates in the South Region, mainly in the Serra GaA(0)cha, the mountain area of the state of Rio Grande do Sul, which is responsible for 90% of the domestic wine production. However, in recent years, two new production regions have developed: the Campanha, the plains to the south and the Serra do Sudeste, the hills to the southeast of the state. Analysis of isotopic ratios of (18)O/(16)O of wine water, (13)C/(12)C of ethanol, and of minerals were used to characterize wines from different regions. The isotope analysis of delta(18)O of wine water and minerals Mg and Rb were the most efficient to differentiate the regions. By using isotope and mineral analysis, and discrimination analysis, it was possible to classify the wines from south Brazil.

Evaluation of grinding methods for pellets preparation aiming at the analysis of plant materials by laser induced breakdown spectrometry

It has been demonstrated that laser induced breakdown spectrometry (LIBS) can be used as an alternative method for the determination of macro (P, K. Ca, Mg) and micronutrients (B, Fe, Cu, Mn, Zn) in pellets of plant materials. However, information is required regarding the sample preparation for plant analysis by LIBS. In this work, methods involving cryogenic grinding and planetary ball milling were evaluated for leaves comminution before pellets preparation. The particle sizes were associated to chemical sample properties such as fiber and cellulose contents, as well as to pellets porosity and density. The pellets were ablated at 30 different sites by applying 25 laser pulses per site (Nd:YAG@1064 nm, 5 ns, 10 Hz, 25J cm(-2)). The plasma emission collected by lenses was directed through an optical fiber towards a high resolution echelle spectrometer equipped with an ICCD. Delay time and integration time gate were fixed at 2.0 and 4.5 mu s, respectively. Experiments carried out with pellets of sugarcane, orange tree and soy leaves showed a significant effect of the plant species for choosing the most appropriate grinding conditions. By using ball milling with agate materials, 20 min grinding for orange tree and soy, and 60 min for sugarcane leaves led to particle size distributions generally lower than 75 mu m. Cryogenic grinding yielded similar particle size distributions after 10 min for orange tree, 20 min for soy and 30 min for sugarcane leaves. There was up to 50% emission signal enhancement on LIBS measurements for most elements by improving particle size distribution and consequently the pellet porosity. (C) 2011 Elsevier B.V. All rights reserved.

Downscaling a multicommuted flow injection analysis system for the photometric determination of iodate in table salt

In this work a downscaled multicommuted flow injection analysis setup for photometric determination is described. The setup consists of a flow system module and a LED based photometer, with a total internal volume of about 170 mu L The system was tested by developing an analytical procedure for the photometric determination of iodate in table salt using N,N-diethyl-henylenediamine (DPD) as the chromogenic reagent. Accuracy was accessed by applying the paired r-test between results obtained using the proposed procedure and a reference method, and no significant difference at the 95% confidence level was observed. Other profitable features, such as a low reagent consumption of 7.3 mu g DPD per determination: a linear response ranging from 0.1 up to 3.0 m IO(3)(-), a relative standard deviation of 0.9% (n = 11) for samples containing 0.5 m IO(3)(-), a detection limit of 17 mu g L(-1) IO(3)(-), a sampling throughput of 117 determination per hour, and a waste generation 600 mu L per determination, were also achieved. (C) 2010 Elsevier B.V. All rights reserved.