Peptidomics of Three Bothrops Snake Venoms: Insights Into the Molecular Diversification of Proteomes and Peptidomes

Snake venom proteomes/peptidomes are highly complex and maintenance of their integrity within the gland lumen is crucial for the expression of toxin activities. There has been considerable progress in the field of venom proteomics, however, peptidomics does not progress as fast, because of the lack of comprehensive venom sequence databases for analysis of MS data. Therefore, in many cases venom peptides have to be sequenced manually by MS/MS analysis or Edman degradation. This is critical for rare snake species, as is the case of Bothrops cotiara (BC) and B. fonsecai (BF), which are regarded as near threatened with extinction. In this study we conducted a comprehensive analysis of the venom peptidomes of BC, BF, and B. jararaca (BJ) using a combination of solid-phase extraction and reversed-phase HPLC to fractionate the peptides, followed by nano-liquid chromatography-tandem MS (LC-MS/MS) or direct infusion electrospray ionization-(ESI)-MS/MS or MALDI-MS/MS analyses. We detected marked differences in the venom peptidomes and identified peptides ranging from 7 to 39 residues in length by de novo sequencing. Forty-four unique sequences were manually identified, out of which 30 are new peptides, including 17 bradykinin-potentiating peptides, three poly-histidine-poly-glycine peptides and interestingly, 10 L-amino acid oxidase fragments. Some of the new bradykinin-potentiating peptides display significant bradykinin potentiating activity. Automated database search revealed fragments from several toxins in the peptidomes, mainly from L-amino acid oxidase, and allowed the determination of the peptide bond specificity of proteinases and amino acid occurrences for the P4-P4' sites. We also demonstrate that the venom lyophilization/resolubilization process greatly increases the complexity of the peptidome because of the imbalance caused to the venom proteome and the consequent activity of proteinases on venom components. The use of proteinase inhibitors clearly showed different outcomes in the peptidome characterization and suggested that degradomic-peptidomic analysis of snake venoms is highly sensitive to the conditions of sampling procedures. Molecular & Cellular Proteomics 11: 10.1074/mcp.M112.019331, 1245-1262, 2012.

Lipid fingerprinting in women with early-onset preeclampsia: A first look

Objectives: The aim of this preliminary study was to characterize the plasma lipid profiling of women with preeclampsia. Design and methods: Plasma samples of 8 pregnant women with early-onset preeclampsia and 8 normal pregnant women were evaluated. Lipids were extracted from plasma using the Bligh-Dyer protocol. The extracts were subjected to MALDI-MS. Data matrix was exported for partial least squares discriminant analysis (PLS-DA) and a parameter VIP was employed to reflect the variable importance in the discriminant analysis. The major discriminant variables were selected and underwent to Mann-Whitney U test. Results: A total of 1290 ions were initially identified and twelve m/z signals were highlighted as the most important lipids for the discrimination of patients with preeclampsia. The identification of these differential lipids was carried out through Lipid Database Search. Conclusions: The main classes identified were glycerophosphocholines [GP01], glycerophosphoserines [GP03], glycerophosphoglycerols [GP04], glycosyldiradylglycerols [GL05] and glycerophosphates [GP10]. (C) 2012 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Pilot survey of expressed sequence tags (ESTs) from the asexual blood stages of Plasmodium vivax in human patients

Abstract Background Plasmodium vivax is the most widely distributed human malaria, responsible for 70–80 million clinical cases each year and large socio-economical burdens for countries such as Brazil where it is the most prevalent species. Unfortunately, due to the impossibility of growing this parasite in continuous in vitro culture, research on P. vivax remains largely neglected. Methods A pilot survey of expressed sequence tags (ESTs) from the asexual blood stages of P. vivax was performed. To do so, 1,184 clones from a cDNA library constructed with parasites obtained from 10 different human patients in the Brazilian Amazon were sequenced. Sequences were automatedly processed to remove contaminants and low quality reads. A total of 806 sequences with an average length of 586 bp met such criteria and their clustering revealed 666 distinct events. The consensus sequence of each cluster and the unique sequences of the singlets were used in similarity searches against different databases that included P. vivax, Plasmodium falciparum, Plasmodium yoelii, Plasmodium knowlesi, Apicomplexa and the GenBank non-redundant database. An E-value of <10-30 was used to define a significant database match. ESTs were manually assigned a gene ontology (GO) terminology Results A total of 769 ESTs could be assigned a putative identity based upon sequence similarity to known proteins in GenBank. Moreover, 292 ESTs were annotated and a GO terminology was assigned to 164 of them. Conclusion These are the first ESTs reported for P. vivax and, as such, they represent a valuable resource to assist in the annotation of the P. vivax genome currently being sequenced. Moreover, since the GC-content of the P. vivax genome is strikingly different from that of P. falciparum, these ESTs will help in the validation of gene predictions for P. vivax and to create a gene index of this malaria parasite.

A Bayesian Approach for Decision Making on the Identification of Genes with Different Expression Levels: An Application to Escherichia coli Bacterium Data

A common interest in gene expression data analysis is to identify from a large pool of candidate genes the genes that present significant changes in expression levels between a treatment and a control biological condition. Usually, it is done using a statistic value and a cutoff value that are used to separate the genes differentially and nondifferentially expressed. In this paper, we propose a Bayesian approach to identify genes differentially expressed calculating sequentially credibility intervals from predictive densities which are constructed using the sampled mean treatment effect from all genes in study excluding the treatment effect of genes previously identified with statistical evidence for difference. We compare our Bayesian approach with the standard ones based on the use of the t-test and modified t-tests via a simulation study, using small sample sizes which are common in gene expression data analysis. Results obtained report evidence that the proposed approach performs better than standard ones, especially for cases with mean differences and increases in treatment variance in relation to control variance. We also apply the methodologies to a well-known publicly available data set on Escherichia coli bacterium.

INFLUENCE OF DISCOUNT PRICE ANNOUNCEMENTS ON CONSUMER'S BEHAVIOR

The theoretical framework that underpins this research study is based on the Prospect Theory formulated by Kahneman and Tversky, and Thaler's Mental Accounting Theory. The research aims to evaluate the consumers' behavior when different patterns of discount are offered (in percentage and absolute value and for larger and smaller discounts). Two experiments were conducted to explore these patterns of behavior and the results that were obtained supported the view that the framing effect was a common occurrence. The patterns of choice of individuals in a sample were found to be different due to changes in the ways discounts were offered. This can be explained by the various ways of presenting discount rates that had an impact on the influence of purchase intentions, recommendations and quality perception.

A simple analysis of the influence of the solvent-induced electronic polarization on the N-15 magnetic shielding of pyridine in water

Electronic polarization induced by the interaction of a reference molecule with a liquid environment is expected to affect the magnetic shielding constants. Understanding this effect using realistic theoretical models is important for proper use of nuclear magnetic resonance in molecular characterization. In this work, we consider the pyridine molecule in water as a model system to briefly investigate this aspect. Thus, Monte Carlo simulations and quantum mechanics calculations based on the B3LYP/6-311++G (d,p) are used to analyze different aspects of the solvent effects on the N-15 magnetic shielding constant of pyridine in water. This includes in special the geometry relaxation and the electronic polarization of the solute by the solvent. The polarization effect is found to be very important, but, as expected for pyridine, the geometry relaxation contribution is essentially negligible. Using an average electrostatic model of the solvent, the magnetic shielding constant is calculated as -58.7 ppm, in good agreement with the experimental value of -56.3 ppm. The explicit inclusion of hydrogen-bonded water molecules embedded in the electrostatic field of the remaining solvent molecules gives the value of -61.8 ppm.

A rationale for long-lived quarks and leptons at the LHC: low energy flavour theory

In the framework of gauged flavour symmetries, new fermions in parity symmetric representations of the standard model are generically needed for the compensation of mixed anomalies. The key point is that their masses are also protected by flavour symmetries and some of them are expected to lie way below the flavour symmetry breaking scale(s), which has to occur many orders of magnitude above the electroweak scale to be compatible with the available data from flavour changing neutral currents and CP violation experiments. We argue that, actually, some of these fermions would plausibly get masses within the LHC range. If they are taken to be heavy quarks and leptons, in (bi)-fundamental representations of the standard model symmetries, their mixings with the light ones are strongly constrained to be very small by electroweak precision data. The alternative chosen here is to exactly forbid such mixings by breaking of flavour symmetries into an exact discrete symmetry, the so-called proton-hexality, primarily suggested to avoid proton decay. As a consequence of the large value needed for the flavour breaking scale, those heavy particles are long-lived and rather appropriate for the current and future searches at the LHC for quasi-stable hadrons and leptons. In fact, the LHC experiments have already started to look for them.

Influence of discount price announcements on consumer's behavior

The theoretical framework that underpins this research study is based on the Prospect Theory formulated by Kahneman and Tversky, and Thaler's Mental Accounting Theory. The research aims to evaluate the consumers' behavior when different patterns of discount are offered (in percentage and absolute value and for larger and smaller discounts). Two experiments were conducted to explore these patterns of behavior and the results that were obtained supported the view that the framing effect was a common occurrence. The patterns of choice of individuals in a sample were found to be different due to changes in the ways discounts were offered. This can be explained by the various ways of presenting discount rates that had an impact on the influence of purchase intentions, recommendations and quality perception.

Evolving decision trees with beam search-based initialization and lexicographic multi-objective evaluation

Decision tree induction algorithms represent one of the most popular techniques for dealing with classification problems. However, traditional decision-tree induction algorithms implement a greedy approach for node splitting that is inherently susceptible to local optima convergence. Evolutionary algorithms can avoid the problems associated with a greedy search and have been successfully employed to the induction of decision trees. Previously, we proposed a lexicographic multi-objective genetic algorithm for decision-tree induction, named LEGAL-Tree. In this work, we propose extending this approach substantially, particularly w.r.t. two important evolutionary aspects: the initialization of the population and the fitness function. We carry out a comprehensive set of experiments to validate our extended algorithm. The experimental results suggest that it is able to outperform both traditional algorithms for decision-tree induction and another evolutionary algorithm in a variety of application domains.