Arabidopsis Sec1/Munc18 protein SEC11 is a competitive and dynamic modulator of SNARE binding and SYP121-dependent vesicle traffic

The Arabidopsis thaliana Qa-SNARE SYP121 (=SYR1/PEN1) drives vesicle traffic at the plasma membrane of cells throughout the vegetative plant. It facilitates responses to drought, to the water stress hormone abscisic acid, and to pathogen attack, and it is essential for recovery from so-called programmed stomatal closure. How SYP121-mediated traffic is regulated is largely unknown, although it is thought to depend on formation of a fusion-competent SNARE core complex with the cognate partners VAMP721 and SNAP33. Like SYP121, the Arabidopsis Sec1/Munc18 protein SEC11 (=KEULE) is expressed throughout the vegetative plant. We find that SEC11 binds directly with SYP121 both in vitro and in vivo to affect secretory traffic. Binding occurs through two distinct modes, one requiring only SEC11 and SYP121 and the second dependent on assembly of a complex with VAMP721 and SNAP33. SEC11 competes dynamically for SYP121 binding with SNAP33 and VAMP721, and this competition is predicated by SEC11 association with the N terminus of SYP121. These and additional data are consistent with a model in which SYP121-mediated vesicle fusion is regulated by an unusual “handshaking” mechanism of concerted SEC11 debinding and rebinding. They also implicate one or more factors that alter or disrupt SEC11 association with the SYP121 N terminus as an early step initiating SNARE complex formation

Aligning Monitoring and Compliance Requirements in Evolving Business Networks

Dynamic business networks (BNs) are intrinsically characterised by change. Compliance requirements management, in this context, may become particularly challenging. Partners in the network may join and leave the collaboration dynamically and tasks over which compliance requirements are specified may be consequently delegated to new partners or backsourced by network participants. This paper considers the issue of aligning the compliance requirements in a BN with the monitoring requirements they induce on the BN participants when change (or evolution) occurs. We first provide a conceptual model of BNs and their compliance requirements, introducing the concept of monitoring capabilities induced by compliance requirements. Then, we present a set of mechanisms to ensure consistency between the monitoring and compliance requirements when BNs evolve, e.g. tasks are delegated or backsourced in-house. Eventually, we discuss a prototype implementation of our framework, which also implements a set of metrics to check the status of a BN in respect of compliance monitorability

Towards a methodology for the engineering of event-driven process applications

Successful applications of the Internet of Things such as smart cities, smart logistics, and predictive maintenance, build on observing and analyzing business-related objects in the real world for business process execution and monitoring. In this context, complex event processing is increasingly used to integrate events from sensors with events stemming from business process management systems. This paper describes a methodology to combine the areas and engineer an event-driven logistics processes application. Thereby, we describe the requirements, use cases and lessons learned to design and implement such an architecture

Phosphorylation Alters the Interaction of the Arabidopsis Phosphotransfer Protein AHP1 with Its Sensor Kinase ETR1

The ethylene receptor ethylene response 1 (ETR1) and the Arabidopsis histidine-containing phosphotransfer protein 1 (AHP1) form a tight complex in vitro. According to our current model ETR1 and AHP1 together with a response regulator form a phosphorelay system controlling the gene expression response to the plant hormone ethylene, similar to the two-component signaling in bacteria. The model implies that ETR1 functions as a sensor kinase and is autophosphorylated in the absence of ethylene. The phosphoryl group is then transferred onto a histidine at the canonical phosphorylation site in AHP1. For phosphoryl group transfer both binding partners need to form a tight complex. After ethylene binding the receptor is switched to the non-phosphorylated state. This switch is accompanied by a conformational change that decreases the affinity to the phosphorylated AHP1. To test this model we used fluorescence polarization and examined how the phosphorylation status of the proteins affects formation of the suggested ETR1−AHP1 signaling complex. We have employed various mutants of ETR1 and AHP1 mimicking permanent phosphorylation or preventing phosphorylation, respectively. Our results show that phosphorylation plays an important role in complex formation as affinity is dramatically reduced when the signaling partners are either both in their non-phosphorylated form or both in their phosphorylated form. On the other hand, affinity is greatly enhanced when either protein is in the phosphorylated state and the corresponding partner in its non-phosphorylated form. Our results indicate that interaction of ETR1 and AHP1 requires that ETR1 is a dimer, as in its functional state as receptor in planta

Comparing Petri Net and Activity Diagram Variants for Workflow Modelling:A Quest for Reactive Petri Nets

Petri net variants are widely used as a workflow modelling technique. Recently, UMLa ctivity diagrams have been used for the same purpose, even though the syntax and semantics of activity diagrams has not been yet fully worked out. Nevertheless, activity diagrams seem very similar to Petri nets and on the surface, one may think that they are variants of each other. To substantiate or deny this claim, we need to formalise the intended semantics of activity diagrams and then compare this with various Petri net semantics. In previous papers we have defined two formal semantics for UMLact ivity diagrams that are intended for workflow modelling. In this paper, we discuss the design choices that underlie these two semantics and investigate whether these design choices can be met in low-level and high-level Petri net semantics. We argue that the main difference between the Petri net semantics and our semantics of UML act ivity diagrams is that the Petri net semantics models resource usage of closed, active systems that are non-reactive, whereas our semantics of UMLact ivity diagrams models open, reactive systems. Since workflow systems are open, reactive systems, we conclude that Petri nets cannot model workflows accurately, unless they are extended with a syntax and semantics for reactivity