Patterns of morphological variation and ecological correlates in the skull of vipers (Serpentes: Viperidae).

The skull of vipers is a highly kinetic anatomical structure involved in envenomating and consuming of prey. Morphological knowledge about the viperid skull is based on studies on some groups of species, but information on its variation within the whole family and its functional morphology is still scarce. In this study, we aimed to explore variation in skull morphology among species of the three subfamilies of Viperidae, and test whether that variation correlates with macrohabitat and diet. We performed quantitative analyses of the viperid skull based on broad taxonomic sampling and two methodological approaches: linear and geometric morphometrics. The results of both approaches showed that much of the variation lies in differences of shape and relative size of the premaxilla, the nasals, the frontals, and the parietals. The results indicated that phylogeny and size influence the shape of the skull, but we also found evidence of morphological differentiation between arboreal and terrestrial species and in species with mammal specialist diet. Our findings imply that, besides evolutionary allometry and phylogenetic signal, demands of particular diets coupled with use of certain habitats have in part shaped morphological evolution of the viperid skull.

Patterns of morphological variation and ecological correlates in the skull of vipers (Serpentes: Viperidae)

The skull of vipers is a highly kinetic anatomical structure involved in envenomating and consuming of prey. Morphological knowledge about the viperid skull is based on studies on some groups of species, but information on its variation within the whole family and its functional morphology is still scarce. In this study, we aimed to explore variation in skull morphology among species of the three subfamilies of Viperidae, and test whether that variation correlates with macrohabitat and diet. We performed quantitative analyses of the viperid skull based on broad taxonomic sampling and two methodological approaches: linear and geometric morphometrics. The results of both approaches showed that much of the variation lies in differences of shape and relative size of the premaxilla, the nasals, the frontals, and the parietals. The results indicated that phylogeny and size influence the shape of the skull, but we also found evidence of morphological differentiation between arboreal and terrestrial species and in species with mammal specialist diet. Our findings imply that, besides evolutionary allometry and phylogenetic signal, demands of particular diets coupled with use of certain habitats have in part shaped morphological evolution of the viperid skull.

Assessment of exposure to metals, As and Se in water and sediment of a freshwater reservoir and their bioaccumulation in fish species of different feeding and habitat preferences.

The concentrations of metals (Ag, Al, Ba, B, Be, Bi, Cd, Co, Cr, Cu, Fe, Ga, Hg, Li, Mn, Mo, Ni, Pb, Rb, Sr, Tl, U, V, Zn), As and Se were analyzed in water and sediments from three sites of Río Tercero Reservoir (Córdoba, Argentina) during the wet and the dry season. The dynamics of metals in six fish species (Hoplias malabaricus, Oligosarcus jenynsii, Rhamdia quelen, Bryconamericus iheringii, Astyanax fasciatus and Odontesthes bonariensis) from the reservoir were investigated to discover the possible differential influence of habitat and diet on metal accumulation in the fish. In the abiotic matrix, the highest heavy metal concentrations were observed in sediment. The concentrations of Al, Cu and Pb in water exceeded the limits considered as hazardous for aquatic life. Potential ecological risk analysis of metal concentrations in sediment indicated a low ecological risk in Río Tercero Reservoir in all sampling periods. The enrichment factor indicated that Cu, Pb, Zn and Hg come from anthropogenic sources. Among five different organs, the highest metal levels were found in gills and intestine. Rhamdia quelen and Oligosarcus jenynsii were the species with the highest values of metal accumulation in the whole body. Our study showed that the accumulation pattern of these multi-elements in the different fish species did not respond to diet or habitat, but seemed to be related to the detoxification mechanisms and the metabolism of each organism.

Comparative evaluation of atom mapping algorithms for balanced metabolic reactions: application to Recon 3D.

The mechanism of each chemical reaction in a metabolic network can be represented as a set of atom mappings, each of which relates an atom in a substrate metabolite to an atom of the same element in a product metabolite. Genome-scale metabolic network reconstructions typically represent biochemistry at the level of reaction stoichiometry. However, a more detailed representation at the underlying level of atom mappings opens the possibility for a broader range of biological, biomedical and biotechnological applications than with stoichiometry alone. Complete manual acquisition of atom mapping data for a genome-scale metabolic network is a laborious process. However, many algorithms exist to predict atom mappings. How do their predictions compare to each other and to manually curated atom mappings? For more than four thousand metabolic reactions in the latest human metabolic reconstruction, Recon 3D, we compared the atom mappings predicted by six atom mapping algorithms. We also compared these predictions to those obtained by manual curation of atom mappings for over five hundred reactions distributed among all top level Enzyme Commission number classes. Five of the evaluated algorithms had similarly high prediction accuracy of over 91% when compared to manually curated atom mapped reactions. On average, the accuracy of the prediction was highest for reactions catalysed by oxidoreductases and lowest for reactions catalysed by ligases. In addition to prediction accuracy, the algorithms were evaluated on their accessibility, their advanced features, such as the ability to identify equivalent atoms, and their ability to map hydrogen atoms. In addition to prediction accuracy, we found that software accessibility and advanced features were fundamental to the selection of an atom mapping algorithm in practice.

Improving information retrieval in functional analysis.

Transcriptome analysis is essential to understand the mechanisms regulating key biological processes and functions. The first step usually consists of identifying candidate genes; to find out which pathways are affected by those genes, however, functional analysis (FA) is mandatory. The most frequently used strategies for this purpose are Gene Set and Singular Enrichment Analysis (GSEA and SEA) over Gene Ontology. Several statistical methods have been developed and compared in terms of computational efficiency and/or statistical appropriateness. However, whether their results are similar or complementary, the sensitivity to parameter settings, or possible bias in the analyzed terms has not been addressed so far. Here, two GSEA and four SEA methods and their parameter combinations were evaluated in six datasets by comparing two breast cancer subtypes with well-known differences in genetic background and patient outcomes. We show that GSEA and SEA lead to different results depending on the chosen statistic, model and/or parameters. Both approaches provide complementary results from a biological perspective. Hence, an Integrative Functional Analysis (IFA) tool is proposed to improve information retrieval in FA. It provides a common gene expression analytic framework that grants a comprehensive and coherent analysis. Only a minimal user parameter setting is required, since the best SEA/GSEA alternatives are integrated. IFA utility was demonstrated by evaluating four prostate cancer and the TCGA breast cancer microarray datasets, which showed its biological generalization capabilities.

Contrasting gene expression patterns induced by levodopa and pramipexole treatments in the rat model of Parkinson's disease.

Whether the treatment of Parkinson's disease has to be initiated with levodopa or a D2 agonist like pramipexole remains debatable. Levodopa is more potent against symptoms than D2 agonists, but D2 agonists are less prone to induce motor complications and may have neuroprotective effects. Although regulation of plastic changes in striatal circuits may be the key to their different therapeutic potential, the gene expression patterns induced by de novo treatments with levodopa or D2 agonists are currently unknown. By studying the whole striatal transcriptome in a rodent model of early stage Parkinson's disease, we have identified the gene expression patterns underlying therapeutically comparable chronic treatments with levodopa or pramipexole. Despite the overall relatively small size of mRNA expression changes at the level of individual transcripts, our data show a robust and complete segregation of the transcript expression patterns induced by both treatments. Moreover, transcripts related to oxidative metabolism and mitochondrial function were enriched in levodopa-treated compared to vehicle-treated and pramipexole-treated animals, whereas transcripts related to olfactory transduction pathways were enriched in both treatment groups compared to vehicle-treated animals. Thus, our data reveal the plasticity of genetic striatal networks possibly contributing to the therapeutic effects of the most common initial treatments for Parkinson's disease, suggesting a role for oxidative stress in the long term complications induced by levodopa and identifying previously overlooked signaling cascades as potentially new therapeutic targets.