Overview of the Alliance for Cellular Signaling

The Alliance for Cellular Signaling is a large-scale collaboration designed to answer global questions about signalling networks. Pathways will be studied intensively in two cells-B lymphocytes (the cells of the immune system) and cardiac myocytes-to facilitate quantitative modelling. One goal is to catalyse complementary research in individual laboratories; to facilitate this, all alliance data are freely available for use by the entire research community.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62977/1/nature01304.pd

Use of cDNA Tiling Arrays for Identifying Protein Interactions Selected by In Vitro Display Technologies

In vitro display technologies such as mRNA display are powerful screening tools for protein interaction analysis, but the final cloning and sequencing processes represent a bottleneck, resulting in many false negatives. Here we describe an application of tiling array technology to identify specifically binding proteins selected with the in vitro virus (IVV) mRNA display technology. We constructed transcription-factor tiling (TFT) arrays containing ∼1,600 open reading frame sequences of known and predicted mouse transcription-regulatory factors (334,372 oligonucleotides, 50-mer in length) to analyze cDNA fragments from mRNA-display screening for Jun-associated proteins. The use of the TFT arrays greatly increased the coverage of known Jun-interactors to 28% (from 14% with the cloning and sequencing approach), without reducing the accuracy (∼75%). This method could detect even targets with extremely low expression levels (less than a single mRNA copy per cell in whole brain tissue). This highly sensitive and reliable method should be useful for high-throughput protein interaction analysis on a genome-wide scale

Rationalization and Design of the Complementarity Determining Region Sequences in an Antibody-Antigen Recognition Interface

Protein-protein interactions are critical determinants in biological systems. Engineered proteins binding to specific areas on protein surfaces could lead to therapeutics or diagnostics for treating diseases in humans. But designing epitope-specific protein-protein interactions with computational atomistic interaction free energy remains a difficult challenge. Here we show that, with the antibody-VEGF (vascular endothelial growth factor) interaction as a model system, the experimentally observed amino acid preferences in the antibody-antigen interface can be rationalized with 3-dimensional distributions of interacting atoms derived from the database of protein structures. Machine learning models established on the rationalization can be generalized to design amino acid preferences in antibody-antigen interfaces, for which the experimental validations are tractable with current high throughput synthetic antibody display technologies. Leave-one-out cross validation on the benchmark system yielded the accuracy, precision, recall (sensitivity) and specificity of the overall binary predictions to be 0.69, 0.45, 0.63, and 0.71 respectively, and the overall Matthews correlation coefficient of the 20 amino acid types in the 24 interface CDR positions was 0.312. The structure-based computational antibody design methodology was further tested with other antibodies binding to VEGF. The results indicate that the methodology could provide alternatives to the current antibody technologies based on animal immune systems in engineering therapeutic and diagnostic antibodies against predetermined antigen epitopes

A split horseradish peroxidase for detection of intercellular protein-protein interactions and sensitive visualization of synapses

Intercellular protein-protein interactions (PPIs) enable communication between cells in diverse biological processes, including cell proliferation, immune responses, infection and synaptic transmission, but they are challenging to visualize because existing techniques1,2,3 have insufficient sensitivity and/or specificity. Here we report split horseradish peroxidase (sHRP) as a sensitive and specific tool for detection of intercellular PPIs. The two sHRP fragments, engineered through screening of 17 cut sites in HRP followed by directed evolution, reconstitute into an active form when driven together by an intercellular PPI, producing bright fluorescence or contrast for electron microscopy. Fusing the sHRP fragments to the proteins neurexin (NRX) and neuroligin (NLG), which bind each other across the synaptic cleft4, enabled sensitive visualization of synapses between specific sets of neurons, including two classes of synapses in the mouse visual system. sHRP should be widely applicable for studying mechanisms of communication between a variety of cell types

Application guide for omics approaches to cell signaling

Research in signal transduction aims to identify the functions of different signaling pathways in physiological and pathological states. Traditional techniques using biochemical, genetic or cell biological approaches have made important contributions to our understanding of cellular signaling. However, the single-gene approach does not take into account the full complexity of cell signaling. With the availability of omics techniques, great progress has been made in understanding signaling networks. Omics approaches can be classified into two categories: 'molecular profiling', including genomic, proteomic, post-translational modification and interactome profiling; and 'molecular perturbation', including genetic and functional perturbations