Computational Pipeline for Analysis of Biomedical Networks with BioNAR.

In a living cell, proteins interact to assemble both transient and constant molecular complexes, which transfer signals/information around internal pathways. Modern proteomic techniques can identify the constituent components of these complexes, but more detailed analysis demands a network approach linking the molecules together and analyzing the emergent architectural properties. The Bioconductor package BioNAR combines a selection of existing R protocols for network analysis with newly designed original methodological features to support step-by-step analysis of biological/biomedical .

BioNAR: an integrated biological network analysis package in bioconductor.

Motivation: Biological function in protein complexes emerges from more than just the sum of their parts: molecules interact in a range of different sub-complexes and transfer signals/information around internal pathways. Modern proteomic techniques are excellent at producing a parts-list for such complexes, but more detailed analysis demands a network approach linking the molecules together and analysing the emergent architectural properties. Methods developed for the analysis of networks in social sciences have proven very useful for splitting biological networks into communities leading to the discovery of sub-complexes enriched with molecules associated with specific diseases or molecular functions that are not apparent from the constituent components alone.

Modelling eNvironment for Isoforms (MoNvIso): A general platform to predict structural determinants of protein isoforms in genetic diseases.

The seamless integration of human disease-related mutation data into protein structures is an essential component of any attempt to correctly assess the impact of the mutation. The key step preliminary to any structural modelling is the identification of the isoforms onto which mutations should be mapped due to there being several functionally different protein isoforms from the same gene. To handle large sets of data coming from omics techniques, this challenging task needs to be automatized.

Synaptome.db: a bioconductor package for synaptic proteomics data.

Summary: The neuronal synapse is underpinned by a large and diverse proteome but the molecular evidence is spread across many primary datasets. These data were recently curated into a single dataset describing a landscape of ∼8000 proteins found in studies of mammalian synapses. Here, we describe programmatic access to the dataset via the R/Bioconductor package Synaptome.

A unified resource and configurable model of the synapse proteome and its role in disease.

Genes encoding synaptic proteins are highly associated with neuronal disorders many of which show clinical co-morbidity. We integrated 58 published synaptic proteomic datasets that describe over 8000 proteins and combined them with direct protein-protein interactions and functional metadata to build a network resource that reveals the shared and unique protein components that underpin multiple disorders. All the data are provided in a flexible and accessible format to encourage custom use.

Dissecting the Shared and Context-Dependent Pathways Mediated by the p140Cap Adaptor Protein in Cancer and in Neurons.

The p140Cap adaptor protein is a scaffold molecule physiologically expressed in few epithelial tissues, such as the mammary gland, and in differentiated neurons. While the role of p140Cap in mammary gland epithelia is not still understood, we already know that a significant subset of breast cancers express p140Cap. In the subgroup of ERBB2-amplified breast cancers, a high p140Cap status predicts a significantly lower probability of developing a distant event and a clear difference in survival.

RKappa: Software for Analyzing Rule-Based Models.

RKappa is a framework for the development, simulation, and analysis of rule-based models within the mature statistically empowered R environment. It is designed for model editing, parameter identification, simulation, sensitivity analysis, and visualization. The framework is optimized for high-performance computing platforms and facilitates analysis of large-scale systems biology models where knowledge of exact mechanisms is limited and parameter values are uncertain.

Regional Diversity in the Postsynaptic Proteome of the Mouse Brain.

The proteome of the postsynaptic terminal of excitatory synapses comprises over one thousand proteins in vertebrate species and plays a central role in behavior and brain disease. The brain is organized into anatomically distinct regions and whether the synapse proteome differs across these regions is poorly understood. Postsynaptic proteomes were isolated from seven forebrain and hindbrain regions in mice and their composition determined using proteomic mass spectrometry.

Rule-based modelling provides an extendable framework for comparing candidate mechanisms underpinning clathrin polymerisation.

Polymerisation of clathrin is a key process that underlies clathrin-mediated endocytosis. Clathrin-coated vesicles are responsible for cell internalization of external substances required for normal homeostasis and life -sustaining activity. There are several hypotheses describing formation of closed clathrin structures.

Proteomic analysis of postsynaptic proteins in regions of the human neocortex.

The postsynaptic proteome of excitatory synapses comprises ~1,000 highly conserved proteins that control the behavioral repertoire, and mutations disrupting their function cause >130 brain diseases. Here, we document the composition of postsynaptic proteomes in human neocortical regions and integrate it with genetic, functional and structural magnetic resonance imaging, positron emission tomography imaging, and behavioral data. Neocortical regions show signatures of expression of individual proteins, protein complexes, biochemical and metabolic pathways.

Synaptic Interactome Mining Reveals p140Cap as a New Hub for PSD Proteins Involved in Psychiatric and Neurological Disorders.

Altered synaptic function has been associated with neurological and psychiatric conditions including intellectual disability, schizophrenia and autism spectrum disorder (ASD). Amongst the recently discovered synaptic proteins is p140Cap, an adaptor that localizes at dendritic spines and regulates their maturation and physiology. We recently showed that p140Cap knockout mice have cognitive deficits, impaired long-term potentiation (LTP) and long-term depression (LTD), and immature, filopodia-like dendritic spines.

Dynamics of elongation factor 2 kinase regulation in cortical neurons in response to synaptic activity.

The rapid regulation of cell signaling in response to calcium in neurons is essential for real-time processing of large amounts of information in the brain. A vital regulatory component, and one of the most energy-intensive biochemical processes in cells, is the elongation phase of mRNA translation, which is controlled by the Ca(2+)/CaM-dependent elongation factor 2 kinase (eEF2K). However, little is known about the dynamics of eEF2K regulation in neurons despite its established role in learning and synaptic plasticity.

A simulator for spatially extended kappa models.

Spatial Kappa is a simulator of models written in a variant of the rule-based stochastic modelling language Kappa, with spatial extensions.

Metabolic turnover of synaptic proteins: kinetics, interdependencies and implications for synaptic maintenance.

Chemical synapses contain multitudes of proteins, which in common with all proteins, have finite lifetimes and therefore need to be continuously replaced. Given the huge numbers of synaptic connections typical neurons form, the demand to maintain the protein contents of these connections might be expected to place considerable metabolic demands on each neuron. Moreover, synaptic proteostasis might differ according to distance from global protein synthesis sites, the availability of distributed protein synthesis facilities, trafficking rates and synaptic protein dynamics.

Evolution of the cognitive proteome: from static to dynamic network models.

Integrative analysis of the neuronal synapse proteome has uncovered an evolutionarily conserved signalling complex that underpins the cognitive capabilities of the brain. Highly dynamic, cell type specific and intricately regulated, the synaptic proteome presents many challenges to systems biology approaches, yet this is likely to be the best route to unlock a new generation of neuroscience research and CNS drug development that society so urgently demands. Most systems biology approaches today have focussed on exploiting protein-protein interaction data to their fullest extent within static interaction models.

Towards a quantitative model of the post-synaptic proteome.

The postsynaptic compartment of the excitatory glutamatergic synapse contains hundreds of distinct polypeptides with a wide range of functions (signalling, trafficking, cell-adhesion, etc.). Structural dynamics in the post-synaptic density (PSD) are believed to underpin cognitive processes.

Microarray data can predict diurnal changes of starch content in the picoalga Ostreococcus.

Background: The storage of photosynthetic carbohydrate products such as starch is subject to complex regulation, effected at both transcriptional and post-translational levels. The relevant genes in plants show pronounced daily regulation. Their temporal RNA expression profiles, however, do not predict the dynamics of metabolite levels, due to the divergence of enzyme activity from the RNA profiles.