Detecção in silico e caracterização dos constituintes micromoleculares majoritários do fungo endofítico Colletotrichum gloeosporioides isolado de folhas de Garcinia xanthochymus usando HPLC-DAD-HRMS e GC-MS

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise in silico de uma pirofosfatase e de uma tiosterase de uma biblioteca metagenômica de solo de Eucalipto spp

Pós-graduação em Microbiologia Agropecuária - FCAV

MetaPPase by in silico analyses predicting the novel gene operate as H+ pumps.

The lastyears declined the discovery of compounds to use in industrial and naturaldiversity has been the best supplier for novel genes, enzymes and compounds inhigh demand by the biotechnology industry. We know immense diversity of microorganisms,yet most remains unexplored. For these reason we use the metagenômica approach toinvestigate the potential of uncultured microorganisms. With this purpose weused the metagenomic library of from Eucalyptus spp. arboretum (EAA), wedid screening to found positive clone and them was submitted to the process of shotgun,the data obtained was submitted a bioinformatics analyses. Our results showsthe hypothesis of high unexplored microbial diversity of soil are able to foundnovel genes and metagenomic approach is and allowed to isolate novel genes and insilico analyses are essential part to identify a novel Inorganicpyrophosphatase (PPase) prediction indicated the novel gene operate as H+ pumps. Thissuggests that a special feature, our work in situ will be cloning thegene expression vector for subsequent kinetic characterization and crystallization.

Highly polymorphic in silico-derived microsatellite loci in the potato-infecting fungal pathogen Rhizoctonia solani anastomosis group 3 from the Colombian Andes

Fourteen polymorphic microsatellite DNA markers derived from the draft genome sequence of Rhizoctonia solani anastomosis group 3 (AG-3), strain Rhs 1AP, were designed and characterized from the potato-infecting soil fungus R. solani AG-3. All loci were polymorphic in two field populations collected from Solanum tuberosum and S. phureja in the Colombian Andes. The total number of alleles per locus ranged from two to seven, while gene diversity (expected heterozygosity) varied from 0.11 to 0.81. Considering the variable levels of genetic diversity observed, these markers should be useful for population genetic analyses of this important dikaryotic fungal pathogen on a global scale.

In silico network topology-based prediction of gene essentiality

The identification of genes essential for survival is important for the understanding of the minimal requirements for cellular life and for drug design. As experimental studies with the purpose of building a catalog of essential genes for a given organism are time-consuming and laborious, a computational approach which could predict gene essentiality with high accuracy would be of great value. We present here a novel computational approach, called NTPGE (Network Topology-based Prediction of Gene Essentiality), that relies on the network topology features of a gene to estimate its essentiality. The first step of NTPGE is to construct the integrated molecular network for a given organism comprising protein physical, metabolic and transcriptional regulation interactions. The second step consists in training a decision-tree-based machine-learning algorithm on known essential and non-essential genes of the organism of interest, considering as learning attributes the network topology information for each of these genes. Finally, the decision-tree classifier generated is applied to the set of genes of this organism to estimate essentiality for each gene. We applied the NTPGE approach for discovering the essential genes in Escherichia coli and then assessed its performance. (C) 2007 Elsevier B.V. All rights reserved.

Boron transport in Eucalyptus. 2. Identification in silico of a putative boron transporter for xylem loading in eucalypt

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

In silico evaluation of the Eucalyptus transcriptome

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Use of reverse transcriptase polymerase chain reaction (RT-PCR) in molecular screening of Newcastle disease virus in poultry and free-living bird populations

The aim of this study was to evaluate a simple molecular method of reverse transcriptase polymerase chain reaction (RT-PCR) to differentiate Newcastle disease virus strains according to their pathogenicity, in order to use it in molecular screening of Newcastle disease virus in poultry and free-living bird populations. Specific primers were developed to differentiate LaSota-LS-(vaccine strain) and Sao Joao do Meriti-SJM-strain (highly pathogenic strain). Chickens and pigeons were experimentally vaccinated/infected for an in vivo study to determine virus shedding in feces. Validation of sensitivity and specificity of the primers (SJM and LS) by experimental models used in the present study and results obtained in the molecular analysis of the primers by BLAST made it possible to generalize results. The development of primers that differentiate the level of pathogenicity of NDV stains is very important, mainly in countries where real-time RT-PCR is still not used as a routine test. These primers were able to determine the presence of the agent and to differentiate it according to its pathogenicity. © 2012 Springer Science+Business Media B.V.

The Development of a Universal In Silico Predictor of Protein-Protein Interactions

Protein-protein interactions (PPIs) are essential for understanding the function of biological systems and have been characterized using a vast array of experimental techniques. These techniques detect only a small proportion of all PPIs and are labor intensive and time consuming. Therefore, the development of computational methods capable of predicting PPIs accelerates the pace of discovery of new interactions. This paper reports a machine learning-based prediction model, the Universal In Silico Predictor of Protein-Protein Interactions (UNISPPI), which is a decision tree model that can reliably predict PPIs for all species (including proteins from parasite-host associations) using only 20 combinations of amino acids frequencies from interacting and non-interacting proteins as learning features. UNISPPI was able to correctly classify 79.4% and 72.6% of experimentally supported interactions and non-interacting protein pairs, respectively, from an independent test set. Moreover, UNISPPI suggests that the frequencies of the amino acids asparagine, cysteine and isoleucine are important features for distinguishing between interacting and non-interacting protein pairs. We envisage that UNISPPI can be a useful tool for prioritizing interactions for experimental validation. © 2013 Valente et al.

Análise in silico de um novo “cluster” de PKS II Metagenômico

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Detecção in silico, isolamento e caracterização estrutural dos constitutintes micromoleculares antimaláricos e antioxidantes em galhosmdemGarcina gardneriana (Clusiaceae)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Detecção in silico dos constituintes majoritários de Strychnos brasiliensis e S. pseudoquina (Loganiaceae) usando CLAE-DAD/EMAR

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estudo de Jatropha gossypifolia e J. multifida (Euphorbiaceae) aplicando métodos analíticos in silico e de desreplicação, visando a detecção e elucidação in situ dos constituintes micromoleculares com atividade acetilcolinesterásicas e antioxidante

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Detecção in silico e caracterização estrutural dos constituintes micromoleculares majoritários presentes no fungo endofitico Phomopsis stipata isolado de folhas de Styrax camporum Pohl (Styracaceae) usando CLAE-DAD/EMAR e CG-MS

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)