Mechanism of ubiquitin ligation and lysine prioritization by a HECT E3

Ubiquitination by HECT E3 enzymes regulates myriad processes, including tumor suppression, transcription, protein trafficking, and degradation. HECT E3s use a two-step mechanism to ligate ubiquitin to target proteins. The first step is guided by interactions between the catalytic HECT domain and the E2∼ubiquitin intermediate, which promote formation of a transient, thioester-bonded HECT∼ubiquitin intermediate. Here we report that the second step of ligation is mediated by a distinct catalytic architecture established by both the HECT E3 and its covalently linked ubiquitin. The structure of a chemically trapped proxy for an E3∼ubiquitin-substrate intermediate reveals three-way interactions between ubiquitin and the bilobal HECT domain orienting the E3∼ubiquitin thioester bond for ligation, and restricting the location of the substrate-binding domain to prioritize target lysines for ubiquitination. The data allow visualization of an E2-to-E3-to-substrate ubiquitin transfer cascade, and show how HECT-specific ubiquitin interactions driving multiple reactions are repurposed by a major E3 conformational change to promote ligation. DOI:http://dx.doi.org/10.7554/eLife.00828.001

Behavioural Consistency Within the Prisoner's Dilemma Game

Mixed-motive games represent situations that confront people with a conflict between cooperative and non-cooperative alternatives. Despite this common basis, recent research has shown that the consistency of people's choices across different mixed-motive games is rather low. The present research examined behavioural consistency within the same mixed-motive game, by presenting participants with a series of one-shot Prisoner's Dilemma Games. Across this set of games, payoffs were manipulated in order to intensify or weaken the conflict between self and the other party while maintaining the game's underlying structure. Our findings indicate that significant differences in choice behaviour are observed as a function of both situational (i.e. manipulations of the Prisoner's Dilemma Game's payoff structure) and personality differences (i.e. individual differences in personality and motivational traits). Moreover, our included situational variables and personality features did not interact with each other and were about equally impactful in shaping cooperation. Crucially, however, despite the significant behavioural differences across game variants, considerable consistency in choices was found as well, which suggests that the game's motivational basis reliably impacts choice behaviour in spite of situational and personality variations. We discuss implications for theorizing on mixed-motive situations and elaborate on the question how cooperation can be promoted

Blocking Simple and Complex Contagion by Edge Removal

Abstract—Eliminating interactions among individuals is an important means of blocking contagion spread; e.g., closing schools during an epidemic or shutting down electronic com-munication channels during social unrest. We study contagion blocking in networked populations by identifying edges to remove from a network, thus blocking contagion transmis-sion pathways. We formulate various problems to minimize contagion spread and show that some are efficiently solvable while others are formally hard. We also compare our hardness results to those from node blocking problems and show interesting differences between the two. Our main problem is not only hard, but also has no approximation guarantee, unless P = NP. Therefore, we devise a heuristic for the problem and compare its performance to state-of-the-art heuristics from the literature. We show, through results of 12 (network, heuristic) combinations on three real social networks, that our method offers considerable improvement in the ability to block contagions in weighted and unweighted networks. We also conduct a parametric study to understand the limitations of our approach. Keywords-contagion blocking; simple contagion; complex contagio

GDSCalc: A Web-Based Application for Evaluating Discrete Graph Dynamical Systems.

Discrete dynamical systems are used to model various realistic systems in network science, from social unrest in human populations to regulation in biological networks. A common approach is to model the agents of a system as vertices of a graph, and the pairwise interactions between agents as edges. Agents are in one of a finite set of states at each discrete time step and are assigned functions that describe how their states change based on neighborhood relations. Full characterization of state transitions of one system can give insights into fundamental behaviors of other dynamical systems. In this paper, we describe a discrete graph dynamical systems (GDSs) application called GDSCalc for computing and characterizing system dynamics. It is an open access system that is used through a web interface. We provide an overview of GDS theory. This theory is the basis of the web application; i.e., an understanding of GDS provides an understanding of the software features, while abstracting away implementation details. We present a set of illustrative examples to demonstrate its use in education and research. Finally, we compare GDSCalc with other discrete dynamical system software tools. Our perspective is that no single software tool will perform all computations that may be required by all users; tools typically have particular features that are more suitable for some tasks. We situate GDSCalc within this space of software tools

Node and shell removal heuristics for CSSP (Venezuela).

<p>Here, we see the largest remaining sub-cascade size in terms of numbers of tweets (normalized by the original size) as a function of numbers of remaining nodes in the cascade graph (normalized by the original number of nodes). This cascade occurred in April 2013, and its original size is 226,179 tweets.</p

Forecasting Social Unrest Using Activity Cascades

<div><p>Social unrest is endemic in many societies, and recent news has drawn attention to happenings in Latin America, the Middle East, and Eastern Europe. Civilian populations mobilize, sometimes spontaneously and sometimes in an organized manner, to raise awareness of key issues or to demand changes in governing or other organizational structures. It is of key interest to social scientists and policy makers to forecast civil unrest using indicators observed on media such as Twitter, news, and blogs. We present an event forecasting model using a notion of activity cascades in Twitter (proposed by Gonzalez-Bailon et al., 2011) to predict the occurrence of protests in three countries of Latin America: Brazil, Mexico, and Venezuela. The basic assumption is that the emergence of a suitably detected activity cascade is a precursor or a surrogate to a real protest event that will happen “on the ground.” Our model supports the theoretical characterization of large cascades using spectral properties and uses properties of detected cascades to forecast events. Experimental results on many datasets, including the recent June 2013 protests in Brazil, demonstrate the effectiveness of our approach.</p></div

Formation of cascades in the Twitter follower network.

<p>At time <i>t</i>, node 1 posts a tweet. Nodes 2 and 4 post at times <i>t</i>₂ and <i>t</i>₄ between <i>t</i> and <i>t</i>′ = <i>t</i> + <i>D</i>. Node 5, which follows 2, posts at some time <i>t</i>₅ between <i>t</i>′ and <i>t</i>″ = <i>t</i>′ + <i>D</i>. Therefore, the cascade <i>C</i>(1, <i>t</i>, <i>D</i>) is <i>C</i>(1, <i>t</i>, <i>D</i>) = {(1, <i>t</i>), (2, <i>t</i>₂), (4, <i>t</i>₄), (5, <i>t</i>₅)}.</p

Descriptive statistics of selected features (Brazil) for the MRT and F models.

<p>The names in the first column consist of the name of the structural feature (i.e., cascade size, duration or slope, which is the incremental increase in the size per day), and the statistical operations (i.e. median, average etc.).</p

LASSO Variables.

<p>Variables selected by LASSO in the cascade model for Brazil, for a training period of November 2012 through May 2013.</p