The WASP Homologue Las17 Activates the Novel Actin-regulatory Activity of Ysc84 to Promote Endocytosis in Yeast

Actin plays an essential role in many eukaryotic cellular processes, including motility, generation of polarity, and membrane trafficking. Actin function in these roles is regulated by association with proteins that affect its polymerization state, dynamics, and organization. Numerous proteins have been shown to localize with cortical patches of yeast actin during endocytosis, but the role of many of these proteins remains poorly understood. Here, we reveal that the yeast protein Ysc84 represents a new class of actin-binding proteins, conserved from yeast to humans. It contains a novel N-terminal actin-binding domain termed Ysc84 actin binding (YAB), which can bind and bundle actin filaments. Intriguingly, full-length Ysc84 alone does not bind to actin, but binding can be activated by a specific motif within the polyproline region of the yeast WASP homologue Las17. We also identify a new monomeric actin-binding site on Las17. Together, the polyproline region of Las17 and Ysc84 can promote actin polymerization. Using live cell imaging, kinetics of assembly and disassembly of proteins at the endocytic site were analyzed and reveal that loss of Ysc84 and its homologue Lsb3 decrease inward movement of vesicles consistent with a role in actin polymerization during endocytosis

From Topology to Phenotype in Protein–Protein Interaction Networks

We have recently witnessed an explosion in biological network data along with the development of computational approaches for their analyses. This new interdisciplinary research area is an integral part of systems biology, promising to provide new insights into organizational principles of life, as well as into evolution and disease. However, there is a danger that the area might become hindered by several emerging issues. In particular, there is typically a weak link between biological and computational scientists, resulting in the use of simple computational techniques of limited potential to explain these complex biological data. Hence, there is a danger that the community might view the topological features of network data as mere statistics, ignoring the value of the information contained in these data. This might result in the imposition of scientific doctrines, such as scale-free-centric (on the modelling side) and genome-centric (on the biological side) opinions onto this nascent research area. In this chapter, we take a network science perspective and present a brief, high-level overview of the area, commenting on possible challenges ahead. We focus on protein-protein interaction networks (PINs) in which nodes correspond to proteins in a cell and edges to physical bindings between the proteins. © 2010 Springer-Verlag London Limited