Rapid evolution of chemosensory receptor genes in a pair of sibling species of orchid bees (Apidae: Euglossini).

BackgroundInsects rely more on chemical signals (semiochemicals) than on any other sensory modality to find, identify, and choose mates. In most insects, pheromone production is typically regulated through biosynthetic pathways, whereas pheromone sensory detection is controlled by the olfactory system. Orchid bees are exceptional in that their semiochemicals are not produced metabolically, but instead male bees collect odoriferous compounds (perfumes) from the environment and store them in specialized hind-leg pockets to subsequently expose during courtship display. Thus, the olfactory sensory system of orchid bees simultaneously controls male perfume traits (sender components) and female preferences (receiver components). This functional linkage increases the opportunities for parallel evolution of male traits and female preferences, particularly in response to genetic changes of chemosensory detection (e.g. Odorant Receptor genes). To identify whether shifts in pheromone composition among related lineages of orchid bees are associated with divergence in chemosensory genes of the olfactory periphery, we searched for patterns of divergent selection across the antennal transcriptomes of two recently diverged sibling species Euglossa dilemma and E. viridissima.ResultsWe identified 3185 orthologous genes including 94 chemosensory loci from five different gene families (Odorant Receptors, Ionotropic Receptors, Gustatory Receptors, Odorant Binding Proteins, and Chemosensory Proteins). Our results revealed that orthologs with signatures of divergent selection between E. dilemma and E. viridissima were significantly enriched for chemosensory genes. Notably, elevated signals of divergent selection were almost exclusively observed among chemosensory receptors (i.e. Odorant Receptors).ConclusionsOur results suggest that rapid changes in the chemosensory gene family occurred among closely related species of orchid bees. These findings are consistent with the hypothesis that strong divergent selection acting on chemosensory receptor genes plays an important role in the evolution and diversification of insect pheromone systems

"If You Can't Beat them, Join them": A Usability Approach to Interdependent Privacy in Cloud Apps

Cloud storage services, like Dropbox and Google Drive, have growing ecosystems of 3rd party apps that are designed to work with users' cloud files. Such apps often request full access to users' files, including files shared with collaborators. Hence, whenever a user grants access to a new vendor, she is inflicting a privacy loss on herself and on her collaborators too. Based on analyzing a real dataset of 183 Google Drive users and 131 third party apps, we discover that collaborators inflict a privacy loss which is at least 39% higher than what users themselves cause. We take a step toward minimizing this loss by introducing the concept of History-based decisions. Simply put, users are informed at decision time about the vendors which have been previously granted access to their data. Thus, they can reduce their privacy loss by not installing apps from new vendors whenever possible. Next, we realize this concept by introducing a new privacy indicator, which can be integrated within the cloud apps' authorization interface. Via a web experiment with 141 participants recruited from CrowdFlower, we show that our privacy indicator can significantly increase the user's likelihood of choosing the app that minimizes her privacy loss. Finally, we explore the network effect of History-based decisions via a simulation on top of large collaboration networks. We demonstrate that adopting such a decision-making process is capable of reducing the growth of users' privacy loss by 70% in a Google Drive-based network and by 40% in an author collaboration network. This is despite the fact that we neither assume that users cooperate nor that they exhibit altruistic behavior. To our knowledge, our work is the first to provide quantifiable evidence of the privacy risk that collaborators pose in cloud apps. We are also the first to mitigate this problem via a usable privacy approach.Comment: Authors' extended version of the paper published at CODASPY 201

A general strategy for discovery of inhibitors and activators of RING and U-box E3 ligases with ubiquitin variants

RING and U-box E3 ubiquitin ligases regulate diverse eukaryotic processes and have been implicated in numerous diseases, but targeting these enzymes remains a major challenge. We report the development of three ubiquitin variants (UbVs), each binding selectively to the RING or U-box domain of a distinct E3 ligase: monomeric UBE4B, phosphorylated active CBL, or dimeric XIAP. Structural and biochemical analyses revealed that UbVs specifically inhibited the activity of UBE4B or phosphorylated CBL by blocking the E2∼Ub binding site. Surprisingly, the UbV selective for dimeric XIAP formed a dimer to stimulate E3 activity by stabilizing the closed E2∼Ub conformation. We further verified the inhibitory and stimulatory functions of UbVs in cells. Our work provides a general strategy to inhibit or activate RING/U-box E3 ligases and provides a resource for the research community to modulate these enzymes

SUNNY: a Lazy Portfolio Approach for Constraint Solving

*** To appear in Theory and Practice of Logic Programming (TPLP) *** Within the context of constraint solving, a portfolio approach allows one to exploit the synergy between different solvers in order to create a globally better solver. In this paper we present SUNNY: a simple and flexible algorithm that takes advantage of a portfolio of constraint solvers in order to compute --- without learning an explicit model --- a schedule of them for solving a given Constraint Satisfaction Problem (CSP). Motivated by the performance reached by SUNNY vs. different simulations of other state of the art approaches, we developed sunny-csp, an effective portfolio solver that exploits the underlying SUNNY algorithm in order to solve a given CSP. Empirical tests conducted on exhaustive benchmarks of MiniZinc models show that the actual performance of SUNNY conforms to the predictions. This is encouraging both for improving the power of CSP portfolio solvers and for trying to export them to fields such as Answer Set Programming and Constraint Logic Programming

Discovery of a small molecule ligand of FRS2 that inhibits invasion and tumor growth

Purpose: Aberrant activation of the fibroblast growth factor receptor (FGFR) family of receptor tyrosine kinases drives oncogenic signaling through its proximal adaptor protein FRS2. Precise disruption of this disease-causing signal transmission in metastatic cancers could stall tumor growth and progression. The purpose of this study was to identify a small molecule ligand of FRS2 to interrupt oncogenic signal transmission from activated FGFRs. Methods: We used pharmacophore-based computational screening to identify potential small molecule ligands of the PTB domain of FRS2, which couples FRS2 to FGFRs. We confirmed PTB domain binding of molecules identified with biophysical binding assays and validated compound activity in cell-based functional assays in vitro and in an ovarian cancer model in vivo. We used thermal proteome profiling to identify potential off-targets of the lead compound. Results: We describe a small molecule ligand of the PTB domain of FRS2 that prevents FRS2 activation and interrupts FGFR signaling. This PTB-domain ligand displays on-target activity in cells and stalls FGFR-dependent matrix invasion in various cancer models. The small molecule ligand is detectable in the serum of mice at the effective concentration for prolonged time and reduces growth of the ovarian cancer model in vivo. Using thermal proteome profiling, we furthermore identified potential off-targets of the lead compound that will guide further compound refinement and drug development. Conclusions: Our results illustrate a phenotype-guided drug discovery strategy that identified a novel mechanism to repress FGFR-driven invasiveness and growth in human cancers. The here identified bioactive leads targeting FGF signaling and cell dissemination provide a novel structural basis for further development as a tumor agnostic strategy to repress FGFR- and FRS2-driven tumors. Keywords: Bioactive small molecule compound; Cell invasion; FGFR; FRS2; Protein–protein interaction interference; Thermal proteome profilin

Metrics for Broadband Networks in the Context of the Digital Economies

In a transition to automated digital management of broadband networks, communication service providers must look for new metrics to monitor these networks. Complete metrics frameworks are already emerging whereas majority of the new metrics are being proposed in technical papers. Considering common metrics for broadband networks and related technologies, this chapter offers insights into what metrics are available, and also suggests active areas of research. The broadband networks being a key component of the digital ecosystems are also an enabler to many other digital technologies and services. Reviewing first the metrics for computing systems, websites and digital platforms, the chapter focus then shifts to the most important technical and business metrics which are used for broadband networks. The demand-side and supply-side metrics including the key metrics of broadband speed and broadband availability are touched on. After outlining the broadband metrics which have been standardized and the metrics for measuring Internet traffic, the most commonly used metrics for broadband networks are surveyed in five categories: energy and power metrics, quality of service, quality of experience, security metrics, and robustness and resilience metrics. The chapter concludes with a discussion on machine learning, big data and the associated metrics