We study the tailoring of structured random graph ensembles to real networks, with the objective of generating precise and practical mathematical tools for quantifying and comparing network topologies macroscopically, beyond the level of degree statistics. Our family of ensembles can produce graphs with any prescribed degree distribution and any degree-degree correlation function, its control parameters can be calculated fully analytically, and as a result we can calculate (asymptotically) formulae for entropies and complexities, and for information-theoretic distances between networks, expressed directly and explicitly in terms of their measured degree distribution and degree correlations.

Herein we discuss how FRET imaging can contribute at various stages to delineate the function of the proteome. Therefore, we briefly describe FRET imaging techniques, the selection of suitable FRET pairs and potential caveats. Furthermore, we discuss state-of-the-art FRET-based screening approaches (underpinned by protein interaction network analysis using computational biology) and preclinical intravital FRET-imaging techniques that can be used for functional validation of candidate hits (nodes and edges) from the network screen, as well as measurement of the efficacy of perturbing these nodes/edges by short hairpin RNA (shRNA) and/or small molecule-based approaches.

We apply our recently developed information-theoretic measures for the characterisation and comparison of protein–protein interaction networks. These measures are used to quantify topological network features via macroscopic statistical properties. Network differences are assessed based on these macroscopic properties as opposed to microscopic overlap, homology information or motif occurrences. We present the results of a large–scale analysis of protein–protein interaction networks. Precise null models are used in our analyses, allowing for reliable interpretation of the results. By quantifying the methodological biases of the experimental data, we can define an information threshold above which networks may be deemed to comprise consistent macroscopic topological properties, despite their small microscopic overlaps. Based on this rationale, data from yeast–two–hybrid methods are sufficiently consistent to allow for intra–species comparisons (between different experiments) and inter–species comparisons, while data from affinity–purification mass–spectrometry methods show large differences even within intra–species comparisons.

This information is current as of 30 November 2011.The following resources related to this article are available online at http://stke.sciencemag.org. The Rho guanosine triphosphatase (GTPase) Cdc42 coordinates cytoskeletal reorganization downstream of many receptors. The Rho-related GTPase from plants 1 (ROP1) exhibits oscillatory activation behavior at the apical plasma membrane of growing pollen tubes; however, a similar oscillation in Rho GTPase activity has so far not been demonstrated in mammalian cells. We hypothesized that oscillations in Cdc42 activity might occur within NK cells as they interact with target cells. Through fluorescence lifetime imaging of a Cdc42 biosensor, we observed that in live NK cells forming immunological synapses with target cells, Cdc42 activity oscillated after exhibiting an initial increase. We used protein-protein interaction networks and structural databases to identify candidate proteins that controlled Cdc42 activity, leading to the design of a targeted short interfering RNA screen. The guanine nucleotide exchange factors RhoGEF6 and RhoGEF7 were necessary for Cdc42 activation within the NK cell immunological synapse. In addition, the kinase Akt and the p85a subunit of phosphoinositide 3-kinase (PI3K) were required for Cdc42 activation, the periodicity of the oscillation in Cdc42 activity, and the subsequent polarization of cytotoxic vesicles toward target cells. Given that PI3Ks are targets of tumor therapies, our findings suggest the need to monitor innate immune function during the course of targeted therapy against these enzymes. Article Toolshttp

Retroposition is a widespread phenomenon resulting in the generation of new genes that are initially related to a parent gene via very high coding sequence similarity. We examine the evolutionary fate of four retrogenes generated by such an event; mouse Inpp5f_v2, Mcts2, Nap1l5, and U2af1-rs1. These genes are all subject to the epigenetic phenomenon of parental imprinting. We first provide new data on the age of these retrogene insertions. Using codon-based models of sequence evolution, we show these retrogenes have diverse evolutionary trajectories, including divergence from the parent coding sequence under positive selection pressure, purifying selection pressure maintaining parent-retrogene similarity, and neutral evolution. Examination of the expression pattern of retrogenes shows an atypical, broad pattern across multiple tissues. Protein 3D structure modeling reveals that a positively selected residue in U2af1-rs1, not shared by its parent, may influence protein conformation. Our case-by-case analysis of the evolution of four imprinted retrogenes reveals that this interesting class of imprinted genes, while similar in regulation and sequence characteristics, follow very varied evolutionary paths.