Using Information Interaction to Discover Epistatic Effects in Complex Diseases

It is widely agreed that complex diseases are typically caused by the joint effects of multiple instead of a single genetic variation. These genetic variations may show stronger effects when considered together than when considered individually, a phenomenon known as epistasis or multilocus interaction. In this work, we explore the applicability of information interaction to discover pairwise epistatic effects related with complex diseases. We start by showing that traditional approaches such as classification methods or greedy feature selection methods (such as the Fleuret method) do not perform well on this problem. We then compare our information interaction method with BEAM and SNPHarvester in artificial datasets simulating epistatic interactions and show that our method is more powerful to detect pairwise epistatic interactions than its competitors. We show results of the application of information interaction method to the WTCCC breast cancer dataset. Our results are validated using permutation tests. We were able to find 89 statistically significant pairwise interactions with a p-value lower than . Even though many recent algorithms have been designed to find epistasis with low marginals, we observed that all (except one) of the SNPs involved in statistically significant interactions have moderate or high marginals. We also report that the interactions found in this work were not present in gene-gene interaction network STRING.     

Praziquantel Treatment Decreases Schistosoma mansoni Genetic Diversity in Experimental Infections

Background

Schistosomiasis has a considerable impact on public health in many tropical and subtropical areas. In the new world, schistosomiasis is caused by the digenetic trematode Schistosoma mansoni. Chemotherapy is the main measure for controlling schistosomiasis, and the current drug of choice for treatment is praziquantel (PZQ). Although PZQ is efficient and safe, its repetitive large-scale use in endemic areas may lead to the selection of resistant strains. Isolates less susceptible to PZQ have been found in the field and selected for in the laboratory. The impact of selecting strains with a decreased susceptibility phenotype on disease dynamics and parasite population genetics is not fully understood. This study addresses the impact of PZQ pressure on the genetics of a laboratory population by analyzing frequency variations of polymorphic genetic markers.

Methodology

Infected mice were treated with increasing PZQ doses until the highest dose of 3×300 mg/Kg was reached. The effect of PZQ treatment on the parasite population was assessed using five polymorphic microsatellite markers. Parasitological and genetic data were compared with those of the untreated control. After six parasite generations submitted to treatment, it was possible to obtain a S. mansoni population with decreased susceptibility to PZQ. In our experiments we also observed that female worms were more susceptible to PZQ than male worms.

Conclusions

The selective pressure exerted by PZQ led to decreased genetic variability in S. mansoni and increased endogamy. The understanding of how S. mansoni populations respond to successive drug pressure has important implications on the appearance and maintenance of a PZQ resistance phenotype in endemic regions.     

Screening Microalgae Strains for Biodiesel Production: Lipid Productivity and Estimation of Fuel Quality Based on Fatty Acids Profiles as Selective Criteria

The viability of algae-based biodiesel industry depends on the selection of adequate strains in regard to profitable yields and oil quality. This work aimed to bioprospecting and screening 12 microalgae strains by applying, as selective criteria, the volumetric lipid productivity and the fatty acid profiles, used for estimating the biodiesel fuel properties. Volumetric lipid productivity varied among strains from 22.61 to 204.91 mg l^?1 day^?1. The highest lipid yields were observed for Chlorella (204.91 mg l^?1 day¹) and Botryococcus strains (112.43 and 98.00 mg l^?1 day^?1 for Botryococcus braunii and Botryococcus terribilis, respectively). Cluster and principal components analysis analysis applied to fatty acid methyl esters (FAME) profiles discriminated three different microalgae groups according to their potential for biodiesel production. Kirchneriella lunaris, Ankistrodesmus fusiformis, Chlamydocapsa bacillus, and Ankistrodesmus falcatus showed the highest levels of polyunsaturated FAME, which incurs in the production of biodiesels with the lowest (42.47–50.52) cetane number (CN), the highest (101.33–136.97) iodine values (IV), and the lowest oxidation stability. The higher levels of saturated FAME in the oils of Chlamydomonas sp. and Scenedesmus obliquus indicated them as source of biodiesel with higher oxidation stability, higher CN (63.63–64.94), and lower IV (27.34–35.28). The third group, except for the Trebouxyophyceae strains that appeared in isolation, are composed by microalgae that generate biodiesel of intermediate values for CN, IV, and oxidation stability, related to their levels of saturated and monosaturated lipids. Thus, in this research, FAME profiling suggested that the best approach for generating a microalgae-biodiesel of top quality is by mixing the oils of distinct cell cultures.     

Transition energy and potential energy curves for ionized inner-shell states of CO, O2 and N2 calculated by several inner-shell multiconfigurational approaches

Potential energy curves and inner-shell ionization energies of carbon monoxide, oxygen and nitrogen molecules were calculated using several forms of the inner-shell multiconfigurational self-consistent field (IS-MCSCF) method—a recently proposed protocol to obtain specifically converged inner-shell states at this level. The particular forms of the IS-MCSCF method designated IS-GVB-PP, IS-FVBL and IS-CASSCF stand for perfect pairing generalized valence bond, full valence bond-like MCSCF and complete active space self consistent field, respectively. A comparison of these different versions of the IS-MCSCF method was carried out for the first time. The results indicate that inner-shell states are described accurately even for the simplest version of the method (IS-GVB-PP). Dynamic correlation was recovered by multireference configuration interaction or multireference perturbation theory. For molecules not having equivalent atoms, all methods led to comparable and accurate transition energies. For molecules with equivalent atoms, the most accurate results were obtained by multireference perturbation theory. Scalar relativistic effects were accounted for using the Douglas-Kroll-Hess Hamiltonian.     

Seasonal Variation on the Contents of Coumarin and Kaurane‐Type Diterpenes in Mikania laevigata and M. glomerata Leaves under Different Shade Levels

Coumarin ( 1 ) and kaurane‐type diterpenes are considered the bioactive constituents of Mikania glomerata and M. laevigata, used in Brazil to treat respiratory affective disorders. The seasonal variation of 1 , ortho‐coumaric acid ( 2 ), benzoylgrandifloric acid ( 3 ), cinnamoylgrandifloric acid ( 4 ), and kaurenoic acid ( 5 ) in leaves of both species, cultivated in full sunlight and under shade levels of 40 and 80%, was quantified by HPLC. Compound 2 was detected solely in M. laevigata in concentrations below the limit of quantification. Coumarin was not found in M. glomerata, whereas its concentration reached 0.94±0.24% (w/w) in M. laevigata farmed in summer under 80% shading. Both Mikania species produced higher amounts of kaurane diterpenes when cultivated in plenty of sunlight. Hence, maximum contents of 1 are reached in M. laevigata cultivated under high shading, but with reduced concentrations of 3 – 5 . Conversely, M. glomerata should be cultivated under full sunlight and harvested in winter for highest concentrations of kaurane‐type diterpenes.     

A new theoretical analysis of the cooperative effect in T-shaped hydrogen complexes of CnHm∙∙∙HCN∙∙∙HW with n = 2, m = 2 or 4, and W = F or CN

In this theoretical work, a new idea about cooperativity in intermolecular clusters of C_nH_m???HCN???HW stabilized by hydrogen bonds composed by lone-electron pairs (nitrogen) and π clouds (C?=?C and C?≡?C) as proton acceptors is developed. The structural study and vibrational analysis have pointed out deformations in the intermolecular clusters caused by the HW terminal proton-donor, in which if W?=?fluorine the largest perturbation occurs. On the contrary, the HCN molecule is considered an intermolecular mediator because its structure is practically unaltered upon the formation of the trimolecular complexes. In order to understand the real contribution of the proton-donor either mediator (HCN) or terminal (HW with W?=?CN or F), a chemometric analysis was performed uniquely to discover which interaction plays a key role in the collapse of the cooperative effect. The formation of strongest interactions leads to more drastic variations in the energy distribution. In this way, the application of the quantum theory of atoms in molecules (QTAIM) has been extremely important because the hydrogen bond strengths followed by indiciums of covalence were predicted, and therefore the cooperative effect could be understood at last.