A rapid and accurate approach for prediction of interactomes from co-elution data (PrInCE).

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Stacey, R Greg; Skinnider, Michael A; Scott, Nichollas E; Foster, Leonard J

2017-10-23

-to-use data analysis pipeline that predicts interactomes and protein complexes from co-elution data. PrInCE allows researchers without bioinformatics expertise to analyze high-throughput co-elution datasets.

Characterization and interactome study of white spot syndrome virus envelope protein VP11.

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Wang-Jing Liu

Full Text Available White spot syndrome virus (WSSV is a large enveloped virus. The WSSV viral particle consists of three structural layers that surround its core DNA: an outer envelope, a tegument and a nucleocapsid. Here we characterize the WSSV structural protein VP11 (WSSV394, GenBank accession number AF440570, and use an interactome approach to analyze the possible associations between this protein and an array of other WSSV and host proteins. Temporal transcription analysis showed that vp11 is an early gene. Western blot hybridization of the intact viral particles and fractionation of the viral components, and immunoelectron microscopy showed that VP11 is an envelope protein. Membrane topology software predicted VP11 to be a type of transmembrane protein with a highly hydrophobic transmembrane domain at its N-terminal. Based on an immunofluorescence assay performed on VP11-transfected Sf9 cells and a trypsin digestion analysis of the virion, we conclude that, contrary to topology software prediction, the C-terminal of this protein is in fact inside the virion. Yeast two-hybrid screening combined with co-immunoprecipitation assays found that VP11 directly interacted with at least 12 other WSSV structural proteins as well as itself. An oligomerization assay further showed that VP11 could form dimers. VP11 is also the first reported WSSV structural protein to interact with the major nucleocapsid protein VP664.

Organization of physical interactomes as uncovered by network schemas.

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Banks, Eric; Nabieva, Elena; Chazelle, Bernard; Singh, Mona

2008-10-01

Large-scale protein-protein interaction networks provide new opportunities for understanding cellular organization and functioning. We introduce network schemas to elucidate shared mechanisms within interactomes. Network schemas specify descriptions of proteins and the topology of interactions among them. We develop algorithms for systematically uncovering recurring, over-represented schemas in physical interaction networks. We apply our methods to the S. cerevisiae interactome, focusing on schemas consisting of proteins described via sequence motifs and molecular function annotations and interacting with one another in one of four basic network topologies. We identify hundreds of recurring and over-represented network schemas of various complexity, and demonstrate via graph-theoretic representations how more complex schemas are organized in terms of their lower-order constituents. The uncovered schemas span a wide range of cellular activities, with many signaling and transport related higher-order schemas. We establish the functional importance of the schemas by showing that they correspond to functionally cohesive sets of proteins, are enriched in the frequency with which they have instances in the H. sapiens interactome, and are useful for predicting protein function. Our findings suggest that network schemas are a powerful paradigm for organizing, interrogating, and annotating cellular networks.

Searching for cellular partners of hantaviral nonstructural protein NSs: Y2H screening of mouse cDNA library and analysis of cellular interactome.

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Rönnberg, Tuomas; Jääskeläinen, Kirsi; Blot, Guillaume; Parviainen, Ville; Vaheri, Antti; Renkonen, Risto; Bouloy, Michele; Plyusnin, Alexander

2012-01-01

Hantaviruses (Bunyaviridae) are negative-strand RNA viruses with a tripartite genome. The small (S) segment encodes the nucleocapsid protein and, in some hantaviruses, also the nonstructural protein (NSs). The aim of this study was to find potential cellular partners for the hantaviral NSs protein. Toward this aim, yeast two-hybrid (Y2H) screening of mouse cDNA library was performed followed by a search for potential NSs protein counterparts via analyzing a cellular interactome. The resulting interaction network was shown to form logical, clustered structures. Furthermore, several potential binding partners for the NSs protein, for instance ACBD3, were identified and, to prove the principle, interaction between NSs and ACBD3 proteins was demonstrated biochemically.

Integration of multiple biological features yields high confidence human protein interactome.

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Karagoz, Kubra; Sevimoglu, Tuba; Arga, Kazim Yalcin

2016-08-21

The biological function of a protein is usually determined by its physical interaction with other proteins. Protein-protein interactions (PPIs) are identified through various experimental methods and are stored in curated databases. The noisiness of the existing PPI data is evident, and it is essential that a more reliable data is generated. Furthermore, the selection of a set of PPIs at different confidence levels might be necessary for many studies. Although different methodologies were introduced to evaluate the confidence scores for binary interactions, a highly reliable, almost complete PPI network of Homo sapiens is not proposed yet. The quality and coverage of human protein interactome need to be improved to be used in various disciplines, especially in biomedicine. In the present work, we propose an unsupervised statistical approach to assign confidence scores to PPIs of H. sapiens. To achieve this goal PPI data from six different databases were collected and a total of 295,288 non-redundant interactions between 15,950 proteins were acquired. The present scoring system included the context information that was assigned to PPIs derived from eight biological attributes. A high confidence network, which included 147,923 binary interactions between 13,213 proteins, had scores greater than the cutoff value of 0.80, for which sensitivity, specificity, and coverage were 94.5%, 80.9%, and 82.8%, respectively. We compared the present scoring method with others for evaluation. Reducing the noise inherent in experimental PPIs via our scoring scheme increased the accuracy significantly. As it was demonstrated through the assessment of process and cancer subnetworks, this study allows researchers to construct and analyze context-specific networks via valid PPI sets and one can easily achieve subnetworks around proteins of interest at a specified confidence level. Copyright © 2016 Elsevier Ltd. All rights reserved.

Systematic differences in signal emitting and receiving revealed by PageRank analysis of a human protein interactome.

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Donglei Du

Full Text Available Most protein PageRank studies do not use signal flow direction information in protein interactions because this information was not readily available in large protein databases until recently. Therefore, four questions have yet to be answered: A What is the general difference between signal emitting and receiving in a protein interactome? B Which proteins are among the top ranked in directional ranking? C Are high ranked proteins more evolutionarily conserved than low ranked ones? D Do proteins with similar ranking tend to have similar subcellular locations? In this study, we address these questions using the forward, reverse, and non-directional PageRank approaches to rank an information-directional network of human proteins and study their evolutionary conservation. The forward ranking gives credit to information receivers, reverse ranking to information emitters, and non-directional ranking mainly to the number of interactions. The protein lists generated by the forward and non-directional rankings are highly correlated, but those by the reverse and non-directional rankings are not. The results suggest that the signal emitting/receiving system is characterized by key-emittings and relatively even receivings in the human protein interactome. Signaling pathway proteins are frequent in top ranked ones. Eight proteins are both informational top emitters and top receivers. Top ranked proteins, except a few species-related novel-function ones, are evolutionarily well conserved. Protein-subunit ranking position reflects subunit function. These results demonstrate the usefulness of different PageRank approaches in characterizing protein networks and provide insights to protein interaction in the cell.

Systematic differences in signal emitting and receiving revealed by PageRank analysis of a human protein interactome.

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Du, Donglei; Lee, Connie F; Li, Xiu-Qing

2012-01-01

Most protein PageRank studies do not use signal flow direction information in protein interactions because this information was not readily available in large protein databases until recently. Therefore, four questions have yet to be answered: A) What is the general difference between signal emitting and receiving in a protein interactome? B) Which proteins are among the top ranked in directional ranking? C) Are high ranked proteins more evolutionarily conserved than low ranked ones? D) Do proteins with similar ranking tend to have similar subcellular locations? In this study, we address these questions using the forward, reverse, and non-directional PageRank approaches to rank an information-directional network of human proteins and study their evolutionary conservation. The forward ranking gives credit to information receivers, reverse ranking to information emitters, and non-directional ranking mainly to the number of interactions. The protein lists generated by the forward and non-directional rankings are highly correlated, but those by the reverse and non-directional rankings are not. The results suggest that the signal emitting/receiving system is characterized by key-emittings and relatively even receivings in the human protein interactome. Signaling pathway proteins are frequent in top ranked ones. Eight proteins are both informational top emitters and top receivers. Top ranked proteins, except a few species-related novel-function ones, are evolutionarily well conserved. Protein-subunit ranking position reflects subunit function. These results demonstrate the usefulness of different PageRank approaches in characterizing protein networks and provide insights to protein interaction in the cell.

Construction and application of a protein and genetic interaction network (yeast interactome).

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Stuart, Gregory R; Copeland, William C; Strand, Micheline K

2009-04-01

Cytoscape is a bioinformatic data analysis and visualization platform that is well-suited to the analysis of gene expression data. To facilitate the analysis of yeast microarray data using Cytoscape, we constructed an interaction network (interactome) using the curated interaction data available from the Saccharomyces Genome Database (www.yeastgenome.org) and the database of yeast transcription factors at YEASTRACT (www.yeastract.com). These data were formatted and imported into Cytoscape using semi-automated methods, including Linux-based scripts, that simplified the process while minimizing the introduction of processing errors. The methods described for the construction of this yeast interactome are generally applicable to the construction of any interactome. Using Cytoscape, we illustrate the use of this interactome through the analysis of expression data from a recent yeast diauxic shift experiment. We also report and briefly describe the complex associations among transcription factors that result in the regulation of thousands of genes through coordinated changes in expression of dozens of transcription factors. These cells are thus able to sensitively regulate cellular metabolism in response to changes in genetic or environmental conditions through relatively small changes in the expression of large numbers of genes, affecting the entire yeast metabolome.

A comprehensive protein-protein interactome for yeast PAS kinase 1 reveals direct inhibition of respiration through the phosphorylation of Cbf1.

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DeMille, Desiree; Bikman, Benjamin T; Mathis, Andrew D; Prince, John T; Mackay, Jordan T; Sowa, Steven W; Hall, Tacie D; Grose, Julianne H

2014-07-15

Per-Arnt-Sim (PAS) kinase is a sensory protein kinase required for glucose homeostasis in yeast, mice, and humans, yet little is known about the molecular mechanisms of its function. Using both yeast two-hybrid and copurification approaches, we identified the protein-protein interactome for yeast PAS kinase 1 (Psk1), revealing 93 novel putative protein binding partners. Several of the Psk1 binding partners expand the role of PAS kinase in glucose homeostasis, including new pathways involved in mitochondrial metabolism. In addition, the interactome suggests novel roles for PAS kinase in cell growth (gene/protein expression, replication/cell division, and protein modification and degradation), vacuole function, and stress tolerance. In vitro kinase studies using a subset of 25 of these binding partners identified Mot3, Zds1, Utr1, and Cbf1 as substrates. Further evidence is provided for the in vivo phosphorylation of Cbf1 at T211/T212 and for the subsequent inhibition of respiration. This respiratory role of PAS kinase is consistent with the reported hypermetabolism of PAS kinase-deficient mice, identifying a possible molecular mechanism and solidifying the evolutionary importance of PAS kinase in the regulation of glucose homeostasis. © 2014 DeMille et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Mapping the Small Molecule Interactome by Mass Spectrometry.

Science.gov (United States)

Flaxman, Hope A; Woo, Christina M

2018-01-16

Mapping small molecule interactions throughout the proteome provides the critical structural basis for functional analysis of their impact on biochemistry. However, translation of mass spectrometry-based proteomics methods to directly profile the interaction between a small molecule and the whole proteome is challenging because of the substoichiometric nature of many interactions, the diversity of covalent and noncovalent interactions involved, and the subsequent computational complexity associated with their spectral assignment. Recent advances in chemical proteomics have begun fill this gap to provide a structural basis for the breadth of small molecule-protein interactions in the whole proteome. Innovations enabling direct characterization of the small molecule interactome include faster, more sensitive instrumentation coupled to chemical conjugation, enrichment, and labeling methods that facilitate detection and assignment. These methods have started to measure molecular interaction hotspots due to inherent differences in local amino acid reactivity and binding affinity throughout the proteome. Measurement of the small molecule interactome is producing structural insights and methods for probing and engineering protein biochemistry. Direct structural characterization of the small molecule interactome is a rapidly emerging area pushing new frontiers in biochemistry at the interface of small molecules and the proteome.

Serial interactome capture of the human cell nucleus.

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Conrad, Thomas; Albrecht, Anne-Susann; de Melo Costa, Veronica Rodrigues; Sauer, Sascha; Meierhofer, David; Ørom, Ulf Andersson

2016-04-04

Novel RNA-guided cellular functions are paralleled by an increasing number of RNA-binding proteins (RBPs). Here we present 'serial RNA interactome capture' (serIC), a multiple purification procedure of ultraviolet-crosslinked poly(A)-RNA-protein complexes that enables global RBP detection with high specificity. We apply serIC to the nuclei of proliferating K562 cells to obtain the first human nuclear RNA interactome. The domain composition of the 382 identified nuclear RBPs markedly differs from previous IC experiments, including few factors without known RNA-binding domains that are in good agreement with computationally predicted RNA binding. serIC extends the number of DNA-RNA-binding proteins (DRBPs), and reveals a network of RBPs involved in p53 signalling and double-strand break repair. serIC is an effective tool to couple global RBP capture with additional selection or labelling steps for specific detection of highly purified RBPs.

Mapping the Interactome of a Major Mammalian Endoplasmic Reticulum Heat Shock Protein 90.

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Feng Hong

Full Text Available Up to 10% of cytosolic proteins are dependent on the mammalian heat shock protein 90 (HSP90 for folding. However, the interactors of its endoplasmic reticulum (ER paralogue (gp96, Grp94 and HSP90b1 has not been systematically identified. By combining genetic and biochemical approaches, we have comprehensively mapped the interactome of gp96 in macrophages and B cells. A total of 511 proteins were reduced in gp96 knockdown cells, compared to levels observed in wild type cells. By immunoprecipitation, we found that 201 proteins associated with gp96. Gene Ontology analysis indicated that these proteins are involved in metabolism, transport, translation, protein folding, development, localization, response to stress and cellular component biogenesis. While known gp96 clients such as integrins, Toll-like receptors (TLRs and Wnt co-receptor LRP6, were confirmed, cell surface HSP receptor CD91, TLR4 pathway protein CD180, WDR1, GANAB and CAPZB were identified as potentially novel substrates of gp96. Taken together, our study establishes gp96 as a critical chaperone to integrate innate immunity, Wnt signaling and organ development.

Functional interactome of Aquaporin 1 sub-family reveals new physiological functions in Arabidopsis Thaliana

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Mohamed Ragab Abdel Gawwad

2013-09-01

Full Text Available Aquaporins are channel proteins found in plasma membranes and intercellular membranes of different cellular compartments, facilitate the water flux, solutes and gases across the cellular plasma membranes. The present study highlights the sub-family plasma membrane intrinsic protein (PIP predicting the 3-D structure and analyzing the functional interactome of it homologs. PIP1 homologs integrate with many proteins with different plant physiological roles in Arabidopsis thaliana including; PIP1A and PIP1B: facilitate the transport of water, diffusion of amino acids and/or peptides from the vacuolar compartment to the cytoplasm, play a role in the control of cell turgor and cell expansion and involved in root water uptake respectively. In addition we found that PIP1B plays a defensive role against Pseudomonas syringae infection through the interaction with the plasma membrane Rps2 protein. Another substantial function of PIP1C via the interaction with PIP2E is the response to nematode infection. Generally, PIP1 sub-family interactome controlling many physiological processes in plant cell like; osmoregulation in plants under high osmotic stress such as under a high salt, response to nematode, facilitate the transport of water across cell membrane and regulation of floral initiation in Arabidopsis thaliana.

Identification of human disease genes from interactome network using graphlet interaction.

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Xiao-Dong Wang

Full Text Available Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes.

Identification of Human Disease Genes from Interactome Network Using Graphlet Interaction

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Yang, Lun; Wei, Dong-Qing; Qi, Ying-Xin; Jiang, Zong-Lai

2014-01-01

Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes. PMID:24465923

Sequence- and interactome-based prediction of viral protein hotspots targeting host proteins: a case study for HIV Nef.

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Mahdi Sarmady

Full Text Available Virus proteins alter protein pathways of the host toward the synthesis of viral particles by breaking and making edges via binding to host proteins. In this study, we developed a computational approach to predict viral sequence hotspots for binding to host proteins based on sequences of viral and host proteins and literature-curated virus-host protein interactome data. We use a motif discovery algorithm repeatedly on collections of sequences of viral proteins and immediate binding partners of their host targets and choose only those motifs that are conserved on viral sequences and highly statistically enriched among binding partners of virus protein targeted host proteins. Our results match experimental data on binding sites of Nef to host proteins such as MAPK1, VAV1, LCK, HCK, HLA-A, CD4, FYN, and GNB2L1 with high statistical significance but is a poor predictor of Nef binding sites on highly flexible, hoop-like regions. Predicted hotspots recapture CD8 cell epitopes of HIV Nef highlighting their importance in modulating virus-host interactions. Host proteins potentially targeted or outcompeted by Nef appear crowding the T cell receptor, natural killer cell mediated cytotoxicity, and neurotrophin signaling pathways. Scanning of HIV Nef motifs on multiple alignments of hepatitis C protein NS5A produces results consistent with literature, indicating the potential value of the hotspot discovery in advancing our understanding of virus-host crosstalk.

A "candidate-interactome" aggregate analysis of genome-wide association data in multiple sclerosis

DEFF Research Database (Denmark)

Mechelli, Rosella; Umeton, Renato; Policano, Claudia

2013-01-01

of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge......, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate...... immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated...

Cell Interactomics and Carcinogenetic Mechanisms

CERN Document Server

Baianu, IC; Report to the Institute of Genomics

2004-01-01

Single cell interactomics in simpler organisms, as well as somatic cell interactomics in multicellular organisms, involve biomolecular interactions in complex signalling pathways that were recently represented in modular terms by quantum automata with ‘reversible behavior’ representing normal cell cycling and division. Other implications of such quantum automata, modular modeling of signaling pathways and cell differentiation during development are in the fields of neural plasticity and brain development leading to quantum-weave dynamic patterns and specific molecular processes underlying extensive memory, learning, anticipation mechanisms and the emergence of human consciousness during the early brain development in children. Cell interactomics is here represented for the first time as a mixture of ‘classical’ states that determine molecular dynamics subject to Boltzmann statistics and ‘steady-state’, metabolic (multi-stable) manifolds, together with ‘configuration’ spaces of metastable quant...

Sequential Elution Interactome Analysis of the Mind Bomb 1 Ubiquitin Ligase Reveals a Novel Role in Dendritic Spine Outgrowth*

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Mertz, Joseph; Tan, Haiyan; Pagala, Vishwajeeth; Bai, Bing; Chen, Ping-Chung; Li, Yuxin; Cho, Ji-Hoon; Shaw, Timothy; Wang, Xusheng; Peng, Junmin

2015-01-01

The mind bomb 1 (Mib1) ubiquitin ligase is essential for controlling metazoan development by Notch signaling and possibly the Wnt pathway. It is also expressed in postmitotic neurons and regulates neuronal morphogenesis and synaptic activity by mechanisms that are largely unknown. We sought to comprehensively characterize the Mib1 interactome and study its potential function in neuron development utilizing a novel sequential elution strategy for affinity purification, in which Mib1 binding proteins were eluted under different stringency and then quantified by the isobaric labeling method. The strategy identified the Mib1 interactome with both deep coverage and the ability to distinguish high-affinity partners from low-affinity partners. A total of 817 proteins were identified during the Mib1 affinity purification, including 56 high-affinity partners and 335 low-affinity partners, whereas the remaining 426 proteins are likely copurified contaminants or extremely weak binding proteins. The analysis detected all previously known Mib1-interacting proteins and revealed a large number of novel components involved in Notch and Wnt pathways, endocytosis and vesicle transport, the ubiquitin-proteasome system, cellular morphogenesis, and synaptic activities. Immunofluorescence studies further showed colocalization of Mib1 with five selected proteins: the Usp9x (FAM) deubiquitinating enzyme, alpha-, beta-, and delta-catenins, and CDKL5. Mutations of CDKL5 are associated with early infantile epileptic encephalopathy-2 (EIEE2), a severe form of mental retardation. We found that the expression of Mib1 down-regulated the protein level of CDKL5 by ubiquitination, and antagonized CDKL5 function during the formation of dendritic spines. Thus, the sequential elution strategy enables biochemical characterization of protein interactomes; and Mib1 analysis provides a comprehensive interactome for investigating its role in signaling networks and neuronal development. PMID:25931508

Comprehensive Protein Interactome Analysis of a Key RNA Helicase: Detection of Novel Stress Granule Proteins

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Rebecca Bish

2015-07-01

Full Text Available DDX6 (p54/RCK is a human RNA helicase with central roles in mRNA decay and translation repression. To help our understanding of how DDX6 performs these multiple functions, we conducted the first unbiased, large-scale study to map the DDX6-centric protein-protein interactome using immunoprecipitation and mass spectrometry. Using DDX6 as bait, we identify a high-confidence and high-quality set of protein interaction partners which are enriched for functions in RNA metabolism and ribosomal proteins. The screen is highly specific, maximizing the number of true positives, as demonstrated by the validation of 81% (47/58 of the RNA-independent interactors through known functions and interactions. Importantly, we minimize the number of indirect interaction partners through use of a nuclease-based digestion to eliminate RNA. We describe eleven new interactors, including proteins involved in splicing which is an as-yet unknown role for DDX6. We validated and characterized in more detail the interaction of DDX6 with Nuclear fragile X mental retardation-interacting protein 2 (NUFIP2 and with two previously uncharacterized proteins, FAM195A and FAM195B (here referred to as granulin-1 and granulin-2, or GRAN1 and GRAN2. We show that NUFIP2, GRAN1, and GRAN2 are not P-body components, but re-localize to stress granules upon exposure to stress, suggesting a function in translation repression in the cellular stress response. Using a complementary analysis that resolved DDX6’s multiple complex memberships, we further validated these interaction partners and the presence of splicing factors. As DDX6 also interacts with the E3 SUMO ligase TIF1β, we tested for and observed a significant enrichment of sumoylation amongst DDX6’s interaction partners. Our results represent the most comprehensive screen for direct interaction partners of a key regulator of RNA life cycle and localization, highlighting new stress granule components and possible DDX6 functions�

Dissection of protein interactomics highlights microRNA synergy.

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Zhu, Wenliang; Zhao, Yilei; Xu, Yingqi; Sun, Yong; Wang, Zhe; Yuan, Wei; Du, Zhimin

2013-01-01

Despite a large amount of microRNAs (miRNAs) have been validated to play crucial roles in human biology and disease, there is little systematic insight into the nature and scale of the potential synergistic interactions executed by miRNAs themselves. Here we established an integrated parameter synergy score to determine miRNA synergy, by combining the two mechanisms for miRNA-miRNA interactions, miRNA-mediated gene co-regulation and functional association between target gene products, into one single parameter. Receiver operating characteristic (ROC) analysis indicated that synergy score accurately identified the gene ontology-defined miRNA synergy (AUC = 0.9415, psynergy, implying poor expectancy of widespread synergy. However, targeting more key genes made two miRNAs more likely to act synergistically. Compared to other miRNAs, miR-21 was a highly exceptional case due to frequent appearance in the top synergistic miRNA pairs. This result highlighted its essential role in coordinating or strengthening physiological and pathological functions of other miRNAs. The synergistic effect of miR-21 and miR-1 were functionally validated for their significant influences on myocardial apoptosis, cardiac hypertrophy and fibrosis. The novel approach established in this study enables easy and effective identification of condition-restricted potent miRNA synergy simply by concentrating the available protein interactomics and miRNA-target interaction data into a single parameter synergy score. Our results may be important for understanding synergistic gene regulation by miRNAs and may have significant implications for miRNA combination therapy of cardiovascular disease.

The chicken B-cell line DT40 proteome, beadome and interactomes

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Johanna S. Rees

2015-06-01

Full Text Available In developing a new quantitative AP-MS method for exploring interactomes in the chicken B-cell line DT40, we also surveyed the most abundant proteins in this organism and explored the likely contaminants that bind to a variety of affinity resins that would later be confirmed quantitatively [1]. We present the ‘Top 150 abundant DT40 proteins list’, the DT40 beadomes as well as protein interaction lists for the Phosphatidyl inositol 5-phosphate 4-kinase 2β and Fanconi anaemia protein complexes.

Investigation of PARP-1, PARP-2, and PARG interactomes by affinity-purification mass spectrometry

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Isabelle Maxim

2010-04-01

Full Text Available Abstract Background Poly(ADP-ribose polymerases (PARPs catalyze the formation of poly(ADP-ribose (pADPr, a post-translational modification involved in several important biological processes, namely surveillance of genome integrity, cell cycle progression, initiation of the DNA damage response, apoptosis, and regulation of transcription. Poly(ADP-ribose glycohydrolase (PARG, on the other hand, catabolizes pADPr and thereby accounts for the transient nature of poly(ADP-ribosylation. Our investigation of the interactomes of PARP-1, PARP-2, and PARG by affinity-purification mass spectrometry (AP-MS aimed, on the one hand, to confirm current knowledge on these interactomes and, on the other hand, to discover new protein partners which could offer insights into PARPs and PARG functions. Results PARP-1, PARP-2, and PARG were immunoprecipitated from human cells, and pulled-down proteins were separated by gel electrophoresis prior to in-gel trypsin digestion. Peptides were identified by tandem mass spectrometry. Our AP-MS experiments resulted in the identifications of 179 interactions, 139 of which are novel interactions. Gene Ontology analysis of the identified protein interactors points to five biological processes in which PARP-1, PARP-2 and PARG may be involved: RNA metabolism for PARP-1, PARP-2 and PARG; DNA repair and apoptosis for PARP-1 and PARP-2; and glycolysis and cell cycle for PARP-1. Conclusions This study reveals several novel protein partners for PARP-1, PARP-2 and PARG. It provides a global view of the interactomes of these proteins as well as a roadmap to establish the systems biology of poly(ADP-ribose metabolism.

Data management of protein interaction networks

CERN Document Server

Cannataro, Mario

2012-01-01

Interactomics: a complete survey from data generation to knowledge extraction With the increasing use of high-throughput experimental assays, more and more protein interaction databases are becoming available. As a result, computational analysis of protein-to-protein interaction (PPI) data and networks, now known as interactomics, has become an essential tool to determine functionally associated proteins. From wet lab technologies to data management to knowledge extraction, this timely book guides readers through the new science of interactomics, giving them the tools needed to: Generate

Characterization of the CLASP2 Protein Interaction Network Identifies SOGA1 as a Microtubule-Associated Protein

DEFF Research Database (Denmark)

Sørensen, Rikke Kruse; Krantz, James; Barker, Natalie

2017-01-01

. The GTPase-activating proteins AGAP1 and AGAP3 were also enriched in the CLASP2 interactome, although subsequent AGAP3 and CLIP2 interactome analysis suggests a preference of AGAP3 for CLIP2. Follow-up MARK2 interactome analysis confirmed reciprocal co-IP of CLASP2 and also revealed MARK2 can co-IP SOGA1......, glycogen synthase, and glycogenin. Investigating the SOGA1 interactome confirmed SOGA1 can reciprocal co-IP both CLASP2 and MARK2 as well as glycogen synthase and glycogenin. SOGA1 was confirmed to colocalize with CLASP2 and also with tubulin, which identifies SOGA1 as a new microtubule-associated protein....... These results introduce the metabolic function of these proposed novel protein networks and their relationship with microtubules as new fields of cytoskeleton-associated protein biology....

Deciphering peculiar protein-protein interacting modules in Deinococcus radiodurans

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Barkallah Insaf

2009-04-01

Full Text Available Abstract Interactomes of proteins under positive selection from ionizing-radiation-resistant bacteria (IRRB might be a part of the answer to the question as to how IRRB, particularly Deinococcus radiodurans R1 (Deira, resist ionizing radiation. Here, using the Database of Interacting Proteins (DIP and the Protein Structural Interactome (PSI-base server for PSI map, we have predicted novel interactions of orthologs of the 58 proteins under positive selection in Deira and other IRRB, but which are absent in IRSB. Among these, 18 domains and their interactomes have been identified in DNA checkpoint and repair; kinases pathways; energy and nucleotide metabolisms were the important biological processes that were found to be involved. This finding provides new clues to the cellular pathways that can to be important for ionizing-radiation resistance in Deira.

Serum Amyloid P Component (SAP) Interactome in Human Plasma Containing Physiological Calcium Levels.

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Poulsen, Ebbe Toftgaard; Pedersen, Kata Wolff; Marzeda, Anna Maria; Enghild, Jan J

2017-02-14

The pentraxin serum amyloid P component (SAP) is secreted by the liver and found in plasma at a concentration of approximately 30 mg/L. SAP is a 25 kDa homopentamer known to bind both protein and nonprotein ligands, all in a calcium-dependent manner. The function of SAP is unclear but likely involves the humoral innate immune system spanning the complement system, inflammation, and coagulation. Also, SAP is known to bind to the generic structure of amyloid deposits and possibly to protect them against proteolysis. In this study, we have characterized the SAP interactome in human plasma containing the physiological Ca 2+ concentration using SAP affinity pull-down and co-immunoprecipitation experiments followed by mass spectrometry analyses. The analyses resulted in the identification of 33 proteins, of which 24 were direct or indirect interaction partners not previously reported. The SAP interactome can be divided into categories that include apolipoproteins, the complement system, coagulation, and proteolytic regulation.

Embryonic stem cell interactomics: the beginning of a long road to biological function.

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Yousefi, Maram; Hajihoseini, Vahid; Jung, Woojin; Hosseinpour, Batol; Rassouli, Hassan; Lee, Bonghee; Baharvand, Hossein; Lee, KiYoung; Salekdeh, Ghasem Hosseini

2012-12-01

Embryonic stem cells (ESCs) are capable of unlimited self-renewal while maintaining pluripotency. They are of great interest in regenerative medicine due to their ability to differentiate into all cell types of the three embryonic germ layers. Recently, induced pluripotent stem cells (iPSCs) have shown similarities to ESCs and thus promise great therapeutic potential in regenerative medicine. Despite progress in stem cell biology, our understanding of the exact mechanisms by which pluripotency and self-renewal are established and maintained is largely unknown. A better understanding of these processes may lead to discovery of alternative ways for reprogramming, differentiation and more reliable applications of stem cells in therapies. It has become evident that proteins generally function as members of large complexes that are part of a more complex network. Therefore, the identification of protein-protein interactions (PPI) is an efficient strategy for understanding protein function and regulation. Systematic genome-wide and pathway-specific PPI analysis of ESCs has generated a network of ESC proteins, including major transcription factors. These PPI networks of ESCs may contribute to a mechanistic understanding of self-renewal and pluripotency. In this review we describe different experimental approaches for the identification of PPIs along with various databases. We discuss biological findings and technical challenges encountered with interactome studies of pluripotent stem cells, and provide insight into how interactomics is likely to develop.

The Interactomic Analysis Reveals Pathogenic Protein Networks in Phomopsis longicolla Underlying Seed Decay of Soybean

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Shuxian Li

2018-04-01

Full Text Available Phomopsis longicolla T. W. Hobbs (syn. Diaporthe longicolla is the primary cause of Phomopsis seed decay (PSD in soybean, Glycine max (L. Merrill. This disease results in poor seed quality and is one of the most economically important seed diseases in soybean. The objectives of this study were to infer protein–protein interactions (PPI and to identify conserved global networks and pathogenicity subnetworks in P. longicolla including orthologous pathways for cell signaling and pathogenesis. The interlog method used in the study identified 215,255 unique PPIs among 3,868 proteins. There were 1,414 pathogenicity related genes in P. longicolla identified using the pathogen host interaction (PHI database. Additionally, 149 plant cell wall degrading enzymes (PCWDE were detected. The network captured five different classes of carbohydrate degrading enzymes, including the auxiliary activities, carbohydrate esterases, glycoside hydrolases, glycosyl transferases, and carbohydrate binding molecules. From the PPI analysis, novel interacting partners were determined for each of the PCWDE classes. The most predominant class of PCWDE was a group of 60 glycoside hydrolases proteins. The glycoside hydrolase subnetwork was found to be interacting with 1,442 proteins within the network and was among the largest clusters. The orthologous proteins FUS3, HOG, CYP1, SGE1, and the g5566t.1 gene identified in this study could play an important role in pathogenicity. Therefore, the P. longicolla protein interactome (PiPhom generated in this study can lead to a better understanding of PPIs in soybean pathogens. Furthermore, the PPI may aid in targeting of genes and proteins for further studies of the pathogenicity mechanisms.

Creating and analyzing pathway and protein interaction compendia for modelling signal transduction networks

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Kirouac Daniel C

2012-05-01

Full Text Available Abstract Background Understanding the information-processing capabilities of signal transduction networks, how those networks are disrupted in disease, and rationally designing therapies to manipulate diseased states require systematic and accurate reconstruction of network topology. Data on networks central to human physiology, such as the inflammatory signalling networks analyzed here, are found in a multiplicity of on-line resources of pathway and interactome databases (Cancer CellMap, GeneGo, KEGG, NCI-Pathway Interactome Database (NCI-PID, PANTHER, Reactome, I2D, and STRING. We sought to determine whether these databases contain overlapping information and whether they can be used to construct high reliability prior knowledge networks for subsequent modeling of experimental data. Results We have assembled an ensemble network from multiple on-line sources representing a significant portion of all machine-readable and reconcilable human knowledge on proteins and protein interactions involved in inflammation. This ensemble network has many features expected of complex signalling networks assembled from high-throughput data: a power law distribution of both node degree and edge annotations, and topological features of a “bow tie” architecture in which diverse pathways converge on a highly conserved set of enzymatic cascades focused around PI3K/AKT, MAPK/ERK, JAK/STAT, NFκB, and apoptotic signaling. Individual pathways exhibit “fuzzy” modularity that is statistically significant but still involving a majority of “cross-talk” interactions. However, we find that the most widely used pathway databases are highly inconsistent with respect to the actual constituents and interactions in this network. Using a set of growth factor signalling networks as examples (epidermal growth factor, transforming growth factor-beta, tumor necrosis factor, and wingless, we find a multiplicity of network topologies in which receptors couple to downstream

RNA/DNA Hybrid Interactome Identifies DXH9 as a Molecular Player in Transcriptional Termination and R-Loop-Associated DNA Damage.

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Cristini, Agnese; Groh, Matthias; Kristiansen, Maiken S; Gromak, Natalia

2018-05-08

R-loops comprise an RNA/DNA hybrid and displaced single-stranded DNA. They play important biological roles and are implicated in pathology. Even so, proteins recognizing these structures are largely undefined. Using affinity purification with the S9.6 antibody coupled to mass spectrometry, we defined the RNA/DNA hybrid interactome in HeLa cells. This consists of known R-loop-associated factors SRSF1, FACT, and Top1, and yet uncharacterized interactors, including helicases, RNA processing, DNA repair, and chromatin factors. We validate specific examples of these interactors and characterize their involvement in R-loop biology. A top candidate DHX9 helicase promotes R-loop suppression and transcriptional termination. DHX9 interacts with PARP1, and both proteins prevent R-loop-associated DNA damage. DHX9 and other interactome helicases are overexpressed in cancer, linking R-loop-mediated DNA damage and disease. Our RNA/DNA hybrid interactome provides a powerful resource to study R-loop biology in health and disease. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Noise reduction in protein-protein interaction graphs by the implementation of a novel weighting scheme

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Moschopoulos Charalampos

2011-06-01

Full Text Available Abstract Background Recent technological advances applied to biology such as yeast-two-hybrid, phage display and mass spectrometry have enabled us to create a detailed map of protein interaction networks. These interaction networks represent a rich, yet noisy, source of data that could be used to extract meaningful information, such as protein complexes. Several interaction network weighting schemes have been proposed so far in the literature in order to eliminate the noise inherent in interactome data. In this paper, we propose a novel weighting scheme and apply it to the S. cerevisiae interactome. Complex prediction rates are improved by up to 39%, depending on the clustering algorithm applied. Results We adopt a two step procedure. During the first step, by applying both novel and well established protein-protein interaction (PPI weighting methods, weights are introduced to the original interactome graph based on the confidence level that a given interaction is a true-positive one. The second step applies clustering using established algorithms in the field of graph theory, as well as two variations of Spectral clustering. The clustered interactome networks are also cross-validated against the confirmed protein complexes present in the MIPS database. Conclusions The results of our experimental work demonstrate that interactome graph weighting methods clearly improve the clustering results of several clustering algorithms. Moreover, our proposed weighting scheme outperforms other approaches of PPI graph weighting.

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

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Annalisa Alfieri

2017-06-01

Full Text Available 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. Only a few p140Cap interacting proteins have been identified in the brain and the molecular complexes and pathways underlying p140Cap synaptic function are largely unknown. Here, we isolated and characterized the p140Cap synaptic interactome by co-immunoprecipitation from crude mouse synaptosomes, followed by mass spectrometry-based proteomics. We identified 351 p140Cap interactors and found that they cluster to sub complexes mostly located in the postsynaptic density (PSD. p140Cap interactors converge on key synaptic processes, including transmission across chemical synapses, actin cytoskeleton remodeling and cell-cell junction organization. Gene co-expression data further support convergent functions: the p140Cap interactors are tightly co-expressed with each other and with p140Cap. Importantly, the p140Cap interactome and its co-expression network show strong enrichment in genes associated with schizophrenia, autism, bipolar disorder, intellectual disability and epilepsy, supporting synaptic dysfunction as a shared biological feature in brain diseases. Overall, our data provide novel insights into the molecular organization of the synapse and indicate that p140Cap acts as a hub for postsynaptic complexes relevant to psychiatric and neurological disorders.

Expression of DISC1-interactome members correlates with cognitive phenotypes related to schizophrenia.

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Rampino, Antonio; Walker, Rosie May; Torrance, Helen Scott; Anderson, Susan Maguire; Fazio, Leonardo; Di Giorgio, Annabella; Taurisano, Paolo; Gelao, Barbara; Romano, Raffaella; Masellis, Rita; Ursini, Gianluca; Caforio, Grazia; Blasi, Giuseppe; Millar, J Kirsty; Porteous, David John; Thomson, Pippa Ann; Bertolino, Alessandro; Evans, Kathryn Louise

2014-01-01

Cognitive dysfunction is central to the schizophrenia phenotype. Genetic and functional studies have implicated Disrupted-in-Schizophrenia 1 (DISC1), a leading candidate gene for schizophrenia and related psychiatric conditions, in cognitive function. Altered expression of DISC1 and DISC1-interactors has been identified in schizophrenia. Dysregulated expression of DISC1-interactome genes might, therefore, contribute to schizophrenia susceptibility via disruption of molecular systems required for normal cognitive function. Here, the blood RNA expression levels of DISC1 and DISC1-interacting proteins were measured in 63 control subjects. Cognitive function was assessed using neuropsychiatric tests and functional magnetic resonance imaging was used to assess the activity of prefrontal cortical regions during the N-back working memory task, which is abnormal in schizophrenia. Pairwise correlations between gene expression levels and the relationship between gene expression levels and cognitive function and N-back-elicited brain activity were assessed. Finally, the expression levels of DISC1, AKAP9, FEZ1, NDEL1 and PCM1 were compared between 63 controls and 69 schizophrenic subjects. We found that DISC1-interactome genes showed correlated expression in the blood of healthy individuals. The expression levels of several interactome members were correlated with cognitive performance and N-back-elicited activity in the prefrontal cortex. In addition, DISC1 and NDEL1 showed decreased expression in schizophrenic subjects compared to healthy controls. Our findings highlight the importance of the coordinated expression of DISC1-interactome genes for normal cognitive function and suggest that dysregulated DISC1 and NDEL1 expression might, in part, contribute to susceptibility for schizophrenia via disruption of prefrontal cortex-dependent cognitive functions.

Expression of DISC1-interactome members correlates with cognitive phenotypes related to schizophrenia.

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Antonio Rampino

Full Text Available Cognitive dysfunction is central to the schizophrenia phenotype. Genetic and functional studies have implicated Disrupted-in-Schizophrenia 1 (DISC1, a leading candidate gene for schizophrenia and related psychiatric conditions, in cognitive function. Altered expression of DISC1 and DISC1-interactors has been identified in schizophrenia. Dysregulated expression of DISC1-interactome genes might, therefore, contribute to schizophrenia susceptibility via disruption of molecular systems required for normal cognitive function. Here, the blood RNA expression levels of DISC1 and DISC1-interacting proteins were measured in 63 control subjects. Cognitive function was assessed using neuropsychiatric tests and functional magnetic resonance imaging was used to assess the activity of prefrontal cortical regions during the N-back working memory task, which is abnormal in schizophrenia. Pairwise correlations between gene expression levels and the relationship between gene expression levels and cognitive function and N-back-elicited brain activity were assessed. Finally, the expression levels of DISC1, AKAP9, FEZ1, NDEL1 and PCM1 were compared between 63 controls and 69 schizophrenic subjects. We found that DISC1-interactome genes showed correlated expression in the blood of healthy individuals. The expression levels of several interactome members were correlated with cognitive performance and N-back-elicited activity in the prefrontal cortex. In addition, DISC1 and NDEL1 showed decreased expression in schizophrenic subjects compared to healthy controls. Our findings highlight the importance of the coordinated expression of DISC1-interactome genes for normal cognitive function and suggest that dysregulated DISC1 and NDEL1 expression might, in part, contribute to susceptibility for schizophrenia via disruption of prefrontal cortex-dependent cognitive functions.

Crowd sourcing a new paradigm for interactome driven drug target identification in Mycobacterium tuberculosis.

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Rohit Vashisht

Full Text Available A decade since the availability of Mycobacterium tuberculosis (Mtb genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative 'Connect to Decode' (C2D to generate the first and largest manually curated interactome of Mtb termed 'interactome pathway' (IPW, encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach.

Crowd Sourcing a New Paradigm for Interactome Driven Drug Target Identification in Mycobacterium tuberculosis

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Rohira, Harsha; Bhat, Ashwini G.; Passi, Anurag; Mukherjee, Keya; Choudhary, Kumari Sonal; Kumar, Vikas; Arora, Anshula; Munusamy, Prabhakaran; Subramanian, Ahalyaa; Venkatachalam, Aparna; S, Gayathri; Raj, Sweety; Chitra, Vijaya; Verma, Kaveri; Zaheer, Salman; J, Balaganesh; Gurusamy, Malarvizhi; Razeeth, Mohammed; Raja, Ilamathi; Thandapani, Madhumohan; Mevada, Vishal; Soni, Raviraj; Rana, Shruti; Ramanna, Girish Muthagadhalli; Raghavan, Swetha; Subramanya, Sunil N.; Kholia, Trupti; Patel, Rajesh; Bhavnani, Varsha; Chiranjeevi, Lakavath; Sengupta, Soumi; Singh, Pankaj Kumar; Atray, Naresh; Gandhi, Swati; Avasthi, Tiruvayipati Suma; Nisthar, Shefin; Anurag, Meenakshi; Sharma, Pratibha; Hasija, Yasha; Dash, Debasis; Sharma, Arun; Scaria, Vinod; Thomas, Zakir; Chandra, Nagasuma; Brahmachari, Samir K.; Bhardwaj, Anshu

2012-01-01

A decade since the availability of Mycobacterium tuberculosis (Mtb) genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative ‘Connect to Decode’ (C2D) to generate the first and largest manually curated interactome of Mtb termed ‘interactome pathway’ (IPW), encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach. PMID:22808064

Improved microarray-based decision support with graph encoded interactome data.

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Anneleen Daemen

Full Text Available In the past, microarray studies have been criticized due to noise and the limited overlap between gene signatures. Prior biological knowledge should therefore be incorporated as side information in models based on gene expression data to improve the accuracy of diagnosis and prognosis in cancer. As prior knowledge, we investigated interaction and pathway information from the human interactome on different aspects of biological systems. By exploiting the properties of kernel methods, relations between genes with similar functions but active in alternative pathways could be incorporated in a support vector machine classifier based on spectral graph theory. Using 10 microarray data sets, we first reduced the number of data sources relevant for multiple cancer types and outcomes. Three sources on metabolic pathway information (KEGG, protein-protein interactions (OPHID and miRNA-gene targeting (microRNA.org outperformed the other sources with regard to the considered class of models. Both fixed and adaptive approaches were subsequently considered to combine the three corresponding classifiers. Averaging the predictions of these classifiers performed best and was significantly better than the model based on microarray data only. These results were confirmed on 6 validation microarray sets, with a significantly improved performance in 4 of them. Integrating interactome data thus improves classification of cancer outcome for the investigated microarray technologies and cancer types. Moreover, this strategy can be incorporated in any kernel method or non-linear version of a non-kernel method.

Bcl2-associated Athanogene 3 Interactome Analysis Reveals a New Role in Modulating Proteasome Activity*

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Chen, Ying; Yang, Li-Na; Cheng, Li; Tu, Shun; Guo, Shu-Juan; Le, Huang-Ying; Xiong, Qian; Mo, Ran; Li, Chong-Yang; Jeong, Jun-Seop; Jiang, Lizhi; Blackshaw, Seth; Bi, Li-Jun; Zhu, Heng; Tao, Sheng-Ce; Ge, Feng

2013-01-01

Bcl2-associated athanogene 3 (BAG3), a member of the BAG family of co-chaperones, plays a critical role in regulating apoptosis, development, cell motility, autophagy, and tumor metastasis and in mediating cell adaptive responses to stressful stimuli. BAG3 carries a BAG domain, a WW domain, and a proline-rich repeat (PXXP), all of which mediate binding to different partners. To elucidate BAG3's interaction network at the molecular level, we employed quantitative immunoprecipitation combined with knockdown and human proteome microarrays to comprehensively profile the BAG3 interactome in humans. We identified a total of 382 BAG3-interacting proteins with diverse functions, including transferase activity, nucleic acid binding, transcription factors, proteases, and chaperones, suggesting that BAG3 is a critical regulator of diverse cellular functions. In addition, we characterized interactions between BAG3 and some of its newly identified partners in greater detail. In particular, bioinformatic analysis revealed that the BAG3 interactome is strongly enriched in proteins functioning within the proteasome-ubiquitination process and that compose the proteasome complex itself, suggesting that a critical biological function of BAG3 is associated with the proteasome. Functional studies demonstrated that BAG3 indeed interacts with the proteasome and modulates its activity, sustaining cell survival and underlying resistance to therapy through the down-modulation of apoptosis. Taken as a whole, this study expands our knowledge of the BAG3 interactome, provides a valuable resource for understanding how BAG3 affects different cellular functions, and demonstrates that biologically relevant data can be harvested using this kind of integrated approach. PMID:23824909

Quantum Interactomics and Cancer Molecular Mechanisms: I. Report Outline

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Baianu, I C

2004-01-01

Single cell interactomics in simpler organisms, as well as somatic cell interactomics in multicellular organisms, involve biomolecular interactions in complex signalling pathways that were recently represented in modular terms by quantum automata with ‘reversible behavior’ representing normal cell cycling and division. Other implications of such quantum automata, modular modeling of signaling pathways and cell differentiation during development are in the fields of neural plasticity and brain development leading to quantum-weave dynamic patterns and specific molecular processes underlying extensive memory, learning, anticipation mechanisms and the emergence of human consciousness during the early brain development in children. Cell interactomics is here represented for the first time as a mixture of ‘classical’ states that determine molecular dynamics subject to Boltzmann statistics and ‘steady-state’, metabolic (multi-stable) manifolds, together with ‘configuration’ spaces of metastable quant...

Protein function prediction involved on radio-resistant bacteria

International Nuclear Information System (INIS)

Mezhoud, Karim; Mankai, Houda; Sghaier, Haitham; Barkallah, Insaf

2009-01-01

Previously, we identified 58 proteins under positive selection in ionizing-radiation-resistant bacteria (IRRB) but absent in all ionizing-radiation-sensitive bacteria (IRSB). These are good reasons to believe these 58 proteins with their interactions with other proteins (interactomes) are a part of the answer to the question as to how IRRB resist to radiation, because our knowledge of interactomes of positively selected orphan proteins in IRRB might allow us to define cellular pathways important to ionizing-radiation resistance. Using the Database of Interacting Proteins and the PSIbase, we have predicted interactions of orthologs of the 58 proteins under positive selection in IRRB but absent in all IRSB. We used integrate experimental data sets with molecular interaction networks and protein structure prediction from databases. Among these, 18 proteins with their interactomes were identified in Deinococcus radiodurans R1. DNA checkpoint and repair, kinases pathways, energetic and nucleotide metabolisms were the important biological process that found. We predicted the interactomes of 58 proteins under positive selection in IRRB. It is hoped our data will provide new clues as to the cellular pathways that are important for ionizing-radiation resistance. We have identified news proteins involved on DNA management which were not previously mentioned. It is an important input in addition to protein that studied. It does still work to deepen our study on these new proteins

An Interactome-Centered Protein Discovery Approach Reveals Novel Components Involved in Mitosome Function and Homeostasis in Giardia lamblia.

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Samuel Rout

2016-12-01

Full Text Available Protozoan parasites of the genus Giardia are highly prevalent globally, and infect a wide range of vertebrate hosts including humans, with proliferation and pathology restricted to the small intestine. This narrow ecological specialization entailed extensive structural and functional adaptations during host-parasite co-evolution. An example is the streamlined mitosomal proteome with iron-sulphur protein maturation as the only biochemical pathway clearly associated with this organelle. Here, we applied techniques in microscopy and protein biochemistry to investigate the mitosomal membrane proteome in association to mitosome homeostasis. Live cell imaging revealed a highly immobilized array of 30-40 physically distinct mitosome organelles in trophozoites. We provide direct evidence for the single giardial dynamin-related protein as a contributor to mitosomal morphogenesis and homeostasis. To overcome inherent limitations that have hitherto severely hampered the characterization of these unique organelles we applied a novel interaction-based proteome discovery strategy using forward and reverse protein co-immunoprecipitation. This allowed generation of organelle proteome data strictly in a protein-protein interaction context. We built an initial Tom40-centered outer membrane interactome by co-immunoprecipitation experiments, identifying small GTPases, factors with dual mitosome and endoplasmic reticulum (ER distribution, as well as novel matrix proteins. Through iterative expansion of this protein-protein interaction network, we were able to i significantly extend this interaction-based mitosomal proteome to include other membrane-associated proteins with possible roles in mitosome morphogenesis and connection to other subcellular compartments, and ii identify novel matrix proteins which may shed light on mitosome-associated metabolic functions other than Fe-S cluster biogenesis. Functional analysis also revealed conceptual conservation of protein

3D structure prediction of histone acetyltransferase (HAC proteins of the p300/CBP family and their interactome in Arabidopsis thaliana

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Amar Cemanovic

2014-09-01

Full Text Available Histone acetylation is an important posttranslational modification correlated with gene activation. In Arabidopsis thaliana the histone acetyltransferase (HAC proteins of the CBP family are homologous to animal p300/CREB (cAMP-responsive element-binding proteins, which are important histone acetyltransferases participating in many physiological processes, including proliferation, differentiation, and apoptosis. In this study the 3-D structure of all HAC protein subunits in Arabidopsis thaliana: HAC1, HAC2, HAC4, HAC5 and HAC12 is predicted by homology modeling and confirmed by Ramachandran plot analysis. The amino acid sequences HAC family members are highly similar to the sequences of the homologous human p300/CREB protein. Conservation of p300/CBP domains among the HAC proteins was examined further by sequence alignment and pattern search. The domains of p300/CBP required for the HAC function, such as PHD, TAZ and ZZ domains, are conserved in all HAC proteins. Interactome analysis revealed that HAC1, HAC5 and HAC12 proteins interact with S-adenosylmethionine-dependent methyltransferase domaincontaining protein that shows methyltransferase activity, suggesting an additional function of the HAC proteins. Additionally, HAC5 has a strong interaction value for the putative c-myb-like transcription factor MYB3R-4, which suggests that it also may have a function in regulation of DNA replication.

Molecular characterization and interactome analysis of Trypanosoma cruzi tryparedoxin II.

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Arias, Diego G; Piñeyro, María Dolores; Iglesias, Alberto A; Guerrero, Sergio A; Robello, Carlos

2015-04-29

Trypanosoma cruzi, the causative agent of Chagas disease, possesses two tryparedoxins (TcTXNI and TcTXNII), belonging to the thioredoxin superfamily. TXNs are oxidoreductases which mediate electron transfer between trypanothione and peroxiredoxins. This constitutes a difference with the host cells, in which these activities are mediated by thioredoxins. These differences make TXNs an attractive target for drug development. In a previous work we characterized TcTXNI, including the redox interactome. In this work we extend the study to TcTXNII. We demonstrate that TcTXNII is a transmembrane protein anchored to the surface of the mitochondria and endoplasmic reticulum, with a cytoplasmatic orientation of the redox domain. It would be expressed during the metacyclogenesis process. In order to continue with the characterization of the redox interactome of T. cruzi, we designed an active site mutant TcTXNII lacking the resolving cysteine, and through the expression of this mutant protein and incubation with T. cruzi proteins, heterodisulfide complexes were isolated by affinity chromatography and identified by mass spectrometry. This allowed us to identify sixteen TcTXNII interacting proteins, which are involved in a wide range of cellular processes, indicating the relevance of TcTXNII, and contributing to our understanding of the redox interactome of T. cruzi. T. cruzi, the causative agent of Chagas disease, constitutes a major sanitary problem in Latin America. The number of estimated infected persons is ca. 8 million, 28 million people are at risk of infection and ~20,000 deaths occur per year in endemic regions. No vaccines are available at present, and most drugs currently in use were developed decades ago and show variable efficacy with undesirable side effects. The parasite is able to live and prolipherate inside macrophage phagosomes, where it is exposed to cytotoxic reactive oxygen and nitrogen species, derived from macrophage activation. Therefore, T. cruzi

Proteomic Analysis of the Mediator Complex Interactome in Saccharomyces cerevisiae.

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Uthe, Henriette; Vanselow, Jens T; Schlosser, Andreas

2017-02-27

Here we present the most comprehensive analysis of the yeast Mediator complex interactome to date. Particularly gentle cell lysis and co-immunopurification conditions allowed us to preserve even transient protein-protein interactions and to comprehensively probe the molecular environment of the Mediator complex in the cell. Metabolic 15 N-labeling thereby enabled stringent discrimination between bona fide interaction partners and nonspecifically captured proteins. Our data indicates a functional role for Mediator beyond transcription initiation. We identified a large number of Mediator-interacting proteins and protein complexes, such as RNA polymerase II, general transcription factors, a large number of transcriptional activators, the SAGA complex, chromatin remodeling complexes, histone chaperones, highly acetylated histones, as well as proteins playing a role in co-transcriptional processes, such as splicing, mRNA decapping and mRNA decay. Moreover, our data provides clear evidence, that the Mediator complex interacts not only with RNA polymerase II, but also with RNA polymerases I and III, and indicates a functional role of the Mediator complex in rRNA processing and ribosome biogenesis.

Efficient Prediction of Progesterone Receptor Interactome Using a Support Vector Machine Model

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Ji-Long Liu

2015-03-01

Full Text Available Protein-protein interaction (PPI is essential for almost all cellular processes and identification of PPI is a crucial task for biomedical researchers. So far, most computational studies of PPI are intended for pair-wise prediction. Theoretically, predicting protein partners for a single protein is likely a simpler problem. Given enough data for a particular protein, the results can be more accurate than general PPI predictors. In the present study, we assessed the potential of using the support vector machine (SVM model with selected features centered on a particular protein for PPI prediction. As a proof-of-concept study, we applied this method to identify the interactome of progesterone receptor (PR, a protein which is essential for coordinating female reproduction in mammals by mediating the actions of ovarian progesterone. We achieved an accuracy of 91.9%, sensitivity of 92.8% and specificity of 91.2%. Our method is generally applicable to any other proteins and therefore may be of help in guiding biomedical experiments.

Structure homology and interaction redundancy for discovering virus–host protein interactions

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de Chassey, Benoît; Meyniel-Schicklin, Laurène; Aublin-Gex, Anne; Navratil, Vincent; Chantier, Thibaut; André, Patrice; Lotteau, Vincent

2013-01-01

Virus–host interactomes are instrumental to understand global perturbations of cellular functions induced by infection and discover new therapies. The construction of such interactomes is, however, technically challenging and time consuming. Here we describe an original method for the prediction of high-confidence interactions between viral and human proteins through a combination of structure and high-quality interactome data. Validation was performed for the NS1 protein of the influenza virus, which led to the identification of new host factors that control viral replication. PMID:24008843

Structure homology and interaction redundancy for discovering virus-host protein interactions.

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de Chassey, Benoît; Meyniel-Schicklin, Laurène; Aublin-Gex, Anne; Navratil, Vincent; Chantier, Thibaut; André, Patrice; Lotteau, Vincent

2013-10-01

Virus-host interactomes are instrumental to understand global perturbations of cellular functions induced by infection and discover new therapies. The construction of such interactomes is, however, technically challenging and time consuming. Here we describe an original method for the prediction of high-confidence interactions between viral and human proteins through a combination of structure and high-quality interactome data. Validation was performed for the NS1 protein of the influenza virus, which led to the identification of new host factors that control viral replication.

Striatal Transcriptome and Interactome Analysis of Shank3-overexpressing Mice Reveals the Connectivity between Shank3 and mTORC1 Signaling

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Yeunkum Lee

2017-06-01

Full Text Available Mania causes symptoms of hyperactivity, impulsivity, elevated mood, reduced anxiety and decreased need for sleep, which suggests that the dysfunction of the striatum, a critical component of the brain motor and reward system, can be causally associated with mania. However, detailed molecular pathophysiology underlying the striatal dysfunction in mania remains largely unknown. In this study, we aimed to identify the molecular pathways showing alterations in the striatum of SH3 and multiple ankyrin repeat domains 3 (Shank3-overexpressing transgenic (TG mice that display manic-like behaviors. The results of transcriptome analysis suggested that mammalian target of rapamycin complex 1 (mTORC1 signaling may be the primary molecular signature altered in the Shank3 TG striatum. Indeed, we found that striatal mTORC1 activity, as measured by mTOR S2448 phosphorylation, was significantly decreased in the Shank3 TG mice compared to wild-type (WT mice. To elucidate the potential underlying mechanism, we re-analyzed previously reported protein interactomes, and detected a high connectivity between Shank3 and several upstream regulators of mTORC1, such as tuberous sclerosis 1 (TSC1, TSC2 and Ras homolog enriched in striatum (Rhes, via 94 common interactors that we denominated “Shank3-mTORC1 interactome”. We noticed that, among the 94 common interactors, 11 proteins were related to actin filaments, the level of which was increased in the dorsal striatum of Shank3 TG mice. Furthermore, we could co-immunoprecipitate Shank3, Rhes and Wiskott-Aldrich syndrome protein family verprolin-homologous protein 1 (WAVE1 proteins from the striatal lysate of Shank3 TG mice. By comparing with the gene sets of psychiatric disorders, we also observed that the 94 proteins of Shank3-mTORC1 interactome were significantly associated with bipolar disorder (BD. Altogether, our results suggest a protein interaction-mediated connectivity between Shank3 and certain upstream

Toxoplasmosis and Polygenic Disease Susceptibility Genes: Extensive Toxoplasma gondii Host/Pathogen Interactome Enrichment in Nine Psychiatric or Neurological Disorders

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C. J. Carter

2013-01-01

Full Text Available Toxoplasma gondii is not only implicated in schizophrenia and related disorders, but also in Alzheimer's or Parkinson's disease, cancer, cardiac myopathies, and autoimmune disorders. During its life cycle, the pathogen interacts with ~3000 host genes or proteins. Susceptibility genes for multiple sclerosis, Alzheimer's disease, schizophrenia, bipolar disorder, depression, childhood obesity, Parkinson's disease, attention deficit hyperactivity disorder (multiple sclerosis, and autism (, but not anorexia or chronic fatigue are highly enriched in the human arm of this interactome and 18 (ADHD to 33% (MS of the susceptibility genes relate to it. The signalling pathways involved in the susceptibility gene/interactome overlaps are relatively specific and relevant to each disease suggesting a means whereby susceptibility genes could orient the attentions of a single pathogen towards disruption of the specific pathways that together contribute (positively or negatively to the endophenotypes of different diseases. Conditional protein knockdown, orchestrated by T. gondii proteins or antibodies binding to those of the host (pathogen derived autoimmunity and metabolite exchange, may contribute to this disruption. Susceptibility genes may thus be related to the causes and influencers of disease, rather than (and as well as to the disease itself.

Grouping annotations on the subcellular layered interactome demonstrates enhanced autophagy activity in a recurrent experimental autoimmune uveitis T cell line.

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Xiuzhi Jia

Full Text Available Human uveitis is a type of T cell-mediated autoimmune disease that often shows relapse-remitting courses affecting multiple biological processes. As a cytoplasmic process, autophagy has been seen as an adaptive response to cell death and survival, yet the link between autophagy and T cell-mediated autoimmunity is not certain. In this study, based on the differentially expressed genes (GSE19652 between the recurrent versus monophasic T cell lines, whose adoptive transfer to susceptible animals may result in respective recurrent or monophasic uveitis, we proposed grouping annotations on a subcellular layered interactome framework to analyze the specific bioprocesses that are linked to the recurrence of T cell autoimmunity. That is, the subcellular layered interactome was established by the Cytoscape and Cerebral plugin based on differential expression, global interactome, and subcellular localization information. Then, the layered interactomes were grouping annotated by the ClueGO plugin based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. The analysis showed that significant bioprocesses with autophagy were orchestrated in the cytoplasmic layered interactome and that mTOR may have a regulatory role in it. Furthermore, by setting up recurrent and monophasic uveitis in Lewis rats, we confirmed by transmission electron microscopy that, in comparison to the monophasic disease, recurrent uveitis in vivo showed significantly increased autophagy activity and extended lymphocyte infiltration to the affected retina. In summary, our framework methodology is a useful tool to disclose specific bioprocesses and molecular targets that can be attributed to a certain disease. Our results indicated that targeted inhibition of autophagy pathways may perturb the recurrence of uveitis.

Specificity and commonality of the phosphoinositide-binding proteome analyzed by quantitative mass spectrometry

DEFF Research Database (Denmark)

Jungmichel, Stephanie; Sylvestersen, Kathrine B; Choudhary, Chuna Ram

2014-01-01

than the total number of phospho- or ubiquitin-binding domains. Translocation and inhibitor assays of identified PIP-binding proteins confirmed that our methodology targets direct interactors. The PIP interactome encompasses proteins from diverse cellular compartments, prominently including the nucleus...

Characterization of hampin/MSL1 as a node in the nuclear interactome

International Nuclear Information System (INIS)

Dmitriev, Ruslan I.; Korneenko, Tatyana V.; Bessonov, Alexander A.; Shakhparonov, Mikhail I.; Modyanov, Nikolai N.; Pestov, Nikolay B.

2007-01-01

Hampin, homolog of Drosophila MSL1, is a partner of histone acetyltransferase MYST1/MOF. Functions of these proteins remain poorly understood beyond their participation in chromatin remodeling complex MSL. In order to identify new proteins interacting with hampin, we screened a mouse cDNA library in yeast two-hybrid system with mouse hampin as bait and found five high-confidence interactors: MYST1, TPR proteins TTC4 and KIAA0103, NOP17 (homolog of a yeast nucleolar protein), and transcription factor GC BP. Subsequently, all these proteins were used as baits in library screenings and more new interactions were found: tumor suppressor RASSF1C and spliceosome component PRP3 for KIAA0103, ring finger RNF10 for RASSF1C, and RNA polymerase II regulator NELF-C for MYST1. The majority of the observed interactions was confirmed in vitro by pull-down of bacterially expressed proteins. Reconstruction of a fragment of mammalian interactome suggests that hampin may be linked to diverse regulatory processes in the nucleus

Exploring off-targets and off-systems for adverse drug reactions via chemical-protein interactome--clozapine-induced agranulocytosis as a case study.

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Lun Yang

2011-03-01

Full Text Available In the era of personalized medical practice, understanding the genetic basis of patient-specific adverse drug reaction (ADR is a major challenge. Clozapine provides effective treatments for schizophrenia but its usage is limited because of life-threatening agranulocytosis. A recent high impact study showed the necessity of moving clozapine to a first line drug, thus identifying the biomarkers for drug-induced agranulocytosis has become important. Here we report a methodology termed as antithesis chemical-protein interactome (CPI, which utilizes the docking method to mimic the differences in the drug-protein interactions across a panel of human proteins. Using this method, we identified HSPA1A, a known susceptibility gene for CIA, to be the off-target of clozapine. Furthermore, the mRNA expression of HSPA1A-related genes (off-target associated systems was also found to be differentially expressed in clozapine treated leukemia cell line. Apart from identifying the CIA causal genes we identified several novel candidate genes which could be responsible for agranulocytosis. Proteins related to reactive oxygen clearance system, such as oxidoreductases and glutathione metabolite enzymes, were significantly enriched in the antithesis CPI. This methodology conducted a multi-dimensional analysis of drugs' perturbation to the biological system, investigating both the off-targets and the associated off-systems to explore the molecular basis of an adverse event or the new uses for old drugs.

IIS--Integrated Interactome System: a web-based platform for the annotation, analysis and visualization of protein-metabolite-gene-drug interactions by integrating a variety of data sources and tools.

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Carazzolle, Marcelo Falsarella; de Carvalho, Lucas Miguel; Slepicka, Hugo Henrique; Vidal, Ramon Oliveira; Pereira, Gonçalo Amarante Guimarães; Kobarg, Jörg; Meirelles, Gabriela Vaz

2014-01-01

High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two

A scalable double-barcode sequencing platform for characterization of dynamic protein-protein interactions.

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Schlecht, Ulrich; Liu, Zhimin; Blundell, Jamie R; St Onge, Robert P; Levy, Sasha F

2017-05-25

Several large-scale efforts have systematically catalogued protein-protein interactions (PPIs) of a cell in a single environment. However, little is known about how the protein interactome changes across environmental perturbations. Current technologies, which assay one PPI at a time, are too low throughput to make it practical to study protein interactome dynamics. Here, we develop a highly parallel protein-protein interaction sequencing (PPiSeq) platform that uses a novel double barcoding system in conjunction with the dihydrofolate reductase protein-fragment complementation assay in Saccharomyces cerevisiae. PPiSeq detects PPIs at a rate that is on par with current assays and, in contrast with current methods, quantitatively scores PPIs with enough accuracy and sensitivity to detect changes across environments. Both PPI scoring and the bulk of strain construction can be performed with cell pools, making the assay scalable and easily reproduced across environments. PPiSeq is therefore a powerful new tool for large-scale investigations of dynamic PPIs.

Frontotemporal dysregulation of the SNARE protein interactome is associated with faster cognitive decline in old age.

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Ramos-Miguel, Alfredo; Jones, Andrea A; Sawada, Ken; Barr, Alasdair M; Bayer, Thomas A; Falkai, Peter; Leurgans, Sue E; Schneider, Julie A; Bennett, David A; Honer, William G

2018-06-01

The molecular underpinnings associated with cognitive reserve remain poorly understood. Because animal models fail to fully recapitulate the complexity of human brain aging, postmortem studies from well-designed cohorts are crucial to unmask mechanisms conferring cognitive resistance against cumulative neuropathologies. We tested the hypothesis that functionality of the SNARE protein interactome might be an important resilience factor preserving cognitive abilities in old age. Cognition was assessed annually in participants from the Rush "Memory and Aging Project" (MAP), a community-dwelling cohort representative of the overall aging population. Associations between cognition and postmortem neurochemical data were evaluated in functional assays quantifying various species of the SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) machinery in samples from the inferior temporal (IT, n = 154) and middle-frontal (MF, n = 174) gyri. Using blue-native gel electrophoresis, we isolated and quantified several types of complexes containing the three SNARE proteins (syntaxin-1, SNAP25, VAMP), as well as the GABAergic/glutamatergic selectively expressed complexins-I/II (CPLX1/2), in brain tissue homogenates and reconstitution assays with recombinant proteins. Multivariate analyses revealed significant associations between IT and MF neurochemical data (SNARE proteins and/or complexes), and multiple age-related neuropathologies, as well as with multiple cognitive domains of MAP participants. Controlling for demographic variables, neuropathologic indices and total synapse density, we found that temporal 150-kDa SNARE species (representative of pan-synaptic functionality) and frontal CPLX1/CPLX2 ratio of 500-kDa heteromeric species (representative of inhibitory/excitatory input functionality) were, among all the immunocharacterized complexes, the strongest predictors of cognitive function nearest death. Interestingly, these two neurochemical

Making connections for life: an in vivo map of the yeast interactome.

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Kast, Juergen

2008-10-01

Proteins are the true workhorses of any cell. To carry out specific tasks, they frequently bind other molecules in their surroundings. Due to their structural complexity and flexibility, the most diverse array of interactions is seen with other proteins. The different geometries and affinities available for such interactions typically bestow specific functions on proteins. Having available a map of protein-protein interactions is therefore of enormous importance for any researcher interested in gaining insight into biological systems at the level of cells and organisms. In a recent report, a novel approach has been employed that relies on the spontaneous folding of complementary enzyme fragments fused to two different proteins to test whether these interact in their actual cellular context [Tarassov et al., Science 320, 1465-1470 (2008)]. Genome-wide application of this protein-fragment complementation assay has resulted in the first map of the in vivo interactome of Saccharomyces cerevisiae. The current data show striking similarities but also significant differences to those obtained using other large-scale approaches for the same task. This warrants a general discussion of the current state of affairs of protein-protein interaction studies and foreseeable future trends, highlighting their significance for a variety of applications and their potential to revolutionize our understanding of the architecture and dynamics of biological systems.

Levetiracetam Affects Differentially Presynaptic Proteins in Rat Cerebral Cortex

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Daniele Marcotulli

2017-12-01

Full Text Available Presynaptic proteins are potential therapeutic targets for epilepsy and other neurological diseases. We tested the hypothesis that chronic treatment with the SV2A ligand levetiracetam affects the expression of other presynaptic proteins. Results showed that in rat neocortex no significant difference was detected in SV2A protein levels in levetiracetam treated animals compared to controls, whereas levetiracetam post-transcriptionally decreased several vesicular proteins and increased LRRK2, without any change in mRNA levels. Analysis of SV2A interactome indicates that the presynaptic proteins regulation induced by levetiracetam reported here is mediated by this interactome, and suggests that LRRK2 plays a role in forging the pattern of effects.

System-level insights into the cellular interactome of a non-model organism: inferring, modelling and analysing functional gene network of soybean (Glycine max.

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Yungang Xu

Full Text Available Cellular interactome, in which genes and/or their products interact on several levels, forming transcriptional regulatory-, protein interaction-, metabolic-, signal transduction networks, etc., has attracted decades of research focuses. However, such a specific type of network alone can hardly explain the various interactive activities among genes. These networks characterize different interaction relationships, implying their unique intrinsic properties and defects, and covering different slices of biological information. Functional gene network (FGN, a consolidated interaction network that models fuzzy and more generalized notion of gene-gene relations, have been proposed to combine heterogeneous networks with the goal of identifying functional modules supported by multiple interaction types. There are yet no successful precedents of FGNs on sparsely studied non-model organisms, such as soybean (Glycine max, due to the absence of sufficient heterogeneous interaction data. We present an alternative solution for inferring the FGNs of soybean (SoyFGNs, in a pioneering study on the soybean interactome, which is also applicable to other organisms. SoyFGNs exhibit the typical characteristics of biological networks: scale-free, small-world architecture and modularization. Verified by co-expression and KEGG pathways, SoyFGNs are more extensive and accurate than an orthology network derived from Arabidopsis. As a case study, network-guided disease-resistance gene discovery indicates that SoyFGNs can provide system-level studies on gene functions and interactions. This work suggests that inferring and modelling the interactome of a non-model plant are feasible. It will speed up the discovery and definition of the functions and interactions of other genes that control important functions, such as nitrogen fixation and protein or lipid synthesis. The efforts of the study are the basis of our further comprehensive studies on the soybean functional

Evaluation of clustering algorithms for protein-protein interaction networks

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van Helden Jacques

2006-11-01

Full Text Available Abstract Background Protein interactions are crucial components of all cellular processes. Recently, high-throughput methods have been developed to obtain a global description of the interactome (the whole network of protein interactions for a given organism. In 2002, the yeast interactome was estimated to contain up to 80,000 potential interactions. This estimate is based on the integration of data sets obtained by various methods (mass spectrometry, two-hybrid methods, genetic studies. High-throughput methods are known, however, to yield a non-negligible rate of false positives, and to miss a fraction of existing interactions. The interactome can be represented as a graph where nodes correspond with proteins and edges with pairwise interactions. In recent years clustering methods have been developed and applied in order to extract relevant modules from such graphs. These algorithms require the specification of parameters that may drastically affect the results. In this paper we present a comparative assessment of four algorithms: Markov Clustering (MCL, Restricted Neighborhood Search Clustering (RNSC, Super Paramagnetic Clustering (SPC, and Molecular Complex Detection (MCODE. Results A test graph was built on the basis of 220 complexes annotated in the MIPS database. To evaluate the robustness to false positives and false negatives, we derived 41 altered graphs by randomly removing edges from or adding edges to the test graph in various proportions. Each clustering algorithm was applied to these graphs with various parameter settings, and the clusters were compared with the annotated complexes. We analyzed the sensitivity of the algorithms to the parameters and determined their optimal parameter values. We also evaluated their robustness to alterations of the test graph. We then applied the four algorithms to six graphs obtained from high-throughput experiments and compared the resulting clusters with the annotated complexes. Conclusion This

Interactome analysis of transcriptional coactivator multiprotein bridging factor 1 unveils a yeast AP-1-like transcription factor involved in oxidation tolerance of mycopathogen Beauveria bassiana.

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Chu, Xin-Ling; Dong, Wei-Xia; Ding, Jin-Li; Feng, Ming-Guang; Ying, Sheng-Hua

2018-02-01

Oxidation tolerance is an important determinant to predict the virulence and biocontrol potential of Beauveria bassiana, a well-known entomopathogenic fungus. As a transcriptional coactivator, multiprotein bridging factor 1 mediates the activity of transcription factor in diverse physiological processes, and its homolog in B. bassiana (BbMBF1) contributes to fungal oxidation tolerance. In this study, the BbMBF1-interactomes under oxidative stress and normal growth condition were deciphered by mass spectrometry integrated with the immunoprecipitation. BbMBF1p factor has a broad interaction with proteins that are involved in various cellular processes, and this interaction is dynamically regulated by oxidative stress. Importantly, a B. bassiana homolog of yeast AP-1-like transcription factor (BbAP-1) was specifically associated with the BbMBF1-interactome under oxidation and significantly contributed to fungal oxidation tolerance. In addition, qPCR analysis revealed that several antioxidant genes are jointly controlled by BbAP-1 and BbMBF1. Conclusively, it is proposed that BbMBF1p protein mediates BbAP-1p factor to transcribe the downstream antioxidant genes in B. bassiana under oxidative stress. This study demonstrates for the first time a proteomic view of the MBF1-interactome in fungi, and presents an initial framework to probe the transcriptional mechanism involved in fungal response to oxidation, which will provide a new strategy to improve the biocontrol efficacy of B. bassiana.

Weighted Protein Interaction Network Analysis of Frontotemporal Dementia.

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Ferrari, Raffaele; Lovering, Ruth C; Hardy, John; Lewis, Patrick A; Manzoni, Claudia

2017-02-03

The genetic analysis of complex disorders has undoubtedly led to the identification of a wealth of associations between genes and specific traits. However, moving from genetics to biochemistry one gene at a time has, to date, rather proved inefficient and under-powered to comprehensively explain the molecular basis of phenotypes. Here we present a novel approach, weighted protein-protein interaction network analysis (W-PPI-NA), to highlight key functional players within relevant biological processes associated with a given trait. This is exemplified in the current study by applying W-PPI-NA to frontotemporal dementia (FTD): We first built the state of the art FTD protein network (FTD-PN) and then analyzed both its topological and functional features. The FTD-PN resulted from the sum of the individual interactomes built around FTD-spectrum genes, leading to a total of 4198 nodes. Twenty nine of 4198 nodes, called inter-interactome hubs (IIHs), represented those interactors able to bridge over 60% of the individual interactomes. Functional annotation analysis not only reiterated and reinforced previous findings from single genes and gene-coexpression analyses but also indicated a number of novel potential disease related mechanisms, including DNA damage response, gene expression regulation, and cell waste disposal and potential biomarkers or therapeutic targets including EP300. These processes and targets likely represent the functional core impacted in FTD, reflecting the underlying genetic architecture contributing to disease. The approach presented in this study can be applied to other complex traits for which risk-causative genes are known as it provides a promising tool for setting the foundations for collating genomics and wet laboratory data in a bidirectional manner. This is and will be critical to accelerate molecular target prioritization and drug discovery.

Interactome of Obesity: Obesidome : Genetic Obesity, Stress Induced Obesity, Pathogenic Obesity Interaction.

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Geronikolou, Styliani A; Pavlopoulou, Athanasia; Cokkinos, Dennis; Chrousos, George

2017-01-01

Obesity is a chronic disease of increasing prevalence reaching epidemic proportions. Genetic defects as well as epigenetic effects contribute to the obesity phenotype. Investigating gene (e.g. MC4R defects)-environment (behavior, infectious agents, stress) interactions is a relative new field of great research interest. In this study, we have made an effort to create an interactome (henceforth referred to as "obesidome"), where extrinsic stressors response, intrinsic predisposition, immunity response to inflammation and autonomous nervous system implications are integrated. These pathways are presented in one interactome network for the first time. In our study, obesity-related genes/gene products were found to form a complex interactions network.

Interactome Screening Identifies the ER Luminal Chaperone Hsp47 as a Regulator of the Unfolded Protein Response Transducer IRE1α.

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Sepulveda, Denisse; Rojas-Rivera, Diego; Rodríguez, Diego A; Groenendyk, Jody; Köhler, Andres; Lebeaupin, Cynthia; Ito, Shinya; Urra, Hery; Carreras-Sureda, Amado; Hazari, Younis; Vasseur-Cognet, Mireille; Ali, Maruf M U; Chevet, Eric; Campos, Gisela; Godoy, Patricio; Vaisar, Tomas; Bailly-Maitre, Béatrice; Nagata, Kazuhiro; Michalak, Marek; Sierralta, Jimena; Hetz, Claudio

2018-01-18

Maintenance of endoplasmic reticulum (ER) proteostasis is controlled by a dynamic signaling network known as the unfolded protein response (UPR). IRE1α is a major UPR transducer, determining cell fate under ER stress. We used an interactome screening to unveil several regulators of the UPR, highlighting the ER chaperone Hsp47 as the major hit. Cellular and biochemical analysis indicated that Hsp47 instigates IRE1α signaling through a physical interaction. Hsp47 directly binds to the ER luminal domain of IRE1α with high affinity, displacing the negative regulator BiP from the complex to facilitate IRE1α oligomerization. The regulation of IRE1α signaling by Hsp47 is evolutionarily conserved as validated using fly and mouse models of ER stress. Hsp47 deficiency sensitized cells and animals to experimental ER stress, revealing the significance of Hsp47 to global proteostasis maintenance. We conclude that Hsp47 adjusts IRE1α signaling by fine-tuning the threshold to engage an adaptive UPR. Copyright © 2018 Elsevier Inc. All rights reserved.

Comparative proteomic analysis of normal and collagen IX null mouse cartilage reveals altered extracellular matrix composition and novel components of the collagen IX interactome.

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Brachvogel, Bent; Zaucke, Frank; Dave, Keyur; Norris, Emma L; Stermann, Jacek; Dayakli, Münire; Koch, Manuel; Gorman, Jeffrey J; Bateman, John F; Wilson, Richard

2013-05-10

Collagen IX is an integral cartilage extracellular matrix component important in skeletal development and joint function. Proteomic analysis and validation studies revealed novel alterations in collagen IX null cartilage. Matrilin-4, collagen XII, thrombospondin-4, fibronectin, βig-h3, and epiphycan are components of the in vivo collagen IX interactome. We applied a proteomics approach to advance our understanding of collagen IX ablation in cartilage. The cartilage extracellular matrix is essential for endochondral bone development and joint function. In addition to the major aggrecan/collagen II framework, the interacting complex of collagen IX, matrilin-3, and cartilage oligomeric matrix protein (COMP) is essential for cartilage matrix stability, as mutations in Col9a1, Col9a2, Col9a3, Comp, and Matn3 genes cause multiple epiphyseal dysplasia, in which patients develop early onset osteoarthritis. In mice, collagen IX ablation results in severely disturbed growth plate organization, hypocellular regions, and abnormal chondrocyte shape. This abnormal differentiation is likely to involve altered cell-matrix interactions but the mechanism is not known. To investigate the molecular basis of the collagen IX null phenotype we analyzed global differences in protein abundance between wild-type and knock-out femoral head cartilage by capillary HPLC tandem mass spectrometry. We identified 297 proteins in 3-day cartilage and 397 proteins in 21-day cartilage. Components that were differentially abundant between wild-type and collagen IX-deficient cartilage included 15 extracellular matrix proteins. Collagen IX ablation was associated with dramatically reduced COMP and matrilin-3, consistent with known interactions. Matrilin-1, matrilin-4, epiphycan, and thrombospondin-4 levels were reduced in collagen IX null cartilage, providing the first in vivo evidence for these proteins belonging to the collagen IX interactome. Thrombospondin-4 expression was reduced at the mRNA level

Comprehensively Characterizing the Thioredoxin Interactome In Vivo Highlights the Central Role Played by This Ubiquitous Oxidoreductase in Redox Control*

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Arts, Isabelle S.; Vertommen, Didier; Baldin, Francesca; Laloux, Géraldine; Collet, Jean-François

2016-01-01

Thioredoxin (Trx) is a ubiquitous oxidoreductase maintaining protein-bound cysteine residues in the reduced thiol state. Here, we combined a well-established method to trap Trx substrates with the power of bacterial genetics to comprehensively characterize the in vivo Trx redox interactome in the model bacterium Escherichia coli. Using strains engineered to optimize trapping, we report the identification of a total 268 Trx substrates, including 201 that had never been reported to depend on Trx for reduction. The newly identified Trx substrates are involved in a variety of cellular processes, ranging from energy metabolism to amino acid synthesis and transcription. The interaction between Trx and two of its newly identified substrates, a protein required for the import of most carbohydrates, PtsI, and the bacterial actin homolog MreB was studied in detail. We provide direct evidence that PtsI and MreB contain cysteine residues that are susceptible to oxidation and that participate in the formation of an intermolecular disulfide with Trx. By considerably expanding the number of Trx targets, our work highlights the role played by this major oxidoreductase in a variety of cellular processes. Moreover, as the dependence on Trx for reduction is often conserved across species, it also provides insightful information on the interactome of Trx in organisms other than E. coli. PMID:27081212

Hypothesis: NDL proteins function in stress responses by regulating microtubule organization.

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Khatri, Nisha; Mudgil, Yashwanti

2015-01-01

N-MYC DOWNREGULATED-LIKE proteins (NDL), members of the alpha/beta hydrolase superfamily were recently rediscovered as interactors of G-protein signaling in Arabidopsis thaliana. Although the precise molecular function of NDL proteins is still elusive, in animals these proteins play protective role in hypoxia and expression is induced by hypoxia and nickel, indicating role in stress. Homology of NDL1 with animal counterpart N-MYC DOWNREGULATED GENE (NDRG) suggests similar functions in animals and plants. It is well established that stress responses leads to the microtubule depolymerization and reorganization which is crucial for stress tolerance. NDRG is a microtubule-associated protein which mediates the microtubule organization in animals by causing acetylation and increases the stability of α-tubulin. As NDL1 is highly homologous to NDRG, involvement of NDL1 in the microtubule organization during plant stress can also be expected. Discovery of interaction of NDL with protein kinesin light chain- related 1, enodomembrane family protein 70, syntaxin-23, tubulin alpha-2 chain, as a part of G protein interactome initiative encourages us to postulate microtubule stabilizing functions for NDL family in plants. Our search for NDL interactors in G protein interactome also predicts the role of NDL proteins in abiotic stress tolerance management. Based on published report in animals and predicted interacting partners for NDL in G protein interactome lead us to hypothesize involvement of NDL in the microtubule organization during abiotic stress management in plants.

Novel Technology for Protein-Protein Interaction-based Targeted Drug Discovery

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Jung Me Hwang

2011-12-01

Full Text Available We have developed a simple but highly efficient in-cell protein-protein interaction (PPI discovery system based on the translocation properties of protein kinase C- and its C1a domain in live cells. This system allows the visual detection of trimeric and dimeric protein interactions including cytosolic, nuclear, and/or membrane proteins with their cognate ligands. In addition, this system can be used to identify pharmacological small compounds that inhibit specific PPIs. These properties make this PPI system an attractive tool for screening drug candidates and mapping the protein interactome.

sCLIP-an integrated platform to study RNA-protein interactomes in biomedical research: identification of CSTF2tau in alternative processing of small nuclear RNAs.

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Kargapolova, Yulia; Levin, Michal; Lackner, Karl; Danckwardt, Sven

2017-06-02

RNA-binding proteins (RBPs) are central for gene expression by controlling the RNA fate from birth to decay. Various disorders arising from perturbations of RNA-protein interactions document their critical function. However, deciphering their function is complex, limiting the general functional elucidation of this growing class of proteins and their contribution to (patho)physiology. Here, we present sCLIP, a simplified and robust platform for genome-wide interrogation of RNA-protein interactomes based on crosslinking-immunoprecipitation and high-throughput sequencing. sCLIP exploits linear amplification of the immunoprecipitated RNA improving the complexity of the sequencing-library despite significantly reducing the amount of input material and omitting several purification steps. Additionally, it permits a radiolabel-free visualization of immunoprecipitated RNA. In a proof of concept, we identify that CSTF2tau binds many previously not recognized RNAs including histone, snoRNA and snRNAs. CSTF2tau-binding is associated with internal oligoadenylation resulting in shortened snRNA isoforms subjected to rapid degradation. We provide evidence for a new mechanism whereby CSTF2tau controls the abundance of snRNAs resulting in alternative splicing of several RNAs including ANK2 with critical roles in tumorigenesis and cardiac function. Combined with a bioinformatic pipeline sCLIP thus uncovers new functions for established RBPs and fosters the illumination of RBP-protein interaction landscapes in health and disease. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

HIV protein sequence hotspots for crosstalk with host hub proteins.

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Mahdi Sarmady

Full Text Available HIV proteins target host hub proteins for transient binding interactions. The presence of viral proteins in the infected cell results in out-competition of host proteins in their interaction with hub proteins, drastically affecting cell physiology. Functional genomics and interactome datasets can be used to quantify the sequence hotspots on the HIV proteome mediating interactions with host hub proteins. In this study, we used the HIV and human interactome databases to identify HIV targeted host hub proteins and their host binding partners (H2. We developed a high throughput computational procedure utilizing motif discovery algorithms on sets of protein sequences, including sequences of HIV and H2 proteins. We identified as HIV sequence hotspots those linear motifs that are highly conserved on HIV sequences and at the same time have a statistically enriched presence on the sequences of H2 proteins. The HIV protein motifs discovered in this study are expressed by subsets of H2 host proteins potentially outcompeted by HIV proteins. A large subset of these motifs is involved in cleavage, nuclear localization, phosphorylation, and transcription factor binding events. Many such motifs are clustered on an HIV sequence in the form of hotspots. The sequential positions of these hotspots are consistent with the curated literature on phenotype altering residue mutations, as well as with existing binding site data. The hotspot map produced in this study is the first global portrayal of HIV motifs involved in altering the host protein network at highly connected hub nodes.

Detection of dysregulated protein-association networks by high-throughput proteomics predicts cancer vulnerabilities.

Science.gov (United States)

Lapek, John D; Greninger, Patricia; Morris, Robert; Amzallag, Arnaud; Pruteanu-Malinici, Iulian; Benes, Cyril H; Haas, Wilhelm

2017-10-01

The formation of protein complexes and the co-regulation of the cellular concentrations of proteins are essential mechanisms for cellular signaling and for maintaining homeostasis. Here we use isobaric-labeling multiplexed proteomics to analyze protein co-regulation and show that this allows the identification of protein-protein associations with high accuracy. We apply this 'interactome mapping by high-throughput quantitative proteome analysis' (IMAHP) method to a panel of 41 breast cancer cell lines and show that deviations of the observed protein co-regulations in specific cell lines from the consensus network affects cellular fitness. Furthermore, these aberrant interactions serve as biomarkers that predict the drug sensitivity of cell lines in screens across 195 drugs. We expect that IMAHP can be broadly used to gain insight into how changing landscapes of protein-protein associations affect the phenotype of biological systems.

Interactomes to Biological Phase Space: a call to begin thinking at a new level in computational biology.

Energy Technology Data Exchange (ETDEWEB)

Davidson, George S.; Brown, William Michael

2007-09-01

Techniques for high throughput determinations of interactomes, together with high resolution protein collocalizations maps within organelles and through membranes will soon create a vast resource. With these data, biological descriptions, akin to the high dimensional phase spaces familiar to physicists, will become possible. These descriptions will capture sufficient information to make possible realistic, system-level models of cells. The descriptions and the computational models they enable will require powerful computing techniques. This report is offered as a call to the computational biology community to begin thinking at this scale and as a challenge to develop the required algorithms and codes to make use of the new data.3

BIPS: BIANA Interolog Prediction Server. A tool for protein-protein interaction inference.

Science.gov (United States)

Garcia-Garcia, Javier; Schleker, Sylvia; Klein-Seetharaman, Judith; Oliva, Baldo

2012-07-01

Protein-protein interactions (PPIs) play a crucial role in biology, and high-throughput experiments have greatly increased the coverage of known interactions. Still, identification of complete inter- and intraspecies interactomes is far from being complete. Experimental data can be complemented by the prediction of PPIs within an organism or between two organisms based on the known interactions of the orthologous genes of other organisms (interologs). Here, we present the BIANA (Biologic Interactions and Network Analysis) Interolog Prediction Server (BIPS), which offers a web-based interface to facilitate PPI predictions based on interolog information. BIPS benefits from the capabilities of the framework BIANA to integrate the several PPI-related databases. Additional metadata can be used to improve the reliability of the predicted interactions. Sensitivity and specificity of the server have been calculated using known PPIs from different interactomes using a leave-one-out approach. The specificity is between 72 and 98%, whereas sensitivity varies between 1 and 59%, depending on the sequence identity cut-off used to calculate similarities between sequences. BIPS is freely accessible at http://sbi.imim.es/BIPS.php.

Hypothesis review: are clathrin-mediated endocytosis and clathrin-dependent membrane and protein trafficking core pathophysiological processes in schizophrenia and bipolar disorder?

LENUS (Irish Health Repository)

2012-02-01

Clathrin-mediated endocytosis (CME) is the best-characterized mechanism governing cellular membrane and protein trafficking. In this hypothesis review, we integrate recent evidence implicating CME and related cellular trafficking mechanisms in the pathophysiology of psychotic disorders such as schizophrenia and bipolar disorder. The evidence includes proteomic and genomic findings implicating proteins and genes of the clathrin interactome. Additionally, several important candidate genes for schizophrenia, such as dysbindin, are involved in processes closely linked to CME and membrane trafficking. We discuss that key aspects of psychosis neuropathology such as synaptic dysfunction, white matter changes and aberrant neurodevelopment are all influenced by clathrin-dependent processes, and that other cellular trafficking mechanisms previously linked to psychoses interact with the clathrin interactome in important ways. Furthermore, many antipsychotic drugs have been shown to affect clathrin-interacting proteins. We propose that the targeted pharmacological manipulation of the clathrin interactome may offer fruitful opportunities for novel treatments of schizophrenia.Molecular Psychiatry advance online publication, 11 October 2011; doi:10.1038\\/mp.2011.123.

A membrane protein / signaling protein interaction network for Arabidopsis version AMPv2

Directory of Open Access Journals (Sweden)

Sylvie Lalonde

2010-09-01

Full Text Available Interactions between membrane proteins and the soluble fraction are essential for signal transduction and for regulating nutrient transport. To gain insights into the membrane-based interactome, 3,852 open reading frames (ORFs out of a target list of 8,383 representing membrane and signaling proteins from Arabidopsis thaliana were cloned into a Gateway compatible vector. The mating-based split-ubiquitin system was used to screen for potential protein-protein interactions (pPPIs among 490 Arabidopsis ORFs. A binary robotic screen between 142 receptor-like kinases, 72 transporters, 57 soluble protein kinases and phosphatases, 40 glycosyltransferases, 95 proteins of various functions and 89 proteins with unknown function detected 387 out of 90,370 possible PPIs. A secondary screen confirmed 343 (of 387 pPPIs between 179 proteins, yielding a scale-free network (r2=0.863. Eighty of 142 transmembrane receptor-like kinases (RLK tested positive, identifying three homomers, 63 heteromers and 80 pPPIs with other proteins. Thirty-one out of 142 RLK interactors (including RLKs had previously been found to be phosphorylated; thus interactors may be substrates for respective RLKs. None of the pPPIs described here had been reported in the major interactome databases, including potential interactors of G protein-coupled receptors, phospholipase C, and AMT ammonium transporters. Two RLKs found as putative interactors of AMT1;1 were independently confirmed using a split luciferase assay in Arabidopsis protoplasts. These RLKs may be involved in ammonium-dependent phosphorylation of the C-terminus and regulation of ammonium uptake activity. The robotic screening method established here will enable a systematic analysis of membrane protein interactions in fungi, plants and metazoa.

An affinity pull-down approach to identify the plant cyclic nucleotide interactome

KAUST Repository

Donaldson, Lara Elizabeth; Meier, Stuart Kurt

2013-01-01

Cyclic nucleotides (CNs) are intracellular second messengers that play an important role in mediating physiological responses to environmental and developmental signals, in species ranging from bacteria to humans. In response to these signals, CNs are synthesized by nucleotidyl cyclases and then act by binding to and altering the activity of downstream target proteins known as cyclic nucleotide-binding proteins (CNBPs). A number of CNBPs have been identified across kingdoms including transcription factors, protein kinases, phosphodiesterases, and channels, all of which harbor conserved CN-binding domains. In plants however, few CNBPs have been identified as homology searches fail to return plant sequences with significant matches to known CNBPs. Recently, affinity pull-down techniques have been successfully used to identify CNBPs in animals and have provided new insights into CN signaling. The application of these techniques to plants has not yet been extensively explored and offers an alternative approach toward the unbiased discovery of novel CNBP candidates in plants. Here, an affinity pull-down technique for the identification of the plant CN interactome is presented. In summary, the method involves an extraction of plant proteins which is incubated with a CN-bait, followed by a series of increasingly stringent elutions that eliminates proteins in a sequential manner according to their affinity to the bait. The eluted and bait-bound proteins are separated by one-dimensional gel electrophoresis, excised, and digested with trypsin after which the resultant peptides are identified by mass spectrometry - techniques that are commonplace in proteomics experiments. The discovery of plant CNBPs promises to provide valuable insight into the mechanism of CN signal transduction in plants. © Springer Science+Business Media New York 2013.

An affinity pull-down approach to identify the plant cyclic nucleotide interactome

KAUST Repository

Donaldson, Lara Elizabeth

2013-09-03

Cyclic nucleotides (CNs) are intracellular second messengers that play an important role in mediating physiological responses to environmental and developmental signals, in species ranging from bacteria to humans. In response to these signals, CNs are synthesized by nucleotidyl cyclases and then act by binding to and altering the activity of downstream target proteins known as cyclic nucleotide-binding proteins (CNBPs). A number of CNBPs have been identified across kingdoms including transcription factors, protein kinases, phosphodiesterases, and channels, all of which harbor conserved CN-binding domains. In plants however, few CNBPs have been identified as homology searches fail to return plant sequences with significant matches to known CNBPs. Recently, affinity pull-down techniques have been successfully used to identify CNBPs in animals and have provided new insights into CN signaling. The application of these techniques to plants has not yet been extensively explored and offers an alternative approach toward the unbiased discovery of novel CNBP candidates in plants. Here, an affinity pull-down technique for the identification of the plant CN interactome is presented. In summary, the method involves an extraction of plant proteins which is incubated with a CN-bait, followed by a series of increasingly stringent elutions that eliminates proteins in a sequential manner according to their affinity to the bait. The eluted and bait-bound proteins are separated by one-dimensional gel electrophoresis, excised, and digested with trypsin after which the resultant peptides are identified by mass spectrometry - techniques that are commonplace in proteomics experiments. The discovery of plant CNBPs promises to provide valuable insight into the mechanism of CN signal transduction in plants. © Springer Science+Business Media New York 2013.

Structures and short linear motif of disordered transcription factor regions provide clues to the interactome of the cellular hub radical-induced cell death1

DEFF Research Database (Denmark)

O'Shea, Charlotte; Staby, Lasse; Bendsen, Sidsel Krogh

2017-01-01

Intrinsically disordered protein regions (IDRs) lack a well-defined three-dimensional structure, but often facilitate key protein functions. Some interactions between IDRs and folded protein domains rely on short linear motifs (SLiMs). These motifs are challenging to identify, but once found can...... point to larger networks of interactions, such as with proteins that serve as hubs for essential cellular functions. The stress-associated plant protein Radical-Induced Cell Death1 (RCD1) is one such hub, interacting with many transcription factors via their flexible IDRs. To identify the SLiM bound......046 formed different structures or were fuzzy in the complexes. These findings allow us to present a model of the stress-associated RCD1-transcription factor interactome and to contribute to the emerging understanding of the interactions between folded hubs and their intrinsically disordered partners....

Exploitation of complex network topology for link prediction in biological interactomes

KAUST Repository

Alanis Lobato, Gregorio

2014-06-01

The network representation of the interactions between proteins and genes allows for a holistic perspective of the complex machinery underlying the living cell. However, the large number of interacting entities within the cell makes network construction a daunting and arduous task, prone to errors and missing information. Fortunately, the structure of biological networks is not different from that of other complex systems, such as social networks, the world-wide web or power grids, for which growth models have been proposed to better understand their structure and function. This means that we can design tools based on these models in order to exploit the topology of biological interactomes with the aim to construct more complete and reliable maps of the cell. In this work, we propose three novel and powerful approaches for the prediction of interactions in biological networks and conclude that it is possible to mine the topology of these complex system representations and produce reliable and biologically meaningful information that enriches the datasets to which we have access today.

Quantitative assessment of protein activity in orphan tissues and single cells using the metaVIPER algorithm. | Office of Cancer Genomics

Science.gov (United States)

We and others have shown that transition and maintenance of biological states is controlled by master regulator proteins, which can be inferred by interrogating tissue-specific regulatory models (interactomes) with transcriptional signatures, using the VIPER algorithm. Yet, some tissues may lack molecular profiles necessary for interactome inference (orphan tissues), or, as for single cells isolated from heterogeneous samples, their tissue context may be undetermined.

Bioinformatics and moonlighting proteins

Directory of Open Access Journals (Sweden)

Sergio eHernández

2015-06-01

Full Text Available Multitasking or moonlighting is the capability of some proteins to execute two or more biochemical functions. Usually, moonlighting proteins are experimentally revealed by serendipity. For this reason, it would be helpful that Bioinformatics could predict this multifunctionality, especially because of the large amounts of sequences from genome projects. In the present work, we analyse and describe several approaches that use sequences, structures, interactomics and current bioinformatics algorithms and programs to try to overcome this problem. Among these approaches are: a remote homology searches using Psi-Blast, b detection of functional motifs and domains, c analysis of data from protein-protein interaction databases (PPIs, d match the query protein sequence to 3D databases (i.e., algorithms as PISITE, e mutation correlation analysis between amino acids by algorithms as MISTIC. Programs designed to identify functional motif/domains detect mainly the canonical function but usually fail in the detection of the moonlighting one, Pfam and ProDom being the best methods. Remote homology search by Psi-Blast combined with data from interactomics databases (PPIs have the best performance. Structural information and mutation correlation analysis can help us to map the functional sites. Mutation correlation analysis can only be used in very specific situations –it requires the existence of multialigned family protein sequences - but can suggest how the evolutionary process of second function acquisition took place. The multitasking protein database MultitaskProtDB (http://wallace.uab.es/multitask/, previously published by our group, has been used as a benchmark for the all of the analyses.

The drug-minded protein interaction database (DrumPID) for efficient target analysis and drug development.

Science.gov (United States)

Kunz, Meik; Liang, Chunguang; Nilla, Santosh; Cecil, Alexander; Dandekar, Thomas

2016-01-01

The drug-minded protein interaction database (DrumPID) has been designed to provide fast, tailored information on drugs and their protein networks including indications, protein targets and side-targets. Starting queries include compound, target and protein interactions and organism-specific protein families. Furthermore, drug name, chemical structures and their SMILES notation, affected proteins (potential drug targets), organisms as well as diseases can be queried including various combinations and refinement of searches. Drugs and protein interactions are analyzed in detail with reference to protein structures and catalytic domains, related compound structures as well as potential targets in other organisms. DrumPID considers drug functionality, compound similarity, target structure, interactome analysis and organismic range for a compound, useful for drug development, predicting drug side-effects and structure-activity relationships.Database URL:http://drumpid.bioapps.biozentrum.uni-wuerzburg.de. © The Author(s) 2016. Published by Oxford University Press.

A Global Interactome Map of the Dengue Virus NS1 Identifies Virus Restriction and Dependency Host Factors

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Mohamed Lamine Hafirassou

2017-12-01

Full Text Available Dengue virus (DENV infections cause the most prevalent mosquito-borne viral disease worldwide, for which no therapies are available. DENV encodes seven non-structural (NS proteins that co-assemble and recruit poorly characterized host factors to form the DENV replication complex essential for viral infection. Here, we provide a global proteomic analysis of the human host factors that interact with the DENV NS1 protein. Combined with a functional RNAi screen, this study reveals a comprehensive network of host cellular processes involved in DENV infection and identifies DENV host restriction and dependency factors. We highlight an important role of RACK1 and the chaperonin TRiC (CCT and oligosaccharyltransferase (OST complexes during DENV replication. We further show that the OST complex mediates NS1 and NS4B glycosylation, and pharmacological inhibition of its N-glycosylation function strongly impairs DENV infection. In conclusion, our study provides a global interactome of the DENV NS1 and identifies host factors targetable for antiviral therapies.

Introducing the hypothome

DEFF Research Database (Denmark)

Madsen, Claus Desler; Zambach, Sine; Suravajhala, Prashanth

2014-01-01

of doing so is the risk of devaluing the definition of interactomes. By adding proteins that have only been predicted, an interactome can no longer be classified as experimentally verified and the integrity of the interactome will be endured. Therefore, we propose the term 'hypothome' (collection......An interactome is defined as a network of protein-protein interactions built from experimentally verified interactions. Basic science as well as application-based research of potential new drugs can be promoted by including proteins that are only predicted into interactomes. The disadvantage...

Understanding Protein-Protein Interactions Using Local Structural Features

DEFF Research Database (Denmark)

Planas-Iglesias, Joan; Bonet, Jaume; García-García, Javier

2013-01-01

Protein-protein interactions (PPIs) play a relevant role among the different functions of a cell. Identifying the PPI network of a given organism (interactome) is useful to shed light on the key molecular mechanisms within a biological system. In this work, we show the role of structural features...... interacting and non-interacting protein pairs to classify the structural features that sustain the binding (or non-binding) behavior. Our study indicates that not only the interacting region but also the rest of the protein surface are important for the interaction fate. The interpretation...... to score the likelihood of the interaction between two proteins and to develop a method for the prediction of PPIs. We have tested our method on several sets with unbalanced ratios of interactions and non-interactions to simulate real conditions, obtaining accuracies higher than 25% in the most unfavorable...

Interactomes, manufacturomes and relational biology: analogies between systems biology and manufacturing systems

Science.gov (United States)

2011-01-01

Background We review and extend the work of Rosen and Casti who discuss category theory with regards to systems biology and manufacturing systems, respectively. Results We describe anticipatory systems, or long-range feed-forward chemical reaction chains, and compare them to open-loop manufacturing processes. We then close the loop by discussing metabolism-repair systems and describe the rationality of the self-referential equation f = f (f). This relationship is derived from some boundary conditions that, in molecular systems biology, can be stated as the cardinality of the following molecular sets must be about equal: metabolome, genome, proteome. We show that this conjecture is not likely correct so the problem of self-referential mappings for describing the boundary between living and nonliving systems remains an open question. We calculate a lower and upper bound for the number of edges in the molecular interaction network (the interactome) for two cellular organisms and for two manufacturomes for CMOS integrated circuit manufacturing. Conclusions We show that the relevant mapping relations may not be Abelian, and that these problems cannot yet be resolved because the interactomes and manufacturomes are incomplete. PMID:21689427

ProteinAC: a frequency domain technique for analyzing protein dynamics

Science.gov (United States)

Bozkurt Varolgunes, Yasemin; Demir, Alper

2018-03-01

It is widely believed that the interactions of proteins with ligands and other proteins are determined by their dynamic characteristics as opposed to only static, time-invariant processes. We propose a novel computational technique, called ProteinAC (PAC), that can be used to analyze small scale functional protein motions as well as interactions with ligands directly in the frequency domain. PAC was inspired by a frequency domain analysis technique that is widely used in electronic circuit design, and can be applied to both coarse-grained and all-atom models. It can be considered as a generalization of previously proposed static perturbation-response methods, where the frequency of the perturbation becomes the key. We discuss the precise relationship of PAC to static perturbation-response schemes. We show that the frequency of the perturbation may be an important factor in protein dynamics. Perturbations at different frequencies may result in completely different response behavior while magnitude and direction are kept constant. Furthermore, we introduce several novel frequency dependent metrics that can be computed via PAC in order to characterize response behavior. We present results for the ferric binding protein that demonstrate the potential utility of the proposed techniques.

PSAIA – Protein Structure and Interaction Analyzer

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Vlahoviček Kristian

2008-04-01

Full Text Available Abstract Background PSAIA (Protein Structure and Interaction Analyzer was developed to compute geometric parameters for large sets of protein structures in order to predict and investigate protein-protein interaction sites. Results In addition to most relevant established algorithms, PSAIA offers a new method PIADA (Protein Interaction Atom Distance Algorithm for the determination of residue interaction pairs. We found that PIADA produced more satisfactory results than comparable algorithms implemented in PSAIA. Particular advantages of PSAIA include its capacity to combine different methods to detect the locations and types of interactions between residues and its ability, without any further automation steps, to handle large numbers of protein structures and complexes. Generally, the integration of a variety of methods enables PSAIA to offer easier automation of analysis and greater reliability of results. PSAIA can be used either via a graphical user interface or from the command-line. Results are generated in either tabular or XML format. Conclusion In a straightforward fashion and for large sets of protein structures, PSAIA enables the calculation of protein geometric parameters and the determination of location and type for protein-protein interaction sites. XML formatted output enables easy conversion of results to various formats suitable for statistic analysis. Results from smaller data sets demonstrated the influence of geometry on protein interaction sites. Comprehensive analysis of properties of large data sets lead to new information useful in the prediction of protein-protein interaction sites.

MitProNet: A knowledgebase and analysis platform of proteome, interactome and diseases for mammalian mitochondria.

Directory of Open Access Journals (Sweden)

Jiabin Wang

Full Text Available Mitochondrion plays a central role in diverse biological processes in most eukaryotes, and its dysfunctions are critically involved in a large number of diseases and the aging process. A systematic identification of mitochondrial proteomes and characterization of functional linkages among mitochondrial proteins are fundamental in understanding the mechanisms underlying biological functions and human diseases associated with mitochondria. Here we present a database MitProNet which provides a comprehensive knowledgebase for mitochondrial proteome, interactome and human diseases. First an inventory of mammalian mitochondrial proteins was compiled by widely collecting proteomic datasets, and the proteins were classified by machine learning to achieve a high-confidence list of mitochondrial proteins. The current version of MitProNet covers 1124 high-confidence proteins, and the remainders were further classified as middle- or low-confidence. An organelle-specific network of functional linkages among mitochondrial proteins was then generated by integrating genomic features encoded by a wide range of datasets including genomic context, gene expression profiles, protein-protein interactions, functional similarity and metabolic pathways. The functional-linkage network should be a valuable resource for the study of biological functions of mitochondrial proteins and human mitochondrial diseases. Furthermore, we utilized the network to predict candidate genes for mitochondrial diseases using prioritization algorithms. All proteins, functional linkages and disease candidate genes in MitProNet were annotated according to the information collected from their original sources including GO, GEO, OMIM, KEGG, MIPS, HPRD and so on. MitProNet features a user-friendly graphic visualization interface to present functional analysis of linkage networks. As an up-to-date database and analysis platform, MitProNet should be particularly helpful in comprehensive studies of

Data set of interactomes and metabolic pathways of proteins differentially expressed in brains with Alzheimer׳s disease

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Benito Minjarez

2016-06-01

Full Text Available Alzheimer׳s disease is one of the main causes of dementia in the elderly and its frequency is on the rise worldwide. It is considered the result of complex interactions between genetic and environmental factors, being many of them unknown. Therefore, there is a dire necessity for the identification of novel molecular players for the understanding of this disease. In this data article we determined the protein expression profiles of whole protein extracts from cortex regions of brains from patients with Alzheimer׳s disease in comparison to a normal brain. We identified 721 iTRAQ-labeled polypeptides with more than 95% in confidence. We analyzed all proteins that changed in their expression level and located them in the KEGG metabolic pathways, as well as in the mitochondrial complexes of the electron transport chain and ATP synthase. In addition, we analyzed the over- and sub-expressed polypeptides through IPA software, specifically Core I and Biomarkers I modules. Data in this article is related to the research article “Identification of proteins that are differentially expressed in brains with Alzheimer’s disease using iTRAQ labeling and tandem mass spectrometry” (Minjarez et al., 2016 [1].

Interactome analyses identify ties of PrP and its mammalian paralogs to oligomannosidic N-glycans and endoplasmic reticulum-derived chaperones.

Directory of Open Access Journals (Sweden)

Joel C Watts

2009-10-01

Full Text Available The physiological environment which hosts the conformational conversion of the cellular prion protein (PrP(C to disease-associated isoforms has remained enigmatic. A quantitative investigation of the PrP(C interactome was conducted in a cell culture model permissive to prion replication. To facilitate recognition of relevant interactors, the study was extended to Doppel (Prnd and Shadoo (Sprn, two mammalian PrP(C paralogs. Interestingly, this work not only established a similar physiological environment for the three prion protein family members in neuroblastoma cells, but also suggested direct interactions amongst them. Furthermore, multiple interactions between PrP(C and the neural cell adhesion molecule, the laminin receptor precursor, Na/K ATPases and protein disulfide isomerases (PDI were confirmed, thereby reconciling previously separate findings. Subsequent validation experiments established that interactions of PrP(C with PDIs may extend beyond the endoplasmic reticulum and may play a hitherto unrecognized role in the accumulation of PrP(Sc. A simple hypothesis is presented which accounts for the majority of interactions observed in uninfected cells and suggests that PrP(C organizes its molecular environment on account of its ability to bind to adhesion molecules harboring immunoglobulin-like domains, which in turn recognize oligomannose-bearing membrane proteins.

Interactome analyses identify ties of PrP and its mammalian paralogs to oligomannosidic N-glycans and endoplasmic reticulum-derived chaperones.

Science.gov (United States)

Watts, Joel C; Huo, Hairu; Bai, Yu; Ehsani, Sepehr; Jeon, Amy Hye Won; Won, Amy Hye; Shi, Tujin; Daude, Nathalie; Lau, Agnes; Young, Rebecca; Xu, Lei; Carlson, George A; Williams, David; Westaway, David; Schmitt-Ulms, Gerold

2009-10-01

The physiological environment which hosts the conformational conversion of the cellular prion protein (PrP(C)) to disease-associated isoforms has remained enigmatic. A quantitative investigation of the PrP(C) interactome was conducted in a cell culture model permissive to prion replication. To facilitate recognition of relevant interactors, the study was extended to Doppel (Prnd) and Shadoo (Sprn), two mammalian PrP(C) paralogs. Interestingly, this work not only established a similar physiological environment for the three prion protein family members in neuroblastoma cells, but also suggested direct interactions amongst them. Furthermore, multiple interactions between PrP(C) and the neural cell adhesion molecule, the laminin receptor precursor, Na/K ATPases and protein disulfide isomerases (PDI) were confirmed, thereby reconciling previously separate findings. Subsequent validation experiments established that interactions of PrP(C) with PDIs may extend beyond the endoplasmic reticulum and may play a hitherto unrecognized role in the accumulation of PrP(Sc). A simple hypothesis is presented which accounts for the majority of interactions observed in uninfected cells and suggests that PrP(C) organizes its molecular environment on account of its ability to bind to adhesion molecules harboring immunoglobulin-like domains, which in turn recognize oligomannose-bearing membrane proteins.

Expanding the substantial interactome of NEMO using protein microarrays.

LENUS (Irish Health Repository)

Fenner, Beau J

2010-01-01

Signal transduction by the NF-kappaB pathway is a key regulator of a host of cellular responses to extracellular and intracellular messages. The NEMO adaptor protein lies at the top of this pathway and serves as a molecular conduit, connecting signals transmitted from upstream sensors to the downstream NF-kappaB transcription factor and subsequent gene activation. The position of NEMO within this pathway makes it an attractive target from which to search for new proteins that link NF-kappaB signaling to additional pathways and upstream effectors. In this work, we have used protein microarrays to identify novel NEMO interactors. A total of 112 protein interactors were identified, with the most statistically significant hit being the canonical NEMO interactor IKKbeta, with IKKalpha also being identified. Of the novel interactors, more than 30% were kinases, while at least 25% were involved in signal transduction. Binding of NEMO to several interactors, including CALB1, CDK2, SAG, SENP2 and SYT1, was confirmed using GST pulldown assays and coimmunoprecipitation, validating the initial screening approach. Overexpression of CALB1, CDK2 and SAG was found to stimulate transcriptional activation by NF-kappaB, while SYT1 overexpression repressed TNFalpha-dependent NF-kappaB transcriptional activation in human embryonic kidney cells. Corresponding with this finding, RNA silencing of CDK2, SAG and SENP2 reduced NF-kappaB transcriptional activation, supporting a positive role for these proteins in the NF-kappaB pathway. The identification of a host of new NEMO interactors opens up new research opportunities to improve understanding of this essential cell signaling pathway.

Analysis of the robustness of network-based disease-gene prioritization methods reveals redundancy in the human interactome and functional diversity of disease-genes.

Directory of Open Access Journals (Sweden)

Emre Guney

Full Text Available Complex biological systems usually pose a trade-off between robustness and fragility where a small number of perturbations can substantially disrupt the system. Although biological systems are robust against changes in many external and internal conditions, even a single mutation can perturb the system substantially, giving rise to a pathophenotype. Recent advances in identifying and analyzing the sequential variations beneath human disorders help to comprehend a systemic view of the mechanisms underlying various disease phenotypes. Network-based disease-gene prioritization methods rank the relevance of genes in a disease under the hypothesis that genes whose proteins interact with each other tend to exhibit similar phenotypes. In this study, we have tested the robustness of several network-based disease-gene prioritization methods with respect to the perturbations of the system using various disease phenotypes from the Online Mendelian Inheritance in Man database. These perturbations have been introduced either in the protein-protein interaction network or in the set of known disease-gene associations. As the network-based disease-gene prioritization methods are based on the connectivity between known disease-gene associations, we have further used these methods to categorize the pathophenotypes with respect to the recoverability of hidden disease-genes. Our results have suggested that, in general, disease-genes are connected through multiple paths in the human interactome. Moreover, even when these paths are disturbed, network-based prioritization can reveal hidden disease-gene associations in some pathophenotypes such as breast cancer, cardiomyopathy, diabetes, leukemia, parkinson disease and obesity to a greater extend compared to the rest of the pathophenotypes tested in this study. Gene Ontology (GO analysis highlighted the role of functional diversity for such diseases.

Comprehensive RNA Polymerase II Interactomes Reveal Distinct and Varied Roles for Each Phospho-CTD Residue

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Kevin M. Harlen

2016-06-01

Full Text Available Transcription controls splicing and other gene regulatory processes, yet mechanisms remain obscure due to our fragmented knowledge of the molecular connections between the dynamically phosphorylated RNA polymerase II (Pol II C-terminal domain (CTD and regulatory factors. By systematically isolating phosphorylation states of the CTD heptapeptide repeat (Y1S2P3T4S5P6S7, we identify hundreds of protein factors that are differentially enriched, revealing unappreciated connections between the Pol II CTD and co-transcriptional processes. These data uncover a role for threonine-4 in 3′ end processing through control of the transition between cleavage and termination. Furthermore, serine-5 phosphorylation seeds spliceosomal assembly immediately downstream of 3′ splice sites through a direct interaction with spliceosomal subcomplex U1. Strikingly, threonine-4 phosphorylation also impacts splicing by serving as a mark of co-transcriptional spliceosome release and ensuring efficient post-transcriptional splicing genome-wide. Thus, comprehensive Pol II interactomes identify the complex and functional connections between transcription machinery and other gene regulatory complexes.

MEGADOCK 4.0: an ultra-high-performance protein-protein docking software for heterogeneous supercomputers.

Science.gov (United States)

Ohue, Masahito; Shimoda, Takehiro; Suzuki, Shuji; Matsuzaki, Yuri; Ishida, Takashi; Akiyama, Yutaka

2014-11-15

The application of protein-protein docking in large-scale interactome analysis is a major challenge in structural bioinformatics and requires huge computing resources. In this work, we present MEGADOCK 4.0, an FFT-based docking software that makes extensive use of recent heterogeneous supercomputers and shows powerful, scalable performance of >97% strong scaling. MEGADOCK 4.0 is written in C++ with OpenMPI and NVIDIA CUDA 5.0 (or later) and is freely available to all academic and non-profit users at: http://www.bi.cs.titech.ac.jp/megadock. akiyama@cs.titech.ac.jp Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

Proteins interacting with cloning scars: a source of false positive protein-protein interactions.

Science.gov (United States)

Banks, Charles A S; Boanca, Gina; Lee, Zachary T; Florens, Laurence; Washburn, Michael P

2015-02-23

A common approach for exploring the interactome, the network of protein-protein interactions in cells, uses a commercially available ORF library to express affinity tagged bait proteins; these can be expressed in cells and endogenous cellular proteins that copurify with the bait can be identified as putative interacting proteins using mass spectrometry. Control experiments can be used to limit false-positive results, but in many cases, there are still a surprising number of prey proteins that appear to copurify specifically with the bait. Here, we have identified one source of false-positive interactions in such studies. We have found that a combination of: 1) the variable sequence of the C-terminus of the bait with 2) a C-terminal valine "cloning scar" present in a commercially available ORF library, can in some cases create a peptide motif that results in the aberrant co-purification of endogenous cellular proteins. Control experiments may not identify false positives resulting from such artificial motifs, as aberrant binding depends on sequences that vary from one bait to another. It is possible that such cryptic protein binding might occur in other systems using affinity tagged proteins; this study highlights the importance of conducting careful follow-up studies where novel protein-protein interactions are suspected.

InSilico Proteomics System: Integration and Application of Protein and Protein-Protein Interaction Data using Microsoft .NET

Directory of Open Access Journals (Sweden)

Straßer Wolfgang

2006-12-01

Full Text Available In the last decades, biological databases became the major knowledge resource for researchers in the field of molecular biology. The distribution of information among these databases is one of the major problems. An overview about the subject area of data access and representation of protein and protein-protein interaction data within public biological databases is described. For a comprehensive and consistent way of searching and analysing integrated protein and protein-protein interaction data, the InSilico Proteomics (ISP project has been initiated. Its three main objectives are (1 to provide an integrated knowledge pool for data investigation and global network analysis functions for a better understanding of a cell’s interactome, (2 employment of public data for plausibility analysis and validation of in-house experimental data and (3 testing the applicability of Microsoft’s .NET architecture for bioinformatics applications. Data integrated into the ISP database can be queried through the Web portal PRIMOS (PRotein Interaction and MOlecule Search which is freely available at http://biomis.fh-hagenberg.at/isp/primos.

Hepatitis C virus infection protein network.

Science.gov (United States)

de Chassey, B; Navratil, V; Tafforeau, L; Hiet, M S; Aublin-Gex, A; Agaugué, S; Meiffren, G; Pradezynski, F; Faria, B F; Chantier, T; Le Breton, M; Pellet, J; Davoust, N; Mangeot, P E; Chaboud, A; Penin, F; Jacob, Y; Vidalain, P O; Vidal, M; André, P; Rabourdin-Combe, C; Lotteau, V

2008-01-01

A proteome-wide mapping of interactions between hepatitis C virus (HCV) and human proteins was performed to provide a comprehensive view of the cellular infection. A total of 314 protein-protein interactions between HCV and human proteins was identified by yeast two-hybrid and 170 by literature mining. Integration of this data set into a reconstructed human interactome showed that cellular proteins interacting with HCV are enriched in highly central and interconnected proteins. A global analysis on the basis of functional annotation highlighted the enrichment of cellular pathways targeted by HCV. A network of proteins associated with frequent clinical disorders of chronically infected patients was constructed by connecting the insulin, Jak/STAT and TGFbeta pathways with cellular proteins targeted by HCV. CORE protein appeared as a major perturbator of this network. Focal adhesion was identified as a new function affected by HCV, mainly by NS3 and NS5A proteins.

Label-free LC-MSe in tissue and serum reveals protein networks underlying differences between benign and malignant serous ovarian tumors.

Directory of Open Access Journals (Sweden)

Wouter Wegdam

Full Text Available PURPOSE: To identify proteins and (molecular/biological pathways associated with differences between benign and malignant epithelial ovarian tumors. EXPERIMENTAL PROCEDURES: Serum of six patients with a serous adenocarcinoma of the ovary was collected before treatment, with a control group consisting of six matched patients with a serous cystadenoma. In addition to the serum, homogeneous regions of cells exhibiting uniform histology were isolated from benign and cancerous tissue by laser microdissection. We subsequently employed label-free liquid chromatography tandem mass spectrometry (LC-MSe to identify proteins in these serum and tissues samples. Analyses of differential expression between samples were performed using Bioconductor packages and in-house scripts in the statistical software package R. Hierarchical clustering and pathway enrichment analyses were performed, as well as network enrichment and interactome analysis using MetaCore. RESULTS: In total, we identified 20 and 71 proteins that were significantly differentially expressed between benign and malignant serum and tissue samples, respectively. The differentially expressed protein sets in serum and tissue largely differed with only 2 proteins in common. MetaCore network analysis, however inferred GCR-alpha and Sp1 as common transcriptional regulators. Interactome analysis highlighted 14-3-3 zeta/delta, 14-3-3 beta/alpha, Alpha-actinin 4, HSP60, and PCBP1 as critical proteins in the tumor proteome signature based on their relative overconnectivity. The data have been deposited to the ProteomeXchange with identifier PXD001084. DISCUSSION: Our analysis identified proteins with both novel and previously known associations to ovarian cancer biology. Despite the small overlap between differentially expressed protein sets in serum and tissue, APOA1 and Serotransferrin were significantly lower expressed in both serum and cancer tissue samples, suggesting a tissue-derived effect in serum

Conserved salt-bridge competition triggered by phosphorylation regulates the protein interactome

KAUST Repository

Skinner, John J.

2017-12-05

Phosphorylation is a major regulator of protein interactions; however, the mechanisms by which regulation occurs are not well understood. Here we identify a salt-bridge competition or “theft” mechanism that enables a phospho-triggered swap of protein partners by Raf Kinase Inhibitory Protein (RKIP). RKIP transitions from inhibiting Raf-1 to inhibiting G-protein–coupled receptor kinase 2 upon phosphorylation, thereby bridging MAP kinase and G-Protein–Coupled Receptor signaling. NMR and crystallography indicate that a phosphoserine, but not a phosphomimetic, competes for a lysine from a preexisting salt bridge, initiating a partial unfolding event and promoting new protein interactions. Structural elements underlying the theft occurred early in evolution and are found in 10% of homo-oligomers and 30% of hetero-oligomers including Bax, Troponin C, and Early Endosome Antigen 1. In contrast to a direct recognition of phosphorylated residues by binding partners, the salt-bridge theft mechanism represents a facile strategy for promoting or disrupting protein interactions using solvent-accessible residues, and it can provide additional specificity at protein interfaces through local unfolding or conformational change.

Conserved salt-bridge competition triggered by phosphorylation regulates the protein interactome

KAUST Repository

Skinner, John J.; Wang, Sheng; Lee, Jiyoung; Ong, Colin; Sommese, Ruth; Sivaramakrishnan, Sivaraj; Koelmel, Wolfgang; Hirschbeck, Maria; Schindelin, Hermann; Kisker, Caroline; Lorenz, Kristina; Sosnick, Tobin R.; Rosner, Marsha Rich

2017-01-01

Phosphorylation is a major regulator of protein interactions; however, the mechanisms by which regulation occurs are not well understood. Here we identify a salt-bridge competition or “theft” mechanism that enables a phospho-triggered swap of protein partners by Raf Kinase Inhibitory Protein (RKIP). RKIP transitions from inhibiting Raf-1 to inhibiting G-protein–coupled receptor kinase 2 upon phosphorylation, thereby bridging MAP kinase and G-Protein–Coupled Receptor signaling. NMR and crystallography indicate that a phosphoserine, but not a phosphomimetic, competes for a lysine from a preexisting salt bridge, initiating a partial unfolding event and promoting new protein interactions. Structural elements underlying the theft occurred early in evolution and are found in 10% of homo-oligomers and 30% of hetero-oligomers including Bax, Troponin C, and Early Endosome Antigen 1. In contrast to a direct recognition of phosphorylated residues by binding partners, the salt-bridge theft mechanism represents a facile strategy for promoting or disrupting protein interactions using solvent-accessible residues, and it can provide additional specificity at protein interfaces through local unfolding or conformational change.

Analyzing the simplicial decomposition of spatial protein structures

Directory of Open Access Journals (Sweden)

Szabadka Zoltán

2008-02-01

Full Text Available Abstract Background The fast growing Protein Data Bank contains the three-dimensional description of more than 45000 protein- and nucleic-acid structures today. The large majority of the data in the PDB are measured by X-ray crystallography by thousands of researchers in millions of work-hours. Unfortunately, lots of structural errors, bad labels, missing atoms, falsely identified chains and groups make dificult the automated processing of this treasury of structural biological data. Results After we performed a rigorous re-structuring of the whole PDB on graph-theoretical basis, we created the RS-PDB (Rich-Structure PDB database. Using this cleaned and repaired database, we defined simplicial complexes on the heavy-atoms of the PDB, and analyzed the tetrahedra for geometric properties. Conclusion We have found surprisingly characteristic differences between simplices with atomic vertices of different types, and between the atomic neighborhoods – described also by simplices – of different ligand atoms in proteins.

Predicting protein-protein interactions from multimodal biological data sources via nonnegative matrix tri-factorization.

Science.gov (United States)

Wang, Hua; Huang, Heng; Ding, Chris; Nie, Feiping

2013-04-01

Protein interactions are central to all the biological processes and structural scaffolds in living organisms, because they orchestrate a number of cellular processes such as metabolic pathways and immunological recognition. Several high-throughput methods, for example, yeast two-hybrid system and mass spectrometry method, can help determine protein interactions, which, however, suffer from high false-positive rates. Moreover, many protein interactions predicted by one method are not supported by another. Therefore, computational methods are necessary and crucial to complete the interactome expeditiously. In this work, we formulate the problem of predicting protein interactions from a new mathematical perspective--sparse matrix completion, and propose a novel nonnegative matrix factorization (NMF)-based matrix completion approach to predict new protein interactions from existing protein interaction networks. Through using manifold regularization, we further develop our method to integrate different biological data sources, such as protein sequences, gene expressions, protein structure information, etc. Extensive experimental results on four species, Saccharomyces cerevisiae, Drosophila melanogaster, Homo sapiens, and Caenorhabditis elegans, have shown that our new methods outperform related state-of-the-art protein interaction prediction methods.

Interactome maps of mouse gene regulatory domains reveal basic principles of transcriptional regulation

DEFF Research Database (Denmark)

Kieffer-Kwon, Kyong-Rim; Tang, Zhonghui; Mathe, Ewy

2013-01-01

IA-PET technologies to map the promoter-enhancer interactomes of pluripotent ES cells and differentiated B lymphocytes. We confirm that enhancer usage varies widely across tissues. Unexpectedly, we find that this feature extends to broadly transcribed genes, including Myc and Pim1 cell-cycle regulators, which...... associate with an entirely different set of enhancers in ES and B cells. By means of high-resolution CpG methylomes, genome editing, and digital footprinting, we show that these enhancers recruit lineage-determining factors. Furthermore, we demonstrate that the turning on and off of enhancers during...

Protein interaction networks by proteome peptide scanning.

Directory of Open Access Journals (Sweden)

Christiane Landgraf

2004-01-01

simultaneously analyzed in an array format, the likelihood of each interaction occurring in any given physiological settings can be evaluated. WISE can be easily extended to a variety of protein interaction domains, including those binding to modified peptides, thereby offering a powerful proteomic tool to help completing a full description of the cell interactome.

The comprehensive native interactome of a fully functional tagged prion protein.

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Dorothea Rutishauser

Full Text Available The enumeration of the interaction partners of the cellular prion protein, PrP(C, may help clarifying its elusive molecular function. Here we added a carboxy proximal myc epitope tag to PrP(C. When expressed in transgenic mice, PrP(myc carried a GPI anchor, was targeted to lipid rafts, and was glycosylated similarly to PrP(C. PrP(myc antagonized the toxicity of truncated PrP, restored prion infectibility of PrP(C-deficient mice, and was physically incorporated into PrP(Sc aggregates, indicating that it possessed all functional characteristics of genuine PrP(C. We then immunopurified myc epitope-containing protein complexes from PrP(myc transgenic mouse brains. Gentle differential elution with epitope-mimetic decapeptides, or a scrambled version thereof, yielded 96 specifically released proteins. Quantitative mass spectrometry with isotope-coded tags identified seven proteins which co-eluted equimolarly with PrP(C and may represent component of a multiprotein complex. Selected PrP(C interactors were validated using independent methods. Several of these proteins appear to exert functions in axomyelinic maintenance.

PerturbationAnalyzer: a tool for investigating the effects of concentration perturbation on protein interaction networks.

Science.gov (United States)

Li, Fei; Li, Peng; Xu, Wenjian; Peng, Yuxing; Bo, Xiaochen; Wang, Shengqi

2010-01-15

The propagation of perturbations in protein concentration through a protein interaction network (PIN) can shed light on network dynamics and function. In order to facilitate this type of study, PerturbationAnalyzer, which is an open source plugin for Cytoscape, has been developed. PerturbationAnalyzer can be used in manual mode for simulating user-defined perturbations, as well as in batch mode for evaluating network robustness and identifying significant proteins that cause large propagation effects in the PINs when their concentrations are perturbed. Results from PerturbationAnalyzer can be represented in an intuitive and customizable way and can also be exported for further exploration. PerturbationAnalyzer has great potential in mining the design principles of protein networks, and may be a useful tool for identifying drug targets. PerturbationAnalyzer can be accessed from the Cytoscape web site http://www.cytoscape.org/plugins/index.php or http://biotech.bmi.ac.cn/PerturbationAnalyzer. Supplementary data are available at Bioinformatics online.

Protein-protein interactions and cancer: targeting the central dogma.

Science.gov (United States)

Garner, Amanda L; Janda, Kim D

2011-01-01

Between 40,000 and 200,000 protein-protein interactions have been predicted to exist within the human interactome. As these interactions are of a critical nature in many important cellular functions and their dysregulation is causal of disease, the modulation of these binding events has emerged as a leading, yet difficult therapeutic arena. In particular, the targeting of protein-protein interactions relevant to cancer is of fundamental importance as the tumor-promoting function of several aberrantly expressed proteins in the cancerous state is directly resultant of its ability to interact with a protein-binding partner. Of significance, these protein complexes play a crucial role in each of the steps of the central dogma of molecular biology, the fundamental processes of genetic transmission. With the many important discoveries being made regarding the mechanisms of these genetic process, the identification of new chemical probes are needed to better understand and validate the druggability of protein-protein interactions related to the central dogma. In this review, we provide an overview of current small molecule-based protein-protein interaction inhibitors for each stage of the central dogma: transcription, mRNA splicing and translation. Importantly, through our analysis we have uncovered a lack of necessary probes targeting mRNA splicing and translation, thus, opening up the possibility for expansion of these fields.

POINeT: protein interactome with sub-network analysis and hub prioritization

Directory of Open Access Journals (Sweden)

Lai Jin-Mei

2009-04-01

Full Text Available Abstract Background Protein-protein interactions (PPIs are critical to every aspect of biological processes. Expansion of all PPIs from a set of given queries often results in a complex PPI network lacking spatiotemporal consideration. Moreover, the reliability of available PPI resources, which consist of low- and high-throughput data, for network construction remains a significant challenge. Even though a number of software tools are available to facilitate PPI network analysis, an integrated tool is crucial to alleviate the burden on querying across multiple web servers and software tools. Results We have constructed an integrated web service, POINeT, to simplify the process of PPI searching, analysis, and visualization. POINeT merges PPI and tissue-specific expression data from multiple resources. The tissue-specific PPIs and the numbers of research papers supporting the PPIs can be filtered with user-adjustable threshold values and are dynamically updated in the viewer. The network constructed in POINeT can be readily analyzed with, for example, the built-in centrality calculation module and an integrated network viewer. Nodes in global networks can also be ranked and filtered using various network analysis formulas, i.e., centralities. To prioritize the sub-network, we developed a ranking filtered method (S3 to uncover potential novel mediators in the midbody network. Several examples are provided to illustrate the functionality of POINeT. The network constructed from four schizophrenia risk markers suggests that EXOC4 might be a novel marker for this disease. Finally, a liver-specific PPI network has been filtered with adult and fetal liver expression profiles. Conclusion The functionalities provided by POINeT are highly improved compared to previous version of POINT. POINeT enables the identification and ranking of potential novel genes involved in a sub-network. Combining with tissue-specific gene expression profiles, PPIs specific to

In silico identification of essential proteins in Corynebacterium pseudotuberculosis based on protein

DEFF Research Database (Denmark)

Folador, Edson Luiz; de Carvalho, Paulo Vinícius Sanches Daltro; Silva, Wanderson Marques

2016-01-01

BACKGROUND: Corynebacterium pseudotuberculosis (Cp) is a gram-positive bacterium that is classified into equi and ovis serovars. The serovar ovis is the etiological agent of caseous lymphadenitis, a chronic infection affecting sheep and goats, causing economic losses due to carcass condemnation...... of the potential Cp interactome and to identify potentially essential proteins serving as putative drug targets. On average, we predict 16,669 interactions for each of the nine strains (with 15,495 interactions shared among all strains). An in silico sanity check suggests that the potential networks were...... not formed by spurious interactions but have a strong biological bias. With the inferred Cp networks we identify 181 essential proteins, among which 41 are non-host homologous. CONCLUSIONS: The list of candidate interactions of the Cp strains lay the basis for developing novel hypotheses and designing...

Infrared analyzers for breast milk analysis: fat levels can influence the accuracy of protein measurements.

Science.gov (United States)

Kwan, Celia; Fusch, Gerhard; Bahonjic, Aldin; Rochow, Niels; Fusch, Christoph

2017-10-26

Currently, there is a growing interest in lacto-engineering in the neonatal intensive care unit, using infrared milk analyzers to rapidly measure the macronutrient content in breast milk before processing and feeding it to preterm infants. However, there is an overlap in the spectral information of different macronutrients, so they can potentially impact the robustness of the measurement. In this study, we investigate whether the measurement of protein is dependent on the levels of fat present while using an infrared milk analyzer. Breast milk samples (n=25) were measured for fat and protein content before and after being completely defatted by centrifugation, using chemical reference methods and near-infrared milk analyzer (Unity SpectraStar) with two different calibration algorithms provided by the manufacturer (released 2009 and 2015). While the protein content remained unchanged, as measured by elemental analysis, measurements by infrared milk analyzer show a difference in protein measurements dependent on fat content; high fat content can lead to falsely high protein content. This difference is less pronounced when measured using the more recent calibration algorithm. Milk analyzer users must be cautious of their devices' measurements, especially if they are changing the matrix of breast milk using more advanced lacto-engineering.

Lukasiewicz-Topos Models of Neural Networks, Cell Genome and Interactome Nonlinear Dynamic Models

CERN Document Server

Baianu, I C

2004-01-01

A categorical and Lukasiewicz-Topos framework for Lukasiewicz Algebraic Logic models of nonlinear dynamics in complex functional systems such as neural networks, genomes and cell interactomes is proposed. Lukasiewicz Algebraic Logic models of genetic networks and signaling pathways in cells are formulated in terms of nonlinear dynamic systems with n-state components that allow for the generalization of previous logical models of both genetic activities and neural networks. An algebraic formulation of variable 'next-state functions' is extended to a Lukasiewicz Topos with an n-valued Lukasiewicz Algebraic Logic subobject classifier description that represents non-random and nonlinear network activities as well as their transformations in developmental processes and carcinogenesis.

Analysis of damaged DNA / proteins interactions: Methodological optimizations and applications to DNA lesions induced by platinum anticancer drugs; Analyse des interactions ADN lese / proteines: Optimisations methodologiques et applications aux dommages de l'ADN engendres par les derives du platine

Energy Technology Data Exchange (ETDEWEB)

Bounaix Morand du Puch, Ch

2010-10-15

DNA lesions contribute to the alteration of DNA structure, thereby inhibiting essential cellular processes. Such alterations may be beneficial for chemotherapies, for example in the case of platinum anticancer agents. They generate bulky adducts that, if not repaired, ultimately cause apoptosis. A better understanding of the biological response to such molecules can be obtained through the study of proteins that directly interact with the damages. These proteins constitute the DNA lesions interactome. This thesis presents the development of tools aiming at increasing the list of platinum adduct-associated proteins. Firstly, we designed a ligand fishing system made of damaged plasmids immobilized onto magnetic beads. Three platinum drugs were selected for our study: cisplatin, oxali-platin and satra-platin. Following exposure of the trap to nuclear extracts from HeLa cancer cells and identification of retained proteins by proteomics, we obtained already known candidates (HMGB1, hUBF, FACT complex) but also 29 new members of the platinated-DNA interactome. Among them, we noted the presence of PNUTS, TOX4 and WDR82, which associate to form the recently-discovered PTW/PP complex. Their capture was then confirmed with a second model, namely breast cancer cell line MDA MB 231, and the biological consequences of such an interaction now need to be elucidated. Secondly, we adapted a SPRi bio-chip to the study of platinum-damaged DNA/proteins interactions. Affinity of HMGB1 and newly characterized TOX4 for adducts generated by our three platinum drugs could be validated thanks to the bio-chip. Finally, we used our tools, as well as analytical chemistry and biochemistry methods, to evaluate the role of DDB2 (a factor involved in the recognition of UV-induced lesions) in the repair of cisplatin adducts. Our experiments using MDA MB 231 cells differentially expressing DDB2 showed that this protein is not responsible for the repair of platinum damages. Instead, it appears to act

Exploiting conformational ensembles in modeling protein-protein interactions on the proteome scale

Science.gov (United States)

Kuzu, Guray; Gursoy, Attila; Nussinov, Ruth; Keskin, Ozlem

2013-01-01

Cellular functions are performed through protein-protein interactions; therefore, identification of these interactions is crucial for understanding biological processes. Recent studies suggest that knowledge-based approaches are more useful than ‘blind’ docking for modeling at large scales. However, a caveat of knowledge-based approaches is that they treat molecules as rigid structures. The Protein Data Bank (PDB) offers a wealth of conformations. Here, we exploited ensemble of the conformations in predictions by a knowledge-based method, PRISM. We tested ‘difficult’ cases in a docking-benchmark dataset, where the unbound and bound protein forms are structurally different. Considering alternative conformations for each protein, the percentage of successfully predicted interactions increased from ~26% to 66%, and 57% of the interactions were successfully predicted in an ‘unbiased’ scenario, in which data related to the bound forms were not utilized. If the appropriate conformation, or relevant template interface, is unavailable in the PDB, PRISM could not predict the interaction successfully. The pace of the growth of the PDB promises a rapid increase of ensemble conformations emphasizing the merit of such knowledge-based ensemble strategies for higher success rates in protein-protein interaction predictions on an interactome-scale. We constructed the structural network of ERK interacting proteins as a case study. PMID:23590674

Characterization of host proteins interacting with the lymphocytic choriomeningitis virus L protein.

Science.gov (United States)

Khamina, Kseniya; Lercher, Alexander; Caldera, Michael; Schliehe, Christopher; Vilagos, Bojan; Sahin, Mehmet; Kosack, Lindsay; Bhattacharya, Anannya; Májek, Peter; Stukalov, Alexey; Sacco, Roberto; James, Leo C; Pinschewer, Daniel D; Bennett, Keiryn L; Menche, Jörg; Bergthaler, Andreas

2017-12-01

RNA-dependent RNA polymerases (RdRps) play a key role in the life cycle of RNA viruses and impact their immunobiology. The arenavirus lymphocytic choriomeningitis virus (LCMV) strain Clone 13 provides a benchmark model for studying chronic infection. A major genetic determinant for its ability to persist maps to a single amino acid exchange in the viral L protein, which exhibits RdRp activity, yet its functional consequences remain elusive. To unravel the L protein interactions with the host proteome, we engineered infectious L protein-tagged LCMV virions by reverse genetics. A subsequent mass-spectrometric analysis of L protein pulldowns from infected human cells revealed a comprehensive network of interacting host proteins. The obtained LCMV L protein interactome was bioinformatically integrated with known host protein interactors of RdRps from other RNA viruses, emphasizing interconnected modules of human proteins. Functional characterization of selected interactors highlighted proviral (DDX3X) as well as antiviral (NKRF, TRIM21) host factors. To corroborate these findings, we infected Trim21-/- mice with LCMV and found impaired virus control in chronic infection. These results provide insights into the complex interactions of the arenavirus LCMV and other viral RdRps with the host proteome and contribute to a better molecular understanding of how chronic viruses interact with their host.

Analysis of damaged DNA / proteins interactions: Methodological optimizations and applications to DNA lesions induced by platinum anticancer drugs

International Nuclear Information System (INIS)

Bounaix Morand du Puch, Ch

2010-10-01

DNA lesions contribute to the alteration of DNA structure, thereby inhibiting essential cellular processes. Such alterations may be beneficial for chemotherapies, for example in the case of platinum anticancer agents. They generate bulky adducts that, if not repaired, ultimately cause apoptosis. A better understanding of the biological response to such molecules can be obtained through the study of proteins that directly interact with the damages. These proteins constitute the DNA lesions interactome. This thesis presents the development of tools aiming at increasing the list of platinum adduct-associated proteins. Firstly, we designed a ligand fishing system made of damaged plasmids immobilized onto magnetic beads. Three platinum drugs were selected for our study: cisplatin, oxali-platin and satra-platin. Following exposure of the trap to nuclear extracts from HeLa cancer cells and identification of retained proteins by proteomics, we obtained already known candidates (HMGB1, hUBF, FACT complex) but also 29 new members of the platinated-DNA interactome. Among them, we noted the presence of PNUTS, TOX4 and WDR82, which associate to form the recently-discovered PTW/PP complex. Their capture was then confirmed with a second model, namely breast cancer cell line MDA MB 231, and the biological consequences of such an interaction now need to be elucidated. Secondly, we adapted a SPRi bio-chip to the study of platinum-damaged DNA/proteins interactions. Affinity of HMGB1 and newly characterized TOX4 for adducts generated by our three platinum drugs could be validated thanks to the bio-chip. Finally, we used our tools, as well as analytical chemistry and biochemistry methods, to evaluate the role of DDB2 (a factor involved in the recognition of UV-induced lesions) in the repair of cisplatin adducts. Our experiments using MDA MB 231 cells differentially expressing DDB2 showed that this protein is not responsible for the repair of platinum damages. Instead, it appears to act

Positive Selection and Centrality in the Yeast and Fly Protein-Protein Interaction Networks

Directory of Open Access Journals (Sweden)

Sandip Chakraborty

2016-01-01

Full Text Available Proteins within a molecular network are expected to be subject to different selective pressures depending on their relative hierarchical positions. However, it is not obvious what genes within a network should be more likely to evolve under positive selection. On one hand, only mutations at genes with a relatively high degree of control over adaptive phenotypes (such as those encoding highly connected proteins are expected to be “seen” by natural selection. On the other hand, a high degree of pleiotropy at these genes is expected to hinder adaptation. Previous analyses of the human protein-protein interaction network have shown that genes under long-term, recurrent positive selection (as inferred from interspecific comparisons tend to act at the periphery of the network. It is unknown, however, whether these trends apply to other organisms. Here, we show that long-term positive selection has preferentially targeted the periphery of the yeast interactome. Conversely, in flies, genes under positive selection encode significantly more connected and central proteins. These observations are not due to covariation of genes’ adaptability and centrality with confounding factors. Therefore, the distribution of proteins encoded by genes under recurrent positive selection across protein-protein interaction networks varies from one species to another.

Intranuclear interactomic inhibition of NF-κB suppresses LPS-induced severe sepsis

International Nuclear Information System (INIS)

Park, Sung-Dong; Cheon, So Yeong; Park, Tae-Yoon; Shin, Bo-Young; Oh, Hyunju; Ghosh, Sankar; Koo, Bon-Nyeo; Lee, Sang-Kyou

2015-01-01

Suppression of nuclear factor-κB (NF-κB) activation, which is best known as a major regulator of innate and adaptive immune responses, is a potent strategy for the treatment of endotoxic sepsis. To inhibit NF-κB functions, we designed the intra-nuclear transducible form of transcription modulation domain (TMD) of RelA (p65), called nt-p65-TMD, which can be delivered effectively into the nucleus without influencing the cell viability, and work as interactomic inhibitors via disruption of the endogenous p65-mediated transcription complex. nt-p65-TMD effectively inhibited the secretion of pro-inflammatory cytokines, including TNF-α, IL-1β, or IL-6 from BV2 microglia cells stimulated by lipopolysaccharide (LPS). nt-p65-TMD did not inhibit tyrosine phosphorylation of signaling mediators such as ZAP-70, p38, JNK, or ERK involved in T cell activation, but was capable of suppressing the transcriptional activity of NF-κB without the functional effect on that of NFAT upon T-cell receptor (TCR) stimulation. The transduced nt-p65-TMD in T cell did not affect the expression of CD69, however significantly inhibited the secretion of T cell-specific cytokines such as IL-2, IFN-γ, IL-4, IL-17A, or IL-10. Systemic administration of nt-p65-TMD showed a significant therapeutic effect on LPS-induced sepsis model by inhibiting pro-inflammatory cytokines secretion. Therefore, nt-p65-TMD can be a novel therapeutics for the treatment of various inflammatory diseases, including sepsis, where a transcription factor has a key role in pathogenesis, and further allows us to discover new functions of p65 under normal physiological condition without genetic alteration. - Highlights: • The nt-p65-TMD is intra-nuclear interactomic inhibitor of endogenous p65. • The nt-p65-TMD effectively inhibited the secretion of pro-inflammatory cytokines. • The excellent therapeutic potential of nt-p65-TMD was confirmed in sepsis model

Intranuclear interactomic inhibition of NF-κB suppresses LPS-induced severe sepsis

Energy Technology Data Exchange (ETDEWEB)

Park, Sung-Dong [Translational Research Center for Protein Function Control, College of Life Science and Biotechnology, Yonsei University, Seoul 120-749 (Korea, Republic of); Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul 120-749 (Korea, Republic of); Cheon, So Yeong [Department of Anesthesiology and Pain Medicine, Anesthesia and Pain Research Institute, Yonsei University College of Medicine, Seoul 120-752 (Korea, Republic of); Park, Tae-Yoon; Shin, Bo-Young [Translational Research Center for Protein Function Control, College of Life Science and Biotechnology, Yonsei University, Seoul 120-749 (Korea, Republic of); Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul 120-749 (Korea, Republic of); Oh, Hyunju; Ghosh, Sankar [Department of Microbiology and Immunology, College of Physicians and Surgeons, Columbia University, New York, NY 10032 (United States); Koo, Bon-Nyeo, E-mail: koobn@yuhs.ac [Department of Anesthesiology and Pain Medicine, Anesthesia and Pain Research Institute, Yonsei University College of Medicine, Seoul 120-752 (Korea, Republic of); Lee, Sang-Kyou, E-mail: sjrlee@yonsei.ac.kr [Translational Research Center for Protein Function Control, College of Life Science and Biotechnology, Yonsei University, Seoul 120-749 (Korea, Republic of); Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul 120-749 (Korea, Republic of)

2015-08-28

Suppression of nuclear factor-κB (NF-κB) activation, which is best known as a major regulator of innate and adaptive immune responses, is a potent strategy for the treatment of endotoxic sepsis. To inhibit NF-κB functions, we designed the intra-nuclear transducible form of transcription modulation domain (TMD) of RelA (p65), called nt-p65-TMD, which can be delivered effectively into the nucleus without influencing the cell viability, and work as interactomic inhibitors via disruption of the endogenous p65-mediated transcription complex. nt-p65-TMD effectively inhibited the secretion of pro-inflammatory cytokines, including TNF-α, IL-1β, or IL-6 from BV2 microglia cells stimulated by lipopolysaccharide (LPS). nt-p65-TMD did not inhibit tyrosine phosphorylation of signaling mediators such as ZAP-70, p38, JNK, or ERK involved in T cell activation, but was capable of suppressing the transcriptional activity of NF-κB without the functional effect on that of NFAT upon T-cell receptor (TCR) stimulation. The transduced nt-p65-TMD in T cell did not affect the expression of CD69, however significantly inhibited the secretion of T cell-specific cytokines such as IL-2, IFN-γ, IL-4, IL-17A, or IL-10. Systemic administration of nt-p65-TMD showed a significant therapeutic effect on LPS-induced sepsis model by inhibiting pro-inflammatory cytokines secretion. Therefore, nt-p65-TMD can be a novel therapeutics for the treatment of various inflammatory diseases, including sepsis, where a transcription factor has a key role in pathogenesis, and further allows us to discover new functions of p65 under normal physiological condition without genetic alteration. - Highlights: • The nt-p65-TMD is intra-nuclear interactomic inhibitor of endogenous p65. • The nt-p65-TMD effectively inhibited the secretion of pro-inflammatory cytokines. • The excellent therapeutic potential of nt-p65-TMD was confirmed in sepsis model.

Predicting Protein-Protein Interactions Using BiGGER: Case Studies

Directory of Open Access Journals (Sweden)

Rui M. Almeida

2016-08-01

Full Text Available The importance of understanding interactomes makes preeminent the study of protein interactions and protein complexes. Traditionally, protein interactions have been elucidated by experimental methods or, with lower impact, by simulation with protein docking algorithms. This article describes features and applications of the BiGGER docking algorithm, which stands at the interface of these two approaches. BiGGER is a user-friendly docking algorithm that was specifically designed to incorporate experimental data at different stages of the simulation, to either guide the search for correct structures or help evaluate the results, in order to combine the reliability of hard data with the convenience of simulations. Herein, the applications of BiGGER are described by illustrative applications divided in three Case Studies: (Case Study A in which no specific contact data is available; (Case Study B when different experimental data (e.g., site-directed mutagenesis, properties of the complex, NMR chemical shift perturbation mapping, electron tunneling on one of the partners is available; and (Case Study C when experimental data are available for both interacting surfaces, which are used during the search and/or evaluation stage of the docking. This algorithm has been extensively used, evidencing its usefulness in a wide range of different biological research fields.

Analyzing import intermediates of mitochondrial proteins by blue native gel electrophoresis.

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Waizenegger, Thomas; Rapaport, Doron

2007-01-01

Blue native gel electrophoresis (BNGE) is a powerful tool for analyzing native protein complexes from biological membranes as well as water-soluble proteins. It can be used for determining relative molecular masses of protein complexes and their subunit composition and for the detection of subcomplexes. We describe the analysis by BNGE of in vitro import reactions composed of radiolabeled precursor proteins and isolated mitochondria. Such an analysis is a powerful tool to follow import intermediates and to study assembly of protein complexes. Analysis of import reactions by BNGE provides information on the molecular mass of the complex with which the imported precursor is associated. In addition, components of such a complex can be identified by incubating the mitochondrial lysate with either soluble antibodies or antibodies coupled to protein A matrix. The binding of soluble antibodies to specific complexes results in an observed shift in their apparent molecular mass (antibody shift). Alternatively, addition of matrix-bound antibodies followed by removal of the matrix from the mixture will result in depletion of the specific complex from the mitochondrial lysate (antibody depletion). The experimental details of these techniques are described.

A Human XPC Protein Interactome—A Resource

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Abigail Lubin

2013-12-01

Full Text Available Global genome nucleotide excision repair (GG-NER is responsible for identifying and removing bulky adducts from non-transcribed DNA that result from damaging agents such as UV radiation and cisplatin. Xeroderma pigmentosum complementation group C (XPC is one of the essential damage recognition proteins of the GG-NER pathway and its dysfunction results in xeroderma pigmentosum (XP, a disorder involving photosensitivity and a predisposition to cancer. To better understand the identification of DNA damage by XPC in the context of chromatin and the role of XPC in the pathogenesis of XP, we characterized the interactome of XPC using a high throughput yeast two-hybrid screening. Our screening showed 49 novel interactors of XPC involved in DNA repair and replication, proteolysis and post-translational modifications, transcription regulation, signal transduction, and metabolism. Importantly, we validated the XPC-OTUD4 interaction by co-IP and provided evidence that OTUD4 knockdown in human cells indeed affects the levels of ubiquitinated XPC, supporting a hypothesis that the OTUD4 deubiquitinase is involved in XPC recycling by cleaving the ubiquitin moiety. This high-throughput characterization of the XPC interactome provides a resource for future exploration and suggests that XPC may have many uncharacterized cellular functions.

Deep sequencing of cardiac microRNA-mRNA interactomes in clinical and experimental cardiomyopathy.

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Matkovich, Scot J; Dorn, Gerald W

2015-01-01

MicroRNAs are a family of short (~21 nucleotide) noncoding RNAs that serve key roles in cellular growth and differentiation and the response of the heart to stress stimuli. As the sequence-specific recognition element of RNA-induced silencing complexes (RISCs), microRNAs bind mRNAs and prevent their translation via mechanisms that may include transcript degradation and/or prevention of ribosome binding. Short microRNA sequences and the ability of microRNAs to bind to mRNA sites having only partial/imperfect sequence complementarity complicate purely computational analyses of microRNA-mRNA interactomes. Furthermore, computational microRNA target prediction programs typically ignore biological context, and therefore the principal determinants of microRNA-mRNA binding: the presence and quantity of each. To address these deficiencies we describe an empirical method, developed via studies of stressed and failing hearts, to determine disease-induced changes in microRNAs, mRNAs, and the mRNAs targeted to the RISC, without cross-linking mRNAs to RISC proteins. Deep sequencing methods are used to determine RNA abundances, delivering unbiased, quantitative RNA data limited only by their annotation in the genome of interest. We describe the laboratory bench steps required to perform these experiments, experimental design strategies to achieve an appropriate number of sequencing reads per biological replicate, and computer-based processing tools and procedures to convert large raw sequencing data files into gene expression measures useful for differential expression analyses.

Modeling complexes of modeled proteins.

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Anishchenko, Ivan; Kundrotas, Petras J; Vakser, Ilya A

2017-03-01

Structural characterization of proteins is essential for understanding life processes at the molecular level. However, only a fraction of known proteins have experimentally determined structures. This fraction is even smaller for protein-protein complexes. Thus, structural modeling of protein-protein interactions (docking) primarily has to rely on modeled structures of the individual proteins, which typically are less accurate than the experimentally determined ones. Such "double" modeling is the Grand Challenge of structural reconstruction of the interactome. Yet it remains so far largely untested in a systematic way. We present a comprehensive validation of template-based and free docking on a set of 165 complexes, where each protein model has six levels of structural accuracy, from 1 to 6 Å C α RMSD. Many template-based docking predictions fall into acceptable quality category, according to the CAPRI criteria, even for highly inaccurate proteins (5-6 Å RMSD), although the number of such models (and, consequently, the docking success rate) drops significantly for models with RMSD > 4 Å. The results show that the existing docking methodologies can be successfully applied to protein models with a broad range of structural accuracy, and the template-based docking is much less sensitive to inaccuracies of protein models than the free docking. Proteins 2017; 85:470-478. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Dengue-2 Structural Proteins Associate with Human Proteins to Produce a Coagulation and Innate Immune Response Biased Interactome

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Soares Luis RB

2011-01-01

Full Text Available Abstract Background Dengue virus infection is a public health threat to hundreds of millions of individuals in the tropical regions of the globe. Although Dengue infection usually manifests itself in its mildest, though often debilitating clinical form, dengue fever, life-threatening complications commonly arise in the form of hemorrhagic shock and encephalitis. The etiological basis for the virus-induced pathology in general, and the different clinical manifestations in particular, are not well understood. We reasoned that a detailed knowledge of the global biological processes affected by virus entry into a cell might help shed new light on this long-standing problem. Methods A bacterial two-hybrid screen using DENV2 structural proteins as bait was performed, and the results were used to feed a manually curated, global dengue-human protein interaction network. Gene ontology and pathway enrichment, along with network topology and microarray meta-analysis, were used to generate hypothesis regarding dengue disease biology. Results Combining bioinformatic tools with two-hybrid technology, we screened human cDNA libraries to catalogue proteins physically interacting with the DENV2 virus structural proteins, Env, cap and PrM. We identified 31 interacting human proteins representing distinct biological processes that are closely related to the major clinical diagnostic feature of dengue infection: haemostatic imbalance. In addition, we found dengue-binding human proteins involved with additional key aspects, previously described as fundamental for virus entry into cells and the innate immune response to infection. Construction of a DENV2-human global protein interaction network revealed interesting biological properties suggested by simple network topology analysis. Conclusions Our experimental strategy revealed that dengue structural proteins interact with human protein targets involved in the maintenance of blood coagulation and innate anti

In silico and biological survey of transcription-associated proteins implicated in the transcriptional machinery during the erythrocytic development of Plasmodium falciparum

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Bischoff Emmanuel

2010-01-01

Full Text Available Abstract Background Malaria is the most important parasitic disease in the world with approximately two million people dying every year, mostly due to Plasmodium falciparum infection. During its complex life cycle in the Anopheles vector and human host, the parasite requires the coordinated and modulated expression of diverse sets of genes involved in epigenetic, transcriptional and post-transcriptional regulation. However, despite the availability of the complete sequence of the Plasmodium falciparum genome, we are still quite ignorant about Plasmodium mechanisms of transcriptional gene regulation. This is due to the poor prediction of nuclear proteins, cognate DNA motifs and structures involved in transcription. Results A comprehensive directory of proteins reported to be potentially involved in Plasmodium transcriptional machinery was built from all in silico reports and databanks. The transcription-associated proteins were clustered in three main sets of factors: general transcription factors, chromatin-related proteins (structuring, remodelling and histone modifying enzymes, and specific transcription factors. Only a few of these factors have been molecularly analysed. Furthermore, from transcriptome and proteome data we modelled expression patterns of transcripts and corresponding proteins during the intra-erythrocytic cycle. Finally, an interactome of these proteins based either on in silico or on 2-yeast-hybrid experimental approaches is discussed. Conclusion This is the first attempt to build a comprehensive directory of potential transcription-associated proteins in Plasmodium. In addition, all complete transcriptome, proteome and interactome raw data were re-analysed, compared and discussed for a better comprehension of the complex biological processes of Plasmodium falciparum transcriptional regulation during the erythrocytic development.

From hub proteins to hub modules: the relationship between essentiality and centrality in the yeast interactome at different scales of organization.

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Jimin Song

Full Text Available Numerous studies have suggested that hub proteins in the S. cerevisiae physical interaction network are more likely to be essential than other proteins. The proposed reasons underlying this observed relationship between topology and functioning have been subject to some controversy, with recent work suggesting that it arises due to the participation of hub proteins in essential complexes and processes. However, do these essential modules themselves have distinct network characteristics, and how do their essential proteins differ in their topological properties from their non-essential proteins? We aimed to advance our understanding of protein essentiality by analyzing proteins, complexes and processes within their broader functional context and by considering physical interactions both within and across complexes and biological processes. In agreement with the view that essentiality is a modular property, we found that the number of intracomplex or intraprocess interactions that a protein has is a better indicator of its essentiality than its overall number of interactions. Moreover, we found that within an essential complex, its essential proteins have on average more interactions, especially intracomplex interactions, than its non-essential proteins. Finally, we built a module-level interaction network and found that essential complexes and processes tend to have higher interaction degrees in this network than non-essential complexes and processes; that is, they exhibit a larger amount of functional cross-talk than their non-essential counterparts.

Fault tolerance in protein interaction networks: stable bipartite subgraphs and redundant pathways.

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Brady, Arthur; Maxwell, Kyle; Daniels, Noah; Cowen, Lenore J

2009-01-01

As increasing amounts of high-throughput data for the yeast interactome become available, more system-wide properties are uncovered. One interesting question concerns the fault tolerance of protein interaction networks: whether there exist alternative pathways that can perform some required function if a gene essential to the main mechanism is defective, absent or suppressed. A signature pattern for redundant pathways is the BPM (between-pathway model) motif, introduced by Kelley and Ideker. Past methods proposed to search the yeast interactome for BPM motifs have had several important limitations. First, they have been driven heuristically by local greedy searches, which can lead to the inclusion of extra genes that may not belong in the motif; second, they have been validated solely by functional coherence of the putative pathways using GO enrichment, making it difficult to evaluate putative BPMs in the absence of already known biological annotation. We introduce stable bipartite subgraphs, and show they form a clean and efficient way of generating meaningful BPMs which naturally discard extra genes included by local greedy methods. We show by GO enrichment measures that our BPM set outperforms previous work, covering more known complexes and functional pathways. Perhaps most importantly, since our BPMs are initially generated by examining the genetic-interaction network only, the location of edges in the protein-protein physical interaction network can then be used to statistically validate each candidate BPM, even with sparse GO annotation (or none at all). We uncover some interesting biological examples of previously unknown putative redundant pathways in such areas as vesicle-mediated transport and DNA repair.

Neuroplasticity pathways and protein-interaction networks are modulated by vortioxetine in rodents

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Waller, Jessica A.; Nygaard, Sara Holm; Li, Yan

2017-01-01

species and sexes, different brain regions, and in response to distinct routes of administration and regimens. Conclusions: A recurring theme, based on the present study as well as previous findings, is that networks related to synaptic plasticity, synaptic transmission, signal transduction...... and rat in response to distinct treatment regimens and in different brain regions. Furthermore, analysis of complexes of physically-interacting proteins reveal that biomarkers involved in transcriptional regulation, neurodevelopment, neuroplasticity, and endocytosis are modulated by vortioxetine....... A subsequent qPCR study examining the expression of targets in the protein-protein interactome space in response to chronic vortioxetine treatment over a range of doses provides further biological validation that vortioxetine engages neuroplasticity networks. Thus, the same biology is regulated in different...

Nanodisc-solubilized membrane protein library reflects the membrane proteome.

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Marty, Michael T; Wilcox, Kyle C; Klein, William L; Sligar, Stephen G

2013-05-01

The isolation and identification of unknown membrane proteins offers the prospect of discovering new pharmaceutical targets and identifying key biochemical receptors. However, interactions between membrane protein targets and soluble ligands are difficult to study in vitro due to the insolubility of membrane proteins in non-detergent systems. Nanodiscs, nanoscale discoidal lipid bilayers encircled by a membrane scaffold protein belt, have proven to be an effective platform to solubilize membrane proteins and have been used to study a wide variety of purified membrane proteins. This report details the incorporation of an unbiased population of membrane proteins from Escherichia coli membranes into Nanodiscs. This solubilized membrane protein library (SMPL) forms a soluble in vitro model of the membrane proteome. Since Nanodiscs contain isolated proteins or small complexes, the SMPL is an ideal platform for interactomics studies and pull-down assays of membrane proteins. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis analysis of the protein population before and after formation of the Nanodisc library indicates that a large percentage of the proteins are incorporated into the library. Proteomic identification of several prominent bands demonstrates the successful incorporation of outer and inner membrane proteins into the Nanodisc library.

Dr. PIAS: an integrative system for assessing the druggability of protein-protein interactions

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Furuya Toshio

2011-02-01

Full Text Available Abstract Background The amount of data on protein-protein interactions (PPIs available in public databases and in the literature has rapidly expanded in recent years. PPI data can provide useful information for researchers in pharmacology and medicine as well as those in interactome studies. There is urgent need for a novel methodology or software allowing the efficient utilization of PPI data in pharmacology and medicine. Results To address this need, we have developed the 'Druggable Protein-protein Interaction Assessment System' (Dr. PIAS. Dr. PIAS has a meta-database that stores various types of information (tertiary structures, drugs/chemicals, and biological functions associated with PPIs retrieved from public sources. By integrating this information, Dr. PIAS assesses whether a PPI is druggable as a target for small chemical ligands by using a supervised machine-learning method, support vector machine (SVM. Dr. PIAS holds not only known druggable PPIs but also all PPIs of human, mouse, rat, and human immunodeficiency virus (HIV proteins identified to date. Conclusions The design concept of Dr. PIAS is distinct from other published PPI databases in that it focuses on selecting the PPIs most likely to make good drug targets, rather than merely collecting PPI data.

SCOWLP classification: Structural comparison and analysis of protein binding regions

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Anders Gerd

2008-01-01

Full Text Available Abstract Background Detailed information about protein interactions is critical for our understanding of the principles governing protein recognition mechanisms. The structures of many proteins have been experimentally determined in complex with different ligands bound either in the same or different binding regions. Thus, the structural interactome requires the development of tools to classify protein binding regions. A proper classification may provide a general view of the regions that a protein uses to bind others and also facilitate a detailed comparative analysis of the interacting information for specific protein binding regions at atomic level. Such classification might be of potential use for deciphering protein interaction networks, understanding protein function, rational engineering and design. Description Protein binding regions (PBRs might be ideally described as well-defined separated regions that share no interacting residues one another. However, PBRs are often irregular, discontinuous and can share a wide range of interacting residues among them. The criteria to define an individual binding region can be often arbitrary and may differ from other binding regions within a protein family. Therefore, the rational behind protein interface classification should aim to fulfil the requirements of the analysis to be performed. We extract detailed interaction information of protein domains, peptides and interfacial solvent from the SCOWLP database and we classify the PBRs of each domain family. For this purpose, we define a similarity index based on the overlapping of interacting residues mapped in pair-wise structural alignments. We perform our classification with agglomerative hierarchical clustering using the complete-linkage method. Our classification is calculated at different similarity cut-offs to allow flexibility in the analysis of PBRs, feature especially interesting for those protein families with conflictive binding regions

A TALE-inspired computational screen for proteins that contain approximate tandem repeats.

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Perycz, Malgorzata; Krwawicz, Joanna; Bochtler, Matthias

2017-01-01

TAL (transcription activator-like) effectors (TALEs) are bacterial proteins that are secreted from bacteria to plant cells to act as transcriptional activators. TALEs and related proteins (RipTALs, BurrH, MOrTL1 and MOrTL2) contain approximate tandem repeats that differ in conserved positions that define specificity. Using PERL, we screened ~47 million protein sequences for TALE-like architecture characterized by approximate tandem repeats (between 30 and 43 amino acids in length) and sequence variability in conserved positions, without requiring sequence similarity to TALEs. Candidate proteins were scored according to their propensity for nuclear localization, secondary structure, repeat sequence complexity, as well as covariation and predicted structural proximity of variable residues. Biological context was tentatively inferred from co-occurrence of other domains and interactome predictions. Approximate repeats with TALE-like features that merit experimental characterization were found in a protein of chestnut blight fungus, a eukaryotic plant pathogen.

Essential protein discovery based on a combination of modularity and conservatism.

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Zhao, Bihai; Wang, Jianxin; Li, Xueyong; Wu, Fang-Xiang

2016-11-01

Essential proteins are indispensable for the survival of a living organism and play important roles in the emerging field of synthetic biology. Many computational methods have been proposed to identify essential proteins by using the topological features of interactome networks. However, most of these methods ignored intrinsic biological meaning of proteins. Researches show that essentiality is tied not only to the protein or gene itself, but also to the molecular modules to which that protein belongs. The results of this study reveal the modularity of essential proteins. On the other hand, essential proteins are more evolutionarily conserved than nonessential proteins and frequently bind each other. That is to say, conservatism is another important feature of essential proteins. Multiple networks are constructed by integrating protein-protein interaction (PPI) networks, time course gene expression data and protein domain information. Based on these networks, a new essential protein identification method is proposed based on a combination of modularity and conservatism of proteins. Experimental results show that the proposed method outperforms other essential protein identification methods in terms of a number essential protein out of top ranked candidates. Copyright © 2016. Published by Elsevier Inc.

Differential binding of calmodulin-related proteins to their targets revealed through high-density Arabidopsis protein microarrays

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Popescu, Sorina C.; Popescu, George V.; Bachan, Shawn; Zhang, Zimei; Seay, Montrell; Gerstein, Mark; Snyder, Michael; Dinesh-Kumar, S. P.

2007-01-01

Calmodulins (CaMs) are the most ubiquitous calcium sensors in eukaryotes. A number of CaM-binding proteins have been identified through classical methods, and many proteins have been predicted to bind CaMs based on their structural homology with known targets. However, multicellular organisms typically contain many CaM-like (CML) proteins, and a global identification of their targets and specificity of interaction is lacking. In an effort to develop a platform for large-scale analysis of proteins in plants we have developed a protein microarray and used it to study the global analysis of CaM/CML interactions. An Arabidopsis thaliana expression collection containing 1,133 ORFs was generated and used to produce proteins with an optimized medium-throughput plant-based expression system. Protein microarrays were prepared and screened with several CaMs/CMLs. A large number of previously known and novel CaM/CML targets were identified, including transcription factors, receptor and intracellular protein kinases, F-box proteins, RNA-binding proteins, and proteins of unknown function. Multiple CaM/CML proteins bound many binding partners, but the majority of targets were specific to one or a few CaMs/CMLs indicating that different CaM family members function through different targets. Based on our analyses, the emergent CaM/CML interactome is more extensive than previously predicted. Our results suggest that calcium functions through distinct CaM/CML proteins to regulate a wide range of targets and cellular activities. PMID:17360592

Fault tolerance in protein interaction networks: stable bipartite subgraphs and redundant pathways.

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Arthur Brady

Full Text Available As increasing amounts of high-throughput data for the yeast interactome become available, more system-wide properties are uncovered. One interesting question concerns the fault tolerance of protein interaction networks: whether there exist alternative pathways that can perform some required function if a gene essential to the main mechanism is defective, absent or suppressed. A signature pattern for redundant pathways is the BPM (between-pathway model motif, introduced by Kelley and Ideker. Past methods proposed to search the yeast interactome for BPM motifs have had several important limitations. First, they have been driven heuristically by local greedy searches, which can lead to the inclusion of extra genes that may not belong in the motif; second, they have been validated solely by functional coherence of the putative pathways using GO enrichment, making it difficult to evaluate putative BPMs in the absence of already known biological annotation. We introduce stable bipartite subgraphs, and show they form a clean and efficient way of generating meaningful BPMs which naturally discard extra genes included by local greedy methods. We show by GO enrichment measures that our BPM set outperforms previous work, covering more known complexes and functional pathways. Perhaps most importantly, since our BPMs are initially generated by examining the genetic-interaction network only, the location of edges in the protein-protein physical interaction network can then be used to statistically validate each candidate BPM, even with sparse GO annotation (or none at all. We uncover some interesting biological examples of previously unknown putative redundant pathways in such areas as vesicle-mediated transport and DNA repair.

Predicting protein-protein interactions in Arabidopsis thaliana through integration of orthology, gene ontology and co-expression

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Vandepoele Klaas

2009-06-01

Full Text Available Abstract Background Large-scale identification of the interrelationships between different components of the cell, such as the interactions between proteins, has recently gained great interest. However, unraveling large-scale protein-protein interaction maps is laborious and expensive. Moreover, assessing the reliability of the interactions can be cumbersome. Results In this study, we have developed a computational method that exploits the existing knowledge on protein-protein interactions in diverse species through orthologous relations on the one hand, and functional association data on the other hand to predict and filter protein-protein interactions in Arabidopsis thaliana. A highly reliable set of protein-protein interactions is predicted through this integrative approach making use of existing protein-protein interaction data from yeast, human, C. elegans and D. melanogaster. Localization, biological process, and co-expression data are used as powerful indicators for protein-protein interactions. The functional repertoire of the identified interactome reveals interactions between proteins functioning in well-conserved as well as plant-specific biological processes. We observe that although common mechanisms (e.g. actin polymerization and components (e.g. ARPs, actin-related proteins exist between different lineages, they are active in specific processes such as growth, cancer metastasis and trichome development in yeast, human and Arabidopsis, respectively. Conclusion We conclude that the integration of orthology with functional association data is adequate to predict protein-protein interactions. Through this approach, a high number of novel protein-protein interactions with diverse biological roles is discovered. Overall, we have predicted a reliable set of protein-protein interactions suitable for further computational as well as experimental analyses.

BioPlex Display: An Interactive Suite for Large-Scale AP-MS Protein-Protein Interaction Data.

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Schweppe, Devin K; Huttlin, Edward L; Harper, J Wade; Gygi, Steven P

2018-01-05

The development of large-scale data sets requires a new means to display and disseminate research studies to large audiences. Knowledge of protein-protein interaction (PPI) networks has become a principle interest of many groups within the field of proteomics. At the confluence of technologies, such as cross-linking mass spectrometry, yeast two-hybrid, protein cofractionation, and affinity purification mass spectrometry (AP-MS), detection of PPIs can uncover novel biological inferences at a high-throughput. Thus new platforms to provide community access to large data sets are necessary. To this end, we have developed a web application that enables exploration and dissemination of the growing BioPlex interaction network. BioPlex is a large-scale interactome data set based on AP-MS of baits from the human ORFeome. The latest BioPlex data set release (BioPlex 2.0) contains 56 553 interactions from 5891 AP-MS experiments. To improve community access to this vast compendium of interactions, we developed BioPlex Display, which integrates individual protein querying, access to empirical data, and on-the-fly annotation of networks within an easy-to-use and mobile web application. BioPlex Display enables rapid acquisition of data from BioPlex and development of hypotheses based on protein interactions.

Comprehensive Characterization of Minichromosome Maintenance Complex (MCM) Protein Interactions Using Affinity and Proximity Purifications Coupled to Mass Spectrometry.

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Dubois, Marie-Line; Bastin, Charlotte; Lévesque, Dominique; Boisvert, François-Michel

2016-09-02

The extensive identification of protein-protein interactions under different conditions is an important challenge to understand the cellular functions of proteins. Here we use and compare different approaches including affinity purification and purification by proximity coupled to mass spectrometry to identify protein complexes. We explore the complete interactome of the minichromosome maintenance (MCM) complex by using both approaches for all of the different MCM proteins. Overall, our analysis identified unique and shared interaction partners and proteins enriched for distinct biological processes including DNA replication, DNA repair, and cell cycle regulation. Furthermore, we mapped the changes in protein interactions of the MCM complex in response to DNA damage, identifying a new role for this complex in DNA repair. In summary, we demonstrate the complementarity of these approaches for the characterization of protein interactions within the MCM complex.

Fly-DPI: database of protein interactomes for D. melanogaster in the approach of systems biology

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Lin Chieh-Hua

2006-12-01

Full Text Available Abstract Background Proteins control and mediate many biological activities of cells by interacting with other protein partners. This work presents a statistical model to predict protein interaction networks of Drosophila melanogaster based on insight into domain interactions. Results Three high-throughput yeast two-hybrid experiments and the collection in FlyBase were used as our starting datasets. The co-occurrences of domains in these interactive events are converted into a probability score of domain-domain interaction. These scores are used to infer putative interaction among all available open reading frames (ORFs of fruit fly. Additionally, the likelihood function is used to estimate all potential protein-protein interactions. All parameters are successfully iterated and MLE is obtained for each pair of domains. Additionally, the maximized likelihood reaches its converged criteria and maintains the probability stable. The hybrid model achieves a high specificity with a loss of sensitivity, suggesting that the model may possess major features of protein-protein interactions. Several putative interactions predicted by the proposed hybrid model are supported by literatures, while experimental data with a low probability score indicate an uncertain reliability and require further proof of interaction. Fly-DPI is the online database used to present this work. It is an integrated proteomics tool with comprehensive protein annotation information from major databases as well as an effective means of predicting protein-protein interactions. As a novel search strategy, the ping-pong search is a naïve path map between two chosen proteins based on pre-computed shortest paths. Adopting effective filtering strategies will facilitate researchers in depicting the bird's eye view of the network of interest. Fly-DPI can be accessed at http://flydpi.nhri.org.tw. Conclusion This work provides two reference systems, statistical and biological, to evaluate

Specificity and evolvability in eukaryotic protein interaction networks.

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Pedro Beltrao

2007-02-01

Full Text Available Progress in uncovering the protein interaction networks of several species has led to questions of what underlying principles might govern their organization. Few studies have tried to determine the impact of protein interaction network evolution on the observed physiological differences between species. Using comparative genomics and structural information, we show here that eukaryotic species have rewired their interactomes at a fast rate of approximately 10(-5 interactions changed per protein pair, per million years of divergence. For Homo sapiens this corresponds to 10(3 interactions changed per million years. Additionally we find that the specificity of binding strongly determines the interaction turnover and that different biological processes show significantly different link dynamics. In particular, human proteins involved in immune response, transport, and establishment of localization show signs of positive selection for change of interactions. Our analysis suggests that a small degree of molecular divergence can give rise to important changes at the network level. We propose that the power law distribution observed in protein interaction networks could be partly explained by the cell's requirement for different degrees of protein binding specificity.

ALS Associated Mutations in Matrin 3 Alter Protein-Protein Interactions and Impede mRNA Nuclear Export.

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Boehringer, Ashley; Garcia-Mansfield, Krystine; Singh, Gurkaran; Bakkar, Nadine; Pirrotte, Patrick; Bowser, Robert

2017-11-06

Mutations in Matrin 3 have recently been linked to ALS, though the mechanism that induces disease in these patients is unknown. To define the protein interactome of wild-type and ALS-linked MATR3 mutations, we performed immunoprecipitation followed by mass spectrometry using NSC-34 cells expressing human wild-type or mutant Matrin 3. Gene ontology analysis identified a novel role for Matrin 3 in mRNA transport centered on proteins in the TRanscription and EXport (TREX) complex, known to function in mRNA biogenesis and nuclear export. ALS-linked mutations in Matrin 3 led to its re-distribution within the nucleus, decreased co-localization with endogenous Matrin 3 and increased co-localization with specific TREX components. Expression of disease-causing Matrin 3 mutations led to nuclear mRNA export defects of both global mRNA and more specifically the mRNA of TDP-43 and FUS. Our findings identify a potential pathogenic mechanism attributable to MATR3 mutations and further link cellular transport defects to ALS.

A human phenome-interactome network of protein complexes implicated in genetic disorders

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Hansen, Kasper Lage; Karlberg, Erik, Olof, Linnart; Størling, Zenia, Marian

2007-01-01

the known disease-causing protein as the top candidate, and in 870 intervals with no identified disease-causing gene, provides novel candidates implicated in disorders such as retinitis pigmentosa, epithelial ovarian cancer, inflammatory bowel disease, amyotrophic lateral sclerosis, Alzheimer disease, type...

Evaluation of colorimetric assays for analyzing reductively methylated proteins: Biases and mechanistic insights.

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Brady, Pamlea N; Macnaughtan, Megan A

2015-12-15

Colorimetric protein assays, such as the Coomassie blue G-250 dye-binding (Bradford) and bicinchoninic acid (BCA) assays, are commonly used to quantify protein concentration. The accuracy of these assays depends on the amino acid composition. Because of the extensive use of reductive methylation in the study of proteins and the importance of biological methylation, it is necessary to evaluate the impact of lysyl methylation on the Bradford and BCA assays. Unmodified and reductively methylated proteins were analyzed using the absorbance at 280 nm to standardize the concentrations. Using model compounds, we demonstrate that the dimethylation of lysyl ε-amines does not affect the proteins' molar extinction coefficients at 280 nm. For the Bradford assay, the responses (absorbance per unit concentration) of the unmodified and reductively methylated proteins were similar, with a slight decrease in the response upon methylation. For the BCA assay, the responses of the reductively methylated proteins were consistently higher, overestimating the concentrations of the methylated proteins. The enhanced color formation in the BCA assay may be due to the lower acid dissociation constants of the lysyl ε-dimethylamines compared with the unmodified ε-amine, favoring Cu(II) binding in biuret-like complexes. The implications for the analysis of biologically methylated samples are discussed. Copyright © 2015 Elsevier Inc. All rights reserved.

The C-terminal domain of the bacterial SSB protein acts as a DNA maintenance hub at active chromosome replication forks.

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Audrey Costes

2010-12-01

Full Text Available We have investigated in vivo the role of the carboxy-terminal domain of the Bacillus subtilis Single-Stranded DNA Binding protein (SSB(Cter as a recruitment platform at active chromosomal forks for many proteins of the genome maintenance machineries. We probed this SSB(Cter interactome using GFP fusions and by Tap-tag and biochemical analysis. It includes at least 12 proteins. The interactome was previously shown to include PriA, RecG, and RecQ and extended in this study by addition of DnaE, SbcC, RarA, RecJ, RecO, XseA, Ung, YpbB, and YrrC. Targeting of YpbB to active forks appears to depend on RecS, a RecQ paralogue, with which it forms a stable complex. Most of these SSB partners are conserved in bacteria, while others, such as the essential DNA polymerase DnaE, YrrC, and the YpbB/RecS complex, appear to be specific to B. subtilis. SSB(Cter deletion has a moderate impact on B. subtilis cell growth. However, it markedly affects the efficiency of repair of damaged genomic DNA and arrested replication forks. ssbΔCter mutant cells appear deficient in RecA loading on ssDNA, explaining their inefficiency in triggering the SOS response upon exposure to genotoxic agents. Together, our findings show that the bacterial SSB(Cter acts as a DNA maintenance hub at active chromosomal forks that secures their propagation along the genome.

Bioinformatics-driven identification and examination of candidate genes for non-alcoholic fatty liver disease.

Directory of Open Access Journals (Sweden)

Karina Banasik

2011-01-01

Full Text Available Candidate genes for non-alcoholic fatty liver disease (NAFLD identified by a bioinformatics approach were examined for variant associations to quantitative traits of NAFLD-related phenotypes.By integrating public database text mining, trans-organism protein-protein interaction transferal, and information on liver protein expression a protein-protein interaction network was constructed and from this a smaller isolated interactome was identified. Five genes from this interactome were selected for genetic analysis. Twenty-one tag single-nucleotide polymorphisms (SNPs which captured all common variation in these genes were genotyped in 10,196 Danes, and analyzed for association with NAFLD-related quantitative traits, type 2 diabetes (T2D, central obesity, and WHO-defined metabolic syndrome (MetS.273 genes were included in the protein-protein interaction analysis and EHHADH, ECHS1, HADHA, HADHB, and ACADL were selected for further examination. A total of 10 nominal statistical significant associations (P<0.05 to quantitative metabolic traits were identified. Also, the case-control study showed associations between variation in the five genes and T2D, central obesity, and MetS, respectively. Bonferroni adjustments for multiple testing negated all associations.Using a bioinformatics approach we identified five candidate genes for NAFLD. However, we failed to provide evidence of associations with major effects between SNPs in these five genes and NAFLD-related quantitative traits, T2D, central obesity, and MetS.

Usher syndrome: molecular links of pathogenesis, proteins and pathways.

Science.gov (United States)

Kremer, Hannie; van Wijk, Erwin; Märker, Tina; Wolfrum, Uwe; Roepman, Ronald

2006-10-15

Usher syndrome is the most common form of deaf-blindness. The syndrome is both clinically and genetically heterogeneous, and to date, eight causative genes have been identified. The proteins encoded by these genes are part of a dynamic protein complex that is present in hair cells of the inner ear and in photoreceptor cells of the retina. The localization of the Usher proteins and the phenotype in animal models indicate that the Usher protein complex is essential in the morphogenesis of the stereocilia bundle in hair cells and in the calycal processes of photoreceptor cells. In addition, the Usher proteins are important in the synaptic processes of both cell types. The association of other proteins with the complex indicates functional links to a number of basic cell-biological processes. Prominently present is the connection to the dynamics of the actin cytoskeleton, involved in cellular morphology, cell polarity and cell-cell interactions. The Usher protein complex can also be linked to the cadherins/catenins in the adherens junction-associated protein complexes, suggesting a role in cell polarity and tissue organization. A third link can be established to the integrin transmembrane signaling network. The Usher interactome, as outlined in this review, participates in pathways common in inner ear and retina that are disrupted in the Usher syndrome.

The Reactive Species Interactome: Evolutionary Emergence, Biological Significance, and Opportunities for Redox Metabolomics and Personalized Medicine.

Science.gov (United States)

Cortese-Krott, Miriam M; Koning, Anne; Kuhnle, Gunter G C; Nagy, Peter; Bianco, Christopher L; Pasch, Andreas; Wink, David A; Fukuto, Jon M; Jackson, Alan A; van Goor, Harry; Olson, Kenneth R; Feelisch, Martin

2017-10-01

Oxidative stress is thought to account for aberrant redox homeostasis and contribute to aging and disease. However, more often than not, administration of antioxidants is ineffective, suggesting that our current understanding of the underlying regulatory processes is incomplete. Recent Advances: Similar to reactive oxygen species and reactive nitrogen species, reactive sulfur species are now emerging as important signaling molecules, targeting regulatory cysteine redox switches in proteins, affecting gene regulation, ion transport, intermediary metabolism, and mitochondrial function. To rationalize the complexity of chemical interactions of reactive species with themselves and their targets and help define their role in systemic metabolic control, we here introduce a novel integrative concept defined as the reactive species interactome (RSI). The RSI is a primeval multilevel redox regulatory system whose architecture, together with the physicochemical characteristics of its constituents, allows efficient sensing and rapid adaptation to environmental changes and various other stressors to enhance fitness and resilience at the local and whole-organism level. To better characterize the RSI-related processes that determine fluxes through specific pathways and enable integration, it is necessary to disentangle the chemical biology and activity of reactive species (including precursors and reaction products), their targets, communication systems, and effects on cellular, organ, and whole-organism bioenergetics using system-level/network analyses. Understanding the mechanisms through which the RSI operates will enable a better appreciation of the possibilities to modulate the entire biological system; moreover, unveiling molecular signatures that characterize specific environmental challenges or other forms of stress will provide new prevention/intervention opportunities for personalized medicine. Antioxid. Redox Signal. 00, 000-000.

Fast kinase domain-containing protein 3 is a mitochondrial protein essential for cellular respiration

Energy Technology Data Exchange (ETDEWEB)

Simarro, Maria [Division of Rheumatology, Immunology and Allergy, Brigham and Women' s Hospital, and Department of Medicine, Harvard Medical School, Boston, MA 02115 (United States); Gimenez-Cassina, Alfredo [Department of Cancer Biology at Dana Farber Institute, Boston, MA 02115 (United States); Kedersha, Nancy [Division of Rheumatology, Immunology and Allergy, Brigham and Women' s Hospital, and Department of Medicine, Harvard Medical School, Boston, MA 02115 (United States); Lazaro, Jean-Bernard; Adelmant, Guillaume O.; Marto, Jarrod A. [Department of Cancer Biology at Dana Farber Institute, Boston, MA 02115 (United States); Rhee, Kirsten [Division of Rheumatology, Immunology and Allergy, Brigham and Women' s Hospital, and Department of Medicine, Harvard Medical School, Boston, MA 02115 (United States); Tisdale, Sarah; Danial, Nika [Department of Cancer Biology at Dana Farber Institute, Boston, MA 02115 (United States); Benarafa, Charaf [Theodor Kocher Institute, University of Bern, 3012 Bern (Switzerland); Orduna, Anonio [Unidad de Investigacion, Hospital Clinico Universitario de Valladolid, 47005 Valladolid (Spain); Anderson, Paul, E-mail: panderson@rics.bwh.harvard.edu [Division of Rheumatology, Immunology and Allergy, Brigham and Women' s Hospital, and Department of Medicine, Harvard Medical School, Boston, MA 02115 (United States)

2010-10-22

Research highlights: {yields} Five members of the FAST kinase domain-containing proteins are localized to mitochondria in mammalian cells. {yields} The FASTKD3 interactome includes proteins involved in various aspects of mitochondrial metabolism. {yields} Targeted knockdown of FASTKD3 significantly reduces basal and maximal mitochondrial oxygen consumption. -- Abstract: Fas-activated serine/threonine phosphoprotein (FAST) is the founding member of the FAST kinase domain-containing protein (FASTKD) family that includes FASTKD1-5. FAST is a sensor of mitochondrial stress that modulates protein translation to promote the survival of cells exposed to adverse conditions. Mutations in FASTKD2 have been linked to a mitochondrial encephalomyopathy that is associated with reduced cytochrome c oxidase activity, an essential component of the mitochondrial electron transport chain. We have confirmed the mitochondrial localization of FASTKD2 and shown that all FASTKD family members are found in mitochondria. Although human and mouse FASTKD1-5 genes are expressed ubiquitously, some of them are most abundantly expressed in mitochondria-enriched tissues. We have found that RNA interference-mediated knockdown of FASTKD3 severely blunts basal and stress-induced mitochondrial oxygen consumption without disrupting the assembly of respiratory chain complexes. Tandem affinity purification reveals that FASTKD3 interacts with components of mitochondrial respiratory and translation machineries. Our results introduce FASTKD3 as an essential component of mitochondrial respiration that may modulate energy balance in cells exposed to adverse conditions by functionally coupling mitochondrial protein synthesis to respiration.

Fast kinase domain-containing protein 3 is a mitochondrial protein essential for cellular respiration

International Nuclear Information System (INIS)

Simarro, Maria; Gimenez-Cassina, Alfredo; Kedersha, Nancy; Lazaro, Jean-Bernard; Adelmant, Guillaume O.; Marto, Jarrod A.; Rhee, Kirsten; Tisdale, Sarah; Danial, Nika; Benarafa, Charaf; Orduna, Anonio; Anderson, Paul

2010-01-01

Research highlights: → Five members of the FAST kinase domain-containing proteins are localized to mitochondria in mammalian cells. → The FASTKD3 interactome includes proteins involved in various aspects of mitochondrial metabolism. → Targeted knockdown of FASTKD3 significantly reduces basal and maximal mitochondrial oxygen consumption. -- Abstract: Fas-activated serine/threonine phosphoprotein (FAST) is the founding member of the FAST kinase domain-containing protein (FASTKD) family that includes FASTKD1-5. FAST is a sensor of mitochondrial stress that modulates protein translation to promote the survival of cells exposed to adverse conditions. Mutations in FASTKD2 have been linked to a mitochondrial encephalomyopathy that is associated with reduced cytochrome c oxidase activity, an essential component of the mitochondrial electron transport chain. We have confirmed the mitochondrial localization of FASTKD2 and shown that all FASTKD family members are found in mitochondria. Although human and mouse FASTKD1-5 genes are expressed ubiquitously, some of them are most abundantly expressed in mitochondria-enriched tissues. We have found that RNA interference-mediated knockdown of FASTKD3 severely blunts basal and stress-induced mitochondrial oxygen consumption without disrupting the assembly of respiratory chain complexes. Tandem affinity purification reveals that FASTKD3 interacts with components of mitochondrial respiratory and translation machineries. Our results introduce FASTKD3 as an essential component of mitochondrial respiration that may modulate energy balance in cells exposed to adverse conditions by functionally coupling mitochondrial protein synthesis to respiration.

SCOWLP: a web-based database for detailed characterization and visualization of protein interfaces

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Schroeder Michael

2006-03-01

Full Text Available Abstract Background Currently there is a strong need for methods that help to obtain an accurate description of protein interfaces in order to be able to understand the principles that govern molecular recognition and protein function. Many of the recent efforts to computationally identify and characterize protein networks extract protein interaction information at atomic resolution from the PDB. However, they pay none or little attention to small protein ligands and solvent. They are key components and mediators of protein interactions and fundamental for a complete description of protein interfaces. Interactome profiling requires the development of computational tools to extract and analyze protein-protein, protein-ligand and detailed solvent interaction information from the PDB in an automatic and comparative fashion. Adding this information to the existing one on protein-protein interactions will allow us to better understand protein interaction networks and protein function. Description SCOWLP (Structural Characterization Of Water, Ligands and Proteins is a user-friendly and publicly accessible web-based relational database for detailed characterization and visualization of the PDB protein interfaces. The SCOWLP database includes proteins, peptidic-ligands and interface water molecules as descriptors of protein interfaces. It contains currently 74,907 protein interfaces and 2,093,976 residue-residue interactions formed by 60,664 structural units (protein domains and peptidic-ligands and their interacting solvent. The SCOWLP web-server allows detailed structural analysis and comparisons of protein interfaces at atomic level by text query of PDB codes and/or by navigating a SCOP-based tree. It includes a visualization tool to interactively display the interfaces and label interacting residues and interface solvent by atomic physicochemical properties. SCOWLP is automatically updated with every SCOP release. Conclusion SCOWLP enriches

Evidence for the robustness of protein complexes to inter-species hybridization.

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Jean-Baptiste Leducq

Full Text Available Despite the tremendous efforts devoted to the identification of genetic incompatibilities underlying hybrid sterility and inviability, little is known about the effect of inter-species hybridization at the protein interactome level. Here, we develop a screening platform for the comparison of protein-protein interactions (PPIs among closely related species and their hybrids. We examine in vivo the architecture of protein complexes in two yeast species (Saccharomyces cerevisiae and Saccharomyces kudriavzevii that diverged 5-20 million years ago and in their F1 hybrids. We focus on 24 proteins of two large complexes: the RNA polymerase II and the nuclear pore complex (NPC, which show contrasting patterns of molecular evolution. We found that, with the exception of one PPI in the NPC sub-complex, PPIs were highly conserved between species, regardless of protein divergence. Unexpectedly, we found that the architecture of the complexes in F1 hybrids could not be distinguished from that of the parental species. Our results suggest that the conservation of PPIs in hybrids likely results from the slow evolution taking place on the very few protein residues involved in the interaction or that protein complexes are inherently robust and may accommodate protein divergence up to the level that is observed among closely related species.

Docking-based modeling of protein-protein interfaces for extensive structural and functional characterization of missense mutations.

Science.gov (United States)

Barradas-Bautista, Didier; Fernández-Recio, Juan

2017-01-01

Next-generation sequencing (NGS) technologies are providing genomic information for an increasing number of healthy individuals and patient populations. In the context of the large amount of generated genomic data that is being generated, understanding the effect of disease-related mutations at molecular level can contribute to close the gap between genotype and phenotype and thus improve prevention, diagnosis or treatment of a pathological condition. In order to fully characterize the effect of a pathological mutation and have useful information for prediction purposes, it is important first to identify whether the mutation is located at a protein-binding interface, and second to understand the effect on the binding affinity of the affected interaction/s. Computational methods, such as protein docking are currently used to complement experimental efforts and could help to build the human structural interactome. Here we have extended the original pyDockNIP method to predict the location of disease-associated nsSNPs at protein-protein interfaces, when there is no available structure for the protein-protein complex. We have applied this approach to the pathological interaction networks of six diseases with low structural data on PPIs. This approach can almost double the number of nsSNPs that can be characterized and identify edgetic effects in many nsSNPs that were previously unknown. This can help to annotate and interpret genomic data from large-scale population studies, and to achieve a better understanding of disease at molecular level.

Docking-based modeling of protein-protein interfaces for extensive structural and functional characterization of missense mutations.

Directory of Open Access Journals (Sweden)

Didier Barradas-Bautista

Full Text Available Next-generation sequencing (NGS technologies are providing genomic information for an increasing number of healthy individuals and patient populations. In the context of the large amount of generated genomic data that is being generated, understanding the effect of disease-related mutations at molecular level can contribute to close the gap between genotype and phenotype and thus improve prevention, diagnosis or treatment of a pathological condition. In order to fully characterize the effect of a pathological mutation and have useful information for prediction purposes, it is important first to identify whether the mutation is located at a protein-binding interface, and second to understand the effect on the binding affinity of the affected interaction/s. Computational methods, such as protein docking are currently used to complement experimental efforts and could help to build the human structural interactome. Here we have extended the original pyDockNIP method to predict the location of disease-associated nsSNPs at protein-protein interfaces, when there is no available structure for the protein-protein complex. We have applied this approach to the pathological interaction networks of six diseases with low structural data on PPIs. This approach can almost double the number of nsSNPs that can be characterized and identify edgetic effects in many nsSNPs that were previously unknown. This can help to annotate and interpret genomic data from large-scale population studies, and to achieve a better understanding of disease at molecular level.

The RNA-binding protein repertoire of Arabidopsis thaliana

KAUST Repository

Marondedze, Claudius

2016-07-11

RNA-binding proteins (RBPs) have essential roles in determining the fate of RNA from synthesis to decay and have been studied on a protein-by-protein basis, or computationally based on a number of well-characterised RNA-binding domains. Recently, high-throughput methods enabled the capture of mammalian RNA-binding proteomes. To gain insight into the role of Arabidopsis thaliana RBPs at the systems level, we have employed interactome capture techniques using cells from different ecotypes grown in cultures and leaves. In vivo UV-crosslinking of RNA to RBPs, oligo(dT) capture and mass spectrometry yielded 1,145 different proteins including 550 RBPs that either belong to the functional category ‘RNA-binding’, have known RNA-binding domains or have orthologs identified in mammals, C. elegans, or S. cerevisiae in addition to 595 novel candidate RBPs. We noted specific subsets of RBPs in cultured cells and leaves and a comparison of Arabidopsis, mammalian, C. elegans, and S. cerevisiae RBPs reveals a common set of proteins with a role in intermediate metabolism, as well as distinct differences suggesting that RBPs are also species and tissue specific. This study provides a foundation for studies that will advance our understanding of the biological significance of RBPs in plant developmental and stimulus specific responses.

TranscriptomeBrowser 3.0: introducing a new compendium of molecular interactions and a new visualization tool for the study of gene regulatory networks.

Science.gov (United States)

Lepoivre, Cyrille; Bergon, Aurélie; Lopez, Fabrice; Perumal, Narayanan B; Nguyen, Catherine; Imbert, Jean; Puthier, Denis

2012-01-31

Deciphering gene regulatory networks by in silico approaches is a crucial step in the study of the molecular perturbations that occur in diseases. The development of regulatory maps is a tedious process requiring the comprehensive integration of various evidences scattered over biological databases. Thus, the research community would greatly benefit from having a unified database storing known and predicted molecular interactions. Furthermore, given the intrinsic complexity of the data, the development of new tools offering integrated and meaningful visualizations of molecular interactions is necessary to help users drawing new hypotheses without being overwhelmed by the density of the subsequent graph. We extend the previously developed TranscriptomeBrowser database with a set of tables containing 1,594,978 human and mouse molecular interactions. The database includes: (i) predicted regulatory interactions (computed by scanning vertebrate alignments with a set of 1,213 position weight matrices), (ii) potential regulatory interactions inferred from systematic analysis of ChIP-seq experiments, (iii) regulatory interactions curated from the literature, (iv) predicted post-transcriptional regulation by micro-RNA, (v) protein kinase-substrate interactions and (vi) physical protein-protein interactions. In order to easily retrieve and efficiently analyze these interactions, we developed In-teractomeBrowser, a graph-based knowledge browser that comes as a plug-in for Transcriptome-Browser. The first objective of InteractomeBrowser is to provide a user-friendly tool to get new insight into any gene list by providing a context-specific display of putative regulatory and physical interactions. To achieve this, InteractomeBrowser relies on a "cell compartments-based layout" that makes use of a subset of the Gene Ontology to map gene products onto relevant cell compartments. This layout is particularly powerful for visual integration of heterogeneous biological information

Setting up a Bioluminescence Resonance Energy Transfer high throughput screening assay to search for protein/protein interaction inhibitors in mammalian cells.

Directory of Open Access Journals (Sweden)

Cyril eCouturier

2012-09-01

Full Text Available Each step of the cell life and its response or adaptation to its environment are mediated by a network of protein/protein interactions termed interactome. Our knowledge of this network keeps growing due to the development of sensitive techniques devoted to study these interactions. The bioluminescence resonance energy transfer (BRET technique was primarily developed to allow the dynamic monitoring of protein-protein interactions in living cells, and has widely been used to study receptor activation by intra- or extra-molecular conformational changes within receptors and activated complexes in mammal cells. Some interactions are described as crucial in human pathological processes, and a new class of drugs targeting them has recently emerged. The BRET method is well suited to identify inhibitors of protein-protein interactions and here is described why and how to set up and optimize a High Throughput Screening assay based on BRET to search for such inhibitory compounds. The different parameters to take into account when developing such BRET assays in mammal cells are reviewed to give general guidelines: considerations on the targeted interaction, choice of BRET version, inducibility of the interaction, kinetic of the monitored interaction, and of the BRET reading, influence substrate concentration, number of cells and medium composition used on the Z’ factor, and expected interferences for colored or fluorescent compounds.

Characterization of protein interactomes of DNA damages: application to oxidation injuries

International Nuclear Information System (INIS)

Pietras-Barbier, Ewa

2013-01-01

Cyclo-nucleosides are complex DNA damages implying both bases and sugar residues. They are generated by free radicals, in particular by the effect of ionizing radiations, and are not easily covered by cellular mechanisms. Using a protein trapping technique on probes containing these injuries, the negative influence of cyclo-nucleosides on the recognition of its target sequence by a DREF transcription factor and on the interactions of PARP1 with DNA have been identified. Interactions between Fpg bacterial glycosylase and cyclo-nucleosides have been analysed and it has been found that this enzyme has an affinity for them, without excision activity. Finally, a Thermococcus gammatolerans radiation resistant archae has been studied: the formation of simple and complex oxidation injuries at strong radiation doses has been measured and the action mechanism of two new glycosylases has been explained. (author) [fr

The arabidopsis cyclic nucleotide interactome

KAUST Repository

Donaldson, Lara Elizabeth

2016-05-11

Background Cyclic nucleotides have been shown to play important signaling roles in many physiological processes in plants including photosynthesis and defence. Despite this, little is known about cyclic nucleotide-dependent signaling mechanisms in plants since the downstream target proteins remain unknown. This is largely due to the fact that bioinformatics searches fail to identify plant homologs of protein kinases and phosphodiesterases that are the main targets of cyclic nucleotides in animals. Methods An affinity purification technique was used to identify cyclic nucleotide binding proteins in Arabidopsis thaliana. The identified proteins were subjected to a computational analysis that included a sequence, transcriptional co-expression and functional annotation analysis in order to assess their potential role in plant cyclic nucleotide signaling. Results A total of twelve cyclic nucleotide binding proteins were identified experimentally including key enzymes in the Calvin cycle and photorespiration pathway. Importantly, eight of the twelve proteins were shown to contain putative cyclic nucleotide binding domains. Moreover, the identified proteins are post-translationally modified by nitric oxide, transcriptionally co-expressed and annotated to function in hydrogen peroxide signaling and the defence response. The activity of one of these proteins, GLYGOLATE OXIDASE 1, a photorespiratory enzyme that produces hydrogen peroxide in response to Pseudomonas, was shown to be repressed by a combination of cGMP and nitric oxide treatment. Conclusions We propose that the identified proteins function together as points of cross-talk between cyclic nucleotide, nitric oxide and reactive oxygen species signaling during the defence response.

A Versatile Platform to Analyze Low-Affinity and Transient Protein-Protein Interactions in Living Cells in Real Time

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Yao-Cheng Li

2014-12-01

Full Text Available Summary: Protein-protein interactions (PPIs play central roles in orchestrating biological processes. While some PPIs are stable, many important ones are transient and hard to detect with conventional approaches. We developed ReBiL, a recombinase enhanced bimolecular luciferase complementation platform, to enable detection of weak PPIs in living cells. ReBiL readily identified challenging transient interactions between an E3 ubiquitin ligase and an E2 ubiquitin-conjugating enzyme. ReBiL’s ability to rapidly interrogate PPIs in diverse conditions revealed that some stapled α-helical peptides, a class of PPI antagonists, induce target-independent cytosolic leakage and cytotoxicity that is antagonized by serum. These results explain the requirement for serum-free conditions to detect stapled peptide activity, and define a required parameter to evaluate for peptide antagonist approaches. ReBiL’s ability to expedite PPI analysis, assess target specificity and cell permeability, and reveal off-target effects of PPI modifiers should facilitate the development of effective, cell-permeable PPI therapeutics and the elaboration of diverse biological mechanisms. : Li et al. developed a recombinase-enhanced bimolecular luciferase complementation platform, termed ReBiL, to evaluate low-affinity protein-protein interactions (PPIs that are not detectable by other methods and to analyze PPI antagonists in living cells. ReBiL showed that small-molecule p53-Mdm2 antagonists disrupt their intended targets effectively in cells, whereas stapled peptides did not. Stapled peptides unexpectedly induced cell membrane disruption resulting in p53-independent death associated with cytoplasmic leakage. ReBiL is also valuable for high-throughput screening and for deciphering signaling mechanisms mediated by protein interactions.

Usher protein functions in hair cells and photoreceptors.

Science.gov (United States)

Cosgrove, Dominic; Zallocchi, Marisa

2014-01-01

The 10 different genes associated with the deaf/blind disorder, Usher syndrome, encode a number of structurally and functionally distinct proteins, most expressed as multiple isoforms/protein variants. Functional characterization of these proteins suggests a role in stereocilia development in cochlear hair cells, likely owing to adhesive interactions in hair bundles. In mature hair cells, homodimers of the Usher cadherins, cadherin 23 and protocadherin 15, interact to form a structural fiber, the tip link, and the linkages that anchor the taller stereocilia's actin cytoskeleton core to the shorter adjacent stereocilia and the elusive mechanotransduction channels, explaining the deafness phenotype when these molecular interactions are perturbed. The conundrum is that photoreceptors lack a synonymous mechanotransduction apparatus, and so a common theory for Usher protein function in the two neurosensory cell types affected in Usher syndrome is lacking. Recent evidence linking photoreceptor cell dysfunction in the shaker 1 mouse model for Usher syndrome to light-induced protein translocation defects, combined with localization of an Usher protein interactome at the periciliary region of the photoreceptors suggests Usher proteins might regulate protein trafficking between the inner and outer segments of photoreceptors. A distinct Usher protein complex is trafficked to the ribbon synapses of hair cells, and synaptic defects have been reported in Usher mutants in both hair cells and photoreceptors. This review aims to clarify what is known about Usher protein function at the synaptic and apical poles of hair cells and photoreceptors and the prospects for identifying a unifying pathobiological mechanism to explain deaf/blindness in Usher syndrome. Copyright © 2013 Elsevier Ltd. All rights reserved.

Analyzing Protein Denaturation using Fast Differential Scanning Calorimetry

NARCIS (Netherlands)

Splinter, R.; Van Herwaarden, A.W.; Iervolino, E.; Vanden Poel, G.; Istrate, D.; Sarro, P.M.

2012-01-01

This paper investigates the possibility to measure protein denaturation with Fast Differential Scanning Calorimetry (FDSC). Cancer can be diagnosed by measuring protein denaturation in blood plasma using Differential Scanning Calorimetry (DSC). FDSC can reduce diagnosis time from hours to minutes,

Different adaptation strategies of two citrus scion/rootstock combinations in response to drought stress.

Science.gov (United States)

Dutra de Souza, Joadson; de Andrade Silva, Edson Mario; Coelho Filho, Mauricio Antônio; Morillon, Raphaël; Bonatto, Diego; Micheli, Fabienne; da Silva Gesteira, Abelmon

2017-01-01

Scion/rootstock interaction is important for plant development and for breeding programs. In this context, polyploid rootstocks presented several advantages, mainly in relation to biotic and abiotic stresses. Here we analyzed the response to drought of two different scion/rootstock combinations presenting different polyploidy: the diploid (2x) and autotetraploid (4x) Rangpur lime (Citrus limonia, Osbeck) rootstocks grafted with 2x Valencia Delta sweet orange (Citrus sinensis) scions, named V/2xRL and V/4xRL, respectively. Based on previous gene expression data, we developed an interactomic approach to identify proteins involved in V/2xRL and V/4xRL response to drought. A main interactomic network containing 3,830 nodes and 97,652 edges was built from V/2xRL and V/4xRL data. Exclusive proteins of the V/2xRL and V/4xRL networks (2,056 and 1,001, respectively), as well as common to both networks (773) were identified. Functional clusters were obtained and two models of drought stress response for the V/2xRL and V/4xRL genotypes were designed. Even if the V/2xRL plant implement some tolerance mechanisms, the global plant response to drought was rapid and quickly exhaustive resulting in a general tendency to dehydration avoidance, which presented some advantage in short and strong drought stress conditions, but which, in long terms, does not allow the plant survival. At the contrary, the V/4xRL plants presented a response which strong impacts on development but that present some advantages in case of prolonged drought. Finally, some specific proteins, which presented high centrality on interactomic analysis were identified as good candidates for subsequent functional analysis of citrus genes related to drought response, as well as be good markers of one or another physiological mechanism implemented by the plants.

Proteomic analysis reveals new cardiac-specific dystrophin-associated proteins.

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Eric K Johnson

Full Text Available Mutations affecting the expression of dystrophin result in progressive loss of skeletal muscle function and cardiomyopathy leading to early mortality. Interestingly, clinical studies revealed no correlation in disease severity or age of onset between cardiac and skeletal muscles, suggesting that dystrophin may play overlapping yet different roles in these two striated muscles. Since dystrophin serves as a structural and signaling scaffold, functional differences likely arise from tissue-specific protein interactions. To test this, we optimized a proteomics-based approach to purify, identify and compare the interactome of dystrophin between cardiac and skeletal muscles from as little as 50 mg of starting material. We found selective tissue-specific differences in the protein associations of cardiac and skeletal muscle full length dystrophin to syntrophins and dystrobrevins that couple dystrophin to signaling pathways. Importantly, we identified novel cardiac-specific interactions of dystrophin with proteins known to regulate cardiac contraction and to be involved in cardiac disease. Our approach overcomes a major challenge in the muscular dystrophy field of rapidly and consistently identifying bona fide dystrophin-interacting proteins in tissues. In addition, our findings support the existence of cardiac-specific functions of dystrophin and may guide studies into early triggers of cardiac disease in Duchenne and Becker muscular dystrophies.

TranscriptomeBrowser 3.0: introducing a new compendium of molecular interactions and a new visualization tool for the study of gene regulatory networks

Directory of Open Access Journals (Sweden)

Lepoivre Cyrille

2012-01-01

Full Text Available Abstract Background Deciphering gene regulatory networks by in silico approaches is a crucial step in the study of the molecular perturbations that occur in diseases. The development of regulatory maps is a tedious process requiring the comprehensive integration of various evidences scattered over biological databases. Thus, the research community would greatly benefit from having a unified database storing known and predicted molecular interactions. Furthermore, given the intrinsic complexity of the data, the development of new tools offering integrated and meaningful visualizations of molecular interactions is necessary to help users drawing new hypotheses without being overwhelmed by the density of the subsequent graph. Results We extend the previously developed TranscriptomeBrowser database with a set of tables containing 1,594,978 human and mouse molecular interactions. The database includes: (i predicted regulatory interactions (computed by scanning vertebrate alignments with a set of 1,213 position weight matrices, (ii potential regulatory interactions inferred from systematic analysis of ChIP-seq experiments, (iii regulatory interactions curated from the literature, (iv predicted post-transcriptional regulation by micro-RNA, (v protein kinase-substrate interactions and (vi physical protein-protein interactions. In order to easily retrieve and efficiently analyze these interactions, we developed In-teractomeBrowser, a graph-based knowledge browser that comes as a plug-in for Transcriptome-Browser. The first objective of InteractomeBrowser is to provide a user-friendly tool to get new insight into any gene list by providing a context-specific display of putative regulatory and physical interactions. To achieve this, InteractomeBrowser relies on a "cell compartments-based layout" that makes use of a subset of the Gene Ontology to map gene products onto relevant cell compartments. This layout is particularly powerful for visual integration

A rapid and cost-effective fluorescence detection in tube (FDIT) method to analyze protein phosphorylation.

Science.gov (United States)

Jin, Xiao; Gou, Jin-Ying

2016-01-01

Protein phosphorylation is one of the most important post-translational modifications catalyzed by protein kinases in living organisms. The advance of genome sequencing provided the information of protein kinase families in many organisms, including both model and non-model plants. The development of proteomics technologies also enabled scientists to efficiently reveal a large number of protein phosphorylations of an organism. However, kinases and phosphorylation targets are still to be connected to illustrate the complicated network in life. Here we adapted Pro-Q ® Diamond (Pro-Q ® Diamond Phosphoprotein Gel Stain), a widely used phosphoprotein gel-staining fluorescence dye, to establish a rapid, economical and non-radioactive fluorescence detection in tube (FDIT) method to analyze phosphorylated proteins. Taking advantages of high sensitivity and specificity of Pro-Q ® diamond, the FDIT method is also demonstrated to be rapid and reliable, with a suitable linear range for in vitro protein phosphorylation. A significant and satisfactory protein kinase reaction was detected as fast as 15 min from Wheat Kinase START 1.1 (WKS1.1) on a thylakoid ascorbate peroxidase (tAPX), an established phosphorylation target in our earlier study. The FDIT method saves up to 95% of the dye consumed in a gel staining method. The FDIT method is remarkably quick, highly reproducible, unambiguous and capable to be scaled up to dozens of samples. The FDIT method could serve as a simple and sensitive alternative procedure to determine protein kinase reactions with zero radiation exposure, as a supplementation to other widely used radioactive and in-gel assays.

A rapid and cost-effective fluorescence detection in tube (FDIT method to analyze protein phosphorylation

Directory of Open Access Journals (Sweden)

Xiao Jin

2016-11-01

Full Text Available Abstract Background Protein phosphorylation is one of the most important post-translational modifications catalyzed by protein kinases in living organisms. The advance of genome sequencing provided the information of protein kinase families in many organisms, including both model and non-model plants. The development of proteomics technologies also enabled scientists to efficiently reveal a large number of protein phosphorylations of an organism. However, kinases and phosphorylation targets are still to be connected to illustrate the complicated network in life. Results Here we adapted Pro-Q® Diamond (Pro-Q® Diamond Phosphoprotein Gel Stain, a widely used phosphoprotein gel-staining fluorescence dye, to establish a rapid, economical and non-radioactive fluorescence detection in tube (FDIT method to analyze phosphorylated proteins. Taking advantages of high sensitivity and specificity of Pro-Q® diamond, the FDIT method is also demonstrated to be rapid and reliable, with a suitable linear range for in vitro protein phosphorylation. A significant and satisfactory protein kinase reaction was detected as fast as 15 min from Wheat Kinase START 1.1 (WKS1.1 on a thylakoid ascorbate peroxidase (tAPX, an established phosphorylation target in our earlier study. Conclusion The FDIT method saves up to 95% of the dye consumed in a gel staining method. The FDIT method is remarkably quick, highly reproducible, unambiguous and capable to be scaled up to dozens of samples. The FDIT method could serve as a simple and sensitive alternative procedure to determine protein kinase reactions with zero radiation exposure, as a supplementation to other widely used radioactive and in-gel assays.

Predicted protein interactions of IFITMs may shed light on mechanisms of Zika virus-induced microcephaly and host invasion [version 2; referees: 2 approved, 1 approved with reservations, 1 not approved

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Madhavi K. Ganapathiraju

2017-11-01

Full Text Available After the first reported case of Zika virus (ZIKV in Brazil, in 2015, a significant increase in the reported cases of microcephaly was observed. Microcephaly is a neurological condition in which the infant’s head is significantly smaller with complications in brain development. Recently, two small membrane-associated interferon-inducible transmembrane proteins (IFITM1 and IFITM3 have been shown to repress members of the flaviviridae family which includes ZIKV. However, the exact mechanisms leading to the inhibition of the virus are yet unknown. Here, we assembled an interactome of IFITM1 and IFITM3 with known protein-protein interactions (PPIs collected from publicly available databases and novel PPIs predicted using the High-confidence Protein-Protein Interaction Prediction (HiPPIP model. We analyzed the functional and pathway associations of the interacting proteins, and found that there are several immunity pathways (toll-like receptor signaling, cd28 signaling in T-helper cells, crosstalk between dendritic cells and natural killer cells, neuronal pathways (axonal guidance signaling, neural tube closure and actin cytoskeleton signaling and developmental pathways (neural tube closure, embryonic skeletal system development that are associated with these interactors. Our novel PPIs associate cilia dysfunction in ependymal cells to microcephaly, and may also shed light on potential targets of ZIKV for host invasion by immunosuppression and cytoskeletal rearrangements. These results could help direct future research in elucidating the mechanisms underlying host defense to ZIKV and other flaviviruses.

Two different protein expression profiles of oral squamous cell carcinoma analyzed by immunoprecipitation high-performance liquid chromatography.

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Kim, Soung Min; Jeong, Dasul; Kim, Min Keun; Lee, Sang Shin; Lee, Suk Keun

2017-08-08

Oral squamous cell carcinoma (OSCC) is one of the most dangerous cancers in the body, producing serious complications with individual behaviors. Many different pathogenetic factors are involved in the carcinogenesis of OSCC. Cancer cells derived from oral keratinocytes can produce different carcinogenic signaling pathways through differences in protein expression, but their protein expression profiles cannot be easily explored with ordinary detection methods. The present study compared the protein expression profiles between two different types of OSCCs, which were analyzed through immunoprecipitation high-performance liquid chromatography (IP-HPLC). Two types of squamous cell carcinoma (SCC) occurred in a mandibular (SCC-1) and maxillary gingiva (SCC-2), but their clinical features and progression were quite different from each other. SCC-1 showed a large gingival ulceration with severe halitosis and extensive bony destruction, while SCC-2 showed a relatively small papillary gingival swelling but rapidly grew to form a large submucosal mass, followed by early cervical lymph node metastasis. In the histological observation, SCC-1 was relatively well differentiated with a severe inflammatory reaction, while SCC-2 showed severely infiltrative growth of each cancer islets accompanied with a mild inflammatory reaction. IP-HPLC analysis revealed contrary protein expression profiles analyzed by 72 different oncogenic proteins. SCC-1 showed more cellular apoptosis and invasive growth than SCC-2 through increased expression of caspases, MMPs, p53 signaling, FAS signaling, TGF-β1 signaling, and angiogenesis factors, while SCC-2 showed more cellular growth and survival than SCC-1 through the increased expression of proliferating factors, RAS signaling, eIF5A signaling, WNT signaling, and survivin. The increased trends of cellular apoptosis and invasiveness in the protein expression profiles of SCC-1 were implicative of its extensive gingival ulceration and bony destruction

Bayesian modeling of the yeast SH3 domain interactome predicts spatiotemporal dynamics of endocytosis proteins.

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Raffi Tonikian

2009-10-01

Full Text Available SH3 domains are peptide recognition modules that mediate the assembly of diverse biological complexes. We scanned billions of phage-displayed peptides to map the binding specificities of the SH3 domain family in the budding yeast, Saccharomyces cerevisiae. Although most of the SH3 domains fall into the canonical classes I and II, each domain utilizes distinct features of its cognate ligands to achieve binding selectivity. Furthermore, we uncovered several SH3 domains with specificity profiles that clearly deviate from the two canonical classes. In conjunction with phage display, we used yeast two-hybrid and peptide array screening to independently identify SH3 domain binding partners. The results from the three complementary techniques were integrated using a Bayesian algorithm to generate a high-confidence yeast SH3 domain interaction map. The interaction map was enriched for proteins involved in endocytosis, revealing a set of SH3-mediated interactions that underlie formation of protein complexes essential to this biological pathway. We used the SH3 domain interaction network to predict the dynamic localization of several previously uncharacterized endocytic proteins, and our analysis suggests a novel role for the SH3 domains of Lsb3p and Lsb4p as hubs that recruit and assemble several endocytic complexes.

When the Web meets the cell: using personalized PageRank for analyzing protein interaction networks.

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Iván, Gábor; Grolmusz, Vince

2011-02-01

Enormous and constantly increasing quantity of biological information is represented in metabolic and in protein interaction network databases. Most of these data are freely accessible through large public depositories. The robust analysis of these resources needs novel technologies, being developed today. Here we demonstrate a technique, originating from the PageRank computation for the World Wide Web, for analyzing large interaction networks. The method is fast, scalable and robust, and its capabilities are demonstrated on metabolic network data of the tuberculosis bacterium and the proteomics analysis of the blood of melanoma patients. The Perl script for computing the personalized PageRank in protein networks is available for non-profit research applications (together with sample input files) at the address: http://uratim.com/pp.zip.

A collaborative filtering approach for protein-protein docking scoring functions.

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Bourquard, Thomas; Bernauer, Julie; Azé, Jérôme; Poupon, Anne

2011-04-22

A protein-protein docking procedure traditionally consists in two successive tasks: a search algorithm generates a large number of candidate conformations mimicking the complex existing in vivo between two proteins, and a scoring function is used to rank them in order to extract a native-like one. We have already shown that using Voronoi constructions and a well chosen set of parameters, an accurate scoring function could be designed and optimized. However to be able to perform large-scale in silico exploration of the interactome, a near-native solution has to be found in the ten best-ranked solutions. This cannot yet be guaranteed by any of the existing scoring functions. In this work, we introduce a new procedure for conformation ranking. We previously developed a set of scoring functions where learning was performed using a genetic algorithm. These functions were used to assign a rank to each possible conformation. We now have a refined rank using different classifiers (decision trees, rules and support vector machines) in a collaborative filtering scheme. The scoring function newly obtained is evaluated using 10 fold cross-validation, and compared to the functions obtained using either genetic algorithms or collaborative filtering taken separately. This new approach was successfully applied to the CAPRI scoring ensembles. We show that for 10 targets out of 12, we are able to find a near-native conformation in the 10 best ranked solutions. Moreover, for 6 of them, the near-native conformation selected is of high accuracy. Finally, we show that this function dramatically enriches the 100 best-ranking conformations in near-native structures.

Comparing human-Salmonella with plant-Salmonella protein-protein interaction predictions

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Sylvia eSchleker

2015-01-01

Full Text Available Salmonellosis is the most frequent food-borne disease world-wide and can be transmitted to humans by a variety of routes, especially via animal and plant products. Salmonella bacteria are believed to use not only animal and human but also plant hosts despite their evolutionary distance. This raises the question if Salmonella employs similar mechanisms in infection of these diverse hosts. Given that most of our understanding comes from its interaction with human hosts, we investigate here to what degree knowledge of Salmonella-human interactions can be transferred to the Salmonella-plant system. Reviewed are recent publications on analysis and prediction of Salmonella-host interactomes. Putative protein-protein interactions (PPIs between Salmonella and its human and Arabidopsis hosts were retrieved utilizing purely interolog-based approaches in which predictions were inferred based on available sequence and domain information of known PPIs, and machine learning approaches that integrate a larger set of useful information from different sources. Transfer learning is an especially suitable machine learning technique to predict plant host targets from the knowledge of human host targets. A comparison of the prediction results with transcriptomic data shows a clear overlap between the host proteins predicted to be targeted by PPIs and their gene ontology enrichment in both host species and regulation of gene expression. In particular, the cellular processes Salmonella interferes with in plants and humans are catabolic processes. The details of how these processes are targeted, however, are quite different between the two organisms, as expected based on their evolutionary and habitat differences. Possible implications of this observation on evolution of host-pathogen communication are discussed.

Proteomic-coupled-network analysis of T877A-androgen receptor interactomes can predict clinical prostate cancer outcomes between White (non-Hispanic and African-American groups.

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Naif Zaman

Full Text Available The androgen receptor (AR remains an important contributor to the neoplastic evolution of prostate cancer (CaP. CaP progression is linked to several somatic AR mutational changes that endow upon the AR dramatic gain-of-function properties. One of the most common somatic mutations identified is Thr877-to-Ala (T877A, located in the ligand-binding domain, that results in a receptor capable of promiscuous binding and activation by a variety of steroid hormones and ligands including estrogens, progestins, glucocorticoids, and several anti-androgens. In an attempt to further define somatic mutated AR gain-of-function properties, as a consequence of its promiscuous ligand binding, we undertook a proteomic/network analysis approach to characterize the protein interactome of the mutant T877A-AR in LNCaP cells under eight different ligand-specific treatments (dihydrotestosterone, mibolerone, R1881, testosterone, estradiol, progesterone, dexamethasone, and cyproterone acetate. In extending the analysis of our multi-ligand complexes of the mutant T877A-AR we observed significant enrichment of specific complexes between normal and primary prostatic tumors, which were furthermore correlated with known clinical outcomes. Further analysis of certain mutant T877A-AR complexes showed specific population preferences distinguishing primary prostatic disease between white (non-Hispanic vs. African-American males. Moreover, these cancer-related AR-protein complexes demonstrated predictive survival outcomes specific to CaP, and not for breast, lung, lymphoma or medulloblastoma cancers. Our study, by coupling data generated by our proteomics to network analysis of clinical samples, has helped to define real and novel biological pathways in complicated gain-of-function AR complex systems.

Protein characterization of pasteurized milk, cheese whey and their mixtures by using the CEM SprintTM analyzer

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Igor Moura Paiva

2016-06-01

Full Text Available In this work, the protein analyzer SprintTM was assessed regarding its capacity of predicting addition of whey in milk. This type of practice is relatively common in dairy plants, since whey, as it is a protein component, may be added with little loss of milk protein content. Besides,its incorrect elimination contributes to environmental pollution. Mixtures of milk and whey were prepared in different levels of addition and two methods of milk partition were tested. The results indicated that the concentration of trichloroacetic acid (TCA from the selected method was not suitable for the present purpose while the chosen method using glacial acetic acid (GAA has presented a satisfactory separation of the soluble and insoluble milk components. Even though the concentration of whey protein and casein are the essential parameters for determining whey addition in milk, the use of measurements from total protein was important in order to improve the linearity of the method due to the fact that the rates whey protein/total protein and casein/total protein presented the best results concerning fraud prediction capacity. Therefore, as the equipment is a rapid, safe and efficient platform, it can be used as an alternative to be implemented in laboratories of food quality control which perform or plan to perform assays to verify the whey addition in fluid milk.

A homologous mapping method for three-dimensional reconstruction of protein networks reveals disease-associated mutations.

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Huang, Sing-Han; Lo, Yu-Shu; Luo, Yong-Chun; Tseng, Yu-Yao; Yang, Jinn-Moon

2018-03-19

One of the crucial steps toward understanding the associations among molecular interactions, pathways, and diseases in a cell is to investigate detailed atomic protein-protein interactions (PPIs) in the structural interactome. Despite the availability of large-scale methods for analyzing PPI networks, these methods often focused on PPI networks using genome-scale data and/or known experimental PPIs. However, these methods are unable to provide structurally resolved interaction residues and their conservations in PPI networks. Here, we reconstructed a human three-dimensional (3D) structural PPI network (hDiSNet) with the detailed atomic binding models and disease-associated mutations by enhancing our PPI families and 3D-domain interologs from 60,618 structural complexes and complete genome database with 6,352,363 protein sequences across 2274 species. hDiSNet is a scale-free network (γ = 2.05), which consists of 5177 proteins and 19,239 PPIs with 5843 mutations. These 19,239 structurally resolved PPIs not only expanded the number of PPIs compared to present structural PPI network, but also achieved higher agreement with gene ontology similarities and higher co-expression correlation than the ones of 181,868 experimental PPIs recorded in public databases. Among 5843 mutations, 1653 and 790 mutations involved in interacting domains and contacting residues, respectively, are highly related to diseases. Our hDiSNet can provide detailed atomic interactions of human disease and their associated proteins with mutations. Our results show that the disease-related mutations are often located at the contacting residues forming the hydrogen bonds or conserved in the PPI family. In addition, hDiSNet provides the insights of the FGFR (EGFR)-MAPK pathway for interpreting the mechanisms of breast cancer and ErbB signaling pathway in brain cancer. Our results demonstrate that hDiSNet can explore structural-based interactions insights for understanding the mechanisms of disease

A side-effect free method for identifying cancer drug targets.

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Ashraf, Md Izhar; Ong, Seng-Kai; Mujawar, Shama; Pawar, Shrikant; More, Pallavi; Paul, Somnath; Lahiri, Chandrajit

2018-04-27

Identifying effective drug targets, with little or no side effects, remains an ever challenging task. A potential pitfall of failing to uncover the correct drug targets, due to side effect of pleiotropic genes, might lead the potential drugs to be illicit and withdrawn. Simplifying disease complexity, for the investigation of the mechanistic aspects and identification of effective drug targets, have been done through several approaches of protein interactome analysis. Of these, centrality measures have always gained importance in identifying candidate drug targets. Here, we put forward an integrated method of analysing a complex network of cancer and depict the importance of k-core, functional connectivity and centrality (KFC) for identifying effective drug targets. Essentially, we have extracted the proteins involved in the pathways leading to cancer from the pathway databases which enlist real experimental datasets. The interactions between these proteins were mapped to build an interactome. Integrative analyses of the interactome enabled us to unearth plausible reasons for drugs being rendered withdrawn, thereby giving future scope to pharmaceutical industries to potentially avoid them (e.g. ESR1, HDAC2, F2, PLG, PPARA, RXRA, etc). Based upon our KFC criteria, we have shortlisted ten proteins (GRB2, FYN, PIK3R1, CBL, JAK2, LCK, LYN, SYK, JAK1 and SOCS3) as effective candidates for drug development.

RNA-binding domain of the A protein component of the U1 small nuclear ribonucleoprotein analyzed by NMR spectroscopy is structurally similar to ribosomal proteins

International Nuclear Information System (INIS)

Hoffman, D.W.; Query, C.C.; Golden, B.L.; White, S.W.; Keene, J.D.

1991-01-01

An RNA recognition motif (RRM) of ∼80 amino acids constitutes the core of RNA-binding domains found in a large family of proteins involved in RNA processing. The U1 RNA-binding domain of the A protein component of the human U1 small nuclear ribonucleoprotein (RNP), which encompasses the RRM sequence, was analyzed by using NMR spectroscopy. The domain of the A protein is a highly stable monomer in solution consisting of four antiparallel β-strands and two α-helices. The highly conserved RNP1 and RNP2 consensus sequences, containing residues previously suggested to be involved in nucleic acid binding, are juxtaposed in adjacent β-strands. Conserved aromatic side chains that are critical for RNA binding are clustered on the surface to the molecule adjacent to a variable loop that influences recognition of specific RNA sequences. The secondary structure and topology of the RRM are similar to those of ribosomal proteins L12 and L30, suggesting a distant evolutionary relationship between these two types of RNA-associated proteins

Novel protein interactions with an actin homolog (MreB) of Helicobacter pylori determined by bacterial two-hybrid system.

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Zepeda Gurrola, Reyna Cristina; Fu, Yajuan; Rodríguez Luna, Isabel Cristina; Benítez Cardoza, Claudia Guadalupe; López López, María de Jesús; López Vidal, Yolanda; Gutíerrez, Germán Rubén Aguilar; Rodríguez Pérez, Mario A; Guo, Xianwu

2017-08-01

The bacterium Helicobacter pylori infects more than 50% of the world population and causes several gastroduodenal diseases, including gastric cancer. Nevertheless, we still need to explore some protein interactions that may be involved in pathogenesis. MreB, an actin homolog, showed some special characteristics in previous studies, indicating that it could have different functions. Protein functions could be realized via protein-protein interactions. In the present study, the MreB protein from H. pylori 26695 fused with two tags 10×His and GST in tandem was overexpressed and purified from Escherchia coli. The purified recombinant protein was used to perform a pull-down assay with H. pylori 26695 cell lysate. The pulled-down proteins were identified by mass spectrometry (MALDI-TOF), in which the known important proteins related to morphogenesis were absent but several proteins related to pathogenesis process were observed. The bacterial two-hybrid system was further used to evaluate the protein interactions and showed that new interactions of MreB respectively with VacA, UreB, HydB, HylB and AddA were confirmed but the interaction MreB-MreC was not validated. These results indicated that the protein MreB in H. pylori has a distinct interactome, does not participate in cell morphogenesis via MreB-MreC but could be related to pathogenesis. Copyright © 2017 Elsevier GmbH. All rights reserved.

Different adaptation strategies of two citrus scion/rootstock combinations in response to drought stress.

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Joadson Dutra de Souza

Full Text Available Scion/rootstock interaction is important for plant development and for breeding programs. In this context, polyploid rootstocks presented several advantages, mainly in relation to biotic and abiotic stresses. Here we analyzed the response to drought of two different scion/rootstock combinations presenting different polyploidy: the diploid (2x and autotetraploid (4x Rangpur lime (Citrus limonia, Osbeck rootstocks grafted with 2x Valencia Delta sweet orange (Citrus sinensis scions, named V/2xRL and V/4xRL, respectively. Based on previous gene expression data, we developed an interactomic approach to identify proteins involved in V/2xRL and V/4xRL response to drought. A main interactomic network containing 3,830 nodes and 97,652 edges was built from V/2xRL and V/4xRL data. Exclusive proteins of the V/2xRL and V/4xRL networks (2,056 and 1,001, respectively, as well as common to both networks (773 were identified. Functional clusters were obtained and two models of drought stress response for the V/2xRL and V/4xRL genotypes were designed. Even if the V/2xRL plant implement some tolerance mechanisms, the global plant response to drought was rapid and quickly exhaustive resulting in a general tendency to dehydration avoidance, which presented some advantage in short and strong drought stress conditions, but which, in long terms, does not allow the plant survival. At the contrary, the V/4xRL plants presented a response which strong impacts on development but that present some advantages in case of prolonged drought. Finally, some specific proteins, which presented high centrality on interactomic analysis were identified as good candidates for subsequent functional analysis of citrus genes related to drought response, as well as be good markers of one or another physiological mechanism implemented by the plants.

Decomposition of overlapping protein complexes: A graph theoretical method for analyzing static and dynamic protein associations

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Guimarães Katia S

2006-04-01

Full Text Available Abstract Background Most cellular processes are carried out by multi-protein complexes, groups of proteins that bind together to perform a specific task. Some proteins form stable complexes, while other proteins form transient associations and are part of several complexes at different stages of a cellular process. A better understanding of this higher-order organization of proteins into overlapping complexes is an important step towards unveiling functional and evolutionary mechanisms behind biological networks. Results We propose a new method for identifying and representing overlapping protein complexes (or larger units called functional groups within a protein interaction network. We develop a graph-theoretical framework that enables automatic construction of such representation. We illustrate the effectiveness of our method by applying it to TNFα/NF-κB and pheromone signaling pathways. Conclusion The proposed representation helps in understanding the transitions between functional groups and allows for tracking a protein's path through a cascade of functional groups. Therefore, depending on the nature of the network, our representation is capable of elucidating temporal relations between functional groups. Our results show that the proposed method opens a new avenue for the analysis of protein interaction networks.

Merging in-silico and in vitro salivary protein complex partners using the STRING database: A tutorial.

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Crosara, Karla Tonelli Bicalho; Moffa, Eduardo Buozi; Xiao, Yizhi; Siqueira, Walter Luiz

2018-01-16

Protein-protein interaction is a common physiological mechanism for protection and actions of proteins in an organism. The identification and characterization of protein-protein interactions in different organisms is necessary to better understand their physiology and to determine their efficacy. In a previous in vitro study using mass spectrometry, we identified 43 proteins that interact with histatin 1. Six previously documented interactors were confirmed and 37 novel partners were identified. In this tutorial, we aimed to demonstrate the usefulness of the STRING database for studying protein-protein interactions. We used an in-silico approach along with the STRING database (http://string-db.org/) and successfully performed a fast simulation of a novel constructed histatin 1 protein-protein network, including both the previously known and the predicted interactors, along with our newly identified interactors. Our study highlights the advantages and importance of applying bioinformatics tools to merge in-silico tactics with experimental in vitro findings for rapid advancement of our knowledge about protein-protein interactions. Our findings also indicate that bioinformatics tools such as the STRING protein network database can help predict potential interactions between proteins and thus serve as a guide for future steps in our exploration of the Human Interactome. Our study highlights the usefulness of the STRING protein database for studying protein-protein interactions. The STRING database can collect and integrate data about known and predicted protein-protein associations from many organisms, including both direct (physical) and indirect (functional) interactions, in an easy-to-use interface. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification of Novel Proteins Co-Purifying with Cockayne Syndrome Group B (CSB Reveals Potential Roles for CSB in RNA Metabolism and Chromatin Dynamics.

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Serena Nicolai

Full Text Available The CSB protein, a member of the SWI/SNF ATP dependent chromatin remodeling family of proteins, plays a role in a sub-pathway of nucleotide excision repair (NER known as transcription coupled repair (TCR. CSB is frequently mutated in Cockayne syndrome group B, a segmental progeroid human autosomal recessive disease characterized by growth failure and degeneration of multiple organs. Though initially classified as a DNA repair protein, recent studies have demonstrated that the loss of CSB results in pleiotropic effects. Identification of novel proteins belonging to the CSB interactome may be useful not only for predicting the molecular basis for diverse pathological symptoms of CS-B patients but also for unraveling the functions of CSB in addition to its authentic role in DNA repair. In this study, we performed tandem affinity purification (TAP technology coupled with mass spectrometry and co-immunoprecipitation studies to identify and characterize the proteins that potentially interact with CSB-TAP. Our approach revealed 33 proteins that were not previously known to interact with CSB. These newly identified proteins indicate potential roles for CSB in RNA metabolism involving repression and activation of transcription process and in the maintenance of chromatin dynamics and integrity.

HINT-KB: The human interactome knowledge base

KAUST Repository

Theofilatos, Konstantinos A.; Dimitrakopoulos, Christos M.; Kleftogiannis, Dimitrios A.; Moschopoulos, Charalampos N.; Papadimitriou, Stergios; Likothanassis, Spiridon D.; Mavroudi, Seferina P.

2012-01-01

Proteins and their interactions are considered to play a significant role in many cellular processes. The identification of Protein-Protein interactions (PPIs) in human is an open research area. Many Databases, which contain information about

High-throughput proteomics : optical approaches.

Energy Technology Data Exchange (ETDEWEB)

Davidson, George S.

2008-09-01

Realistic cell models could greatly accelerate our ability to engineer biochemical pathways and the production of valuable organic products, which would be of great use in the development of biofuels, pharmaceuticals, and the crops for the next green revolution. However, this level of engineering will require a great deal more knowledge about the mechanisms of life than is currently available. In particular, we need to understand the interactome (which proteins interact) as it is situated in the three dimensional geometry of the cell (i.e., a situated interactome), and the regulation/dynamics of these interactions. Methods for optical proteomics have become available that allow the monitoring and even disruption/control of interacting proteins in living cells. Here, a range of these methods is reviewed with respect to their role in elucidating the interactome and the relevant spatial localizations. Development of these technologies and their integration into the core competencies of research organizations can position whole institutions and teams of researchers to lead in both the fundamental science and the engineering applications of cellular biology. That leadership could be particularly important with respect to problems of national urgency centered around security, biofuels, and healthcare.

NR4A nuclear receptors are orphans but not lonesome.

Science.gov (United States)

Kurakula, Kondababu; Koenis, Duco S; van Tiel, Claudia M; de Vries, Carlie J M

2014-11-01

The NR4A subfamily of nuclear receptors consists of three mammalian members: Nur77, Nurr1, and NOR-1. The NR4A receptors are involved in essential physiological processes such as adaptive and innate immune cell differentiation, metabolism and brain function. They act as transcription factors that directly modulate gene expression, but can also form trans-repressive complexes with other transcription factors. In contrast to steroid hormone nuclear receptors such as the estrogen receptor or the glucocorticoid receptor, no ligands have been described for the NR4A receptors. This lack of known ligands might be explained by the structure of the ligand-binding domain of NR4A receptors, which shows an active conformation and a ligand-binding pocket that is filled with bulky amino acid side-chains. Other mechanisms, such as transcriptional control, post-translational modifications and protein-protein interactions therefore seem to be more important in regulating the activity of the NR4A receptors. For Nur77, over 80 interacting proteins (the interactome) have been identified so far, and roughly half of these interactions has been studied in more detail. Although the NR4As show some overlap in interacting proteins, less information is available on the interactome of Nurr1 and NOR-1. Therefore, the present review will describe the current knowledge on the interactomes of all three NR4A nuclear receptors with emphasis on Nur77. Copyright © 2014 Elsevier B.V. All rights reserved.

Taking advantage of local structure descriptors to analyze interresidue contacts in protein structures and protein complexes.

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Martin, Juliette; Regad, Leslie; Etchebest, Catherine; Camproux, Anne-Claude

2008-11-15

Interresidue protein contacts in proteins structures and at protein-protein interface are classically described by the amino acid types of interacting residues and the local structural context of the contact, if any, is described using secondary structures. In this study, we present an alternate analysis of interresidue contact using local structures defined by the structural alphabet introduced by Camproux et al. This structural alphabet allows to describe a 3D structure as a sequence of prototype fragments called structural letters, of 27 different types. Each residue can then be assigned to a particular local structure, even in loop regions. The analysis of interresidue contacts within protein structures defined using Voronoï tessellations reveals that pairwise contact specificity is greater in terms of structural letters than amino acids. Using a simple heuristic based on specificity score comparison, we find that 74% of the long-range contacts within protein structures are better described using structural letters than amino acid types. The investigation is extended to a set of protein-protein complexes, showing that the similar global rules apply as for intraprotein contacts, with 64% of the interprotein contacts best described by local structures. We then present an evaluation of pairing functions integrating structural letters to decoy scoring and show that some complexes could benefit from the use of structural letter-based pairing functions.

The expanding universe of ribonucleoproteins: of novel RNA-binding proteins and unconventional interactions.

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Beckmann, Benedikt M; Castello, Alfredo; Medenbach, Jan

2016-06-01

Post-transcriptional regulation of gene expression plays a critical role in almost all cellular processes. Regulation occurs mostly by RNA-binding proteins (RBPs) that recognise RNA elements and form ribonucleoproteins (RNPs) to control RNA metabolism from synthesis to decay. Recently, the repertoire of RBPs was significantly expanded owing to methodological advances such as RNA interactome capture. The newly identified RNA binders are involved in diverse biological processes and belong to a broad spectrum of protein families, many of them exhibiting enzymatic activities. This suggests the existence of an extensive crosstalk between RNA biology and other, in principle unrelated, cell functions such as intermediary metabolism. Unexpectedly, hundreds of new RBPs do not contain identifiable RNA-binding domains (RBDs), raising the question of how they interact with RNA. Despite the many functions that have been attributed to RNA, our understanding of RNPs is still mostly governed by a rather protein-centric view, leading to the idea that proteins have evolved to bind to and regulate RNA and not vice versa. However, RNPs formed by an RNA-driven interaction mechanism (RNA-determined RNPs) are abundant and offer an alternative explanation for the surprising lack of classical RBDs in many RNA-interacting proteins. Moreover, RNAs can act as scaffolds to orchestrate and organise protein networks and directly control their activity, suggesting that nucleic acids might play an important regulatory role in many cellular processes, including metabolism.

The human interactome knowledge base (hint-kb): An integrative human protein interaction database enriched with predicted protein–protein interaction scores using a novel hybrid technique

KAUST Repository

Theofilatos, Konstantinos A.; Dimitrakopoulos, Christos M.; Likothanassis, Spiridon D.; Kleftogiannis, Dimitrios A.; Moschopoulos, Charalampos N.; Alexakos, Christos; Papadimitriou, Stergios; Mavroudi, Seferina P.

2013-01-01

Proteins are the functional components of many cellular processes and the identification of their physical protein–protein interactions (PPIs) is an area of mature academic research. Various databases have been developed containing information about

A Cross-Species Study of PI3K Protein-Protein Interactions Reveals the Direct Interaction of P85 and SHP2

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Breitkopf, Susanne B.; Yang, Xuemei; Begley, Michael J.; Kulkarni, Meghana; Chiu, Yu-Hsin; Turke, Alexa B.; Lauriol, Jessica; Yuan, Min; Qi, Jie; Engelman, Jeffrey A.; Hong, Pengyu; Kontaridis, Maria I.; Cantley, Lewis C.; Perrimon, Norbert; Asara, John M.

2016-02-01

Using a series of immunoprecipitation (IP) - tandem mass spectrometry (LC-MS/MS) experiments and reciprocal BLAST, we conducted a fly-human cross-species comparison of the phosphoinositide-3-kinase (PI3K) interactome in a drosophila S2R+ cell line and several NSCLC and human multiple myeloma cell lines to identify conserved interacting proteins to PI3K, a critical signaling regulator of the AKT pathway. Using H929 human cancer cells and drosophila S2R+ cells, our data revealed an unexpected direct binding of Corkscrew, the drosophila ortholog of the non-receptor protein tyrosine phosphatase type II (SHP2) to the Pi3k21B (p60) regulatory subunit of PI3K (p50/p85 human ortholog) but no association with Pi3k92e, the human ortholog of the p110 catalytic subunit. The p85-SHP2 association was validated in human cell lines, and formed a ternary regulatory complex with GRB2-associated-binding protein 2 (GAB2). Validation experiments with knockdown of GAB2 and Far-Western blots proved the direct interaction of SHP2 with p85, independent of adaptor proteins and transfected FLAG-p85 provided evidence that SHP2 binding on p85 occurred on the SH2 domains. A disruption of the SHP2-p85 complex took place after insulin/IGF1 stimulation or imatinib treatment, suggesting that the direct SHP2-p85 interaction was both independent of AKT activation and positively regulates the ERK signaling pathway.

The human interactome knowledge base (hint-kb): An integrative human protein interaction database enriched with predicted protein–protein interaction scores using a novel hybrid technique

KAUST Repository

Theofilatos, Konstantinos A.

2013-07-12

Proteins are the functional components of many cellular processes and the identification of their physical protein–protein interactions (PPIs) is an area of mature academic research. Various databases have been developed containing information about experimentally and computationally detected human PPIs as well as their corresponding annotation data. However, these databases contain many false positive interactions, are partial and only a few of them incorporate data from various sources. To overcome these limitations, we have developed HINT-KB (http://biotools.ceid.upatras.gr/hint-kb/), a knowledge base that integrates data from various sources, provides a user-friendly interface for their retrieval, cal-culatesasetoffeaturesofinterest and computesaconfidence score for every candidate protein interaction. This confidence score is essential for filtering the false positive interactions which are present in existing databases, predicting new protein interactions and measuring the frequency of each true protein interaction. For this reason, a novel machine learning hybrid methodology, called (Evolutionary Kalman Mathematical Modelling—EvoKalMaModel), was used to achieve an accurate and interpretable scoring methodology. The experimental results indicated that the proposed scoring scheme outperforms existing computational methods for the prediction of PPIs.

PROFEAT Update: A Protein Features Web Server with Added Facility to Compute Network Descriptors for Studying Omics-Derived Networks.

Science.gov (United States)

Zhang, P; Tao, L; Zeng, X; Qin, C; Chen, S Y; Zhu, F; Yang, S Y; Li, Z R; Chen, W P; Chen, Y Z

2017-02-03

The studies of biological, disease, and pharmacological networks are facilitated by the systems-level investigations using computational tools. In particular, the network descriptors developed in other disciplines have found increasing applications in the study of the protein, gene regulatory, metabolic, disease, and drug-targeted networks. Facilities are provided by the public web servers for computing network descriptors, but many descriptors are not covered, including those used or useful for biological studies. We upgraded the PROFEAT web server http://bidd2.nus.edu.sg/cgi-bin/profeat2016/main.cgi for computing up to 329 network descriptors and protein-protein interaction descriptors. PROFEAT network descriptors comprehensively describe the topological and connectivity characteristics of unweighted (uniform binding constants and molecular levels), edge-weighted (varying binding constants), node-weighted (varying molecular levels), edge-node-weighted (varying binding constants and molecular levels), and directed (oriented processes) networks. The usefulness of the network descriptors is illustrated by the literature-reported studies of the biological networks derived from the genome, interactome, transcriptome, metabolome, and diseasome profiles. Copyright © 2016 Elsevier Ltd. All rights reserved.

CanisOme--The protein signatures of Canis lupus familiaris diseases.

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Fernandes, Mónica; Rosa, Nuno; Esteves, Eduardo; Correia, Maria José; Arrais, Joel; Ribeiro, Paulo; Vala, Helena; Barros, Marlene

2016-03-16

Although the applications of Proteomics in Human Biomedicine have been explored for some time now, in animal and veterinary research, the potential of this resource has just started to be explored, especially when companion animal health is considered. In the last years, knowledge on the Canis lupus familiaris proteome has been accumulating in the literature and a resource compiling all this information and critically reviewing it was lacking. This article presents such a resource for the first time. CanisOme is a database of all proteins identified in Canis lupus familiaris tissues, either in health or in disease, annotated with information on the proteins present on the sample and on the donors. This database reunites information on 549 proteins, associated with 63 dog diseases and 33 dog breeds. Examples of how this information may be used to produce new hypothesis on disease mechanisms is presented both through the functional analysis of the proteins quantified in canine cutaneous mast cell tumors and through the study of the interactome of C. lupus familiaris and Leishmania infantum. Therefore, the usefulness of CanisOme for researchers looking for protein biomarkers in dogs and interested in a comprehensive analysis of disease mechanisms is demonstrated. This paper presents CanisOme, a database of proteomic studies with relevant protein annotation, allowing the enlightenment of disease mechanisms and the discovery of novel disease biomarkers for C. lupus familiaris. This knowledge is important not only for the improvement of animal health but also for the use of dogs as models for human health studies. Copyright © 2016 Elsevier B.V. All rights reserved.

A two-hybrid assay to study protein interactions within the secretory pathway.

Directory of Open Access Journals (Sweden)

Danielle H Dube

Full Text Available Interactions of transcriptional activators are difficult to study using transcription-based two-hybrid assays due to potent activation resulting in false positives. Here we report the development of the Golgi two-hybrid (G2H, a method that interrogates protein interactions within the Golgi, where transcriptional activators can be assayed with negligible background. The G2H relies on cell surface glycosylation to report extracellularly on protein-protein interactions occurring within the secretory pathway. In the G2H, protein pairs are fused to modular domains of the reporter glycosyltransferase, Och1p, and proper cell wall formation due to Och1p activity is observed only when a pair of proteins interacts. Cells containing interacting protein pairs are identified by selectable phenotypes associated with Och1p activity and proper cell wall formation: cells that have interacting proteins grow under selective conditions and display weak wheat germ agglutinin (WGA binding by flow cytometry, whereas cells that lack interacting proteins display stunted growth and strong WGA binding. Using this assay, we detected the interaction between transcription factor MyoD and its binding partner Id2. Interfering mutations along the MyoD:Id2 interaction interface ablated signal in the G2H assay. Furthermore, we used the G2H to detect interactions of the activation domain of Gal4p with a variety of binding partners. Finally, selective conditions were used to enrich for cells encoding interacting partners. The G2H detects protein-protein interactions that cannot be identified via traditional two-hybrid methods and should be broadly useful for probing previously inaccessible subsets of the interactome, including transcriptional activators and proteins that traffic through the secretory pathway.

Identification of New Protein Interactions between Dengue Fever Virus and Its Hosts, Human and Mosquito

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Mairiang, Dumrong; Zhang, Huamei; Sodja, Ann; Murali, Thilakam; Suriyaphol, Prapat; Malasit, Prida; Limjindaporn, Thawornchai; Finley, Russell L.

2013-01-01

The four divergent serotypes of dengue virus are the causative agents of dengue fever, dengue hemorrhagic fever and dengue shock syndrome. About two-fifths of the world's population live in areas where dengue is prevalent, and thousands of deaths are caused by the viruses every year. Dengue virus is transmitted from one person to another primarily by the yellow fever mosquito, Aedes aegypti. Recent studies have begun to define how the dengue viral proteins interact with host proteins to mediate viral replication and pathogenesis. A combined analysis of these studies, however, suggests that many virus-host protein interactions remain to be identified, especially for the mosquito host. In this study, we used high-throughput yeast two-hybrid screening to identify mosquito and human proteins that physically interact with dengue proteins. We tested each identified host protein against the proteins from all four serotypes of dengue to identify interactions that are conserved across serotypes. We further confirmed many of the interactions using co-affinity purification assays. As in other large-scale screens, we identified some previously detected interactions and many new ones, moving us closer to a complete host – dengue protein interactome. To help summarize and prioritize the data for further study, we combined our interactions with other published data and identified a subset of the host-dengue interactions that are now supported by multiple forms of evidence. These data should be useful for understanding the interplay between dengue and its hosts and may provide candidates for drug targets and vector control strategies. PMID:23326450

Identification of new protein interactions between dengue fever virus and its hosts, human and mosquito.

Science.gov (United States)

Mairiang, Dumrong; Zhang, Huamei; Sodja, Ann; Murali, Thilakam; Suriyaphol, Prapat; Malasit, Prida; Limjindaporn, Thawornchai; Finley, Russell L

2013-01-01

The four divergent serotypes of dengue virus are the causative agents of dengue fever, dengue hemorrhagic fever and dengue shock syndrome. About two-fifths of the world's population live in areas where dengue is prevalent, and thousands of deaths are caused by the viruses every year. Dengue virus is transmitted from one person to another primarily by the yellow fever mosquito, Aedes aegypti. Recent studies have begun to define how the dengue viral proteins interact with host proteins to mediate viral replication and pathogenesis. A combined analysis of these studies, however, suggests that many virus-host protein interactions remain to be identified, especially for the mosquito host. In this study, we used high-throughput yeast two-hybrid screening to identify mosquito and human proteins that physically interact with dengue proteins. We tested each identified host protein against the proteins from all four serotypes of dengue to identify interactions that are conserved across serotypes. We further confirmed many of the interactions using co-affinity purification assays. As in other large-scale screens, we identified some previously detected interactions and many new ones, moving us closer to a complete host - dengue protein interactome. To help summarize and prioritize the data for further study, we combined our interactions with other published data and identified a subset of the host-dengue interactions that are now supported by multiple forms of evidence. These data should be useful for understanding the interplay between dengue and its hosts and may provide candidates for drug targets and vector control strategies.

Identification of new protein interactions between dengue fever virus and its hosts, human and mosquito.

Directory of Open Access Journals (Sweden)

Dumrong Mairiang

Full Text Available The four divergent serotypes of dengue virus are the causative agents of dengue fever, dengue hemorrhagic fever and dengue shock syndrome. About two-fifths of the world's population live in areas where dengue is prevalent, and thousands of deaths are caused by the viruses every year. Dengue virus is transmitted from one person to another primarily by the yellow fever mosquito, Aedes aegypti. Recent studies have begun to define how the dengue viral proteins interact with host proteins to mediate viral replication and pathogenesis. A combined analysis of these studies, however, suggests that many virus-host protein interactions remain to be identified, especially for the mosquito host. In this study, we used high-throughput yeast two-hybrid screening to identify mosquito and human proteins that physically interact with dengue proteins. We tested each identified host protein against the proteins from all four serotypes of dengue to identify interactions that are conserved across serotypes. We further confirmed many of the interactions using co-affinity purification assays. As in other large-scale screens, we identified some previously detected interactions and many new ones, moving us closer to a complete host - dengue protein interactome. To help summarize and prioritize the data for further study, we combined our interactions with other published data and identified a subset of the host-dengue interactions that are now supported by multiple forms of evidence. These data should be useful for understanding the interplay between dengue and its hosts and may provide candidates for drug targets and vector control strategies.

WD40-repeat proteins in plant cell wall formation: current evidence and research prospects

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Gea eGuerriero

2015-12-01

Full Text Available The metabolic complexity of living organisms relies on supramolecular protein structures which ensure vital processes, such as signal transduction, transcription, translation and cell wall synthesis. In eukaryotes WD40-repeat (WDR proteins often function as molecular hubs mediating supramolecular interactions. WDR proteins may display a variety of interacting partners and participate in the assembly of complexes involved in distinct cellular functions. In plants, the formation of lignocellulosic biomass involves extensive synthesis of cell wall polysaccharides, a process that requires the assembly of large transmembrane enzyme complexes, intensive vesicle trafficking, interactions with the cytoskeleton, and coordinated gene expression. Because of their function as supramolecular hubs, WDR proteins could participate in each or any of these steps, although to date only few WDR proteins have been linked to the cell wall by experimental evidence. Nevertheless, several potential cell wall-related WDR proteins were recently identified using in silico aproaches, such as analyses of co-expression, interactome and conserved gene neighbourhood. Notably, some WDR genes are frequently genomic neighbours of genes coding for GT2-family polysaccharide synthases in eukaryotes, and this WDR-GT2 collinear microsynteny is detected in diverse taxa. In angiosperms, two WDR genes are collinear to cellulose synthase genes, CESAs, whereas in ascomycetous fungi several WDR genes are adjacent to chitin synthase genes, chs. In this Perspective we summarize and discuss experimental and in silico studies on the possible involvement of WDR proteins in plant cell wall formation. The prospects of biotechnological engineering for enhanced biomass production are discussed.

HINT-KB: The human interactome knowledge base

KAUST Repository

Theofilatos, Konstantinos A.

2012-01-01

Proteins and their interactions are considered to play a significant role in many cellular processes. The identification of Protein-Protein interactions (PPIs) in human is an open research area. Many Databases, which contain information about experimentally and computationally detected human PPIs as well as their corresponding annotation data, have been developed. However, these databases contain many false positive interactions, are partial and only a few of them incorporate data from various sources. To overcome these limitations, we have developed HINT-KB (http://150.140.142.24:84/Default.aspx) which is a knowledge base that integrates data from various sources, provides a user-friendly interface for their retrieval, estimates a set of features of interest and computes a confidence score for every candidate protein interaction using a modern computational hybrid methodology. © 2012 IFIP International Federation for Information Processing.

Analyzing the Effects of Climate Factors on Soybean Protein, Oil Contents, and Composition by Extensive and High-Density Sampling in China.

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Song, Wenwen; Yang, Ruping; Wu, Tingting; Wu, Cunxiang; Sun, Shi; Zhang, Shouwei; Jiang, Bingjun; Tian, Shiyan; Liu, Xiaobing; Han, Tianfu

2016-05-25

From 2010 to 2013, 763 soybean samples were collected from an extensive area of China. The correlations between seed compositions and climate data were analyzed. The contents of crude protein and water-soluble protein, total amount of protein plus oil, and most of the amino acids were positively correlated with an accumulated temperature ≥15 °C (AT15) and the mean daily temperature (MDT) but were negatively correlated with hours of sunshine (HS) and diurnal temperature range (DTR). The correlations of crude oil and most fatty acids with climate factors were opposite to those of crude protein. Crude oil content had a quadratic regression relationship with MDT, and a positive correlation between oil content and MDT was found when the daily temperature was soybean protein and oil contents. The study illustrated the effects of climate factors on soybean protein and oil contents and proposed agronomic practices for improving soybean quality in different regions of China. The results provide a foundation for the regionalization of high-quality soybean production in China and similar regions in the world.

Phosphorylation of the Usher syndrome 1G protein SANS controls Magi2-mediated endocytosis.

Science.gov (United States)

Bauß, Katharina; Knapp, Barbara; Jores, Pia; Roepman, Ronald; Kremer, Hannie; Wijk, Erwin V; Märker, Tina; Wolfrum, Uwe

2014-08-01

The human Usher syndrome (USH) is a complex ciliopathy with at least 12 chromosomal loci assigned to three clinical subtypes, USH1-3. The heterogeneous USH proteins are organized into protein networks. Here, we identified Magi2 (membrane-associated guanylate kinase inverted-2) as a new component of the USH protein interactome, binding to the multifunctional scaffold protein SANS (USH1G). We showed that the SANS-Magi2 complex assembly is regulated by the phosphorylation of an internal PDZ-binding motif in the sterile alpha motif domain of SANS by the protein kinase CK2. We affirmed Magi2's role in receptor-mediated, clathrin-dependent endocytosis and showed that phosphorylated SANS tightly regulates Magi2-mediated endocytosis. Specific depletions by RNAi revealed that SANS and Magi2-mediated endocytosis regulates aspects of ciliogenesis. Furthermore, we demonstrated the localization of the SANS-Magi2 complex in the periciliary membrane complex facing the ciliary pocket of retinal photoreceptor cells in situ. Our data suggest that endocytotic processes may not only contribute to photoreceptor cell homeostasis but also counterbalance the periciliary membrane delivery accompanying the exocytosis processes for the cargo vesicle delivery. In USH1G patients, mutations in SANS eliminate Magi2 binding and thereby deregulate endocytosis, lead to defective ciliary transport modules and ultimately disrupt photoreceptor cell function inducing retinal degeneration. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Supplementary Material for: The arabidopsis cyclic nucleotide interactome

KAUST Repository

Donaldson, Lara; Meier, Stuart; Gehring, Christoph A

2016-01-01

Abstract Background Cyclic nucleotides have been shown to play important signaling roles in many physiological processes in plants including photosynthesis and defence. Despite this, little is known about cyclic nucleotide-dependent signaling mechanisms in plants since the downstream target proteins remain unknown. This is largely due to the fact that bioinformatics searches fail to identify plant homologs of protein kinases and phosphodiesterases that are the main targets of cyclic nucleotides in animals. Methods An affinity purification technique was used to identify cyclic nucleotide binding proteins in Arabidopsis thaliana. The identified proteins were subjected to a computational analysis that included a sequence, transcriptional co-expression and functional annotation analysis in order to assess their potential role in plant cyclic nucleotide signaling. Results A total of twelve cyclic nucleotide binding proteins were identified experimentally including key enzymes in the Calvin cycle and photorespiration pathway. Importantly, eight of the twelve proteins were shown to contain putative cyclic nucleotide binding domains. Moreover, the identified proteins are post-translationally modified by nitric oxide, transcriptionally co-expressed and annotated to function in hydrogen peroxide signaling and the defence response. The activity of one of these proteins, GLYGOLATE OXIDASE 1, a photorespiratory enzyme that produces hydrogen peroxide in response to Pseudomonas, was shown to be repressed by a combination of cGMP and nitric oxide treatment. Conclusions We propose that the identified proteins function together as points of cross-talk between cyclic nucleotide, nitric oxide and reactive oxygen species signaling during the defence response.

Cellular Assays for Ferredoxins: A Strategy for Understanding Electron Flow through Protein Carriers That Link Metabolic Pathways.

Science.gov (United States)

Atkinson, Joshua T; Campbell, Ian; Bennett, George N; Silberg, Jonathan J

2016-12-27

The ferredoxin (Fd) protein family is a structurally diverse group of iron-sulfur proteins that function as electron carriers, linking biochemical pathways important for energy transduction, nutrient assimilation, and primary metabolism. While considerable biochemical information about individual Fd protein electron carriers and their reactions has been acquired, we cannot yet anticipate the proportion of electrons shuttled between different Fd-partner proteins within cells using biochemical parameters that govern electron flow, such as holo-Fd concentration, midpoint potential (driving force), molecular interactions (affinity and kinetics), conformational changes (allostery), and off-pathway electron leakage (chemical oxidation). Herein, we describe functional and structural gaps in our Fd knowledge within the context of a sequence similarity network and phylogenetic tree, and we propose a strategy for improving our understanding of Fd sequence-function relationships. We suggest comparing the functions of divergent Fds within cells whose growth, or other measurable output, requires electron transfer between defined electron donor and acceptor proteins. By comparing Fd-mediated electron transfer with biochemical parameters that govern electron flow, we posit that models that anticipate energy flow across Fd interactomes can be built. This approach is expected to transform our ability to anticipate Fd control over electron flow in cellular settings, an obstacle to the construction of synthetic electron transfer pathways and rational optimization of existing energy-conserving pathways.

A systems wide mass spectrometric based linear motif screen to identify dominant in-vivo interacting proteins for the ubiquitin ligase MDM2.

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Nicholson, Judith; Scherl, Alex; Way, Luke; Blackburn, Elizabeth A; Walkinshaw, Malcolm D; Ball, Kathryn L; Hupp, Ted R

2014-06-01

Linear motifs mediate protein-protein interactions (PPI) that allow expansion of a target protein interactome at a systems level. This study uses a proteomics approach and linear motif sub-stratifications to expand on PPIs of MDM2. MDM2 is a multi-functional protein with over one hundred known binding partners not stratified by hierarchy or function. A new linear motif based on a MDM2 interaction consensus is used to select novel MDM2 interactors based on Nutlin-3 responsiveness in a cell-based proteomics screen. MDM2 binds a subset of peptide motifs corresponding to real proteins with a range of allosteric responses to MDM2 ligands. We validate cyclophilin B as a novel protein with a consensus MDM2 binding motif that is stabilised by Nutlin-3 in vivo, thus identifying one of the few known interactors of MDM2 that is stabilised by Nutlin-3. These data invoke two modes of peptide binding at the MDM2 N-terminus that rely on a consensus core motif to control the equilibrium between MDM2 binding proteins. This approach stratifies MDM2 interacting proteins based on the linear motif feature and provides a new biomarker assay to define clinically relevant Nutlin-3 responsive MDM2 interactors. Copyright © 2014 Elsevier Inc. All rights reserved.

The pepATTRACT web server for blind, large-scale peptide-protein docking.

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de Vries, Sjoerd J; Rey, Julien; Schindler, Christina E M; Zacharias, Martin; Tuffery, Pierre

2017-07-03

Peptide-protein interactions are ubiquitous in the cell and form an important part of the interactome. Computational docking methods can complement experimental characterization of these complexes, but current protocols are not applicable on the proteome scale. pepATTRACT is a novel docking protocol that is fully blind, i.e. it does not require any information about the binding site. In various stages of its development, pepATTRACT has participated in CAPRI, making successful predictions for five out of seven protein-peptide targets. Its performance is similar or better than state-of-the-art local docking protocols that do require binding site information. Here we present a novel web server that carries out the rigid-body stage of pepATTRACT. On the peptiDB benchmark, the web server generates a correct model in the top 50 in 34% of the cases. Compared to the full pepATTRACT protocol, this leads to some loss of performance, but the computation time is reduced from ∼18 h to ∼10 min. Combined with the fact that it is fully blind, this makes the web server well-suited for large-scale in silico protein-peptide docking experiments. The rigid-body pepATTRACT server is freely available at http://bioserv.rpbs.univ-paris-diderot.fr/services/pepATTRACT. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

A new theoretical approach to analyze complex processes in cytoskeleton proteins.

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Li, Xin; Kolomeisky, Anatoly B

2014-03-20

Cytoskeleton proteins are filament structures that support a large number of important biological processes. These dynamic biopolymers exist in nonequilibrium conditions stimulated by hydrolysis chemical reactions in their monomers. Current theoretical methods provide a comprehensive picture of biochemical and biophysical processes in cytoskeleton proteins. However, the description is only qualitative under biologically relevant conditions because utilized theoretical mean-field models neglect correlations. We develop a new theoretical method to describe dynamic processes in cytoskeleton proteins that takes into account spatial correlations in the chemical composition of these biopolymers. Our approach is based on analysis of probabilities of different clusters of subunits. It allows us to obtain exact analytical expressions for a variety of dynamic properties of cytoskeleton filaments. By comparing theoretical predictions with Monte Carlo computer simulations, it is shown that our method provides a fully quantitative description of complex dynamic phenomena in cytoskeleton proteins under all conditions.

Epsilon-Q: An Automated Analyzer Interface for Mass Spectral Library Search and Label-Free Protein Quantification.

Science.gov (United States)

Cho, Jin-Young; Lee, Hyoung-Joo; Jeong, Seul-Ki; Paik, Young-Ki

2017-12-01

Mass spectrometry (MS) is a widely used proteome analysis tool for biomedical science. In an MS-based bottom-up proteomic approach to protein identification, sequence database (DB) searching has been routinely used because of its simplicity and convenience. However, searching a sequence DB with multiple variable modification options can increase processing time, false-positive errors in large and complicated MS data sets. Spectral library searching is an alternative solution, avoiding the limitations of sequence DB searching and allowing the detection of more peptides with high sensitivity. Unfortunately, this technique has less proteome coverage, resulting in limitations in the detection of novel and whole peptide sequences in biological samples. To solve these problems, we previously developed the "Combo-Spec Search" method, which uses manually multiple references and simulated spectral library searching to analyze whole proteomes in a biological sample. In this study, we have developed a new analytical interface tool called "Epsilon-Q" to enhance the functions of both the Combo-Spec Search method and label-free protein quantification. Epsilon-Q performs automatically multiple spectral library searching, class-specific false-discovery rate control, and result integration. It has a user-friendly graphical interface and demonstrates good performance in identifying and quantifying proteins by supporting standard MS data formats and spectrum-to-spectrum matching powered by SpectraST. Furthermore, when the Epsilon-Q interface is combined with the Combo-Spec search method, called the Epsilon-Q system, it shows a synergistic function by outperforming other sequence DB search engines for identifying and quantifying low-abundance proteins in biological samples. The Epsilon-Q system can be a versatile tool for comparative proteome analysis based on multiple spectral libraries and label-free quantification.

PREFACE: Physics approaches to protein interactions and gene regulation Physics approaches to protein interactions and gene regulation

Science.gov (United States)

Nussinov, Ruth; Panchenko, Anna R.; Przytycka, Teresa

2011-06-01

Physics approaches focus on uncovering, modeling and quantitating the general principles governing the micro and macro universe. This has always been an important component of biological research, however recent advances in experimental techniques and the accumulation of unprecedented genome-scale experimental data produced by these novel technologies now allow for addressing fundamental questions on a large scale. These relate to molecular interactions, principles of bimolecular recognition, and mechanisms of signal propagation. The functioning of a cell requires a variety of intermolecular interactions including protein-protein, protein-DNA, protein-RNA, hormones, peptides, small molecules, lipids and more. Biomolecules work together to provide specific functions and perturbations in intermolecular communication channels often lead to cellular malfunction and disease. A full understanding of the interactome requires an in-depth grasp of the biophysical principles underlying individual interactions as well as their organization in cellular networks. Phenomena can be described at different levels of abstraction. Computational and systems biology strive to model cellular processes by integrating and analyzing complex data from multiple experimental sources using interdisciplinary tools. As a result, both the causal relationships between the variables and the general features of the system can be discovered, which even without knowing the details of the underlying mechanisms allow for putting forth hypotheses and predicting the behavior of the systems in response to perturbation. And here lies the strength of in silico models which provide control and predictive power. At the same time, the complexity of individual elements and molecules can be addressed by the fields of molecular biophysics, physical biology and structural biology, which focus on the underlying physico-chemical principles and may explain the molecular mechanisms of cellular function. In this issue

Identification of TTAGGG-binding proteins in Neurospora crassa, a fungus with vertebrate-like telomere repeats.

Science.gov (United States)

Casas-Vila, Núria; Scheibe, Marion; Freiwald, Anja; Kappei, Dennis; Butter, Falk

2015-11-17

To date, telomere research in fungi has mainly focused on Saccharomyces cerevisiae and Schizosaccharomyces pombe, despite the fact that both yeasts have degenerated telomeric repeats in contrast to the canonical TTAGGG motif found in vertebrates and also several other fungi. Using label-free quantitative proteomics, we here investigate the telosome of Neurospora crassa, a fungus with canonical telomeric repeats. We show that at least six of the candidates detected in our screen are direct TTAGGG-repeat binding proteins. While three of the direct interactors (NCU03416 [ncTbf1], NCU01991 [ncTbf2] and NCU02182 [ncTay1]) feature the known myb/homeobox DNA interaction domain also found in the vertebrate telomeric factors, we additionally show that a zinc-finger protein (NCU07846) and two proteins without any annotated DNA-binding domain (NCU02644 and NCU05718) are also direct double-strand TTAGGG binders. We further find two single-strand binders (NCU02404 [ncGbp2] and NCU07735 [ncTcg1]). By quantitative label-free interactomics we identify TTAGGG-binding proteins in Neurospora crassa, suggesting candidates for telomeric factors that are supported by phylogenomic comparison with yeast species. Intriguingly, homologs in yeast species with degenerated telomeric repeats are also TTAGGG-binding proteins, e.g. in S. cerevisiae Tbf1 recognizes the TTAGGG motif found in its subtelomeres. However, there is also a subset of proteins that is not conserved. While a rudimentary core TTAGGG-recognition machinery may be conserved across yeast species, our data suggests Neurospora as an emerging model organism with unique features.

Resistance to Inhibitors of Cholinesterase 3 (Ric-3 Expression Promotes Selective Protein Associations with the Human α7-Nicotinic Acetylcholine Receptor Interactome.

Directory of Open Access Journals (Sweden)

Matthew J Mulcahy

Full Text Available The α7-nicotinic acetylcholine receptor (α7-nAChR is a ligand-gated ion channel widely expressed in vertebrates and is associated with numerous physiological functions. As transmembrane ion channels, α7-nAChRs need to be expressed on the surface of the plasma membrane to function. The receptor has been reported to associate with proteins involved with receptor biogenesis, modulation of receptor properties, as well as intracellular signaling cascades and some of these associated proteins may affect surface expression of α7-nAChRs. The putative chaperone resistance to inhibitors of cholinesterase 3 (Ric-3 has been reported to interact with, and enhance the surface expression of, α7-nAChRs. In this study, we identified proteins that associate with α7-nAChRs when Ric-3 is expressed. Using α-bungarotoxin (α-bgtx, we isolated and compared α7-nAChR-associated proteins from two stably transfected, human tumor-derived cell lines: SH-EP1-hα7 expressing human α7-nAChRs and the same cell line further transfected to express Ric-3, SH-EP1-hα7-Ric-3. Mass spectrometric analysis of peptides identified thirty-nine proteins that are associated with α7-nAChRs only when Ric-3 was expressed. Significantly, and consistent with reports of Ric-3 function in the literature, several of the identified proteins are involved in biological processes that may affect nAChR surface expression such as post-translational processing of proteins, protein trafficking, and protein transport. Additionally, proteins affecting the cell cycle, the cytoskeleton, stress responses, as well as cyclic AMP- and inositol triphosphate-dependent signaling cascades were identified. These results illuminate how α-bgtx may be used to isolate and identify α7-nAChRs as well as how the expression of chaperones such as Ric-3 can influence proteins associating with α7-nAChRs. These associating proteins may alter activities of α7-nAChRs to expand their functionally-relevant repertoire as

Scaffold protein harmonin (USH1C) provides molecular links between Usher syndrome type 1 and type 2.

Science.gov (United States)

Reiners, Jan; van Wijk, Erwin; Märker, Tina; Zimmermann, Ulrike; Jürgens, Karin; te Brinke, Heleen; Overlack, Nora; Roepman, Ronald; Knipper, Marlies; Kremer, Hannie; Wolfrum, Uwe

2005-12-15

Usher syndrome (USH) is the most frequent cause of combined deaf-blindness in man. USH is clinically and genetically heterogeneous with at least 11 chromosomal loci assigned to the three USH types (USH1A-G, USH2A-C, USH3A). Although the different USH types exhibit almost the same phenotype in human, the identified USH genes encode for proteins which belong to very different protein classes and families. We and others recently reported that the scaffold protein harmonin (USH1C-gene product) integrates all identified USH1 molecules in a USH1-protein network. Here, we investigated the relationship between the USH2 molecules and this USH1-protein network. We show a molecular interaction between the scaffold protein harmonin (USH1C) and the USH2A protein, VLGR1 (USH2C) and the candidate for USH2B, NBC3. We pinpoint these interactions to interactions between the PDZ1 domain of harmonin and the PDZ-binding motifs at the C-termini of the USH2 proteins and NBC3. We demonstrate that USH2A, VLGR1 and NBC3 are co-expressed with the USH1-protein harmonin in the synaptic terminals of both retinal photoreceptors and inner ear hair cells. In hair cells, these USH proteins are also localized in the signal uptaking stereocilia. Our data indicate that the USH2 proteins and NBC3 are further partners in the supramolecular USH-protein network in the retina and inner ear which shed new light on the function of USH2 proteins and the entire USH-protein network. These findings provide first evidence for a molecular linkage between the pathophysiology in USH1 and USH2. The organization of USH molecules in a mutual 'interactome' related to the disease can explain the common phenotype in USH.

Mass Spectrometry-Based Proteomic Profiling of Thrombotic Material Obtained by Endovascular Thrombectomy in Patients with Ischemic Stroke

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Roberto Muñoz

2018-02-01

Full Text Available Thrombotic material retrieved from acute ischemic stroke (AIS patients represents a valuable source of biological information. In this study, we have developed a clinical proteomics workflow to characterize the protein cargo of thrombi derived from AIS patients. To analyze the thrombus proteome in a large-scale format, we developed a workflow that combines the isolation of thrombus by endovascular thrombectomy and peptide chromatographic fractionation coupled to mass-spectrometry. Using this workflow, we have characterized a specific proteomic expression profile derived from four AIS patients included in this study. Around 1600 protein species were unambiguously identified in the analyzed material. Functional bioinformatics analyses were performed, emphasizing a clustering of proteins with immunological functions as well as cardiopathy-related proteins with blood-cell dependent functions and peripheral vascular processes. In addition, we established a reference proteomic fingerprint of 341 proteins commonly detected in all patients. Protein interactome network of this subproteome revealed protein clusters involved in the interaction of fibronectin with 14-3-3 proteins, TGFβ signaling, and TCP complex network. Taken together, our data contributes to the repertoire of the human thrombus proteome, serving as a reference library to increase our knowledge about the molecular basis of thrombus derived from AIS patients, paving the way toward the establishment of a quantitative approach necessary to detect and characterize potential novel biomarkers in the stroke field.

Emerging putative associations between non-coding RNAs and protein-coding genes in Neuropathic Pain. Added value from re-using microarray data.

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Enrico Capobianco

2016-10-01

Full Text Available Regeneration of injured nerves is likely occurring in the peripheral nervous system, but not in the central nervous system. Although protein-coding gene expression has been assessed during nerve regeneration, little is currently known about the role of non-coding RNAs (ncRNAs. This leaves open questions about the potential effects of ncRNAs at transcriptome level. Due to the limited availability of human neuropathic pain data, we have identified the most comprehensive time-course gene expression profile referred to sciatic nerve injury, and studied in a rat model, using two neuronal tissues, namely dorsal root ganglion (DRG and sciatic nerve (SN. We have developed a methodology to identify differentially expressed bioentities starting from microarray probes, and re-purposing them to annotate ncRNAs, while analyzing the expression profiles of protein-coding genes. The approach is designed to reuse microarray data and perform first profiling and then meta-analysis through three main steps. First, we used contextual analysis to identify what we considered putative or potential protein coding targets for selected ncRNAs. Relevance was therefore assigned to differential expression of neighbor protein-coding genes, with neighborhood defined by a fixed genomic distance from long or antisense ncRNA loci, and of parent genes associated with pseudogenes. Second, connectivity among putative targets was used to build networks, in turn useful to conduct inference at interactomic scale. Last, network paths were annotated to assess relevance to neuropathic pain. We found significant differential expression in long-intergenic ncRNAs (32 lincRNAs in SN, and 8 in DRG, antisense RNA (31 asRNA in SN, and 12 in DRG and pseudogenes (456 in SN, 56 in DRG. In particular, contextual analysis centered on pseudogenes revealed some targets with known association to neurodegeneration and/or neurogenesis processes. While modules of the olfactory receptors were clearly

Y-box-binding protein 1 interacts with hepatitis C virus NS3/4A and influences the equilibrium between viral RNA replication and infectious particle production.

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Chatel-Chaix, Laurent; Melançon, Pierre; Racine, Marie-Ève; Baril, Martin; Lamarre, Daniel

2011-11-01

The hepatitis C virus (HCV) NS3/4A protein has several essential roles in the virus life cycle, most probably through dynamic interactions with host factors. To discover cellular cofactors that are co-opted by HCV for its replication, we elucidated the NS3/4A interactome using mass spectrometry and identified Y-box-binding protein 1 (YB-1) as an interacting partner of NS3/4A protein and HCV genomic RNA. Importantly, silencing YB-1 expression decreased viral RNA replication and severely impaired the propagation of the infectious HCV molecular clone JFH-1. Immunofluorescence studies further revealed a drastic HCV-dependent redistribution of YB-1 to the surface of the lipid droplets, an important organelle for HCV assembly. Core and NS3 protein-dependent polyprotein maturation were shown to be required for YB-1 relocalization. Unexpectedly, YB-1 knockdown cells showed the increased production of viral infectious particles while HCV RNA replication was impaired. Our data support that HCV hijacks YB-1-containing ribonucleoparticles and that YB-1-NS3/4A-HCV RNA complexes regulate the equilibrium between HCV RNA replication and viral particle production.

Phrase Mining of Textual Data to Analyze Extracellular Matrix Protein Patterns Across Cardiovascular Disease.

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Liem, David Alexandre; Murali, Sanjana; Sigdel, Dibakar; Shi, Yu; Wang, Xuan; Shen, Jiaming; Choi, Howard; Caufield, J Harry; Wang, Wei; Ping, Peipei; Han, Jiawei

2018-05-18

Extracellular matrix (ECM) proteins have been shown to play important roles regulating multiple biological processes in an array of organ systems, including the cardiovascular system. By using a novel bioinformatics text-mining tool, we studied six categories of cardiovascular disease (CVD), namely ischemic heart disease (IHD), cardiomyopathies (CM), cerebrovascular accident (CVA), congenital heart disease (CHD), arrhythmias (ARR), and valve disease (VD), anticipating novel ECM protein-disease and protein-protein relationships hidden within vast quantities of textual data. We conducted a phrase-mining analysis, delineating the relationships of 709 ECM proteins with the six groups of CVDs reported in 1,099,254 abstracts. The technology pipeline known as Context-aware Semantic Online Analytical Processing (CaseOLAP) was applied to semantically rank the association of proteins to each and all six CVDs, performing analyses to quantify each protein-disease relationship. We performed principal component analysis and hierarchical clustering of the data, where each protein is visualized as a six dimensional vector. We found that ECM proteins display variable degrees of association with the six CVDs; certain CVDs share groups of associated proteins whereas others have divergent protein associations. We identified 82 ECM proteins sharing associations with all six CVDs. Our bioinformatics analysis ascribed distinct ECM pathways (via Reactome) from this subset of proteins, namely insulin-like growth factor regulation and interleukin-4 and interleukin-13 signaling, suggesting their contribution to the pathogenesis of all six CVDs. Finally, we performed hierarchical clustering analysis and identified protein clusters associated with a targeted CVD; analyses revealed unexpected insights underlying ECM-pathogenesis of CVDs.

Multilayered proteomics reveals molecular switches dictating ligand-dependent EGFR trafficking

DEFF Research Database (Denmark)

Francavilla, Chiara; Papetti, Moreno; Rigbolt, Kristoffer T G

2016-01-01

, we devised an integrated multilayered proteomics approach (IMPA). We analyzed dynamic changes in the receptor interactome, ubiquitinome, phosphoproteome, and late proteome in response to both ligands in human cells by quantitative MS and identified 67 proteins regulated at multiple levels. We...... identified RAB7 phosphorylation and RCP recruitment to EGFR as switches for EGF and TGF-α outputs, controlling receptor trafficking, signaling duration, proliferation, and migration. By manipulating RCP levels or phosphorylation of RAB7 in EGFR-positive cancer cells, we were able to switch a TGF......-α-mediated response to an EGF-like response or vice versa as EGFR trafficking was rerouted. We propose IMPA as an approach to uncover fine-tuned regulatory mechanisms in cell signaling....

Analyzing the genes related to Alzheimer's disease via a network and pathway-based approach.

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Hu, Yan-Shi; Xin, Juncai; Hu, Ying; Zhang, Lei; Wang, Ju

2017-04-27

Our understanding of the molecular mechanisms underlying Alzheimer's disease (AD) remains incomplete. Previous studies have revealed that genetic factors provide a significant contribution to the pathogenesis and development of AD. In the past years, numerous genes implicated in this disease have been identified via genetic association studies on candidate genes or at the genome-wide level. However, in many cases, the roles of these genes and their interactions in AD are still unclear. A comprehensive and systematic analysis focusing on the biological function and interactions of these genes in the context of AD will therefore provide valuable insights to understand the molecular features of the disease. In this study, we collected genes potentially associated with AD by screening publications on genetic association studies deposited in PubMed. The major biological themes linked with these genes were then revealed by function and biochemical pathway enrichment analysis, and the relation between the pathways was explored by pathway crosstalk analysis. Furthermore, the network features of these AD-related genes were analyzed in the context of human interactome and an AD-specific network was inferred using the Steiner minimal tree algorithm. We compiled 430 human genes reported to be associated with AD from 823 publications. Biological theme analysis indicated that the biological processes and biochemical pathways related to neurodevelopment, metabolism, cell growth and/or survival, and immunology were enriched in these genes. Pathway crosstalk analysis then revealed that the significantly enriched pathways could be grouped into three interlinked modules-neuronal and metabolic module, cell growth/survival and neuroendocrine pathway module, and immune response-related module-indicating an AD-specific immune-endocrine-neuronal regulatory network. Furthermore, an AD-specific protein network was inferred and novel genes potentially associated with AD were identified. By

The conservation pattern of short linear motifs is highly correlated with the function of interacting protein domains

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Wang Yiguo

2008-10-01

Full Text Available Abstract Background Many well-represented domains recognize primary sequences usually less than 10 amino acids in length, called Short Linear Motifs (SLiMs. Accurate prediction of SLiMs has been difficult because they are short (often Results Our combined approach revealed that SLiMs are highly conserved in proteins from functional classes that are known to interact with a specific domain, but that they are not conserved in most other protein groups. We found that SLiMs recognized by SH2 domains were highly conserved in receptor kinases/phosphatases, adaptor molecules, and tyrosine kinases/phosphatases, that SLiMs recognized by SH3 domains were highly conserved in cytoskeletal and cytoskeletal-associated proteins, that SLiMs recognized by PDZ domains were highly conserved in membrane proteins such as channels and receptors, and that SLiMs recognized by S/T kinase domains were highly conserved in adaptor molecules, S/T kinases/phosphatases, and proteins involved in transcription or cell cycle control. We studied Tyr-SLiMs recognized by SH2 domains in more detail, and found that SH2-recognized Tyr-SLiMs on the cytoplasmic side of membrane proteins are more highly conserved than those on the extra-cellular side. Also, we found that SH2-recognized Tyr-SLiMs that are associated with SH3 motifs and a tyrosine kinase phosphorylation motif are more highly conserved. Conclusion The interactome of protein domains is reflected by the evolutionary conservation of SLiMs recognized by these domains. Combining scoring matrixes derived from peptide libraries and conservation analysis, we would be able to find those protein groups that are more likely to interact with specific domains.

Evaluation of a Bead-Free Coimmunoprecipitation Technique for Identification of Virus-Host Protein Interactions Using High-Resolution Mass Spectrometry.

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DeBlasio, Stacy L; Bereman, Michael S; Mahoney, Jaclyn; Thannhauser, Theodore W; Gray, Stewart M; MacCoss, Michael J; Cilia Heck, Michelle

2017-09-01

Protein interactions between virus and host are essential for viral propagation and movement, as viruses lack most of the proteins required to thrive on their own. Precision methods aimed at disrupting virus-host interactions represent new approaches to disease management but require in-depth knowledge of the identity and binding specificity of host proteins within these interaction networks. Protein coimmunoprecipitation (co-IP) coupled with mass spectrometry (MS) provides a high-throughput way to characterize virus-host interactomes in a single experiment. Common co-IP methods use antibodies immobilized on agarose or magnetic beads to isolate virus-host complexes in solutions of host tissue homogenate. Although these workflows are well established, they can be fairly laborious and expensive. Therefore, we evaluated the feasibility of using antibody-coated microtiter plates coupled with MS analysis as an easy, less expensive way to identify host proteins that interact with Potato leafroll virus (PLRV), an insect-borne RNA virus that infects potatoes. With the use of the bead-free platform, we were able to detect 36 plant and 1 nonstructural viral protein significantly coimmunoprecipitating with PLRV. Two of these proteins, a 14-3-3 signal transduction protein and malate dehydrogenase 2 (mMDH2), were detected as having a weakened or lost association with a structural mutant of the virus, demonstrating that the bead-free method is sensitive enough to detect quantitative differences that can be used to pin-point domains of interaction. Collectively, our analysis shows that the bead-free platform is a low-cost alternative that can be used by core facilities and other investigators to identify plant and viral proteins interacting with virions and/or the viral structural proteins.

The Cardiomyocyte RNA-Binding Proteome: Links to Intermediary Metabolism and Heart Disease

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Yalin Liao

2016-08-01

Full Text Available RNA functions through the dynamic formation of complexes with RNA-binding proteins (RBPs in all clades of life. We determined the RBP repertoire of beating cardiomyocytic HL-1 cells by jointly employing two in vivo proteomic methods, mRNA interactome capture and RBDmap. Together, these yielded 1,148 RBPs, 391 of which are shared with all other available mammalian RBP repertoires, while 393 are thus far unique to cardiomyocytes. RBDmap further identified 568 regions of RNA contact within 368 RBPs. The cardiomyocyte mRNA interactome composition reflects their unique biology. Proteins with roles in cardiovascular physiology or disease, mitochondrial function, and intermediary metabolism are all highly represented. Notably, we identified 73 metabolic enzymes as RBPs. RNA-enzyme contacts frequently involve Rossmann fold domains with examples in evidence of both, mutual exclusivity of, or compatibility between RNA binding and enzymatic function. Our findings raise the prospect of previously hidden RNA-mediated regulatory interactions among cardiomyocyte gene expression, physiology, and metabolism.

Using structural knowledge in the protein data bank to inform the search for potential host-microbe protein interactions in sequence space: application to Mycobacterium tuberculosis.

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Mahajan, Gaurang; Mande, Shekhar C

2017-04-04

A comprehensive map of the human-M. tuberculosis (MTB) protein interactome would help fill the gaps in our understanding of the disease, and computational prediction can aid and complement experimental studies towards this end. Several sequence-based in silico approaches tap the existing data on experimentally validated protein-protein interactions (PPIs); these PPIs serve as templates from which novel interactions between pathogen and host are inferred. Such comparative approaches typically make use of local sequence alignment, which, in the absence of structural details about the interfaces mediating the template interactions, could lead to incorrect inferences, particularly when multi-domain proteins are involved. We propose leveraging the domain-domain interaction (DDI) information in PDB complexes to score and prioritize candidate PPIs between host and pathogen proteomes based on targeted sequence-level comparisons. Our method picks out a small set of human-MTB protein pairs as candidates for physical interactions, and the use of functional meta-data suggests that some of them could contribute to the in vivo molecular cross-talk between pathogen and host that regulates the course of the infection. Further, we present numerical data for Pfam domain families that highlights interaction specificity on the domain level. Not every instance of a pair of domains, for which interaction evidence has been found in a few instances (i.e. structures), is likely to functionally interact. Our sorting approach scores candidates according to how "distant" they are in sequence space from known examples of DDIs (templates). Thus, it provides a natural way to deal with the heterogeneity in domain-level interactions. Our method represents a more informed application of local alignment to the sequence-based search for potential human-microbial interactions that uses available PPI data as a prior. Our approach is somewhat limited in its sensitivity by the restricted size and

Dioscorea alata tuber proteome analysis shows over thirty dioscorin isoforms and novel tuber proteins.

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Sharma, Shruti; Gupta, Ravi; Deswal, Renu

2017-05-01

In Dioscorea, dioscorin (31 kDa) is the major storage protein constituting 85% of the total tuber proteins. An integrated proteomic and biochemical approach was used to understand the physiological role of dioscorin in the two contrasting growth stages (germinating and mature tuber). HPLC analysis showed 3 fold reduction in mannitol and 12.88 and 1.24 fold increase in sucrose and maltose in the germinating tuber. A 1.8 and 3 fold increase in sucrose phosphate synthase and mannitol dehydrogenase activity respectively was observed in the germinating tuber while a 2 fold higher invertase probably lowers the sucrose accumulation in the mature tuber. SDS-PAGE and 2-D maps of the mature and germinating tubers confirmed depletion (more than 50%) of dioscorin on germination. Dioscorin was purified using ion exchange and gel filtration chromatography with 43.32 fold purification and 38.16 yield. Out of a trail of 35 spots at 31 kDa only 12 spots (identified as dioscorin isoforms) were present in the 2D gel of the purified fraction. To search for other tuber proteins besides dioscorin, the unbound fractions of DEAE column were analysed by 2DGE. DREB 1A, caffeic acid 3-O-methyltransferase and Rab-1 small GTP binding protein were identified perhaps for the first time in the Dioscorea proteome. The interactome analysis revealed these to be involved in oxidative stress, carotenoid synthesis and vesicular transport. This is perhaps the first attempt to identify tuber proteome (although limited) and to understand the physiological significance of these proteins. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Evaluation of Colorimetric Assays for Analyzing Reductively Methylated Proteins: Biases and Mechanistic Insights

OpenAIRE

Brady, Pamlea N.; Macnaughtan, Megan A.

2015-01-01

Colorimetric protein assays, such as the Coomassie blue G-250 dye-binding (Bradford) and bicinchoninic acid (BCA) assays, are commonly used to quantify protein concentration. The accuracy of these assays depends on the amino acid composition. Because of the extensive use of reductive methylation in the study of proteins and the importance of biological methylation, it is necessary to evaluate the impact of lysyl methylation on the Bradford and BCA assays. Unmodified and reductively methylated...

Codon Bias Patterns of E. coli's Interacting Proteins.

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Maddalena Dilucca

Full Text Available Synonymous codons, i.e., DNA nucleotide triplets coding for the same amino acid, are used differently across the variety of living organisms. The biological meaning of this phenomenon, known as codon usage bias, is still controversial. In order to shed light on this point, we propose a new codon bias index, CompAI, that is based on the competition between cognate and near-cognate tRNAs during translation, without being tuned to the usage bias of highly expressed genes. We perform a genome-wide evaluation of codon bias for E.coli, comparing CompAI with other widely used indices: tAI, CAI, and Nc. We show that CompAI and tAI capture similar information by being positively correlated with gene conservation, measured by the Evolutionary Retention Index (ERI, and essentiality, whereas, CAI and Nc appear to be less sensitive to evolutionary-functional parameters. Notably, the rate of variation of tAI and CompAI with ERI allows to obtain sets of genes that consistently belong to specific clusters of orthologous genes (COGs. We also investigate the correlation of codon bias at the genomic level with the network features of protein-protein interactions in E.coli. We find that the most densely connected communities of the network share a similar level of codon bias (as measured by CompAI and tAI. Conversely, a small difference in codon bias between two genes is, statistically, a prerequisite for the corresponding proteins to interact. Importantly, among all codon bias indices, CompAI turns out to have the most coherent distribution over the communities of the interactome, pointing to the significance of competition among cognate and near-cognate tRNAs for explaining codon usage adaptation. Notably, CompAI may potentially correlate with translation speed measurements, by accounting for the specific delay induced by wobble-pairing between codons and anticodons.

A procedure to analyze surface profiles of the protein molecules visualized by quick-freeze deep-etch replica electron microscopy

Energy Technology Data Exchange (ETDEWEB)

Kimori, Yoshitaka [Division of Biomolecular Imaging, Institute of Medical Science, The University of Tokyo, Minato-ku, Tokyo 108-8639 (Japan); Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, Iizuka, Fukuoka 820-8502 (Japan); Oguchi, Yosuke [Department of Electric Engineering, Kogakuin University, Hachioji, Tokyo 192-0015 (Japan); Ichise, Norihiko [Department of Visual Communication, Komazawa Women' s University, Inagi, Tokyo 206-8511 (Japan); Baba, Norio [Department of Electric Engineering, Kogakuin University, Hachioji, Tokyo 192-0015 (Japan); Katayama, Eisaku [Division of Biomolecular Imaging, Institute of Medical Science, The University of Tokyo, Minato-ku, Tokyo 108-8639 (Japan)]. E-mail: ekatayam@ims.u-tokyo.ac.jp

2007-01-15

Quick-freeze deep-etch replica electron microscopy gives high contrast snapshots of individual protein molecules under physiological conditions in vitro or in situ. The images show delicate internal pattern, possibly reflecting the rotary-shadowed surface profile of the molecule. As a step to build the new system for the 'Structural analysis of single molecules', we propose a procedure to quantitatively characterize the structural property of individual molecules; e.g. conformational type and precise view-angle of the molecules, if the crystallographic structure of the target molecule is available. This paper presents a framework to determine the observed face of the protein molecule by analyzing the surface profile of individual molecules visualized in freeze-replica specimens. A comprehensive set of rotary-shadowed views of the protein molecule was artificially generated from the available atomic coordinates using light-rendering software. Exploiting new mathematical morphology-based image filter, characteristic features were extracted from each image and stored as template. Similar features were extracted from the true replica image and the most likely projection angle and the conformation of the observed particle were determined by quantitative comparison with a set of archived images. The performance and the robustness of the procedure were examined with myosin head structure in defined configuration for actual application.

A procedure to analyze surface profiles of the protein molecules visualized by quick-freeze deep-etch replica electron microscopy

International Nuclear Information System (INIS)

Kimori, Yoshitaka; Oguchi, Yosuke; Ichise, Norihiko; Baba, Norio; Katayama, Eisaku

2007-01-01

Quick-freeze deep-etch replica electron microscopy gives high contrast snapshots of individual protein molecules under physiological conditions in vitro or in situ. The images show delicate internal pattern, possibly reflecting the rotary-shadowed surface profile of the molecule. As a step to build the new system for the 'Structural analysis of single molecules', we propose a procedure to quantitatively characterize the structural property of individual molecules; e.g. conformational type and precise view-angle of the molecules, if the crystallographic structure of the target molecule is available. This paper presents a framework to determine the observed face of the protein molecule by analyzing the surface profile of individual molecules visualized in freeze-replica specimens. A comprehensive set of rotary-shadowed views of the protein molecule was artificially generated from the available atomic coordinates using light-rendering software. Exploiting new mathematical morphology-based image filter, characteristic features were extracted from each image and stored as template. Similar features were extracted from the true replica image and the most likely projection angle and the conformation of the observed particle were determined by quantitative comparison with a set of archived images. The performance and the robustness of the procedure were examined with myosin head structure in defined configuration for actual application

Visualization of protein interaction networks: problems and solutions

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Agapito Giuseppe

2013-01-01

Full Text Available Abstract Background Visualization concerns the representation of data visually and is an important task in scientific research. Protein-protein interactions (PPI are discovered using either wet lab techniques, such mass spectrometry, or in silico predictions tools, resulting in large collections of interactions stored in specialized databases. The set of all interactions of an organism forms a protein-protein interaction network (PIN and is an important tool for studying the behaviour of the cell machinery. Since graphic representation of PINs may highlight important substructures, e.g. protein complexes, visualization is more and more used to study the underlying graph structure of PINs. Although graphs are well known data structures, there are different open problems regarding PINs visualization: the high number of nodes and connections, the heterogeneity of nodes (proteins and edges (interactions, the possibility to annotate proteins and interactions with biological information extracted by ontologies (e.g. Gene Ontology that enriches the PINs with semantic information, but complicates their visualization. Methods In these last years many software tools for the visualization of PINs have been developed. Initially thought for visualization only, some of them have been successively enriched with new functions for PPI data management and PIN analysis. The paper analyzes the main software tools for PINs visualization considering four main criteria: (i technology, i.e. availability/license of the software and supported OS (Operating System platforms; (ii interoperability, i.e. ability to import/export networks in various formats, ability to export data in a graphic format, extensibility of the system, e.g. through plug-ins; (iii visualization, i.e. supported layout and rendering algorithms and availability of parallel implementation; (iv analysis, i.e. availability of network analysis functions, such as clustering or mining of the graph, and the

Completing sparse and disconnected protein-protein network by deep learning.

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Huang, Lei; Liao, Li; Wu, Cathy H

2018-03-22

Protein-protein interaction (PPI) prediction remains a central task in systems biology to achieve a better and holistic understanding of cellular and intracellular processes. Recently, an increasing number of computational methods have shifted from pair-wise prediction to network level prediction. Many of the existing network level methods predict PPIs under the assumption that the training network should be connected. However, this assumption greatly affects the prediction power and limits the application area because the current golden standard PPI networks are usually very sparse and disconnected. Therefore, how to effectively predict PPIs based on a training network that is sparse and disconnected remains a challenge. In this work, we developed a novel PPI prediction method based on deep learning neural network and regularized Laplacian kernel. We use a neural network with an autoencoder-like architecture to implicitly simulate the evolutionary processes of a PPI network. Neurons of the output layer correspond to proteins and are labeled with values (1 for interaction and 0 for otherwise) from the adjacency matrix of a sparse disconnected training PPI network. Unlike autoencoder, neurons at the input layer are given all zero input, reflecting an assumption of no a priori knowledge about PPIs, and hidden layers of smaller sizes mimic ancient interactome at different times during evolution. After the training step, an evolved PPI network whose rows are outputs of the neural network can be obtained. We then predict PPIs by applying the regularized Laplacian kernel to the transition matrix that is built upon the evolved PPI network. The results from cross-validation experiments show that the PPI prediction accuracies for yeast data and human data measured as AUC are increased by up to 8.4 and 14.9% respectively, as compared to the baseline. Moreover, the evolved PPI network can also help us leverage complementary information from the disconnected training network

Adipocyte size and cellular expression of caveolar proteins analyzed by confocal microscopy

DEFF Research Database (Denmark)

Hulstrøm, Veronica; Prats Gavalda, Clara; Vinten, Jørgen

2013-01-01

Caveolae are abundant in adipocytes and are involved in the regulation of lipid accumulation, which is the main volume determinant of these cells. We have developed and applied a confocal microscopic technique for measuring individual cellular expression of the caveolar proteins cavin-1 and caveo......Caveolae are abundant in adipocytes and are involved in the regulation of lipid accumulation, which is the main volume determinant of these cells. We have developed and applied a confocal microscopic technique for measuring individual cellular expression of the caveolar proteins cavin-1...

Evidence That a Psychopathology Interactome Has Diagnostic Value, Predicting Clinical Needs: An Experience Sampling Study

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van Os, Jim; Lataster, Tineke; Delespaul, Philippe; Wichers, Marieke; Myin-Germeys, Inez

2014-01-01

measures of psychopathology, similarly moderated by momentary interactions with emotions and context. Conclusion The results suggest that psychopathology, represented as an interactome at the momentary level of temporal resolution, is informative in diagnosing clinical needs, over and above traditional symptom measures. PMID:24466189

Network-based association of hypoxia-responsive genes with cardiovascular diseases

International Nuclear Information System (INIS)

Wang, Rui-Sheng; Oldham, William M; Loscalzo, Joseph

2014-01-01

Molecular oxygen is indispensable for cellular viability and function. Hypoxia is a stress condition in which oxygen demand exceeds supply. Low cellular oxygen content induces a number of molecular changes to activate regulatory pathways responsible for increasing the oxygen supply and optimizing cellular metabolism under limited oxygen conditions. Hypoxia plays critical roles in the pathobiology of many diseases, such as cancer, heart failure, myocardial ischemia, stroke, and chronic lung diseases. Although the complicated associations between hypoxia and cardiovascular (and cerebrovascular) diseases (CVD) have been recognized for some time, there are few studies that investigate their biological link from a systems biology perspective. In this study, we integrate hypoxia genes, CVD genes, and the human protein interactome in order to explore the relationship between hypoxia and cardiovascular diseases at a systems level. We show that hypoxia genes are much closer to CVD genes in the human protein interactome than that expected by chance. We also find that hypoxia genes play significant bridging roles in connecting different cardiovascular diseases. We construct a hypoxia-CVD bipartite network and find several interesting hypoxia-CVD modules with significant gene ontology similarity. Finally, we show that hypoxia genes tend to have more CVD interactors in the human interactome than in random networks of matching topology. Based on these observations, we can predict novel genes that may be associated with CVD. This network-based association study gives us a broad view of the relationships between hypoxia and cardiovascular diseases and provides new insights into the role of hypoxia in cardiovascular biology. (paper)

Water-Protein Interactions: The Secret of Protein Dynamics

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Silvia Martini

2013-01-01

Full Text Available Water-protein interactions help to maintain flexible conformation conditions which are required for multifunctional protein recognition processes. The intimate relationship between the protein surface and hydration water can be analyzed by studying experimental water properties measured in protein systems in solution. In particular, proteins in solution modify the structure and the dynamics of the bulk water at the solute-solvent interface. The ordering effects of proteins on hydration water are extended for several angstroms. In this paper we propose a method for analyzing the dynamical properties of the water molecules present in the hydration shells of proteins. The approach is based on the analysis of the effects of protein-solvent interactions on water protons NMR relaxation parameters. NMR relaxation parameters, especially the nonselective (R1NS and selective (R1SE spin-lattice relaxation rates of water protons, are useful for investigating the solvent dynamics at the macromolecule-solvent interfaces as well as the perturbation effects caused by the water-macromolecule interactions on the solvent dynamical properties. In this paper we demonstrate that Nuclear Magnetic Resonance Spectroscopy can be used to determine the dynamical contributions of proteins to the water molecules belonging to their hydration shells.

Complex Systems Analysis of Cell Cycling Models in Carcinogenesis:II. Cell Genome and Interactome, Neoplastic Non-random Transformation Models in Topoi with Lukasiewicz-Logic and MV Algebras

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Baianu, I C

2004-01-01

Quantitative Biology, abstract q-bio.OT/0406045 From: I.C. Baianu Dr. [view email] Date (v1): Thu, 24 Jun 2004 02:45:13 GMT (164kb) Date (revised v2): Fri, 2 Jul 2004 00:58:06 GMT (160kb) Complex Systems Analysis of Cell Cycling Models in Carcinogenesis: II. Authors: I.C. Baianu Comments: 23 pages, 1 Figure Report-no: CC04 Subj-class: Other Carcinogenesis is a complex process that involves dynamically inter-connected modular sub-networks that evolve under the influence of micro-environmentally induced perturbations, in non-random, pseudo-Markov chain processes. An appropriate n-stage model of carcinogenesis involves therefore n-valued Logic treatments of nonlinear dynamic transformations of complex functional genomes and cell interactomes. Lukasiewicz Algebraic Logic models of genetic networks and signaling pathways in cells are formulated in terms of nonlinear dynamic systems with n-state components that allow for the generalization of previous, Boolean or "fuzzy", logic models of genetic activities in vivo....

A bioinformatic survey of RNA-binding proteins in Plasmodium.

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Reddy, B P Niranjan; Shrestha, Sony; Hart, Kevin J; Liang, Xiaoying; Kemirembe, Karen; Cui, Liwang; Lindner, Scott E

2015-11-02

The malaria parasites in the genus Plasmodium have a very complicated life cycle involving an invertebrate vector and a vertebrate host. RNA-binding proteins (RBPs) are critical factors involved in every aspect of the development of these parasites. However, very few RBPs have been functionally characterized to date in the human parasite Plasmodium falciparum. Using different bioinformatic methods and tools we searched P. falciparum genome to list and annotate RBPs. A representative 3D models for each of the RBD domain identified in P. falciparum was created using I-TESSAR and SWISS-MODEL. Microarray and RNAseq data analysis pertaining PfRBPs was performed using MeV software. Finally, Cytoscape was used to create protein-protein interaction network for CITH-Dozi and Caf1-CCR4-Not complexes. We report the identification of 189 putative RBP genes belonging to 13 different families in Plasmodium, which comprise 3.5% of all annotated genes. Almost 90% (169/189) of these genes belong to six prominent RBP classes, namely RNA recognition motifs, DEAD/H-box RNA helicases, K homology, Zinc finger, Puf and Alba gene families. Interestingly, almost all of the identified RNA-binding helicases and KH genes have cognate homologs in model species, suggesting their evolutionary conservation. Exploration of the existing P. falciparum blood-stage transcriptomes revealed that most RBPs have peak mRNA expression levels early during the intraerythrocytic development cycle, which taper off in later stages. Nearly 27% of RBPs have elevated expression in gametocytes, while 47 and 24% have elevated mRNA expression in ookinete and asexual stages. Comparative interactome analyses using human and Plasmodium protein-protein interaction datasets suggest extensive conservation of the PfCITH/PfDOZI and PfCaf1-CCR4-NOT complexes. The Plasmodium parasites possess a large number of putative RBPs belonging to most of RBP families identified so far, suggesting the presence of extensive post

Clustered, Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9-coupled Affinity Purification/Mass Spectrometry Analysis Revealed a Novel Role of Neurofibromin in mTOR Signaling.

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Li, Xu; Gao, Min; Choi, Jong Min; Kim, Beom-Jun; Zhou, Mao-Tian; Chen, Zhen; Jain, Antrix N; Jung, Sung Yun; Yuan, Jingsong; Wang, Wenqi; Wang, Yi; Chen, Junjie

2017-04-01

Neurofibromin (NF1) is a well known tumor suppressor that is commonly mutated in cancer patients. It physically interacts with RAS and negatively regulates RAS GTPase activity. Despite the importance of NF1 in cancer, a high quality endogenous NF1 interactome has yet to be established. In this study, we combined c lustered, r egularly i nterspaced s hort p alindromic r epeats (CRISPR)/Cas9-mediated gene knock-out technology with affinity purification using antibodies against endogenous proteins, followed by mass spectrometry analysis, to sensitively and accurately detect NF1 protein-protein interactions in unaltered in vivo settings. Using this system, we analyzed endogenous NF1-associated protein complexes and identified 49 high-confidence candidate interaction proteins, including RAS and other functionally relevant proteins. Through functional validation, we found that NF1 negatively regulates mechanistic target of rapamycin signaling (mTOR) in a LAMTOR1-dependent manner. In addition, the cell growth and survival of NF1-deficient cells have become dependent on hyperactivation of the mTOR pathway, and the tumorigenic properties of these cells have become dependent on LAMTOR1. Taken together, our findings may provide novel insights into therapeutic approaches targeting NF1-deficient tumors. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Designing Focused Chemical Libraries Enriched in Protein-Protein Interaction Inhibitors using Machine-Learning Methods

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Reynès, Christelle; Host, Hélène; Camproux, Anne-Claude; Laconde, Guillaume; Leroux, Florence; Mazars, Anne; Deprez, Benoit; Fahraeus, Robin; Villoutreix, Bruno O.; Sperandio, Olivier

2010-01-01

Protein-protein interactions (PPIs) may represent one of the next major classes of therapeutic targets. So far, only a minute fraction of the estimated 650,000 PPIs that comprise the human interactome are known with a tiny number of complexes being drugged. Such intricate biological systems cannot be cost-efficiently tackled using conventional high-throughput screening methods. Rather, time has come for designing new strategies that will maximize the chance for hit identification through a rationalization of the PPI inhibitor chemical space and the design of PPI-focused compound libraries (global or target-specific). Here, we train machine-learning-based models, mainly decision trees, using a dataset of known PPI inhibitors and of regular drugs in order to determine a global physico-chemical profile for putative PPI inhibitors. This statistical analysis unravels two important molecular descriptors for PPI inhibitors characterizing specific molecular shapes and the presence of a privileged number of aromatic bonds. The best model has been transposed into a computer program, PPI-HitProfiler, that can output from any drug-like compound collection a focused chemical library enriched in putative PPI inhibitors. Our PPI inhibitor profiler is challenged on the experimental screening results of 11 different PPIs among which the p53/MDM2 interaction screened within our own CDithem platform, that in addition to the validation of our concept led to the identification of 4 novel p53/MDM2 inhibitors. Collectively, our tool shows a robust behavior on the 11 experimental datasets by correctly profiling 70% of the experimentally identified hits while removing 52% of the inactive compounds from the initial compound collections. We strongly believe that this new tool can be used as a global PPI inhibitor profiler prior to screening assays to reduce the size of the compound collections to be experimentally screened while keeping most of the true PPI inhibitors. PPI-HitProfiler is

Designing focused chemical libraries enriched in protein-protein interaction inhibitors using machine-learning methods.

Directory of Open Access Journals (Sweden)

Christelle Reynès

2010-03-01

Full Text Available Protein-protein interactions (PPIs may represent one of the next major classes of therapeutic targets. So far, only a minute fraction of the estimated 650,000 PPIs that comprise the human interactome are known with a tiny number of complexes being drugged. Such intricate biological systems cannot be cost-efficiently tackled using conventional high-throughput screening methods. Rather, time has come for designing new strategies that will maximize the chance for hit identification through a rationalization of the PPI inhibitor chemical space and the design of PPI-focused compound libraries (global or target-specific. Here, we train machine-learning-based models, mainly decision trees, using a dataset of known PPI inhibitors and of regular drugs in order to determine a global physico-chemical profile for putative PPI inhibitors. This statistical analysis unravels two important molecular descriptors for PPI inhibitors characterizing specific molecular shapes and the presence of a privileged number of aromatic bonds. The best model has been transposed into a computer program, PPI-HitProfiler, that can output from any drug-like compound collection a focused chemical library enriched in putative PPI inhibitors. Our PPI inhibitor profiler is challenged on the experimental screening results of 11 different PPIs among which the p53/MDM2 interaction screened within our own CDithem platform, that in addition to the validation of our concept led to the identification of 4 novel p53/MDM2 inhibitors. Collectively, our tool shows a robust behavior on the 11 experimental datasets by correctly profiling 70% of the experimentally identified hits while removing 52% of the inactive compounds from the initial compound collections. We strongly believe that this new tool can be used as a global PPI inhibitor profiler prior to screening assays to reduce the size of the compound collections to be experimentally screened while keeping most of the true PPI inhibitors. PPI

Designing focused chemical libraries enriched in protein-protein interaction inhibitors using machine-learning methods.

Science.gov (United States)

Reynès, Christelle; Host, Hélène; Camproux, Anne-Claude; Laconde, Guillaume; Leroux, Florence; Mazars, Anne; Deprez, Benoit; Fahraeus, Robin; Villoutreix, Bruno O; Sperandio, Olivier

2010-03-05

Protein-protein interactions (PPIs) may represent one of the next major classes of therapeutic targets. So far, only a minute fraction of the estimated 650,000 PPIs that comprise the human interactome are known with a tiny number of complexes being drugged. Such intricate biological systems cannot be cost-efficiently tackled using conventional high-throughput screening methods. Rather, time has come for designing new strategies that will maximize the chance for hit identification through a rationalization of the PPI inhibitor chemical space and the design of PPI-focused compound libraries (global or target-specific). Here, we train machine-learning-based models, mainly decision trees, using a dataset of known PPI inhibitors and of regular drugs in order to determine a global physico-chemical profile for putative PPI inhibitors. This statistical analysis unravels two important molecular descriptors for PPI inhibitors characterizing specific molecular shapes and the presence of a privileged number of aromatic bonds. The best model has been transposed into a computer program, PPI-HitProfiler, that can output from any drug-like compound collection a focused chemical library enriched in putative PPI inhibitors. Our PPI inhibitor profiler is challenged on the experimental screening results of 11 different PPIs among which the p53/MDM2 interaction screened within our own CDithem platform, that in addition to the validation of our concept led to the identification of 4 novel p53/MDM2 inhibitors. Collectively, our tool shows a robust behavior on the 11 experimental datasets by correctly profiling 70% of the experimentally identified hits while removing 52% of the inactive compounds from the initial compound collections. We strongly believe that this new tool can be used as a global PPI inhibitor profiler prior to screening assays to reduce the size of the compound collections to be experimentally screened while keeping most of the true PPI inhibitors. PPI-HitProfiler is

Correlation between centromere protein-F autoantibodies and cancer analyzed by enzyme-linked immunosorbent assay

DEFF Research Database (Denmark)

Welner, Simon; Trier, Nicole Hartwig; Morten Frisch, Morten

2013-01-01

Centromere protein-F (CENP-F) is a large nuclear protein of 367 kDa, which is involved in multiple mitosis-related events such as proper assembly of the kinetochores, stabilization of heterochromatin, chromosome alignment and mitotic checkpoint signaling. Several studies have shown a correlation...

Yeast ribosomal proteins

International Nuclear Information System (INIS)

Otaka, E.; Kobata, K.

1978-01-01

The cytoplasmic 80s ribosomal proteins from the cells of yeast Saccharomyces cerevisiae were analyzed by SDS two-dimensional polyacrylamide gel electrophoresis. Seventyfour proteins were identified and consecutively numbered from 1 to 74. Upon oxidation of the 80s proteins with performic acid, ten proteins (no. 15, 20, 35, 40, 44, 46, 49, 51, 54 and 55) were dislocated on the gel without change of the total number of protein spots. Five proteins (no. 8, 14, 16, 36 and 74) were phosphorylated in vivo as seen in 32 P-labelling experiments. The large and small subunits separated in low magnesium medium were analyzed by the above gel electrophoresis. At least forty-five and twenty-eight proteins were assumed to be in the large and small subunits, respectively. All proteins found in the 80s ribosomes, except for no. 3, were detected in either subunit without appearance of new spots. The acidic protein no. 3 seems to be lost during subunit dissociation. (orig.) [de

A draft of the human septin interactome.

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Marcel Nakahira

Full Text Available BACKGROUND: Septins belong to the GTPase superclass of proteins and have been functionally implicated in cytokinesis and the maintenance of cellular morphology. They are found in all eukaryotes, except in plants. In mammals, 14 septins have been described that can be divided into four groups. It has been shown that mammalian septins can engage in homo- and heterooligomeric assemblies, in the form of filaments, which have as a basic unit a hetero-trimeric core. In addition, it has been speculated that the septin filaments may serve as scaffolds for the recruitment of additional proteins. METHODOLOGY/PRINCIPAL FINDINGS: Here, we performed yeast two-hybrid screens with human septins 1-10, which include representatives of all four septin groups. Among the interactors detected, we found predominantly other septins, confirming the tendency of septins to engage in the formation of homo- and heteropolymeric filaments. CONCLUSIONS/SIGNIFICANCE: If we take as reference the reported arrangement of the septins 2, 6 and 7 within the heterofilament, (7-6-2-2-6-7, we note that the majority of the observed interactions respect the "group rule", i.e. members of the same group (e.g. 6, 8, 10 and 11 can replace each other in the specific position along the heterofilament. Septins of the SEPT6 group preferentially interacted with septins of the SEPT2 group (p<0.001, SEPT3 group (p<0.001 and SEPT7 group (p<0.001. SEPT2 type septins preferentially interacted with septins of the SEPT6 group (p<0.001 aside from being the only septin group which interacted with members of its own group. Finally, septins of the SEPT3 group interacted preferentially with septins of the SEPT7 group (p<0.001. Furthermore, we found non-septin interactors which can be functionally attributed to a variety of different cellular activities, including: ubiquitin/sumoylation cycles, microtubular transport and motor activities, cell division and the cell cycle, cell motility, protein

Liver plasma membranes: an effective method to analyze membrane proteome.

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Cao, Rui; Liang, Songping

2012-01-01

Plasma membrane proteins are critical for the maintenance of biological systems and represent important targets for the treatment of disease. The hydrophobicity and low abundance of plasma membrane proteins make them difficult to analyze. The protocols given here are the efficient isolation/digestion procedures for liver plasma membrane proteomic analysis. Both protocol for the isolation of plasma membranes and protocol for the in-gel digestion of gel-embedded plasma membrane proteins are presented. The later method allows the use of a high detergent concentration to achieve efficient solubilization of hydrophobic plasma membrane proteins while avoiding interference with the subsequent LC-MS/MS analysis.

Specificity of molecular interactions in transient protein-protein interaction interfaces.

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Cho, Kyu-il; Lee, KiYoung; Lee, Kwang H; Kim, Dongsup; Lee, Doheon

2006-11-15

In this study, we investigate what types of interactions are specific to their biological function, and what types of interactions are persistent regardless of their functional category in transient protein-protein heterocomplexes. This is the first approach to analyze protein-protein interfaces systematically at the molecular interaction level in the context of protein functions. We perform systematic analysis at the molecular interaction level using classification and feature subset selection technique prevalent in the field of pattern recognition. To represent the physicochemical properties of protein-protein interfaces, we design 18 molecular interaction types using canonical and noncanonical interactions. Then, we construct input vector using the frequency of each interaction type in protein-protein interface. We analyze the 131 interfaces of transient protein-protein heterocomplexes in PDB: 33 protease-inhibitors, 52 antibody-antigens, 46 signaling proteins including 4 cyclin dependent kinase and 26 G-protein. Using kNN classification and feature subset selection technique, we show that there are specific interaction types based on their functional category, and such interaction types are conserved through the common binding mechanism, rather than through the sequence or structure conservation. The extracted interaction types are C(alpha)-- H...O==C interaction, cation...anion interaction, amine...amine interaction, and amine...cation interaction. With these four interaction types, we achieve the classification success rate up to 83.2% with leave-one-out cross-validation at k = 15. Of these four interaction types, C(alpha)--H...O==C shows binding specificity for protease-inhibitor complexes, while cation-anion interaction is predominant in signaling complexes. The amine ... amine and amine...cation interaction give a minor contribution to the classification accuracy. When combined with these two interactions, they increase the accuracy by 3.8%. In the case of

The Pleiotropic MET Receptor Network: Circuit Development and the Neural-Medical Interface of Autism.

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Eagleson, Kathie L; Xie, Zhihui; Levitt, Pat

2017-03-01

People with autism spectrum disorder and other neurodevelopmental disorders (NDDs) are behaviorally and medically heterogeneous. The combination of polygenicity and gene pleiotropy-the influence of one gene on distinct phenotypes-raises questions of how specific genes and their protein products interact to contribute to NDDs. A preponderance of evidence supports developmental and pathophysiological roles for the MET receptor tyrosine kinase, a multifunctional receptor that mediates distinct biological responses depending upon cell context. MET influences neuron architecture and synapse maturation in the forebrain and regulates homeostasis in gastrointestinal and immune systems, both commonly disrupted in NDDs. Peak expression of synapse-enriched MET is conserved across rodent and primate forebrain, yet regional differences in primate neocortex are pronounced, with enrichment in circuits that participate in social information processing. A functional risk allele in the MET promoter, enriched in subgroups of children with autism spectrum disorder, reduces transcription and disrupts socially relevant neural circuits structurally and functionally. In mice, circuit-specific deletion of Met causes distinct atypical behaviors. MET activation increases dendritic complexity and nascent synapse number, but synapse maturation requires reductions in MET. MET mediates its specific biological effects through different intracellular signaling pathways and has a complex protein interactome that is enriched in autism spectrum disorder and other NDD candidates. The interactome is coregulated in developing human neocortex. We suggest that a gene as pleiotropic and highly regulated as MET, together with its interactome, is biologically relevant in normal and pathophysiological contexts, affecting central and peripheral phenotypes that contribute to NDD risk and clinical symptoms. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Bam35 tectivirus intraviral interaction map unveils new function and localization of phage ORFan proteins.

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Berjón-Otero, Mónica; Lechuga, Ana; Mehla, Jitender; Uetz, Peter; Salas, Margarita; Redrejo-Rodríguez, Modesto

2017-07-26

Tectiviridae comprises a group of tail-less, icosahedral, membrane-containing bacteriophages that can be divided into two groups by their hosts, either Gram-negative or Gram-positive bacteria. While the first group is composed of PRD1 and nearly identical well characterized lytic viruses, the second one includes more variable temperate phages, like GIL16 or Bam35, whose hosts are Bacillus cereus and related Gram-positive bacteria.In the genome of Bam35, nearly half of the 32 annotated open reading frames (ORFs) have no homologs in databases (ORFans), being putative proteins of unknown function, which hinders the understanding of their biology. With the aim of increasing the knowledge of the viral proteome, we carried out a comprehensive yeast two-hybrid analysis among all the putative proteins encoded by the Bam35 genome. The resulting protein interactome comprises 76 unique interactions among 24 proteins, of which 12 have an unknown function. These results suggested that the P17 protein is the minor capsid protein of Bam35 and P24 is the penton protein, being the latter also supported by iterative threading protein modeling. Moreover, the inner membrane transglycosylase protein P26 could have an additional structural role. We also detected interactions involving non-structural proteins, such as the DNA binding protein P1 and the genome terminal protein (P4), which was confirmed by co-immunoprecipitation of recombinant proteins. Altogether, our results provide a functional view of the Bam35 viral proteome, with a focus on the composition and organization of the viral particle. IMPORTANCE Tail-less viruses of the family Tectiviridae can infect commensal and pathogenic Gram-positive and Gram-negative bacteria. Moreover, they have been proposed to be at the evolutionary origin of several groups of large eukaryotic DNA viruses and self-replicating plasmids. However, due to their ancient origin and complex diversity, many tectiviral proteins are ORFans of unknown

Cloud prediction of protein structure and function with PredictProtein for Debian.

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Kaján, László; Yachdav, Guy; Vicedo, Esmeralda; Steinegger, Martin; Mirdita, Milot; Angermüller, Christof; Böhm, Ariane; Domke, Simon; Ertl, Julia; Mertes, Christian; Reisinger, Eva; Staniewski, Cedric; Rost, Burkhard

2013-01-01

We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also present two case studies that successfully utilize PredictProtein packages for high performance computing in the cloud: the first analyzes protein disorder for whole organisms, and the second analyzes the effect of all possible single sequence variants in protein coding regions of the human genome.

Designing Dietary Recommendations Using System Level Interactomics Analysis and Network-Based Inference

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Tingting Zheng

2017-09-01

Full Text Available Background: A range of computational methods that rely on the analysis of genome-wide expression datasets have been developed and successfully used for drug repositioning. The success of these methods is based on the hypothesis that introducing a factor (in this case, a drug molecule that could reverse the disease gene expression signature will lead to a therapeutic effect. However, it has also been shown that globally reversing the disease expression signature is not a prerequisite for drug activity. On the other hand, the basic idea of significant anti-correlation in expression profiles could have great value for establishing diet-disease associations and could provide new insights into the role of dietary interventions in disease.Methods: We performed an integrated analysis of publicly available gene expression profiles for foods, diseases and drugs, by calculating pairwise similarity scores for diet and disease gene expression signatures and characterizing their topological features in protein-protein interaction networks.Results: We identified 485 diet-disease pairs where diet could positively influence disease development and 472 pairs where specific diets should be avoided in a disease state. Multiple evidence suggests that orange, whey and coconut fat could be beneficial for psoriasis, lung adenocarcinoma and macular degeneration, respectively. On the other hand, fructose-rich diet should be restricted in patients with chronic intermittent hypoxia and ovarian cancer. Since humans normally do not consume foods in isolation, we also applied different algorithms to predict synergism; as a result, 58 food pairs were predicted. Interestingly, the diets identified as anti-correlated with diseases showed a topological proximity to the disease proteins similar to that of the corresponding drugs.Conclusions: In conclusion, we provide a computational framework for establishing diet-disease associations and additional information on the role of

Architectures and Functional Coverage of Protein-Protein Interfaces

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Tuncbag, Nurcan; Gursoy, Attila; Guney, Emre; Nussinov, Ruth; Keskin, Ozlem

2008-01-01

The diverse range of cellular functions is performed by a limited number of protein folds existing in nature. One may similarly expect that cellular functional diversity would be covered by a limited number of protein-protein interface architectures. Here, we present 8205 interface clusters, each representing unique interface architecture. This dataset of protein-protein interfaces is analyzed and compared with older datasets. We observe that the number of both biological and crystal interfaces increase significantly compared to the number of PDB entries. Further, we find that the number of distinct interface architectures grows at a much faster rate than the number of folds and is yet to level off. We further analyze the growth trend of the functional coverage by constructing functional interaction networks from interfaces. The functional coverage is also found to steadily increase. Interestingly, we also observe that despite the diversity of interface architectures, some are more favorable and frequently used, and of particular interest, those are the ones which are also preferred in single chains. PMID:18620705

Insights into the polerovirus-plant interactome revealed by coimmunoprecipitation and mass spectrometry.

Science.gov (United States)

DeBlasio, Stacy L; Johnson, Richard; Mahoney, Jaclyn; Karasev, Alexander; Gray, Stewart M; MacCoss, Michael J; Cilia, Michelle

2015-04-01

Identification of host proteins interacting with the aphidborne Potato leafroll virus (PLRV) from the genus Polerovirus, family Luteoviridae, is a critical step toward understanding how PLRV and related viruses infect plants. However, the tight spatial distribution of PLRV to phloem tissues poses challenges. A polyclonal antibody raised against purified PLRV virions was used to coimmunoprecipitate virus-host protein complexes from Nicotiana benthamiana tissue inoculated with an infectious PLRV cDNA clone using Agrobacterium tumefaciens. A. tumefaciens-mediated delivery of PLRV enabled infection and production of assembled, insect-transmissible virus in most leaf cells, overcoming the dynamic range constraint posed by a systemically infected host. Isolated protein complexes were characterized using high-resolution mass spectrometry and consisted of host proteins interacting directly or indirectly with virions, as well as the nonincorporated readthrough protein (RTP) and three phosphorylated positional isomers of the RTP. A bioinformatics analysis using ClueGO and STRING showed that plant proteins in the PLRV protein interaction network regulate key biochemical processes, including carbon fixation, amino acid biosynthesis, ion transport, protein folding, and trafficking.

Image Processing for Bioluminescence Resonance Energy Transfer Measurement—BRET-Analyzer

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Yan Chastagnier

2018-01-01

Full Text Available A growing number of tools now allow live recordings of various signaling pathways and protein-protein interaction dynamics in time and space by ratiometric measurements, such as Bioluminescence Resonance Energy Transfer (BRET Imaging. Accurate and reproducible analysis of ratiometric measurements has thus become mandatory to interpret quantitative imaging. In order to fulfill this necessity, we have developed an open source toolset for Fiji—BRET-Analyzer—allowing a systematic analysis, from image processing to ratio quantification. We share this open source solution and a step-by-step tutorial at https://github.com/ychastagnier/BRET-Analyzer. This toolset proposes (1 image background subtraction, (2 image alignment over time, (3 a composite thresholding method of the image used as the denominator of the ratio to refine the precise limits of the sample, (4 pixel by pixel division of the images and efficient distribution of the ratio intensity on a pseudocolor scale, and (5 quantification of the ratio mean intensity and standard variation among pixels in chosen areas. In addition to systematize the analysis process, we show that the BRET-Analyzer allows proper reconstitution and quantification of the ratiometric image in time and space, even from heterogeneous subcellular volumes. Indeed, analyzing twice the same images, we demonstrate that compared to standard analysis BRET-Analyzer precisely define the luminescent specimen limits, enlightening proficient strengths from small and big ensembles over time. For example, we followed and quantified, in live, scaffold proteins interaction dynamics in neuronal sub-cellular compartments including dendritic spines, for half an hour. In conclusion, BRET-Analyzer provides a complete, versatile and efficient toolset for automated reproducible and meaningful image ratio analysis.

Modulation of neuronal proteome profile in response to Japanese encephalitis virus infection.

Science.gov (United States)

Sengupta, Nabonita; Ghosh, Sourish; Vasaikar, Suhas V; Gomes, James; Basu, Anirban

2014-01-01

In this study we have reported the in vivo proteomic changes during Japanese Encephalitis Virus (JEV) infection in combination with in vitro studies which will help in the comprehensive characterization of the modifications in the host metabolism in response to JEV infection. We performed a 2-DE based quantitative proteomic study of JEV-infected mouse brain as well as mouse neuroblastoma (Neuro2a) cells to analyze the host response to this lethal virus. 56 host proteins were found to be differentially expressed post JEV infection (defined as exhibiting ≥ 1.5-fold change in protein abundance upon JEV infection). Bioinformatics analyses were used to generate JEV-regulated host response networks which reported that the identified proteins were found to be associated with various cellular processes ranging from intracellular protein transport, cellular metabolism and ER stress associated unfolded protein response. JEV was found to invade the host protein folding machinery to sustain its survival and replication inside the host thereby generating a vigorous unfolded protein response, subsequently triggering a number of pathways responsible for the JEV associated pathologies. The results were also validated using a human cell line to correlate them to the human response to JEV. The present investigation is the first report on JEV-host interactome in in vivo model and will be of potential interest for future antiviral research in this field.

Crosstalk between apoptosis and autophagy within the Beclin 1 interactome.

Science.gov (United States)

Maiuri, Maria Chiara; Criollo, Alfredo; Kroemer, Guido

2010-02-03

Although the essential genes for autophagy (Atg) have been identified, the molecular mechanisms through which Atg proteins control 'self eating' in mammalian cells remain elusive. Beclin 1 (Bec1), the mammalian orthologue of yeast Atg6, is part of the class III phosphatidylinositol 3-kinase (PI3K) complex that induces autophagy. The first among an increasing number of Bec1-interacting proteins that has been identified is the anti-apoptotic protein Bcl-2. The dissociation of Bec1 from Bcl-2 is essential for its autophagic activity, and Bcl-2 only inhibits autophagy when it is present in the endoplasmic reticulum (ER). A paper in this issue of the EMBO Journal has identified a novel protein, NAF-1 (nutrient-deprivation autophagy factor-1), that binds Bcl-2 at the ER. NAF-1 is a component of the inositol-1,4,5 trisphosphate (IP3) receptor complex, which contributes to the interaction of Bcl-2 with Bec1 and is required for Bcl-2 to functionally antagonize Bec1-mediated autophagy. This work provides mechanistic insights into how autophagy- and apoptosis-regulatory molecules crosstalk at the ER.

Comparative metabolite fingerprinting of the rumen system during colonisation of three forage grass (Lolium perenne L. varieties.

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Alison H Kingston-Smith

Full Text Available The rumen microbiota enable ruminants to degrade complex ligno-cellulosic compounds to produce high quality protein for human consumption. However, enteric fermentation by domestic ruminants generates negative by-products: greenhouse gases (methane and environmental nitrogen pollution. The current lack of cultured isolates representative of the totality of rumen microbial species creates an information gap about the in vivo function of the rumen microbiota and limits our ability to apply predictive biology for improvement of feed for ruminants. In this work we took a whole ecosystem approach to understanding how the metabolism of the microbial population responds to introduction of its substrate. Fourier Transform Infra Red (FTIR spectroscopy-based metabolite fingerprinting was used to discriminate differences in the plant-microbial interactome of the rumen when using three forage grass varieties (Lolium perenne L. cv AberDart, AberMagic and Premium as substrates for microbial colonisation and fermentation. Specific examination of spectral regions associated with fatty acids, amides, sugars and alkanes indicated that although the three forages were apparently similar by traditional nutritional analysis, patterns of metabolite flux within the plant-microbial interactome were distinct and plant genotype dependent. Thus, the utilisation pattern of forage nutrients by the rumen microbiota can be influenced by subtleties determined by forage genotypes. These data suggest that our interactomic approach represents an important means to improve forages and ultimately the livestock environment.

Protein-Protein Interaction Databases

DEFF Research Database (Denmark)

Szklarczyk, Damian; Jensen, Lars Juhl

2015-01-01

Years of meticulous curation of scientific literature and increasingly reliable computational predictions have resulted in creation of vast databases of protein interaction data. Over the years, these repositories have become a basic framework in which experiments are analyzed and new directions...

The interactomes of influenza virus NS1 and NS2 proteins identify new host factors and provide insights for ADAR1 playing a supportive role in virus replication.

Science.gov (United States)

de Chassey, Benoît; Aublin-Gex, Anne; Ruggieri, Alessia; Meyniel-Schicklin, Laurène; Pradezynski, Fabrine; Davoust, Nathalie; Chantier, Thibault; Tafforeau, Lionel; Mangeot, Philippe-Emmanuel; Ciancia, Claire; Perrin-Cocon, Laure; Bartenschlager, Ralf; André, Patrice; Lotteau, Vincent

2013-01-01

Influenza A NS1 and NS2 proteins are encoded by the RNA segment 8 of the viral genome. NS1 is a multifunctional protein and a virulence factor while NS2 is involved in nuclear export of viral ribonucleoprotein complexes. A yeast two-hybrid screening strategy was used to identify host factors supporting NS1 and NS2 functions. More than 560 interactions between 79 cellular proteins and NS1 and NS2 proteins from 9 different influenza virus strains have been identified. These interacting proteins are potentially involved in each step of the infectious process and their contribution to viral replication was tested by RNA interference. Validation of the relevance of these host cell proteins for the viral replication cycle revealed that 7 of the 79 NS1 and/or NS2-interacting proteins positively or negatively controlled virus replication. One of the main factors targeted by NS1 of all virus strains was double-stranded RNA binding domain protein family. In particular, adenosine deaminase acting on RNA 1 (ADAR1) appeared as a pro-viral host factor whose expression is necessary for optimal viral protein synthesis and replication. Surprisingly, ADAR1 also appeared as a pro-viral host factor for dengue virus replication and directly interacted with the viral NS3 protein. ADAR1 editing activity was enhanced by both viruses through dengue virus NS3 and influenza virus NS1 proteins, suggesting a similar virus-host co-evolution.

The interactomes of influenza virus NS1 and NS2 proteins identify new host factors and provide insights for ADAR1 playing a supportive role in virus replication.

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Benoît de Chassey

Full Text Available Influenza A NS1 and NS2 proteins are encoded by the RNA segment 8 of the viral genome. NS1 is a multifunctional protein and a virulence factor while NS2 is involved in nuclear export of viral ribonucleoprotein complexes. A yeast two-hybrid screening strategy was used to identify host factors supporting NS1 and NS2 functions. More than 560 interactions between 79 cellular proteins and NS1 and NS2 proteins from 9 different influenza virus strains have been identified. These interacting proteins are potentially involved in each step of the infectious process and their contribution to viral replication was tested by RNA interference. Validation of the relevance of these host cell proteins for the viral replication cycle revealed that 7 of the 79 NS1 and/or NS2-interacting proteins positively or negatively controlled virus replication. One of the main factors targeted by NS1 of all virus strains was double-stranded RNA binding domain protein family. In particular, adenosine deaminase acting on RNA 1 (ADAR1 appeared as a pro-viral host factor whose expression is necessary for optimal viral protein synthesis and replication. Surprisingly, ADAR1 also appeared as a pro-viral host factor for dengue virus replication and directly interacted with the viral NS3 protein. ADAR1 editing activity was enhanced by both viruses through dengue virus NS3 and influenza virus NS1 proteins, suggesting a similar virus-host co-evolution.

Analysis of the Protein Kinase A-Regulated Proteome of Cryptococcus neoformans Identifies a Role for the Ubiquitin-Proteasome Pathway in Capsule Formation

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J. M. H. Geddes

2016-01-01

Full Text Available The opportunistic fungal pathogen Cryptococcus neoformans causes life-threatening meningitis in immunocompromised individuals. The expression of virulence factors, including capsule and melanin, is in part regulated by the cyclic-AMP/protein kinase A (cAMP/PKA signal transduction pathway. In this study, we investigated the influence of PKA on the composition of the intracellular proteome to obtain a comprehensive understanding of the regulation that underpins virulence. Through quantitative proteomics, enrichment and bioinformatic analyses, and an interactome study, we uncovered a pattern of PKA regulation for proteins associated with translation, the proteasome, metabolism, amino acid biosynthesis, and virulence-related functions. PKA regulation of the ubiquitin-proteasome pathway in C. neoformans showed a striking parallel with connections between PKA and protein degradation in chronic neurodegenerative disorders and other human diseases. Further investigation of proteasome function with the inhibitor bortezomib revealed an impact on capsule production as well as hypersusceptibility for strains with altered expression or activity of PKA. Parallel studies with tunicamycin also linked endoplasmic reticulum stress with capsule production and PKA. Taken together, the data suggest a model whereby expression of PKA regulatory and catalytic subunits and the activation of PKA influence proteostasis and the function of the endoplasmic reticulum to control the elaboration of the polysaccharide capsule. Overall, this study revealed both broad and conserved influences of the cAMP/PKA pathway on the proteome and identified proteostasis as a potential therapeutic target for the treatment of cryptococcosis.

Protein-protein interaction network-based detection of functionally similar proteins within species.

Science.gov (United States)

Song, Baoxing; Wang, Fen; Guo, Yang; Sang, Qing; Liu, Min; Li, Dengyun; Fang, Wei; Zhang, Deli

2012-07-01

Although functionally similar proteins across species have been widely studied, functionally similar proteins within species showing low sequence similarity have not been examined in detail. Identification of these proteins is of significant importance for understanding biological functions, evolution of protein families, progression of co-evolution, and convergent evolution and others which cannot be obtained by detection of functionally similar proteins across species. Here, we explored a method of detecting functionally similar proteins within species based on graph theory. After denoting protein-protein interaction networks using graphs, we split the graphs into subgraphs using the 1-hop method. Proteins with functional similarities in a species were detected using a method of modified shortest path to compare these subgraphs and to find the eligible optimal results. Using seven protein-protein interaction networks and this method, some functionally similar proteins with low sequence similarity that cannot detected by sequence alignment were identified. By analyzing the results, we found that, sometimes, it is difficult to separate homologous from convergent evolution. Evaluation of the performance of our method by gene ontology term overlap showed that the precision of our method was excellent. Copyright © 2012 Wiley Periodicals, Inc.

Characterization of the Arabidopsis thaliana 2-Cys peroxiredoxin interactome.

Science.gov (United States)

Cerveau, Delphine; Kraut, Alexandra; Stotz, Henrik U; Mueller, Martin J; Couté, Yohann; Rey, Pascal

2016-11-01

Peroxiredoxins are ubiquitous thiol-dependent peroxidases for which chaperone and signaling roles have been reported in various types of organisms in recent years. In plants, the peroxidase function of the two typical plastidial 2-Cys peroxiredoxins (2-Cys PRX A and B) has been highlighted while the other functions, particularly in ROS-dependent signaling pathways, are still elusive notably due to the lack of knowledge of interacting partners. Using an ex vivo approach based on co-immunoprecipitation of leaf extracts from Arabidopsis thaliana wild-type and mutant plants lacking 2-Cys PRX expression followed by mass spectrometry-based proteomics, 158 proteins were found associated with 2-Cys PRXs. Already known partners like thioredoxin-related electron donors (Chloroplastic Drought-induced Stress Protein of 32kDa, Atypical Cysteine Histidine-rich Thioredoxin 2) and enzymes involved in chlorophyll synthesis (Protochlorophyllide OxidoReductase B) or carbon metabolism (Fructose-1,6-BisPhosphatase) were identified, validating the relevance of the approach. Bioinformatic and bibliographic analyses allowed the functional classification of the identified proteins and revealed that more than 40% are localized in plastids. The possible roles of plant 2-Cys PRXs in redox signaling pathways are discussed in relation with the functions of the potential partners notably those involved in redox homeostasis, carbon and amino acid metabolisms as well as chlorophyll biosynthesis. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Analyzing modifiers of protein aggregation in C. elegans by native agarose gel electrophoresis

NARCIS (Netherlands)

Holmberg, Mats; Nollen, Ellen A A; Hatters, Danny M.; Hannan, Anthony J.

2013-01-01

The accumulation of specific aggregation-prone proteins during aging is thought to be involved in several diseases, most notably Alzheimer's and Parkinson's disease as well as polyglutamine expansion disorders such as Huntington's disease. Caenorhabditis elegans disease models with transgenic

Globular and disordered-the non-identical twins in protein-protein interactions

DEFF Research Database (Denmark)

Teilum, Kaare; Olsen, Johan Gotthardt; Kragelund, Birthe Brandt

2015-01-01

as a strong determinant for their function. This has fostered the notion that IDP's bind with low affinity but high specificity. Here we have analyzed available detailed thermodynamic data for protein-protein interactions to put to the test if the thermodynamic profiles of IDP interactions differ from those...... of other protein-protein interactions. We find that ordered proteins and the disordered ones act as non-identical twins operating by similar principles but where the disordered proteins complexes are on average less stable by 2.5 kcal mol(-1)....

Analysis of the protein-protein interactions between the human acidic ribosomal P-proteins: evaluation by the two hybrid system

DEFF Research Database (Denmark)

Tchórzewski, M; Boldyreff, B; Issinger, O

2000-01-01

The surface acidic ribosomal proteins (P-proteins), together with ribosomal core protein P0 form a multimeric lateral protuberance on the 60 S ribosomal subunit. This structure, also called stalk, is important for efficient translational activity of the ribosome. In order to shed more light...... forms the 60 S ribosomal stalk: P0-(P1/P2)(2). Additionally, mutual interactions among human and yeast P-proteins were analyzed. Heterodimer formation could be observed between human P2 and yeast P1 proteins....

Protein complexes in the archaeon Methanothermobacter thermautotrophicus analyzed by blue native/SDS-PAGE and mass spectrometry.

NARCIS (Netherlands)

Farhoud, M.H.; Wessels, H.C.T.; Steenbakkers, P.J.M.; Mattijssen, S.; Wevers, R.A.; Engelen, B.G.M. van; Jetten, M.S.M.; Smeitink, J.A.M.; Heuvel, L.P.W.J. van den; Keltjens, J.T.M.

2005-01-01

Methanothermobacter thermautotrophicus is a thermophilic archaeon that produces methane as the end product of its primary metabolism. The biochemistry of methane formation has been extensively studied and is catalyzed by individual enzymes and proteins that are organized in protein complexes.

Viral Genome DataBase: storing and analyzing genes and proteins from complete viral genomes.

Science.gov (United States)

Hiscock, D; Upton, C

2000-05-01

The Viral Genome DataBase (VGDB) contains detailed information of the genes and predicted protein sequences from 15 completely sequenced genomes of large (&100 kb) viruses (2847 genes). The data that is stored includes DNA sequence, protein sequence, GenBank and user-entered notes, molecular weight (MW), isoelectric point (pI), amino acid content, A + T%, nucleotide frequency, dinucleotide frequency and codon use. The VGDB is a mySQL database with a user-friendly JAVA GUI. Results of queries can be easily sorted by any of the individual parameters. The software and additional figures and information are available at http://athena.bioc.uvic.ca/genomes/index.html .

Functional structural motifs for protein-ligand, protein-protein, and protein-nucleic acid interactions and their connection to supersecondary structures.

Science.gov (United States)

Kinjo, Akira R; Nakamura, Haruki

2013-01-01

Protein functions are mediated by interactions between proteins and other molecules. One useful approach to analyze protein functions is to compare and classify the structures of interaction interfaces of proteins. Here, we describe the procedures for compiling a database of interface structures and efficiently comparing the interface structures. To do so requires a good understanding of the data structures of the Protein Data Bank (PDB). Therefore, we also provide a detailed account of the PDB exchange dictionary necessary for extracting data that are relevant for analyzing interaction interfaces and secondary structures. We identify recurring structural motifs by classifying similar interface structures, and we define a coarse-grained representation of supersecondary structures (SSS) which represents a sequence of two or three secondary structure elements including their relative orientations as a string of four to seven letters. By examining the correspondence between structural motifs and SSS strings, we show that no SSS string has particularly high propensity to be found interaction interfaces in general, indicating any SSS can be used as a binding interface. When individual structural motifs are examined, there are some SSS strings that have high propensity for particular groups of structural motifs. In addition, it is shown that while the SSS strings found in particular structural motifs for nonpolymer and protein interfaces are as abundant as in other structural motifs that belong to the same subunit, structural motifs for nucleic acid interfaces exhibit somewhat stronger preference for SSS strings. In regard to protein folds, many motif-specific SSS strings were found across many folds, suggesting that SSS may be a useful description to investigate the universality of ligand binding modes.

Triangle network motifs predict complexes by complementing high-error interactomes with structural information.

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Andreopoulos, Bill; Winter, Christof; Labudde, Dirk; Schroeder, Michael

2009-06-27

A lot of high-throughput studies produce protein-protein interaction networks (PPINs) with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs) were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs) representing binding evidence on proteins, forming PPI-SDDI-PPI triangles. We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS). PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes. Given high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that relatively little structural information would be sufficient

The Ciliopathy Protein CC2D2A Associates with NINL and Functions in RAB8-MICAL3-Regulated Vesicle Trafficking.

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Ruxandra Bachmann-Gagescu

2015-10-01

Full Text Available Ciliopathies are a group of human disorders caused by dysfunction of primary cilia, ubiquitous microtubule-based organelles involved in transduction of extra-cellular signals to the cell. This function requires the concentration of receptors and channels in the ciliary membrane, which is achieved by complex trafficking mechanisms, in part controlled by the small GTPase RAB8, and by sorting at the transition zone located at the entrance of the ciliary compartment. Mutations in the transition zone gene CC2D2A cause the related Joubert and Meckel syndromes, two typical ciliopathies characterized by central nervous system malformations, and result in loss of ciliary localization of multiple proteins in various models. The precise mechanisms by which CC2D2A and other transition zone proteins control protein entrance into the cilium and how they are linked to vesicular trafficking of incoming cargo remain largely unknown. In this work, we identify the centrosomal protein NINL as a physical interaction partner of CC2D2A. NINL partially co-localizes with CC2D2A at the base of cilia and ninl knockdown in zebrafish leads to photoreceptor outer segment loss, mislocalization of opsins and vesicle accumulation, similar to cc2d2a-/- phenotypes. Moreover, partial ninl knockdown in cc2d2a-/- embryos enhances the retinal phenotype of the mutants, indicating a genetic interaction in vivo, for which an illustration is found in patients from a Joubert Syndrome cohort. Similar to zebrafish cc2d2a mutants, ninl morphants display altered Rab8a localization. Further exploration of the NINL-associated interactome identifies MICAL3, a protein known to interact with Rab8 and to play an important role in vesicle docking and fusion. Together, these data support a model where CC2D2A associates with NINL to provide a docking point for cilia-directed cargo vesicles, suggesting a mechanism by which transition zone proteins can control the protein content of the ciliary

Application of computational systems biology to explore environmental toxicity hazards

DEFF Research Database (Denmark)

Audouze, Karine Marie Laure; Grandjean, Philippe

2011-01-01

Background: Computer-based modeling is part of a new approach to predictive toxicology.Objectives: We investigated the usefulness of an integrated computational systems biology approach in a case study involving the isomers and metabolites of the pesticide dichlorodiphenyltrichloroethane (DDT......) to ascertain their possible links to relevant adverse effects.Methods: We extracted chemical-protein association networks for each DDT isomer and its metabolites using ChemProt, a disease chemical biology database that includes both binding and gene expression data, and we explored protein-protein interactions...... using a human interactome network. To identify associated dysfunctions and diseases, we integrated protein-disease annotations into the protein complexes using the Online Mendelian Inheritance in Man database and the Comparative Toxicogenomics Database.Results: We found 175 human proteins linked to p,p´-DDT...

Triangle network motifs predict complexes by complementing high-error interactomes with structural information

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Labudde Dirk

2009-06-01

Full Text Available Abstract Background A lot of high-throughput studies produce protein-protein interaction networks (PPINs with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs representing binding evidence on proteins, forming PPI-SDDI-PPI triangles. Results We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS. PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes. Conclusion Given high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that

Protein-protein interactions within late pre-40S ribosomes.

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Melody G Campbell

2011-01-01

Full Text Available Ribosome assembly in eukaryotic organisms requires more than 200 assembly factors to facilitate and coordinate rRNA transcription, processing, and folding with the binding of the ribosomal proteins. Many of these assembly factors bind and dissociate at defined times giving rise to discrete assembly intermediates, some of which have been partially characterized with regards to their protein and RNA composition. Here, we have analyzed the protein-protein interactions between the seven assembly factors bound to late cytoplasmic pre-40S ribosomes using recombinant proteins in binding assays. Our data show that these factors form two modules: one comprising Enp1 and the export adaptor Ltv1 near the beak structure, and the second comprising the kinase Rio2, the nuclease Nob1, and a regulatory RNA binding protein Dim2/Pno1 on the front of the head. The GTPase-like Tsr1 and the universally conserved methylase Dim1 are also peripherally connected to this second module. Additionally, in an effort to further define the locations for these essential proteins, we have analyzed the interactions between these assembly factors and six ribosomal proteins: Rps0, Rps3, Rps5, Rps14, Rps15 and Rps29. Together, these results and previous RNA-protein crosslinking data allow us to propose a model for the binding sites of these seven assembly factors. Furthermore, our data show that the essential kinase Rio2 is located at the center of the pre-ribosomal particle and interacts, directly or indirectly, with every other assembly factor, as well as three ribosomal proteins required for cytoplasmic 40S maturation. These data suggest that Rio2 could play a central role in regulating cytoplasmic maturation steps.

Insights into the polerovirus-plant interactome revealed by co-immunoprecipitation and mass spectrometry

Science.gov (United States)

The identification of host proteins that interact with virus proteins is a major challenge for the field of virology. Phloem-limited viruses pose extraordinary challenges for in vivo protein interaction experiments because these viruses are localized in very few and highly specialized host cells. ...

ING1 induces apoptosis through direct effects at the mitochondria

DEFF Research Database (Denmark)

Bose, P; Thakur, S; Thalappilly, S

2013-01-01

The ING family of tumor suppressors acts as readers and writers of the histone epigenetic code, affecting DNA repair, chromatin remodeling, cellular senescence, cell cycle regulation and apoptosis. The best characterized member of the ING family, ING1,interacts with the proliferating cell nuclear....... Bioinformatic analysis of the yeast interactome indicates that yeast ING proteins interact with 64 mitochondrial proteins. Also, sequence analysis of ING1 reveals the presence of a BH3-like domain. These data suggest a model in which stress-induced cytoplasmic relocalization of ING1 by14-3-3 induces ING1-BAX...

Poplar Interactome: Project Final Report

Energy Technology Data Exchange (ETDEWEB)

Jaiswal, Pankaj [Oregon State Univ., Corvallis, OR (United States)

2018-03-21

The feedstock plant Poplar has many advantages over traditional crop plants. Not only Poplar needs low energy input and off season storage as compared to feedstocks such as corn, in the winter season Poplar biomass is stored on the stem/trunk, and Poplar plantations serve as large carbon sink. A key constraint to the expansion of cellulosic bioenergy sources such as in Poplar however, is the negative consequence of converting land use from food crops to energy crops. Therefore in order for Poplar to become a viable energy crop it needs to be grown mostly on marginal land unsuitable agricultural crops. For this we need a better understanding of abiotic stress and adaptation response in poplar. In the process we expected to find new and existing poplar genes and their function that respond to sustain abiotic stress. We carried out an extensive gene expression study on the control untreated and stress (drought, salinity, cold and heat) treated poplar plants. The samples were collected from the stem, leaf and root tissues. The RNA of protein coding genes and regulatory smallRNA genes were sequenced generating more than a billion reads. This is the first such known study in Poplar plants. These were used for quantification and genomic analysis to identify stress responsive genes in poplar. Based on the quantification and genomic analysis, a select set of genes were studied for gene-gene interactions to find their association to stress response. The data was also used to find novel stress responsive genes in poplar that were previously not identified in the Poplar reference genome. The data is made available to the public through the national and international genomic data archives.

Evidence for systems-level molecular mechanisms of tumorigenesis

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Capellá Gabriel

2007-06-01

Full Text Available Abstract Background Cancer arises from the consecutive acquisition of genetic alterations. Increasing evidence suggests that as a consequence of these alterations, molecular interactions are reprogrammed in the context of highly connected and regulated cellular networks. Coordinated reprogramming would allow the cell to acquire the capabilities for malignant growth. Results Here, we determine the coordinated function of cancer gene products (i.e., proteins encoded by differentially expressed genes in tumors relative to healthy tissue counterparts, hereafter referred to as "CGPs" defined as their topological properties and organization in the interactome network. We show that CGPs are central to information exchange and propagation and that they are specifically organized to promote tumorigenesis. Centrality is identified by both local (degree and global (betweenness and closeness measures, and systematically appears in down-regulated CGPs. Up-regulated CGPs do not consistently exhibit centrality, but both types of cancer products determine the overall integrity of the network structure. In addition to centrality, down-regulated CGPs show topological association that correlates with common biological processes and pathways involved in tumorigenesis. Conclusion Given the current limited coverage of the human interactome, this study proposes that tumorigenesis takes place in a specific and organized way at the molecular systems-level and suggests a model that comprises the precise down-regulation of groups of topologically-associated proteins involved in particular functions, orchestrated with the up-regulation of specific proteins.

Generation and Comprehensive Analysis of an Influenza Virus Polymerase Cellular Interaction Network▿†§

Science.gov (United States)

Tafforeau, Lionel; Chantier, Thibault; Pradezynski, Fabrine; Pellet, Johann; Mangeot, Philippe E.; Vidalain, Pierre-Olivier; Andre, Patrice; Rabourdin-Combe, Chantal; Lotteau, Vincent

2011-01-01

The influenza virus transcribes and replicates its genome inside the nucleus of infected cells. Both activities are performed by the viral RNA-dependent RNA polymerase that is composed of the three subunits PA, PB1, and PB2, and recent studies have shown that it requires host cell factors to transcribe and replicate the viral genome. To identify these cellular partners, we generated a comprehensive physical interaction map between each polymerase subunit and the host cellular proteome. A total of 109 human interactors were identified by yeast two-hybrid screens, whereas 90 were retrieved by literature mining. We built the FluPol interactome network composed of the influenza virus polymerase (PA, PB1, and PB2) and the nucleoprotein NP and 234 human proteins that are connected through 279 viral-cellular protein interactions. Analysis of this interactome map revealed enriched cellular functions associated with the influenza virus polymerase, including host factors involved in RNA polymerase II-dependent transcription and mRNA processing. We confirmed that eight influenza virus polymerase-interacting proteins are required for virus replication and transcriptional activity of the viral polymerase. These are involved in cellular transcription (C14orf166, COPS5, MNAT1, NMI, and POLR2A), translation (EIF3S6IP), nuclear transport (NUP54), and DNA repair (FANCG). Conversely, we identified PRKRA, which acts as an inhibitor of the viral polymerase transcriptional activity and thus is required for the cellular antiviral response. PMID:21994455

Generation and comprehensive analysis of an influenza virus polymerase cellular interaction network.

Science.gov (United States)

Tafforeau, Lionel; Chantier, Thibault; Pradezynski, Fabrine; Pellet, Johann; Mangeot, Philippe E; Vidalain, Pierre-Olivier; Andre, Patrice; Rabourdin-Combe, Chantal; Lotteau, Vincent

2011-12-01

The influenza virus transcribes and replicates its genome inside the nucleus of infected cells. Both activities are performed by the viral RNA-dependent RNA polymerase that is composed of the three subunits PA, PB1, and PB2, and recent studies have shown that it requires host cell factors to transcribe and replicate the viral genome. To identify these cellular partners, we generated a comprehensive physical interaction map between each polymerase subunit and the host cellular proteome. A total of 109 human interactors were identified by yeast two-hybrid screens, whereas 90 were retrieved by literature mining. We built the FluPol interactome network composed of the influenza virus polymerase (PA, PB1, and PB2) and the nucleoprotein NP and 234 human proteins that are connected through 279 viral-cellular protein interactions. Analysis of this interactome map revealed enriched cellular functions associated with the influenza virus polymerase, including host factors involved in RNA polymerase II-dependent transcription and mRNA processing. We confirmed that eight influenza virus polymerase-interacting proteins are required for virus replication and transcriptional activity of the viral polymerase. These are involved in cellular transcription (C14orf166, COPS5, MNAT1, NMI, and POLR2A), translation (EIF3S6IP), nuclear transport (NUP54), and DNA repair (FANCG). Conversely, we identified PRKRA, which acts as an inhibitor of the viral polymerase transcriptional activity and thus is required for the cellular antiviral response.

MADS interactomics : towards understanding the molecular mechanisms of plant MADS-domain transcription factor function

NARCIS (Netherlands)

Smaczniak, C.D.

2013-01-01

Protein-protein and protein-DNA interactions are essential for the molecular action of transcription factors. By combinatorial binding to target gene promoters, transcription factors are able to up- or down-regulate the expression of these genes. MADS-domain proteins comprise a large family of

New Targets for Zika Virus Determined by Human-Viral Interactomic: A Bioinformatics Approach

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Eduardo Esteves

2017-01-01

Full Text Available Identifying ZIKV factors interfering with human host pathways represents a major challenge in understanding ZIKV tropism and pathogenesis. The integration of proteomic, gene expression and Protein-Protein Interactions (PPIs established between ZIKV and human host proteins predicted by the OralInt algorithm identified 1898 interactions with medium or high score (≥0.7. Targets implicated in vesicular traffic and docking were identified. New receptors involved in endocytosis pathways as ZIKV entry targets, using both clathrin-dependent (17 receptors and independent (10 receptors pathways, are described. New targets used by the ZIKV to undermine the host’s antiviral immune response are proposed based on predicted interactions established between the virus and host cell receptors and/or proteins with an effector or signaling role in the immune response such as IFN receptors and TLR. Complement and cytokines are proposed as extracellular potential interacting partners of the secreted form of NS1 ZIKV protein. Altogether, in this article, 18 new human targets for structural and nonstructural ZIKV proteins are proposed. These results are of great relevance for the understanding of viral pathogenesis and consequently the development of preventive (vaccines and therapeutic targets for ZIKV infection management.

Combining blue native polyacrylamide gel electrophoresis with liquid chromatography tandem mass spectrometry as an effective strategy for analyzing potential membrane protein complexes of Mycobacterium bovis bacillus Calmette-Guérin

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Li Weijun

2011-01-01

Full Text Available Abstract Background Tuberculosis is an infectious bacterial disease in humans caused primarily by Mycobacterium tuberculosis, and infects one-third of the world's total population. Mycobacterium bovis bacillus Calmette-Guérin (BCG vaccine has been widely used to prevent tuberculosis worldwide since 1921. Membrane proteins play important roles in various cellular processes, and the protein-protein interactions involved in these processes may provide further information about molecular organization and cellular pathways. However, membrane proteins are notoriously under-represented by traditional two-dimensional polyacrylamide gel electrophoresis (2-D PAGE and little is known about mycobacterial membrane and membrane-associated protein complexes. Here we investigated M. bovis BCG by an alternative proteomic strategy coupling blue native PAGE to liquid chromatography tandem mass spectrometry (LC-MS/MS to characterize potential protein-protein interactions in membrane fractions. Results Using this approach, we analyzed native molecular composition of protein complexes in BCG membrane fractions. As a result, 40 proteins (including 12 integral membrane proteins, which were organized in 9 different gel bands, were unambiguous identified. The proteins identified have been experimentally confirmed using 2-D SDS PAGE. We identified MmpL8 and four neighboring proteins that were involved in lipid transport complexes, and all subunits of ATP synthase complex in their monomeric states. Two phenolpthiocerol synthases and three arabinosyltransferases belonging to individual operons were obtained in different gel bands. Furthermore, two giant multifunctional enzymes, Pks7 and Pks8, and four mycobacterial Hsp family members were determined. Additionally, seven ribosomal proteins involved in polyribosome complex and two subunits of the succinate dehydrogenase complex were also found. Notablely, some proteins with high hydrophobicity or multiple transmembrane

Combining blue native polyacrylamide gel electrophoresis with liquid chromatography tandem mass spectrometry as an effective strategy for analyzing potential membrane protein complexes of Mycobacterium bovis bacillus Calmette-Guérin.

Science.gov (United States)

Zheng, Jianhua; Wei, Candong; Zhao, Lina; Liu, Liguo; Leng, Wenchuan; Li, Weijun; Jin, Qi

2011-01-18

Tuberculosis is an infectious bacterial disease in humans caused primarily by Mycobacterium tuberculosis, and infects one-third of the world's total population. Mycobacterium bovis bacillus Calmette-Guérin (BCG) vaccine has been widely used to prevent tuberculosis worldwide since 1921. Membrane proteins play important roles in various cellular processes, and the protein-protein interactions involved in these processes may provide further information about molecular organization and cellular pathways. However, membrane proteins are notoriously under-represented by traditional two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) and little is known about mycobacterial membrane and membrane-associated protein complexes. Here we investigated M. bovis BCG by an alternative proteomic strategy coupling blue native PAGE to liquid chromatography tandem mass spectrometry (LC-MS/MS) to characterize potential protein-protein interactions in membrane fractions. Using this approach, we analyzed native molecular composition of protein complexes in BCG membrane fractions. As a result, 40 proteins (including 12 integral membrane proteins), which were organized in 9 different gel bands, were unambiguous identified. The proteins identified have been experimentally confirmed using 2-D SDS PAGE. We identified MmpL8 and four neighboring proteins that were involved in lipid transport complexes, and all subunits of ATP synthase complex in their monomeric states. Two phenolpthiocerol synthases and three arabinosyltransferases belonging to individual operons were obtained in different gel bands. Furthermore, two giant multifunctional enzymes, Pks7 and Pks8, and four mycobacterial Hsp family members were determined. Additionally, seven ribosomal proteins involved in polyribosome complex and two subunits of the succinate dehydrogenase complex were also found. Notablely, some proteins with high hydrophobicity or multiple transmembrane helixes were identified well in our work. In this

MDcons: Intermolecular contact maps as a tool to analyze the interface of protein complexes from molecular dynamics trajectories

KAUST Repository

Abdel-Azeim, Safwat

2014-05-06

Background: Molecular Dynamics ( MD) simulations of protein complexes suffer from the lack of specific tools in the analysis step. Analyses of MD trajectories of protein complexes indeed generally rely on classical measures, such as the RMSD, RMSF and gyration radius, conceived and developed for single macromolecules. As a matter of fact, instead, researchers engaged in simulating the dynamics of a protein complex are mainly interested in characterizing the conservation/variation of its biological interface. Results: On these bases, herein we propose a novel approach to the analysis of MD trajectories or other conformational ensembles of protein complexes, MDcons, which uses the conservation of inter-residue contacts at the interface as a measure of the similarity between different snapshots. A "consensus contact map" is also provided, where the conservation of the different contacts is drawn in a grey scale. Finally, the interface area of the complex is monitored during the simulations. To show its utility, we used this novel approach to study two protein-protein complexes with interfaces of comparable size and both dominated by hydrophilic interactions, but having binding affinities at the extremes of the experimental range. MDcons is demonstrated to be extremely useful to analyse the MD trajectories of the investigated complexes, adding important insight into the dynamic behavior of their biological interface. Conclusions: MDcons specifically allows the user to highlight and characterize the dynamics of the interface in protein complexes and can thus be used as a complementary tool for the analysis of MD simulations of both experimental and predicted structures of protein complexes.

Analysis of protein-protein docking decoys using interaction fingerprints: application to the reconstruction of CaM-ligand complexes

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Uchikoga Nobuyuki

2010-05-01

Full Text Available Abstract Background Protein-protein docking for proteins with large conformational changes was analyzed by using interaction fingerprints, one of the scales for measuring similarities among complex structures, utilized especially for searching near-native protein-ligand or protein-protein complex structures. Here, we have proposed a combined method for analyzing protein-protein docking by taking large conformational changes into consideration. This combined method consists of ensemble soft docking with multiple protein structures, refinement of complexes, and cluster analysis using interaction fingerprints and energy profiles. Results To test for the applicability of this combined method, various CaM-ligand complexes were reconstructed from the NMR structures of unbound CaM. For the purpose of reconstruction, we used three known CaM-ligands, namely, the CaM-binding peptides of cyclic nucleotide gateway (CNG, CaM kinase kinase (CaMKK and the plasma membrane Ca2+ ATPase pump (PMCA, and thirty-one structurally diverse CaM conformations. For each ligand, 62000 CaM-ligand complexes were generated in the docking step and the relationship between their energy profiles and structural similarities to the native complex were analyzed using interaction fingerprint and RMSD. Near-native clusters were obtained in the case of CNG and CaMKK. Conclusions The interaction fingerprint method discriminated near-native structures better than the RMSD method in cluster analysis. We showed that a combined method that includes the interaction fingerprint is very useful for protein-protein docking analysis of certain cases.

Lipid vesicle-mediated affinity chromatography using magnetic activated cell sorting (LIMACS): a novel method to analyze protein-lipid interaction.

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Bieberich, Erhard

2011-04-26

The analysis of lipid protein interaction is difficult because lipids are embedded in cell membranes and therefore, inaccessible to most purification procedures. As an alternative, lipids can be coated on flat surfaces as used for lipid ELISA and Plasmon resonance spectroscopy. However, surface coating lipids do not form microdomain structures, which may be important for the lipid binding properties. Further, these methods do not allow for the purification of larger amounts of proteins binding to their target lipids. To overcome these limitations of testing lipid protein interaction and to purify lipid binding proteins we developed a novel method termed lipid vesicle-mediated affinity chromatography using magnetic-activated cell sorting (LIMACS). In this method, lipid vesicles are prepared with the target lipid and phosphatidylserine as the anchor lipid for Annexin V MACS. Phosphatidylserine is a ubiquitous cell membrane phospholipid that shows high affinity to the protein Annexin V. Using magnetic beads conjugated to Annexin V the phosphatidylserine-containing lipid vesicles will bind to the magnetic beads. When the lipid vesicles are incubated with a cell lysate the protein binding to the target lipid will also be bound to the beads and can be co-purified using MACS. This method can also be used to test if recombinant proteins reconstitute a protein complex binding to the target lipid. We have used this method to show the interaction of atypical PKC (aPKC) with the sphingolipid ceramide and to co-purify prostate apoptosis response 4 (PAR-4), a protein binding to ceramide-associated aPKC. We have also used this method for the reconstitution of a ceramide-associated complex of recombinant aPKC with the cell polarity-related proteins Par6 and Cdc42. Since lipid vesicles can be prepared with a variety of sphingo- or phospholipids, LIMACS offers a versatile test for lipid-protein interaction in a lipid environment that resembles closely that of the cell membrane

Chromatin immunoprecipitation to analyze DNA binding sites of HMGA2.

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Nina Winter

Full Text Available BACKGROUND: HMGA2 is an architectonic transcription factor abundantly expressed during embryonic and fetal development and it is associated with the progression of malignant tumors. The protein harbours three basically charged DNA binding domains and an acidic protein binding C-terminal domain. DNA binding induces changes of DNA conformation and hence results in global overall change of gene expression patterns. Recently, using a PCR-based SELEX (Systematic Evolution of Ligands by Exponential Enrichment procedure two consensus sequences for HMGA2 binding have been identified. METHODOLOGY/PRINCIPAL FINDINGS: In this investigation chromatin immunoprecipitation (ChIP experiments and bioinformatic methods were used to analyze if these binding sequences can be verified on chromatin of living cells as well. CONCLUSION: After quantification of HMGA2 protein in different cell lines the colon cancer derived cell line HCT116 was chosen for further ChIP experiments because of its 3.4-fold higher HMGA2 protein level. 49 DNA fragments were obtained by ChIP. These fragments containing HMGA2 binding sites have been analyzed for their AT-content, location in the human genome and similarities to sequences generated by a SELEX study. The sequences show a significantly higher AT-content than the average of the human genome. The artificially generated SELEX sequences and short BLAST alignments (11 and 12 bp of the ChIP fragments from living cells show similarities in their organization. The flanking regions are AT-rich, whereas a lower conservation is present in the center of the sequences.

Regulation of the Src Kinase-associated Phosphoprotein 55 Homologue by the Protein Tyrosine Phosphatase PTP-PEST in the Control of Cell Motility*

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Ayoub, Emily; Hall, Anita; Scott, Adam M.; Chagnon, Mélanie J.; Miquel, Géraldine; Hallé, Maxime; Noda, Masaharu; Bikfalvi, Andreas; Tremblay, Michel L.

2013-01-01

PTP-PEST is a cytosolic ubiquitous protein tyrosine phosphatase (PTP) that contains, in addition to its catalytic domain, several protein-protein interaction domains that allow it to interface with several signaling pathways. Among others, PTP-PEST is a key regulator of cellular motility and cytoskeleton dynamics. The complexity of the PTP-PEST interactome underscores the necessity to identify its interacting partners and physiological substrates in order to further understand its role in focal adhesion complex turnover and actin organization. Using a modified yeast substrate trapping two-hybrid system, we identified a cytosolic adaptor protein named Src kinase-associated phosphoprotein 55 homologue (SKAP-Hom) as a novel substrate of PTP-PEST. To confirm PTP-PEST interaction with SKAP-Hom, in vitro pull down assays were performed demonstrating that the PTP catalytic domain and Proline-rich 1 (P1) domain are respectively binding to the SKAP-Hom Y260 and Y297 residues and its SH3 domain. Subsequently, we generated and rescued SKAP-Hom-deficient mouse embryonic fibroblasts (MEFs) with WT SKAP-Hom, SKAP-Hom tyrosine mutants (Y260F, Y260F/Y297F), or SKAP-Hom SH3 domain mutant (W335K). Given the role of PTP-PEST, wound-healing and trans-well migration assays were performed using the generated lines. Indeed, SKAP-Hom-deficient MEFs showed a defect in migration compared with WT-rescued MEFs. Interestingly, the SH3 domain mutant-rescued MEFs showed an enhanced cell migration corresponding potentially with higher tyrosine phosphorylation levels of SKAP-Hom. These findings suggest a novel role of SKAP-Hom and its phosphorylation in the regulation of cellular motility. Moreover, these results open new avenues by which PTP-PEST regulates cellular migration, a hallmark of metastasis. PMID:23897807

Globular and disordered – the non-identical twins in protein-protein interactions

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Kaare eTeilum

2015-07-01

Full Text Available In biology proteins from different structural classes interact across and within classes in ways that are optimized to achieve balanced functional outputs. The interactions between intrinsically disordered proteins (IDPs and other proteins rely on changes in flexibility and this is seen as a strong determinant for their function. This has fostered the notion that IDP’s bind with low affinity but high specificity. Here we have analyzed available detailed thermodynamic data for protein-protein interactions to put to the test if the thermodynamic profiles of IDP interactions differ from those of other protein-protein interactions. We find that ordered proteins and the disordered ones act as non identical twins operating by similar principles but where the disordered proteins complexes are on average less stable by 2.5 kcal mol-1.

The Clavibacter michiganensis subsp. michiganensis-tomato interactome reveals the perception of pathogen by the host and suggests mechanisms of infection

Energy Technology Data Exchange (ETDEWEB)

Savidor, Alon [Tel Aviv University; Teper, [Tel Aviv University; Gartemann, KH [Tel Aviv University; Eichenlaub, R [Tel Aviv University; Chalupowicz, L [Tel Aviv University; Manulis-Sasson, S [Tel Aviv University; Barash, I [Tel Aviv University; Tews, H [Tel Aviv University; Mayer, K [Tel Aviv University; Giannone, Richard J [ORNL; Hettich, Robert {Bob} L [ORNL; Sessa, G [Tel Aviv University

2012-01-01

The Gram-positive bacterium Clavibacter michiganensis subsp. michiganensis (Cmm) causes wilt and canker disease of tomato (Solanum lycopersicum). Mechanisms of Cmm pathogenicity and tomato response to Cmm infection are not well understood. To explore the interaction between Cmm and tomato, multidimensional protein identification technology (MudPIT) and tandem mass spectrometry were used to analyze in vitro and in planta generated samples. The results show that during infection Cmm senses the plant environment, transmits signals, induces, and then secretes multiple hydrolytic enzymes, including serine proteases of the Pat-1, Ppa, and Sbt familes, the CelA, XysA, and NagA glycosyl hydrolases, and other cell wall-degrading enzymes. Tomato induction of pathogenesis-related (PR) proteins, LOX1, and other defense-related proteins during infection indicates that the plant senses the invading bacterium and mounts a basal defense response, although partial with some suppressed components including class III peroxidases and a secreted serine peptidase. The tomato ethylene-synthesizing enzyme ACC-oxidase was induced during infection with the wild-type Cmm but not during infection with an endophytic Cmm strain, identifying Cmm-triggered host synthesis of ethylene as an important factor in disease symptom development. The proteomic data were also used to improve Cmm genome annotation, and thousands of Cmm gene models were confirmed or expanded.

Detecting protein complexes based on a combination of topological and biological properties in protein-protein interaction network

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Pooja Sharma

2018-06-01

Full Text Available Protein complexes are known to play a major role in controlling cellular activity in a living being. Identifying complexes from raw protein protein interactions (PPIs is an important area of research. Earlier work has been limited mostly to yeast. Such protein complex identification methods, when applied to large human PPIs often give poor performance. We introduce a novel method called CSC to detect protein complexes. The method is evaluated in terms of positive predictive value, sensitivity and accuracy using the datasets of the model organism, yeast and humans. CSC outperforms several other competing algorithms for both organisms. Further, we present a framework to establish the usefulness of CSC in analyzing the influence of a given disease gene in a complex topologically as well as biologically considering eight major association factors. Keywords: Protein complex, Connectivity, Semantic similarity, Contribution

Systems-level analysis of risk genes reveals the modular nature of schizophrenia.

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Liu, Jiewei; Li, Ming; Luo, Xiong-Jian; Su, Bing

2018-05-19

Schizophrenia (SCZ) is a complex mental disorder with high heritability. Genetic studies (especially recent genome-wide association studies) have identified many risk genes for schizophrenia. However, the physical interactions among the proteins encoded by schizophrenia risk genes remain elusive and it is not known whether the identified risk genes converge on common molecular networks or pathways. Here we systematically investigated the network characteristics of schizophrenia risk genes using the high-confidence protein-protein interactions (PPI) from the human interactome. We found that schizophrenia risk genes encode a densely interconnected PPI network (P = 4.15 × 10 -31 ). Compared with the background genes, the schizophrenia risk genes in the interactome have significantly higher degree (P = 5.39 × 10 -11 ), closeness centrality (P = 7.56 × 10 -11 ), betweeness centrality (P = 1.29 × 10 -11 ), clustering coefficient (P = 2.22 × 10 -2 ), and shorter average shortest path length (P = 7.56 × 10 -11 ). Based on the densely interconnected PPI network, we identified 48 hub genes and 4 modules formed by highly interconnected schizophrenia genes. We showed that the proteins encoded by schizophrenia hub genes have significantly more direct physical interactions. Gene ontology (GO) analysis revealed that cell adhesion, cell cycle, immune system response, and GABR-receptor complex categories were enriched in the modules formed by highly interconnected schizophrenia risk genes. Our study reveals that schizophrenia risk genes encode a densely interconnected molecular network and demonstrates the modular nature of schizophrenia. Copyright © 2018 Elsevier B.V. All rights reserved.

Novel algorithms for protein sequence analysis

NARCIS (Netherlands)

Ye, Kai

2008-01-01

Each protein is characterized by its unique sequential order of amino acids, the so-called protein sequence. Biology”s paradigm is that this order of amino acids determines the protein”s architecture and function. In this thesis, we introduce novel algorithms to analyze protein sequences. Chapter 1

Improved data visualization techniques for analyzing macromolecule structural changes.

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Kim, Jae Hyun; Iyer, Vidyashankara; Joshi, Sangeeta B; Volkin, David B; Middaugh, C Russell

2012-10-01

The empirical phase diagram (EPD) is a colored representation of overall structural integrity and conformational stability of macromolecules in response to various environmental perturbations. Numerous proteins and macromolecular complexes have been analyzed by EPDs to summarize results from large data sets from multiple biophysical techniques. The current EPD method suffers from a number of deficiencies including lack of a meaningful relationship between color and actual molecular features, difficulties in identifying contributions from individual techniques, and a limited ability to be interpreted by color-blind individuals. In this work, three improved data visualization approaches are proposed as techniques complementary to the EPD. The secondary, tertiary, and quaternary structural changes of multiple proteins as a function of environmental stress were first measured using circular dichroism, intrinsic fluorescence spectroscopy, and static light scattering, respectively. Data sets were then visualized as (1) RGB colors using three-index EPDs, (2) equiangular polygons using radar charts, and (3) human facial features using Chernoff face diagrams. Data as a function of temperature and pH for bovine serum albumin, aldolase, and chymotrypsin as well as candidate protein vaccine antigens including a serine threonine kinase protein (SP1732) and surface antigen A (SP1650) from S. pneumoniae and hemagglutinin from an H1N1 influenza virus are used to illustrate the advantages and disadvantages of each type of data visualization technique. Copyright © 2012 The Protein Society.

Protein extraction and gel-based separation methods to analyze responses to pathogens in carnation (Dianthus caryophyllus L).

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Ardila, Harold Duban; Fernández, Raquel González; Higuera, Blanca Ligia; Redondo, Inmaculada; Martínez, Sixta Tulia

2014-01-01

We are currently using a 2-DE-based proteomics approach to study plant responses to pathogenic fungi by using the carnation (Dianthus caryophyllus L)-Fusarium oxysporum f. sp. dianthi pathosystem. It is clear that the protocols for the first stages of a standard proteomics workflow must be optimized to each biological system and objectives of the research. The optimization procedure for the extraction and separation of proteins by 1-DE and 2-DE in the indicated system is reported. This strategy can be extrapolated to other plant-pathogen interaction systems in order to perform an evaluation of the changes in the host protein profile caused by the pathogen and to identify proteins which, at early stages, are involved or implicated in the plant defense response.

Identifying candidate agents for lung adenocarcinoma by walking the human interactome

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Sun Y

2016-09-01

Full Text Available Yajiao Sun,1 Ranran Zhang,2 Zhe Jiang,1 Rongyao Xia,1 Jingwen Zhang,1 Jing Liu,1 Fuhui Chen1 1Department of Respiratory, The Second Affiliated Hospital of Harbin Medical University, 2Department of Respiratory, Harbin First Hospital, Harbin, People’s Republic of China Abstract: Despite recent advances in therapeutic strategies for lung cancer, mortality is still increasing. Therefore, there is an urgent need to identify effective novel drugs. In the present study, we implement drug repositioning for lung adenocarcinoma (LUAD by a bioinformatics method followed by experimental validation. We first identified differentially expressed genes between LUAD tissues and nontumor tissues from RNA sequencing data obtained from The Cancer Genome Atlas database. Then, candidate small molecular drugs were ranked according to the effect of their targets on differentially expressed genes of LUAD by a random walk with restart algorithm in protein–protein interaction networks. Our method identified some potentially novel agents for LUAD besides those that had been previously reported (eg, hesperidin. Finally, we experimentally verified that atracurium, one of the potential agents, could induce A549 cells death in non-small-cell lung cancer-derived A549 cells by an MTT assay, acridine orange and ethidium bromide staining, and electron microscopy. Furthermore, Western blot assays demonstrated that atracurium upregulated the proapoptotic Bad and Bax proteins, downregulated the antiapoptotic p-Bad and Bcl-2 proteins, and enhanced caspase-3 activity. It could also reduce the expression of p53 and p21Cip1/Waf1 in A549 cells. In brief, the candidate agents identified by our approach may provide greater insights into improving the therapeutic status of LUAD. Keywords: lung adenocarcinoma, drug repositioning, bioinformatics, protein–protein interaction network, atracurium

Analyzing Big Data in Psychology: A Split/Analyze/Meta-Analyze Approach

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Mike W.-L. Cheung

2016-05-01

Full Text Available Big data is a field that has traditionally been dominated by disciplines such as computer science and business, where mainly data-driven analyses have been performed. Psychology, a discipline in which a strong emphasis is placed on behavioral theories and empirical research, has the potential to contribute greatly to the big data movement. However, one challenge to psychologists – and probably the most crucial one – is that most researchers may not have the necessary programming and computational skills to analyze big data. In this study we argue that psychologists can also conduct big data research and that, rather than trying to acquire new programming and computational skills, they should focus on their strengths, such as performing psychometric analyses and testing theories using multivariate analyses to explain phenomena. We propose a split/analyze/meta-analyze approach that allows psychologists to easily analyze big data. Two real datasets are used to demonstrate the proposed procedures in R. A new research agenda related to the analysis of big data in psychology is outlined at the end of the study.

Analyzing Big Data in Psychology: A Split/Analyze/Meta-Analyze Approach.

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Cheung, Mike W-L; Jak, Suzanne

2016-01-01

Big data is a field that has traditionally been dominated by disciplines such as computer science and business, where mainly data-driven analyses have been performed. Psychology, a discipline in which a strong emphasis is placed on behavioral theories and empirical research, has the potential to contribute greatly to the big data movement. However, one challenge to psychologists-and probably the most crucial one-is that most researchers may not have the necessary programming and computational skills to analyze big data. In this study we argue that psychologists can also conduct big data research and that, rather than trying to acquire new programming and computational skills, they should focus on their strengths, such as performing psychometric analyses and testing theories using multivariate analyses to explain phenomena. We propose a split/analyze/meta-analyze approach that allows psychologists to easily analyze big data. Two real datasets are used to demonstrate the proposed procedures in R. A new research agenda related to the analysis of big data in psychology is outlined at the end of the study.

Animal and Plant Proteins as Precursors of Peptides with ACE Inhibitory Activity – An in silico Strategy of Protein Evaluation

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Anna Iwaniak

2009-01-01

Full Text Available This paper presents a modern in silico approach useful in the evaluation of proteins as a source of ACE inhibitors. All protein sequences analyzed were derived from the BIOPEP database. To determine the protein value, the following criteria of evaluation were applied: the profile of potential biological (ACE inhibitory activity of a protein, the frequency of the occurrence of fragments with ACE inhibitory activity (A and the potential biological activity of a protein (B. The results, based on a statistical analysis, indicate that milk proteins can be a better source of ACE inhibitors than wheat gliadins. Moreover, all analyzed gliadins possessed more potent ACE inhibitors than chicken meat proteins. No significant differences were observed when comparing A values between soy globulins and β-lactoglobulins. Although criteria such as the profile of potential biological activity of protein, as well as parameters A and B, can be suitable tools in protein evaluation, the proteolytic digestion of protein needs to be considered. Moreover, computerised methods of classifying proteins according to different algorithms are often subjective due to discretion in interpretation of the results.

Comparison of avian biochemical test results with Abaxis VetScan and Hitachi 911 analyzers.

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Greenacre, Cheryl B; Flatland, Bente; Souza, Marcy J; Fry, Michael M

2008-12-01

To compare results of clinical biochemical analysis using an Abaxis VetScan bench-top analyzer with reagents specifically marketed for avian use and a Hitachi 911 analyzer, plasma (both methods) and whole blood (VetScan method) samples from 20 clinically healthy Hispaniolan Amazon parrots (Amazona ventralis) were analyzed. Correlation between methods was very high (r = 0.9-1.0) for aspartate aminotransferase (AST), calcium, glucose, and uric acid; high (r = 0.7-0.89) for creatine kinase (CK), phosphorus, potassium, and total protein; moderate (r = 0.5-0.69) for globulin; and low (r = 0.3-0.49) for albumin and sodium. VetScan analyzer results for globulin, sodium, and uric acid had a constant negative bias (values below those from the Hitachi method). Based on difference plot analysis, results for AST, calcium, CK, and glucose are comparable. Because 16 of 20 values fell below the lower detection limit of the VetScan analyzer, bile acid data were excluded from analysis. By using a relatively small sample size (0.1 ml whole blood or plasma), the VetScan analyzer offers rapid in-house results, compact size, and ease of operation. For 4 of the most clinically relevant biochemical analytes used in avian medicine (AST, calcium, CK, glucose), it offers reliable values. For an additional 4 analytes (phosphorous, potassium, total protein, uric acid), establishing analyzer-specific reference intervals is recommended. Neither the VetScan nor the Hitachi method is recommended to assess albumin and globulin concentrations.

Major proteins in normal human lymphocyte subpopulations separated by fluorescence-activated cell sorting and analyzed by two-dimensional gel electrophoresis

DEFF Research Database (Denmark)

Madsen, P S; Hokland, M; Ellegaard, J

1988-01-01

markers were observed in all cell types. All the putative protein markers have been identified in the protein database of human peripheral blood mononuclear cells (PBMCs) (see accompanying article by Celis et al.). Comparison of the overall patterns of protein synthesis of the unsorted PBMCs with those...... of the four subpopulations showed that the synthesis of some major PBMC proteins decreased substantially in the sorted subsets. These proteins are most likely not of monocyte origin, as these cells constituted only about 15% of the total PBMCs. Also, the inhibition does not seem to be due to the addition...

Analyzing pepsin degradation assay conditions used for allergenicity assessments to ensure that pepsin susceptible and pepsin resistant dietary proteins are distinguishable.

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Rong Wang

Full Text Available The susceptibility of a dietary protein to proteolytic degradation by digestive enzymes, such as gastric pepsin, provides information on the likelihood of systemic exposure to a structurally intact and biologically active macromolecule, thus informing on the safety of proteins for human and animal consumption. Therefore, the purpose of standardized in vitro degradation studies that are performed during protein safety assessments is to distinguish whether proteins of interest are susceptible or resistant to pepsin degradation via a study design that enables study-to-study comparison. Attempting to assess pepsin degradation under a wide-range of possible physiological conditions poses a problem because of the lack of robust and consistent data collected under a large-range of sub-optimal conditions, which undermines the needs to harmonize in vitro degradation conditions. This report systematically compares the effects of pH, incubation time, and pepsin-to-substrate protein ratio on the relative degradation of five dietary proteins: three pepsin susceptible proteins [ribulose 1,5-bisphosphate carboxylase-oxygenase (Rubisco, horseradish peroxidase (HRP, hemoglobin (Hb], and two pepsin resistant proteins [lipid transfer protein (LTP and soybean trypsin inhibitor (STI]. The results indicate that proteins susceptible to pepsin degradation are readily distinguishable from pepsin-resistant proteins when the reaction conditions are within the well-characterized optima for pepsin. The current standardized in vitro pepsin resistant assay with low pH and high pepsin-to-substrate ratio fits this purpose. Using non-optimal pH and/or pepsin-to-substrate protein ratios resulted in susceptible proteins no longer being reliably degraded by this stomach enzyme, which compromises the ability of this in vitro assay to distinguish between resistant and susceptible proteins and, therefore, no longer providing useful data to an overall weight-of-evidence approach to

Protein characterization of protein bodies from cotyledons of Mucuna pruriens (L.) DC.

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Bellani, Lorenza; Giglioni, Stefania; Muccifora, Simonetta

2013-03-01

Seeds of Mucuna pruriens (L.) DC. (Fabaceae) were analyzed for protein composition of protein bodies isolated from cotyledons. Protein bodies were successfully separated by Lympholyte and those of dry seeds, observed by scanning electron microscope, were elliptical or spherical in shape with a diameter of 5-12 μm. Protein content in dry seed protein bodies was 10.6 mg/g dry weight. Globulin was the largest protein fraction isolated (62.5 %), followed by albumin (18.3 %), glutelin (15.8 %) and prolamin (3.4 %). The prolamin fraction and high glutelin content are uncommon in legumes. SDS-PAGE of albumins, globulins, prolamins and glutelins provided different band numbers and molecular weights under reducing and non reducing conditions and suggested that the albumin fraction is rich in disulphide bonds.

Introducing Students to Protein Analysis Techniques: Separation and Comparative Analysis of Gluten Proteins in Various Wheat Strains

Science.gov (United States)

Pirinelli, Alyssa L.; Trinidad, Jonathan C.; Pohl, Nicola L. B.

2016-01-01

Polyacrylamide gel electrophoresis (PAGE) is commonly taught in undergraduate laboratory classes as a traditional method to analyze proteins. An experiment has been developed to teach these basic protein gel skills in the context of gluten protein isolation from various types of wheat flour. A further goal is to relate this technique to current…

Protein stability: a crystallographer’s perspective

Science.gov (United States)

Deller, Marc C.; Kong, Leopold; Rupp, Bernhard

2016-01-01

Protein stability is a topic of major interest for the biotechnology, pharmaceutical and food industries, in addition to being a daily consideration for academic researchers studying proteins. An understanding of protein stability is essential for optimizing the expression, purification, formulation, storage and structural studies of proteins. In this review, discussion will focus on factors affecting protein stability, on a somewhat practical level, particularly from the view of a protein crystallographer. The differences between protein conformational stability and protein compositional stability will be discussed, along with a brief introduction to key methods useful for analyzing protein stability. Finally, tactics for addressing protein-stability issues during protein expression, purification and crystallization will be discussed. PMID:26841758

Rapid measurement of macronutrients in breast milk: How reliable are infrared milk analyzers?✩

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Fusch, Gerhard; Rochow, Niels; Choi, Arum; Fusch, Stephanie; Poeschl, Susanna; Ubah, Adelaide Obianuju; Lee, Sau-Young; Raja, Preeya; Fusch, Christoph

2016-01-01

SUMMARY Background & aims Significant biological variation in macronutrient content of breast milk is an important barrier that needs to be overcome to meet nutritional needs of preterm infants. To analyze macronutrient content, commercial infrared milk analyzers have been proposed as efficient and practical tools in terms of efficiency and practicality. Since milk analyzers were originally developed for the dairy industry, they must be validated using a significant number of human milk samples that represent the broad range of variation in macronutrient content in preterm and term milk. Aim of this study was to validate two milk analyzers for breast milk analysis with reference methods and to determine an effective sample pretreatment. Current evidence for the influence of (i) aliquoting, (ii) storage time and (iii) temperature, and (iv) vessel wall adsorption on stability and availability of macronutrients in frozen breast milk is reviewed. Methods Breast milk samples (n = 1188) were collected from 63 mothers of preterm and term infants. Milk analyzers: (A) Near-infrared milk analyzer (Unity SpectraStar, USA) and (B) Mid-infrared milk analyzer (Miris, Sweden) were compared to reference methods, e.g. ether extraction, elemental analysis, and UPLC-MS/MS for fat, protein, and lactose, respectively. Results For fat analysis, (A) measured precisely but not accurately (y = 0.55x + 1.25, r2 = 0.85), whereas (B) measured precisely and accurately (y = 0.93x + 0.18, r2 = 0.86). For protein analysis, (A) was precise but not accurate (y = 0.55x + 0.54, r2 = 0.67) while (B) was both precise and accurate (y = 0.78x + 0.05, r2 = 0.73). For lactose analysis, both devices (A) and (B) showed two distinct concentration levels and measured therefore neither accurately nor precisely (y = 0.02x + 5.69, r2 = 0.01 and y = −0.09x + 6.62, r2 = 0.02 respectively). Macronutrient levels were unchanged in two independent samples of stored breast milk (−20 °C measured with IR; −80 �

Application of clustering methods: Regularized Markov clustering (R-MCL) for analyzing dengue virus similarity

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Lestari, D.; Raharjo, D.; Bustamam, A.; Abdillah, B.; Widhianto, W.

2017-07-01

Dengue virus consists of 10 different constituent proteins and are classified into 4 major serotypes (DEN 1 - DEN 4). This study was designed to perform clustering against 30 protein sequences of dengue virus taken from Virus Pathogen Database and Analysis Resource (VIPR) using Regularized Markov Clustering (R-MCL) algorithm and then we analyze the result. By using Python program 3.4, R-MCL algorithm produces 8 clusters with more than one centroid in several clusters. The number of centroid shows the density level of interaction. Protein interactions that are connected in a tissue, form a complex protein that serves as a specific biological process unit. The analysis of result shows the R-MCL clustering produces clusters of dengue virus family based on the similarity role of their constituent protein, regardless of serotypes.

Protein-Protein Interaction Network and Gene Ontology

Science.gov (United States)

Choi, Yunkyu; Kim, Seok; Yi, Gwan-Su; Park, Jinah

Evolution of computer technologies makes it possible to access a large amount and various kinds of biological data via internet such as DNA sequences, proteomics data and information discovered about them. It is expected that the combination of various data could help researchers find further knowledge about them. Roles of a visualization system are to invoke human abilities to integrate information and to recognize certain patterns in the data. Thus, when the various kinds of data are examined and analyzed manually, an effective visualization system is an essential part. One instance of these integrated visualizations can be combination of protein-protein interaction (PPI) data and Gene Ontology (GO) which could help enhance the analysis of PPI network. We introduce a simple but comprehensive visualization system that integrates GO and PPI data where GO and PPI graphs are visualized side-by-side and supports quick reference functions between them. Furthermore, the proposed system provides several interactive visualization methods for efficiently analyzing the PPI network and GO directedacyclic- graph such as context-based browsing and common ancestors finding.

Detecting protein-protein interactions in the intact cell of Bacillus subtilis (ATCC 6633).

Science.gov (United States)

Winters, Michael S; Day, R A

2003-07-01

The salt bridge, paired group-specific reagent cyanogen (ethanedinitrile; C(2)N(2)) converts naturally occurring pairs of functional groups into covalently linked products. Cyanogen readily permeates cell walls and membranes. When the paired groups are shared between associated proteins, isolation of the covalently linked proteins allows their identity to be assigned. Examination of organisms of known genome sequence permits identification of the linked proteins by mass spectrometric techniques applied to peptides derived from them. The cyanogen-linked proteins were isolated by polyacrylamide gel electrophoresis. Digestion of the isolated proteins with proteases of known specificity afforded sets of peptides that could be analyzed by mass spectrometry. These data were compared with those derived theoretically from the Swiss Protein Database by computer-based comparisons (Protein Prospector; http://prospector.ucsf.edu). Identification of associated proteins in the ribosome of Bacillus subtilis strain ATCC 6633 showed that there is an association homology with the association patterns of the ribosomal proteins of Haloarcula marismortui and Thermus thermophilus. In addition, other proteins involved in protein biosynthesis were shown to be associated with ribosomal proteins.

Hubungan antara konsumsi protein dengan produksi, protein dan laktosa susu kambing Peranakan Ettawa

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Galuh Estu Prihatiningsih

2015-09-01

Full Text Available The study aimed to determine a correlation between crude protein intake, milk production, milk protein and milk lactose. This study used purposive sampling method. The sample used in this study were 35 Etawa crossbred goats with months of lactation 4-5 and lactation periods 2-3. Parameters observed were crude protein intake, milk production, milk protein and milk lactose. Data were analyzed using correlation analysis and simple linear regression. The result showed that crude protein intake, total milk production concentrations of milk protein and lactose were 0.77 kg/day; 0.30 kg/day; 0.196% and 3.32% respectively. There was a medium positive linear correlation between the crude protein intake with total milk production, protein and lactose content of milk. The correlation coefficient (r were 0.258; 0.254 and 0,255 respectively. It could be concluded that the higher crude protein intake would increase the amount of milk production, protein and lactose contents. Keywords: crude protein intake, total milk production, milk protein, milk lactose

Next challenges in protein–protein docking: from proteome to interactome and beyond

NARCIS (Netherlands)

Melquiond, A.S.J.; Karaca, E.; Kastritis, P.; Bonvin, A.M.J.J.

2012-01-01

Advances in biophysics and biochemistry have pushed back the limits for the structural characterization of biomolecular assemblies. Large efforts have been devoted to increase both resolution and accuracy of the methods, probe into the smallest biomolecules as well as the largest macromolecular

Simultaneous genome-wide inference of physical, genetic, regulatory, and functional pathway components.

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Christopher Y Park

2010-11-01

Full Text Available Biomolecular pathways are built from diverse types of pairwise interactions, ranging from physical protein-protein interactions and modifications to indirect regulatory relationships. One goal of systems biology is to bridge three aspects of this complexity: the growing body of high-throughput data assaying these interactions; the specific interactions in which individual genes participate; and the genome-wide patterns of interactions in a system of interest. Here, we describe methodology for simultaneously predicting specific types of biomolecular interactions using high-throughput genomic data. This results in a comprehensive compendium of whole-genome networks for yeast, derived from ∼3,500 experimental conditions and describing 30 interaction types, which range from general (e.g. physical or regulatory to specific (e.g. phosphorylation or transcriptional regulation. We used these networks to investigate molecular pathways in carbon metabolism and cellular transport, proposing a novel connection between glycogen breakdown and glucose utilization supported by recent publications. Additionally, 14 specific predicted interactions in DNA topological change and protein biosynthesis were experimentally validated. We analyzed the systems-level network features within all interactomes, verifying the presence of small-world properties and enrichment for recurring network motifs. This compendium of physical, synthetic, regulatory, and functional interaction networks has been made publicly available through an interactive web interface for investigators to utilize in future research at http://function.princeton.edu/bioweaver/.

Human Antiviral Protein IFIX Suppresses Viral Gene Expression during Herpes Simplex Virus 1 (HSV-1) Infection and Is Counteracted by Virus-induced Proteasomal Degradation.

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Crow, Marni S; Cristea, Ileana M

2017-04-01

The interferon-inducible protein X (IFIX), a member of the PYHIN family, was recently recognized as an antiviral factor against infection with herpes simplex virus 1 (HSV-1). IFIX binds viral DNA upon infection and promotes expression of antiviral cytokines. How IFIX exerts its host defense functions and whether it is inhibited by the virus remain unknown. Here, we integrated live cell microscopy, proteomics, IFIX domain characterization, and molecular virology to investigate IFIX regulation and antiviral functions during HSV-1 infection. We find that IFIX has a dynamic localization during infection that changes from diffuse nuclear and nucleoli distribution in uninfected cells to discrete nuclear puncta early in infection. This is rapidly followed by a reduction in IFIX protein levels. Indeed, using immunoaffinity purification and mass spectrometry, we define IFIX interactions during HSV-1 infection, finding an association with a proteasome subunit and proteins involved in ubiquitin-proteasome processes. Using synchronized HSV-1 infection, microscopy, and proteasome-inhibition experiments, we demonstrate that IFIX co-localizes with nuclear proteasome puncta shortly after 3 h of infection and that its pyrin domain is rapidly degraded in a proteasome-dependent manner. We further demonstrate that, in contrast to several other host defense factors, IFIX degradation is not dependent on the E3 ubiquitin ligase activity of the viral protein ICP0. However, we show IFIX degradation requires immediate-early viral gene expression, suggesting a viral host suppression mechanism. The IFIX interactome also demonstrated its association with transcriptional regulatory proteins, including the 5FMC complex. We validate this interaction using microscopy and reciprocal isolations and determine it is mediated by the IFIX HIN domain. Finally, we show IFIX suppresses immediate-early and early viral gene expression during infection. Altogether, our study demonstrates that IFIX antiviral

A genetic electrophoretic variant of high-sulfur hair proteins for forensic hair comparisons. I. Characterization of variant high-sulfur proteins of human hair.

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Miyake, B

1989-02-01

In a survey of the proteins from human hair, a genetic electrophoretic variant has been observed in the high-sulfur protein region. S-carboxymethylated proteins were examined by 15% polyacrylamide gel electrophoresis at pH 8.9. Out of 150 unrelated samples of Japanese head hairs analyzed, 107 showed 6 major high-sulfur protein bands (normal) and the remaining 43 samples showed an additional high-sulfur protein band (variant). Of 21 Caucasian samples analyzed only one variant sample was found. Characterization of the proteins by two-dimensional electrophoresis evidenced a variant protein spot which showed an apparent molecular weight of 30 k Da. Isoelectric points of the high-sulfur proteins ranged from 3.25-3.55 and that of variant protein band from 3.3-3.4. Family studies of 21 matings resulting in 49 children indicated that this variant was inherited in an autosomal fashion.

Analyzing the structural aspects of Isoprenoid biosynthesis pathway proteins in Ocimum species

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Muktesh Chandra

2017-10-01

Full Text Available Generally thought that the extremely diverse array of secondary metabolites observed within Ocimum species defends against a comparable diverse array of biotic pests, pathogens and herbivores encountered around its natural range. Along with defense the diverse array of secondary metabolite also leads to the therapeutic and remedial property which justifies Ocimum as natural medicinal and aromatic casket. Many of the defense compounds, aroma compounds and medicinal derivatives are secondary metabolites isolated from trichome glands, mainly consist of terpenoids as well as phenylpropanoids. Various pathways fabricating these compounds are known viz. mevalonate pathway (MVA, phenylpropanoid pathway and MEP pathways. The enzyme cascade responsible for various secondary metabolites, need to be explored in various aspects. Here we had studied the MVA pathway enzymes in O. basilicum and O. gratissimum to figure out variations in enzyme structures due to speciation. Hence, in depth analysis of the transcriptome of O. basilicum and O. gratissimum, varrying in qualitative and quantitative aspects of essential oil were carried out. The transcriptome data from NCBI server was assembled using bioinformatic approaches. nr database at NCBI repository used for annotation, which assigned 60% contigs to known functions. Contigs corresponding to Mevalonate pathway enzymes are isolated using perl pipelines developed in our lab, which were further assembled using CLC workbench to remove redundancy and make larger stretch of sequence. Blastx of these larger sequences assigned them function and they are mapped to validated sequences to make full length. Data from both species led us to overall seven enzymes (total 14 of MVA pathway. These enzymes are studied in detail for various physio-chemical properties, steriochemical properties and motif/domain for protein-protein interaction (PPI study. Homolog models of all enzymes were predicted, against templates from RCSB

Cross-phosphorylation of bacterial serine/threonine and tyrosine protein kinases on key regulatory residues

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Lei eShi

2014-09-01

Full Text Available Bacteria possess protein serine/threonine and tyrosine kinases which resemble eukaryal kinases in their capacity to phosphorylate multiple substrates. We hypothesized that the analogy might extend further, and bacterial kinases may also undergo mutual phosphorylation and activation, which is currently considered as a hallmark of eukaryal kinase networks. In order to test this hypothesis, we explored the capacity of all members of four different classes of serine/threonine and tyrosine kinases present in the firmicute model organism Bacillus subtilis to phosphorylate each other in vitro and interact with each other in vivo. The interactomics data suggested a high degree of connectivity among all types of kinases, while phosphorylation assays revealed equally wide-spread cross-phosphorylation events. Our findings suggest that the Hanks-type kinases PrkC, PrkD and YabT exhibit the highest capacity to phosphorylate other B. subtilis kinases, while the BY-kinase PtkA and the two-component-like kinases RsbW and SpoIIAB show the highest propensity to be phosphorylated by other kinases. Analysis of phosphorylated residues on several selected recipient kinases suggests that most cross-phosphorylation events concern key regulatory residues. Therefore, cross-phosphorylation events are very likely to influence the capacity of recipient kinases to phosphorylate substrates downstream in the signal transduction cascade. We therefore conclude that bacterial serine/threonine and tyrosine kinases probably engage in a network-type behavior previously described only in eukaryal cells.

Structure, function and networks of transcription factors involved in abiotic stress responses

DEFF Research Database (Denmark)

Lindemose, Søren; O'Shea, Charlotte; Jensen, Michael Krogh

2013-01-01

Transcription factors (TFs) are master regulators of abiotic stress responses in plants. This review focuses on TFs from seven major TF families, known to play functional roles in response to abiotic stresses, including drought, high salinity, high osmolarity, temperature extremes...... and the phytohormone ABA. Although ectopic expression of several TFs has improved abiotic stress tolerance in plants, fine-tuning of TF expression and protein levels remains a challenge to avoid crop yield loss. To further our understanding of TFs in abiotic stress responses, emerging gene regulatory networks based...... on TFs and their direct targets genes are presented. These revealed components shared between ABA-dependent and independent signaling as well as abiotic and biotic stress signaling. Protein structure analysis suggested that TFs hubs of large interactomes have extended regions with protein intrinsic...

Homozygous disruption of PDZD7 by reciprocal translocation in a consanguineous family: a new member of the Usher syndrome protein interactome causing congenital hearing impairment.

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Schneider, Eberhard; Märker, Tina; Daser, Angelika; Frey-Mahn, Gabriele; Beyer, Vera; Farcas, Ruxandra; Schneider-Rätzke, Brigitte; Kohlschmidt, Nicolai; Grossmann, Bärbel; Bauss, Katharina; Napiontek, Ulrike; Keilmann, Annerose; Bartsch, Oliver; Zechner, Ulrich; Wolfrum, Uwe; Haaf, Thomas

2009-02-15

A homozygous reciprocal translocation, 46,XY,t(10;11),t(10;11), was detected in a boy with non-syndromic congenital sensorineural hearing impairment. Both parents and their four other children were heterozygous translocation carriers, 46,XX,t(10;11) and 46,XY,t(10;11), respectively. Fluorescence in situ hybridization of region-specific clones to patient chromosomes was used to localize the breakpoints within bacterial artificial chromosome (BAC) RP11-108L7 on chromosome 10q24.3 and within BAC CTD-2527F12 on chromosome 11q23.3. Junction fragments were cloned by vector ligation and sequenced. The chromosome 10 breakpoint was identified within the PDZ domain containing 7 (PDZD7) gene, disrupting the open reading frame of transcript PDZD7-C (without PDZ domain) and the 5'-untranslated region of transcript PDZD7-D (with one PDZ and two prolin-rich domains). The chromosome 11 breakpoint was localized in an intergenic segment. Reverse transcriptase-polymerase chain reaction analysis revealed PDZD7 expression in the human inner ear. A murine Pdzd7 transcript that is most similar in structure to human PDZD7-D is known to be expressed in the adult inner ear and retina. PDZD7 shares sequence homology with the PDZ domain-containing genes, USH1C (harmonin) and DFNB31 (whirlin). Allelic mutations in harmonin and whirlin can cause both Usher syndrome (USH1C and USH2D, respectively) and congenital hearing impairment (DFNB18 and DFNB31, respectively). Protein-protein interaction assays revealed the integration of PDZD7 in the protein network related to the human Usher syndrome. Collectively, our data provide strong evidence that PDZD7 is a new autosomal-recessive deafness-causing gene and also a prime candidate gene for Usher syndrome.

Protein-protein interactions in the regulation of WRKY transcription factors.

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Chi, Yingjun; Yang, Yan; Zhou, Yuan; Zhou, Jie; Fan, Baofang; Yu, Jing-Quan; Chen, Zhixiang

2013-03-01

It has been almost 20 years since the first report of a WRKY transcription factor, SPF1, from sweet potato. Great progress has been made since then in establishing the diverse biological roles of WRKY transcription factors in plant growth, development, and responses to biotic and abiotic stress. Despite the functional diversity, almost all analyzed WRKY proteins recognize the TTGACC/T W-box sequences and, therefore, mechanisms other than mere recognition of the core W-box promoter elements are necessary to achieve the regulatory specificity of WRKY transcription factors. Research over the past several years has revealed that WRKY transcription factors physically interact with a wide range of proteins with roles in signaling, transcription, and chromatin remodeling. Studies of WRKY-interacting proteins have provided important insights into the regulation and mode of action of members of the important family of transcription factors. It has also emerged that the slightly varied WRKY domains and other protein motifs conserved within each of the seven WRKY subfamilies participate in protein-protein interactions and mediate complex functional interactions between WRKY proteins and between WRKY and other regulatory proteins in the modulation of important biological processes. In this review, we summarize studies of protein-protein interactions for WRKY transcription factors and discuss how the interacting partners contribute, at different levels, to the establishment of the complex regulatory and functional network of WRKY transcription factors.

An HDAC3-PROX1 corepressor module acts on HNF4α to control hepatic triglycerides.

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Armour, Sean M; Remsberg, Jarrett R; Damle, Manashree; Sidoli, Simone; Ho, Wesley Y; Li, Zhenghui; Garcia, Benjamin A; Lazar, Mitchell A

2017-09-15

The histone deacetylase HDAC3 is a critical mediator of hepatic lipid metabolism, and liver-specific deletion of HDAC3 leads to fatty liver. To elucidate the underlying mechanism, here we report a method of cross-linking followed by mass spectrometry to define a high-confidence HDAC3 interactome in vivo that includes the canonical NCoR-HDAC3 complex as well as Prospero-related homeobox 1 protein (PROX1). HDAC3 and PROX1 co-localize extensively on the mouse liver genome, and are co-recruited by hepatocyte nuclear factor 4α (HNF4α). The HDAC3-PROX1 module controls the expression of a gene program regulating lipid homeostasis, and hepatic-specific ablation of either component increases triglyceride content in liver. These findings underscore the importance of specific combinations of transcription factors and coregulators in the fine tuning of organismal metabolism.HDAC3 is a critical mediator of hepatic lipid metabolism and its loss leads to fatty liver. Here, the authors characterize the liver HDAC3 interactome in vivo, provide evidence that HDAC3 interacts with PROX1, and show that HDAC3 and PROX1 control expression of genes regulating lipid homeostasis.

Transduction proteins of olfactory receptor cells: identification of guanine nucleotide binding proteins and protein kinase C

International Nuclear Information System (INIS)

Anholt, R.R.H.; Mumby, S.M.; Stoffers, D.A.; Girard, P.R.; Kuo, J.F.; Snyder, S.H.

1987-01-01

The authors have analyzed guanine nucleotide binding proteins (G-proteins) in the olfactory epithelium of Rana catesbeiana using subunit-specific antisera. The olfactory epithelium contained the α subunits of three G-proteins, migrating on polyacrylamide gels in SDS with apparent molecular weights of 45,000, 42,000, and 40,000, corresponding to G/sub s/, G/sub i/, and G/sub o/, respectively. A single β subunit with an apparent molecular weight of 36,000 was detected. An antiserum against the α subunit of retinal transducin failed to detect immunoreactive proteins in olfactory cilia detached from the epithelium. The olfactory cilia appeared to be enriched in immunoreactive G/sub sα/ relative to G/sub ichemical bond/ and G/sub ochemical bond/ when compared to membranes prepared from the olfactory epithelium after detachment of the cilia. Bound antibody was detected by autoradiography after incubation with [ 125 I]protein. Immunohistochemical studies using an antiserum against the β subunit of G-proteins revealed intense staining of the ciliary surface of the olfactory epithelium and of the axon bundles in the lamina propria. In contrast, an antiserum against a common sequence of the α subunits preferentially stained the cell membranes of the olfactory receptor cells and the acinar cells of Bowman's glands and the deep submucosal glands. In addition to G-proteins, they have identified protein kinase C in olfactory cilia via a protein kinase C specific antiserum and via phorbol ester binding. However, in contrast to the G-proteins, protein kinase C occurred also in cilia isolated from respiratory epithelium

Digital Microfluidics Sample Analyzer

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Pollack, Michael G.; Srinivasan, Vijay; Eckhardt, Allen; Paik, Philip Y.; Sudarsan, Arjun; Shenderov, Alex; Hua, Zhishan; Pamula, Vamsee K.

2010-01-01

Three innovations address the needs of the medical world with regard to microfluidic manipulation and testing of physiological samples in ways that can benefit point-of-care needs for patients such as premature infants, for which drawing of blood for continuous tests can be life-threatening in their own right, and for expedited results. A chip with sample injection elements, reservoirs (and waste), droplet formation structures, fluidic pathways, mixing areas, and optical detection sites, was fabricated to test the various components of the microfluidic platform, both individually and in integrated fashion. The droplet control system permits a user to control droplet microactuator system functions, such as droplet operations and detector operations. Also, the programming system allows a user to develop software routines for controlling droplet microactuator system functions, such as droplet operations and detector operations. A chip is incorporated into the system with a controller, a detector, input and output devices, and software. A novel filler fluid formulation is used for the transport of droplets with high protein concentrations. Novel assemblies for detection of photons from an on-chip droplet are present, as well as novel systems for conducting various assays, such as immunoassays and PCR (polymerase chain reaction). The lab-on-a-chip (a.k.a., lab-on-a-printed-circuit board) processes physiological samples and comprises a system for automated, multi-analyte measurements using sub-microliter samples of human serum. The invention also relates to a diagnostic chip and system including the chip that performs many of the routine operations of a central labbased chemistry analyzer, integrating, for example, colorimetric assays (e.g., for proteins), chemiluminescence/fluorescence assays (e.g., for enzymes, electrolytes, and gases), and/or conductometric assays (e.g., for hematocrit on plasma and whole blood) on a single chip platform.

An analysis pipeline for the inference of protein-protein interaction networks

Energy Technology Data Exchange (ETDEWEB)

Taylor, Ronald C.; Singhal, Mudita; Daly, Don S.; Gilmore, Jason M.; Cannon, William R.; Domico, Kelly O.; White, Amanda M.; Auberry, Deanna L.; Auberry, Kenneth J.; Hooker, Brian S.; Hurst, G. B.; McDermott, Jason E.; McDonald, W. H.; Pelletier, Dale A.; Schmoyer, Denise A.; Wiley, H. S.

2009-12-01

An analysis pipeline has been created for deployment of a novel algorithm, the Bayesian Estimator of Protein-Protein Association Probabilities (BEPro), for use in the reconstruction of protein-protein interaction networks. We have combined the Software Environment for BIological Network Inference (SEBINI), an interactive environment for the deployment and testing of network inference algorithms that use high-throughput data, and the Collective Analysis of Biological Interaction Networks (CABIN), software that allows integration and analysis of protein-protein interaction and gene-to-gene regulatory evidence obtained from multiple sources, to allow interactions computed by BEPro to be stored, visualized, and further analyzed. Incorporating BEPro into SEBINI and automatically feeding the resulting inferred network into CABIN, we have created a structured workflow for protein-protein network inference and supplemental analysis from sets of mass spectrometry bait-prey experiment data. SEBINI demo site: https://www.emsl.pnl.gov /SEBINI/ Contact: ronald.taylor@pnl.gov. BEPro is available at http://www.pnl.gov/statistics/BEPro3/index.htm. Contact: ds.daly@pnl.gov. CABIN is available at http://www.sysbio.org/dataresources/cabin.stm. Contact: mudita.singhal@pnl.gov.

Green Fluorescent Protein (GFP-Based Overexpression Screening and Characterization of AgrC, a Receptor Protein of Quorum Sensing in Staphylococcus aureus

Directory of Open Access Journals (Sweden)

Shengdi Fan

2013-09-01

Full Text Available Staphylococcus aureus AgrC is an important component of the agr quorum-sensing system. AgrC is a membrane-embedded histidine kinase that is thought to act as a sensor for the recognition of environmental signals and the transduction of signals into the cytoplasm. However, the difficulty of expressing and purifying functional membrane proteins has drastically hindered in-depth understanding of the molecular structures and physiological functions of these proteins. Here, we describe the high-yield expression and purification of AgrC, and analyze its kinase activity. A C-terminal green fluorescent protein (GFP fusion to AgrC served as a reporter for monitoring protein expression levels in real time. Protein expression levels were analyzed by the microscopic assessment of the whole-cell fluorescence. The expressed AgrC-GFP protein with a C-terminal His-tagged was purified using immobilized metal affinity chromatography (IMAC and size exclusion chromatography (SEC at yields of ≥10 mg/L, following optimization. We also assessed the effects of different detergents on membrane solubilization and AgrC kinase activity, and polyoxyethylene-(23-lauryl-ether (Brij-35 was identified as the most suitable detergent. Furthermore, the secondary structural stability of purified AgrC was analyzed using circular dichroism (CD spectroscopy. This study may serve as a general guide for improving the yields of other membrane protein preparations and selecting the appropriate detergent to stabilize membrane proteins for biophysical and biochemical analyses.

Training signaling pathway maps to biochemical data with constrained fuzzy logic: quantitative analysis of liver cell responses to inflammatory stimuli.

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Melody K Morris

2011-03-01

Full Text Available Predictive understanding of cell signaling network operation based on general prior knowledge but consistent with empirical data in a specific environmental context is a current challenge in computational biology. Recent work has demonstrated that Boolean logic can be used to create context-specific network models by training proteomic pathway maps to dedicated biochemical data; however, the Boolean formalism is restricted to characterizing protein species as either fully active or inactive. To advance beyond this limitation, we propose a novel form of fuzzy logic sufficiently flexible to model quantitative data but also sufficiently simple to efficiently construct models by training pathway maps on dedicated experimental measurements. Our new approach, termed constrained fuzzy logic (cFL, converts a prior knowledge network (obtained from literature or interactome databases into a computable model that describes graded values of protein activation across multiple pathways. We train a cFL-converted network to experimental data describing hepatocytic protein activation by inflammatory cytokines and demonstrate the application of the resultant trained models for three important purposes: (a generating experimentally testable biological hypotheses concerning pathway crosstalk, (b establishing capability for quantitative prediction of protein activity, and (c prediction and understanding of the cytokine release phenotypic response. Our methodology systematically and quantitatively trains a protein pathway map summarizing curated literature to context-specific biochemical data. This process generates a computable model yielding successful prediction of new test data and offering biological insight into complex datasets that are difficult to fully analyze by intuition alone.

Analysis of the human HP1 interactome reveals novel binding partners

DEFF Research Database (Denmark)

Rosnoblet, Claire; Vandamme, Julien; Völkel, Pamela

2011-01-01

Heterochromatin protein 1 (HP1) has first been described in Drosophila as an essential component of constitutive heterochromatin required for stable epigenetic gene silencing. Less is known about the three mammalian HP1 isotypes CBX1, CBX3 and CBX5. Here, we applied a tandem affinity purification...

Analyzing endocrine system conservation and evolution.

Science.gov (United States)

Bonett, Ronald M

2016-08-01

Analyzing variation in rates of evolution can provide important insights into the factors that constrain trait evolution, as well as those that promote diversification. Metazoan endocrine systems exhibit apparent variation in evolutionary rates of their constituent components at multiple levels, yet relatively few studies have quantified these patterns and analyzed them in a phylogenetic context. This may be in part due to historical and current data limitations for many endocrine components and taxonomic groups. However, recent technological advancements such as high-throughput sequencing provide the opportunity to collect large-scale comparative data sets for even non-model species. Such ventures will produce a fertile data landscape for evolutionary analyses of nucleic acid and amino acid based endocrine components. Here I summarize evolutionary rate analyses that can be applied to categorical and continuous endocrine traits, and also those for nucleic acid and protein-based components. I emphasize analyses that could be used to test whether other variables (e.g., ecology, ontogenetic timing of expression, etc.) are related to patterns of rate variation and endocrine component diversification. The application of phylogenetic-based rate analyses to comparative endocrine data will greatly enhance our understanding of the factors that have shaped endocrine system evolution. Copyright © 2016 Elsevier Inc. All rights reserved.

Hemopexin as biomarkers for analyzing the biological responses associated with exposure to silica nanoparticles

Science.gov (United States)

Higashisaka, Kazuma; Yoshioka, Yasuo; Yamashita, Kohei; Morishita, Yuki; Pan, Huiyan; Ogura, Toshinobu; Nagano, Takashi; Kunieda, Akiyoshi; Nagano, Kazuya; Abe, Yasuhiro; Kamada, Haruhiko; Tsunoda, Shin-ichi; Nabeshi, Hiromi; Yoshikawa, Tomoaki; Tsutsumi, Yasuo

2012-10-01

Practical uses of nanomaterials are rapidly spreading to a wide variety of fields. However, potential harmful effects of nanomaterials are raising concerns about their safety. Therefore, it is important that a risk assessment system is developed so that the safety of nanomaterials can be evaluated or predicted. Here, we attempted to identify novel biomarkers of nanomaterial-induced health effects by a comprehensive screen of plasma proteins using two-dimensional differential in gel electrophoresis (2D-DIGE) analysis. Initially, we used 2D-DIGE to analyze changes in the level of plasma proteins in mice after intravenous injection via tail veins of 0.8 mg/mouse silica nanoparticles with diameters of 70 nm (nSP70) or saline as controls. By quantitative image analysis, protein spots representing >2.0-fold alteration in expression were found and identified by mass spectrometry. Among these proteins, we focused on hemopexin as a potential biomarker. The levels of hemopexin in the plasma increased as the silica particle size decreased. In addition, the production of hemopexin depended on the characteristics of the nanomaterials. These results suggested that hemopexin could be an additional biomarker for analyzing the biological responses associated with exposure to silica nanoparticles. We believe that this study will contribute to the development of biomarkers to ensure the safety of silica nanoparticles.

Systems and methods for modeling and analyzing networks

Science.gov (United States)

Hill, Colin C; Church, Bruce W; McDonagh, Paul D; Khalil, Iya G; Neyarapally, Thomas A; Pitluk, Zachary W

2013-10-29

The systems and methods described herein utilize a probabilistic modeling framework for reverse engineering an ensemble of causal models, from data and then forward simulating the ensemble of models to analyze and predict the behavior of the network. In certain embodiments, the systems and methods described herein include data-driven techniques for developing causal models for biological networks. Causal network models include computational representations of the causal relationships between independent variables such as a compound of interest and dependent variables such as measured DNA alterations, changes in mRNA, protein, and metabolites to phenotypic readouts of efficacy and toxicity.

Partial sequence determination of metabolically labeled radioactive proteins and peptides

International Nuclear Information System (INIS)

Anderson, C.W.

1982-01-01

The author has used the sequence analysis of radioactive proteins and peptides to approach several problems during the past few years. They, in collaboration with others, have mapped precisely several adenovirus proteins with respect to the nucleotide sequence of the adenovirus genome; identified hitherto missed proteins encoded by bacteriophage MS2 and by simian virus 40; analyzed the aminoterminal maturation of several virus proteins; determined the cleavage sites for processing of the poliovirus polyprotein; and analyzed the mechanism of frameshifting by excess normal tRNAs during cell-free protein synthesis. This chapter is designed to aid those without prior experience at protein sequence determinations. It is based primarily on the experience gained in the studies cited above, which made use of the Beckman 890 series automated protein sequencers

Protein-Protein Interactions Prediction Based on Iterative Clique Extension with Gene Ontology Filtering

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Lei Yang

2014-01-01

Full Text Available Cliques (maximal complete subnets in protein-protein interaction (PPI network are an important resource used to analyze protein complexes and functional modules. Clique-based methods of predicting PPI complement the data defection from biological experiments. However, clique-based predicting methods only depend on the topology of network. The false-positive and false-negative interactions in a network usually interfere with prediction. Therefore, we propose a method combining clique-based method of prediction and gene ontology (GO annotations to overcome the shortcoming and improve the accuracy of predictions. According to different GO correcting rules, we generate two predicted interaction sets which guarantee the quality and quantity of predicted protein interactions. The proposed method is applied to the PPI network from the Database of Interacting Proteins (DIP and most of the predicted interactions are verified by another biological database, BioGRID. The predicted protein interactions are appended to the original protein network, which leads to clique extension and shows the significance of biological meaning.

Protein stability: a crystallographer’s perspective

International Nuclear Information System (INIS)

Deller, Marc C.; Kong, Leopold; Rupp, Bernhard

2016-01-01

An understanding of protein stability is essential for optimizing the expression, purification and crystallization of proteins. In this review, discussion will focus on factors affecting protein stability on a somewhat practical level, particularly from the view of a protein crystallographer. Protein stability is a topic of major interest for the biotechnology, pharmaceutical and food industries, in addition to being a daily consideration for academic researchers studying proteins. An understanding of protein stability is essential for optimizing the expression, purification, formulation, storage and structural studies of proteins. In this review, discussion will focus on factors affecting protein stability, on a somewhat practical level, particularly from the view of a protein crystallographer. The differences between protein conformational stability and protein compositional stability will be discussed, along with a brief introduction to key methods useful for analyzing protein stability. Finally, tactics for addressing protein-stability issues during protein expression, purification and crystallization will be discussed

Protein stability: a crystallographer’s perspective

Energy Technology Data Exchange (ETDEWEB)

Deller, Marc C., E-mail: mdeller@stanford.edu [Stanford University, Shriram Center, 443 Via Ortega, Room 097, MC5082, Stanford, CA 94305-4125 (United States); Kong, Leopold [National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Building 8, Room 1A03, 8 Center Drive, Bethesda, MD 20814 (United States); Rupp, Bernhard [k.-k. Hofkristallamt, 91 Audrey Place, Vista, CA 92084 (United States); Medical University of Innsbruck, Schöpfstrasse 41, A-6020 Innsbruck (Austria)

2016-01-26

An understanding of protein stability is essential for optimizing the expression, purification and crystallization of proteins. In this review, discussion will focus on factors affecting protein stability on a somewhat practical level, particularly from the view of a protein crystallographer. Protein stability is a topic of major interest for the biotechnology, pharmaceutical and food industries, in addition to being a daily consideration for academic researchers studying proteins. An understanding of protein stability is essential for optimizing the expression, purification, formulation, storage and structural studies of proteins. In this review, discussion will focus on factors affecting protein stability, on a somewhat practical level, particularly from the view of a protein crystallographer. The differences between protein conformational stability and protein compositional stability will be discussed, along with a brief introduction to key methods useful for analyzing protein stability. Finally, tactics for addressing protein-stability issues during protein expression, purification and crystallization will be discussed.

High-throughput proteomic characterization of plasma rich in growth factors (PRGF-Endoret)-derived fibrin clot interactome.

Science.gov (United States)

Anitua, Eduardo; Prado, Roberto; Azkargorta, Mikel; Rodriguez-Suárez, Eva; Iloro, Ibon; Casado-Vela, Juan; Elortza, Felix; Orive, Gorka

2015-11-01

Plasma rich in growth factors (PRGF®-Endoret®) is an autologous technology that contains a set of proteins specifically addressed to wound healing and tissue regeneration. The scaffold formed by using this technology is a clot mainly composed of fibrin protein, forming a three-dimensional (3D) macroscopic network. This biomaterial is easily obtained by biotechnological means from blood and can be used in a range of situations to help wound healing and tissue regeneration. Although the main constituent of this clot is the fibrin scaffold, little is known about other proteins interacting in this clot that may act as adjuvants in the healing process. The aim of this study was to characterize the proteins enclosed by PRGF-Endoret scaffold, using a double-proteomic approach that combines 1D-SDS-PAGE approach followed by LC-MS/MS, and 2-DE followed by MALDI-TOF/TOF. The results presented here provide a description of the catalogue of key proteins in close contact with the fibrin scaffold. The obtained lists of proteins were grouped into families and networks according to gene ontology. Taken together, an enrichment of both proteins and protein families specifically involved in tissue regeneration and wound healing has been found. Copyright © 2013 John Wiley & Sons, Ltd.

Unraveling the WRKY transcription factors network in Arabidopsis Thaliana by integrative approach

Directory of Open Access Journals (Sweden)

Mouna Choura

2015-06-01

Full Text Available The WRKY transcription factors superfamily are involved in diverse biological processes in plants including response to biotic and abiotic stresses and plant immunity. Protein-protein interaction network is a useful approach for understanding these complex processes. The availability of Arabidopsis Thaliana interactome offers a good opportunity to do get a global view of protein network. In this work, we have constructed the WRKY transcription factor network by combining different sources of evidence and we characterized its topological features using computational tools. We found that WRKY network is a hub-based network involving multifunctional proteins denoted as hubs such as WRKY 70, WRKY40, WRKY 53, WRKY 60, WRKY 33 and WRKY 51. Functional annotation showed seven functional modules particularly involved in biotic stress and defense responses. Furthermore, the gene ontology and pathway enrichment analysis revealed that WRKY proteins are mainly involved in plant-pathogen interaction pathways and their functions are directly related to the stress response and immune system process.

HiQuant: Rapid Postquantification Analysis of Large-Scale MS-Generated Proteomics Data.

Science.gov (United States)

Bryan, Kenneth; Jarboui, Mohamed-Ali; Raso, Cinzia; Bernal-Llinares, Manuel; McCann, Brendan; Rauch, Jens; Boldt, Karsten; Lynn, David J

2016-06-03

Recent advances in mass-spectrometry-based proteomics are now facilitating ambitious large-scale investigations of the spatial and temporal dynamics of the proteome; however, the increasing size and complexity of these data sets is overwhelming current downstream computational methods, specifically those that support the postquantification analysis pipeline. Here we present HiQuant, a novel application that enables the design and execution of a postquantification workflow, including common data-processing steps, such as assay normalization and grouping, and experimental replicate quality control and statistical analysis. HiQuant also enables the interpretation of results generated from large-scale data sets by supporting interactive heatmap analysis and also the direct export to Cytoscape and Gephi, two leading network analysis platforms. HiQuant may be run via a user-friendly graphical interface and also supports complete one-touch automation via a command-line mode. We evaluate HiQuant's performance by analyzing a large-scale, complex interactome mapping data set and demonstrate a 200-fold improvement in the execution time over current methods. We also demonstrate HiQuant's general utility by analyzing proteome-wide quantification data generated from both a large-scale public tyrosine kinase siRNA knock-down study and an in-house investigation into the temporal dynamics of the KSR1 and KSR2 interactomes. Download HiQuant, sample data sets, and supporting documentation at http://hiquant.primesdb.eu .

Detecting mutually exclusive interactions in protein-protein interaction maps.

KAUST Repository

Sánchez Claros, Carmen

2012-06-08

Comprehensive protein interaction maps can complement genetic and biochemical experiments and allow the formulation of new hypotheses to be tested in the system of interest. The computational analysis of the maps may help to focus on interesting cases and thereby to appropriately prioritize the validation experiments. We show here that, by automatically comparing and analyzing structurally similar regions of proteins of known structure interacting with a common partner, it is possible to identify mutually exclusive interactions present in the maps with a sensitivity of 70% and a specificity higher than 85% and that, in about three fourth of the correctly identified complexes, we also correctly recognize at least one residue (five on average) belonging to the interaction interface. Given the present and continuously increasing number of proteins of known structure, the requirement of the knowledge of the structure of the interacting proteins does not substantially impact on the coverage of our strategy that can be estimated to be around 25%. We also introduce here the Estrella server that embodies this strategy, is designed for users interested in validating specific hypotheses about the functional role of a protein-protein interaction and it also allows access to pre-computed data for seven organisms.

Detecting mutually exclusive interactions in protein-protein interaction maps.

KAUST Repository

Sá nchez Claros, Carmen; Tramontano, Anna

2012-01-01

Comprehensive protein interaction maps can complement genetic and biochemical experiments and allow the formulation of new hypotheses to be tested in the system of interest. The computational analysis of the maps may help to focus on interesting cases and thereby to appropriately prioritize the validation experiments. We show here that, by automatically comparing and analyzing structurally similar regions of proteins of known structure interacting with a common partner, it is possible to identify mutually exclusive interactions present in the maps with a sensitivity of 70% and a specificity higher than 85% and that, in about three fourth of the correctly identified complexes, we also correctly recognize at least one residue (five on average) belonging to the interaction interface. Given the present and continuously increasing number of proteins of known structure, the requirement of the knowledge of the structure of the interacting proteins does not substantially impact on the coverage of our strategy that can be estimated to be around 25%. We also introduce here the Estrella server that embodies this strategy, is designed for users interested in validating specific hypotheses about the functional role of a protein-protein interaction and it also allows access to pre-computed data for seven organisms.

Structural analysis of recombinant human protein QM

International Nuclear Information System (INIS)

Gualberto, D.C.H.; Fernandes, J.L.; Silva, F.S.; Saraiva, K.W.; Affonso, R.; Pereira, L.M.; Silva, I.D.C.G.

2012-01-01

Full text: The ribosomal protein QM belongs to a family of ribosomal proteins, which is highly conserved from yeast to humans. The presence of the QM protein is necessary for joining the 60S and 40S subunits in a late step of the initiation of mRNA translation. Although the exact extra-ribosomal functions of QM are not yet fully understood, it has been identified as a putative tumor suppressor. This protein was reported to interact with the transcription factor c-Jun and thereby prevent c-Jun actives genes of the cellular growth. In this study, the human QM protein was expressed in bacterial system, in the soluble form and this structure was analyzed by Circular Dichroism and Fluorescence. The results of Circular Dichroism showed that this protein has less alpha helix than beta sheet, as described in the literature. QM protein does not contain a leucine zipper region; however the ion zinc is necessary for binding of QM to c-Jun. Then we analyzed the relationship between the removal of zinc ions and folding of protein. Preliminary results obtained by the technique Fluorescence showed a gradual increase in fluorescence with the addition of increasing concentration of EDTA. This suggests that the zinc is important in the tertiary structure of the protein. More studies are being made for better understand these results. (author)

Transient analyzer

International Nuclear Information System (INIS)

Muir, M.D.

1975-01-01

The design and design philosophy of a high performance, extremely versatile transient analyzer is described. This sub-system was designed to be controlled through the data acquisition computer system which allows hands off operation. Thus it may be placed on the experiment side of the high voltage safety break between the experimental device and the control room. This analyzer provides control features which are extremely useful for data acquisition from PPPL diagnostics. These include dynamic sample rate changing, which may be intermixed with multiple post trigger operations with variable length blocks using normal, peak to peak or integrate modes. Included in the discussion are general remarks on the advantages of adding intelligence to transient analyzers, a detailed description of the characteristics of the PPPL transient analyzer, a description of the hardware, firmware, control language and operation of the PPPL transient analyzer, and general remarks on future trends in this type of instrumentation both at PPPL and in general

PROFIL PROTEIN SUSU DAN PRODUK OLAHANNYA

Directory of Open Access Journals (Sweden)

R. Susanti

2017-03-01

Full Text Available Penelitian ini bertujuan untuk menganalisis kadar protein dan profil protein pada beberapa susu (susu kedelai, susu kambing dan olahannya (yogurt, tofu. Kadar protein diukur dengan metode Lowry, sedangkan profil protein dianalisis menggunakan SDS PAGE. Data yang diperoleh dianalisis secara deskriptif. Kadar protein tertinggi pada sampel yang dianalisis terdapat pada produk yogurt A (579,5 mg/ml, disusul susu kedelai (289,99 mg/ml dan susu kambing (133,1 mg/ml. Analisis profil protein terlihat pita protein dengan mobilitas terendah sampai tertinggi terletak pada berat molekul 14-150 KDa. Pita protein khas yang hanya dimiliki susu kambing adalah pita 150kDa. Sementara pita protein khas yang hanya dimiliki susu kedelai adalah pita 44 kDa dan 55kDa. Pita protein yang khas hanya dimiliki yogurt A (dengan bakteri Lactobacillus bulgaricus dan Streptococcus thermophillus adalah pita 65Da. Semua jenis susu dan olahannya memiliki pita 70kDa, kecuali susu kedelai. Profil protein susu kedelai dan tofu menunjukkan profil protein yang sangat berbeda, namun keduanya memiliki pita 18kDa.This study aimed to observe protein level and profiles on some milks (soy milk, goat's milk and dairy (yogurt, tofu product. Protein content was observed by Lowry method, whereas the protein profiles were analyzed by polyacrylamide gel electrophoresis. Data were analyzed descriptively. The highest protein content of the observed sample was in yogurt A products (579,5 mg/ml, followed by soy milk (289,99 mg/ml and goat's milk (133,1 mg/ml. Analysis of protein profiles showed protein bands with lowest to highest mobility lies in the molecular weight of 14-150 KDa. Typical protein band of goat's milk was a 150kDa band. While the typical protein bands of soy milk were 44 kDa and 55kDa band. The typical protein band of yogurt A (with Lactobacillus bulgaricus and Streptococcus thermophillus bacterium was 65Da. All types of milks and dairy had 70kDa band, except for soy milk. Protein

The near-symmetry of proteins.

Science.gov (United States)

Bonjack-Shterengartz, Maayan; Avnir, David

2015-04-01

The majority of protein oligomers form clusters which are nearly symmetric. Understanding of that imperfection, its origins, and perhaps also its advantages requires the conversion of the currently used vague qualitative descriptive language of the near-symmetry into an accurate quantitative measure that will allow to answer questions such as: "What is the degree of symmetry deviation of the protein?," "how do these deviations compare within a family of proteins?," and so on. We developed quantitative methods to answer this type of questions, which are capable of analyzing the whole protein, its backbone or selected portions of it, down to comparison of symmetry-related specific amino-acids, and which are capable of visualizing the various levels of symmetry deviations in the form of symmetry maps. We have applied these methods on an extensive list of homomers and heteromers and found that apparently all proteins never reach perfect symmetry. Strikingly, even homomeric protein clusters are never ideally symmetric. We also found that the main burden of symmetry distortion is on the amino-acids near the symmetry axis; that it is mainly the more hydrophilic amino-acids that take place in symmetry-distortive interactions; and more. The remarkable ability of heteromers to preserve near-symmetry, despite the different sequences, was also shown and analyzed. The comprehensive literature on the suggested advantages symmetric oligomerizations raises a yet-unsolved key question: If symmetry is so advantageous, why do proteins stop shy of perfect symmetry? Some tentative answers to be tested in further studies are suggested in a concluding outlook. © 2014 Wiley Periodicals, Inc.

Ultra-high resolution protein crystallography

International Nuclear Information System (INIS)

Takeda, Kazuki; Hirano, Yu; Miki, Kunio

2010-01-01

Many protein structures have been determined by X-ray crystallography and deposited with the Protein Data Bank. However, these structures at usual resolution (1.5< d<3.0 A) are insufficient in their precision and quantity for elucidating the molecular mechanism of protein functions directly from structural information. Several studies at ultra-high resolution (d<0.8 A) have been performed with synchrotron radiation in the last decade. The highest resolution of the protein crystals was achieved at 0.54 A resolution for a small protein, crambin. In such high resolution crystals, almost all of hydrogen atoms of proteins and some hydrogen atoms of bound water molecules are experimentally observed. In addition, outer-shell electrons of proteins can be analyzed by the multipole refinement procedure. However, the influence of X-rays should be precisely estimated in order to derive meaningful information from the crystallographic results. In this review, we summarize refinement procedures, current status and perspectives for ultra high resolution protein crystallography. (author)

Preparation of ubiquitin-conjugated proteins using an insect cell-free protein synthesis system.

Science.gov (United States)

Suzuki, Takashi; Ezure, Toru; Ando, Eiji; Nishimura, Osamu; Utsumi, Toshihiko; Tsunasawa, Susumu

2010-01-01

Ubiquitination is one of the most significant posttranslational modifications (PTMs). To evaluate the ability of an insect cell-free protein synthesis system to carry out ubiquitin (Ub) conjugation to in vitro translated proteins, poly-Ub chain formation was studied in an insect cell-free protein synthesis system. Poly-Ub was generated in the presence of Ub aldehyde (UA), a de-ubiquitinating enzyme inhibitor. In vitro ubiquitination of the p53 tumor suppressor protein was also analyzed, and p53 was poly-ubiquitinated when Ub, UA, and Mdm2, an E3 Ub ligase (E3) for p53, were added to the in vitro reaction mixture. These results suggest that the insect cell-free protein synthesis system contains enzymatic activities capable of carrying out ubiquitination. CBB-detectable ubiquitinated p53 was easily purified from the insect cell-free protein synthesis system, allowing analysis of the Ub-conjugated proteins by mass spectrometry (MS). Lys 305 of p53 was identified as one of the Ub acceptor sites using this strategy. Thus, we conclude that the insect cell-free protein synthesis system is a powerful tool for studying various PTMs of eukaryotic proteins including ubiqutination presented here.

Inferring Mechanisms of Compensation from E-MAP and SGA Data Using Local Search Algorithms for Max Cut

Science.gov (United States)

Leiserson, Mark D. M.; Tatar, Diana; Cowen, Lenore J.; Hescott, Benjamin J.

A new method based on a mathematically natural local search framework for max cut is developed to uncover functionally coherent module and BPM motifs in high-throughput genetic interaction data. Unlike previous methods which also consider physical protein-protein interaction data, our method utilizes genetic interaction data only; this becomes increasingly important as high-throughput genetic interaction data is becoming available in settings where less is known about physical interaction data. We compare modules and BPMs obtained to previous methods and across different datasets. Despite needing no physical interaction information, the BPMs produced by our method are competitive with previous methods. Biological findings include a suggested global role for the prefoldin complex and a SWR subcomplex in pathway buffering in the budding yeast interactome.

Computational structural and functional analysis of hypothetical proteins of Staphylococcus aureus

OpenAIRE

Mohan, Ramadevi; Venugopal, Subhashree

2012-01-01

Genome sequencing projects has led to an explosion of large amount of gene products in which many are of hypothetical proteins with unknown function. Analyzing and annotating the functions of hypothetical proteins is important in Staphylococcus aureus which is a pathogenic bacterium that cause multiple types of diseases by infecting various sites in humans and animals. In this study, ten hypothetical proteins of Staphylococcus aureus were retrieved from NCBI and analyzed for their structural ...

Protein profile of human hepatocarcinoma cell line SMMC-7721: Identification and functional analysis

Institute of Scientific and Technical Information of China (English)

Yi Feng; Zhong-Min Tian; Ming-Xi Wan; Zhao-Bin Zheng

2007-01-01

AIM: To investigate the protein profile of human hepatocarcinoma cell line SMMC-7721, to analyze the specific functions of abundant expressed proteins in the processes of hepatocarcinoma genesis, growth and metastasis, to identify the hepatocarcinoma-specific biomarkers for the early prediction in diagnosis, and to explore the new drug targets for liver cancer therapy.METHODS: Total proteins from human hepatocarcinomacell line SMMC-7721 were separated by two-dimensional electrophoresis (2DE). The silver-stained gel was analyzed by 2DE software Image Master 2D Elite.Interesting protein spots were identified by peptide mass fingerprinting based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS)and database searching.RESULTS: We obtained protein profile of human hepatocarcinoma cell line SMMC-7721. Among the twenty-one successfully identified proteins, mitofilin,endoplasmic reticulum protein ERp29, ubiquinol-cytochrome C reductase complex core protein Ⅰ,peroxisomal enoyl CoA hydratase, peroxiredoxin-4 and probable 3-oxoacid CoA transferase 1 precursor were the six novel proteins identified in human hepatocarcinoma cells or tissues. Specific functions of the identified heat-shock proteins were analyzed in detail, and the results suggested that these proteins might promote tumorigenesis via inhibiting cell death induced by several cancer-related stresses or via inhibiting apoptosis at multiple points in the apoptotic signal pathway. Other identified chaperones and cancer-related proteins were also analyzed.CONCLUSION: Based on the protein profile of SMMC-7721 cells, functional analysis suggests that the identified chaperones and cancer-related proteins have their own pathways to contribute to the tumorigenesis, tumor growth and metastasis of liver cancer. Furthermore, proteomic analysis is indicated to be feasible in the cancer study.

A Simple Spreadsheet Program to Simulate and Analyze the Far-UV Circular Dichroism Spectra of Proteins

Science.gov (United States)

Abriata, Luciano A.

2011-01-01

A simple algorithm was implemented in a spreadsheet program to simulate the circular dichroism spectra of proteins from their secondary structure content and to fit [alpha]-helix, [beta]-sheet, and random coil contents from experimental far-UV circular dichroism spectra. The physical basis of the method is briefly reviewed within the context of…

Angiogenesis interactome and time course microarray data reveal the distinct activation patterns in endothelial cells.

Directory of Open Access Journals (Sweden)

Liang-Hui Chu

Full Text Available Angiogenesis involves stimulation of endothelial cells (EC by various cytokines and growth factors, but the signaling mechanisms are not completely understood. Combining dynamic gene expression time-course data for stimulated EC with protein-protein interactions associated with angiogenesis (the "angiome" could reveal how different stimuli result in different patterns of network activation and could implicate signaling intermediates as points for control or intervention. We constructed the protein-protein interaction networks of positive and negative regulation of angiogenesis comprising 367 and 245 proteins, respectively. We used five published gene expression datasets derived from in vitro assays using different types of blood endothelial cells stimulated by VEGFA (vascular endothelial growth factor A. We used the Short Time-series Expression Miner (STEM to identify significant temporal gene expression profiles. The statistically significant patterns between 2D fibronectin and 3D type I collagen substrates for telomerase-immortalized EC (TIME show that different substrates could influence the temporal gene activation patterns in the same cell line. We investigated the different activation patterns among 18 transmembrane tyrosine kinase receptors, and experimentally measured the protein level of the tyrosine-kinase receptors VEGFR1, VEGFR2 and VEGFR3 in human umbilical vein EC (HUVEC and human microvascular EC (MEC. The results show that VEGFR1-VEGFR2 levels are more closely coupled than VEGFR1-VEGFR3 or VEGFR2-VEGFR3 in HUVEC and MEC. This computational methodology can be extended to investigate other molecules or biological processes such as cell cycle.

Modulating fracture properties of mixed protein systems

NARCIS (Netherlands)

Ersch, C.E.; Laak, I. ter; Linden, E. van der; Venema, P.; Martin, A.H.

2015-01-01

To design foods with desired textures it is important to understand structure build-up and breakdown. One can obtain a wide range of structures using mixtures of different structuring ingredients such as for example protein mixtures. Mixed soy protein isolate (SPI)/gelatine gels were analyzed for

Protein splicing and its evolution in eukaryotes

Directory of Open Access Journals (Sweden)

Starokadomskyy P. L.

2010-02-01

Full Text Available Inteins, or protein introns, are parts of protein sequences that are post-translationally excised, their flanking regions (exteins being spliced together. This process was called protein splicing. Originally inteins were found in prokaryotic or unicellular eukaryotic organisms. But the general principles of post-translation protein rearrangement are evolving yielding different post-translation modification of proteins in multicellular organisms. For clarity, these non-intein mediated events call either protein rearrangements or protein editing. The most intriguing example of protein editing is proteasome-mediated splicing of antigens in vertebrates that may play important role in antigen presentation. Other examples of protein rearrangements are maturation of Hg-proteins (critical receptors in embryogenesis as well as maturation of several metabolic enzymes. Despite a lack of experimental data we try to analyze some intriguing examples of protein splicing evolution.

Load-dependent surface diffusion model for analyzing the kinetics of protein adsorption onto mesoporous materials.

Science.gov (United States)

Marbán, Gregorio; Ramírez-Montoya, Luis A; García, Héctor; Menéndez, J Ángel; Arenillas, Ana; Montes-Morán, Miguel A

2018-02-01

The adsorption of cytochrome c in water onto organic and carbon xerogels with narrow pore size distributions has been studied by carrying out transient and equilibrium batch adsorption experiments. It was found that equilibrium adsorption exhibits a quasi-Langmuirian behavior (a g coefficient in the Redlich-Peterson isotherms of over 0.95) involving the formation of a monolayer of cyt c with a depth of ∼4nm on the surface of all xerogels for a packing density of the protein inside the pores of 0.29gcm -3 . A load-dependent surface diffusion model (LDSDM) has been developed and numerically solved to fit the experimental kinetic adsorption curves. The results of the LDSDM show better fittings than the standard homogeneous surface diffusion model. The value of the external mass transfer coefficient obtained by numerical optimization confirms that the process is controlled by the intraparticle surface diffusion of cyt c. The surface diffusion coefficients decrease with increasing protein load down to zero for the maximum possible load. The decrease is steeper in the case of the xerogels with the smallest average pore diameter (∼15nm), the limit at which the zero-load diffusion coefficient of cyt c also begins to be negatively affected by interactions with the opposite wall of the pore. Copyright © 2017 Elsevier Inc. All rights reserved.

The Yersinia enterocolitica type three secretion chaperone SycO is integrated into the Yop regulatory network and binds to the Yop secretion protein YscM1

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Heesemann Jürgen

2007-07-01

Full Text Available Abstract Background Pathogenic yersiniae (Y. pestis, Y. pseudotuberculosis, Y. enterocolitica share a virulence plasmid encoding a type three secretion system (T3SS. This T3SS comprises more than 40 constituents. Among these are the transport substrates called Yops (Yersinia outer proteins, the specific Yop chaperones (Sycs, and the Ysc (Yop secretion proteins which form the transport machinery. The effectors YopO and YopP are encoded on an operon together with SycO, the chaperone of YopO. The characterization of SycO is the focus of this study. Results We have established the large-scale production of recombinant SycO in its outright form. We confirm that Y. enterocolitica SycO forms homodimers which is typical for Syc chaperones. SycO overproduction in Y. enterocolitica decreases secretion of Yops into the culture supernatant suggesting a regulatory role of SycO in type III secretion. We demonstrate that in vitro SycO interacts with YscM1, a negative regulator of Yop expression in Y. enterocolitica. However, the SycO overproduction phenotype was not mediated by YscM1, YscM2, YopO or YopP as revealed by analysis of isogenic deletion mutants. Conclusion We present evidence that SycO is integrated into the regulatory network of the Yersinia T3SS. Our picture of the Yersinia T3SS interactome is supplemented by identification of the SycO/YscM1 interaction. Further, our results suggest that at least one additional interaction partner of SycO has to be identified.

Self-organized critical model for protein folding

Science.gov (United States)

Moret, M. A.

2011-09-01

The major factor that drives a protein toward collapse and folding is the hydrophobic effect. At the folding process a hydrophobic core is shielded by the solvent-accessible surface area of the protein. We study the fractal behavior of 5526 protein structures present in the Brookhaven Protein Data Bank. Power laws of protein mass, volume and solvent-accessible surface area are measured independently. The present findings indicate that self-organized criticality is an alternative explanation for the protein folding. Also we note that the protein packing is an independent and constant value because the self-similar behavior of the volumes and protein masses have the same fractal dimension. This power law guarantees that a protein is a complex system. From the analyzed data, q-Gaussian distributions seem to fit well this class of systems.

Role of Bacterioferritin & Ferritin in M. tuberculosis Pathogenesis and Drug Resistance: A Future Perspective by Interactomic Approach

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Divakar Sharma

2017-06-01

Full Text Available Tuberculosis is caused by Mycobacterium tuberculosis, one of the most successful and deadliest human pathogen. Aminoglycosides resistance leads to emergence of extremely drug resistant strains of M. tuberculosis. Iron is crucial for the biological functions of the cells. Iron assimilation, storage and their utilization is not only involved in pathogenesis but also in emergence of drug resistance strains. We previously reported that iron storing proteins (bacterioferritin and ferritin were found to be overexpressed in aminoglycosides resistant isolates. In this study we performed the STRING analysis of bacterioferritin & ferritin proteins and predicted their interactive partners [ferrochelatase (hemH, Rv1877 (hypothetical protein/probable conserved integral membrane protein, uroporphyrinogen decarboxylase (hemE trigger factor (tig, transcriptional regulatory protein (MT3948, hypothetical protein (MT1928, glnA3 (glutamine synthetase, molecular chaperone GroEL (groEL1 & hsp65, and hypothetical protein (MT3947]. We suggested that interactive partners of bacterioferritin and ferritin are directly or indirectly involved in M. tuberculosis growth, homeostasis, iron assimilation, virulence, resistance, and stresses.

Isofocusing and immunological investigations on cephalopod lens proteins

NARCIS (Netherlands)

Brahma, S.K.; Lancieri, M.

1979-01-01

Soluble lens proteins from Octopus vulgaris, Sepia officinalis, and Loligo vulgaris were analyzed by thin-layer isoelectric focusing and compared by various immunochemical methods using antibodies directed against total soluble lens protein antigens from the said three species. The results show

Identification of membrane proteins by tandem mass spectrometry of protein ions

Science.gov (United States)

Carroll, Joe; Altman, Matthew C.; Fearnley, Ian M.; Walker, John E.

2007-01-01

The most common way of identifying proteins in proteomic analyses is to use short segments of sequence (“tags”) determined by mass spectrometric analysis of proteolytic fragments. The approach is effective with globular proteins and with membrane proteins with significant polar segments between membrane-spanning α-helices, but it is ineffective with other hydrophobic proteins where protease cleavage sites are either infrequent or absent. By developing methods to purify hydrophobic proteins in organic solvents and by fragmenting ions of these proteins by collision induced dissociation with argon, we have shown that partial sequences of many membrane proteins can be deduced easily by manual inspection. The spectra from small proteolipids (1–4 transmembrane α-helices) are dominated usually by fragment ions arising from internal amide cleavages, from which internal sequences can be obtained, whereas the spectra from larger membrane proteins (5–18 transmembrane α-helices) often contain fragment ions from N- and/or C-terminal parts yielding sequences in those regions. With these techniques, we have, for example, identified an abundant protein of unknown function from inner membranes of mitochondria that to our knowledge has escaped detection in proteomic studies, and we have produced sequences from 10 of 13 proteins encoded in mitochondrial DNA. They include the ND6 subunit of complex I, the last of its 45 subunits to be analyzed. The procedures have the potential to be developed further, for example by using newly introduced methods for protein ion dissociation to induce fragmentation of internal regions of large membrane proteins, which may remain partially folded in the gas phase. PMID:17720804

Retinoid-binding proteins: similar protein architectures bind similar ligands via completely different ways.

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Yu-Ru Zhang

Full Text Available BACKGROUND: Retinoids are a class of compounds that are chemically related to vitamin A, which is an essential nutrient that plays a key role in vision, cell growth and differentiation. In vivo, retinoids must bind with specific proteins to perform their necessary functions. Plasma retinol-binding protein (RBP and epididymal retinoic acid binding protein (ERABP carry retinoids in bodily fluids, while cellular retinol-binding proteins (CRBPs and cellular retinoic acid-binding proteins (CRABPs carry retinoids within cells. Interestingly, although all of these transport proteins possess similar structures, the modes of binding for the different retinoid ligands with their carrier proteins are different. METHODOLOGY/PRINCIPAL FINDINGS: In this work, we analyzed the various retinoid transport mechanisms using structure and sequence comparisons, binding site analyses and molecular dynamics simulations. Our results show that in the same family of proteins and subcellular location, the orientation of a retinoid molecule within a binding protein is same, whereas when different families of proteins are considered, the orientation of the bound retinoid is completely different. In addition, none of the amino acid residues involved in ligand binding is conserved between the transport proteins. However, for each specific binding protein, the amino acids involved in the ligand binding are conserved. The results of this study allow us to propose a possible transport model for retinoids. CONCLUSIONS/SIGNIFICANCE: Our results reveal the differences in the binding modes between the different retinoid-binding proteins.

The research methods and model of protein turnover in animal

International Nuclear Information System (INIS)

Wu Xilin; Yang Feng

2002-01-01

The author discussed the concept and research methods of protein turnover in animal body. The existing problems and the research results of animal protein turnover in recent years were presented. Meanwhile, the measures to improve the models of animal protein turnover were analyzed

Schizophrenia: A Pathogenetic Autoimmune Disease Caused by Viruses and Pathogens and Dependent on Genes

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C. J. Carter

2011-01-01

Full Text Available Many genes have been implicated in schizophrenia as have viral prenatal or adult infections and toxoplasmosis or Lyme disease. Several autoantigens also target key pathology-related proteins. These factors are interrelated. Susceptibility genes encode for proteins homologous to those of the pathogens while the autoantigens are homologous to pathogens' proteins, suggesting that the risk-promoting effects of genes and risk factors are conditional upon each other, and dependent upon protein matching between pathogen and susceptibility gene products. Pathogens' proteins may act as dummy ligands, decoy receptors, or via interactome interference. Many such proteins are immunogenic suggesting that antibody mediated knockdown of multiple schizophrenia gene products could contribute to the disease, explaining the immune activation in the brain and lymphocytes in schizophrenia, and the preponderance of immune-related gene variants in the schizophrenia genome. Schizophrenia may thus be a “pathogenetic” autoimmune disorder, caused by pathogens, genes, and the immune system acting together, and perhaps preventable by pathogen elimination, or curable by the removal of culpable antibodies and antigens.

Protein profiles of hatchery egg shell membrane.

Science.gov (United States)

Rath, N C; Liyanage, R; Makkar, S K; Lay, J O

2016-01-01

Eggshells which consist largely of calcareous outer shell and shell membranes, constitute a significant part of poultry hatchery waste. The shell membranes (ESM) not only contain proteins that originate from egg whites but also from the developing embryos and different contaminants of microbial and environmental origins. As feed supplements, during post hatch growth, the hatchery egg shell membranes (HESM) have shown potential for imparting resistance of chickens to endotoxin stress and exert positive health effects. Considering that these effects are mediated by the bioactive proteins and peptides present in the membrane, the objective of the study was to identify the protein profiles of hatchery eggshell membranes (HESM). Hatchery egg shell membranes were extracted with acidified methanol and a guanidine hydrochloride buffer then subjected to reduction/alkylation, and trypsin digestion. The methanol extract was additionally analyzed by matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF-MS). The tryptic digests were analyzed by liquid chromatography and tandem mass spectrometry (LC-MS-MS) to identify the proteins. Our results showed the presence of several proteins that are inherent and abundant in egg white such as, ovalbumin, ovotransferrin, ovocleidin-116, and lysozyme, and several proteins associated with cytoskeletal, cell signaling, antimicrobial, and catalytic functions involving carbohydrate, nucleic acid, and protein metabolisms. There were some blood derived proteins most likely originating from the embryos and several other proteins identified with different aerobic, anaerobic, gram positive, gram negative, soil, and marine bacterial species some commensals and others zoonotic. The variety of bioactive proteins, particularly the cell signaling and enzymatic proteins along with the diverse microbial proteins, make the HESM suitable for nutritional and biological application to improve post hatch immunity of poultry.

Use of refractometry for determination of psittacine plasma protein concentration.

Science.gov (United States)

Cray, Carolyn; Rodriguez, Marilyn; Arheart, Kristopher L

2008-12-01

Previous studies have demonstrated both poor and good correlation of total protein concentrations in various avian species using refractometry and biuret methodologies. The purpose of the current study was to compare these 2 techniques of total protein determination using plasma samples from several psittacine species and to determine the effect of cholesterol and other solutes on refractometry results. Total protein concentration in heparinized plasma samples without visible lipemia was analyzed by refractometry and an automated biuret method on a dry reagent analyzer (Ortho 250). Cholesterol, glucose, and uric acid concentrations were measured using the same analyzer. Results were compared using Deming regression analysis, Bland-Altman bias plots, and Spearman's rank correlation. Correlation coefficients (r) for total protein results by refractometry and biuret methods were 0.49 in African grey parrots (n=28), 0.77 in Amazon parrots (20), 0.57 in cockatiels (20), 0.73 in cockatoos (36), 0.86 in conures (20), and 0.93 in macaws (38) (Prefractometry in Amazon parrots, conures, and macaws (n=25 each, PRefractometry can be used to accurately measure total protein concentration in nonlipemic plasma samples from some psittacine species. Method and species-specific reference intervals should be used in the interpretation of total protein values.

Study of the proteins in the defatted flour and protein concentrate of baru nuts (Dipteryx alata Vog

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Rita de Cássia Avellaneda Guimarães

2012-09-01

Full Text Available Baru (Dipteryx alata Vog. is an abundant legume in the Brazilian Savanna. Its nuts can be exploited sustainably using its protein and lipid fractions. This study aimed to analyze the proteins of the nuts present in the defatted flour and protein concentrate in terms of their functional properties, the profile of their fractions, and the in vitro digestibility. The flour was defatted with hexane and extracted at the pH of higher protein solubility to obtain the protein concentrate. The electrophoretic profile of the protein fractions was evaluated in SDS-PAGE gel. The functional properties of the proteins indicate the possibility of their use in various foods, like soybeans providing water absorption capacity, oil absorption capacity, emulsifying properties, and foamability. Globulins, followed by the albumins, are the major fractions of the flour and protein concentrate, respectively. Digestibility was greater for the concentrate than for the defatted flour.

Semantics based approach for analyzing disease-target associations.

Science.gov (United States)

Kaalia, Rama; Ghosh, Indira

2016-08-01

A complex disease is caused by heterogeneous biological interactions between genes and their products along with the influence of environmental factors. There have been many attempts for understanding the cause of these diseases using experimental, statistical and computational methods. In the present work the objective is to address the challenge of representation and integration of information from heterogeneous biomedical aspects of a complex disease using semantics based approach. Semantic web technology is used to design Disease Association Ontology (DAO-db) for representation and integration of disease associated information with diabetes as the case study. The functional associations of disease genes are integrated using RDF graphs of DAO-db. Three semantic web based scoring algorithms (PageRank, HITS (Hyperlink Induced Topic Search) and HITS with semantic weights) are used to score the gene nodes on the basis of their functional interactions in the graph. Disease Association Ontology for Diabetes (DAO-db) provides a standard ontology-driven platform for describing genes, proteins, pathways involved in diabetes and for integrating functional associations from various interaction levels (gene-disease, gene-pathway, gene-function, gene-cellular component and protein-protein interactions). An automatic instance loader module is also developed in present work that helps in adding instances to DAO-db on a large scale. Our ontology provides a framework for querying and analyzing the disease associated information in the form of RDF graphs. The above developed methodology is used to predict novel potential targets involved in diabetes disease from the long list of loose (statistically associated) gene-disease associations. Copyright © 2016 Elsevier Inc. All rights reserved.

Role of Nab2 in RNA metabolism in Saccharomyces cerevisiae

DEFF Research Database (Denmark)

Olszewski, Pawel

RNP assembly generates errors, which are tracked down by nuclear surveillance mechanisms. Thus, not surprisingly, protein components of mRNPs have multiple functions in the biogenesis of the particle but also interact with the surveillance machinery. An example of such a multifunctional factor is the S......RNP components showed changes in the Nab2 interactome in the absence of Rrp6, and also suggested that Nab2 binds to multiple sites on the mRNA. Wide-range proteomic analysis of Nab2 immunoprecipitates revealed association with C/D box snoRNP components. These novel interactions were supported by the presence...

Conformational analysis of g protein-coupled receptor signaling by hydrogen/deuterium exchange mass spectrometry.

Science.gov (United States)

Li, Sheng; Lee, Su Youn; Chung, Ka Young

2015-01-01

Conformational change and protein-protein interactions are two major mechanisms of membrane protein signal transduction, including G protein-coupled receptors (GPCRs). Upon agonist binding, GPCRs change conformation, resulting in interaction with downstream signaling molecules such as G proteins. To understand the precise signaling mechanism, studies have investigated the structural mechanism of GPCR signaling using X-ray crystallography, nuclear magnetic resonance (NMR), or electron paramagnetic resonance. In addition to these techniques, hydrogen/deuterium exchange mass spectrometry (HDX-MS) has recently been used in GPCR studies. HDX-MS measures the rate at which peptide amide hydrogens exchange with deuterium in the solvent. Exposed or flexible regions have higher exchange rates and excluded or ordered regions have lower exchange rates. Therefore, HDX-MS is a useful tool for studying protein-protein interfaces and conformational changes after protein activation or protein-protein interactions. Although HDX-MS does not give high-resolution structures, it analyzes protein conformations that are difficult to study with X-ray crystallography or NMR. Furthermore, conformational information from HDX-MS can help in the crystallization of X-ray crystallography by suggesting highly flexible regions. Interactions between GPCRs and downstream signaling molecules are not easily analyzed by X-ray crystallography or NMR because of the large size of the GPCR-signaling molecule complexes, hydrophobicity, and flexibility of GPCRs. HDX-MS could be useful for analyzing the conformational mechanism of GPCR signaling. In this chapter, we discuss details of HDX-MS for analyzing GPCRs using the β2AR-G protein complex as a model system. © 2015 Elsevier Inc. All rights reserved.

QUALITY AND NUTRITIONAL VALUE OF WHEAT BREAD WITH A PREPARATION OF OAT PROTEINS

Directory of Open Access Journals (Sweden)

Renata Sabat

2012-02-01

Full Text Available The aim of this study was to investigate possibilities and advisability of the use of oats insoluble protein preparation for the production of wheat bread, in order to increase the amount of protein and biological value of protein in this kind of bakery. Research material consisted of the preparation of insoluble oats protein, wheat flour and wheat bread made with the share of oat protein: 5%, 7.5% and 10%, by weight of wheat flour. AOAC methods (2006 were used to determine protein, β-D-glucan and dietary fiber in raw materials and final products. Amino acid composition was measured with the help of amino acid analyzer AAA 400 and used to calculate chemical score (CS and the integrated index of essential amino acids (EAAI, according to FAO/WHO/UNU, 2007. Quality of breads was evaluated by their volume, baking yield and total baking loss, and organoleptic assessment. Bread crumb texture profile was analyzed by texture analyzer TA.XT Plus.

Induction of the SOS response in ultraviolet-irradiated Escherichia coli analyzed by dynamics of LexA, RecA and SulA proteins

International Nuclear Information System (INIS)

Aksenov, S.V.

1999-01-01

The SOS response in Escherichia coli is induced after DNA-damaging treatments including ultraviolet light. Regulation of the SOS response is accomplished through specific interaction of the two SOS regulator proteins, LexA and RecA. In ultraviolet light treated cells nucleotide excision repair is the major system that removes the induced lesions from the DNA. Here, induction of the SOS response in Escherichia coli with normal and impaired excision repair function is studied by simulation of intracellular levels of regulatory LexA and RecA proteins, and SulA protein. SulA protein is responsible for SOS-inducible cell division inhibition. Results of the simulations show that nucleotide excision repair influences time-courses of LexA , RecA and SulA induction by modulating the dynamics of RecA protein distribution between its normal and SOS-activated forms

Recovering protein-protein and domain-domain interactions from aggregation of IP-MS proteomics of coregulator complexes.

Directory of Open Access Journals (Sweden)

Amin R Mazloom

2011-12-01

Full Text Available Coregulator proteins (CoRegs are part of multi-protein complexes that transiently assemble with transcription factors and chromatin modifiers to regulate gene expression. In this study we analyzed data from 3,290 immuno-precipitations (IP followed by mass spectrometry (MS applied to human cell lines aimed at identifying CoRegs complexes. Using the semi-quantitative spectral counts, we scored binary protein-protein and domain-domain associations with several equations. Unlike previous applications, our methods scored prey-prey protein-protein interactions regardless of the baits used. We also predicted domain-domain interactions underlying predicted protein-protein interactions. The quality of predicted protein-protein and domain-domain interactions was evaluated using known binary interactions from the literature, whereas one protein-protein interaction, between STRN and CTTNBP2NL, was validated experimentally; and one domain-domain interaction, between the HEAT domain of PPP2R1A and the Pkinase domain of STK25, was validated using molecular docking simulations. The scoring schemes presented here recovered known, and predicted many new, complexes, protein-protein, and domain-domain interactions. The networks that resulted from the predictions are provided as a web-based interactive application at http://maayanlab.net/HT-IP-MS-2-PPI-DDI/.

Categorizing Biases in High-Confidence High-Throughput Protein-Protein Interaction Data Sets*

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Yu, Xueping; Ivanic, Joseph; Memišević, Vesna; Wallqvist, Anders; Reifman, Jaques

2011-01-01

We characterized and evaluated the functional attributes of three yeast high-confidence protein-protein interaction data sets derived from affinity purification/mass spectrometry, protein-fragment complementation assay, and yeast two-hybrid experiments. The interacting proteins retrieved from these data sets formed distinct, partially overlapping sets with different protein-protein interaction characteristics. These differences were primarily a function of the deployed experimental technologies used to recover these interactions. This affected the total coverage of interactions and was especially evident in the recovery of interactions among different functional classes of proteins. We found that the interaction data obtained by the yeast two-hybrid method was the least biased toward any particular functional characterization. In contrast, interacting proteins in the affinity purification/mass spectrometry and protein-fragment complementation assay data sets were over- and under-represented among distinct and different functional categories. We delineated how these differences affected protein complex organization in the network of interactions, in particular for strongly interacting complexes (e.g. RNA and protein synthesis) versus weak and transient interacting complexes (e.g. protein transport). We quantified methodological differences in detecting protein interactions from larger protein complexes, in the correlation of protein abundance among interacting proteins, and in their connectivity of essential proteins. In the latter case, we showed that minimizing inherent methodology biases removed many of the ambiguous conclusions about protein essentiality and protein connectivity. We used these findings to rationalize how biological insights obtained by analyzing data sets originating from different sources sometimes do not agree or may even contradict each other. An important corollary of this work was that discrepancies in biological insights did not

Differential Protein Expressions in Virus-Infected and Uninfected Trichomonas vaginalis.

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He, Ding; Pengtao, Gong; Ju, Yang; Jianhua, Li; He, Li; Guocai, Zhang; Xichen, Zhang

2017-04-01

Protozoan viruses may influence the function and pathogenicity of the protozoa. Trichomonas vaginalis is a parasitic protozoan that could contain a double stranded RNA (dsRNA) virus, T. vaginalis virus (TVV). However, there are few reports on the properties of the virus. To further determine variations in protein expression of T. vaginalis , we detected 2 strains of T. vaginalis ; the virus-infected (V + ) and uninfected (V - ) isolates to examine differentially expressed proteins upon TVV infection. Using a stable isotope N-terminal labeling strategy (iTRAQ) on soluble fractions to analyze proteomes, we identified 293 proteins, of which 50 were altered in V + compared with V - isolates. The results showed that the expression of 29 proteins was increased, and 21 proteins decreased in V + isolates. These differentially expressed proteins can be classified into 4 categories: ribosomal proteins, metabolic enzymes, heat shock proteins, and putative uncharacterized proteins. Quantitative PCR was used to detect 4 metabolic processes proteins: glycogen phosphorylase, malate dehydrogenase, triosephosphate isomerase, and glucose-6-phosphate isomerase, which were differentially expressed in V + and V - isolates. Our findings suggest that mRNA levels of these genes were consistent with protein expression levels. This study was the first which analyzed protein expression variations upon TVV infection. These observations will provide a basis for future studies concerning the possible roles of these proteins in host-parasite interactions.

Simultaneous Multiplexed Measurement of RNA and Proteins in Single Cells

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Spyros Darmanis

2016-01-01

Full Text Available Significant advances have been made in methods to analyze genomes and transcriptomes of single cells, but to fully define cell states, proteins must also be accessed as central actors defining a cell’s phenotype. Methods currently used to analyze endogenous protein expression in single cells are limited in specificity, throughput, or multiplex capability. Here, we present an approach to simultaneously and specifically interrogate large sets of protein and RNA targets in lysates from individual cells, enabling investigations of cell functions and responses. We applied our method to investigate the effects of BMP4, an experimental therapeutic agent, on early-passage glioblastoma cell cultures. We uncovered significant heterogeneity in responses to treatment at levels of RNA and protein, with a subset of cells reacting in a distinct manner to BMP4. Moreover, we found overall poor correlation between protein and RNA at the level of single cells, with proteins more accurately defining responses to treatment.

Simultaneous Multiplexed Measurement of RNA and Proteins in Single Cells.

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Darmanis, Spyros; Gallant, Caroline Julie; Marinescu, Voichita Dana; Niklasson, Mia; Segerman, Anna; Flamourakis, Georgios; Fredriksson, Simon; Assarsson, Erika; Lundberg, Martin; Nelander, Sven; Westermark, Bengt; Landegren, Ulf

2016-01-12

Significant advances have been made in methods to analyze genomes and transcriptomes of single cells, but to fully define cell states, proteins must also be accessed as central actors defining a cell's phenotype. Methods currently used to analyze endogenous protein expression in single cells are limited in specificity, throughput, or multiplex capability. Here, we present an approach to simultaneously and specifically interrogate large sets of protein and RNA targets in lysates from individual cells, enabling investigations of cell functions and responses. We applied our method to investigate the effects of BMP4, an experimental therapeutic agent, on early-passage glioblastoma cell cultures. We uncovered significant heterogeneity in responses to treatment at levels of RNA and protein, with a subset of cells reacting in a distinct manner to BMP4. Moreover, we found overall poor correlation between protein and RNA at the level of single cells, with proteins more accurately defining responses to treatment. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Linearization of the Bradford protein assay to application in cow milk proteins quantification by UV-Vis spectrophotometry method.

OpenAIRE

SANTOS, A. S. de O. dos; COSTA, F. F.; ESTEVES, W. T.; BRITO, M. A. V. P. e; FURTADO, M. A. M.; MARTINS, M. F.

2015-01-01

Reliable methods for determination and quantification of total protein in food are essential information to ensure quality and safety of food trade. The objective of this study was to evaluate the linearity of calibration curves obtained from different proteins (blood serum albumin-BSA, α-LA, β-LG, αs, β and κ-CAS) with the reagent of Bradford. Comercial UHT skimmed bovine milk was analyzed for the determination of total protein using the Bradford method by reading at 595 nm. The determinatio...

Correlation between protein sequence similarity and x-ray diffraction quality in the protein data bank.

Science.gov (United States)

Lu, Hui-Meng; Yin, Da-Chuan; Ye, Ya-Jing; Luo, Hui-Min; Geng, Li-Qiang; Li, Hai-Sheng; Guo, Wei-Hong; Shang, Peng

2009-01-01

As the most widely utilized technique to determine the 3-dimensional structure of protein molecules, X-ray crystallography can provide structure of the highest resolution among the developed techniques. The resolution obtained via X-ray crystallography is known to be influenced by many factors, such as the crystal quality, diffraction techniques, and X-ray sources, etc. In this paper, the authors found that the protein sequence could also be one of the factors. We extracted information of the resolution and the sequence of proteins from the Protein Data Bank (PDB), classified the proteins into different clusters according to the sequence similarity, and statistically analyzed the relationship between the sequence similarity and the best resolution obtained. The results showed that there was a pronounced correlation between the sequence similarity and the obtained resolution. These results indicate that protein structure itself is one variable that may affect resolution when X-ray crystallography is used.

How the shapes of seeds can influence pathology.

Science.gov (United States)

Melki, Ronald

2018-01-01

It is widely accepted that the loss of function of different cellular proteins following their aggregation into highly stable aggregates or the gain of pathologic function of the resulting macromolecular assemblies or both processes are tightly associated to distinct debilitating neurodegenerative diseases such as Alzheimer's, Parkinson's, Creutzfeldt-Jacob, Amyotrophic Lateral Sclerosis and Huntington's diseases. How the aggregation of one given protein leads to distinct diseases is unclear. Here, a structural-molecular explanation based on the ability of proteins such as α-synuclein or tau to form assemblies that differ by their intrinsic architecture, stability, seeding capacity, and surfaces is proposed to account for distinct synucleinopathies and tauopathies. The shape and surfaces of the seeds is proposed to define at the same time their seeding capacity, interactome and tropism for defined neuronal cells within the central nervous system. Copyright © 2017 Elsevier Inc. All rights reserved.

Protein quality and growth in malnourished children

DEFF Research Database (Denmark)

Manary, Mark; Callaghan, Meghan; Singh, Lauren

2016-01-01

BACKGROUND: Protein quality refers to the amounts and ratios of essential amino acids in a food. Two methods most commonly used for determining protein quality are the protein digestibility-corrected amino acid score (PDCAAS) and the digestible indispensible amino acid score (DIAAS). OBJECTIVE...... in children with SAM and acute infection, and these data were reviewed with respect to protein synthesis. Eleven published treatment trials for SAM with different therapeutic foods were analyzed to examine the relationship between protein quality scores with weight gain (g/kg/d). Protein scores were...... calculated with the PDCAAS and DIAAS amino acid reference patterns. A DIAAS score adjusted for the higher weight gain expected in malnourished children was also used. Bivariate correlation analysis was used to examine this relationship. RESULTS: The protein kinetic data supported the hypothesis...

Molecular basis of human Usher syndrome: deciphering the meshes of the Usher protein network provides insights into the pathomechanisms of the Usher disease.

Science.gov (United States)

Reiners, Jan; Nagel-Wolfrum, Kerstin; Jürgens, Karin; Märker, Tina; Wolfrum, Uwe

2006-07-01

integrated into this USH protein network. In the inner ear, these interactions are essential for the differentiation of hair cell stereocilia but may also participate in the mechano-electrical signal transduction and the synaptic function of maturated hair cells. In the retina, the co-expression of all USH1 and USH2 proteins at the synapse of photoreceptor cells indicates that they are organized in an USH protein network there. The identification of the USH protein network indicates a common pathophysiological pathway in USH. Dysfunction or absence of any of the molecules in the mutual "interactome" related to the USH disease may lead to disruption of the network causing senso-neuronal degeneration in the inner ear and the retina, the clinical symptoms of USH.

MDTRA: a molecular dynamics trajectory analyzer with a graphical user interface.

Science.gov (United States)

Popov, Alexander V; Vorobjev, Yury N; Zharkov, Dmitry O

2013-02-05

Most of existing software for analysis of molecular dynamics (MD) simulation results is based on command-line, script-guided processes that require the researchers to have an idea about programming language constructions used, often applied to the one and only product. Here, we describe an open-source cross-platform program, MD Trajectory Reader and Analyzer (MDTRA), that performs a large number of MD analysis tasks assisted with a graphical user interface. The program has been developed to facilitate the process of search and visualization of results. MDTRA can handle trajectories as sets of protein data bank files and presents tools and guidelines to convert some other trajectory formats into such sets. The parameters analyzed by MDTRA include interatomic distances, angles, dihedral angles, angles between planes, one-dimensional and two-dimensional root-mean-square deviation, solvent-accessible area, and so on. As an example of using the program, we describe the application of MDTRA to analyze the MD of formamidopyrimidine-DNA glycosylase, a DNA repair enzyme from Escherichia coli. Copyright © 2012 Wiley Periodicals, Inc.

Discovering disease-associated genes in weighted protein-protein interaction networks

Science.gov (United States)

Cui, Ying; Cai, Meng; Stanley, H. Eugene

2018-04-01

Although there have been many network-based attempts to discover disease-associated genes, most of them have not taken edge weight - which quantifies their relative strength - into consideration. We use connection weights in a protein-protein interaction (PPI) network to locate disease-related genes. We analyze the topological properties of both weighted and unweighted PPI networks and design an improved random forest classifier to distinguish disease genes from non-disease genes. We use a cross-validation test to confirm that weighted networks are better able to discover disease-associated genes than unweighted networks, which indicates that including link weight in the analysis of network properties provides a better model of complex genotype-phenotype associations.

Protein - Which is Best?

Science.gov (United States)

Hoffman, Jay R; Falvo, Michael J

2004-09-01

Protein intake that exceeds the recommended daily allowance is widely accepted for both endurance and power athletes. However, considering the variety of proteins that are available much less is known concerning the benefits of consuming one protein versus another. The purpose of this paper is to identify and analyze key factors in order to make responsible recommendations to both the general and athletic populations. Evaluation of a protein is fundamental in determining its appropriateness in the human diet. Proteins that are of inferior content and digestibility are important to recognize and restrict or limit in the diet. Similarly, such knowledge will provide an ability to identify proteins that provide the greatest benefit and should be consumed. The various techniques utilized to rate protein will be discussed. Traditionally, sources of dietary protein are seen as either being of animal or vegetable origin. Animal sources provide a complete source of protein (i.e. containing all essential amino acids), whereas vegetable sources generally lack one or more of the essential amino acids. Animal sources of dietary protein, despite providing a complete protein and numerous vitamins and minerals, have some health professionals concerned about the amount of saturated fat common in these foods compared to vegetable sources. The advent of processing techniques has shifted some of this attention and ignited the sports supplement marketplace with derivative products such as whey, casein and soy. Individually, these products vary in quality and applicability to certain populations. The benefits that these particular proteins possess are discussed. In addition, the impact that elevated protein consumption has on health and safety issues (i.e. bone health, renal function) are also reviewed. Key PointsHigher protein needs are seen in athletic populations.Animal proteins is an important source of protein, however potential health concerns do exist from a diet of protein

The Number, Organization, and Size of Polymorphic Membrane Protein Coding Sequences as well as the Most Conserved Pmp Protein Differ within and across Chlamydia Species.

Science.gov (United States)

Van Lent, Sarah; Creasy, Heather Huot; Myers, Garry S A; Vanrompay, Daisy

2016-01-01

Variation is a central trait of the polymorphic membrane protein (Pmp) family. The number of pmp coding sequences differs between Chlamydia species, but it is unknown whether the number of pmp coding sequences is constant within a Chlamydia species. The level of conservation of the Pmp proteins has previously only been determined for Chlamydia trachomatis. As different Pmp proteins might be indispensible for the pathogenesis of different Chlamydia species, this study investigated the conservation of Pmp proteins both within and across C. trachomatis,C. pneumoniae,C. abortus, and C. psittaci. The pmp coding sequences were annotated in 16 C. trachomatis, 6 C. pneumoniae, 2 C. abortus, and 16 C. psittaci genomes. The number and organization of polymorphic membrane coding sequences differed within and across the analyzed Chlamydia species. The length of coding sequences of pmpA,pmpB, and pmpH was conserved among all analyzed genomes, while the length of pmpE/F and pmpG, and remarkably also of the subtype pmpD, differed among the analyzed genomes. PmpD, PmpA, PmpH, and PmpA were the most conserved Pmp in C. trachomatis,C. pneumoniae,C. abortus, and C. psittaci, respectively. PmpB was the most conserved Pmp across the 4 analyzed Chlamydia species. © 2016 S. Karger AG, Basel.

PROTEIN - WHICH IS BEST?

Directory of Open Access Journals (Sweden)

Michael J. Falvo

2004-09-01

Full Text Available Protein intake that exceeds the recommended daily allowance is widely accepted for both endurance and power athletes. However, considering the variety of proteins that are available much less is known concerning the benefits of consuming one protein versus another. The purpose of this paper is to identify and analyze key factors in order to make responsible recommendations to both the general and athletic populations. Evaluation of a protein is fundamental in determining its appropriateness in the human diet. Proteins that are of inferior content and digestibility are important to recognize and restrict or limit in the diet. Similarly, such knowledge will provide an ability to identify proteins that provide the greatest benefit and should be consumed. The various techniques utilized to rate protein will be discussed. Traditionally, sources of dietary protein are seen as either being of animal or vegetable origin. Animal sources provide a complete source of protein (i.e. containing all essential amino acids, whereas vegetable sources generally lack one or more of the essential amino acids. Animal sources of dietary protein, despite providing a complete protein and numerous vitamins and minerals, have some health professionals concerned about the amount of saturated fat common in these foods compared to vegetable sources. The advent of processing techniques has shifted some of this attention and ignited the sports supplement marketplace with derivative products such as whey, casein and soy. Individually, these products vary in quality and applicability to certain populations. The benefits that these particular proteins possess are discussed. In addition, the impact that elevated protein consumption has on health and safety issues (i.e. bone health, renal function are also reviewed

Statistical Analysis of Protein Ensembles

Science.gov (United States)

Máté, Gabriell; Heermann, Dieter

2014-04-01

As 3D protein-configuration data is piling up, there is an ever-increasing need for well-defined, mathematically rigorous analysis approaches, especially that the vast majority of the currently available methods rely heavily on heuristics. We propose an analysis framework which stems from topology, the field of mathematics which studies properties preserved under continuous deformations. First, we calculate a barcode representation of the molecules employing computational topology algorithms. Bars in this barcode represent different topological features. Molecules are compared through their barcodes by statistically determining the difference in the set of their topological features. As a proof-of-principle application, we analyze a dataset compiled of ensembles of different proteins, obtained from the Ensemble Protein Database. We demonstrate that our approach correctly detects the different protein groupings.

Azurophil granule proteins constitute the major mycobactericidal proteins in human neutrophils and enhance the killing of mycobacteria in macrophages

DEFF Research Database (Denmark)

Jena, Prajna; Mohanty, Soumitra; Mohanty, Tirthankar

2012-01-01

Pathogenic mycobacteria reside in, and are in turn controlled by, macrophages. However, emerging data suggest that neutrophils also play a critical role in innate immunity to tuberculosis, presumably by their different antibacterial granule proteins. In this study, we purified neutrophil azurophil...... and specific granules and systematically analyzed the antimycobacterial activity of some purified azurophil and specific granule proteins against M. smegmatis, M. bovis-BCG and M. tuberculosis H37Rv. Using gel overlay and colony forming unit assays we showed that the defensin-depleted azurophil granule...... proteins (AZP) were more active against mycobacteria compared to other granule proteins and cytosolic proteins. The proteins showing antimycobacterial activity were identified by MALDI-TOF mass spectrometry. Electron microscopic studies demonstrate that the AZP disintegrate bacterial cell membrane...

Inferring high-confidence human protein-protein interactions

Directory of Open Access Journals (Sweden)

Yu Xueping

2012-05-01

Full Text Available Abstract Background As numerous experimental factors drive the acquisition, identification, and interpretation of protein-protein interactions (PPIs, aggregated assemblies of human PPI data invariably contain experiment-dependent noise. Ascertaining the reliability of PPIs collected from these diverse studies and scoring them to infer high-confidence networks is a non-trivial task. Moreover, a large number of PPIs share the same number of reported occurrences, making it impossible to distinguish the reliability of these PPIs and rank-order them. For example, for the data analyzed here, we found that the majority (>83% of currently available human PPIs have been reported only once. Results In this work, we proposed an unsupervised statistical approach to score a set of diverse, experimentally identified PPIs from nine primary databases to create subsets of high-confidence human PPI networks. We evaluated this ranking method by comparing it with other methods and assessing their ability to retrieve protein associations from a number of diverse and independent reference sets. These reference sets contain known biological data that are either directly or indirectly linked to interactions between proteins. We quantified the average effect of using ranked protein interaction data to retrieve this information and showed that, when compared to randomly ranked interaction data sets, the proposed method created a larger enrichment (~134% than either ranking based on the hypergeometric test (~109% or occurrence ranking (~46%. Conclusions From our evaluations, it was clear that ranked interactions were always of value because higher-ranked PPIs had a higher likelihood of retrieving high-confidence experimental data. Reducing the noise inherent in aggregated experimental PPIs via our ranking scheme further increased the accuracy and enrichment of PPIs derived from a number of biologically relevant data sets. These results suggest that using our high

Uncoupling proteins (UCP) in unicellular eukaryotes: true UCPs or UCP1-like acting proteins?

Science.gov (United States)

Luévano-Martínez, Luis Alberto

2012-04-05

Uncoupling proteins belong to the superfamily of mitochondrial anion carriers. They are apparently present throughout the Eukarya domain in which only some members have an established physiological function, i.e. UCP1 from brown adipose tissue is involved in non-shivering thermogenesis. However, the proteins responsible for the phenotype observed in unicellular organisms have not been characterized. In this report we analyzed functional evidence concerning unicellular UCPs and found that true UCPs are restricted to some taxonomical groups while proteins conferring a UCP1-like phenotype to fungi and most protists are the result of a promiscuous activity exerted by other mitochondrial anion carriers. We describe a possible evolutionary route followed by these proteins by which they acquire this promiscuous mechanism. Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Portable Microplate Analyzer with a Thermostatic Chamber Based on a Smartphone for On-site Rapid Detection.

Science.gov (United States)

Wan, Zijian; Zhong, Longjie; Pan, Yuxiang; Li, Hongbo; Zou, Quchao; Su, Kaiqi; Wang, Ping

2017-01-01

A microplate method provides an efficient way to use modern detection technology. However, there are some difficulties concerning on-site detection, such as being non-portable and time-consuming. In this work, a novel portable microplate analyzer with a thermostatic chamber based on a smartphone was designed for rapid on-site detection. An analyzer with a wide-angle lens and an optical filter provides a proper environment for the microplate. A smartphone app-iPlate Monitor was used for RGB analyze of image. After a consistency experiment with a microtiter plate reader (MTPR), the normalized calibration curves were y = 0.7276x + 0.0243 (R 2 = 0.9906) and y = 0.3207x + 0.0094 (R 2 = 0.9917) with a BCA protein kit as well as y = 0.182x + 0.0134 (R 2 = 0.994) and y = 0.0674x + 0.0003 (R 2 = 0.9988) with a glucose kit. The times for obtaining the detection requirement were 15 and 10 min for the BCA protein kit and the glucose kit at 37°C; in contrast, it required more than 30 and 20 min at ambient temperature. Meanwhile, it also showed good repeatability for detections.

ProteinWorldDB: querying radical pairwise alignments among protein sets from complete genomes.

Science.gov (United States)

Otto, Thomas Dan; Catanho, Marcos; Tristão, Cristian; Bezerra, Márcia; Fernandes, Renan Mathias; Elias, Guilherme Steinberger; Scaglia, Alexandre Capeletto; Bovermann, Bill; Berstis, Viktors; Lifschitz, Sergio; de Miranda, Antonio Basílio; Degrave, Wim

2010-03-01

Many analyses in modern biological research are based on comparisons between biological sequences, resulting in functional, evolutionary and structural inferences. When large numbers of sequences are compared, heuristics are often used resulting in a certain lack of accuracy. In order to improve and validate results of such comparisons, we have performed radical all-against-all comparisons of 4 million protein sequences belonging to the RefSeq database, using an implementation of the Smith-Waterman algorithm. This extremely intensive computational approach was made possible with the help of World Community Grid, through the Genome Comparison Project. The resulting database, ProteinWorldDB, which contains coordinates of pairwise protein alignments and their respective scores, is now made available. Users can download, compare and analyze the results, filtered by genomes, protein functions or clusters. ProteinWorldDB is integrated with annotations derived from Swiss-Prot, Pfam, KEGG, NCBI Taxonomy database and gene ontology. The database is a unique and valuable asset, representing a major effort to create a reliable and consistent dataset of cross-comparisons of the whole protein content encoded in hundreds of completely sequenced genomes using a rigorous dynamic programming approach. The database can be accessed through http://proteinworlddb.org

Stoichiometric balance of protein copy numbers is measurable and functionally significant in a protein-protein interaction network for yeast endocytosis.

Science.gov (United States)

Holland, David O; Johnson, Margaret E

2018-03-01

Stoichiometric balance, or dosage balance, implies that proteins that are subunits of obligate complexes (e.g. the ribosome) should have copy numbers expressed to match their stoichiometry in that complex. Establishing balance (or imbalance) is an important tool for inferring subunit function and assembly bottlenecks. We show here that these correlations in protein copy numbers can extend beyond complex subunits to larger protein-protein interactions networks (PPIN) involving a range of reversible binding interactions. We develop a simple method for quantifying balance in any interface-resolved PPINs based on network structure and experimentally observed protein copy numbers. By analyzing such a network for the clathrin-mediated endocytosis (CME) system in yeast, we found that the real protein copy numbers were significantly more balanced in relation to their binding partners compared to randomly sampled sets of yeast copy numbers. The observed balance is not perfect, highlighting both under and overexpressed proteins. We evaluate the potential cost and benefits of imbalance using two criteria. First, a potential cost to imbalance is that 'leftover' proteins without remaining functional partners are free to misinteract. We systematically quantify how this misinteraction cost is most dangerous for strong-binding protein interactions and for network topologies observed in biological PPINs. Second, a more direct consequence of imbalance is that the formation of specific functional complexes depends on relative copy numbers. We therefore construct simple kinetic models of two sub-networks in the CME network to assess multi-protein assembly of the ARP2/3 complex and a minimal, nine-protein clathrin-coated vesicle forming module. We find that the observed, imperfectly balanced copy numbers are less effective than balanced copy numbers in producing fast and complete multi-protein assemblies. However, we speculate that strategic imbalance in the vesicle forming module

General Protein Data Bank-Based Collective Variables for Protein Folding.

Science.gov (United States)

Ardevol, Albert; Palazzesi, Ferruccio; Tribello, Gareth A; Parrinello, Michele

2016-01-12

New, automated forms of data analysis are required to understand the high-dimensional trajectories that are obtained from molecular dynamics simulations on proteins. Dimensionality reduction algorithms are particularly appealing in this regard as they allow one to construct unbiased, low-dimensional representations of the trajectory using only the information encoded in the trajectory. The downside of this approach is that a different set of coordinates are required for each different chemical system under study precisely because the coordinates are constructed using information from the trajectory. In this paper, we show how one can resolve this problem by using the sketch-map algorithm that we recently proposed to construct a low-dimensional representation of the structures contained in the protein data bank. We show that the resulting coordinates are as useful for analyzing trajectory data as coordinates constructed using landmark configurations taken from the trajectory and that these coordinates can thus be used for understanding protein folding across a range of systems.

Sound of proteins

DEFF Research Database (Denmark)

2007-01-01

In my group we work with Molecular Dynamics to model several different proteins and protein systems. We submit our modelled molecules to changes in temperature, changes in solvent composition and even external pulling forces. To analyze our simulation results we have so far used visual inspection...... and statistical analysis of the resulting molecular trajectories (as everybody else!). However, recently I started assigning a particular sound frequency to each amino acid in the protein, and by setting the amplitude of each frequency according to the movement amplitude we can "hear" whenever two aminoacids...... example of soundfile was obtained from using Steered Molecular Dynamics for stretching the neck region of the scallop myosin molecule (in rigor, PDB-id: 1SR6), in such a way as to cause a rotation of the myosin head. Myosin is the molecule responsible for producing the force during muscle contraction...

Electron attachment analyzer

International Nuclear Information System (INIS)

Popp, P.; Grosse, H.J.; Leonhardt, J.; Mothes, S.; Oppermann, G.

1984-01-01

The invention concerns an electron attachment analyzer for detecting traces of electroaffine substances in electronegative gases, especially in air. The analyzer can be used for monitoring working places, e. g., in operating theatres. The analyzer consists of two electrodes inserted in a base frame of insulating material (quartz or ceramics) and a high-temperature resistant radiation source ( 85 Kr, 3 H, or 63 Ni)

Pharmacological targeting of the transcription factor SOX18 delays breast cancer in mice

Science.gov (United States)

Overman, Jeroen; Fontaine, Frank; Moustaqil, Mehdi; Mittal, Deepak; Sierecki, Emma; Sacilotto, Natalia; Zuegg, Johannes; Robertson, Avril AB; Holmes, Kelly; Salim, Angela A; Mamidyala, Sreeman; Butler, Mark S; Robinson, Ashley S; Lesieur, Emmanuelle; Johnston, Wayne; Alexandrov, Kirill; Black, Brian L; Hogan, Benjamin M; De Val, Sarah; Capon, Robert J; Carroll, Jason S; Bailey, Timothy L; Koopman, Peter; Jauch, Ralf; Smyth, Mark J; Cooper, Matthew A; Gambin, Yann; Francois, Mathias

2017-01-01

Pharmacological targeting of transcription factors holds great promise for the development of new therapeutics, but strategies based on blockade of DNA binding, nuclear shuttling, or individual protein partner recruitment have yielded limited success to date. Transcription factors typically engage in complex interaction networks, likely masking the effects of specifically inhibiting single protein-protein interactions. Here, we used a combination of genomic, proteomic and biophysical methods to discover a suite of protein-protein interactions involving the SOX18 transcription factor, a known regulator of vascular development and disease. We describe a small-molecule that is able to disrupt a discrete subset of SOX18-dependent interactions. This compound selectively suppressed SOX18 transcriptional outputs in vitro and interfered with vascular development in zebrafish larvae. In a mouse pre-clinical model of breast cancer, treatment with this inhibitor significantly improved survival by reducing tumour vascular density and metastatic spread. Our studies validate an interactome-based molecular strategy to interfere with transcription factor activity, for the development of novel disease therapeutics. DOI: http://dx.doi.org/10.7554/eLife.21221.001 PMID:28137359

Protein-based nanotoxicology assessment strategy

DEFF Research Database (Denmark)

Elnegaard, Marlene Pedersen; List, Markus; Christiansen, Helle

2017-01-01

to improve selection of primary hits for subsequent analysis. As nanodrug mimics, we analyzed the effect of transiently transfected siRNAs in MCF7 breast cancer cells and normal MCF12A breast cells, resembling a differential screen. As a measure of cytotoxicity, we determined cell viability as well...... as protein expression of glyceraldehyde-3-phosphate dehydrogenase, transferrin receptor, and the proliferation marker Ki67. The evaluation of cell lethality and protein expression unraveled cellular effects overseen by one method alone....

Chronological protein synthesis in regenerating rat liver.

Science.gov (United States)

He, Jinjun; Hao, Shuai; Zhang, Hao; Guo, Fuzheng; Huang, Lingyun; Xiao, Xueyuan; He, Dacheng

2015-07-01

Liver regeneration has been studied for decades; however, its regulation remains unclear. In this study, we report a dynamic tracing of protein synthesis in rat regenerating liver with a new proteomic technique, (35) S in vivo labeling analysis for dynamic proteomics (SiLAD). Conventional proteomic techniques typically measure protein alteration in accumulated amounts. The SiLAD technique specifically detects protein synthesis velocity instead of accumulated amounts of protein through (35) S pulse labeling of newly synthesized proteins, providing a direct way for analyzing protein synthesis variations. Consequently, protein synthesis within short as 30 min was visualized and protein regulations in the first 8 h of regenerating liver were dynamically traced. Further, the 3.5-5 h post partial hepatectomy (PHx) was shown to be an important regulatory turning point by acute regulation of many proteins in the initiation of liver regeneration. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Identification of an intracellular protein that specifically interacts with photoaffinity-labeled oncogenic p21 protein

International Nuclear Information System (INIS)

Lee, G.; Ronai, Z.A.; Pincus, M.R.; Brandt-Rauf, P.W.; Weinstein, I.B.; Murphy, R.B.; Delohery, T.M.; Nishimura, S.; Yamaizumi, Z.

1989-01-01

An oncogenic 21-kDa (p21) protein (Harvey RAS protein with Val-12) has been covalently modified with a functional reagent that contains a photoactivatable aromatic azide group. This modified p21 protein has been introduced quantitatively into NIH 3T3 cells using an erythrocyte-mediated fusion technique. The introduced p21 protein was capable of inducing enhanced pinocytosis and DNA synthesis in the recipient cells. To identify the putative intracellular protein(s) that specifically interact with modified p21 protein, the cells were pulsed with [ 35 S]methionine at selected times after fusion and then UV-irradiated to activate the azide group. The resulting nitrene covalently binds to amino acid residues in adjacent proteins, thus linking the p21 protein to these proteins. The cells were then lysed, and the lysate was immunoprecipitated with the anti-p21 monoclonal antibody Y13-259. The immunoprecipitate was analyzed by SDS/PAGE to identify p21 - protein complexes. By using this technique, the authors found that three protein complexes of 51, 64, and 82 kDa were labeled specifically and reproducibly. The most prominent band is the 64-kDa protein complex that shows a time-dependent rise and fall, peaking within a 5-hr period after introduction of the p21 protein the cells. These studies provide evidence that in vitro the p21 protein becomes associated with a protein whose mass is about 43 kDa. They suggest that the formation of this complex may play a role in mediating early events involved with cell transformation induced by RAS oncogenes

Copper carrier protein in copper toxic sheep liver

Energy Technology Data Exchange (ETDEWEB)

Harris, A L; Dean, P D.G.

1973-01-01

The livers of copper-toxic sheep have been analyzed by gel electrophoresis followed by staining the gels for copper with diethyldithiocarbamate and for protein with amido schwartz. These gels were compared with similar gels obtained from the livers of normal and copper-deficient animals. The copper-toxic livers contained an extra protein band which possessed relatively weakly bound copper. Possible origins of this protein are discussed. 8 references, 1 figure, 2 tables.

Membrane Proteins Are Dramatically Less Conserved than Water-Soluble Proteins across the Tree of Life.

Science.gov (United States)

Sojo, Victor; Dessimoz, Christophe; Pomiankowski, Andrew; Lane, Nick

2016-11-01

Membrane proteins are crucial in transport, signaling, bioenergetics, catalysis, and as drug targets. Here, we show that membrane proteins have dramatically fewer detectable orthologs than water-soluble proteins, less than half in most species analyzed. This sparse distribution could reflect rapid divergence or gene loss. We find that both mechanisms operate. First, membrane proteins evolve faster than water-soluble proteins, particularly in their exterior-facing portions. Second, we demonstrate that predicted ancestral membrane proteins are preferentially lost compared with water-soluble proteins in closely related species of archaea and bacteria. These patterns are consistent across the whole tree of life, and in each of the three domains of archaea, bacteria, and eukaryotes. Our findings point to a fundamental evolutionary principle: membrane proteins evolve faster due to stronger adaptive selection in changing environments, whereas cytosolic proteins are under more stringent purifying selection in the homeostatic interior of the cell. This effect should be strongest in prokaryotes, weaker in unicellular eukaryotes (with intracellular membranes), and weakest in multicellular eukaryotes (with extracellular homeostasis). We demonstrate that this is indeed the case. Similarly, we show that extracellular water-soluble proteins exhibit an even stronger pattern of low homology than membrane proteins. These striking differences in conservation of membrane proteins versus water-soluble proteins have important implications for evolution and medicine. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Characterizing alpha helical properties of Ebola viral proteins as potential targets for inhibition of alpha-helix mediated protein-protein interactions [v3; ref status: indexed, http://f1000r.es/50u

Directory of Open Access Journals (Sweden)

Sandeep Chakraborty

2015-01-01

Full Text Available Ebola, considered till recently as a rare and endemic disease, has dramatically transformed into a potentially global humanitarian crisis. The genome of Ebola, a member of the Filoviridae family, encodes seven proteins. Based on the recently implemented software (PAGAL for analyzing the hydrophobicity and amphipathicity properties of alpha helices (AH in proteins, we characterize the helices in the Ebola proteome. We demonstrate that AHs with characteristically unique features are involved in critical interactions with the host proteins. For example, the Ebola virus membrane fusion subunit, GP2, from the envelope glycoprotein ectodomain has an AH with a large hydrophobic moment. The neutralizing antibody (KZ52 derived from a human survivor of the 1995 Kikwit outbreak recognizes a protein epitope on this AH, emphasizing the critical nature of this secondary structure in the virulence of the Ebola virus. Our method ensures a comprehensive list of such `hotspots'. These helices probably are or can be the target of molecules designed to inhibit AH mediated protein-protein interactions. Further, by comparing the AHs in proteins of the related Marburg viruses, we are able to elicit subtle changes in the proteins that might render them ineffective to previously successful drugs. Such differences are difficult to identify by a simple sequence or structural alignment. Thus, analyzing AHs in the small Ebola proteome can aid rational design aimed at countering the `largest Ebola epidemic, affecting multiple countries in West Africa' (http://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/index.html.

Regulation of protein translation initiation in response to ionizing radiation

International Nuclear Information System (INIS)

Trivigno, Donatella; Bornes, Laura; Huber, Stephan M; Rudner, Justine

2013-01-01

Proliferating tumor cells require continuous protein synthesis. De novo synthesis of most proteins is regulated through cap-dependent translation. Cellular stress such as ionizing radiation (IR) blocks cap-dependent translation resulting in shut-down of global protein translation which saves resources and energy needed for the stress response. At the same time, levels of proteins required for stress response are maintained or even increased. The study aimed to analyze the regulation of signaling pathways controlling protein translation in response to IR and the impact on Mcl-1, an anti-apoptotic and radioprotective protein, which levels rapidly decline upon IR. Protein levels and processing were analyzed by Western blot. The assembly of the translational pre-initiation complex was examined by Immunoprecipitation and pull-down experiments with 7-methyl GTP agarose. To analyze IR-induced cell death, dissipation of the mitochondrial membrane potential and DNA fragmentation were determined by flow cytometry. Protein levels of the different initiation factors were down-regulated using RNA interference approach. IR induced caspase-dependent cleavage of the translational initiation factors eIF4G1, eIF3A, and eIF4B resulting in disassembly of the cap-dependent initiation complex. In addition, DAP5-dependent initiation complex that regulates IRES-dependent translation was disassembled in response to IR. Moreover, IR resulted in dephosphorylation of 4EBP1, an inhibitor of cap-dependent translation upstream of caspase activation. However, knock-down of eIF4G1, eIF4B, DAP5, or 4EBP1 did not affect IR-induced decline of the anti-apoptotic protein Mcl-1. Our data shows that cap-dependent translation is regulated at several levels in response to IR. However, the experiments indicate that IR-induced Mcl-1 decline is not a consequence of translational inhibition in Jurkat cells