Soluble NSF attachment protein receptor molecular mimicry by a Legionella pneumophila Dot/Icm effector

Upon infection, Legionella pneumophila uses the Dot/Icm type IV secretion system to translocate effector proteins from the Legionella-containing vacuole (LCV) into the host cell cytoplasm. The effectors target a wide array of host cellular processes that aid LCV biogenesis, including the manipulation of membrane trafficking. In this study, we used a hidden Markov model screen to identify two novel, non-eukaryotic soluble NSF attachment protein receptor (SNARE) homologs: the bacterial Legionella SNARE effector A (LseA) and viral SNARE homolog A proteins. We characterized LseA as a Dot/Icm effector of L. pneumophila, which has close homology to the Qc-SNARE subfamily. The lseA gene was present in multiple sequenced L. pneumophila strains including Corby and was well distributed among L. pneumophila clinical and environmental isolates. Employing a variety of biochemical, cell biological and microbiological techniques, we found that farnesylated LseA localized to membranes associated with the Golgi complex in mammalian cells and LseA interacted with a subset of Qa-, Qb- and R-SNAREs in host cells. Our results suggested that LseA acts as a SNARE protein and has the potential to regulate or mediate membrane fusion events in Golgi-associated pathways.

On Merging Business Process Management and Geographic Information Systems : Modeling and Execution of Ecological Concerns in Processes

Business Process Management describes a holistic management approach for the systematic design, modeling, execution, validation, monitoring and improvement of organizational business processes. Traditionally, most attention within this community has been given to control-flow aspects, i.e., the ordering and sequencing of business activities, oftentimes in isolation with regards to the context in which these activities occur. In this paper, we propose an approach that allows executable process models to be integrated with Geographic Information Systems. This approach enables process models to take geospatial and other geographic aspects into account in an explicit manner both during the modeling phase and the execution phase. We contribute a structured modeling methodology, based on the well-known Business Process Model and Notation standard, which is formalized by means of a mapping to executable Colored Petri nets. We illustrate the feasibility of our approach by means of a sustainability-focused case example of a process with important ecological concerns.