Functional characterisation of the mammalian NDR1 and NDR2 protein kinases and their regulation by the mammalian Ste20-like kinase MST3

Protein modification is a common regulatory mechanism in order to transduce a signal from one molecule to another. One of the best-studied protein modifications is phosphorylation. The enzymes that are capable of transferring phosphate groups onto other proteins are called protein kinases. Depending on the acceptor group, kinases can be distinguished into tyrosine, serine/threonine and dual-specificity kinases. This work describes the characterisation of human and mouse NDR1 and NDR2 kinases, members of the AGC group of serine/threonine kinases. The NDR protein kinase family is highly conserved between yeast and human, and several members have been shown to be involved in the regulation of cell morphology and the control of cell cycle progression. For example, the yeast NDR kinases Sid2p (Schizosaccharomyces pombe) and Dbf2p (Saccharomyces cerevisiae) are central components of the septation-initiation network and the mitosis exit network, respectively. The closest yeast relatives Cbk1p and Orb6p, members of the regulation of Ace2p transcription and morphogenesis network and Orb6 signalling pathways, are implicated in the coordination of cell cycle progression and cell morphology. This study, as well as studies using worms and flies, provide evidence that not only NDR is conserved, but also the NDR signalling pathway and regulation. Similar to yeast, NDR kinase activation is regulated by phosphorylation at the activation segment phosphorylation site and the hydrophobic motif phosphorylation site. This phosphorylation is regulated by a conserved signaling module consisting of MOB proteins and a STE20–like kinase. Here we show that the STE20-like kinase MST3 activates NDR by phosphorylation specifically at the hydrophobic motif in vitro and in vivo. Furthermore, MOB1A binding is important for the release of autoinhibition and full kinase activation. The data also indicate that NDR is part of a feedback mechanism, which induces cleavage and nuclear translocation of MST3. The data presented here also show that NDR1 and NDR2 are differentially expressed, but regulated in a similar manner. Mouse Ndr1 mRNA is mainly expressed in spleen, thymus and lung, whereas Ndr2 mRNA is more ubiquitously expressed, with the highest levels in the gastrointestinal tract. Both, NDR1 and NDR2, are activated by S100B protein and okadaic acid stimulated phosphorylation; NDR1 and NDR2 are also indistinguishable in the biochemical assays used: membrane targetting, phosphorylation by MST3, and activation by MOB. Further, this work describes the generation and initial characterisation of a mouse model for NDR1 deficiency. Protein analysis using NDR1 knockout mouse embryonic fibroblasts suggest a compensation of the loss of NDR1 by upregulation of NDR2 expression

The physics of spreading processes in multilayer networks

The study of networks plays a crucial role in investigating the structure, dynamics, and function of a wide variety of complex systems in myriad disciplines. Despite the success of traditional network analysis, standard networks provide a limited representation of complex systems, which often include different types of relationships (i.e., "multiplexity") among their constituent components and/or multiple interacting subsystems. Such structural complexity has a significant effect on both dynamics and function. Throwing away or aggregating available structural information can generate misleading results and be a major obstacle towards attempts to understand complex systems. The recent "multilayer" approach for modeling networked systems explicitly allows the incorporation of multiplexity and other features of realistic systems. On one hand, it allows one to couple different structural relationships by encoding them in a convenient mathematical object. On the other hand, it also allows one to couple different dynamical processes on top of such interconnected structures. The resulting framework plays a crucial role in helping achieve a thorough, accurate understanding of complex systems. The study of multilayer networks has also revealed new physical phenomena that remain hidden when using ordinary graphs, the traditional network representation. Here we survey progress towards attaining a deeper understanding of spreading processes on multilayer networks, and we highlight some of the physical phenomena related to spreading processes that emerge from multilayer structure.Comment: 25 pages, 4 figure

Identification and Classification of Hubs in Brain Networks

Brain regions in the mammalian cerebral cortex are linked by a complex network of fiber bundles. These inter-regional networks have previously been analyzed in terms of their node degree, structural motif, path length and clustering coefficient distributions. In this paper we focus on the identification and classification of hub regions, which are thought to play pivotal roles in the coordination of information flow. We identify hubs and characterize their network contributions by examining motif fingerprints and centrality indices for all regions within the cerebral cortices of both the cat and the macaque. Motif fingerprints capture the statistics of local connection patterns, while measures of centrality identify regions that lie on many of the shortest paths between parts of the network. Within both cat and macaque networks, we find that a combination of degree, motif participation, betweenness centrality and closeness centrality allows for reliable identification of hub regions, many of which have previously been functionally classified as polysensory or multimodal. We then classify hubs as either provincial (intra-cluster) hubs or connector (inter-cluster) hubs, and proceed to show that lesioning hubs of each type from the network produces opposite effects on the small-world index. Our study presents an approach to the identification and classification of putative hub regions in brain networks on the basis of multiple network attributes and charts potential links between the structural embedding of such regions and their functional roles