A Novel Phosphopeptide Microarray Based Interactome Map in Breast Cancer Cells Reveals Phosphoprotein-GRB2 Cell Signaling Networks

The architecture of cellular proteins connected to form signaling pathways in response to internal and external cues is much more complex than a group of simple protein-protein interactions. Post translational modifications on proteins (e.g., phosphorylation of serine, threonine and tyrosine residues on proteins) initiate many downstream signaling events leading to protein-protein interactions and subsequent activation of signaling cascades leading to cell proliferation, cell differentiation and cell death. As evidenced by a rapidly expanding mass spectrometry database demonstrating protein phosphorylation at specific motifs, there is currently a large gap in understanding the functional significance of phosphoproteins with respect to their specific protein connections in the signaling cascades. A comprehensive map that interconnects phospho-motifs in pathways will enable identification of nodal protein interactions that are sensitive signatures indicating a disease phenotype from the physiological hemostasis and provide clues into control of disease. Using a novel phosphopeptide microarray technology, we have mapped endogenous tyrosine-phosphoproteome interaction networks in breast cancer cells mediated by signaling adaptor protein GRB2, which transduces cellular responses downstream of several RTKs through the Ras-ERK signaling cascade. We have identified several previously reported motif specific interactions and novel interactions. The peptide microarray data indicate that various phospho-motifs on a single protein are differentially regulated in various cell types and shows global downregulation of phosphoprotein interactions specifically in cells with metastatic potential. The study has revealed novel phosphoprotein mediated signaling networks, which warrants further detailed analysis of the nodes of protein-protein interaction to uncover their biomarker or therapeutic potential.     

Effect of secondary structure on the potential of mean force for poly-L-lysine in the alpha-helix and beta-sheet conformations

Because poly-L-lysine (PLL) can exist in the alpha-helix or beta-sheet conformation depending on solution preparation and solution conditions, PLL is a suitable candidate to probe the dependence of protein interactions on secondary structure. The osmotic second virial coefficient and weight-average molecular weight are reported from low-angle laser-light scattering measurements for PLL as a function of NaCl concentration, pH, and alpha-helix or beta-sheet content. Interactions between PLL molecules become more attractive as salt concentration increases due to screening of PLL charge by salt ions and at low salt concentration become more attractive as pH increases due to decreased net charge on PLL. The experimental results show that interactions are stronger for the beta-sheet conformation than for the alpha-helix conformation. A spherically-symmetric model for the potential of mean force is used to account for specific interactions not described by DLVO theory and to show how differences in secondary structure affect PLL interactions.     

Cell penetrating peptides to dissect host-pathogen protein-protein interactions in Theileria-transformed leukocytes

One powerful application of cell penetrating peptides is the delivery into cells of molecules that function as specific competitors or inhibitors of protein-protein interactions. Ablating defined protein-protein interactions is a refined way to explore their contribution to a particular cellular phenotype in a given disease context. Cell-penetrating peptides can be synthetically constrained through various chemical modifications that stabilize a given structural fold with the potential to improve competitive binding to specific targets. Theileria-transformed leukocytes display high PKA activity, but PKA is an enzyme that plays key roles in multiple cellular processes; consequently genetic ablation of kinase activity gives rise to a myriad of confounding phenotypes. By contrast, ablation of a specific kinase-substrate interaction has the potential to give more refined information and we illustrate this here by describing how surgically ablating PKA interactions with BAD gives precise information on the type of glycolysis performed by Theileria-transformed leukocytes. In addition, we provide two other examples of how ablating specific protein-protein interactions in Theileria-infected leukocytes leads to precise phenotypes and argue that constrained penetrating peptides have great therapeutic potential to combat infectious diseases in general.     

Interactions of Ras proteins with the plasma membrane and their roles in signaling

The complex dynamic structure of the plasma membrane plays critical roles in cellular signaling; interactions with the membrane lipid milieu, spatial segregation within and between cellular membranes and/or targeting to specific membrane-associated scaffolds are intimately involved in many signal transduction pathways. In this review, we focus on the membrane interactions of Ras proteins. These small GTPases play central roles in the regulation of cell growth and proliferation, and their excessive activation is commonly encountered in human tumors. Ras proteins associate with the membrane continuously via C-terminal lipidation and additional interactions in both their inactive and active forms; this association, as well as the targeting of specific Ras isoforms to plasma membrane microdomains and to intracellular organelles, have recently been implicated in Ras signaling and oncogenic potential. We discuss biochemical and biophysical evidence for the roles of specific domains of Ras proteins in mediating their association with the plasma membrane, and consider the potential effects of lateral segregation and interactions with membrane-associated protein assemblies on the signaling outcomes.     

Identifying responsive functional modules from protein-protein interaction network

Proteins interact with each other within a cell, and those interactions give rise to the biological function and dynamical behavior of cellular systems. Generally, the protein interactions are temporal, spatial, or condition dependent in a specific cell, where only a small part of interactions usually take place under certain conditions. Recently, although a large amount of protein interaction data have been collected by high-throughput technologies, the interactions are recorded or summarized under various or different conditions and therefore cannot be directly used to identify signaling pathways or active networks, which are believed to work in specific cells under specific conditions. However, protein interactions activated under specific conditions may give hints to the biological process underlying corresponding phenotypes. In particular, responsive functional modules consist of protein interactions activated under specific conditions can provide insight into the mechanism underlying biological systems, e.g. protein interaction subnetworks found for certain diseases rather than normal conditions may help to discover potential biomarkers. From computational viewpoint, identifying responsive functional modules can be formulated as an optimization problem. Therefore, efficient computational methods for extracting responsive functional modules are strongly demanded due to the NP-hard nature of such a combinatorial problem. In this review, we first report recent advances in development of computational methods for extracting responsive functional modules or active pathways from protein interaction network and microarray data. Then from computational aspect, we discuss remaining obstacles and perspectives for this attractive and challenging topic in the area of systems biology.     

Integrating Structure to Protein-Protein Interaction Networks That Drive Metastasis to Brain and Lung in Breast Cancer

Blocking specific protein interactions can lead to human diseases. Accordingly, protein interactions and the structural knowledge on interacting surfaces of proteins (interfaces) have an important role in predicting the genotype-phenotype relationship. We have built the phenotype specific sub-networks of protein-protein interactions (PPIs) involving the relevant genes responsible for lung and brain metastasis from primary tumor in breast cancer. First, we selected the PPIs most relevant to metastasis causing genes (seed genes), by using the “guilt-by-association” principle. Then, we modeled structures of the interactions whose complex forms are not available in Protein Databank (PDB). Finally, we mapped mutations to interface structures (real and modeled), in order to spot the interactions that might be manipulated by these mutations. Functional analyses performed on these sub-networks revealed the potential relationship between immune system-infectious diseases and lung metastasis progression, but this connection was not observed significantly in the brain metastasis. Besides, structural analyses showed that some PPI interfaces in both metastasis sub-networks are originating from microbial proteins, which in turn were mostly related with cell adhesion. Cell adhesion is a key mechanism in metastasis, therefore these PPIs may be involved in similar molecular pathways that are shared by infectious disease and metastasis. Finally, by mapping the mutations and amino acid variations on the interface regions of the proteins in the metastasis sub-networks we found evidence for some mutations to be involved in the mechanisms differentiating the type of the metastasis.     

SRC Homology 2 Domain Binding Sites in Insulin, IGF-1 and FGF receptor mediated signaling networks reveal an extensive potential interactome

ABSTRACT: Specific peptide ligand recognition by modular interaction domains is essential for the fidelity of information flow through the signal transduction networks that control cell behavior in response to extrinsic and intrinsic stimuli. Src homology 2 (SH2) domains recognize distinct phosphotyrosine peptide motifs, but the specific sites that are phosphorylated and the complement of available SH2 domains varies considerably in individual cell types. Such differences are the basis for a wide range of available protein interaction microstates from which signaling can evolve in highly divergent ways. This underlying complexity suggests the need to broadly map the signaling potential of systems as a prerequisite for understanding signaling in specific cell types as well as various pathologies that involve signal transduction such as cancer, developmental defects and metabolic disorders. This report describes interactions between SH2 domains and potential binding partners that comprise initial signaling downstream of activated fibroblast growth factor (FGF), insulin (Ins), and insulin-like growth factor-1 (IGF-1) receptors. A panel of 50 SH2 domains screened against a set of 192 phosphotyrosine peptides defines an extensive potential interactome while demonstrating the selectivity of individual SH2 domains. The interactions described confirm virtually all previously reported associations while describing a large set of potential novel interactions that imply additional complexity in the signaling networks initiated from activated receptors. This study of pTyr ligand binding by SH2 domains provides valuable insight into the selectivity that underpins complex signaling networks that are assembled using modular protein interaction domains.     

Building protein interaction maps for Down's syndrome.

Now that the complete sequences for human chromosome 21 and the orthologous mouse genomic regions are known, reasonably complete, conserved, protein-coding gene catalogues are also available. The central issue now facing Down's syndrome researchers is the correlation of increased expression of specific, normal, chromosome 21 genes with the development of specific deficits in learning and memory. Because of the number of candidate genes involved, the number of alternative splice variants of individual genes and the number of pathways in which these genes function, a pathway analysis approach will be critical to success. Here, three examples, both gene specific and pathway related, that would benefit from pathway analysis are discussed: (1) the potential roles of eight chromosome 21 proteins in RNA processing pathways; (2) the chromosome 21 protein intersectin 1 and its domain composition, alternative splicing, protein interactions and functions; and (3) the interactions of ten chromosome 21 proteins with components of the mitogen-activated protein kinase and the calcineurin signalling pathways. A productive approach to developing gene-phenotype correlations in Down's syndrome will make use of known and predicted functions and interactions of chromosome 21 genes to predict pathways that may be perturbed by their increased levels of expression. Investigations may then be targeted in animal models to specific interactions, intermediate steps or end-points of such pathways and the downstream - perhaps amplified - consequences of gene dosage directly assessed. Once pathway perturbations have been identified, the potential for rational design of therapeutics becomes practical.     

Temperature-specific outcomes of cytoplasmic-nuclear interactions on egg-to-adult development time in seed beetles

The integration of the mitochondrial and nuclear genomes coordinates cellular energy production and is fundamental to life among eukaryotes. Therefore, there is potential for strong selection to shape the interactions between the two genomes. Several studies have now demonstrated that epistatic interactions between cytoplasmic and nuclear genes for fitness can occur both at a "within" and "across" population level. Genotype-by-environment interactions are common for traits that are encoded by nuclear genes, but the effects of environmental heterogeneity on traits that are partly encoded by cytoplasmic genes have received little attention despite the fact that there are reasons to believe that phenotypic effects of cytoplasmic genetic variation may often be environment specific. Consequently, the importance of environmental heterogeneity to the outcomes of cyto-nuclear fitness interactions and to the maintenance of mitochondrial polymorphism is unclear. Here, we assess the influence of temperature on cyto-nuclear effects on egg-to-adult development time in seed beetles (Callosobruchus maculatus). We employed an "across-population" design, sourcing beetles from five distinct populations and using backcrossing to create orthogonal combinations of distinct introgression lines, fixed for their cytoplasmic and nuclear lineages. We then assayed development times at two different temperatures and found sizeable cyto-nuclear effects in general, as well as temperature- and block-specific cyto-nuclear effects. These results demonstrate that environmental factors such as temperature do exert selection on cytoplasmic genes by favoring specific cyto-nuclear genetic combinations, and are consistent with the suggestion that complex genotype-by-environment interactions may promote the maintenance of polymorphism in mitochondrial genes.     

THE POTENTIAL FOR COEVOLUTION IN A HOST-PARASITOID SYSTEM. II. GENETIC VARIATION WITHIN A POPULATION OF WASPS IN THE ABILITY TO PARASITIZE AN APHID HOST

Much of the study of coevolution has focused on the adaptations that have resulted from interactions between species. For reciprocal evolution to occur, there must be genetic variation in each species for traits that directly affect their interaction. Here I report evidence of significant additive genetic variance within a population of parasitic wasps in the ability to successfully parasitize an aphid host. These data, combined with companion work documenting clonal variation in a population of aphids from the same site, provide evidence that within the same population both a host and its parasitoid have the potential for specific and reciprocal genetic interactions.     

A generalized weighted quantile sum approach for analyzing correlated data in the presence of interactions

A weighted quantile sum (WQS) regression has been used to assess the associations between environmental exposures and health outcomes. However, the currently available WQS approach, which is based on additive effects, does not allow exploring for potential interactions of exposures with other covariates in relation to a health outcome. In addition, the current WQS cannot account for clustering, thus it may not be valid for analysis of clustered data. We propose a generalized WQS approach that can assess interactions by estimating stratum‐specific weights of exposures in a mixture, while accounting for potential clustering effect of matched pairs of cases and controls as well as censored exposure data due to being below the limits of detection. The performance of the proposed method in identifying interactions is evaluated through simulations based on various scenarios of correlation structures among the exposures and with an outcome. We also assess how well the proposed method performs in the presence of the varying levels of censoring in exposures. Our findings from the simulation study show that the proposed method outperforms the traditional WQS, as indicated by higher power of detecting interactions. We also find no strong evidence that the proposed method falsely identifies interactions when there are no true interactive effects. We demonstrate application of the proposed method to real data from the Epidemiological Research on Autism Spectrum Disorder (ASD) in Jamaica (ERAJ) by examining interactions between exposure to manganese and glutathione S‐transferase family gene, GSTP1 in relation to ASD.     

Exudate molecules initiating fungal responses to seeds and roots

Plant pathogenic fungi survive in soils in a quiescent state. In order for many root-pathogen interactions to be initiated, dormant propagules must be activated by molecules present in seed and root exudates. Without the release of such stimulatory molecules, the majority of root infections do not occur. Currently, little is known about the specific molecules involved in stimulating propagule germination and initiating root-pathogen interactions. Although certain molecules can be shown to elicit germination responses in vitro, responses of propagules reared on conventional culture media do not always reflect the responses of those formed on plant tissues in soil. Consequently, it is not possible to extend conclusions from laboratory determinations of the role of specific exudate molecules in stimulating fungal propagule germination to soil systems. The interaction of Pythium species with germinating seeds has served as a model system to answer questions about propagule behavior and the role of exudate stimulant molecules in establishing root-fungus interactions. The potential role of both volatile and water-soluble molecules in stimulating propagule germination are discussed.     

A Simple Method for Discovering Druggable,Specific Glycosaminoglycan-Protein Systems. Elucidation of Key Principles from Heparin/Heparan Sulfate-Binding Proteins

Glycosaminoglycans (GAGs) affect human physiology and pathology by modulating more than 500 proteins. GAG-protein interactions are generally assumed to be ionic and nonspecific, but specific interactions do exist. Here, we present a simple method to identify the GAG-binding site (GBS) on proteins that in turn helps predict high specific GAG–protein systems. Contrary to contemporary thinking, we found that the electrostatic potential at basic arginine and lysine residues neither identifies the GBS consistently, nor its specificity. GBSs are better identified by considering the potential at neutral hydrogen bond donors such as asparagine or glutamine sidechains. Our studies also reveal that an unusual constellation of ionic and non-ionic residues in the binding site leads to specificity. Nature engineers the local environment of Asn45 of antithrombin, Gln255 of 3-O-sulfotransferase 3, Gln163 and Asn167 of 3-O-sulfotransferase 1 and Asn27 of basic fibroblast growth factor in the respective GBSs to induce specificity. Such residues are distinct from other uncharged residues on the same protein structure in possessing a significantly higher electrostatic potential, resultant from the local topology. In contrast, uncharged residues on nonspecific GBSs such as thrombin and serum albumin possess a diffuse spread of electrostatic potential. Our findings also contradict the paradigm that GAG-binding sites are simply a collection of contiguous Arg/Lys residues. Our work demonstrates the basis for discovering specifically interacting and druggable GAG-protein systems based on the structure of protein alone, without requiring access to any structure-function relationship data.     

A computerized protein–protein interaction modeling study of ampicillin antibody specificity in relation to biosensor development

Nonspecific interactions between immobilized biomolecules and interfering proteins significantly impede biosensor development and commercialization. Advances in bioinformatics and computer technology have facilitated a greater understanding of biological interactions. We employed two different protein–protein docking programs to simulate the nonspecific interaction between ampicillin antibody and potential interfering proteins (human serum albumin and ovalbumin). To evaluate the contact and probability of association with the active site of the antibody, different amino acid chains from human serum albumin (HSA) and ovalbumin (OVA) were modeled in the simulation. In addition, a well-known specific immune complex, lysozyme and lysozyme antibody, was simulated for comparison. The results demonstrated that the cluster density of nonspecific interactions was smaller than the specific interaction between lysozyme and antibody, and that the dock scores were scattered. However, the active site of ampicillin antibody was prone to nonspecific protein interactions. The strength of interaction was different for specific binding and nonspecific binding. These results provide a platform for detecting the probability of nonspecific interactions and for improving methods of biosensor detection construction with reduced nonspecific adsorption.     

Modelling the effects of climate change on the distribution and production of marine fishes: accounting for trophic interactions in a dynamic bioclimate envelope model

Climate change has already altered the distribution of marine fishes. Future predictions of fish distributions and catches based on bioclimate envelope models are available, but to date they have not considered interspecific interactions. We address this by combining the species‐based Dynamic Bioclimate Envelope Model (DBEM) with a size‐based trophic model. The new approach provides spatially and temporally resolved predictions of changes in species' size, abundance and catch potential that account for the effects of ecological interactions. Predicted latitudinal shifts are, on average, reduced by 20% when species interactions are incorporated, compared to DBEM predictions, with pelagic species showing the greatest reductions. Goodness‐of‐fit of biomass data from fish stock assessments in the North Atlantic between 1991 and 2003 is improved slightly by including species interactions. The differences between predictions from the two models may be relatively modest because, at the North Atlantic basin scale, (i) predators and competitors may respond to climate change together; (ii) existing parameterization of the DBEM might implicitly incorporate trophic interactions; and/or (iii) trophic interactions might not be the main driver of responses to climate. Future analyses using ecologically explicit models and data will improve understanding of the effects of inter‐specific interactions on responses to climate change, and better inform managers about plausible ecological and fishery consequences of a changing environment.     

Drosophila fushi tarazu. a gene on the border of homeotic function

BACKGROUND: Hox genes specify cell fate and regional identity during animal development. These genes are present in evolutionarily conserved clusters thought to have arisen by gene duplication and divergence. Most members of the Drosophila Hox complex (HOM-C) have homeotic functions. However, a small number of HOM-C genes, such as the segmentation gene fushi tarazu (ftz), have nonhomeotic functions. If these genes arose from a homeotic ancestor, their functional properties must have changed significantly during the evolution of modern Drosophila. RESULTS: Here, we have asked how Drosophila ftz evolved from an ancestral homeotic gene to obtain a novel function in segmentation. We expressed Ftz proteins at various developmental stages to assess their potential to regulate segmentation and to generate homeotic transformations. Drosophila Ftz protein has lost the inherent ability to mediate homeosis and functions exclusively in segmentation pathways. In contrast, Ftz from the primitive insect Tribolium (Tc-Ftz) has retained homeotic potential, generating homeotic transformations in larvae and adults and retaining the ability to repress homothorax, a hallmark of homeotic genes. Similarly, Schistocerca Ftz (Sg-Ftz) caused homeotic transformations of antenna toward leg. Primitive Ftz orthologs have moderate segmentation potential, reflected by weak interactions with the segmentation-specific cofactor Ftz-F1. Thus, Ftz orthologs represent evolutionary intermediates that have weak segmentation potential but retain the ability to act as homeotic genes. CONCLUSIONS: ftz evolved from an ancestral homeotic gene as a result of changes in both regulation of expression and specific alterations in the protein-coding region. Studies of ftz orthologs from primitive insects have provided a "snap-shot" view of the progressive evolution of a Hox protein as it took on segmentation function and lost homeotic potential. We propose that the specialization of Drosophila Ftz for segmentation resulted from loss and gain of specific domains that mediate interactions with distinct cofactors.     

Host-pathogen interactions: a proteomic view

Host-pathogen interactions reflect the balance of host defenses and pathogen virulence mechanisms. Advances in proteomic technologies now afford opportunities to compare protein content between complex biologic systems ranging from cells to animals and clinical samples. Thus, it is now possible to characterize host-pathogen interactions from a global proteomic view. Most reports to date focus on cataloging protein content of pathogens and identifying virulence-associated proteins or proteomic alterations in host response. A more in-depth understanding of host-pathogen interactions has the potential to improve our mechanistic understanding of pathogenicity and virulence, thereby defining novel therapeutic and vaccine targets. In addition, proteomic characterization of the host response can provide pathogen-specific host biomarkers for rapid pathogen detection and characterization, as well as for early and specific detection of infectious diseases. A review of host-pathogen interactions focusing on proteomic analyses of both pathogen and host will be presented. Relevant genomic studies and host model systems will be also be discussed.