Burkholderia cenocepacia disrupts host cell actin cytoskeleton by inactivating Rac and Cdc42

Burkholderia cenocepacia, a member of the Burkholderia cepacia complex, is an opportunistic pathogen that causes devastating infections in patients with cystic fibrosis. The ability of B. cenocepacia to survive within host cells could contribute significantly to its virulence in immunocompromised patients. In this study, we explored the mechanisms that enable B. cenocepacia to survive inside macrophages. We found that B. cenocepacia disrupts the actin cytoskeleton of infected macrophages, drastically altering their morphology. Submembranous actin undergoes depolymerization, leading to cell retraction. The bacteria perturb actin architecture by inactivating Rho family GTPases, particularly Rac1 and Cdc42. GTPase inactivation follows internalization of viable B. cenocepacia and compromises phagocyte function: macropinocytosis and phagocytosis are markedly inhibited, likely impairing the microbicidal and antigen-presenting capability of infected macrophages. The type VI secretion system is essential for the bacteria to elicit these changes. This is the first report demonstrating inactivation of Rho family GTPases by a member of the B. cepacia complex.

A constraints-based resource discovery model for multi-provider cloud environments

Increasingly infrastructure providers are supplying the cloud marketplace with storage and on-demand compute resources to host cloud applications. From an application user's point of view, it is desirable to identify the most appropriate set of available resources on which to execute an application. Resource choice can be complex and may involve comparing available hardware specifications, operating systems, value-added services, such as network configuration or data replication, and operating costs, such as hosting cost and data throughput. Providers' cost models often change and new commodity cost models, such as spot pricing, have been introduced to offer significant savings. In this paper, a software abstraction layer is used to discover infrastructure resources for a particular application, across multiple providers, by using a two-phase constraints-based approach. In the first phase, a set of possible infrastructure resources are identified for a given application. In the second phase, a heuristic is used to select the most appropriate resources from the initial set. For some applications a cost-based heuristic is most appropriate; for others a performance-based heuristic may be used. A financial services application and a high performance computing application are used to illustrate the execution of the proposed resource discovery mechanism. The experimental result shows the proposed model could dynamically select an appropriate set of resouces that match the application's requirements.

Diverse pathogenicity of Burkholderia cepacia complex strains in the Caenorhabditis elegans host model

A fast screening method was developed to assess the pathogenicity of a diverse collection of environmental and clinical Burkholderia cepacia complex isolates in the nematode Caenorhabditis elegans. The method was validated by comparison with the standard slow-killing assay. We observed that the pathogenicity of B. cepacia complex isolates in C. elegans was strain-dependent but species-independent. The wide range of observed pathogenic phenotypes agrees with the high degree of phenotypic variation among species of the B. cepacia complex and suggests that the taxonomic classification of a given strain within the complex cannot predict pathogenicity.