Azotobacter vinelandii is a soil bacterium related to the Pseudomonas genus that fixes nitrogen under aerobic conditions while simultaneously protecting nitrogenase from oxygen damage. In response to carbon availability, this organism undergoes a simple differentiation process to form cysts that are resistant to drought and other physical and chemical agents. Here we report the complete genome sequence of A. vinelandii DJ, which has a single circular genome of 5,365,318 bp. In order to reconcile an obligate aerobic lifestyle with exquisitely oxygen-sensitive processes, A. vinelandii is specialized in terms of its complement of respiratory proteins. It is able to produce alginate, a polymer that further protects the organism from excess exogenous oxygen, and it has multiple duplications of alginate modification genes, which may alter alginate composition in response to oxygen availability. The genome analysis identified the chromosomal locations of the genes coding for the three known oxygen-sensitive nitrogenases, as well as genes coding for other oxygen-sensitive enzymes, such as carbon monoxide dehydrogenase and formate dehydrogenase. These findings offer new prospects for the wider application of A. vinelandii as a host for the production and characterization of oxygen-sensitive proteins.
Diverse gene products including phytotoxins, pathogen-associated molecular patterns, and type III secreted effectors influence interactions between Pseudomonas syringae strains and plants, with additional yet uncharacterized factors likely contributing as well. Of particular interest are those interactions governing pathogen-host specificity. Comparative genomics of closely related pathogens with different host specificity represents an excellent approach for identification of genes contributing to host-range determination. A draft genome sequence of Pseudomonas syringae pv. tomato T1, which is pathogenic on tomato but nonpathogenic on Arabidopsis thaliana, was obtained for this purpose and compared with the genome of the closely related A. thaliana and tomato model pathogen P. syringae pv. tomato DC3000. Although the overall genetic content of each of the two genomes appears to be highly similar, the repertoire of effectors was found to diverge significantly. Several P. syringae pv. tomato T1 effectors absent from strain DC3000 were confirmed to be translocated into plants, with the well-studied effector AvrRpt2 representing a likely candidate for host-range determination. However, the presence of avrRpt2 was not found sufficient to explain A. thaliana resistance to P. syringae pv. tomato T1, suggesting that other effectors and possibly type III secretion system-independent factors also play a role in this interaction.
MamMiBase is available at http://www.mammibase.lncc.br
-Multiagent systems (MASs) have been applied to several application domains, such as e-commerce, unmanned vehicles, and many others. In addition, a set of different techniques has been integrated into multiagent applications. However, few of these applications have been commercially deployed and few of these techniques have been fully exploited by industrial applications. One reason is the lack of procedures guaranteeing that multiagent systems would behave as desired. Most of the existing test approaches only test agents as single individuals and do not provide ways of inspecting the behavior of an agent as part of a group, and the behavior of the whole group of agents. Accordingly, we modeled and developed a publishsubscribe-based architecture to facilitate the implementation of systems to test MASs at the agent and group levels. To illustrate and evaluate the use of the proposed architecture, we developed an MAS-based application and performed functional and performance ad-hoc tests.
With the advance in the genome sequencing techniques together with the arising of several repositories of biological data, computational techniques had become indispensable tools for a better characterization and understanding of the organisms in study. One way to analyze the genomes is to compare its sequences with other sequences from previously studied genomes, to define the similarities. Frequent updates in the biological data repositories led to the problem of reprocessing of the comparisons, that consists to avoid new comparisons among sequences of the study genome with already compared sequences from the repository. These comparisons are performed by biological comparasion tools, such as BLAST. This paper describes the problem, comparing it to the data flows, trying to visualize the frequent updates as a biological data flow, and addressing data streams techniques tha can be usefull to deal with the problems related to the reprocessing of the comparasions.Resumo. Com o avanço nas técnicas de sequenciamento de genomas, juntamente com o surgimento de diversos repositórios de dados biológicos, técnicas computacionais tornaramse indispensáveis ferramentas para uma melhor caracterização e compreensão dos organismos em estudo. Uma forma de analisar os genomas é comparar as suas sequências para determinar as sequências similares em relação a outros genomas estudados anteriormente. Atualizações frequentes nos repostiórios de dados biológicos deram origem ao problema da recomputação, que consistem em evitar recomparações entre as sequências dos genomas em estudo com as sequências dos repositórios, comparações essas efetuadas por ferramentas como o blast. Este trabalho apresenta o problema relacionando-o a fluxos de dados, visualizando as frequentes atualizações como um fluxo de dados biológicos, e abordando algumas técnicas em data streams que podem ser utilizadas para tratar os problemas relacionados a essas recomparações.Palavras-chave: Fluxos de dados, bancos de dados biológicos, comparação de sequências, BLAST Responsável por publicações:
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