Mapping the molecular characteristics of Brazilian human T-cell lymphotropic virus type 1 Env (gp46) and Pol amino acid sequences for vaccine design

This study was carried out to evaluate the molecular pattern of all available Brazilian human T-cell lymphotropic virus type 1 Env (n = 15) and Pol (n = 43) nucleotide sequences via epitope prediction, physico-chemical analysis, and protein potential sites identification, giving support to the Brazilian AIDS vaccine program. In 12 previously described peptides of the Env sequences we found 12 epitopes, while in 4 peptides of the Pol sequences we found 4 epitopes. The total variation on the amino acid composition was 9 and 17% for human leukocyte antigen (HLA) class I and class II Env epitopes, respectively. After analyzing the Pol sequences, results revealed a total amino acid variation of 0.75% for HLA-I and HLA-II epitopes. In 5 of the 12 Env epitopes the physico-chemical analysis demonstrated that the mutations magnified the antigenicity profile. The potential protein domain analysis of Env sequences showed the loss of a CK-2 phosphorylation site caused by D197N mutation in one epitope, and a N-glycosylation site caused by S246Y and V247I mutations in another epitope. Besides, the analysis of selection pressure have found 8 positive selected sites (w = 9.59) using the codon-based substitution models and maximum-likelihood methods. These studies underscore the importance of this Env region for the virus fitness, for the host immune response and, therefore, for the development of vaccine candidates.

Methods for testing association between uncertain genotypes and quantitative traits.

Interpretability and power of genome-wide association studies can be increased by imputing unobserved genotypes, using a reference panel of individuals genotyped at higher marker density. For many markers, genotypes cannot be imputed with complete certainty, and the uncertainty needs to be taken into account when testing for association with a given phenotype. In this paper, we compare currently available methods for testing association between uncertain genotypes and quantitative traits. We show that some previously described methods offer poor control of the false-positive rate (FPR), and that satisfactory performance of these methods is obtained only by using ad hoc filtering rules or by using a harsh transformation of the trait under study. We propose new methods that are based on exact maximum likelihood estimation and use a mixture model to accommodate nonnormal trait distributions when necessary. The new methods adequately control the FPR and also have equal or better power compared to all previously described methods. We provide a fast software implementation of all the methods studied here; our new method requires computation time of less than one computer-day for a typical genome-wide scan, with 2.5 M single nucleotide polymorphisms and 5000 individuals.

Discovery of catalases in members of the Chlamydiales order.

Catalase is an important virulence factor for survival in macrophages and other phagocytic cells. In Chlamydiaceae, no catalase had been described so far. With the sequencing and annotation of the full genomes of Chlamydia-related bacteria, the presence of different catalase-encoding genes has been documented. However, their distribution in the Chlamydiales order and the functionality of these catalases remain unknown. Phylogeny of chlamydial catalases was inferred using MrBayes, maximum likelihood, and maximum parsimony algorithms, allowing the description of three clade 3 and two clade 2 catalases. Only monofunctional catalases were found (no catalase-peroxidase or Mn-catalase). All presented a conserved catalytic domain and tertiary structure. Enzymatic activity of cloned chlamydial catalases was assessed by measuring hydrogen peroxide degradation. The catalases are enzymatically active with different efficiencies. The catalase of Parachlamydia acanthamoebae is the least efficient of all (its catalytic activity was 2 logs lower than that of Pseudomonas aeruginosa). Based on the phylogenetic analysis, we hypothesize that an ancestral class 2 catalase probably was present in the common ancestor of all current Chlamydiales but was retained only in Criblamydia sequanensis and Neochlamydia hartmannellae. The catalases of class 3, present in Estrella lausannensis and Parachlamydia acanthamoebae, probably were acquired by lateral gene transfer from Rhizobiales, whereas for Waddlia chondrophila they likely originated from Legionellales or Actinomycetales. The acquisition of catalases on several occasions in the Chlamydiales suggests the importance of this enzyme for the bacteria in their host environment.

The evolutionary history of the CD209 (DC-SIGN) family in humans and non-human primates

The CD209 gene family that encodes C-type lectins in primates includes CD209 (DC-SIGN), CD209L (L-SIGN) and CD209L2. Understanding the evolution of these genes can help understand the duplication events generating this family, the process leading to the repeated neck region and identify protein domains under selective pressure. We compiled sequences from 14 primates representing 40 million years of evolution and from three non-primate mammal species. Phylogenetic analyses used Bayesian inference, and nucleotide substitutional patterns were assessed by codon-based maximum likelihood. Analyses suggest that CD209 genes emerged from a first duplication event in the common ancestor of anthropoids, yielding CD209L2 and an ancestral CD209 gene, which, in turn, duplicated in the common Old World primate ancestor, giving rise to CD209L and CD209. K(A)/K(S) values averaged over the entire tree were 0.43 (CD209), 0.52 (CD209L) and 0.35 (CD209L2), consistent with overall signatures of purifying selection. We also assessed the Toll-like receptor (TLR) gene family, which shares with CD209 genes a common profile of evolutionary constraint. The general feature of purifying selection of CD209 genes, despite an apparent redundancy (gene absence and gene loss), may reflect the need to faithfully recognize a multiplicity of pathogen motifs, commensals and a number of self-antigens

SlimCodeML: An Optimized Version of CodeML for the Branch-Site Model

CodeML (part of the PAML package) im- plements a maximum likelihood-based approach to de- tect positive selection on a specific branch of a given phylogenetic tree. While CodeML is widely used, it is very compute-intensive. We present SlimCodeML, an optimized version of CodeML for the branch-site model. Our performance analysis shows that SlimCodeML substantially outperforms CodeML (up to 9.38 times faster), especially for large-scale genomic analyses.

Efectos de la reforma del IRPF sobre la oferta laboral de las mujeres

The aim of this paper is to simulate the effects of the Spanish 1999 taxreform on the married women s labour behaviour and welfare in a partialequilibrium context. We estimate by maximum likelihood two models of laboursupply which take into account of the characteristics of the budgetconstraint. The simulation exercises suggest that the new tax can havesignificant effects on female s labour supply decisions and seems toincrease the individual s welfare.

Firm investment in imperfect capital markets: A structural estimation

We set up a dynamic model of firm investment in which liquidity constraintsenter explicity into the firm's maximization problem. The optimal policyrules are incorporated into a maximum likelihood procedure which estimatesthe structural parameters of the model. Investment is positively related tothe firm's internal financial position when the firm is relatively poor. This relationship disappears for wealthy firms, which can reach theirdesired level of investment. Borrowing is an increasing function of financial position for poor firms. This relationship is reversed as a firm's financial position improves, and large firms hold little debt.Liquidity constrained firms may be unused credits lines and the capacity toinvest further if they desire. However the fear that liquidity constraintswill become binding in the future induces them to invest only when internalresources increase.We estimate the structural parameters of the model and use them to quantifythe importance of liquidity constraints on firms' investment. We find thatliquidity constraints matter significantly for the investment decisions of firms. If firms can finance investment by issuing fresh equity, rather than with internal funds or debt, average capital stock is almost 35% higher overa period of 20 years. Transitory shocks to internal funds have a sustained effect on the capital stock. This effect lasts for several periods and ismore persistent for small firms than for large firms. A 10% negative shock to firm fundamentals reduces the capital stock of firms which face liquidityconstraints by almost 8% over a period as opposed to only 3.5% for firms which do not face these constraints.

The role of migration and domestic transmission in the spread of HIV-1 non-B subtypes in Switzerland.

BACKGROUND: By analyzing human immunodeficiency virus type 1 (HIV-1) pol sequences from the Swiss HIV Cohort Study (SHCS), we explored whether the prevalence of non-B subtypes reflects domestic transmission or migration patterns. METHODS: Swiss non-B sequences and sequences collected abroad were pooled to construct maximum likelihood trees, which were analyzed for Swiss-specific subepidemics, (subtrees including ≥80% Swiss sequences, bootstrap >70%; macroscale analysis) or evidence for domestic transmission (sequence pairs with genetic distance <1.5%, bootstrap ≥98%; microscale analysis). RESULTS: Of 8287 SHCS participants, 1732 (21%) were infected with non-B subtypes, of which A (n = 328), C (n = 272), CRF01_AE (n = 258), and CRF02_AG (n = 285) were studied further. The macroscale analysis revealed that 21% (A), 16% (C), 24% (CRF01_AE), and 28% (CRF02_AG) belonged to Swiss-specific subepidemics. The microscale analysis identified 26 possible transmission pairs: 3 (12%) including only homosexual Swiss men of white ethnicity; 3 (12%) including homosexual white men from Switzerland and partners from foreign countries; and 10 (38%) involving heterosexual white Swiss men and females of different nationality and predominantly nonwhite ethnicity. CONCLUSIONS: Of all non-B infections diagnosed in Switzerland, <25% could be prevented by domestic interventions. Awareness should be raised among immigrants and Swiss individuals with partners from high prevalence countries to contain the spread of non-B subtypes.

High-level molecular diversity of copper-zinc superoxide dismutase genes among and within species of arbuscular Mycorrhizal fungi.

In the ecologically important arbuscular mycorrhizal fungi (AMF), Sod1 encodes a functional polypeptide that confers increased tolerance to oxidative stress and that is upregulated inside the roots during early steps of the symbiosis with host plants. It is still unclear whether its expression is directed at scavenging reactive oxygen species (ROS) produced by the host, if it plays a role in the fungus-host dialogue, or if it is a consequence of oxidative stress from the surrounding environment. All these possibilities are equally likely, and molecular variation at the Sod1 locus can possibly have adaptive implications for one or all of the three mentioned functions. In this paper, we analyzed the diversity of the Sod1 gene in six AMF species, as well as 14 Glomus intraradices isolates from a single natural population. By sequencing this locus, we identified a large amount of nucleotide and amino acid molecular diversity both among AMF species and individuals, suggesting a rapid divergence of its codons. The Sod1 gene was monomorphic within each isolate we analyzed, and quantitative PCR strongly suggest this locus is present as a single copy in G. intraradices. Maximum-likelihood analyses performed using a variety of models for codon evolution indicated that a number of amino acid sites most likely evolved under the regime of positive selection among AMF species. In addition, we found that some isolates of G. intraradices from a natural population harbor very divergent orthologous Sod1 sequences, and our analysis suggested that diversifying selection, rather than recombination, was responsible for the persistence of this molecular diversity within the AMF population.

Bayesian image reconstruction with space-variant noise suppression

In this paper we present a Bayesian image reconstruction algorithm with entropy prior (FMAPE) that uses a space-variant hyperparameter. The spatial variation of the hyperparameter allows different degrees of resolution in areas of different statistical characteristics, thus avoiding the large residuals resulting from algorithms that use a constant hyperparameter. In the first implementation of the algorithm, we begin by segmenting a Maximum Likelihood Estimator (MLE) reconstruction. The segmentation method is based on using a wavelet decomposition and a self-organizing neural network. The result is a predetermined number of extended regions plus a small region for each star or bright object. To assign a different value of the hyperparameter to each extended region and star, we use either feasibility tests or cross-validation methods. Once the set of hyperparameters is obtained, we carried out the final Bayesian reconstruction, leading to a reconstruction with decreased bias and excellent visual characteristics. The method has been applied to data from the non-refurbished Hubble Space Telescope. The method can be also applied to ground-based images.

Postglacial recolonization at a snail's pace (Trochulus villosus): confronting competing refugia hypotheses using model selection.

The localization of Last Glacial Maximum (LGM) refugia is crucial information to understand a species' history and predict its reaction to future climate changes. However, many phylogeographical studies often lack sampling designs intensive enough to precisely localize these refugia. The hairy land snail Trochulus villosus has a small range centred on Switzerland, which could be intensively covered by sampling 455 individuals from 52 populations. Based on mitochondrial DNA sequences (COI and 16S), we identified two divergent lineages with distinct geographical distributions. Bayesian skyline plots suggested that both lineages expanded at the end of the LGM. To find where the origin populations were located, we applied the principles of ancestral character reconstruction and identified a candidate refugium for each mtDNA lineage: the French Jura and Central Switzerland, both ice-free during the LGM. Additional refugia, however, could not be excluded, as suggested by the microsatellite analysis of a population subset. Modelling the LGM niche of T. villosus, we showed that suitable climatic conditions were expected in the inferred refugia, but potentially also in the nunataks of the alpine ice shield. In a model selection approach, we compared several alternative recolonization scenarios by estimating the Akaike information criterion for their respective maximum-likelihood migration rates. The 'two refugia' scenario received by far the best support given the distribution of genetic diversity in T. villosus populations. Provided that fine-scale sampling designs and various analytical approaches are combined, it is possible to refine our necessary understanding of species responses to environmental changes.

Diagnostic techniques applied in geostatistics for agricultural data analysis

The structural modeling of spatial dependence, using a geostatistical approach, is an indispensable tool to determine parameters that define this structure, applied on interpolation of values at unsampled points by kriging techniques. However, the estimation of parameters can be greatly affected by the presence of atypical observations in sampled data. The purpose of this study was to use diagnostic techniques in Gaussian spatial linear models in geostatistics to evaluate the sensitivity of maximum likelihood and restrict maximum likelihood estimators to small perturbations in these data. For this purpose, studies with simulated and experimental data were conducted. Results with simulated data showed that the diagnostic techniques were efficient to identify the perturbation in data. The results with real data indicated that atypical values among the sampled data may have a strong influence on thematic maps, thus changing the spatial dependence structure. The application of diagnostic techniques should be part of any geostatistical analysis, to ensure a better quality of the information from thematic maps.

Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping

Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

Zonation for 3D aquifer characterization based on joint inversions of multimethod crosshole geophysical data

Predictive groundwater modeling requires accurate information about aquifer characteristics. Geophysical imaging is a powerful tool for delineating aquifer properties at an appropriate scale and resolution, but it suffers from problems of ambiguity. One way to overcome such limitations is to adopt a simultaneous multitechnique inversion strategy. We have developed a methodology for aquifer characterization based on structural joint inversion of multiple geophysical data sets followed by clustering to form zones and subsequent inversion for zonal parameters. Joint inversions based on cross-gradient structural constraints require less restrictive assumptions than, say, applying predefined petro-physical relationships and generally yield superior results. This approach has, for the first time, been applied to three geophysical data types in three dimensions. A classification scheme using maximum likelihood estimation is used to determine the parameters of a Gaussian mixture model that defines zonal geometries from joint-inversion tomograms. The resulting zones are used to estimate representative geophysical parameters of each zone, which are then used for field-scale petrophysical analysis. A synthetic study demonstrated how joint inversion of seismic and radar traveltimes and electrical resistance tomography (ERT) data greatly reduces misclassification of zones (down from 21.3% to 3.7%) and improves the accuracy of retrieved zonal parameters (from 1.8% to 0.3%) compared to individual inversions. We applied our scheme to a data set collected in northeastern Switzerland to delineate lithologic subunits within a gravel aquifer. The inversion models resolve three principal subhorizontal units along with some important 3D heterogeneity. Petro-physical analysis of the zonal parameters indicated approximately 30% variation in porosity within the gravel aquifer and an increasing fraction of finer sediments with depth.