Production of cyclodextrin glycosyltransferase by immobilized <Emphasis Type="Italic">Bacillus</Emphasis> sp. on chitosan matrix

The whole-cell immobilization on chitosan matrix was evaluated. Bacillus sp., as producer of CGTase, was grown in solid-state and batch cultivation using three types of starches (cassava, potato and cornstarch). Biomass growth and substrate consumption were assessed by flow cytometry and modified phenol–sulfuric acid assays, respectively. Qualitative analysis of CGTase production was determined by colorless area formation on solid culture containing phenolphthalein. Scanning electron microscopy (SEM) analysis demonstrated that bacterial cells were immobilized on chitosan matrix efficiently. Free cells reached very high numbers during batch culture while immobilized cells maintained initial inoculum concentration. The maximum enzyme activity achieved by free cells was 58.15 U ml^?1 (36 h), 47.50 U ml^?1 (36 h) and 68.36 U ml^?1 (36 h) on cassava, potato and cornstarch, respectively. CGTase activities for immobilized cells were 82.15 U ml^?1 (18 h) on cassava, 79.17 U ml^?1 (12 h) on potato and 55.37 U ml^?1 (in 6 h and max 77.75 U ml^?1 in 36 h) on cornstarch. Application of immobilization technique increased CGTase activity significantly. The immobilized cells produced CGTase with higher activity in a shorter fermentation time comparing to free cells.     

Muscle Tissue Damage Induced by the Venom of Bothrops asper: Identification of Early and Late Pathological Events through Proteomic Analysis

The time-course of the pathological effects induced by the venom of the snake Bothrops asper in muscle tissue was investigated by a combination of histology, proteomic analysis of exudates collected in the vicinity of damaged muscle, and immunodetection of extracellular matrix proteins in exudates. Proteomic assay of exudates has become an excellent new methodological tool to detect key biomarkers of tissue alterations for a more integrative perspective of snake venom-induced pathology. The time-course analysis of the intracellular proteins showed an early presence of cytosolic and mitochondrial proteins in exudates, while cytoskeletal proteins increased later on. This underscores the rapid cytotoxic effect of venom, especially in muscle fibers, due to the action of myotoxic phospholipases A₂, followed by the action of proteinases in the cytoskeleton of damaged muscle fibers. Similarly, the early presence of basement membrane (BM) and other extracellular matrix (ECM) proteins in exudates reflects the rapid microvascular damage and hemorrhage induced by snake venom metalloproteinases. The presence of fragments of type IV collagen and perlecan one hour after envenoming suggests that hydrolysis of these mechanically/structurally-relevant BM components plays a key role in the genesis of hemorrhage. On the other hand, the increment of some ECM proteins in the exudate at later time intervals is likely a consequence of the action of endogenous matrix metalloproteinases (MMPs) or of de novo synthesis of ECM proteins during tissue remodeling as part of the inflammatory reaction. Our results offer relevant insights for a more integrative and systematic understanding of the time-course dynamics of muscle tissue damage induced by B. asper venom and possibly other viperid venoms.     

A Novel Method to Predict Genomic Islands Based on Mean Shift Clustering Algorithm

Genomic Islands (GIs) are regions of bacterial genomes that are acquired from other organisms by the phenomenon of horizontal transfer. These regions are often responsible for many important acquired adaptations of the bacteria, with great impact on their evolution and behavior. Nevertheless, these adaptations are usually associated with pathogenicity, antibiotic resistance, degradation and metabolism. Identification of such regions is of medical and industrial interest. For this reason, different approaches for genomic islands prediction have been proposed. However, none of them are capable of predicting precisely the complete repertory of GIs in a genome. The difficulties arise due to the changes in performance of different algorithms in the face of the variety of nucleotide distribution in different species. In this paper, we present a novel method to predict GIs that is built upon mean shift clustering algorithm. It does not require any information regarding the number of clusters, and the bandwidth parameter is automatically calculated based on a heuristic approach. The method was implemented in a new user-friendly tool named MSGIP—Mean Shift Genomic Island Predictor. Genomes of bacteria with GIs discussed in other papers were used to evaluate the proposed method. The application of this tool revealed the same GIs predicted by other methods and also different novel unpredicted islands. A detailed investigation of the different features related to typical GI elements inserted in these new regions confirmed its effectiveness. Stand-alone and user-friendly versions for this new methodology are available at http://msgip.integrativebioinformatics.me.     

New Insights on Wood Dimensional Stability Influenced by Secondary Metabolites: The Case of a Fast-Growing Tropical Species Bagassa guianensis Aubl.

Challenging evaluation of tropical forest biodiversity requires the reporting of taxonomic diversity but also the systematic characterization of wood properties in order to discover new promising species for timber industry. Among wood properties, the dimensional stability is regarded as a major technological characteristic to validate whether a wood species is adapted to commercial uses. Cell structure and organization are known to influence the drying shrinkage making wood density and microfibrils angle markers of choice to predict wood dimensional stability. On the contrary the role of wood extractive content remains unclear. This work focuses on the fast-growing tropical species Bagassa guianensis and we report herein a correlation between heartwood drying shrinkage and extractive content. Chemical extractions and shrinkage experiments were performed on separate wood twin samples to better evaluate correctly how secondary metabolites influence the wood shrinkage behaviour. Extractive content were qualitatively and quantitatively analysed using HPLC and NMR spectroscopy. We found that B guianensis heartwood has a homogeneous low shrinkage along its radius that could not be explained only by its basic density. In fact the low drying shrinkage is correlated to the high extractive content and a corrected model to improve the prediction of wood dimensional stability is presented. Additionally NMR experiments conducted on sapwood and heartwood extracts demonstrate that secondary metabolites biosynthesis occurs in sapwood thus revealing B. guianensis as a Juglans-Type heartwood formation. This work demonstrates that B. guianensis, a fast-growing species associated with high durability and high dimensional stability, is a good candidate for lumber production and commercial purposes.     

An improved neutral landscape model for recreating real landscapes and generating landscape series for spatial ecological simulations

Many studies have assessed the effect of landscape patterns on spatial ecological processes by simulating these processes in computer‐generated landscapes with varying composition and configuration. To generate such landscapes, various neutral landscape models have been developed. However, the limited set of landscape‐level pattern variables included in these models is often inadequate to generate landscapes that reflect real landscapes. In order to achieve more flexibility and variability in the generated landscapes patterns, a more complete set of class‐ and patch‐level pattern variables should be implemented in these models. These enhancements have been implemented in Landscape Generator (LG), which is a software that uses optimization algorithms to generate landscapes that match user‐defined target values. Developed for participatory spatial planning at small scale, we enhanced the usability of LG and demonstrated how it can be used for larger scale ecological studies. First, we used LG to recreate landscape patterns from a real landscape (i.e., a mountainous region in Switzerland). Second, we generated landscape series with incrementally changing pattern variables, which could be used in ecological simulation studies. We found that LG was able to recreate landscape patterns that approximate those of real landscapes. Furthermore, we successfully generated landscape series that would not have been possible with traditional neutral landscape models. LG is a promising novel approach for generating neutral landscapes and enables testing of new hypotheses regarding the influence of landscape patterns on ecological processes. LG is freely available online.     

Cryo-EM Data Are Superior to Contact and Interface Information in Integrative Modeling

Protein-protein interactions carry out a large variety of essential cellular processes. Cryo-electron microscopy (cryo-EM) is a powerful technique for the modeling of protein-protein interactions at a wide range of resolutions, and recent developments have caused a revolution in the field. At low resolution, cryo-EM maps can drive integrative modeling of the interaction, assembling existing structures into the map. Other experimental techniques can provide information on the interface or on the contacts between the monomers in the complex. This inevitably raises the question regarding which type of data is best suited to drive integrative modeling approaches. Systematic comparison of the prediction accuracy and specificity of the different integrative modeling paradigms is unavailable to date. Here, we compare EM-driven, interface-driven, and contact-driven integrative modeling paradigms. Models were generated for the protein docking benchmark using the ATTRACT docking engine and evaluated using the CAPRI two-star criterion. At 20 Å resolution, EM-driven modeling achieved a success rate of 100%, outperforming the other paradigms even with perfect interface and contact information. Therefore, even very low resolution cryo-EM data is superior in predicting heterodimeric and heterotrimeric protein assemblies. Our study demonstrates that a force field is not necessary, cryo-EM data alone is sufficient to accurately guide the monomers into place. The resulting rigid models successfully identify regions of conformational change, opening up perspectives for targeted flexible remodeling.     

Functional connectivity and genetic diversity of Eulaema atleticana (Apidae,Euglossina) in the Brazilian Atlantic Forest Corridor: assessment of gene flow

The mobility and dispersal of organisms affect population genetics and dynamics, and consequently affect persistence and the risk of extinction. Thus, it is important to understand how organisms move in the fragmented landscapes in order to manage populations and predict the effects of habitat changes on species persistence. This study evaluated the functional connectivity of an orchid bee (Eulaema atleticana Nemésio, 2009) with a high fidelity to forest habitats in the Brazilian Atlantic Forest Corridor by analyzing genetic diversity, spatial genetic structure, and gene flow estimated from microsatellite and mitochondrial markers. Genetic diversity was not correlated with area of the forest fragments, or with forest isolation. At the mosaic scale, Eulaema atleticana showed no significant or low genetic differentiation, indicating genetic homogeneity among forest fragments. A previous field study indicated that Eulaema atleticana was one of the most sensitive Euglossina bees to forest fragmentation but the present molecular analyses demonstrates that current gene flow is sufficient to maintain genetic variability at the mosaic scale.